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Cancer Stem Cells—Origins and Biomarkers: Perspectives for Targeted Personalized Therapies

Lia Walcher, Ann-Kathrin Kistenmacher, Huizhen Suo and 7 more (opens in a new tab)

Frontiers in Immunology · 2020 · Review · CC BY

doi:10.3389/fimmu.2020.01280 (opens in a new tab)

Abstract

The use of biomarkers in diagnosis, therapy and prognosis has gained increasing interest over the last decades. In particular, the analysis of biomarkers in cancer patients within the pre- and post-therapeutic period is required to identify several types of cells, which carry a risk for a disease progression and subsequent post-therapeutic relapse. Cancer stem cells (CSCs) are a subpopulation of tumor cells that can drive tumor initiation and can cause relapses. At the time point of tumor initiation, CSCs originate from either differentiated cells or adult tissue resident stem cells. Due to their importance, several biomarkers that characterize CSCs have been identified and correlated to diagnosis, therapy and prognosis. However, CSCs have been shown to display a high plasticity, which changes their phenotypic and functional appearance. Such changes are induced by chemo- and radiotherapeutics as well as senescent tumor cells, which cause alterations in the tumor microenvironment. Induction of senescence causes tumor shrinkage by modulating an anti-tumorigenic environment in which tumor cells undergo growth arrest and immune cells are attracted. Besides these positive effects after therapy, senescence can also have negative effects displayed post-therapeutically. These unfavorable effects can directly promote cancer stemness by increasing CSC plasticity phenotypes, by activating stemness pathways in non-CSCs, as well as by promoting senescence escape and subsequent activation of stemness pathways. At the end, all these effects can lead to tumor relapse and metastasis. This review provides an overview of the most frequently used CSC markers and their implementation as biomarkers by focussing on deadliest solid (lung, stomach, liver, breast and colorectal cancers) and hematological (acute myeloid leukemia, chronic myeloid leukemia) cancers. Furthermore, it gives examples on how the CSC markers might be influenced by therapeutics, such as chemo- and radiotherapy, and the tumor microenvironment. It points out, that it is crucial to identify and monitor residual CSCs, senescent tumor cells, and the pro-tumorigenic senescence-associated secretory phenotype in a therapy follow-up using specific biomarkers. As a future perspective, a targeted immune-mediated strategy using chimeric antigen receptor based approaches for the removal of remaining chemotherapy-resistant cells as well as CSCs in a personalized therapeutic approach are discussed.

Full text

From PubMed Central, U.S. National Library of Medicine, as current on Oct 16, 2026. Paragraph numbers are ours, so an answer can point at one.

Introduction

1In 2018, according to the GLOBOCAN study, the malignant neoplasms with the highest mortality were lung (1.76 million deaths), stomach (783,000 deaths), liver (782,000 deaths), breast (627,000 deaths), and colorectal cancers (551,000 deaths) as well as blood cancers including leukemia (309,000 deaths). All of these cancers are heterogeneous tumors containing cells with various stem cell properties, as described below. Already in 1877, Virchow's student Cohnheim noticed this cell population and pointed out that it possesses an embryonic character. Today, those cells are called cancer stem cells (CSCs) or tumor-initiating cells (TICs) and are seen as drivers of tumor establishment and growth, often correlated to aggressive, heterogeneous and therapy-resistant tumors. Upon application of therapeutic regimens such as chemo- or radiotherapy the composition of tumor cell subpopulations changes. At first, tumor cells with a high proliferative capacity are targeted and depleted causing a decrease in tumor size while CSCs survive. Additionally, some tumor cells will become senescent [therapy-induced senescence (TIS)], and subsequently can cause a change in the tumor microenvironment (TME) with tumor promoting effects due to the senescence-associated secretory phenotype (SASP).

2It is well-known that CSCs are resistant to treatment and can cause tumor relapses. However, under the therapeutic pressure and changed microenvironment CSCs can be newly generated. In this case, these cells do originate from non-CSCs or from therapy-induced senescent tumor cells. It is therefore of importance to characterize these cells in detail and to understand their origin at the time of tumor initiation and tumor relapse.

3This review underlines the role for a thorough investigation of tumors especially in the post-therapeutic period. Such post-therapeutic or therapy follow-up diagnostics are not conducted in the clinic on a regular basis, yet. The importance of specific biomarkers that analyze several parameters, such as CSCs phenotypes, senescence and TME composition, will allow the detection of therapy-resistant CSCs that cause tumor recurrence. A precise elimination of those cells of risk in a timely fashion using targeted cellular therapeutic approaches as the second line therapy is discussed in this study.

CSCs and Their Origin at Tumor Initiation

4Tumor initiation can either be driven by transformed differentiated cells or transformed tissue resident stem cells (compare Figure 1). The transformation can take place during tissue regeneration and can additionally, be initiated and/or accelerated as a response to infections, toxins, radiation or metabolic influences causing mutations. During the transformation process, oncogenes are overexpressed and tumor suppressors are inactivated promoting uncontrolled growth of the cells. As a consequence, cells de-differentiate and acquire stem cell characteristics. The transformation of tissue resident stem cells or their progeny is believed to presuppose a different set of genomic changes allowing uncontrolled, niche-independent proliferation. As stem cells already possess unlimited growth potential, it is believed that the transformation of stem cells and their progeny requires only few genomic changes. For example, the low mutagenic changes, identified in more than 10% of gastric cancers suggest that these tumors arise from tissue resident stem cell populations. Two stem cell populations have been identified in gastric cancers: slow cycling cells expressing the transcription factor Mist1 in the gastric corpus and Leucine-rich repeat-containing G-protein coupled receptor 5 (Lgr5)-expressing cells in the gastric antrum. Both populations have been linked to cancer generation in mouse models. In colon cancers, recent studies in mice have shown that even differentiated intestinal epithelial cells can be potential CSCs. The fact that adult differentiated cells, tissue resident stem cells or their progeny can promote tumor generation has also been shown in the liver. Cell tracking, in vitro and in vivo studies showed that liver cancer can originate from adult hepatocytes as well as from hepatoblasts and hepatic progenitors.

5Tumor type, prognosis and aggressiveness are also influenced by the origin of the tumor, as analyzed for instance in breast cancers. Breast tumors originating from luminal progenitors are associated with a good prognosis, except those overexpressing Her2. Tumors originating from basal-like progenitors show a very aggressive phenotype.

6In squamous cell carcinomas the differentiation phenotype seems to be influenced by the cell of origin and the kind of driver mutation, both responsible for the invasiveness and aggressiveness of the tumor. Loss of the phosphatase and tensin homolog (Pten) as well as the liver kinase B1 (Lkb1) in lung epithelia causes tumor formation of highly penetrant tumors. These tumors are rarely metastatic and are characterized by a differentiated phenotype. Basal cells located within the trachea and main bronchi have been shown to self-renew and to form heterogeneous spheres. These basal stem cells can cause basal cell hyperplasia or epithelial hypoplasia, finally resulting in squamous cell metaplasia or dysplasia, which are discussed as precursors of squamous cell lung carcinomas (SCC). Studies by Fukui et al. suggest that high basal cell signatures correlate to a clinically aggressive phenotype in lung adenocarcinoma. Adenocarcinomas are considered to originate from sub-segmental airways of the bronchioalveolar stem cells or Type I and Type II pneumocytes. These bronchioalveolar stem cells are quiescent in healthy lungs but can enter proliferation cycles and could be targets of mutations causing transformation. In mouse models, data indicate that small cell lung cancers (SCLC) can also originate from other cell types, i.e., neuroendocrine cells.

7While in solid tumors the origin is heavily discussed, in hematological tumors the situation seems to be clearer. In acute myeloid leukemia (AML), the cell of origin is thought to be a hematopoietic stem or progenitor cell. However, a subgroup of human AML has been shown to share expression profiles with lymphoid T-cell progenitors. The authors showed that under oncogenic conditions, DN2 (double negative 2) T-cell progenitors process into lymphoid, biphenotypic, and myeloid leukemia cells. In chronic myeloid leukemia (CML), the cell of origin is characterized by the expression of the Bcr-Abl oncogene, generated from a chromosomal translocation between chromosome 9 and 22. This molecular aberration defines the chronic phase in CML, which progresses into blast crisis upon additional mutations that promote self-renewal. While leukemic stem cells (LSCs) are well-defined and characterized in AML and CML, the concept of CSCs in acute lymphoblastic leukemia (ALL) and also in non-hodgkin lymphoma (NHL) is less established.

8Tumors generated on the basis of CSCs are believed to follow a unidirectional hierarchy, in which only the CSC population is able to initiate tumor growth. At the time point of tumor initiation, it is suggested that cancer stem cells divide asymmetrically to maintain the CSC pool. These asymmetric divisions generate transient amplifying cells, which are undergoing symmetric divisions; therefore having a high proliferative capacity. Based on recent data from hematological cancers (AML), the hierarchical model proposed by Bonnet and Dick is most likely a simplified description. It is now believed that the organization of CSCs (in solid as well as in hematological cancers) is more complex. In contrast to the CSC model in which only a small subpopulation of cells is able to promote tumor initiation and growth, the clonal evolution model states that genetically unstable cells accumulate genomic and genetic alterations over time causing an increase in tumor aggressiveness, resistance and heterogeneity. Both models are not mutually exclusive, which can be explained by the cellular plasticity (plasticity model) that suggests, that different cellular states can interconvert (as explained later).

9Because CSCs have been shown to cause tumor initiation and tumor relapses, the search for biomarkers that characterize these cells and allow therapeutic as well as prognostic prediction or follow-up is ongoing. The most prominent markers of solid and hematological tumors are described in the following section.

Biomarkers for CSC Populations in Solid Cancers

10In solid cancers, the clinical use of CSC specific biomarkers is very limited, besides the use of the carcinoembryonic antigen (CAE), fragments of the cytokeratin 19 (YFRA 21-1) and the alpha-fetoprotein (AFP) that is expressed by cancer stem cells. Importantly, most markers expressed in CSCs can also be found in adult tissue resident stem cell populations, human embryonic stem cells (hESC) or adult tissues. Additionally, most markers label heterogeneous stem cell populations pointing to the fact that their characterization and isolation has to be based on marker combinations using several surface markers or combinations of extracellular as well as intracellular markers; to identify and isolate cells that promote tumor initiation, resistance and relapse.

11Below, a short summary of the most prominent markers is provided. CSC markers that could have potential usefulness within therapeutic, diagnostic, and prognostic approaches are pointed out (compare Tables 1–7) and focus on most deadliest tumors of lung, liver, breast, stomach, and colorectal as well as AML and CML. Tables 1–7 provide an extensive list of markers expressed in CSCs. A comparison shows that several markers are expressed in several tumor types.

CD44

12CD44 is a biomarker which is not only expressed in solid but also in hematological cancers (see below). Its expression is associated with increased proliferation, self-renewal and metastasis. For example, in colorectal cancers, expression of CD44/CD166 characterizes a cell population able to form tumor spheres, suggesting anchorage-independent proliferation of these cells. In other studies, CD44high/CD133high cells showed increased tumorigenic capabilities. Also in breast cancers, the percentage of CD44+/CD24−/CK+/CD45− cells was shown to be increased in malignant lesions compared to non-malignant lesions. A significant decrease in proliferation and migration of breast cancer cells was observed after the knock-down of CD44. In gastric cancers, the knock-down of CD44 reduced sphere formation and caused decreased tumor growth in severe combined immunodeficiency mice. In many tumors (e.g., breast and liver), CD44 is expressed as isoform and its expression has been associated with increased cancer stem cell properties. In lung cancers, CD44v9 expression correlates significantly with early-stage lung adenocarcinoma and epidermal growth factor receptor (EGFR) mutations. Variants of CD44 are also expressed in gastric cancers and promote tumor initiation.

13The CSC marker CD44 has been indicated as a biomarker for diagnostic, therapeutic, and prognostic approaches (compare Tables 1–5). In gastric cancer patients, CD44+ circulating tumor cells correlated with a poor prognosis. In colorectal cancers, a prognostic quantitative real-time PCR was established to analyze the expression of CD44v2 showing that a high expression correlated with a worse prognosis. In gastric cancers, the expression of CD44 and CD90 correlated with distant metastasis and could therefore be used as a diagnostic biomarker and was suggested as a biomarker for treatment response. Therapeutic approaches targeting CD44 have been made using e.g. adenoviral delivery of siRNA in vitro. Furthermore, CD44-targeting drug conjugated aptamers or hyaluronic acid coated onto nanoparticles have been in the focus of research. Antibody-based photosensitizer conjugates for combined fluorescent detection and photo-immunotherapy (PIT) of CD44-expressing cells in triple-negative breast cancers (TNBC) or other antibody-based approaches tested in safety studies.

CD133

14The biomarker CD133 (Prominin-1) is expressed on hESCs and rarely found on normal tissue cells. The marker has been additionally identified in tumors of breast, liver, stomach, and colon (compare Tables 1–5) and has also been described as a marker that characterizes cells with high tumorigenicity and a high ability to form spheroids. In breast cancers, its expression correlates with N-cadherin expression that was found to be significantly higher in patients with metastasis. In lung cancers, the expression of CD133 has been correlated to epithelial to mesenchymal transitions (EMT), in combination with other additional stem cell markers, such as BMI1.

15The expression of CD44 and CD133 in colorectal cancers can predict metastasis, however, no correlation to patient outcome could be detected. In breast cancers, CD133 mRNA was suggested to be suitable for prognosis prediction and CD133 protein has been correlated to a poor prognosis. Pre-clinical therapeutic approaches cover antibody-based targeting of colorectal as well as breast cancers (compare Tables 1–5).

EpCAM

16The epithelial cell adhesion molecule (EpCAM, CD326) is expressed on CSCs in various tumor types including colon and hepatocellular cancers. Furthermore, it is expressed in non-transformed tissues such as epithelial cells, and various stem and progenitor cells. EpCAM is involved in proliferation and differentiation as well as in cell signaling and formation and maintenance of organ morphology. In cancer tissue, EpCAM is homogeneously expressed on the cell surface, while in epithelia it is expressed on the basolateral side.

17In breast cancers, the expression of EpCAM is correlated to CSC-like phenotypes that promote formation of bone metastases in mice. In lung cancers, the expression of EpCAM is often associated with the expression of CD44 and CD166. Triple positive cells show increased clonogenicity, spheroid formation, self-renewal capacity, and show increased resistance to both 5-fluouracil and cisplatin.

18As one of the first CSC markers, EpCAM has been evaluated as a therapeutic biomarker (compare Tables 1–5). Targeting EpCAM with different antibody formats has been performed in colorectal as well as breast cancers. In colorectal cancers, a therapeutic approach targeting EpCAM+ cells with aptamers has been performed in pre-clinical conditions.

Intracellular Biomarkers as Regulators of Stemness in Solid Cancers

19Both embryonic and CSCs show unlimited growth, invasive capacity and are characterized by an undifferentiated cellular state. This feature depends on transitions between epithelial and mesenchymal states, regulated by a network of intracellular pluripotency transcription factors. As reviewed by Hadjimichael et al. and also described by others pluripotency in ESC is regulated by a core-network of transcription factors, consisting amongst others of Oct-3/4, Sox2, Nanog, Klf4, and c-MYC as well as signaling pathways such as the Jak/Stat, Wnt/ß-catenin, Hedgehog/Notch, TGF-ß as well as FGF signaling pathways. The core-pluripotency network consisting of Nanog, Oct-3/4 and Sox2 (described in detail below) activates genes of self-renewal and suppresses genes involved in differentiation. Pluripotency factors as well as signaling pathways have been indicated as biomarkers for CSCs as shortly described below (compare Tables 1–5). Of note, the tables do not include all biomarkers, however describe the most abundant ones reported in the literature.

Sox2

20The transcription factor Sox2 belongs to the SRY-related HMG-box (SOX) family, and is involved in the maintenance of an undifferentiated cellular phenotype. Its aberrant expression in cancers often leads to increased chemotherapy resistance and asymmetric divisions, as observed in colorectal cancers. In those, Sox2 expression correlates with a stem cell state and with a decreased expression of the caudal-related homeobox transcription factor 2 (CDX2), which could serve as a prognostic marker for a poor prognosis. In gastric cancers, expression of Sox2 correlates with the tumor stage as well as with a poor prognosis. The formation of tumor spheroids in vitro also correlates to the overexpression of CD44 and CD133 as well as the transcription factors Sox2, Nanog and Oct-3/4. However, in another study, Sox2 levels were downregulated in gastric cancers in comparison to normal tissue and high Sox2 expression correlated with decreased metastasis and a better prognosis for the patient due to increased p21 levels. Therefore, the oncogenic functions of Sox2 are controversially discussed in gastric cancers, in which Sox2 might also have tumor-suppressor functions. These different functions seem to depend on the cancer origin and cellular context.

Oct-3/4

21Oct-3/4, also known as POU5F1, belongs to the POU homeobox gene family and is also a regulator of pluripotency in mammalian stem cell population. Oct-3/4 is upregulated in several cancers and may support the neoplastic transformation and resistance. In colorectal cancer cells, Oct-3/4 causes increased migration and liver metastasis correlating with poor survival. As reviewed by Prabavathy et al. Oct-3/4 expression is correlated to increased self-renewal and metastasis in lung cancer cells. A meta-analysis showed that Oct-3/4 expression in lung cancer was associated with poor outcomes concerning the differentiation degree, the TNM Classification of Malignant Tumors (TNM) and lymphatic metastasis. In hepatocellular carcinoma (HCC) Oct-3/4 expression was correlating with tumor size and recurrence.

Nanog

22Nanog is a homeobox domain transcription factor widely expressed in human cancers. In colorectal tumors its expression was significantly increased in CD133+ cells, and on the basis of a univariate analysis, Nanog expression correlated linearly to liver and lymph node metastasis and the TNM stage. It might therefore be useful as a prognostic biomarker in post-operative liver metastasis. In breast cancer, expression of Nanog and Oct-3/4 has been correlated to a poor prognosis of the patient as well as EMT. In HCC cell lines Nanog expression drives selfrenewal and invasion, metastasis, and drug resistance.

Biomarkers for CSC Populations in Hematological Cancer

23CSC biomarkers of AML and CML have been listed in Tables 6, 7. They indicate commonly used markers and point out possible functions of these markers as biomarkers in prognosis, therapy, and diagnosis. Below a short introduction of the most relevant markers is given.

CD44

24As mentioned above, CD44 is a common marker shared by many cancers. In hematological cancers, CD44 expression is functionally associated with chemotherapy resistance. The expression of CD44 in AML is significantly correlated with a poor overall survival (OS). Furthermore, CD44 was shown to be significantly higher expressed in non-remission AML patients. A highly relevant function of CD44 for LSCs is the adhesion to the bone marrow niche.

CD123 and CD33

25In hematological malignancies, such as AML, CD123 as well as CD33 have been described as the “classical” CSC markers. CD123 is a marker expressed on LSCs, but not exclusively. In AML patients, CD123 expression correlates to the therapy response rate, the relapse risk, and a shorter disease-free period and OS. CD123 has been associated with increased proliferation and differentiation.

26CD33 is historically, the most commonly used marker for AML stem cells, with clinical implementation of CD33 targeting, dating back to the Food and Drug Administration (FDA) approval of gemtuzumab ozogamicin (GO) in 2000. CD33 is highly expressed on blasts in around 85–90% of AML patients and also expressed at higher densities in CML but less on healthy hematopoietic stem cells (HSCs). These cells are additionally characterized by expression of CD25, CD26, and Interleukin-1 receptor accessory protein (IL-1RAP) and also other markers.

CLL-1

27The C-type lectin-like molecule-1 (CLL-1) is a promising alternative to the “classical” LSC targets. The majority of AML patients shows CLL-1+ LSCs, a marker not being expressed on HSCs. Compared to CD33, CLL-1 was not only more frequently and stronger expressed on LSCs, but also not or more weakly expressed on normal tissues leading to reduced off-target effects after treatment with a respective antibody-drug conjugate. Therefore, CLL-1 might be a more suitable and specific LSC target than CD33. A high expression of CLL-1 is associated with poor prognosis and a faster relapse in AML. Interestingly, controversial observations have been made using CLL-1 as a biomarker after chemotherapy. The diagnostic value of CLL-1 is discussed controversially: while Zhang et al. showed that CLL-1 was increased after chemotherapy, others showed that there is no difference between CLL-1 expression at diagnosis and at relapse or even detected a decreased CLL-1 expression at relapse. The relevance of CLL-1 as a prognostic biomarker for chemotherapy failure or relapse is therefore still unclear. Its expression is not detectablewithin the chronic phase of CML.

TIM-3

28Another “non-classical” LSC biomarker is T-cell immunoglobulin and mucin 3 (TIM-3), that is highly expressed on LSCs but not expressed on healthy HSCs. It is correlated to a poor prognosis and treatment failure. Stem cell properties of TIM-3+ cells were confirmed by engraftment in a xenograft mouse model.

Intracellular Biomarkers as Regulators of Stemness in Hematological Cancers

29The core-network of pluripotency associated transcription factors as well as signaling pathways have also been analyzed in hematological cancers. Fifty AML patients have been analyzed for the expression of Sox proteins, which are overexpressed in 10–22% of the patients. The analysis showed that high levels of Sox proteins may have a prognostic value. The analysis of Oct-3/4 expression correlated with an unfavorable prognosis and is associated with FMS-like tyrosine kinase 3-internal tandem duplications (FLT3-ITD).

30Activation of stemness-associated pathways especially in CML has been shown to promote extensive proliferation and has been linked to the onset of blast crisis, which is associated with a loss of differentiation of the leukemia initiating cells. An important impact on this effect has the Wnt/ß-catenin pathway that promotes HSC proliferation, independent of the bone marrow niche. Especially, resistance to the tyrosine kinase inhibitor imatinib has been shown to correlate to an increased nuclear localization of ß-catenin. Inhibitors targeting the Wnt pathway have been shown to be of advantage for example in long-term cell cultures. Additionally, the hedgehog pathway has been suggested to be involved in chemotherapeutic resistance in CML, which is also characteristic for chronic phase CML cells. Mouse studies also indicate the involvement of the hedgehog pathway, which has been implicated as a therapeutic biomarker for CML.

31To summarize, CSCs at tumor initiation originate from either differentiated cells or adult tissue resident stem cells. Several data indicate that the origin strongly correlates to the aggressiveness of the tumor. Therefore, extra- and intracellular biomarkers that characterize CSCs have been identified and implemented to be of diagnostic and prognostic advantage. However, stem cells are subject to a high degree of plasticity modulated by the TME, that is significantly changed by chemo- and radiotherapies and composed of several different cell types. In the following section, focus will be laying on senescent tumor cells as part of the TME as they have long-term influence on TME and CSC development and progression.

The Escape of Cancer Stem Cells From Therapy

32At the moment first-line therapeutic treatments in progressed tumors include in the most cases surgery, chemo- as well as radiotherapies (compare Figure 2). Those have been shown to induce DNA damage and to trigger senescence in cancer cells, a process known as therapy-induced senescence (TIS). TIS will cause a decreased tumor size and attracts immune cells such as neutrophils, monocytes as well as T-cells toward senescent tumor site. However, over a long-term period the anti-tumorigenic effects of TIS are lost and the cancer might gain stemness causing tumor relapses (Figure 2).

Therapy-Induced Senescence: Its Hallmarks, Biomarkers, and Its Role in CSC Generation

33Agents that induce DNA damage such as chemo- and radiation therapies have been identified to trigger senescence in differentiated cancer cells. TIS has been in the research focus, because it significantly contributes to the long-term outcome of patients. The DNA damage response ultimately activates one or several tumor suppressors pathways [p53, p16 (Ink4a), p21 (Waf1), and retinoblastoma (RB)], that trigger and maintain the senescence growth arrest. However, it is important to mention that the senescence phenotype can also be induced in cancer cells which lack functional p53 and RB protein. TIS and senescence in general, are recognized as a double-edged sword, that on the one hand leads to the attraction of immune cells, inflammation, and elimination of senescent tumor cells and correlates with a positive post-treatment prognosis and treatment outcome. On the other hand, senescence can play a strong pro-tumorigenic role that supports CSC generation, as described below.

34Senescent cells are characterized by biochemical and morphological changes such as flattening and/or nuclear enlargement. There are several classical biomarkers of cellular senescence and they comprise: senescence-associated beta-galactosidase (SA-ß-gal) activity, expression of p53 protein, the amount of p53 in the nucleus, increase in expression of p14 (Arf), p16 (Ink4a) and p21 (Waf1), SASP, and often senescence-associated heterochromatic foci (SAHF). Furthermore, senescent cells display low Ki67 levels and show levels of heterochromatin protein 1 (HP1) gamma, as well as di- or tri-methylated lysine 9 of histone H3 (H3K9Me2/3) and histone H2A variant (macroH2A). The usefulness of telomere length as a biomarker of senescence has been questioned.

35Biomarkers that underline the effect of a therapeutic approach based on the induction of senescence have to be evaluated carefully and quite often simultaneously. The investigation of senescence markers after post-operative chemotherapy in muscle-invasive bladder cancer (MIBC) revealed that the simultaneous expression of several markers involved in the p53 pathway has to be checked to correctly assess the pathological outcome of MIBC. The analysis revealed that the expression of p14 (Arf) was associated with an impaired response to chemotherapy and poor prognosis, whereas p21 (Waf1) expression was related to reduced tumor cell proliferation.

36TIS can play an anti-cancerous role. As demonstrated in our studies in premalignant and malignant liver disease, the induction of senescence leads to a so-called “senescence surveillance” mechanism, which relies on innate and adaptive immune cells. These cells clear senescent premalignant cells, thereby protecting premalignant liver from cancer development. Interestingly, in further studies, we could show that the chemokine (monocyte chemoattractant protein 1, MCP-1) axis is of importance for the induction and maintenance of senescence and for the sufficient immune surveillance in the liver. Several biomarkers of senescence were found to correlate with a disease-free survival or with an improved OS in several solid cancers. One such indicator, a lysosomal-beta-galactosidase (GLB1) that hydrolyzes beta-galactose from glycoconjugates and represents the origin of SA-ß-gal, was reported as a reliable senescence biomarker in prostate cancer. Inhibition of the cyclin-dependent kinase 4/6 (CDK)-RB pathway by a novel drug, SHR6390, resulted in reducing the levels of Ser780-phosphorylated RB protein and correlated with the G1 arrest as well as with cellular senescence in a wide range of human RB+ tumor cells in vitro. Xiang et al. identified seven senescence-associated genes (SAGs, Table 8) significantly decreased in senescent cells and increased in HCC tissues. Interestingly, those SAGs were strongly associated with OS, especially in Asian populations, and had a better predictive accuracy in comparison to serum AFP in predicting OS of HCC patients. Recently, Smolle et al. reviewed and underlined the role of members of the inhibition of growth (ING) family. These act as tumor suppressors, regulating cell cycle, apoptosis, and cellular senescence. The authors proposed them as clinically useful biomarkers in the detection and prognosis of lung cancer.

37In line with the positive role of senescence, evidence exists regarding the role of TIS in turning “cold” tumors toward a “hot” phenotype that results in activating immune responses against tumor antigens. As reported in Her2+ breast cancer patients treated with Trastuzumab and chemotherapy, the treatment-induced epitope spreading was characterized by increased antibody responses not only to the tumor antigen Her2, but also to endogenous CEA, insulin-like growth factor-binding protein 2 (IGFBP2), and p53.

38TIS is a very important protective mechanism that is induced immediately after chemo- or radiation therapy. TIS mediates the recognition and clearance of senescent tumor cells by immune cells. Induction of TIS after the therapy is associated with a better prognosis and OS. However, if senescent tumor cells are not cleared in a timely fashion, their role at a later time points shifts from positive to negative, as discussed in the section below.

Negative Role of TIS: Cancer Progression

39Several studies report a pro-tumorigenic effect of TIS leading to cancer recurrence and support of tumor development. Uncleared senescent cells acquire additional mutations, thereby escaping the cell cycle arrest and transform into malignant cells. Moreover, factors secreted by senescent cells are also reported to play a strong tumor-promoting role.

40Was et al. suggested that senescent human colon cancer cells (HCT116) that appear during a doxorubicin-based therapy enter a “dormant” cellular state, survive the treatment, and cause tumor re-growth. Importantly, the recent findings by Scuric et al. suggest a long-term effect of chemotherapy and/or radiation exposure upon TIS. In this study, markers of cellular senescence, including higher DNA damage and lower telomerase activity, were observed many years later in breast cancer survivors. Elevated levels of a soluble tumor necrosis factor (TNF)-receptor-II, a pro-inflammatory biomarker and one of the main SASP molecules, were also detected. A negative effect of SASP was correlated to a p53 single-nucleotide polymorphism (SNP) at codon 72 which is correlated to increased risk of breast cancers. Using a humanized mouse model, Gunaratna et al. showed that SASP caused an increased invasion of pro-inflammatory macrophages. However, the inflammation proceeded into a chronic inflammation with pro-tumorigenic action and tumor-associated macrophages (TAMs) contributed to angiogenesis and increased tumor growth rates. Also, senescent cancer-associated fibroblasts (CAFs) and, in particular, expression of Caveolin-1 (CAV1) promote tumor invasion in pancreatic cancer. Moreover, in clinicopathological characteristics of patients, a high CAV1 expression directly correlates with higher levels of serum tumor antigens, with the rate of advanced tumor stage, and with significantly worse outcomes in both overall and disease-free survival.

41It has been suggested that cancer therapies, especially chemo- and radiotherapies, possess long- and late-term pro-tumorigenic side effects and could therefore contribute to the relapse of the malignant disease they were intended to treat. Such long-term effects could be caused by the decreased removal of senescent cells, as described below.

Cancer Stemness: Senescence Escape

42As mentioned above, cells undergoing senescence can still escape the senescence program and become malignant while acquiring additional mutations (Figure 2). In our studies, we observed a spontaneous mutation [a deficiency in p19 (Arf)] in Ras-expressing hepatocytes, which resulted in a full-blown HCC development using a Ras-induced precancerous liver disease model. The reversibility of TIS can be caused through the inactivation of tumor suppressors p53, p16 (Ink4A), p19 (Ink4d), and/or RB. Additionally, the over-expression of CDC2/CDK1 and survivin can promote cancer stem cell survival and can also promote the development of polyploidy. In general, mutations in CDKN2A, coding for p16 (Ink4a, CDKN2A), p21 (Waf1, CDKN1A), and p27 (Kip1, CDKN1B) as well as E2F3 and EZH2, and a high c-MYC expression might result in low percentages of senescent cells. Moreover, particular mutations completely protect melanoma cells from cell cycle arrest upon chemotherapy: DMBC29 melanoma cells that carried a EZH2S412C mutation, expressed c-MYC at a low level and a wild type of CDKN2A did not undergo senescence, in contrast to many melanoma cells treated with vemurafenib and trametinib.

43An escape of cells from senescence was also identified by Milanovic et al. in B-cell lymphoma studies. In those studies, the researchers showed that senescent cells substantially upregulated an adult tissue stem cell signature and activated Wnt signaling. This senescence-associated stemness was an unexpected cell-autonomous phenotype that caused the generation of cells with a higher tumorigenic potential in vitro.

44However, escape from senescence is not the only pathway that promotes an increase in the cancer stemness phenotype. Stemness within the tumor tissue is also regulated indirectly by signaling molecules which support the maintenance of stemness in CSCs as well as non-CSCs, as described in the following sections.

Cancer Stemness: SASP and CSC Maintenance

45The stemness phenotype within a tumor can also be mediated via SASP. Several studies address the strong pro-tumorigenic phenotype whose cytokines can mediate the maintenance of CSCs. The most prominent interleukins (IL) of SASP are IL-1,−6, and−8. These cytokines can influence the CSC phenotype and functionality and therefore influence the plasticity phenotype of CSCs.

46Using breast cancer cell lines, Di et al. showed that an induction of senescence in mesenchymal stem cells by hydrogen peroxide treatment causes an increased secretion of the inflammatory cytokine IL-6, which led to a higher migratory capacity of breast cancer cells in vitro as well as in xenotransplants. An increase in the aggressive metastatic chemoresistant phenotype upon inflammatory cytokine stimulation such as IL-1ß, IL-6, and RANTES (regulated on activation, normal T cell expressed, and secreted) was also observed by others. Our own work indicated that IL-8 blocks differentiation of hepatocellular premalignant cells, a pathway mediated via mammalian target of rapamycin complex 1 (mTORC1) kinase, that causes an increase in chemotherapy resistance. An increase in tumorigenicity and EMT of breast cancer cells has been shown to correlate to an increased expression of CD44 or CSC-like properties and be caused by the senescence-associated IL-8 and IL-6. Pathways that might be involved in such cellular reprogramming processes are the JAK2/STAT3 signaling pathway, the IL-6/STAT3 and NOTCH cross-talk signaling as well NFκB-IL-6 signaling axis, responsible for the generation of CSCs. Interestingly, interference with those pathways by aspirin increased chemosensitivity and decreased self-renewal in breast cancer cells. In colorectal cancer cells the inflammatory cytokine IL-6 mediates deacetylation, which subsequently activates NANOG transcription and accumulation of stemness phenotypes, correlating with malignant progression and poor prognosis.

47To summarize, TIS on the one hand has positive effects that eliminates differentiated tumor cells and also causes invasion of immune cells with anti-tumorigenic functions. On the other hand, senescence causes negative effects that are reflected by pro-tumorigenic functions causing CSC development and a gain of cancer stemness (Figure 2).

48An additional level of complexity is added by the plasticity of CSCs as well as non-CSCs, which also causes increased cancer stemness, resistance, and relapse. Examples are given in the next paragraph.

Cancer Stemness: Plasticity of CSCs and Non-CSCs

49Cancer stemness is not only triggered by senescence escape and acquisition of stemness phenotypes or supported by maintenance of stemness but also by the plasticity of CSCs and non-CSCs, altogether causing tumor relapses after treatment, as described below.

50Plasticity is regulated by the TME that is very heterogeneous and consists of CAFs, TAMs, and neutrophils as well as of cancer-associated adipocytes, tumor-infiltrating lymphocytes, and cancer cells with or without stem cell characteristics. Therefore, a clear separation between SASP effects and plasticity cannot be made as several direct and also indirect regulatory networks are involved (Figure 2).

51Mechanistically, plasticity of cells is a characteristic that ensures robust tissue regeneration and homeostasis and describes the phenotypic and molecular changes of tumor cells increasing stemness and reflecting the tumor's ability to self-renew. This phenotype is ultimately closely linked to EMT. As described, the transition from the epithelial to mesenchymal state is associated with defined regulatory networks, chromatin remodeling and gene expression programs that are specific to the epithelial, mesenchymal or hybrid cellular state. Plasticity increases the complexity by suggesting that CSCs can switch between different cellular states, characterized by the expression of surface markers as well as transcription factors. Examples for this come from the analysis of different tumor cells: Chaffer et al. demonstrated that CD44low cells (non-CSCs) can switch to a CD44high phenotype (CSCs) resulting in mammosphere formation, a phenotype that could be induced by upregulation of the zinc finger E-box binding homeobox 1 (ZEB1) protein expression induced by TGF-ß, which is a major cytokine of the TME. In NSCLC cell lines, two distinct CSC subpopulations have been described by expression of CD133 and the aldehyde dehydrogenase (ALDH). ALDHs compose an enzyme superfamily with metabolic functions. The analysis of its activity is often used to identify CSCs. Analyzing CD133 and ALDH activity, Akunuru et al. separated cancer stem/progenitor cells (CD133+, ALDHhigh) from non-CSCs (CD133− or ALDHlow) and showed that non-CSCs can interconvert into CSCs. The latter process is activated by TGF-ß signaling or signaling by the zinc finger protein SNAI (Snail) transcription factor family. The described process underlines the dynamic plasticity of CSC/non-CSCs cells. After TGF-ß treatment, the authors observed an increase in IL-1ß and IL-6 as well as an increase in CD133+ and ALDHhigh subpopulations.

52Interferon-ß (IFN-ß) as well as Oncostatin M (OSM), also cytokines within the TME, have been shown to regulate CSC phenotypes. Activation of IFN-ß signaling pathways in non-CSCs blocks the expression of CD44 and Snail, which causes a decrease tumor sphere formation and additionally inhibits invasion. In contrast, OSM induces a stemness phenotype in non-CSCs. One of the major regulators of colorectal tumor plasticity (either CSCs or cancer cells) are the Wnt-ß-catenin and the KRAS/BRAF/ERK pathways, which have been implicated to regulate tumorsphere formation, self-renewal as well as resistance, as reviewed by Pereira et al. and Zhan et al.. Activation of Wnt-signaling increased sphere and clone formation as well as drug resistance. Acquisition of stemness was also described by Perekatt et al. using transgenic mice to analyze the function of Wnt-signaling in tumorigenesis and de-differentiation in the gut. The authors show that the inactivation of Smad 4, a factor that regulates the differentiation program, promoted the development of adenomas with characteristics of activated Wnt signaling over long-term periods. Such Wnt activation can correlate with increased treatment resistance as reviewed by Mohammed et al.. Also in gastric cancer, activation of the Wnt pathway causes an increase in CD44 as well as Oct-3/4 expression and correlates with an increased proliferation.

53As described above, a gain of stemness due to SASP and CSC maintenance or by plasticity of CSCs and non-CSCs, can cause increased resistance (Figure 2). CSCs (pre-existing or post-therapeutically generated de novo) can escape the treatment by the expression of drug exporters and detoxification proteins, entrance into dormancy as well as resistance to DNA damage induced cell death. Their survival causes tumor relapses (Figure 2). To interfere with the relapse, several strategies have been under investigation to block CSC resistance and growth, as described below (Figures 3, 4).

Eradication of CSCs: New Targeted Approaches

54Targeting CSCs has been in the focus of research for many years. As reviewed by Shibata and Hoque, the combination of CSC-targeted therapies and conventional non-targeted therapies can result in a decreased chemoresistance. Approaches of CSC-targeted therapies include kinase inhibitors as well as targeting stem cell associated pathways such as Wnt and β-catenin, some of which have already entered the clinical phase. Immunological approaches that target CSCs via MHC-restricted killing include adoptive cell transfer, targeting checkpoint inhibitors as well as antibody-based approaches and vaccination. MHC-unrestricted killing based on NK-, γδT-, and chimeric antigen receptor (CAR) T-cell approaches have been established. Currently, these approaches are performed after failures of the first-line therapies.

55Based on the promising results of CAR T-cellular therapy in treating hematological diseases, CAR T-cell-based approaches have also moved forward into the therapy of solid cancers. Although, CAR T-cell-based approaches face difficulties in treating solid cancers, their therapeutic use could be a promising alternative.

Targeting CD133+ CSCs

56Targeting CD133+ CSCs in solid cancers has shown quite promising preclinical results either using monotherapeutic approaches or using combinational approaches together with cytostatic agents. Recently, a clinical trial testing CD133-directed CAR T-cells in patients with ALL, AML, breast, brain, liver, pancreatic and ovarian cancers as well as colorectal cancers has been completed (NCT02541370, Table 9). Initial results showed feasibility, safety, and efficacy of CD133-directed CAR T-cells in patients. Especially, HCC patients who were not responsive to sorafenib showed a median progression-free survival of 7 months. In all patients the duration of response ranged from 9 to 63 weeks; three patients showed a continued response at the time of publication. Stable disease was observed in 14 out of 23 patients for 9 weeks to 15.7 months and 21 patients did not show detectable signs of metastasis.

57Additional studies (Table 9) are ongoing for the treatment of relapsed or refractory AML (NCT03473457), relapsed or late staged sarcoma (NCT03356782), as well as glioma (NCT03423992). A case study of a patient receiving CD133-directed CAR T-cells after previous chemo- and radiotherapy as well as EGFR-directed CAR T-cell therapy reported a partial response for a period of 4.5 months. However, severe toxicities affecting the skin, the oral mucosa, and the gastrointestinal tract were reported.

Targeting CD44+ CSCs

58Although CD44 is a very prominent CSC antigen, only few CAR-based approaches targeting CD44 have been developed. Early approaches that entered clinical trials included monoclonal antibodies and antibody-conjugates. First studies involving 186Re-conjugated antibody against the splice variant CD44v6 showed advantageous effects at first, however a long-term stable disease was only observed in one patient. Likewise, the CD44-directed monoclonal antibody RG7356 showed only modest success in clinical trials with AML patients and solid tumors. Tijink et al. coupled the CD44v6-directed antibody bivatuzumab to the cytotoxic antimicrotubule agent mertansine to produce an antibody-prodrug conjugate. Bivatuzumab mertansine was administered to seven patients and two of them showed stable disease during the therapy phase. However, one patient with squamous cell carcinoma of the esophagus died after treatment due to toxic epidermal necrolysis, which caused the premature cancelation of this trial. Because of this fatality, two clinical trials that were conducted in parallel for patients with metastatic breast cancer and head and neck squamous cell carcinoma had to be terminated.

59Still, there are some promising approaches involving CD44v6-directed CAR therapies. For instance, cytokine-induced killer (CIK) cells carrying a CAR against CD44v6 showed anti-cancer effects against sarcoma in vitro and in vivo. Furthermore, a phase I/IIa clinical trial using CD44v6-directed CAR T-cells for AML and multiple myeloma patients is currently recruiting (NCT04097301) (Table 9).

Targeting EpCAM+ CSCs

60Pre-clinical as well as clinical studies targeting EpCAM+ cancer cells using monoclonal antibodies or CAR constructs have been performed to date using co-culture and xenograft approaches (Table 9). Combination therapy of EpCAM-directed CAR NK-92-cells and regorafenib, a potent multikinase inhibitor, resulted in a synergistic antitumor effect using for example colorectal cancer cells or xenograft models. CAR T-cells targeting EpCAM have been shown to significantly block tumor growth in xenografts and to secrete cytotoxic cytokines, including interferon-γ (IFN-γ) and tumor necrosis factor alpha (TNF-α) in vitro. Additionally, an injection of EpCAM-directed CAR T-cells led to delayed disease progression in immunodeficient mice with peritoneal ovarian and colorectal xenografts. Currently, there are several clinical trials with EpCAM-directed CAR T-cells listed for patients with various malignancies: three trials are ongoing (NCT02915445, NCT03563326, and NCT03013712), one trial is not yet recruiting (NCT04151186), and four trials are listed with unknown status (NCT02725125, NCT02728882, NCT02735291, and NCT02729493) (Table 9).

LSC-Directed CAR Therapies

61In the field of CAR therapeutics, CD123 and CD33 are frequent targets for AML-specific CAR cells (Table 9). CAR T- and CAR NK-92-cells redirected against CD33 have entered clinical trials (Table 9). Case reports show a good tolerability of CD33-directed CAR NK-92-cells, but disease progression after treatment with CD33-directed CAR T-cells was still present. Currently, numerous clinical trials using CAR T-cells targeting CD123 are ongoing. NCT03672851 with two participants had to be terminated due to adverse effects. Furthermore, first studies implement CLL-1 as a target of CAR T-cells [Table 9;, NCT04010877 and NCT03222674].

Next Generation CARs and Targeting of CSCs in Combinational Therapies

62For the more efficient CSC elimination, different approaches that have been developed can be used, i.e., tandem CAR T-cells (TanCAR) as well as single universal (U) tricistronic transgene CAR T-cells (UCAR T-cells). Multi-targeting of Her2, IL-13 receptor subunit alpha-2 (IL13Rα2), and ephrin-A2 (EphA2) was shown to overcome antigenic heterogeneity in 15 primary GBM samples and to increase the therapeutic success using xenograft models. Targeting two or more antigens may increase the risk for on-target/off-tumor toxicity, since most of the antigens are not only expressed on malignant cells, but also on healthy cells. Improved safety, specificity, and flexibility can be obtained using universal CARs (UniCAR) or split, universal and programmable (SUPRA) CARs. Both consist of an inert and universal CAR construct without a single chain variable fragment (scFv) adaptor molecule domain in combination with a multiple tumor-targeting scFv adaptor molecule. In both cases, the activity of CAR T-cells can be regulated by the dosage of the scFv adaptor molecules or by introducing competitive molecules, such as leucine zippers as a regulator for the SUPRA CARs. Additional safety of CAR T-cells can be achieved by the induction of suicide genes, e.g., iCasp9 or by inhibitory CAR (iCAR) constructs, in which signaling domains consist of an immuno-inhibitory receptor [e.g., CTLA-4 or PD-1;]. An antigen only expressed on the surface of healthy cells is a target of iCAR and therefore the the attack of non-tumorigenic cells is greatly reduced. Specificity can be improved by using synthetic Notch (synNotch) receptors. The binding of synNotch specific to the antigen induces the cleavage of an intracellular domain and activates in turn the transcription of a second CAR, specific to another tumor antigen.

63To enhance the targeting of solid tumors using CAR-based approaches, the combination treatment with conventional chemotherapeutic drugs could be a novel strategy to enhance antitumor response. To test this approach, NK-92 cells were modified with an EGFR-directed CAR construct against renal cell carcinoma (RCC) cell lines. In combination with the multikinase inhibitor cabozantinib, EGFR-directed CAR NK-92 cells showed synergistic effects in vitro and in vivo. Cabozantinib also caused a decrease of the anti-inflammatory PD-L1 surface expression in renal cell carcinoma cell lines. Furthermore, cabozantinib is known to reduce tumor infiltration of immuno-modulatory subpopulations like regulatory T-cells (Tregs) and myeloid-derived suppressor cells (MDSCs).

64The combination of the multikinase inhibitor sunitinib and CAR T -cells targeting carbonic anhydrase IX (CAIX) has been shown to be of advantage as sunitinib reduces immunosuppressive components of the TME. Improvements could also be made using Her2-directed CAR NK-92-cells (92/5.137.z) in combination with apatinib. Treatment with CAR NK-92 alone resulted in an efficient elimination of small Her2+ tumor xenografts in vivo, but not in an elimination of larger solid tumors in gastric cancers. A combinatorial treatment with apatinib increased CAR NK-92 cell infiltration into these larger tumor xenografts and resulted in an enhanced antitumor efficacy of the cells.

65In AML, early approaches focused on the targeting of single markers; combinatorial therapies, targeting more than one marker, have been tested here as well. Haubner et al. analyzed optimal combinations of different LSC markers and concluded that CD33/TIM-3 or CLL-1/TIM-3 combinatorial targeting is most suitable since these markers maximally cover AML cells and are minimally co-expressed on HSCs. Interestingly, the combination of CD33 and CD123 was found unsuitable. Approaches that already implement combinatorial targeting of AML LSCs include tri-specific killer engagers against CD33 and CD123, compound CAR T-cells against CD33 and CD123 or CLL-1 and CD33 (i.e., NCT03795779), universal CAR T-cells against CD33 and CD123, and CAR CIK-cells against CD33 and CD123.

Future Perspectives

66Studies obtained in the last 5–10 years confirmed the importance and the urgent need of diagnostic screening of the TME not only before the treatment, but also at several stages in the post-therapeutic period. This is within the context of personalized therapies that are based on the idea to identify the best therapeutic approach for the patient. This approach should be based on the tumors molecular signature, involving the TME. The best and the most appropriate therapeutic options, which match each individual patient's requirements will increase the therapeutic efficacy and will cause fewer side effects.

67The particular value of post-therapeutic local biopsies is that they enable the evaluation of tumor relapse risk on the basis of multivariate biomarkers and also provide information on therapeutically addressable targets within the remaining tumor tissue. In-time detection of tumor-promoting cells, which re-emerge in the post-therapeutic period (Figure 3), will allow an application of the individualized and precise second-line therapy in a timely fashion. Detection of tumor cells with stemness phenotypes will allow for their directed and specific targeting using the second-line treatments, depending on a different mode of action. This secondary specific therapy can include, targeted therapies such as e.g., immunotherapies, CAR NK-, and CAR T-cells that mediate a precise eradication of several types of cells: CSCs, CAFs, and/or remaining senescent cells. To increase the specificity and therapeutic outcome and to decrease severe side effects, CAR-based therapeutics are constantly being optimized, as discussed in the section above. Special needs are: improvement of target specificity in combination with decreased off-target effects. In addition, secondary therapies could also include senolytic drugs that selectively kill senescent cells as it was discussed in a recent comprehensive review by Short et al.. These therapies cause very low or minor side-effects after their administration. In the post-therapeutic period, however, it is important to focus on the biomarkers of CSCs as well as the biomarkers of senescent tumor cells, tumor-promoting SASP molecules, CAFs and TAMs. These cells and molecules strongly influence tumor relapse and their monitoring and their in-time elimination is crucial (Figure 3). As currently available blood test systems are not sensitive enough to detect local changes in the TME, other methods for instance local biopsies and subsequent multivariant analysis of obtained tissues should be used whenever possible and even after many years upon the first-line therapy (Figure 3).

68The analysis of multivariant biomarker, however is not only of importance within the post-therapeutic situation. A detailed understanding of the tumor composition before the treatment could allow straight forward first line therapies (Figure 4). Target analysis includes CSCs, CAFs, tumors cells and TAMs, and other tumor-promoting cells. Therapeutic options such as chemotherapy and radiotherapy in combination with small molecules and immunotherapies (CAR cells) could tremendously improve the outcome of the first-line approaches and predict relapses (Figure 4). Combinations already in the first-line therapy are especially required in advanced stages of malignant disease.

69In conclusion, our review gives an overview of the most important biomarkers of CSCs in the TME. Furthermore, we underline the value of local biopsies and precise diagnostics and screening of biomarkers in both pre- and post-therapeutic situations (Figures 3, 4). We suggest the implementation of those strategies in the first and second-line personalized therapy required to eradicate the remaining tumor-promoting senescent tumor cells, CAFs, TAMs, and finally CSCs to protect from tumor recurrence.

70The high costs are one point of contention regarding the biopsies and their analysis as well as the implementation of immunotherapies into the first and secondary line targeted therapies. However, considering the costs for therapies, comprising resection, and medication strategies, as well as the patient's sufferings due to a re-emerged full-blown cancer, the targeted therapy will help to save the patients and clinics from high personnel, emotional, and medicinal costs.

Author Contributions

71SF, UK-B, and TY performed a conceptualization for the review and defined the future perspectives. LW, A-KK, HS, RK, SD, AS, A-RB, TY, SF, and UK-B analyzed the publications and created the figures and tables. All authors contributed to the article and approved the submitted version.

Conflict of Interest

72The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Not in our library10.5483/bmbrep.2017.50.6.039 (opens in a new tab)
61.
Su J Wu S Wu H Le Li Guo T. CD44 is functionally crucial for driving lung cancer stem cells metastasis through Wnt/β-catenin-FoxM1-Twist signaling. Mol Carcinog. (2016 ) 55:1962–73.
Not in our library10.1002/mc.22443 (opens in a new tab)
62.
Satar NA Fakiruddin KS Lim MN Mok PL Zakaria N Fakharuzi NA. Novel triplepositive markers identified in human nonsmall cell lung cancer cell line with chemotherapy-resistant and putative cancer stem cell characteristics. Oncol Rep. (2018 ) 40:669–81.
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63.
Hu B Ma Y Yang Y Zhang L Han H Chen J. CD44 promotes cell proliferation in non-small cell lung cancer. Oncol Lett. (2018 ) 15:5627–33.
Not in our library10.3892/ol.2018.8051 (opens in a new tab)
64.
Suda K Murakami I Yu H Kim J Tan A-C Mizuuchi H. CD44 facilitates epithelial-to-Mesenchymal transition phenotypic change at acquisition of resistance to EGFR kinase inhibitors in lung cancer. Mol Cancer Ther. (2018 ) 17:2257–65.
Not in our library10.1158/1535-7163.mct-17-1279 (opens in a new tab)
65.
Nishino M Ozaki M Hegab AE Hamamoto J Kagawa S Arai D. Variant CD44 expression is enriching for a cell population with cancer stem cell-like characteristics in human lung adenocarcinoma. J Cancer. (2017 ) 8:1774–85.
Not in our library10.7150/jca.19732 (opens in a new tab)
66.
Zakaria N Yusoff NM Zakaria Z Lim MN Baharuddin PJ Fakiruddin KS. Human non-small cell lung cancer expresses putative cancer stem cell markers and exhibits the transcriptomic profile of multipotent cells. BMC Cancer. (2015 ) 15:84.
Not in our library10.1186/s12885-015-1086-3 (opens in a new tab)
67.
Prabavathy D SwaRNAlatha Y Ramadoss N. Lung cancer stem cells-origin, characteristics and therapy. Stem Cell Investig. (2018 ) 5:6.
Not in our library10.21037/sci.2018.02.01 (opens in a new tab)
68.
Lung Cancers: Molecular Characterization, Clonal Heterogeneity and Evolution, and Cancer Stem Cells · 2018
No notice
69.
Maiuthed A Chantarawong W Chanvorachote P. Lung cancer stem cells and cancer stem cell-targeting natural compounds. Anticancer Res. (2018 ) 38:3797–809.
Not in our library10.21873/anticanres.12663 (opens in a new tab)
70.
Park E Park SY Sun P-L Jin Y Kim JE Jheon S. Prognostic significance of stem cell-related marker expression and its correlation with histologic subtypes in lung adenocarcinoma. Oncotarget. (2016 ) 7:42502–12.
Not in our library10.18632/oncotarget.9894 (opens in a new tab)
71.
Alamgeer M Neil Watkins D Banakh I Kumar B Gough DJ Markman B. A phase IIa study of HA-irinotecan, formulation of hyaluronic acid and irinotecan targeting CD44 in extensive-stage small cell lung cancer. Invest New Drugs. (2018 ) 36:288–98.
Not in our library10.1007/s10637-017-0555-8 (opens in a new tab)
72.
Quan YH Lim J-Y Choi BH Choi Y Choi YH Park J-H. Self-targeted knockdown of CD44 improves cisplatin sensitivity of chemoresistant non-small cell lung cancer cells. Cancer Chemother Pharmacol. (2019 ) 83:399–410.
Not in our library10.1007/s00280-018-3737-y (opens in a new tab)
73.
Kawano Y Iwama E Tsuchihashi K Shibahara D Harada T Tanaka K. CD44 variant-dependent regulation of redox balance in EGFR mutation-positive non-small cell lung cancer: a target for treatment. Lung Cancer. (2017 ) 113:72–8.
Not in our library10.1016/j.lungcan.2017.09.008 (opens in a new tab)
74.
Huang X Wan J Leng D Zhang Y Yang S. Dual-targeting nanomicelles with CD133 and CD44 aptamers for enhanced delivery of gefitinib to two populations of lung cancer-initiating cells. Exp Ther Med. (2020 ) 19:192–204.
Not in our library10.3892/etm.2019.8220 (opens in a new tab)
75.
Luo Y Wang X Du D Lin Y. Hyaluronic acid-conjugated apoferritin nanocages for lung cancer targeted drug delivery. Biomater Sci. (2015 ) 3:1386–94.
Not in our library10.1039/c5bm00067j (opens in a new tab)
76.
Alshaer W Hillaireau H Vergnaud J Ismail S Fattal E. Functionalizing liposomes with anti-CD44 aptamer for selective targeting of cancer cells. Bioconjug Chem. (2015 ) 26:1307–13.
Not in our library10.1021/bc5004313 (opens in a new tab)
77.
Song Y Cai H Yin T Huo M Ma P Zhou J. PaCLitaxel-loaded redox-sensitive nanopartiCLes based on hyaluronic acid-vitamin E succinate conjugates for improved lung cancer treatment. Int J Nanomed. (2018 ) 13:1585–600.
Not in our library10.2147/ijn.s155383 (opens in a new tab)
78.
Parashar P Rathor M Dwivedi M Saraf SA. Hyaluronic acid decorated naringenin nanoparticles: appraisal of chemopreventive and curative potential for lung cancer. Pharmaceutics. (2018 ) 10:33.
Not in our library10.3390/pharmaceutics10010033 (opens in a new tab)
79.
Tian Y Zhang H Qin Y Li D Liu Y Wang H. Overcoming drug-resistant lung cancer by paCLitaxel-loaded hyaluronic acid-coated liposomes targeted to mitochondria. Drug Dev Ind Pharm. (2018 ) 44:2071–82.
Not in our library10.1080/03639045.2018.1512613 (opens in a new tab)
80.
Zhang W Xu W Lan Y He X Liu K Liang Y. Antitumor effect of hyaluronic-acid-modified chitosan nanopartiCLes loaded with siRNA for targeted therapy for non-small cell lung cancer. Int J Nanomedicine. (2019 ) 14:5287–301.
Not in our library10.2147/ijn.s203113 (opens in a new tab)
81.
Shinohara S Hanagiri T Taira A Takenaka M Oka S Chikaishi Y. Immunohistochemical expression and serum levels of CD44 as prognostic indicators in patients with non-small cell lung cancer. Oncology. (2016 ) 90:327–38.
Not in our library10.1159/000445951 (opens in a new tab)
82.
Qiu X Wang Z Li Y Miao Y Ren Y Luan Y. Characterization of sphere-forming cells with stem-like properties from the small cell lung cancer cell line H446. Cancer Lett. (2012 ) 323:161–70.
Not in our library10.1016/j.canlet.2012.04.004 (opens in a new tab)
83.
Yan X Luo H Zhou X Zhu B Wang Y Bian X. Identification of CD90 as a marker for lung cancer stem cells in a549 and h446 cell lines. Oncol Rep. (2013 ) 30:2733–40.
Not in our library10.3892/or.2013.2784 (opens in a new tab)
84.
Koren A Rijavec M Kern I Sodja E Korosec P Cufer T. BMI1, ALDH1A1, and CD133 transcripts connect epithelial-mesenchymal transition to cancer stem cells in lung carcinoma. Stem Cells Int. (2016 ) 2016:9714315.
Not in our library10.1155/2016/9714315 (opens in a new tab)
85.
Alama A Gangemi R Ferrini S Barisione G Orengo AM Truini M. CD133-Positive cells from non-Small cell lung cancer show distinct sensitivity to cisplatin and afatinib. Arch Immunol Ther Exp. (2015 ) 63:207–14.
Not in our library10.1007/s00005-015-0330-5 (opens in a new tab)
86.
Eramo A Lotti F Sette G Pilozzi E Biffoni M Di Virgilio A. Identification and expansion of the tumorigenic lung cancer stem cell population. Cell Death Differ. (2008 ) 15:504–14.
Not in our library10.1038/sj.cdd.4402283 (opens in a new tab)
87.
Huang Z Yu H Zhang J Jing H Zhu W Li X. Correlation of cancer stem cell markers and immune cell markers in resected non-small cell lung cancer. J Cancer. (2017 ) 8:3190–7.
Not in our library10.7150/jca.20172 (opens in a new tab)
88.
Li L Li J-C Yang H Zhang X Liu L-L Li Y. Expansion of cancer stem cell pool initiates lung cancer recurrence before angiogenesis. Proc Natl Acad Sci USA. (2018 ) 115:E8948–57.
Not in our library10.1073/pnas.1806219115 (opens in a new tab)
89.
Liu X Wei H Liu Y Zhao M Wu S Yang Y. Construction of high sensitive CD133 immune PLGA magnetic spheres platform for lung cancer stem cells isolation and its property evaluation. J Biomed Nanotechnol. (2018 ) 14:1066–74.
Not in our library10.1166/jbn.2018.2562 (opens in a new tab)
90.
Su Y-J Lin W-H Chang Y-W Wei K-C Liang C-L Chen S-C. Polarized cell migration induces cancer type-specific CD133/integrin/Src/Akt/GSK3β/β-catenin signaling required for maintenance of cancer stem cell properties. Oncotarget. (2015 ) 6:38029–45.
Not in our library10.18632/oncotarget.5703 (opens in a new tab)
91.
Bertolini G D'Amico L Moro M Landoni E Perego P Miceli R. Microenvironment-modulated metastatic CD133+/CXCR4+/EpCAM- lung cancer-Initiating cells sustain tumor dissemination and correlate with poor prognosis. Cancer Res. (2015 ) 75:3636–49.
Not in our library10.1158/0008-5472.can-14-3781 (opens in a new tab)
92.
Chen Y Zhang F Tsai Y Yang X Yang L Duan S. IL-6 signaling promotes DNA repair and prevents apoptosis in CD133+ stem-like cells of lung cancer after radiation. Radiat Oncol. (2015 ) 10:227.
Not in our library10.1186/s13014-015-0534-1 (opens in a new tab)
93.
Zhao W Luo Y Li B Zhang T. Tumorigenic lung tumorospheres exhibit stem-like features with significantly increased expression of CD133 and ABCG2. Mol Med Rep. (2016 ) 14:2598–606.
Not in our library10.3892/mmr.2016.5524 (opens in a new tab)
94.
Koyama K Katsurada N Jimbo N Tachihara M Tamura D Nakata K. Overexpression of CD 133 and bCL-2 in non-small cell lung cancer with neuroendocrine differentiation after transformation in ALK rearrangement-positive adenocarcinoma. Pathol Int. (2019 ) 69:294–9.
Not in our library10.1111/pin.12782 (opens in a new tab)
95.
Moro M Bertolini G Caserini R Borzi C Boeri M Fabbri A. Establishment of patient derived xenografts as functional testing of lung cancer aggressiveness. Sci. Rep. (2017 ) 7:6689.
Not in our library10.1038/s41598-017-06912-7 (opens in a new tab)
96.
Zhao C Setrerrahmane S Xu H. Enrichment and characterization of cancer stem cells from a human non-small cell lung cancer cell line. Oncol Rep. (2015 ) 34:2126–32.
Not in our library10.3892/or.2015.4163 (opens in a new tab)
97.
Sun F-F Hu Y-H Xiong L-P Tu X-Y Zhao J-H Chen S-S. Enhanced expression of stem cell markers and drug resistance in sphere-forming non-small cell lung cancer cells. Int J Clin Exp Pathol. (2015 ) 8:6287–300.
Not in our library
98.
Yu J Wang S Zhao W Duan J Wang Z Chen H. Mechanistic exploration of cancer stem cell marker voltage-Dependent calcium channel α2δ1 subunit-mediated chemotherapy resistance in small-cell lung cancer. Clin Cancer Res. (2018 ) 24:2148–58.
Not in our library10.1158/1078-0432.ccr-17-1932 (opens in a new tab)
99.
Sarvi S Mackinnon AC Avlonitis N Bradley M Rintoul RC Rassl DM. CD133+ cancer stem-like cells in small cell lung cancer are highly tumorigenic and chemoresistant but sensitive to a novel neuropeptide antagonist. Cancer Res. (2014 ) 74:1554–65.
Not in our library10.1158/0008-5472.can-13-1541 (opens in a new tab)
100.
Meng X Li M Wang X Wang Y Ma D. Both CD133+ and CD133- subpopulations of a549 and h446 cells contain cancer-initiating cells. Cancer Sci. (2009 ) 100:1040–6.
Not in our library10.1111/j.1349-7006.2009.01144.x (opens in a new tab)
101.
Huang X Huang J Leng D Yang S Yao Q Sun J. Gefitinib-loaded DSPE-PEG2000 nanomicelles with CD133 aptamers target lung cancer stem cells. World J Surg Oncol. (2017 ) 15:167.
Not in our library10.1186/s12957-017-1230-4 (opens in a new tab)
102.
Ma J Zhuang H Zhuang Z Lu Y Xia R Gan L. Development of docetaxel liposome surface modified with CD133 aptamers for lung cancer targeting. Artif Cells Nanomed Biotechnol. (2018 ) 46:1864–71.
Not in our library10.1080/21691401.2017.1394874 (opens in a new tab)
103.
Zhou J Sun J Chen H Peng Q. Promoted delivery of salinomycin sodium to lung cancer cells by dual targeting PLGA hybrid nanopartiCLes. Int J Oncol. (2018 ) 53:1289–300.
Not in our library10.3892/ijo.2018.4474 (opens in a new tab)
104.
Combined using of paclitaxel and salinomycin active targeting nanostructured lipid carriers against non-small cell lung cancer and cancer stem cells · 2019
Not checked
105.
Bertolini G Roz L Perego P Tortoreto M Fontanella E Gatti L. Highly tumorigenic lung cancer CD133+ cells display stem-like features and are spared by cisplatin treatment. Proc Natl Acad Sci USA. (2009 ) 106:16281–6.
Not in our library10.1073/pnas.0905653106 (opens in a new tab)
106.
Wang D Wen G-M Hou W Xia P. The roles of CD133 expression in the patients with non-small cell lung cancer. Cancer Biomark. (2018 ) 22:385–94.
Not in our library10.3233/cbm-170835 (opens in a new tab)
107.
Miyata T Oyama T Yoshimatsu T Higa H Kawano D Sekimura A. The Clinical significance of cancer stem cell markers ALDH1A1 and CD133 in lung adenocarcinoma. Anticancer Res. (2017 ) 37:2541–7.
Not in our library10.21873/anticanres.11597 (opens in a new tab)
108.
Su C Xu Y Li X Ren S Zhao C Hou L. Predictive and prognostic effect of CD133 and cancer-testis antigens in stage Ib-IIIA non-small cell lung cancer. Int J Clin Exp Pathol. (2015 ) 8:5509–18.
Not in our library
109.
Qiu Z-X Zhao S Mo X-M Li W-M. Overexpression of PROM1 (CD133) confers poor prognosis in non-small cell lung cancer. Int J Clin Exp Pathol. (2015 ) 8:6589–95.
Not in our library
110.
Wen G-M Mou F-F Hou W Wang D Xia P. Integrative analysis of CD133 mRNA in human cancers based on data mining. Stem Cell Rev Rep. (2019 ) 15:23–34.
Not in our library10.1007/s12015-018-9865-2 (opens in a new tab)
111.
Sowa T Menju T Sonobe M Nakanishi T Shikuma K Imamura N. Association between epithelial-mesenchymal transition and cancer stemness and their effect on the prognosis of lung adenocarcinoma. Cancer Med. (2015 ) 4:1853–62.
Not in our library10.1002/cam4.556 (opens in a new tab)
112.
Chen E Zeng Z Bai B Zhu J Song Z. The prognostic value of CSCs biomarker CD133 in NSCLC: a meta-analysis. Oncotarget. (2016 ) 7:56526–39.
Not in our library10.18632/oncotarget.10964 (opens in a new tab)
113.
Zhao M Zhang Y Zhang H Wang S Zhang M Chen X. Hypoxia-induced cell stemness leads to drug resistance and poor prognosis in lung adenocarcinoma. Lung Cancer. (2015 ) 87:98–106.
Not in our library10.1016/j.lungcan.2014.11.017 (opens in a new tab)
114.
Hanssen A Wagner J Gorges TM Taenzer A Uzunoglu FG Driemel C. Characterization of different CTC subpopulations in non-small cell lung cancer. Sci. Rep. (2016 ) 6:28010.
Not in our library10.1038/srep28010 (opens in a new tab)
115.
Jahchan NS Lim JS Bola B Morris K Seitz G Tran KQ. Identification and targeting of long-term tumor-Propagating cells in small cell lung cancer. Cell Rep. (2016 ) 16:644–56.
Not in our library10.1016/j.celrep.2016.06.021 (opens in a new tab)
116.
Chen L Peng M Li N Song Q Yao Y Xu B. Combined use of epCAM and FRα enables the high-efficiency capture of circulating tumor cells in non-small cell lung cancer. Sci. Rep. (2018 ) 8:1188.
Not in our library10.1038/s41598-018-19391-1 (opens in a new tab)
117.
Wit S de Rossi E Weber S Tamminga M Manicone M Swennenhuis JF. Single tube liquid biopsy for advanced non-small cell lung cancer. Int J Cancer. (2019 ) 144:3127–37.
Not in our library10.1002/ijc.32056 (opens in a new tab)
118.
Zamay GS Kolovskaya OS Ivanchenko TI Zamay TN Veprintsev DV Grigorieva VL. Development of DNA aptamers to native EpCAM for isolation of lung circulating tumor cells from human blood. Cancers. (2019 ) 11:351.
Not in our library10.3390/cancers11030351 (opens in a new tab)
119.
Rud AK Boye K Fodstad Ø Juell S Jørgensen LH Solberg S. Detection of disseminated tumor cells in lymph nodes from patients with early stage non-small cell lung cancer. Diagn Pathol. (2016 ) 11:50.
Not in our library10.1186/s13000-016-0504-4 (opens in a new tab)
120.
Gao W Huang T Yuan H Yang J Jin Q Jia C. Highly sensitive detection and mutational analysis of lung cancer circulating tumor cells using integrated combined immunomagnetic beads with a droplet digital PCR chip. Talanta. (2018 ) 185:229–36.
Not in our library10.1016/j.talanta.2018.03.083 (opens in a new tab)
121.
Alibolandi M Ramezani M Abnous K Sadeghi F Atyabi F Asouri M. In vitro and in vivo evaluation of therapy targeting epithelial-cell adhesion-molecule aptamers for non-small cell lung cancer. J Control Release. (2015 ) 209:88–100.
Not in our library10.1016/j.jconrel.2015.04.026 (opens in a new tab)
122.
Thompson JC Fan R Black T Yu GH Savitch SL Chien A. Measurement and immunophenotyping of pleural fluid epCAM-positive cells and CLusters for the management of non-small cell lung cancer patients. Lung Cancer. (2019 ) 127:25–33.
Not in our library10.1016/j.lungcan.2018.11.020 (opens in a new tab)
123.
Zhou N Wang H Liu H Xue H Lin F Meng X. MTA1-upregulated epCAM is associated with metastatic behaviors and poor prognosis in lung cancer. J Exp Clin Cancer Res. (2015 ) 34:157.
Not in our library10.1186/s13046-015-0263-1 (opens in a new tab)
124.
The detection of EpCAM+ and EpCAM– circulating tumor cells · 2015
No notice
125.
Gao F Zhou B Xu J-C Gao X Li S-X Zhu G-C. The role of LGR5 and ALDH1A1 in non-small cell lung cancer: cancer progression and prognosis. Biochem Biophys Res Commun. (2015 ) 462:91–8.
Not in our library10.1016/j.bbrc.2015.04.029 (opens in a new tab)
126.
Koh YW Han J-H Haam S Jung J. ALDH1 expression correlates with an epithelial-like phenotype and favorable prognosis in lung adenocarcinoma: a study based on immunohistochemistry and mRNA expression data. J Cancer Res Clin Oncol. (2019 ) 145:1427–36.
Not in our library10.1007/s00432-019-02906-2 (opens in a new tab)
127.
Codony-Servat J Codony-Servat C Cardona AF Giménez-Capitán A Drozdowskyj A Berenguer J. Cancer stem cell biomarkers in EGFR-mutation-positive non-small-cell lung cancer. Clin Lung Cancer. (2019 ) 20:167–77.
Not in our library10.1016/j.cllc.2019.02.005 (opens in a new tab)
128.
Jiang F Qiu Q Khanna A Todd NW Deepak J Xing L. Aldehyde dehydrogenase 1 is a tumor stem cell-associated marker in lung cancer. Mol Cancer Res. (2009 ) 7:330–8.
Not in our library10.1158/1541-7786.mcr-08-0393 (opens in a new tab)
129.
Masciale V Grisendi G Banchelli F D'Amico R Maiorana A Sighinolfi P. Isolation and identification of cancer stem-like cells in adenocarcinoma and squamous cell carcinoma of the lung: a Pilot study. Front. Oncol. (2019 ) 9:1394.
Not in our library10.3389/fonc.2019.01394 (opens in a new tab)
130.
Codony-Servat J Verlicchi A Rosell R. Cancer stem cells in small cell lung cancer. Transl Lung Cancer Res. (2016 ) 5:16–25.
Not in our library10.3978/j.issn.2218-6751.2016.01.01 (opens in a new tab)
131.
Rossi A Voigtlaender M Klose H Schlüter H Schön G Loges S. High aldehyde dehydrogenase levels are detectable in the serum of patients with lung cancer and may be exploited as screening biomarkers. J Oncol. (2019 ) 2019:8970645.
Not in our library10.1155/2019/8970645 (opens in a new tab)
132.
Liu X Wang L Cui W Yuan X Lin L Cao Q. Targeting ALDH1A1 by disulfiram/copper complex inhibits non-small cell lung cancer recurrence driven by ALDH-positive cancer stem cells. Oncotarget. (2016 ) 7:58516–30.
Not in our library10.18632/oncotarget.11305 (opens in a new tab)
133.
Kang JH Lee S-H Lee J-S Nam B Seong TW Son J. Aldehyde dehydrogenase inhibition combined with phenformin treatment reversed nSCLC through aTP depletion. Oncotarget. (2016 ) 7:49397–410.
Not in our library10.18632/oncotarget.10354 (opens in a new tab)
134.
Wang N-N Wang L-H Li Y Fu S-Y Xue X Jia L-N. Targeting ALDH2 with disulfiram/copper reverses the resistance of cancer cells to microtubule inhibitors. Exp Cell Res. (2018 ) 362:72–82.
Not in our library10.1016/j.yexcr.2017.11.004 (opens in a new tab)
135.
Morise M Hishida T Takahashi A Yoshida J Ohe Y Nagai K. CLinicopathological significance of cancer stem-like cell markers in high-grade neuroendocrine carcinoma of the lung. J Cancer Res Clin Oncol. (2015 ) 141:2121–30.
Not in our library10.1007/s00432-015-1985-3 (opens in a new tab)
136.
Li S-J Huang J Zhou X-D Zhang W-B Lai Y-T Che G-W. CLinicopathological and prognostic significance of oct-4 expression in patients with non-small cell lung cancer: a systematic review and meta-analysis. J Thorac Dis. (2016 ) 8:1587–600.
Not in our library10.21037/jtd.2016.06.01 (opens in a new tab)
137.
Kouros-Mehr H Bechis SK Slorach EM Littlepage LE Egeblad M Ewald AJ. GATA-3 links tumor differentiation and dissemination in a luminal breast cancer model. Cancer Cell. (2008 ) 13:141–52.
Not in our library10.1016/j.ccr.2008.01.011 (opens in a new tab)
138.
Barnawi R Al-Khaldi S Colak D Tulbah A Al-Tweigeri T Fallatah M. β1 Integrin is essential for fascin-mediated breast cancer stem cell function and disease progression. Int J Cancer. (2019 ) 145:830–41.
Not in our library10.1002/ijc.32183 (opens in a new tab)
139.
Da Cruz Paula A Leitão C Marques O Rosa AM Santos AH Rêma A. Molecular characterization of CD44+/CD24-/Ck+/CD45- cells in benign and malignant breast lesions. Virchows Arch. (2017 ) 470:311–22.
Not in our library10.1007/s00428-017-2068-4 (opens in a new tab)
140.
Nam K Oh S Lee KM Yoo SA Shin I. CD44 regulates cell proliferation, migration, and invasion via modulation of c-Src transcription in human breast cancer cells. Cell Signal. (2015 ) 27:1882–94.
Not in our library10.1016/j.cellsig.2015.05.002 (opens in a new tab)
141.
Zhang H Brown RL Wei Y Zhao P Liu S Liu X. CD44 splice isoform switching determines breast cancer stem cell state. Genes Dev. (2019 ) 33:166–79.
Not in our library10.1101/gad.319889.118 (opens in a new tab)
142.
Zhang L Xu L Zhang F Vlashi E. Doxycycline inhibits the cancer stem cell phenotype and epithelial-to-mesenchymal transition in breast cancer. Cell Cycle. (2017 ) 16:737–45.
Not in our library10.1080/15384101.2016.1241929 (opens in a new tab)
143.
Ge G Zhou C Ren Y Tang X Wang K Zhang W. Enhanced SLC34A2 in breast cancer stem cell-like cells induces chemotherapeutic resistance to doxorubicin via SLC34A2-Bmi1-ABCC5 signaling. Tumour Biol. (2016 ) 37:5049–62.
Not in our library10.1007/s13277-015-4226-0 (opens in a new tab)
144.
Colacino JA Azizi E Brooks MD Harouaka R Fouladdel S MCDermott SP. Heterogeneity of human breast stem and progenitor cells as revealed by transcriptional profiling. Stem Cell Reports. (2018 ) 10:1596–609.
Not in our library10.1016/j.stemcr.2018.03.001 (opens in a new tab)
145.
Hu J Li G Zhang P Zhuang X Hu G. A CD44v+ subpopulation of breast cancer stem-like cells with enhanced lung metastasis capacity. Cell Death Dis. (2017 ) 8:e2679.
Not in our library10.1038/cddis.2017.72 (opens in a new tab)
146.
Ji P Zhang Y Wang S-J Ge H-L Zhao G-P Xu Y-C. CD44hiCD24lo mammosphere-forming cells from primary breast cancer display resistance to multiple chemotherapeutic drugs. Oncol Rep. (2016 ) 35:3293–302.
Not in our library10.3892/or.2016.4739 (opens in a new tab)
147.
Unraveling the roles of CD44/CD24 and ALDH1 as cancer stem cell markers in tumorigenesis and metastasis · 2017
Corrected
148.
Louhichi T Ziadi S Saad H Dhiab MB Mestiri S Trimeche M. CLinicopathological significance of cancer stem cell markers CD44 and ALDH1 expression in breast cancer. Breast Cancer. (2018 ) 25:698–705.
Not in our library10.1007/s12282-018-0875-3 (opens in a new tab)
149.
Cho Y Lee H-W Kang H-G Kim H-Y Kim S-J Chun K-H. Cleaved CD44 intracellular domain supports activation of stemness factors and promotes tumorigenesis of breast cancer. Oncotarget. (2015 ) 6:8709–21.
Not in our library10.18632/oncotarget.3325 (opens in a new tab)
150.
Jin J Krishnamachary B Mironchik Y Kobayashi H Bhujwalla ZM. Phototheranostics of CD44-positive cell populations in triple negative breast cancer. Sci. Rep. (2016 ) 6:27871.
Not in our library10.1038/srep27871 (opens in a new tab)
151.
Qiu Y Zhou B Yang X Long D Hao Y Yang P. Novel single-cell analysis platform based on a solid-State zinc-Coadsorbed carbon quantum dots electrochemiluminescence probe for the evaluation of CD44 expression on breast cancer cells. ACS Appl Mater Interfaces. (2017 ) 9:16848–56.
Not in our library10.1021/acsami.7b02793 (opens in a new tab)
152.
Wang Z Sau S Alsaab HO Iyer AK. CD44 directed nanomicellar payload delivery platform for selective anticancer effect and tumor specific imaging of triple negative breast cancer. Nanomedicine. (2018 ) 14:1441–54.
Not in our library10.1016/j.nano.2018.04.004 (opens in a new tab)
153.
Yaghjyan L Stoll E Ghosh K Scott CG Jensen MR Brandt KR. Tissue-based associations of mammographic breast density with breast stem cell markers. Breast Cancer Res. (2017 ) 19:100.
Not in our library10.1186/s13058-017-0889-3 (opens in a new tab)
154.
Yang R-M Fu C-P Fang J-Z Xu X-D Wei X-H Tang W-J. Hyaluronan-modified superparamagnetic iron oxide nanopartiCLes for bimodal breast cancer imaging and photothermal therapy. Int J Nanomedicine. (2017 ) 12:197–206.
Not in our library10.2147/ijn.s121249 (opens in a new tab)
155.
MunTIMadugu E Kumar R Saladi S Rafeeqi TA Khan W. CD44 targeted chemotherapy for co-eradication of breast cancer stem cells and cancer cells using polymeric nanopartiCLes of salinomycin and paclitaxel. Colloids Surf B Biointerfaces. (2016 ) 143:532–46.
Not in our library10.1016/j.colsurfb.2016.03.075 (opens in a new tab)
156.
Agrawal S Dwivedi M Ahmad H Chadchan SB Arya A Sikandar R. CD44 targeting hyaluronic acid coated lapatinib nanocrystals foster the efficacy against triple-negative breast cancer. Nanomedicine. (2018 ) 14:327–37.
Not in our library10.1016/j.nano.2017.10.010 (opens in a new tab)
157.
Aguirre-Alvarado C Segura-Cabrera A Velázquez-Quesada I Hernández-Esquivel MA García-Pérez CA Guerrero-Rodríguez SL. Virtual screening-driven repositioning of etoposide as CD44 antagonist in breast cancer cells. Oncotarget. (2016 ) 7:23772–84.
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158.
Chen J He H Deng C Yin L Zhong Z. Saporin-loaded CD44 and EGFR dual-targeted nanogels for potent inhibition of metastatic breast cancer in vivo. Int J Pharm. (2019 ) 560:57–64.
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159.
Chen J Ouyang J Chen Q Deng C Meng F Zhang J. EGFR and CD44 dual-Targeted multifunctional hyaluronic acid nanogels boost protein delivery to ovarian and breast cancers in vitro and in vivo. ACS Appl Mater Interfaces. (2017 ) 9:24140–7.
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160.
Fan W Wang X Ding B Cai H Wang X Fan Y. Thioaptamer-conjugated CD44-targeted delivery system for the treatment of breast cancer in vitro and in vivo. J Drug Target. (2016 ) 24:359–71.
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161.
Fan Y Wang Q Lin G Shi Y Gu Z Ding T. Combination of using prodrug-modified cationic liposome nanocomplexes and a potentiating strategy via targeted co-delivery of gemcitabine and docetaxel for CD44-overexpressed triple negative breast cancer therapy. Acta Biomater. (2017 ) 62:257–72.
Not in our library10.1016/j.actbio.2017.08.034 (opens in a new tab)
162.
Fu W Sun H Zhao Y Chen M Yang L Yang X. Targeted delivery of CD44s-siRNA by ScFv overcomes de novo resistance to cetuximab in triple negative breast cancer. Mol Immunol. (2018 ) 99:124–33.
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163.
Han N-K Shin DH Kim JS Weon KY Jang C-Y Kim J-S. Hyaluronan-conjugated liposomes encapsulating gemcitabine for breast cancer stem cells. Int J Nanomedicine. (2016 ) 11:1413–25.
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164.
Liang D-S Zhang W-J Wang A-T Su H-T Zhong H-J Qi X-R. Treating metastatic triple negative breast cancer with CD44/neuropilin dual molecular targets of multifunctional nanopartiCLes. Biomaterials. (2017 ) 137:23–36.
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165.
Xie X Huang X Tang H Ye F Yang L Guo X. Diallyl disulfide inhibits breast cancer stem cell progression and glucose metabolism by targeting CD44/PKM2/AMPK signaling. Curr Cancer Drug Targets. (2018 ) 18:592–9.
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166.
Yang C He Y Zhang H Liu Y Wang W Du Y. Selective killing of breast cancer cells expressing activated CD44 using CD44 ligand-coated nanopartiCLes in vitro and in vivo. Oncotarget. (2015 ) 6:15283–96.
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167.
McFarlane S Coulter JA Tibbits P O'Grady A McFarlane C Montgomery N CD44 increases the efficiency of distant metastasis of breast cancer. Oncotarget. (2015 ) 6:11465–76.
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168.
Rico MJ Perroud HA Herrera C Alasino CM Roggero EA Pezzotto SM. Putative biomarkers of response to treatment in breast cancer patients: a pilot assay. Cancer Invest. (2017 ) 35:377–85.
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169.
Sanmartín E Ortiz-Martínez F Pomares-Navarro E García-Martínez A Rodrigo-Baños M García-Escolano M. CD44 induces FOXP3 expression and is related with favorable outcome in breast carcinoma. Virchows Arch. (2017 ) 470:81–90.
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170.
Seo AN Lee HJ Kim EJ Jang MH Kim YJ Kim JH. Expression of breast cancer stem cell markers as predictors of prognosis and response to trastuzumab in HER2-positive breast cancer. Br J Cancer. (2016 ) 114:1109–16.
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171.
Da Cruz Paula A Marques O Sampaio R Rosa A Garcia J Rêma A. Characterization of CD44+ALDH1+Ki-67- cells in non-malignant and neoplastic lesions of the breast. Anticancer Res. (2016 ) 36:4629–38.
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172.
Rabinovich I Sebastião AP Lima RS Urban CD Junior ES Anselmi KF. Cancer stem cell markers ALDH1 and CD44+/CD24- phenotype and their prognosis impact in invasive ductal carcinoma. Eur J Histochem. (2018 ) 62:2943.
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173.
Yaghjyan L Esnakula AK Scott CG Wijayabahu AT Jensen MR Vachon CM. Associations of mammographic breast density with breast stem cell marker-defined breast cancer subtypes. Cancer Causes Control. (2019 ) 30:1103–11.
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174.
Gómez-Miragaya J Palafox M Paré L Yoldi G Ferrer I Vila S. Resistance to taxanes in triple-negative breast cancer associates with the dynamics of a CD49f+ tumor-Initiating population. Stem Cell Reports. (2017 ) 8:1392–407.
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175.
Ye F Zhong X Qiu Y Yang L Wei B Zhang Z CD49f can act as a biomarker for local or distant recurrence in breast cancer. J Breast Cancer. (2017 ) 20:142–9.
Not in our library10.4048/jbc.2017.20.2.142 (opens in a new tab)
176.
Gomez-Miragaya J González-Suárez E. Tumor-initiating CD49f cells are a hallmark of chemoresistant triple negative breast cancer. Mol Cell Oncol. (2017 ) 4:e1338208.
Not in our library10.1080/23723556.2017.1338208 (opens in a new tab)
177.
Krebsbach PH Villa-Diaz LG. The role of integrin α6 (CD49f) in stem cells: more than a conserved biomarker. Stem Cells Dev. (2017 ) 26:1090–9.
Not in our library10.1089/scd.2016.0319 (opens in a new tab)
178.
Hu T Zhou R Zhao Y Wu G. Integrin α6/Akt/Erk signaling is essential for human breast cancer resistance to radiotherapy. Sci. Rep. (2016 ) 6:33376.
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179.
Ye F Qiu Y Li L Yang L Cheng F Zhang H. The presence of epCAM(-)/CD49f(+) cells in breast cancer is associated with a poor clinical outcome. J Breast Cancer. (2015 ) 18:242–8.
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180.
Yeo SK Wen J Chen S Guan J-L. Autophagy differentially regulates distinct breast cancer stem-like cells in murine models via EGFR/Stat3 and Tgfβ/Smad signaling. Cancer Res. (2016 ) 76:3397–410.
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181.
Liu L Yin B Yi Z Liu X Hu Z Gao W. Breast cancer stem cells characterized by CD70 expression preferentially metastasize to the lungs. Breast Cancer. (2018 ) 25:706–16.
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182.
Wang X Liu Y Zhou K Zhang G Wang F Ren J. Isolation and characterization of CD105+/CD90+ subpopulation in breast cancer mDA-MB-231 cell line. Int J Clin Exp Pathol. (2015 ) 8:5105–12.
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183.
Sansone P Berishaj M Rajasekhar VK Ceccarelli C Chang Q Strillacci A. Evolution of cancer stem-like cells in endocrine-resistant metastatic breast cancers is mediated by stromal microvesiCLes. Cancer Res. (2017 ) 77:1927–41.
Not in our library10.1158/0008-5472.can-16-2129 (opens in a new tab)
184.
Brugnoli F Grassilli S Al-Qassab Y Capitani S Bertagnolo V. CD133 in breast cancer cells: more than a stem cell marker. J Oncol. (2019 ) 2019:7512632.
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185.
Zhang D Sun B Zhao X Ma Y Ji R Gu Q. Twist1 expression induced by sunitinib accelerates tumor cell vasculogenic mimicry by increasing the population of CD133+ cells in triple-negative breast cancer. Mol Cancer. (2014 ) 13:207.
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186.
Up-modulation of PLC-β2 reduces the number and malignancy of triple-negative breast tumor cells with a CD133+/EpCAM+ phenotype: a promising target for preventing progression of TNBC · 2017
Not checked
187.
Self-renewal of CD133hi cells by IL6/Notch3 signalling regulates endocrine resistance in metastatic breast cancer · 2016
No notice
188.
Swaminathan SK Roger E Toti U Niu L Ohlfest JR Panyam J. CD133-targeted paCLitaxel delivery inhibits local tumor recurrence in a mouse model of breast cancer. J Control Release. (2013 ) 171:280–7.
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189.
Brugnoli F Grassilli S Piazzi M Palomba M Nika E Bavelloni A. In triple negative breast tumor cells, pLC-β2 promotes the conversion of CD133high to CD133low phenotype and reduces the CD133-related invasiveness. Mol Cancer. (2013 ) 12:165.
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190.
Latorre E Carelli S Raimondi I D'Agostino V Castiglioni I Zucal C. The ribonucleic complex HuR-MALAT1 represses CD133 expression and suppresses epithelial-Mesenchymal transition in breast cancer. Cancer Res. (2016 ) 76:2626–36.
Not in our library10.1158/0008-5472.can-15-2018 (opens in a new tab)
191.
Bock C Kuhn C Ditsch N Krebold R Heublein S Mayr D. Strong correlation between n-cadherin and CD133 in breast cancer: role of both markers in metastatic events. J Cancer Res Clin Oncol. (2014 ) 140:1873–81.
Not in our library10.1007/s00432-014-1750-z (opens in a new tab)
192.
Nozaki Y Tamori S Inada M Katayama R Nakane H Minamishima O. Correlation between c-Met and ALDH1 contributes to the survival and tumor-sphere formation of ALDH1 positive breast cancer stem cells and predicts poor Clinical outcome in breast cancer. Genes Cancer. (2017 ) 8:628–39.
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193.
Joseph C Arshad M Kurozomi S Althobiti M Miligy IM Al-Izzi S. Overexpression of the cancer stem cell marker CD133 confers a poor prognosis in invasive breast cancer. Breast Cancer Res Treat. (2019 ) 174:387–99.
Not in our library10.1007/s10549-018-05085-9 (opens in a new tab)
194.
Zhang M Tsimelzon A Chang C-H Fan C Wolff A Perou CM. Intratumoral heterogeneity in a trp53-null mouse model of human breast cancer. Cancer Discov. (2015 ) 5:520–33.
Not in our library10.1158/2159-8290.cd-14-1101 (opens in a new tab)
195.
Yang L Tang H Kong Y Xie X Chen J Song C. LGR5 promotes breast cancer progression and maintains stem-Like cells through activation of wnt/β-Catenin signaling. Stem Cells. (2015 ) 33:2913–24.
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196.
Wang D Cai C Dong X Yu QC Zhang X-O Yang L. Identification of multipotent mammary stem cells by protein C receptor expression. Nature. (2015 ) 517:81–4.
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197.
Ginestier C Hur MH Charafe-Jauffret E Monville F Dutcher J Brown M. ALDH1 is a marker of normal and malignant human mammary stem cells and a predictor of poor clinical outcome. Cell Stem Cell. (2007 ) 1:555–67.
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198.
Kim R-J Park J-R Roh K-J Choi A-R Kim S-R Kim P-H. High aldehyde dehydrogenase activity enhances stem cell features in breast cancer cells by activating hypoxia-inducible factor-2α. Cancer Lett. (2013 ) 333:18–31.
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199.
Rodriguez-Torres M Allan AL. Aldehyde dehydrogenase as a marker and functional mediator of metastasis in solid tumors. Clin Exp Metastasis. (2016 ) 33:97–113.
Not in our library10.1007/s10585-015-9755-9 (opens in a new tab)
200.
Aldehyde dehydrogenase 1A1 in stem cells and cancer · 2016
No notice
201.
Liu P Kumar IS Brown S Kannappan V Tawari PE Tang JZ Disulfiram targets cancer stem-like cells and reverses resistance and cross-resistance in acquired paCLitaxel-resistant triple-negative breast cancer cells. Br J Cancer. (2013 ) 109:1876–85.
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202.
Matsunaga N Ogino T Hara Y Tanaka T Koyanagi S Ohdo S. Optimized dosing schedule based on circadian dynamics of mouse breast cancer stem cells improves the antitumor effects of aldehyde dehydrogenase inhibitor. Cancer Res. (2018 ) 78:3698–708.
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203.
Charafe-Jauffret E Ginestier C Iovino F Tarpin C Diebel M Esterni B. Aldehyde dehydrogenase 1-positive cancer stem cells mediate metastasis and poor Clinical outcome in inflammatory breast cancer. Clin Cancer Res. (2010 ) 16:45–55.
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204.
Liu Y Lv D-l Duan J-j Xu S-l Zhang J-f Yang X-j. ALDH1A1 expression correlates with CLinicopathologic features and poor prognosis of breast cancer patients: a systematic review and meta-analysis. BMC Cancer. (2014 ) 14:444.
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205.
Marcato P Dean CA Liu R-Z Coyle KM Bydoun M Wallace M. Aldehyde dehydrogenase 1A3 influences breast cancer progression via differential retinoic acid signaling. Mol Oncol. (2015 ) 9:17–31.
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206.
Khoury T Ademuyiwa FO Chandrasekhar R Chandraseekhar R Jabbour M Deleo A. Aldehyde dehydrogenase 1A1 expression in breast cancer is associated with stage, triple negativity, and outcome to neoadjuvant chemotherapy. Mod Pathol. (2012 ) 25:388–97.
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207.
Woodward WA Krishnamurthy S Lodhi A Xiao L Gong Y Cristofanilli M Aldehyde dehydrogenase1 immunohistochemical staining in primary breast cancer cells independently predicted overall survival but did not correlate with the presence of circulating or disseminated tumors cells. J Cancer. (2014 ) 5:360–7.
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208.
Zhong Y Shen S Zhou Y Mao F Guan J Lin Y. ALDH1 is a better clinical indicator for relapse of invasive ductal breast cancer than the CD44+/CD24- phenotype. Med Oncol. (2014 ) 31:864.
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209.
Tan EY Thike AA Tan PH. ALDH1 expression is enriched in breast cancers arising in young women but does not predict outcome. Br J Cancer. (2013 ) 109:109–13.
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210.
Collina F Di Bonito M Li Bergolis V Laurentiis M de Vitagliano C Cerrone M. Prognostic value of cancer stem cells markers in triple-negative breast cancer. Biomed Res Int. (2015 ) 2015:158682.
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211.
Srinivasan M Bharali DJ Sudha T Khedr M Guest I Sell S. Downregulation of BMI1 in breast cancer stem cells suppresses tumor growth and proliferation. Oncotarget. (2017 ) 8:38731–42.
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212.
Kim S-H Singh SV. The role of polycomb group protein BMI-1 and notch4 in breast cancer stem cell inhibition by benzyl isothiocyanate. Breast Cancer Res Treat. (2015 ) 149:681–92.
Not in our library10.1007/s10549-015-3279-5 (opens in a new tab)
213.
Yuan W Yuan Y Zhang T Wu S. Role of BMI-1 in regulation of ionizing irradiation-induced epithelial-mesenchymal transition and migration of breast cancer cells. PLoS ONE. (2015 ) 10:e0118799.
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214.
Yan Y Wang Y Zhao P Ma W Hu Z Zhang K. BMI-1 promotes self-Renewal of radio- and temozolomide (TMZ)-Resistant breast cancer cells. Reprod Sci. (2017 ) 24:1620–9.
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215.
Gong X-F Yu A-L Tang J Wang C-L He J-R Chen G-Q. MicroRNA-630 inhibits breast cancer progression by directly targeting BMI1. Exp Cell Res. (2018 ) 362:378–85.
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216.
Griffith J Andrade D Mehta M Berry W Benbrook DM Aravindan N. Silencing BMI1 radiosensitizes human breast cancer cells by inducing DNA damage and autophagy. Oncol Rep. (2017 ) 37:2382–90.
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217.
Ojo D Lin X Wu Y Cockburn J Bane A Tang D. Polycomb complex protein BMI1 confers resistance to tamoxifen in estrogen receptor positive breast cancer. Cancer Lett. (2018 ) 426:4–13.
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218.
Elango R Vishnubalaji R Manikandan M Binhamdan SI Siyal A-A Alshawakir YA. Concurrent targeting of BMI1 and CDK4/6 abrogates tumor growth in vitro and in vivo. Sci. Rep. (2019 ) 9:13696.
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219.
Janaki Ramaiah M Vaishnave S. BMI1 and PTEN are key determinants of breast cancer therapy: a plausible therapeutic target in breast cancer. Gene. (2018 ) 678:302–11.
Not in our library10.1016/j.gene.2018.08.022 (opens in a new tab)
220.
Oct-4 and Nanog promote the epithelial-mesenchymal transition of breast cancer stem cells and are associated with poor prognosis in breast cancer patients · 2014
No notice
221.
Yang F Zhang J Yang H. OCT4, SOX2, and NANOG positive expression correlates with poor differentiation, advanced disease stages, and worse overall survival in HER2+ breast cancer patients. Onco Targets Ther. (2018 ) 11:7873–81.
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222.
D'Angelo RC Ouzounova M Davis A Choi D Tchuenkam SM Kim G. Notch reporter activity in breast cancer cell lines identifies a subset of cells with stem cell activity. Mol Cancer Ther. (2015 ) 14:779–87.
Not in our library10.1158/1535-7163.mct-14-0228 (opens in a new tab)
223.
Luminal Progenitors Restrict Their Lineage Potential during Mammary Gland Development · 2015
No notice
224.
Mamaeva V Niemi R Beck M Özliseli E Desai D Landor S. Inhibiting notch activity in breast cancer stem cells by glucose functionalized nanoparticles carrying γ-secretase inhibitors. Mol Ther. (2016 ) 24:926–36.
Not in our library10.1038/mt.2016.42 (opens in a new tab)
225.
Anjanappa M Hao Y Simpson ER Bhat-Nakshatri P Nelson JB Tersey SA. A system for detecting high impact-low frequency mutations in primary tumors and metastases. Oncogene. (2018 ) 37:185–96.
Not in our library10.1038/onc.2017.322 (opens in a new tab)
226.
Baker A Wyatt D Bocchetta M Li J Filipovic A Green A. Notch-1-PTEN-ERK1/2 signaling axis promotes hER2+ breast cancer cell proliferation and stem cell survival. Oncogene. (2018 ) 37:4489–504.
Not in our library10.1038/s41388-018-0251-y (opens in a new tab)
227.
Diluvio G Del Gaudio F Giuli MV Franciosa G Giuliani E Palermo R. NOTCH3 inactivation increases triple negative breast cancer sensitivity to gefitinib by promoting eGFR tyrosine dephosphorylation and its intracellular arrest. Oncogenesis. (2018 ) 7:42.
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228.
γ‐Secretase inhibitors in cancer clinical trials are pharmacologically and functionally distinct · 2017
No notice
229.
Sizemore GM Balakrishnan S Hammer AM Thies KA Trimboli AJ Wallace JA Stromal pTEN inhibits the expansion of mammary epithelial stem cells through jagged-1. Oncogene. (2017 ) 36:2297–308.
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230.
Bhola NE Jansen VM Koch JP Li H Formisano L Williams JA. Treatment of triple-Negative breast cancer with TORC1/2 inhibitors sustains a drug-Resistant and notch-dependent cancer stem cell population. Cancer Res. (2016 ) 76:440–52.
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231.
Leontovich AA Jalalirad M Salisbury JL Mills L Haddox C Schroeder M. NOTCH3 expression is linked to breast cancer seeding and distant metastasis. Breast Cancer Res. (2018 ) 20:105.
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232.
Dou X-W Liang Y-K Lin H-Y Wei X-L Zhang Y-Q Bai J-W. Notch3 maintains luminal phenotype and suppresses tumorigenesis and metastasis of breast cancer via trans-activating estrogen receptor-α. Theranostics. (2017 ) 7:4041–56.
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233.
Wieland E Rodriguez-Vita J Liebler SS Mogler C Moll I Herberich SE. Endothelial notch1 activity facilitates metastasis. Cancer Cell. (2017 ) 31:355–67.
Not in our library10.1016/j.ccell.2017.01.007 (opens in a new tab)
234.
Gu X Lu C He D Lu Y Jin J Liu D. Notch3 negatively regulates chemoresistance in breast cancers. Tumour Biol. (2016 ) 37.
Not in our library10.1007/s13277-016-5412-4 (opens in a new tab)
235.
Notch Signaling as a Regulator of the Tumor Immune Response: To Target or Not To Target? · 2018
Not checked
236.
Siddharth S Goutam K Das S Nayak A Nayak D Sethy C. Nectin-4 is a breast cancer stem cell marker that induces wNT/β-catenin signaling via pi3k/Akt axis. Int J Biochem Cell Biol. (2017 ) 89:85–94.
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237.
Jang G-B Hong I-S Kim R-J Lee S-Y Park S-J Lee E-S. Wnt/β-catenin small-molecule inhibitor CWP232228 preferentially inhibits the growth of breast cancer stem-like cells. Cancer Res. (2015 ) 75:1691–702.
Not in our library10.1158/0008-5472.can-14-2041 (opens in a new tab)
238.
Zhang C Li C He F Cai Y Yang H. Identification of CD44+CD24+ gastric cancer stem cells. J Cancer Res Clin Oncol. (2011 ) 137:1679–86.
Not in our library10.1007/s00432-011-1038-5 (opens in a new tab)
239.
Brungs D Aghmesheh M Vine KL Becker TM Carolan MG Ranson M. Gastric cancer stem cells: evidence, potential markers, and clinical implications. J Gastroenterol. (2016 ) 51:313–26.
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240.
Li K Dan Z Nie Y-Q. Gastric cancer stem cells in gastric carcinogenesis, progression, prevention and treatment. World J Gastroenterol. (2014 ) 20:5420–6.
Not in our library10.3748/wjg.v20.i18.5420 (opens in a new tab)
241.
Jiao X-L Zhao C Niu M Chen D. Downregulation of CD24 inhibits invasive growth, facilitates apoptosis and enhances chemosensitivity in gastric cancer AGS cells. Eur Rev Med Pharmacol Sci. (2013 ) 17:1709–15.
Not in our library
242.
Fujikuni N Yamamoto H Tanabe K Naito Y Sakamoto N Tanaka Y. Hypoxia-mediated CD24 expression is correlated with gastric cancer aggressiveness by promoting cell migration and invasion. Cancer Sci. (2014 ) 105:1411–20.
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243.
Wu J-X Zhao Y-Y Wu X An H-X. CLinicopathological and prognostic significance of CD24 overexpression in patients with gastric cancer: a meta-analysis. PLoS ONE. (2014 ) 9:e114746.
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244.
Zhao H Wen J Dong X He R Gao C Zhang W. Identification of AQP3 and CD24 as biomarkers for carcinogenesis of gastric intestinal metaplasia. Oncotarget. (2017 ) 8:63382–91.
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245.
Fu Y Du P Zhao J Hu C'e Qin Y Huang G. Gastric cancer stem cells: mechanisms and therapeutic approaches. Yonsei Med J. (2018 ) 59:1150–8.
Not in our library10.3349/ymj.2018.59.10.1150 (opens in a new tab)
246.
Takaishi S Okumura T Tu S Wang SS Shibata W Vigneshwaran R. Identification of gastric cancer stem cells using the cell surface marker CD44. Stem Cells. (2009 ) 27:1006–20.
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247.
Zhang X Hua R Wang X Huang M Gan L Wu Z. Identification of stem-like cells and clinical significance of candidate stem cell markers in gastric cancer. Oncotarget. (2016 ) 7:9815–31.
Not in our library10.18632/oncotarget.6890 (opens in a new tab)
248.
Lau WM Teng E Chong HS Lopez KA Tay AY Salto-Tellez M. CD44v8-10 is a cancer-specific marker for gastric cancer stem cells. Cancer Res. (2014 ) 74:2630–41.
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249.
Nguyen PH Giraud J Chambonnier L Dubus P Wittkop L Belleannée G. Characterization of biomarkers of tumorigenic and chemoresistant cancer stem cells in human gastric carcinoma. Clin Cancer Res. (2017 ) 23:1586–97.
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250.
Nosrati A Naghshvar F Khanari S. Cancer stem cell markers CD44, CD133 in primary gastric adenocarcinoma. Int J Mol Cell Med. (2014 ) 3:279–86.
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251.
Shu X Liu H Pan Y Sun L Yu L Sun L. Distinct biological characterization of the CD44 and CD90 phenotypes of cancer stem cells in gastric cancer cell lines. Mol Cell Biochem. (2019 ) 459:35–47.
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252.
Bekaii-Saab T El-Rayes B. Identifying and targeting cancer stem cells in the treatment of gastric cancer. Cancer. (2017 ) 123:1303–12.
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253.
Watanabe T Okumura T Hirano K Yamaguchi T Sekine S Nagata T. Circulating tumor cells expressing cancer stem cell marker CD44 as a diagnostic biomarker in patients with gastric cancer. Oncol Lett. (2017 ) 13:281–8.
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254.
Lu L Wu M Sun L Li W Fu W Zhang X. CLinicopathological and prognostic significance of cancer stem cell markers CD44 and CD133 in patients with gastric cancer: a comprehensive meta-analysis with 4729 patients involved. Medicine. (2016 ) 95:e5163.
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255.
Jang E Kim E Son H-Y Lim E-K Lee H Choi Y. Nanovesicle-mediated systemic delivery of microRNA-34a for CD44 overexpressing gastric cancer stem cell therapy. Biomaterials. (2016 ) 105:12–24.
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267.
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Kim BH Park J-W Kim JS Lee S-K Hong EK. Stem cell markers predict the response to sorafenib in patients with hepatocellular carcinoma. Gut Liver. (2019 ) 13:342–8.
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307.
Zhang K Che S Su Z Zheng S Zhang H Yang S. CD90 promotes cell migration, viability and sphere-forming ability of hepatocellular carcinoma cells. Int J Mol Med. (2018 ) 41:946–54.
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Zhao RC Zhou J Chen KF Gong J Liu J He JY. The prognostic value of combination of CD90 and OCT4 for hepatocellular carcinoma after curative resection. Neoplasma. (2016 ) 63:288–98.
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312.
Liu K Hao M Ouyang Y Zheng J Chen D. CD133+ cancer stem cells promoted by VEGF accelerate the recurrence of hepatocellular carcinoma. Sci. Rep. (2017 ) 7:41499.
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313.
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314.
Jun SY Jeon S-J Yoon J-Y Lee J-J Yoon HR Choi M-H. The positive correlation of TIPRL with lC3 and CD133 contributes to cancer aggressiveness: potential biomarkers for early liver cancer. Sci. Rep. (2019 ) 9:16802.
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315.
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316.
Chen D Li Z Cheng Q Wang Y Qian L Gao J. Genetic alterations and expression of PTEN and its relationship with cancer stem cell markers to investigate pathogenesis and to evaluate prognosis in hepatocellular carcinoma. J Clin Pathol. (2019 ) 72:588–96.
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317.
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Su R Nan H Guo H Ruan Z Jiang L Song Y. Associations of components of PTEN/AKT/mTOR pathway with cancer stem cell markers and prognostic value of these biomarkers in hepatocellular carcinoma. Hepatol Res. (2016 ) 46:1380–91.
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Yu G-F Lin X Luo R-C Fang W-Y. Nuclear CD133 expression predicts poor prognosis for hepatocellular carcinoma. Int J Clin Exp Pathol. (2018 ) 11:2092–9.
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326.
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Zhou L Zhu Y. The EpCAM overexpression is associated with Clinicopathological significance and prognosis in hepatocellular carcinoma patients: a systematic review and meta-analysis. Int J Surg. (2018 ) 56:274–80.
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328.
Zhu M Li W Lu Y Dong X Chen Y Lin B. Alpha fetoprotein antagonizes apoptosis induced by paclitaxel in hepatoma cells in vitro. Sci. Rep. (2016 ) 6:26472.
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329.
Jin J Niu X Zou L Li L Li S Han J. AFP mRNA level in enriched circulating tumor cells from hepatocellular carcinoma patient blood samples is a pivotal predictive marker for metastasis. Cancer Lett. (2016 ) 378:33–7.
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330.
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Chang T-S Wu Y-C Chi C-C Su W-C Chang P-J Lee K-F. Activation of IL6/IGFIR confers poor prognosis of HBV-related hepatocellular carcinoma through induction of OCT4/NANOG expression. Clin Cancer Res. (2015 ) 21:201–10.
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332.
Was H Czarnecka J Kominek A Barszcz K BeRNAs T Piwocka K. Some chemotherapeutics-treated colon cancer cells display a specific phenotype being a combination of stem-like and senescent cell features. Cancer Biol Ther. (2018 ) 19:63–75.
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333.
Manhas J Bhattacharya A Agrawal SK Gupta B Das P Deo SV. Characterization of cancer stem cells from different grades of human colorectal cancer. Tumour Biol. (2016 ) 37:14069–81.
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335.
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337.
Lee SY Kim KA Kim CH Kim YJ Lee J-H Kim HR. CD44-shRNA recombinant adenovirus inhibits cell proliferation, invasion, and migration, and promotes apoptosis in HCT116 colon cancer cells. Int J Oncol. (2017 ) 50:329–36.
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338.
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342.
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344.
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AlShamaileh H Wang T Xiang D Yin W Tran PH-L Barrero RA. Aptamer-mediated survivin RNAi enables 5-fluorouracil to eliminate colorectal cancer stem cells. Sci Rep. (2017 ) 7:5898.
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346.
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349.
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Jiang Y Li W He X Zhang H Jiang F Chen Z. Lgr5 expression is a valuable prognostic factor for colorectal cancer: evidence from a meta-analysis. BMC Cancer. (2015 ) 15:948.
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355.
Vishnubalaji R Manikandan M Fahad M Hamam R Alfayez M Kassem M. Molecular profiling of ALDH1+ colorectal cancer stem cells reveals preferential activation of mAPK, FAK, and oxidative stress pro-survival signalling pathways. Oncotarget. (2018 ) 9:13551–64.
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356.
Kozovska Z Patsalias A Bajzik V Durinikova E Demkova L Jargasova S. ALDH1A inhibition sensitizes colon cancer cells to chemotherapy. BMC Cancer. (2018 ) 18:656.
Not in our library10.1186/s12885-018-4572-6 (opens in a new tab)
357.
Kahlert C Gaitzsch E Steinert G Mogler C Herpel E Hoffmeister M. Expression analysis of aldehyde dehydrogenase 1A1 (ALDH1A1) in colon and rectal cancer in association with prognosis and response to chemotherapy. Ann Surg Oncol. (2012 ) 19:4193–201.
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358.
Piao L Feng Y Yang Z Qi W Li H Han H. LETM1 is a potential cancer stem-like cell marker and predicts poor prognosis in colorectal adenocarcinoma. Pathol Res Pract. (2019 ) 215:152437.
Not in our library10.1016/j.prp.2019.152437 (opens in a new tab)
359.
Yang L Ding C Tang W Yang T Liu M Wu H. INPP4B exerts a dual function in the stemness of colorectal cancer stem-like cells through regulating sox2 and nanog expression. Carcinogenesis. (2019 ) 41:78–90.
Not in our library10.1093/carcin/bgz110 (opens in a new tab)
360.
Yao C Su L Shan J Zhu C Liu L Liu C. IGF/STAT3/NANOG/Slug signaling axis simultaneously controls epithelial-Mesenchymal transition and stemness maintenance in colorectal cancer. Stem Cells. (2016 ) 34:820–31.
Not in our library10.1002/stem.2320 (opens in a new tab)
361.
Wang H Liu B Wang J Li J Gong Y Li S. Reduction of NANOG mediates the inhibitory effect of aspirin on tumor growth and stemness in colorectal cancer. Cell Physiol Biochem. (2017 ) 44:1051–63.
Not in our library10.1159/000485405 (opens in a new tab)
362.
Xu F Dai C Zhang R Zhao Y Peng S Jia C. Nanog: a potential biomarker for liver metastasis of colorectal cancer. Dig Dis Sci. (2012 ) 57:2340–6.
Not in our library10.1007/s10620-012-2182-8 (opens in a new tab)
363.
Fujino S Miyoshi N. Oct4 gene expression in primary colorectal cancer promotes liver metastasis. Stem Cells Int. (2019 ) 2019:7896524.
Not in our library10.1155/2019/7896524 (opens in a new tab)
364.
Lee JH Yun CW Han Y-S Kim S Jeong D Kwon HY. Melatonin and 5-fluorouracil co-suppress colon cancer stem cells by regulating cellular prion protein-Oct4 axis. J Pineal Res. (2018 ) 65:e12519.
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365.
Miyoshi N Fujino S Ohue M Yasui M Takahashi Y Sugimura K. The POU5F1 gene expression in colorectal cancer: a novel prognostic marker. Surg Today. (2018 ) 48:709–15.
Not in our library10.1007/s00595-018-1644-9 (opens in a new tab)
366.
Ardalan Khales S Abbaszadegan MR Abdollahi A Raeisossadati R Tousi MF Forghanifard MM. SALL4 as a new biomarker for early colorectal cancers. J Cancer Res Clin Oncol. (2015 ) 141:229–35.
Not in our library10.1007/s00432-014-1808-y (opens in a new tab)
367.
Lundberg IV Edin S Eklöf V Öberg Å Palmqvist R Wikberg ML. SOX2 expression is associated with a cancer stem cell state and down-regulation of CDX2 in colorectal cancer. BMC Cancer. (2016 ) 16:471.
Not in our library10.1186/s12885-016-2509-5 (opens in a new tab)
368.
Takeda K Mizushima T Yokoyama Y Hirose H Wu X Qian Y. Sox2 is associated with cancer stem-like properties in colorectal cancer. Sci Rep. (2018 ) 8:17639.
Not in our library10.1038/s41598-018-36251-0 (opens in a new tab)
369.
Miller TJ McCoy MJ Hemmings C Bulsara MK Iacopetta B Platell CF. The prognostic value of cancer stem-like cell markers SOX2 and CD133 in stage iII colon cancer is modified by expression of the immune-related markers FoxP3, PD-L1 and CD3. Pathology. (2017 ) 49:721–30.
Not in our library10.1016/j.pathol.2017.08.007 (opens in a new tab)
370.
Coexpression profile of leukemic stem cell markers for combinatorial targeted therapy in AML · 2018
No notice
371.
Zhang CC Yan Z Pascual B Jackson-Fisher A Huang DS Zong Q. Gemtuzumab ozogamicin (GO) inclusion to induction chemotherapy eliminates leukemic initiating cells and significantly improves survival in mouse models of acute myeloid leukemia. Neoplasia. (2018 ) 20:1–11.
Not in our library10.1016/j.neo.2017.10.008 (opens in a new tab)
372.
Tang X Yang L Li Z Nalin AP Dai H Xu T First-in-man clinical trial of CAR NK-92 cells: safety test of CD33-CAR NK-92 cells in patients with relapsed and refractory acute myeloid leukemia. Am J Cancer Res. (2018 ) 8:1083–9.
Not in our library
373.
Braciak TA Roskopf CC Wildenhain S Fenn NC Schiller CB Schubert IA. Dual-targeting triplebody 33-16-123 (SPM-2) mediates effective redirected lysis of primary blasts from patients with a broad range of AML subtypes in combination with natural killer cells. Oncoimmunology. (2018 ) 7:e1472195.
Not in our library10.1080/2162402x.2018.1472195 (opens in a new tab)
374.
Petrov JC Wada M Pinz KG Yan LE Chen KH Shuai X. Compound CAR T-cells as a double-pronged approach for treating acute myeloid leukemia. Leukemia. (2018 ) 32:1317–26.
Not in our library10.1038/s41375-018-0075-3 (opens in a new tab)
375.
Switching CAR T cells on and off: a novel modular platform for retargeting of T cells to AML blasts · 2016
No notice
376.
Pizzitola I Anjos-Afonso F Rouault-Pierre K Lassailly F Tettamanti S Spinelli O. Chimeric antigen receptors against CD33/CD123 antigens efficiently target primary acute myeloid leukemia cells in vivo. Leukemia. (2014 ) 28:1596–605.
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377.
Vallera DA Felices M McElmurry R McCullar V Zhou X Schmohl JU. IL15 trispecific killer engagers (Trike) make natural killer cells specific to CD33+ targets while also inducing persistence, in vivo expansion, and enhanced function. Clin Cancer Res. (2016 ) 22:3440–50.
Not in our library10.1158/1078-0432.ccr-15-2710 (opens in a new tab)
378.
Hoseini SS Guo H Wu Z Hatano MN Cheung N-KV. A potent tetravalent t-cell-engaging bispecific antibody against CD33 in acute myeloid leukemia. Blood Adv. (2018 ) 2:1250–8.
Not in our library10.1182/bloodadvances.2017014373 (opens in a new tab)
379.
Kovtun Y Noordhuis P Whiteman KR Watkins K Jones GE Harvey L. IMGN779, a novel CD33-Targeting antibody–drug conjugate with DNA-Alkylating activity, exhibits potent antitumor activity in models of AML. Mol Cancer Ther. (2018 ) 17:1271–9.
Not in our library10.1158/1535-7163.mct-17-1077 (opens in a new tab)
380.
Vasu S He S Cheney C Gopalakrishnan B Mani R Lozanski G. Decitabine enhances anti-CD33 monoclonal antibody BI 836858-mediated natural killer ADCC against AML blasts. Blood. (2016 ) 127:2879–89.
Not in our library10.1182/blood-2015-11-680546 (opens in a new tab)
381.
Kloess S Ede Valverde da Silva A Oberschmidt O Gardlowski T Matthies N Vyas M. Triplebody mediates increased anti-Leukemic reactivity of IL-2 activated donor natural killer (NK) cells and impairs viability of their CD33-expressing NK subset. Front Immunol. (2017 ) 8:1100.
Not in our library10.3389/fimmu.2017.01100 (opens in a new tab)
382.
Schneider D Xiong Y Hu P Wu D Chen W Ying T. A unique human immunoglobulin heavy chain variable domain-only CD33 CAR for the treatment of acute myeloid leukemia. Front. Oncol. (2018 ) 8:539.
Not in our library10.3389/fonc.2018.00539 (opens in a new tab)
383.
Kenderian SS Ruella M Shestova O Klichinsky M Aikawa V Morrissette JJ. CD33-specific chimeric antigen receptor T cells exhibit potent preClinical activity against human acute myeloid leukemia. Leukemia. (2015 ) 29:1637–47.
Not in our library10.1038/leu.2015.52 (opens in a new tab)
384.
Hills RK Castaigne S Appelbaum FR Delaunay J Petersdorf S Othus M. Addition of gemtuzumab ozogamicin to induction chemotherapy in adult patients with acute myeloid leukaemia: a meta-analysis of individual patient data from randomised controlled trials. Lancet Oncol. (2014 ) 15:986–96.
Not in our library10.1016/s1470-2045(14)70281-5 (opens in a new tab)
385.
Gamis AS Alonzo TA Meshinchi S Sung L Gerbing RB Raimondi SC. Gemtuzumab ozogamicin in children and adolescents with de novo acute myeloid leukemia improves event-free survival by reducing relapse risk: results from the randomized phase iII children's oncology group trial AAML0531. JCO. (2014 ) 32:3021–32.
Not in our library10.1200/jco.2014.55.3628 (opens in a new tab)
386.
Stein EM Walter RB Erba HP Fathi AT Advani AS Lancet JE. A phase 1 trial of vadastuximab talirine as monotherapy in patients with CD33-positive acute myeloid leukemia. Blood. (2018 ) 131:387–96.
Not in our library10.1182/blood-2017-06-789800 (opens in a new tab)
387.
Wang Q-S Wang Y Lv H-Y Han Q-W Fan H Guo B. Treatment of CD33-directed chimeric antigen receptor-modified T cells in one patient with relapsed and refractory acute myeloid leukemia. Mol Ther. (2015 ) 23:184–91.
Not in our library10.1038/mt.2014.164 (opens in a new tab)
388.
Zahler S Bhatia M Ricci A Roy S Morris E Harrison L. A phase I Study of reduced-Intensity conditioning and allogeneic stem cell transplantation followed by dose escalation of targeted consolidation immunotherapy with gemtuzumab ozogamicin in children and adolescents with CD33+ acute myeloid leukemia. Biol Blood Marrow Transpl. (2016 ) 22:698–704.
Not in our library10.1016/j.bbmt.2016.01.019 (opens in a new tab)
389.
Niktoreh N Lerius B Zimmermann M Gruhn B Escherich G Bourquin J-P. Gemtuzumab ozogamicin in children with relapsed or refractory acute myeloid leukemia: a report by Berlin-Frankfurt-Münster study group. Haematologica. (2019 ) 104:120–7.
Not in our library10.3324/haematol.2018.191841 (opens in a new tab)
390.
Tarlock K Alonzo TA Gerbing RB Raimondi SC Hirsch BA Sung L. Gemtuzumab ozogamicin reduces relapse risk in FLT3/ITD acute myeloid leukemia: a report from the children's oncology group. Clin Cancer Res. (2016 ) 22:1951–7.
Not in our library10.1158/1078-0432.ccr-15-1349 (opens in a new tab)
391.
Amadori S Suciu S Selleslag D Aversa F Gaidano G Musso M. Gemtuzumab ozogamicin versus best supportive care in older patients with newly diagnosed acute myeloid leukemia unsuitable for intensive chemotherapy: results of the randomized phase III EORTC-GIMEMA AML-19 trial. J Clin Oncol. (2016 ) 34:972–9.
Not in our library10.1200/jco.2015.64.0060 (opens in a new tab)
392.
Portwood S Puchalski RA Walker RM Wang ES Combining IMGN779, a novel anti-CD33 antibody-drug conjugate (ADC), with the pARP inhibitor, olaparib, results in enhanced anti-Tumor activity in preclinical acute myeloid leukemia (AML) models. Blood. (2016 ) 128:1645
Not in our library10.1182/blood.v128.22.1645.1645 (opens in a new tab)
393.
Pollard JA Loken M Gerbing RB Raimondi SC Hirsch BA Aplenc R. CD33 expression and its association with gemtuzumab ozogamicin response: results from the randomized phase III children's oncology group trial AAML0531. J Clin Oncol. (2016 ) 34:747–55.
Not in our library10.1200/jco.2015.62.6846 (opens in a new tab)
394.
Yabushita T Satake H Maruoka H Morita M Katoh D Shimomura Y. Expression of multiple leukemic stem cell markers is associated with poor prognosis in de novo acute myeloid leukemia. Leuk Lymphoma. (2018 ) 59:2144–51.
Not in our library10.1080/10428194.2017.1410888 (opens in a new tab)
395.
Immunoprofiling of leukemic stem cells CD34+/CD38−/CD123+ delineate FLT3/ITD-positive clones · 2016
Not checked
396.
Jordan CT Upchurch D Szilvassy SJ Guzman ML Howard DS Pettigrew AL. The interleukin-3 receptor alpha chain is a unique marker for human acute myelogenous leukemia stem cells. Leukemia. (2000 ) 14:1777–84.
Not in our library10.1038/sj.leu.2401903 (opens in a new tab)
397.
Xie LH Biondo M Busfield SJ Arruda A Yang X Vairo G. CD123 target validation and preClinical evaluation of ADCC activity of anti-CD123 antibody CSL362 in combination with NKs from AML patients in remission. Blood Cancer J. (2017 ) 7:e567.
Not in our library10.1038/bcj.2017.52 (opens in a new tab)
398.
Bras AE Haas V de van Stigt A Jongen-Lavrencic M Beverloo HB Te Marvelde JG. CD123 expression levels in 846 acute leukemia patients based on standardized immunophenotyping. Cytometry B Clin Cytom. (2019 ) 96:134–42.
Not in our library10.1002/cyto.b.21745 (opens in a new tab)
399.
Arai N Homma M Abe M Baba Y Murai S Watanuki M. Impact of CD123 expression, analyzed by immunohistochemistry, on Clinical outcomes in patients with acute myeloid leukemia. Int J Hematol. (2019 ) 109:539–44.
Not in our library10.1007/s12185-019-02616-y (opens in a new tab)
400.
Bonifant CL Szoor A Torres D Joseph N Velasquez MP Iwahori K. CD123-engager T cells as a novel immunotherapeutic for acute myeloid leukemia. Mol Ther. (2016 ) 24:1615–26.
Not in our library10.1038/mt.2016.116 (opens in a new tab)
401.
Li F Sutherland MK Yu C Walter RB Westendorf L Valliere-Douglass J. Characterization of SGN-CD123A, a potent CD123-directed antibody-drug conjugate for acute myeloid leukemia. Mol Cancer Ther. (2018 ) 17:554–64.
Not in our library10.1158/1535-7163.mct-17-0742 (opens in a new tab)
402.
Kovtun Y Jones GE Adams S Harvey L Audette CA Wilhelm A. A CD123-targeting antibody-drug conjugate, IMGN632, designed to eradicate AML while sparing normal bone marrow cells. Blood Adv. (2018 ) 2:848–58.
Not in our library10.1182/bloodadvances.2018017517 (opens in a new tab)
403.
Han L Jorgensen JL Brooks C Shi C Zhang Q Nogueras González GM. Antileukemia efficacy and mechanisms of action of SL-101, a novel anti-CD123 antibody conjugate, in acute myeloid leukemia. Clin Cancer Res. (2017 ) 23:3385–95.
Not in our library10.1158/1078-0432.ccr-16-1904 (opens in a new tab)
404.
Fan D Li Z Zhang X Yang Y Yuan X Zhang X. AntiCD3Fv fused to human interleukin-3 deletion variant redirected T cells against human acute myeloid leukemic stem cells. J Hematol Oncol. (2015 ) 8:18.
Not in our library10.1186/s13045-015-0109-5 (opens in a new tab)
405.
Busfield SJ Biondo M Wong M Ramshaw HS Lee EM Ghosh S. Targeting of acute myeloid leukemia in vitro and in vivo with an anti-CD123 mAb engineered for optimal ADCC. Leukemia. (2014 ) 28:2213–21.
Not in our library10.1038/leu.2014.128 (opens in a new tab)
406.
Williams BA Wang X-H Leyton JV Maghera S Deif B Reilly RM. CD16+NK-92 and anti-CD123 monoclonal antibody prolongs survival in primary human acute myeloid leukemia xenografted mice. Haematologica. (2018 ) 103:1720–9.
Not in our library10.3324/haematol.2017.187385 (opens in a new tab)
407.
Hutmacher C Volta L Rinaldi F Murer P Myburgh R Manz MG. Development of a novel fully-human anti-CD123 antibody to target acute myeloid leukemia. Leuk Res. (2019 ) 84:106178.
Not in our library10.1016/j.leukres.2019.106178 (opens in a new tab)
408.
Thokala R Olivares S Mi T Maiti S Deniger D Huls H. Redirecting specificity of t cells using the sleeping beauty system to express chimeric antigen receptors by mix-and-matching of VL and VH domains targeting CD123+ tumors. PLoS ONE. (2016 ) 11:e0159477.
Not in our library10.1371/journal.pone.0159477 (opens in a new tab)
409.
Oberschmidt O Morgan M Huppert V Kessler J Gardlowski T Matthies N. Development of automated separation, expansion, and quality control protocols for clinical-scale manufacturing of primary human NK cells and alpharetroviral chimeric antigen receptor engineering. Hum Gene Ther Methods. (2019 ) 30:102–20.
Not in our library10.1089/hgtb.2019.039 (opens in a new tab)
410.
Tasian SK Kenderian SS Shen F Ruella M Shestova O Kozlowski M. Optimized depletion of chimeric antigen receptor T cells in murine xenograft models of human acute myeloid leukemia. Blood. (2017 ) 129:2395–407.
Not in our library10.1182/blood-2016-08-736041 (opens in a new tab)
411.
He SZ Busfield S Ritchie DS Hertzberg MS Durrant S Lewis ID A phase 1 study of the safety, pharmacokinetics and anti-leukemic activity of the anti-CD123 monoclonal antibody CSL360 in relapsed, refractory or high-risk acute myeloid leukemia. Leuk Lymphoma. (2015 ) 56:1406–15.
Not in our library10.3109/10428194.2014.956316 (opens in a new tab)
412.
Al-Hussaini M Rettig MP Ritchey JK Karpova D Uy GL Eissenberg LG. Targeting CD123 in acute myeloid leukemia using a T-cell-directed dual-affinity retargeting platform. Blood. (2016 ) 127:122–31.
Not in our library10.1182/blood-2014-05-575704 (opens in a new tab)
413.
Zahran AM Aly SS Rayan A El-Badawy O Fattah MA Ali AM. Survival outcomes of CD34+CD38-LSCs and their expression of CD123 in adult AML patients. Oncotarget. (2018 ) 9:34056–65.
Not in our library10.18632/oncotarget.26118 (opens in a new tab)
414.
Jiang Y-P Liu BY Zheng Q Panuganti S Chen R Zhu J. CLT030, a leukemic stem cell-targeting CLL1 antibody-drug conjugate for treatment of acute myeloid leukemia. Blood Adv. (2018 ) 2:1738–49.
Not in our library10.1182/bloodadvances.2018020107 (opens in a new tab)
415.
van Rhenen A van Dongen GA Kelder A Rombouts EJ Feller N Moshaver B. The novel AML stem cell associated antigen CLL-1 aids in discrimination between normal and leukemic stem cells. Blood. (2007 ) 110:2659–66.
Not in our library10.1182/blood-2007-03-083048 (opens in a new tab)
416.
Bill M Aggerholm A Kjeldsen E Roug AS Hokland P Nederby L. Revisiting CLEC12A as leukaemic stem cell marker in AML: highlighting the necessity of precision diagnostics in patients eligible for targeted therapy. Br J Haematol. (2019 ) 184:769–81.
Not in our library10.1111/bjh.15711 (opens in a new tab)
417.
Leong SR Sukumaran S Hristopoulos M Totpal K Stainton S Lu E. An anti-CD3/anti–CLL-1 bispecific antibody for the treatment of acute myeloid leukemia. Blood. (2017 ) 129:609–18.
Not in our library10.1182/blood-2016-08-735365 (opens in a new tab)
418.
Lin TY Zhu Y Li Y Zhang H Ma AH Long Q. Daunorubicin-containing CLL1-targeting nanomicelles have anti-leukemia stem cell activity in acute myeloid leukemia. Nanomedicine. (2019 ) 20:102004.
Not in our library10.1016/j.nano.2019.04.007 (opens in a new tab)
419.
Kenderian SS Ruella M Shestova O Klichinsky M Kim M Soderquist C Targeting CLEC12A with chimeric antigen receptor T Cells can overcome the chemotherapy refractoriness of leukemia stem cells. Biol. Blood Marrow Transpl. (2017 ) 23:S247–8.
Not in our library10.1016/j.bbmt.2016.12.413 (opens in a new tab)
420.
Darwish NHE Sudha T Godugu K Elbaz O Abdelghaffar HA Hassan EEA. Acute myeloid leukemia stem cell markers in prognosis and targeted therapy: potential impact of BMI-1, TIM-3 and CLL-1. Oncotarget. (2016 ) 7:57811–20.
Not in our library10.18632/oncotarget.11063 (opens in a new tab)
421.
Kikushige Y Shima T Takayanagi S-i Urata S Miyamoto T Iwasaki H. TIM-3 is a promising target to selectively kill acute myeloid leukemia stem cells. Cell Stem Cell. (2010 ) 7:708–17.
Not in our library10.1016/j.stem.2010.11.014 (opens in a new tab)
422.
Homayouni V Ganjalikhani-hakemi M Rezaei A Khanahmad H Behdani M Lomedasht FK. Preparation and characterization of a novel nanobody against T-cell immunoglobulin and mucin-3 (TIM-3). Iran J Basic Med Sci. (2016 ) 19:1201–8.
Not in our library10.15171/ijb.1427 (opens in a new tab)
423.
Gal9/Tim-3 expression level is higher in AML patients who fail chemotherapy · 2019
Not checked
424.
van Hoang T Buss EC Wang W Hoffmann I Raffel S Zepeda-Moreno A. The rarity of ALDH(+) cells is the key to separation of normal versus leukemia stem cells by ALDH activity in AML patients. Int J Cancer. (2015 ) 137:525–36.
Not in our library10.1002/ijc.29410 (opens in a new tab)
425.
Blume R Rempel E Manta L Saeed BR Wang W Raffel S. The molecular signature of AML with increased ALDH activity suggests a stem cell origin. Leuk Lymphoma. (2018 ) 59:2201–10.
Not in our library10.1080/10428194.2017.1422862 (opens in a new tab)
426.
Voeltzel T Flores-Violante M Zylbersztejn F Lefort S Billandon M Jeanpierre S. A new signaling cascade linking BMP4, BMPR1A, ΔNp73 and NANOG impacts on stem-like human cell properties and patient outcome. Cell Death Dis. (2018 ) 9:1011.
Not in our library10.1038/s41419-018-1042-7 (opens in a new tab)
427.
Kakiuchi S Minami Y Miyata Y Mizutani Y Goto H Kawamoto S. NANOG expression as a responsive biomarker during treatment with hedgehog signal inhibitor in acute myeloid leukemia. Int J Mol Sci. (2017 ) 18:486.
Not in our library10.3390/ijms18030486 (opens in a new tab)
428.
Picot T Kesr S Wu Y Aanei CM Flandrin-Gresta P Tondeur S. Potential role of OCT4 in leukemogenesis. Stem Cells Dev. (2017 ) 26:1637–47.
Not in our library10.1089/scd.2017.0134 (opens in a new tab)
429.
Yin J-Y Tang Q Zhai L-L Zhou L-Y Qian J Lin J. High expression of OCT4 is frequent and may cause undesirable treatment outcomes in patients with acute myeloid leukemia. Tumour Biol. (2015 ) 36:9711–6.
Not in our library10.1007/s13277-015-3731-5 (opens in a new tab)
430.
Xiang Y Zhou X. Octamer-binding transcription factor 4 correlates with complex karyotype, fLT3-ITD mutation and poorer risk stratification, and predicts unfavourable prognosis in patients with acute myeloid leukaemia. Hematology. (2018 ) 23:721–8.
Not in our library10.1080/10245332.2018.1482050 (opens in a new tab)
431.
Zhang L-Y Yuan Y-Q Zhou D-M Wang Z-Y Ju S-G Sun Y Impact of global and gene-specific DNA methylation in de novo or relapsed acute myeloid leukemia patients treated with decitabine. Asian Pac J Cancer Prev. (2016 ) 17:431–7.
Not in our library10.7314/apjcp.2016.17.1.431 (opens in a new tab)
432.
Tosic N Petrovic I Grujicic NK Davidovic S Virijevic M Vukovic NS. Prognostic significance of SOX2, SOX3, SOX11, SOX14 and SOX18 gene expression in adult de novo acute myeloid leukemia. Leuk Res. (2018 ) 67:32–8.
Not in our library10.1016/j.leukres.2018.02.001 (opens in a new tab)
433.
Sadovnik I Hoelbl-Kovacic A Herrmann H Eisenwort G Cerny-Reiterer S Warsch W. Identification of CD25 as STAT5-Dependent growth-Regulator of leukemic stem cells in PH+ CML. Clin Cancer Res. (2015 ) 22:2051–61.
Not in our library10.1158/1078-0432.ccr-15-0767 (opens in a new tab)
434.
Herrmann H Sadovnik I Cerny-Reiterer S Rülicke T Stefanzl G Willmann M. Dipeptidylpeptidase IV (CD26) defines leukemic stem cells (LSC) in chronic myeloid leukemia. Blood. (2014 ) 123:3951–62.
Not in our library10.1182/blood-2013-10-536078 (opens in a new tab)
435.
Landberg N Palffy S von Askmyr M Lilljebjörn H Sandén C Rissler M. CD36 defines primitive chronic myeloid leukemia cells less responsive to imatinib but vulnerable to antibody-based therapeutic targeting. Haematologica. (2018 ) 103:447–55.
Not in our library10.3324/haematol.2017.169946 (opens in a new tab)
436.
Warfvinge R Geironson L Sommarin MN Lang S Karlsson C Roschupkina T. Single-cell molecular analysis defines therapy response and immunophenotype of stem cell subpopulations in CML. Blood. (2017 ) 129:2384–94.
Not in our library10.1182/blood-2016-07-728873 (opens in a new tab)
437.
Landberg N Hansen N Askmyr M Ågerstam H Lassen C Rissler M. IL1RAP expression as a measure of leukemic stem cell burden at diagnosis of chronic myeloid leukemia predicts therapy outcome. Leukemia. (2016 ) 30:255–8.
Not in our library10.1038/leu.2015.135 (opens in a new tab)
438.
Chronic myeloid leukemia stem cells · 2019
No notice
439.
Sadovnik I Herrmann H Eisenwort G Blatt K Hoermann G Mueller N. Expression of CD25 on leukemic stem cells in BCR-ABL1+ CML: potential diagnostic value and functional implications. Exp Hematol. (2017 ) 51:17–24.
Not in our library10.1016/j.exphem.2017.04.003 (opens in a new tab)
440.
Valent P Sadovnik I Eisenwort G Bauer K Herrmann H Gleixner KV. Immunotherapy-Based targeting and elimination of leukemic stem cells in AML and CML. Int J Mol Sci. (2019 ) 20.
Not in our library10.3390/ijms20174233 (opens in a new tab)
441.
Madhumathi J Sridevi S Verma RS. CD25 targeted therapy of chemotherapy resistant leukemic stem cells using DR5 specific TRAIL peptide. Stem Cell Res. (2017 ) 19:65–75.
Not in our library10.1016/j.scr.2017.01.001 (opens in a new tab)
442.
Bocchia M Sicuranza A Abruzzese E Iurlo A Sirianni S Gozzini A. Residual peripheral blood CD26+ leukemic stem cells in chronic myeloid leukemia patients during TKI therapy and during treatment-free remission. Front. Oncol. (2018 ) 8:194.
Not in our library10.3389/fonc.2018.00194 (opens in a new tab)
443.
Culen M Borsky M Nemethova V Razga F Smejkal J Jurcek T. Quantitative assessment of the CD26+ leukemic stem cell compartment in chronic myeloid leukemia: patient-subgroups, prognostic impact, and technical aspects. Oncotarget. (2016 ) 7:33016–24.
Not in our library10.18632/oncotarget.9108 (opens in a new tab)
444.
Galimberti S Grassi S Baratè C Guerrini F Ciabatti E Perutelli F. The polycomb BMI1 protein is co-expressed with CD26+ in leukemic stem cells of chronic myeloid leukemia. Front. Oncol. (2018 ) 8:555.
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445.
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453.
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456.
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457.
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458.
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459.
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465.
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468.
First-in-human phase I clinical trial of RG7356, an anti-CD44 humanized antibody, in patients with advanced, CD44-expressing solid tumors · 2016
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469.
CD133: a stem cell biomarker and beyond · 2013
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470.
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478.
Heterogeneity and stochastic growth regulation of biliary epithelial cells dictate dynamic epithelial tissue remodeling · 2016
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479.
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485.
Wang Y-J Herlyn M. The emerging roles of Oct4 in tumor-initiating cells. Am J Physiol Cell Physiol. (2015 ) 309:C709–18.
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486.
Dai X Ge J Wang X Qian X Zhang C Li X. OCT4 regulates epithelial-mesenchymal transition and its knockdown inhibits colorectal cancer cell migration and invasion. Oncol Rep. (2013 ) 29:155–60.
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487.
Jeter CR Yang T Wang J Chao H-P Tang DG. Concise review: NANOG in cancer stem cells and tumor development: an update and outstanding questions. Stem Cells. (2015 ) 33:2381–90.
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488.
Quéré R Andradottir S Brun AC Zubarev RA Karlsson G Olsson K. High levels of the adhesion molecule CD44 on leukemic cells generate acute myeloid leukemia relapse after withdrawal of the initial transforming event. Leukemia. (2010 ) 25:515–26.
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489.
Wang N-S Wei M Ma W-l Meng W Zheng W-l. Knockdown of CD44 enhances chemosensitivity of acute myeloid leukemia cells to ADM Ara-C. Tumour Biol. (2014 ) 35:3933–40.
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490.
Huang X Li D Li T Zhao BO Chen X. Prognostic value of the expression of phosphatase and tensin homolog and CD44 in elderly patients with refractory acute myeloid leukemia. Oncol Lett. (2015 ) 10:103–10.
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491.
Zhou H-S Carter BZ Andreeff M. Bone marrow niche-mediated survival of leukemia stem cells in acute myeloid leukemia: Yin and Yang. Cancer Biol Med. (2016 ) 13:248–59.
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492.
CD123 as a Therapeutic Target in the Treatment of Hematological Malignancies · 2019
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493.
Pollyea DA Jordan CT. Therapeutic targeting of acute myeloid leukemia stem cells. Blood. (2017 ) 129:1627–35.
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494.
Wittwer NL Brumatti G Marchant C Sandow JJ Pudney MK Dottore M. High CD123 levels enhance proliferation in response to IL-3, but reduce chemotaxis by downregulating CXCR4 expression. Blood Adv. (2017 ) 1:1067–79.
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495.
Faez A Subh SA-M. Impact of leukemia stem cells phenotype expression on response to induction therapy in acute myeloid leukemia patients. Cardiovasc Hematol Disord Drug Targets. (2020 ) 20:145–151.
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496.
Zhou J Chng W-J. Identification and targeting leukemia stem cells: the path to the cure for acute myeloid leukemia. World J Stem Cells. (2014 ) 6:473–84.
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497.
Davis JR Benjamin DJ Jonas BA. New and emerging therapies for acute myeloid leukaemia. J Investig Med. (2018 ) 66:1088–95.
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498.
Kikushige Y Miyamoto T. Identification of TIM-3 as a leukemic stem cell surface molecule in primary acute myeloid leukemia. Oncology. (2015 ) 89(Suppl. 1):28–32.
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499.
Grainger S Traver D Willert K. Wnt signaling in hematological malignancies. Prog Mol Biol Transl Sci. (2018 ) 153:321–41.
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500.
Zhao Y Wu K Wu Y Melendez E Smbatyan G Massiello D Characterization of imatinib resistant CML leukemic stem/Initiating cells and their sensitivity to CBP/Catenin antagonists. Curr Mol Pharmacol. (2018 ) 11:113–21.
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501.
Blaudszun A-R Moldenhauer G Schneider M Philippi A. A photosensitizer delivered by bispecific antibody redirected T lymphocytes enhances cytotoxicity against EpCAM-expressing carcinoma cells upon light irradiation. J Control Release. (2015 ) 197:58–68.
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502.
Hosoya N Miyagawa K. Targeting DNA damage response in cancer therapy. Cancer Sci. (2014 ) 105:370–88.
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503.
Ruhland MK Coussens LM Stewart SA. Senescence and cancer: an evolving inflammatory paradox. Biochim Biophys Acta. (2016 ) 1865:14–22.
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504.
Ewald JA Desotelle JA Wilding G Jarrard DF. Therapy-induced senescence in cancer. J Natl Cancer Inst. (2010 ) 102:1536–46.
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505.
Hallmarks of senescence and aging · 2019
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506.
Lee S Lee J-S. Cellular senescence: a promising strategy for cancer therapy. BMB Rep. (2019 ) 52:35–41.
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507.
Chakradeo S Elmore LW Gewirtz DA. Is senescence reversible? Curr Drug Targets. (2016 ) 17:460–6.
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508.
Zhao H Darzynkiewicz Z. Biomarkers of cell senescence assessed by imaging cytometry. Methods Mol Biol. (2013 ) 965:83–92.
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509.
Aljabery F Shabo I Gimm O Jahnson S Olsson H. The expression profile of p14, p53 and p21 in tumour cells is associated with disease-specific survival and the outcome of postoperative chemotherapy treatment in muscle-invasive bladder cancer. Urol Oncol. (2018 ) 36:530.e7-530.e18.
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510.
Fallah M Mohammadi H Shaki F Hosseini-Khah Z Moloudizargari M Dashti A. Doxorubicin and liposomal doxorubicin induce senescence by enhancing nuclear factor kappa B and mitochondrial membrane potential. Life Sci. (2019 ) 232:116677.
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511.
Hayman L Chaudhry WR Revin VV Zhelev N Bourdon J-C. What is the potential of p53 isoforms as a predictive biomarker in the treatment of cancer? Expert Rev Mol Diagn. (2019 ) 19:149–59.
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512.
Moraes JK de Wagner VP Fonseca FP Amaral-Silva GK Farias CB de Pilar EF. Activation of BDNF/TrkB/Akt pathway is associated with aggressiveness and unfavorable survival in oral squamous cell carcinoma. Oral Dis. (2019 ) 25:1925–36.
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513.
Lin T Hou P-F Meng S Chen F Jiang T Li M-L. Emerging roles of p53 related lncRNAs in cancer progression: a systematic review. Int J Biol Sci. (2019 ) 15:1287–98.
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514.
van den Bossche J Deben C Pauw I de Lambrechts H Hermans C Deschoolmeester V. In vitro study of the polo-like kinase 1 inhibitor volasertib in non-small-cell lung cancer reveals a role for the tumor suppressor p53. Mol Oncol. (2019 ) 13:1196–213.
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515.
Zamorano-León JJ Ballesteros S las Heras N de Alvarez-Sala L La SeRNA-Soto M de Zekri-Nechar K. Effect of pectin on the expression of proteins associated with mitochondrial biogenesis and cell senescence in HT29-human colorectal adenocarcinoma cells. Prev Nutr Food Sci. (2019 ) 24:187–96.
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516.
Wagner J Damaschke N Yang B Truong M Guenther C McCormick J. Overexpression of the novel senescence marker β-Galactosidase (GLB1) in prostate cancer predicts reduced PSA recurrence. PLoS ONE. (2015 ) 10:e0124366.
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517.
Zhang R Chen W Adams PD. Molecular dissection of formation of senescence-Associated heterochromatin foci?†. Mol Cell Biol. (2007 ) 27:2343–58.
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518.
Markers of cellular senescence. Telomere shortening as a marker of cellular senescence · 2016
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519.
Hartman ML Sztiller-Sikorska M Czyz M. Whole-exome sequencing reveals novel genetic variants associated with diverse phenotypes of melanoma cells. Mol Carcinog. (2019 ) 58:588–602.
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520.
Long F He Y Fu H Li Y Bao X Wang Q. PreClinical characterization of SHR6390, a novel CDK 4/6 inhibitor, in vitro and in human tumor xenograft models. Cancer Sci. (2019 ) 110:1420–30.
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521.
Knutson KL CLynes R Shreeder B Yeramian P Kemp KP Ballman K. Improved survival of HER2+ breast cancer patients treated with trastuzumab and chemotherapy is associated with host antibody immunity against the HER2 intracellular domain. Cancer Res. (2016 ) 76:3702–10.
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522.
Gunaratna RT Santos A Luo L Nagi C Lambertz I Spier M. Dynamic role of the codon 72 p53 single-Nucleotide polymorphism in mammary tumorigenesis in a humanized mouse model. Oncogene. (2019 ) 38:3535–50.
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523.
Smolle E Fink-Neuboeck N Lindenmann J Smolle-Juettner F Pichler M. The biological and clinical relevance of inhibitor of growth (ING) genes in non-Small cell lung cancer. Cancers. (2019 ) 11.
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524.
Xiang X-H Yang L Zhang X Ma X-H Miao R-C Gu J-X. Seven-senescence-associated gene signature predicts overall survival for asian patients with hepatocellular carcinoma. World J Gastroenterol. (2019 ) 25:1715–28.
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525.
Eggert T Wolter K Ji J Ma C Yevsa T Klotz S. Distinct functions of senescence-associated immune responses in liver tumor surveillance and tumor progression. Cancer Cell. (2016 ) 30:533–47.
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526.
Coppé J-P Desprez P-Y Krtolica A Campisi J. The senescence-associated secretory phenotype: the dark side of tumor suppression. Annu Rev Pathol. (2010 ) 5:99–118.
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527.
Human Umbilical Cord Mesenchymal Stem Cells Promote Breast Cancer Metastasis by Interleukin-8- and Interleukin-6-Dependent Induction of CD44/CD24 Cells · 2015
Not checked
528.
Senescence-associated IL-6 and IL-8 cytokines induce a self- and cross-reinforced senescence/inflammatory milieu strengthening tumorigenic capabilities in the MCF-7 breast cancer cell line · 2017
No notice
529.
Yamaguchi N Nakayama Y Yamaguchi N. Down-regulation of forkhead box protein A1 (FOXA1) leads to cancer stem cell-like properties in tamoxifen-resistant breast cancer cells through induction of interleukin-6. J Biol Chem. (2017 ) 292:8136–48.
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530.
Peng D Tanikawa T Li W Zhao L Vatan L Szeliga W. Myeloid-Derived suppressor cells endow stem-like qualities to breast cancer cells through IL6/STAT3 and NO/NOTCH cross-talk signaling. Cancer Res. (2016 ) 76:3156–65.
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531.
Saha S Mukherjee S Khan P Kajal K Mazumdar M Manna A. Aspirin suppresses the acquisition of chemoresistance in breast cancer by disrupting an NFκB-IL6 signaling axis responsible for the generation of cancer stem cells. Cancer Res. (2016 ) 76:2000–12.
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532.
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533.
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534.
Gallo M Frezzetti D Roma C Chicchinelli N Barbieri A Arra C. RANTES and IL-6 cooperate in inducing a more aggressive phenotype in breast cancer cells. Oncotarget. (2018 ) 9:17543–53.
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535.
Yevsa T Kang T-W Zender L. Immune surveillance of pre-cancerous senescent hepatocytes limits hepatocellular carcinoma development. Oncoimmunology. (2012 ) 1:398–9.
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536.
Kang T-W Yevsa T Woller N Hoenicke L Wuestefeld T Dauch D. Senescence surveillance of pre-malignant hepatocytes limits liver cancer development. Nature. (2011 ) 479:547–51.
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537.
Was H Barszcz K Czarnecka J Kowalczyk A Bernas T Uzarowska E. Bafilomycin A1 triggers proliferative potential of senescent cancer cells in vitro and in NOD/SCID mice. Oncotarget. (2016 ) 8:9303–22.
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538.
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539.
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540.
Jabbour W Wion D. Biomarkers of aging associated with past treatments in breast cancer survivors: when therapy-induced pathways turn out to be potential therapeutic targets. NPJ Breast Cancer. (2018 ) 4:1–2.
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541.
Di G-H Liu Y Lu Y Liu J Wu C Duan H-F. IL-6 secreted from senescent mesenchymal stem cells promotes proliferation and migration of breast cancer cells. PLoS ONE. (2014 ) 9:e113572.
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542.
Marotta LL Almendro V Marusyk A Shipitsin M Schemme J Walker SR. The JAK2/STAT3 signaling pathway is required for growth of CD44+CD24− stem cell-like breast cancer cells in human tumors. J Clin Invest. (2011 ) 121:2723–35.
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543.
Wang T Song P Zhong T Wang X Xiang X Liu Q. The inflammatory cytokine IL-6 induces FRA1 deacetylation promoting colorectal cancer stem-like properties. Oncogene. (2019 ) 38:4932–47.
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544.
Dou Z Berger SL. Senescence elicits stemness: a surprising mechanism for cancer relapse. Cell Metab. (2018 ) 27:710–1.
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545.
The Role of the Extracellular Matrix and Its Molecular and Cellular Regulators in Cancer Cell Plasticity · 2018
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546.
Aloia L McKie MA Huch M. Cellular plasticity in the adult liver and stomach. J Physiol. (2016 ) 594:4815–25.
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547.
Chen Y Wong PP Sjeklocha L Steer CJ Sahin MB. Mature hepatocytes exhibit unexpected plasticity by direct dedifferentiation into liver progenitor cells in culture. Hepatology. (2012 ) 55:563–74.
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