No retraction, correction or concern found when last checked on Oct 19, 2026.
Tumor cell plasticity in targeted therapy-induced resistance: mechanisms and new strategies
Zhen-Duo Shi, Kun Pang, Zhuo-Xun Wu and 6 more (opens in a new tab)
Signal Transduction and Targeted Therapy · 2023 · Review · CC BY
doi:10.1038/s41392-023-01383-x (opens in a new tab)
Abstract
Despite the success of targeted therapies in cancer treatment, therapy-induced resistance remains a major obstacle to a complete cure. Tumor cells evade treatments and relapse via phenotypic switching driven by intrinsic or induced cell plasticity. Several reversible mechanisms have been proposed to circumvent tumor cell plasticity, including epigenetic modifications, regulation of transcription factors, activation or suppression of key signaling pathways, as well as modification of the tumor environment. Epithelial-to-mesenchymal transition, tumor cell and cancer stem cell formation also serve as roads towards tumor cell plasticity. Corresponding treatment strategies have recently been developed that either target plasticity-related mechanisms or employ combination treatments. In this review, we delineate the formation of tumor cell plasticity and its manipulation of tumor evasion from targeted therapy. We discuss the non-genetic mechanisms of targeted drug-induced tumor cell plasticity in various types of tumors and provide insights into the contribution of tumor cell plasticity to acquired drug resistance. New therapeutic strategies such as inhibition or reversal of tumor cell plasticity are also presented. We also discuss the multitude of clinical trials that are ongoing worldwide with the intention of improving clinical outcomes. These advances provide a direction for developing novel therapeutic strategies and combination therapy regimens that target tumor cell plasticity.
Full text
From PubMed Central, U.S. National Library of Medicine, as current on Oct 19, 2026. Paragraph numbers are ours, so an answer can point at one.
Introduction to tumor cell plasticity (TCP)
Cellular plasticity is a fundamental feature of cells. During development, cells progressively differentiate into different hierarchies and obtain specific developmental commitments. Such processes are reversible, and the phenotypic changes can be diversely directed as needed. Genetic lineage tracing has demonstrated that functionally mature cells can undergo dedifferentiation (lineage reversion), transdifferentiation (cells converting into other distant lineages), or transdetermination (cells switching lineage commitment to a closely related cell type) upon injury or disease., As far back as 1956, Conrad Waddington stated that during development embryonic progenitor cells progressively differentiate into distinct cell types and are increasingly restricted within a specific lineage. The final specialized cells are then integrated into their respective tissues and conduct their specific invariable functions. However, later studies subverted this paradigm. Han Driesch isolated from a sea urchin embryo a single blastomere in an early multicellular state could develop into an entire larva. This finding suggested that partially developed cells are not fully determined but retain the potency to produce all types of cells found in an entire organism.
In fact, the states of cells are quite dynamic, especially when injury or disease occurs. An equilibrium between new cell generation and old cell loss is generally maintained in multicellular organisms. If perturbed by unexpected loss, stem cell replication and differentiation along with transformation of mature differentiated cells can restore equilibrium. For example, endothelial cells assume arterial, venous, or lymphatic identity in an early developmental stage. However, upon injury, endothelial cells can undergo lineage changes to become hematopoietic progenitor or cardiac valve cells.– In liver homeostasis, the modest proliferation of hepatocytes in all zones contributes to the homeostatic hepatocyte pool, rather than a rare type of liver progenitor cell (LPC) subpopulation., In a genetic mouse model which mimics human Alagille syndrome and contributes to biliary epithelium regeneration, hepatocytes are able to transdifferentiate into biliary epithelial cells. Additionally, cellular plasticity can be “artificially” enhanced, as demonstrated by induced pluripotent stem cells (iPSCs), which were first generated in 2007, providing unprecedented opportunities for novel therapies.
Cellular plasticity also contributes to pathological conditions. Similar to the cell plasticity observed during post-injury repair and regeneration, plasticity in tumor cells promotes survival against the immune attack and anti-tumor treatments. A major obstacle preventing complete remission, this evasion to therapy occurs as cancer cells play “hide and seek” by constant phenotypic switching. Some regard this phenotypic switching of cancer cells to result from passive Darwinian selection and enrichment upon drug exposure,, while others argue it is an active adaptation to internal or external stimuli (Lamarckian induction). A coexisting model has also been formulated to illustrate that these two concepts complement and intertwine with each other (Fig. 1).– The “hide and seek” behavior of cancer cells is known as TCP, which is a process that re-activates various developmental programs to achieve phenotypic switching. TCP enables transformation of tumor cell identity that allows the cells to adapt to different microenvironments and circumvent the drug-targeted pathway. This subpopulation of tumor cells is characterized by its dormant and stem-like trait and termed drug-tolerant persisters (DTPs). The “acquired inertia” of DTPs is regarded as a survival skill exposed by antitumor treatment that can fade away after a drug-free interval. Thus, with TCP, a reversible switching of phenotypes can be achieved between proliferative, metastatic tumor cells and dormant, drug-indifferent DTPs, thereby hindering the desired outcome of targeted therapies. By this universally plastic behavior, tumor cells transform in different but functionally overlapping processes, including epithelial-mesenchymal transition (EMT), transdifferentiation, and acquiring properties of cancer stem cells (CSCs).,,
Epithelial–mesenchymal transition
EMT is a process by which tumor cells lose their epithelial features and acquire mesenchymal characteristics. EMT is characterized by loss of apical-basal polarity and disruption of intercellular interactions, accompanied by the acquisition of front-rear polarity and remodeling of the cytoskeleton., On the other hand, mesenchymal-epithelial transition (MET) is the inverse process of EMT. EMT and MET are thought to be regulated mainly at the transcriptional level by the activity of EMT transcription factors (EMT-TFs), including Snail, Slug, Zeb1/2, Twist, and microRNAs (miRs). Signaling pathways such as transforming growth factor (TGF-β), wingless/integrated (WNT), NOTCH, and HIPPO are also involved., Two double-negative feedback loops that include Snail/miR-34 and Zeb/miR-200 help to manipulate the initiation, transition, and maintenance of EMT program., Genetic mutations may also play a role in EMT regulation. As indicated by Martin et al., a combined loss of the tumor suppressor gene P53 and PTEN in clonal prostate epithelial cells can lead to transformation of multipotent progenitors and ultimately EMT. Yamasaki et al. recently proposed that Kirsten rat sarcoma viral oncogene homolog (KRAS) mutation can also promote an EMT-like phenotypic change.
Both EMT and MET have been proposed to play key roles in cancer progression. Apart from a complete EMT/MET transition, tumor cells can exhibit a “partial EMT” state, a hybrid of epithelial and mesenchymal phenotypes. In fact, tumor cells can exhibit a spectrum of EMT states characterized by varying proportions of epithelial and mesenchymal traits, both in circulation and at a secondary site., Panchy et al. recently confirmed this epithelial-mesenchymal spectrum using transcriptomic analysis. This hybrid epithelial-mesenchymal state enables tumor cells to self-adapt and adjust quickly to changing environments, thus representing an ideal mechanism of TCP. Previous studies indicate that dynamic changes between epithelial and mesenchymal phenotype in tumor cells with partial EMT are critically important to the metastatic potential and therapy resistance of tumor cells.
The contributions made by EMT programs to metastasis were first proposed by Yang et al., who described that inhibition of Twist, a classic EMT-TF, can significantly restrain highly metastatic mammary carcinoma cells from metastasizing to the lung. The impact of other EMT-TFs on metastasis was then extensively investigated in different types of cancers. For example, depletion of Zeb1 was found to markedly inhibit pancreatic ductal adenocarcinoma progression towards metastatic type. Zeb1 was also found to function as a key master regulator of multiple EMT-TFs and metastasis in breast cancer. The MET program, in contrast, presumably functions during metastasis when the migratory CSCs settle down and adapt to a new microenvironment. In the process of colonization, the migratory CSCs regain self-renewal capacity and spawn fast-cycling epithelial progeny, thereby restoring epithelial characteristics. Such reversible EMT-MET programs seem to be a common feature shared by different cancer types during the seeding of a secondary tumor.–
Evidence also suggests that EMT can serve as a survival mechanism for cancer cells to escape immunosurveillance and resist therapy-induced death. Multiple studies have observed a strong correlation between the level of mesenchymal cell markers and therapeutic resistance.,– For example, Farmer et al. demonstrated that an upregulation of stromal gene expression predicted resistance to preoperative chemotherapy with 5-fluororacil, epirubicin, and cyclophosphamide in estrogen receptor (ER)-negative breast cancer. In ovarian cancer, inhibition of EMT can effectively eliminate cisplatin resistance. Byers et al. revealed a correlation between a 76-gene mesenchymal signature and non-small-cell lung cancer (NSCLC) resistance to epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) and phosphatidylinositol 3-kinase/protein kinase B (PI3K/Akt) inhibitors. By proteomic screening, Paulitschke et al. also found that two EMT-related markers are effective in determining drug susceptibility in melanoma cells. Although the mechanisms underlying the therapeutic resistance conferred by EMT remain unclear, several hypotheses have been put forward, including reduced levels of proapoptotic proteins, increased drug efflux, and immunosuppressive tumor microenvironment (TME).–
Transdifferentiation
Transdifferentiation, also known as lineage plasticity or lineage switching, is a radical shift in cell identity that leads to cells acquiring new transcriptional or morphological characteristics., In the context of cancer, such lineage plasticity may serve as a promising therapeutic approach. For example, melanoma spheroid cells are able to transdifferentiate into benign cell lineages including melanocytes, adipocytes, osteocytes and chondrocytes. However, transdifferentiation in cancer cells can also be a double-edge sword. Transdifferentiation observed in basal cell carcinoma (BCC) contributes to BCC relapse following treatment discontinuation., When treated with vismodegib, some BCC cells transitioned from a phenotype featuring a transcriptional bulge-like signature to a mixed isthmus/interfollicular epidermis cell phenotype, thereby achieving drug resistance. A discontinuation of treatment led to tumor cell reactivation and resumption of proliferation., Another distinctive form of transdifferentiation is characterized by a drug-induced neuroendocrine transdifferentiation (NET). Observed in prostate cancer (PC) and lung adenocarcinoma (LUAD), NET induces drug resistance, thereby causing treatment failure and relapse.,, Here, we consider PC and LUAD as two typical examples of NET for further discussion.
Through NET, PC tumor cells gradually obtain the histomorphology of small cell prostate cancers (SCPC) that are “therapy indifferent” to androgen receptor signaling inhibitors (ARSi)., The switch from PC to SCPC is characterized by the presence of neuroendocrine markers (chromogranin A, synaptophysin, and others), and the absence of androgen receptor (AR) and serum prostate-specific antigen. Functionally, SCPC cells have an elevated metastatic potential, enhanced stemness, heightened therapeutic resistance, and a worse prognosis., Inactivation of TP53, RB1, PTEN, and amplification of MYCN have been reported to be involved at the molecular level of the cell identity shift., Mutations in these candidate genes provide a specific genomic background that enables epigenetic regulation towards tumor plasticity.,
Moreover, epigenetic events are also indispensable. NET of PC cells towards SCPC is associated with the well-established undifferentiated cell marker SRY-Box Transcription Factor 2 (SOX2), epigenetic regulator histone methyltransferase enhancer of zeste homolog 2 (EZH2), the catalytic subunit of the polycomb repressive complex 2 (PRC2), and RE1-silencing transcription factor (REST).,,– A recent study by Cyrta et al. suggested that the switch/sucrose non-fermentable (SWI/SNF) chromatin remodeling complexes may also be a potential regulator of SCPC lineage plasticity. Correspondingly, SCPC can be reverted to its original lineage by the re-establishment of TP53 and RB1 as well as re-exposure to androgens, or inhibition of SOX2, thus re-sensitized to ARSi treatment., This reversibility of lineage plasticity could be of critical importance as a future target in PC therapy.
Like SCPC, LUAD undergoes NET through LUAD – small-cell lung cancer (SCLC) transition, which enables the tumor to escape from EGFR-TKI treatment and gain a higher level of malignancy.,, Although NET is also identified in non-EGFR-mutant NSCLC, EGFR mutant LUADs are more likely to switch lineage. Oser et al. reported that 5–15% of EGFR mutant LUAD patients with TKI resistance showed small cell histology in relapsed tumors, and became sensitive to SCLC chemotherapy. The mechanism of LUAD NET at the molecular level is similar to that of PC NET. LUADs with loss of TP53 and RB1 expression are more likely to transdifferentiate into SCLC tumors, which suggests that these two genes may be critical in promoting transdifferentiation towards a neuroendocrine identity.,– The epigenetic regulator EZH2 is also regarded as a potential therapeutic target to reverse NET.,
PC and LUAD are currently the most extensively studied cancers exhibiting NET; however, transdifferentiation of epithelial cells is more common. According to a recent study, many epithelial cancers, including bladder, endometrial, and gastric cancer with neuroendocrine gene expression signatures tend to exhibit high-grade tumors and poor prognosis. This finding indicates that a latent neuroendocrine lineage plasticity may occur in multiple tissues.
Cancer stem cells
Accumulating evidence suggests that the existence of CSCs within tumor tissues is responsible for tumor initiation and intertumoral heterogeneity. CSCs have the potential to proliferate infinitely, self-renew, and differentiate., A recent study proposed that a CSC is a highly plastic state that results in fast adaptation of tumor cells to varying conditions in the TME. Previous studies revealed CSCs and adult stem cells share multiple signatures, including the surface markers CD133, CD44, CD24, CD26, CD166, and EPCAM, and intracellular proteins like ALDH1.– Additionally, CSCs and stem cells also share similar developmental related signaling pathways, such as WNT, NOTCH, and Hedgehog (Hh).,
Like normal stem cells, CSCs propagate through asymmetric division, which produces one daughter cell that remains a CSC and one committed progenitor cell that differentiates into a non-CSC., Symmetric division can also occur simultaneously, with the production of either two CSCs (symmetric renewal) or two committed cells (symmetric commitment)., The transition between CSC and non-CSC states seems irreversible and dynamically balanced. Under certain circumstances, however, the balance can shift in either direction. A shift towards renewal results in replenishment of the CSC pool and consequently produces a more aggressive, undifferentiated phenotype. A shift towards non-CSCs suggests tumor-formation. Equilibrium represents the plasticity of tumor cell fate and can be manipulated by various influencing factors. For example, a second mutation introduced in chronic-phase chronic myeloid leukemia (CML) has been found to trigger an imbalance that favors symmetric renewal and results in higher malignancy. EMT-TF Twist2 has been reported to induce stemness properties in lung CSCs by moving the balance towards symmetric division, while repressing asymmetric division. Other epigenetic regulations, including deoxyribonucleic acid (DNA) methylation, histone modification, and bivalent chromatin state, have been found to contribute to CSC plasticity., These studies indicate that manipulation of CSC division may be promising for cancer control.
CSCs and EMT share a high degree of consistency and may be a partially overlapping concept., As mentioned, the EMT program largely facilitates tumor cell dissemination. CSCs are also enriched in disseminated tumor cells and feature EMT expression signatures. Circulating tumor cells express a remarkably congruent transcriptomic profile with CSCs and have been found to overexpress both EMT and stem cell markers. CSCs led to therapeutic resistance through various mechanisms. For example, CSCs can specifically inherit effective drug-discharging ATP-binding cassette (ABC) transporters from asymmetrical division, which enable tumors to sustain long-term expansion., CSCs can also facilitate efficient DNA damage.– Another mechanism of therapeutic resistance in CSCs is the formation of a protective niche, an immunosuppressive microenvironment characterized by low infiltration of immune cells and downregulated signaling by the programmed cell death ligand 1(PD-L1)., Non-CSCs also help to maintain of a pool of CSCs by secreting supportive signals such as WNT and brain-derived neurotrophic factor (BDNF), as well as supportive factors such as interleukin (IL)-6 and IL-8.–
Mechanism of therapy-induced TCP
Various therapies have been developed to prolong survival and improve the quality of life of cancer patients, yet therapy-induced drug resistance remains a major challenge to achieving the desired clinical outcomes. Notably, up to 90% cancer-associated deaths are attributed to drug resistance. Acquired drug resistance can be induced by targeted treatments and is associated with TCP, the “hide-and-seek” behavior of cancer cells. The drug-resistant phenotype of cancer cells is not heritable but is a transient and reversible process. Therefore, a comprehensive understanding of the mechanism of such induced plasticity should greatly facilitate the development of novel therapies. Epigenetic alterations, transcription factors, key signaling pathways, and TME can each potentially contribute to the therapy-induced plasticity in multiple cancers.
Epigenetic mechanisms
Therapy-induced epigenetic plasticity largely contributes to the reprogramming of tumor cells and phenotypic switching towards therapy resistance. The epigenetic modifications can be either chemical (DNA methylation and histone modification) or structural (chromatin remodeling and inter/intrachromosomal interactions), (Figs. 2a and 3).
DNA methylation is widespread in the human genome and functions differently based on various methylated regions. The aberrant methylation status of gene promoters plays an instrumental role in acquired drug resistance in a variety of tumor types., The most common mechanisms of drug resistance include hypomethylation of gene promoters of drug efflux, hypermethylation of promoters of pro-apoptotic genes, and altered methylation levels of DNA-repair genes. Global loss of DNA methylation and histone acetylation has been observed in therapy-induced drug-resistant tumor cells under extended treatment with the neoadjuvant aromatase inhibitor (letrozole). Such epigenetic alterations result in tumor cells escaping from dormancy and acquiring resistance after targeted therapy in breast cancer patients.
In contrast, indifference or resistance to endocrine therapy in ER-positive breast cancer is due to hypermethylation of estrogen-responsive enhancers. Moreover, effective therapies targeting the AR in PC inadvertently promote NET. The lineage switching into neuroendocrine PC was associated with increased DNA methylation, turning the original PC into a lethal, castration-resistant type. This process can be reversed by inhibition of DNA methyltransferase (DNMT). Histone modification, represented by euchromatin histone lysine methyltransferase 2 (EHMT2), has been implicated in acquired drug resistance following targeted therapy. EHMT2 overexpression was observed in erlotinib resistance in NSCLC, leading to transcriptional activation of PTEN and repressed Akt signaling, whereas inhibition of EHMT2 reverses the acquired indifference to therapy and re-sensitizes NSCLC cells to EGFR-TKI treatment. Histone modifications, either via EHMT2 or histone deacetylase 3 (HDAC3), can result in acquired resistance against mitogen-activated extracellular signal-regulated kinase inhibitors (MEKi) treatment in pancreatic ductal adenocarcinoma (PDAC).
Structural epigenetic alterations, including changes in high-order structures of chromatin and interactions among distal regulatory elements, may also be involved in therapy-induced TCP. For example, targeted therapy using γ-secretase inhibitors in T cell acute lymphoblastic leukemias (T-ALL) can induce the expansion of a rare group of pre-existing persister cells. These persisters contain more compact chromatin and higher levels of repressive histone modifications compared to γ-secretase inhibitor-sensitive naïve cells. Similar to trametinib-resistant triple-negative breast cancer (TNBC), remodeling of enhancers and promoters was observed accompanied with adaptive transcriptomic responses.
The role of transcription factors in controlling TCP
A network of transcription factors also plays an important role in TCP against targeted therapy. EMT-TFs like Twist and Snail actively respond to targeted therapy during the EMT process and result in enhanced plasticity and mesenchymal switching., In addition to multiple EMT-TFs, several other transcription factors function in controlling TCP.
AR is known as a ligand-activated transcription factor which regulates gene expression in the prostate epithelium. AR-targeted inhibitors, including bicalutamide and enzalutamide, have been developed for PC treatment., However, upon castration therapy, evading mechanisms are launched by AR amplification, point mutation, splicing variants, as well as substitution of AR functions by glucocorticoid receptors.
Signal transducer and activator of transcription 3 (STAT3) is a transcription factor that has been studied extensively in multiple cancers. Previous studies have suggested that STAT3 activation is associated with trastuzumab as well as trastuzumab-emtansine resistance in human epidermal growth factor receptor 2 (HER2)-positive breast cancer., In triple-negative (ER-/PR-/HER2-) breast cancer (TNBC) patients, a strong transcriptomic response was observed after treatment with trametinib for seven continuous days, with up to 22% of the transcriptome either significantly up- or downregulated. The super transcription factor cellular MYC underwent rapid degradation during the treatment process and functioned as a controller of genomic reorganization and transcriptional complex recruitment in the phenotypic change of tumors.,
In melanoma, an assay for transposase-accessible chromatin using sequencing (ATAC-seq) revealed an initial loss of transcription factor binding sites, followed by an increase in accessible sites, during BRAF inhibition (BRAFi) treatment. These results indicated that targeted therapy altered transcription factors. According to a recent study by Yang et al., activating transcription factor 4 (ATF4) stress signaling led to rapid tumor evasion within a few days after the initiation of mitogen-activated protein kinase (MAPK) pathway inhibition, and was accompanied by elevated levels of microphthalmia-associated transcription factor (MITF). This was followed by tumor cell dedifferentiation and a dormant phenotype marked with decrease in MITF expression. Additionally, the helix-loop-helix transcription factor inhibitor of DNA binding 3 (ID3) was upregulated after BRAFi therapy compared to that in the pretreatment state. ID3 acted as a transcriptional repressor of sex-determining region Y-box 10 (SOX10) and MITF, thereby promoting tumor cell transformation to a drug-resistant phenotype. Moreover, Sun et al. also observed an increase in the percentage of SOX10low EGFRhigh melanoma cells after BRAFi and MEKi treatment. This subset of tumor cells displayed a slow-cycling phenotype in response to these targeted drugs, highlighting the potential of transcription factors to mediate plasticity in melanoma.
The regulation patterns of the numerous known transcription factors are quite distinct in targeted therapy-induced tumor cell lines., This complexity indicates that tumors acquire resistance against targeted therapies in a patient- and drug-dependent manner. Hence, the transcription factors and their interaction modes remain to be explored.
Key signaling pathways in controlling TCP
Numerous signaling pathways are involved in embryonic development, and a re-activation of these signaling pathways is critical in tumor progression and therapy resistance. Interaction of these conserved signaling pathways (e.g., Hh, Wnt, and Notch pathways) and their crosstalk with other oncogenic pathways (e.g., Nuclear factor kappa B (NF-κB), PI3K/AKT/Mammalian target of rapamycin (mTOR), and MAPK pathways) contributes significantly to TCP by regulating the fluctuating expression of downstream effectors– (Fig. 2b). Phenotypic switching driven by multiple signaling pathways is a huge challenge to successful tumor treatment.
Alterations of the Hh (Hedgehog) signaling pathway occur in one-third of cancers, and deregulation of the Hh signaling pathway plays an important role in therapeutic resistance.,– Aberrant activation of Hh signaling and subsequent upregulation of downstream effector glioma-associated transcription factor 2 (GLI2) was observed in bortezomib-resistant myeloma cells., Further studies demonstrated that Hh signaling is involved in CSC self-renewal in multiple myeloma, and blocking Hh signaling can lead to CSC differentiation. In TNBC, the Hh ligand produced by tumor cells can reprogram cancer-associated fibroblasts (CAFs) to promote a CSC-phenotype switching and the acquisition of chemo-resistant traits. Therefore, an effective Hh signaling pathway blockade is capable of lowering CSC proliferation, metastasis, and the EMT program, thereby controlling TCP.
Wnt signaling pathway is also highly associated with TCP. Wnt signaling is complex and can function through either an autocrine or a paracrine mode, by canonical (Wnt/β-catenin pathway) or non-canonical (the planar cell polarity pathway) pathways. Wnt signaling contributes to EMT regulation and TCP. In most cases, the Wnt/β-catenin signaling pathway is constitutively activated, which increases the expression of Snail, a regulator of EMT. Inhibition of the Wnt/β-catenin pathway inhibits EMT and tumor metastasis in a colorectal cancer model. Slug is another EMT modulator that is considered to be a downstream protein in Wnt/β-catenin-mediated tumor invasion. Moon et al. reported that concurrent expression of β-catenin and Slug predicts lymph node metastasis and survival rate in patients with head and neck squamous cell carcinoma. Overexpression of Slug can induce cancer cell stemness and enhance cell invasion and metastasis. Sun et al. reported that Slug overexpression is associated with the invasiveness of liver cancer both in vitro and in vivo. In contrast, overexpression of Snail did not have a similar effect in liver cancer cells. The Wnt pathway has been linked to increased expression of another EMT transcription factor, Twist, in mammary epithelial cells.,
Accumulating data show that TWIST not only induces EMT, but also promotes the formation of CSCs and enhances tumorigenesis. Therefore, inhibiting these EMT mediators may represent the strategy for inhibiting tumor metastasis and recurrence. Additionally, activation of the Wnt signaling pathway reportedly controls the stemness of CSCs in different types of cancers including hepatocellular carcinoma (HCC), and colon, lung, and other cancers.– According to clinical practice, targeted treatment using MEKi (selumetinib, trametinib, and PD318088) inadvertently increased Wnt activity and led to enhanced stemness and tumor relapse in colorectal cancer. Similarly, valproic acid, which was originally regarded as a histone deacetylase (HDAC) inhibitor in breast cancer treatment, can activate Wnt signaling pathway and promote the pool of mammary CSCs, leading to tumor progression. Hence, attention should be paid to unexpected phenotypic switching regulated by Wnt signaling pathway in the processes of targeted therapy.
The Notch signaling pathway also enriches CSCs and regulates the EMT program in multiple cancers, including breast and lung cancer, pancreatic ductal adenocarcinoma, and malignant mesothelioma.– A previous finding showed a change in EMT status in lung adenocarcinoma upon treatment with gefitinib. Subsequent studies further confirmed that the EMT process resulted from the activation of Notch-1 signaling pathway and led to gefitinib-acquired resistance. Notch signaling is one of the master regulators of neuroendocrine transdifferentiation in NSCLC, which enables NSCLC to transdifferentiate into SCLC and acquire resistance to EGFR-TKIs after initial targeted treatment.
By extension, the Notch pathway has been discovered to play a crucial role in the EMT process in prostate cancer cells, promote a transformation towards basal stem-like properties, and lead to a castration-resistant phenotype., Components of the Notch signaling pathway are expressed at significant levels in tumor invasive regions, which suggests its crucial role in EMT regulation. A recent paper by Natsuizaka et al. reported that Notch1 signaling and EMT work closely to promote squamous cell carcinoma tumor initiation. Moreover, another important protein, TGF-β, guides Notch1 to drive EMT. A study by Zeng et al. showed that inhibition of Notch1 reverses the EMT process and overcomes cisplatin resistance in breast cancer cells. The data also suggested that high expression of Notch1 predicts a poor prognosis in TNBC patients. Saad et al. demonstrated that the Notch-mediated activation of EMT is associated with the regulation of EMT transcription factors. The two transcription factors, Snail and Slug, are involved in the inhibition of E-cadherin and β-catenin mediated by the Notch pathway. Inhibition of Notch activation limits the increase of MMP-2 and −9 expression, while it decreases Snail expression. The study provided direct evidence that Notch signaling induces EMT via the Snail pathway. Surprisingly, Notch signaling can synergistically work with other pathways to facilitate the EMT process. The crosstalk between these pathways is mediated by suppressor of mothers against decapentaplegic (SMADs) proteins that associate with other transcription factors for regulating the expression of genes required for the transition to mesenchymal characteristics. A single-cell sequencing study by Deshmukh et al. revealed both sequential and parallel activation of EMT signaling pathways. The Notch pathway also functions as a crucial regulator of TGF-β–induced EMT.
The role of TME in controlling TCP
TME is a key player in TCP induced by targeted treatment. The characteristics of TME, including immune and stromal cells, cytokines, exosomes, hypoxia, pH change, nutritional deficiency, and angiogenesis, are key regulators of TCP.–
CAFs are recognized as major contributors in the crosstalk between tumor cells and adjacent stromal cells. By producing a variety of bioactive molecules such as growth factors and cytokines, CAFs exert a profound impact on TME and influence TCP,,, and have long been described as crucial players in the EMT program. CAFs also participate in CSC pool expansion.– The effect of CAFs in manipulating therapy resistance was reported by Apicella et al. In this study, a prolonged treatment with TKIs generated resistance to erlotinib in vivo, but not in vitro. This intriguing phenomenon was explained by the existence of CAFs. Erlotinib treatment in vivo induces a metabolic rewiring towards aerobic glycolysis and increases lactate production; the secreted lactate triggers the overproduction of hepatocyte growth factor (HGF) in CAFs. Engulfed lactate and the subsequently increased HGF then activate the MET signaling pathway in cancer cells and cause resistance to erlotinib.– Moreover, hypoxia-induced glycolysis represses natural killer (NK) cells via lactate accumulation and reduces cytotoxicity by decreased level of NKG2D, CD16, perforin, and granzyme B, thereby forming an immunosuppressive TME. Such hypoxia-related TME conditions were reported to play a role in resistance to therapeutic monoclonal antibodies.,
Cytokines secreted by immune and stromal cells also provide clues for acquired TCP induced by targeted therapy.– According to Li et al., IL-6 in EFGR-mutant NSCLC patients was significantly increased upon osimertinib therapy. This associated Upregulation of laminin α5, which is among the most widely distributed laminins and is a major component of extracellular matrix (ECM), also occurred. By upregulation of laminin α5, IL-6 remodeled ECM and activated a downstream target focal adhesion kinase (FAK), thus contributing to acquired resistance against Osimertinib.– FAK activation was confirmed to be dispensable for IL-6 production in the maintenance of mesenchymal stem cells and can lead to acquired resistance of gefitinib as well.,
Contribution of TCP to targeted therapy resistance
Targeted therapy is one of the most successful treatments that strike at the heart of a wide range of cancers. Nonetheless, the emergence of drug resistance significantly impairs the efficacy of targeted drugs and contributes to cancer mortality. Drug target mutations and activation of bypass pathways are known to confer resistance in cancer cells to targeted inhibitors. With an increasing understanding of TCP, it is now recognized that TCP is an important factor in mediating drug resistance. In this section, we focus on the role of TCP in shaping tumor cell characteristics and mediating targeted therapy resistance (Fig. 4).
Epithelial–mesenchymal transition related factors in mediating drug resistance
As described above, EMT plays a critical role in mediating TCP and resistance to targeted therapy. The principal mechanisms of EMT-related drug resistance can be attributed to slow cell proliferation, increased drug efflux, and escape from apoptosis. Lung cancer is by far the most well-documented subtype of cancer that links EMT and targeted drug resistance. Namba et al. demonstrated that the upregulation of EMT-related gene AXL contributes to acquired resistance to osimertinib. Other EMT-related transcription factors, such as Snail, Slug, and ZEB1/2, are also reported to cause TKI resistance by regulation of EMT-related signaling pathways.– Therefore, a comprehensive understanding of the EMT process is critical to combat targeted therapy resistance. In this subsection, we delineate the current research on signaling pathways and related factors that modulate EMT associated with drug resistance.
Signaling pathways including Notch, Wnt/β-catenin, and TGF-β play crucial roles in activating EMT-related transcription factors. Evidence supports that EMT transcription factors are involved in targeted therapy resistance, especially towards EGFR inhibitors. Consequently, signaling pathways that regulate the EMT process are important in mediating drug resistance. Chang et al. reported that Slug contributes to gefitinib resistance in NSCLC cells through downregulation of Bim and inhibition of caspase-9 activity. Among EMT inducers, TGF-β is significant because of its potency in inducing EMT and its roles in cancer-associated EMT. TGF-β-induced EMT is essential in cellular activities such as glycolysis and lipid/choline metabolism reprogramming. In response to TGF-β, cancer cells undergo complete or partial EMT, where epithelial and mesenchymal markers co-exist on cancer cells. The partial EMT status is characterized by an aggressive phenotype that renders cancer cells with high stemness and cell plasticity. Upon stimulation of TGF-β receptors, TGF-β signaling is divided into SMAD-dependent and -independent pathways. Both TGF-β/SMAD and non-SMAD pathways play a significant role in mediating EMT and promoting cell plasticity. Additionally, signaling pathways such as PI3K/AKT, mTOR, and MAPK are reported to play essential roles in TGF-β-induced EMT., Surprisingly, TGF-β-induced EMT can be reversed. A study conducted by Katsuno et al. found that upon TGF-β removal, mesenchymal cells revert to an epithelial cell phenotype. Moreover, prolonged TGF-β exposure promotes a stable EMT process in cancer cells, which is accompanied by increased tumor stemness and cancer drug resistance. The authors also identified that mTOR inhibitors can be a promising agent to target CSCs by antagonizing the TGF-β-induced EMT process.
MicroRNA (miRNAs) are small non-coding RNAs that play a pivotal role in the regulation of both EMT that promotes tumor metastasis and MET that facilitates metastatic colonization. EMT-related miRNAs are documented to impact cancer cell stemness and drug resistance. Recent evidence showed that miRNAs may affect the EMT process by targeting related transcription factors, including Snail, Slug, Twist, and ZEB1/2. The expression level of the Snail transcription factor may be controlled by multiple metastasis-related miRNAs, including miR-153, miR-203, miR-204, and miR-34c. The miR-30 family are well-documented mediators of EMT transcription factor Snail in different cancer subtypes, including lung and breast cancer. Liu et al. showed that miR-1 and miR-200 can inhibit EMT and mesenchymal differentiation via Slug-dependent mechanisms. Other newly identified EMT-related miRNAs include miR-27b-3p, which promotes the generation of circulating tumor cells, and miRNA-490-3p, which promotes the metastasis of invasive ductal carcinoma. Nonetheless, recent studies have reported that some miRNAs, such as miRNA-128 MiRNA-155-5p,, are able to hinder the EMT process through inhibition of diverse EMT-related signaling pathways. With the increased understanding of miRNAs in EMT and TCP, different strategies focused on hindering miRNA function or miRNA delivery into tumor cells can be utilized to overcome cancer drug resistance.
Tumor heterogeneity
Tumor heterogeneity is defined as the existence of a subpopulation of cancer cells with different genotypes and phenotypes that exhibit various characteristics within a primary tumor. Heterogeneity may lead to divergent sensitivity to treatment and facilitate the development of drug resistance.
The most recent tumor heterogeneity model is known as the CSC plasticity model. CSC is a subpopulation of cancer cells with self-renewal capacity to switch between stem and differentiated states. This dynamic transition can be attributed to gene mutations, epigenetic modification, as well as changes in TME. It should be noted that the EMT signaling pathway plays a central role in mediating CSC transition, which promotes cancer metastasis, recurrence, and drug resistance. Morel et al. reported that the induction of EMT can enhance human breast epithelial cell stemness and tumorigenic characteristics, which has also been confirmed in colorectal, pancreatic, and liver cancers.– Quintana et al. demonstrated that most of the phenotypic heterogeneity in melanoma can be explained by the phenotypic plasticity model. Although they did not identify a marker that can significantly distinguish tumorigenic from non-tumorigenic cells, CD271 + cells were shown to have little tumorigenic activity. However, the results were inconsistent in different studies, suggesting that the role of cell plasticity in tumor heterogeneity may vary in cancer subtypes. Another study carried out by Charles et al. showed that nitric oxide can enhance the tumorigenic capacity of platelet-derived growth factor (PDGF)-driven glioma cells in vivo; therefore, it reversibly promotes their ability to form tumors. Nakano et al. reported the dynamic equilibrium between CSCs and non-CSCs in the development of colorectal cancer. Such equilibrium is mainly controlled by EMT-related TGF-β signaling pathway. One study demonstrated that, in colon cancer cells, the ablation of LGR5 + CSCs allowed the cancer cells to dedifferentiate into CSCs, which highlights the distinct CSC dependency for primary and metastatic tumor growth.
Multiple studies showed that a high level of tumor heterogeneity is associated with poor response to targeted drugs, including osimertinib, rociletinib, and gefitinib.– Chabon et al. demonstrated that multi-drug resistance was observed in 46% patients after targeted therapies, suggesting a frequent intra-tumor heterogeneity. TCP, i.e., phenotype switching between different signaling pathways, can potentially lead to heterogeneity under therapeutic selective pressure. As mentioned above, cell plasticity is essential in multiple crucial biological processes, including embryonic development, wound healing, and tissue regeneration. In tumors, the reactivation of these mechanisms allows tumor cells to switch between non-CSC and CSC-like phenotypes, leading to tumor progression, metastases, and drug resistance. Easwaran et al. performed a genome-wide analysis and found that silencing abnormal DNA methylation of promoters can decrease changes of plasticity of cell population and help in locking cell clones with abnormal retention of self-renewal capacity. Therefore, an effective approach to disrupt TCP may represent a promising strategy to tackle tumor heterogeneity and overcome drug resistance.
Interplay between TCP and TME
A tumor is not only a group of cancer cells, but also a complex interaction between cancer cells and their surrounding environment, known as the tumor microenvironment (TME), which has attracted substantial research and clinical interest in recent years. TME consists of tumor, immune (macrophages and lymphocytes), and stromal (stromal fibroblasts and endothelial cells) cells, blood vessels, and extracellular matrix (ECM). Accumulating data show that cancer cells are able to control the function of cellular and non-cellular components through complex signaling pathways. The cell-cell and cell-ECM interactions force non-malignant cells to acquire new phenotypes that facilitate the formation, progression, and metastasis of tumor cells. In addition, theinteractions of cancer cells with their TME are crucial to stimulate tumor heterogeneity, clonal evolution, and mediate drug resistance.
TCP allows tumor cells to switch phenotypes and survive treatment through adaptive strategies, and the TME is involved in mediating TCP. For example, both cancer-associated fibroblasts (CAFs) and hypoxia contribute to oxidative stress, which is an important mediator of multiple adaptive strategies. Hypoxia is a hallmark of the TME and strongly linked to malignant progression, poor clinical response, and therapy resistance. Recent studies have shown that hypoxia may induce phenotypic switching, leading to drug resistance. Terry et al. reported that hypoxic stress induces phenotypic diversity of EMT in lung cancer, and leads to changes in EMT transcription factors such as SNAI1, SNAI2, and ZEB2, which ultimately result in the resistance to cell-mediated cytotoxicity. Paolicchi et al. suggested that tumor hypoxia is a major contributor to drug resistance and a predisposing factor for increased CSC formation and metastases. Therefore, one promising cancer treatment strategy is to block the proteins related to hypoxia-induced factor (HIF)-1α, EMT, and mitochondria functions, which in turn inhibits the response to hypoxia. In addition, cytokines such as interferon-gamma and tumor necrosis factor-alpha are believed to enhance stromal cell plasticity and contribute to TME.
The interaction between TME and TCP can significantly contribute to the genetic heterogeneity. Reynolds et al. demonstrated that the number of genetic mutations arising in cells within tumors is much higher than that in the laboratory culture. Their results provide strong evidence that TME promotes genetic instability during tumor progression. On the other hand, tumor heterogeneity can lead to TME reprogramming and thus give rise to cancer drug resistance. Taken together, the interplay between TCP and TME serves an important role in mediating tumor progression, heterogeneity, and drug resistance.
Preventing initiation of TCP
Strategies that target TCP include intermittent treatments, combination therapies, and targeting the key nodes of phenotypic switching. A study showed that intermittent treatments and off dosing schedules may double the time of melanoma response to vemurafenib. However, intermittent treatment strategies are usually difficult to design as drug resistance may be complex and come from multiple mechanisms other than TCP., Combination therapies have also been applied to target parallel activation of key signaling pathways such as Hippo/yes-associated protein (YAP), PI3K, and EGFR,, resulting in a significant decrease in the number of residual tumor cells. However, combination therapies usually require more optimized drug administration protocols to maximize responses and limit toxicity due to their complexity.
Other strategies to prevent TCP have focused on inhibiting the key nodes of phenotypic switching genes. Histone demethylases, KDM5A/B and KDM6A, were known to play significant roles in DTP survival.– KDM inhibitors have been developed; however, they are still under assessment for their specificity and efficacy.– DTPs undergo transcriptional adaptation through changing their global chromatin landscape. Another similar strategy that targets the bromodomain and extra terminal domain (BET) BRD4 gene overcame trametinib resistance in triple-negative breast cancer and was efficient both in vitro and in vivo. In basal cell carcinoma, the assessment of inhibition or activation of Wnt and Notch signaling pathways are underperforming in clinical trials to treat pathway-dependent malignancies. Notch-activated tumor cells tend to undergo apoptosis upon vismodegib treatment. Inhibitions of Retinoid X receptor (RXR) pathways using HX531 together with MAPK inhibitors can significantly delay development of resistance to MAPK inhibitors, compared to treatment with MAPK inhibitors alone. Discovery of more drug targets that prevent tumor plasticity will enable the design of treatment strategies.
Targeting the fate of new cells
In addition to preventing the formation of cell plasticity, targeting the emerging drug-resistant new cell identity holds great potential for overcoming tumor plasticity (Fig. 4). Transformation from the NSCLC to SCLC usually causes strong drug resistance due to cell plasticity. SCLC cells often lose EGFR expression; therefore, they are resistant to EGFR inhibitors, in contrast to the nontransformed NSCLC (specifically LUAD). Transformed SCLCs were more responsive to platinum-etoposide, similar to de novo SCLC. However, compared to de novo SCLC, transformed SCLC showed a higher response rate to taxanes yet were resistant to checkpoint inhibitor therapy, which was similar to EGFR-mutant LUAD. Recently, molecular studies showed that the growth of some mesenchymal cancer cells depends on the expression of phospholipid glutathione peroxidase 4 (GPX4), and inhibition of GPX4 can profoundly decrease DTP, thus preventing tumor relapse. However, current GPX4 inhibitors are chloroacetamide-containing compounds (such as RLS3), which have been identified to possess only poor pharmacokinetic properties, such as low stability, promiscuity, and bioavailability. The GPX-knockout mouse was lethal, indicating that choosing the therapeutic window that targets this protein is challenging.– Thus, finding drugs that target the new cell identity is necessary for designing therapeutic strategies.
Reversing TCP
TCP can be driven by an inflamed and suppressive TME. Drugs and therapies have been developed against intracellular signaling kinases and extracellular signaling molecules in TME., Additionally, since epigenetic changes contribute to TCP, targeting those processes could potentially re-sensitize tumor cells to drug treatments.
IL-8
IL-8, a pro-inflammatory cytokine, is known to promote tumor cell remodeling and is involved in regulation of tumor cell stemness, EMT, and therapy resistance in multiple types of tumors., IL-8 production promotes tumor cells to transform to a mesenchymal phenotype and increase tumor cell migration, leading to metastases. C-X-C chemokine receptor 1 (CXCR1) antagonist therapies have been found to reverse the IL-8 related events. Resistance to PI3K/Akt/mTOR pathway inhibition in hepatocellular carcinoma has been associated with both liver cancer stem cells and a high level of IL-8 expression. Rapamycin, the mTOR inhibitor, was able to decrease the IL-8 expression, thus decrease the resistance to sorafenib. A neutralizing antibody, HuMAX-IL8, was used to deplete IL-8 secretion and treat human TNBC. Another study showed that neutralizing IL-8 can alleviate resistance to erlotinib in NSCLC, thereby enhancing sensitivity in chemotherapy-resistant cells. Inhibition of CXCR2 with SB225002 also alleviated the IL-8-related resistance in sorafenib-resistant ovarian tumor cells.
TGF-β
Reversing EMT by blockage of TGF-β signaling is acknowledged as a promising way to reverse TCP, as TGF-β has been widely recognized as the major inducer of EMT. A recent single-cell transcriptome-based study showed that blocking TGF-β1 could restore stromal plasticity in tumors by affecting a subset of interferon-licensed fibroblasts. However, the pleiotropic functions of TGF-β1 in cancer render therapeutic inhibition of this pathway challenging. TGF-β1 inhibition in various combination therapies that target the drug-induced plasticity is under evaluation. Galunisertib (LY2157299 monohydrate), a small molecule inhibitor that inhibits TGFβRI ALK5 kinase, has been used in numerous preclinical trials. Forskolin and cholera toxin have been identified through a drug screen for E-cadherin promoter activation. JMF3086, a dual inhibitor that targets both HDAC and 3-hydroxy-3-methylglutaryl coenzyme A reductase, can restore the sensitivity of NSCLC to EGFR-TKIs (34). A preclinical study showed that galunisertib has the potential to regulate pancreatic cancer cell growth through prevention of TGF-β mediated E-cadherin downregulation. Galunisertib also demonstrated anti-tumor efficacy in patients with pancreatic cancer as well as in a subset of patients with advanced HCC. A recent study also demonstrated that inhibition of TGF-β and leukocyte-associated immunoglobin like receptor-1 (LAIR-1) can remodel TME, thereby enabling programmed-death ligand 1 (PD-L1)-mediated tumor eradication. Dual-blockade of CD73-TGFβ promotes a multifaceted inflammatory environment in TNBC, by diminishing myeloid-derived suppressor cells and M2-macrophages but increasing cytotoxic T cells and activated dendritic cells. These studies and novel drugs have provided strong evidence that blocking TGF-β can reverse TCP, thereby sensitizing tumor cells to targeted or immune-mediated cell death.
EZH2
EZH2, the catalytic subunit of polycomb repressive complex 2 (PRC2), is the central player in the process of epigenetic gene silencing. EZH2 promotes tumor cell survival, proliferation, EMT, and invasion, as well as drug resistance. Reversible transition between EMT and MET are key aspects of TCP. Interestingly, EZH2 was recently found to support TCP through MET facilitation and tumor colonization. Overexpression of EZH2 was associated with the conversion of prostate adenocarcinoma to neuroendocrine prostate cancer (NEPC), which is a more aggressive variant., Inhibition of EZH2 can reverse the cell lineage switch, leading to a decrease in neuroendocrine related key factors and restoring the sensitivity of NEPC cells to enzalutamide. Some EZH2 inhibitors (for example, CPI-1205 and Tazemetostat) have entered phase I and II clinical trials for lymphomas and solid tumors.,
Other targets and pathways
Other targets and pathways with potential ability to reverse TCP are emerging. Ferroptosis was identified as a new type of programmed cell death that can be harnessed to target drug resistance and EMT. Gagliardi et al. identified that EMT-associated gene expression reprogramming process that determines ferroptotic susceptibility cannot be applied to metastatic-derived cells, but SCL7A11 was a valuable marker to predict the susceptibility. Increased sensitivity to ferroptosis through crosstalk of BACH1 target genes can also impose programmed vulnerability upon cancer cells. Other than ferroptosis, HDAC inhibition was recently found to reverse EBV-induced dedifferentiation in nasopharyngeal carcinoma. The Yap-Sox9 axis was recently reported to determine hepatocyte plasticity in hepatocarcinogenesis and could be a promising target. Some other SOX factors have also been considered as promising candidates through proteolysis-targeting chimeric molecules or thalidomide analogues., An anti-CLDN6 antibody-drug conjugate has been reported to target tumor lineage plasticity. Another recent study showed that blocking the MNK1/2-eIF4E axis could inhibit melanoma phenotypic switching, thereby, sensitizing melanoma to anti–PD-1 immunotherapy. These studies suggest that reversing TCP through other targets could be a propitious future direction.
New therapies for overcoming TCP-induced drug resistance
TCP enables tumor cells to evade traditional anti-tumor therapies. Therefore, agents that block these escape routes can deprive the residual tumor cells of their hiding place and ensure positive treatment results (Fig. 5).
With immune checkpoint blockade (ICB)
An immunosuppressive TME is formed upon drug exposure as a consequence of the interaction between non-tumor and tumor cells. It is worth mentioning that the expression of immune checkpoint proteins, including programmed cell death 1 receptor (PD-1) and (PD-L1), cytotoxic T lymphocyte-associated protein 4 (CTLA-4), T cell immunoglobulin 3 (TIM-3), lymphocyte activation gene 3 (LAG-3), and T cell immunoreceptor with Ig and ITIM domains (TIGIT) contribute significantly to immunosuppression and serve as a bridge between EMT programs and immunosuppression.– A positive correlation between EMT and immune checkpoint proteins was identified in multiple cancer types, including lung, breast, colorectum, oral, and esophageal cancers,,– and a higher expression of these checkpoint molecules indicates worse prognosis in a broad range of cancers.– The functional relationship between immune checkpoint proteins and therapy evasion suggests that a combination treatment with immune checkpoint blockade (ICB) could be promising in developing a new approach against TCP.
Combining targeted therapy with ICB seems feasible according to current practice. Traditional EGFR-TKI was found to interfere with TME, thus laying a theoretical foundation for ICB application in EGFR-TKI-resistant NSCLC, especially in those with upregulated PD-L1 expression.– Moreover, recent studies revealed that dynamic changes occur in TME in response to EGFR-TKIs and suggested that a combination treatment with immune-mediated anticancer approaches could be beneficial.,– EGFR-TKI-ICB combination treatment provided better clinical benefit for NSCLC patients with increased overall response rate (ORR) (41.7% vs 14.3%) and median progression free survival (PFS) (19.5 months vs 1.4 months) in comparison to monotherapy of either pembrolizumab or gefitinib alone. Patients with short EGFR-TKI-PFS may even benefit more from a combination therapy as a second-line treatment. A similar combination strategy was applied in multiple cancer types as a so-called basket trial design. A combination of ICB with antiangiogenic molecular targeted therapy is an attractive approach for treating HCC. According to the IMbrave150 trial, atezolizumab in combination with bevacizumab showed greater benefits compared with sorafenib in advanced HCC patients and suggested that this combination strategy could be used as the first-line standard of care.– Additionally, a combination of ICB with other targeted therapeutic approaches, including ATR kinase inhibition and androgen receptor blockade resulted in synergistic therapeutic response in prostate cancer.–
Combining chemotherapy with ICB can be used to extend a synergistic therapeutic effect., A pooled analysis of three randomized clinical trials indicated that among patients with PD-L1-negative advanced / metastatic NSCLC, efficacy is better with pembrolizumab plus chemotherapy compared with chemotherapy alone. Similar results were obtained in PD-L1-positive NSCLC patients. As indicated by Zhang et al., the combination regimen of toripalimab and pemetrexed/carboplatin was superior to chemotherapy alone. Moreover, an IMpower150 trial showed that a combination of atezolizumab, bevacizumab, carboplatin, and paclitaxel (ABCP) led to significant improvement in median overall survival (OS) in chemotherapy-naïve patients with NSCLC. Anti-CTLA-4 ipilimumab was also tested in the treatment for NSCLC in combination with nivolumab and platinum doublet chemotherapy and exhibited clinical value as a first-line treatment. Another phase III clinical trial compared the efficacy of chemotherapy with nivolumab and chemotherapy alone in treatment for advanced gastric, gastroesophageal junction (GEJ), and esophageal adenocarcinoma, and found that the combination strategy had a benefit of significantly superior OS and PFS. Janjigian et al. proposed that this combination treatment represented a new first-line therapy for patients with upper gastrointestinal tumors. A recent phase III study (KEYNOTE-811) also confirmed that adding pembrolizumab to standard first-line treatment (trastuzumab plus chemotherapy) in advanced gastric or GEJ adenocarcinoma could markedly improve prognosis.
Though the basket trial design has greatly improved the clinical outcome of multiple cancer types, our understanding of the underlying mechanisms of the combination regimens remains limited. For example, nab-paclitaxel combined with atezolizumab are able to effectively prolong PFS in patients with metastatic TNBC as shown by the IMPASSION130 trial; however, the combination of paclitaxel with atezolizumab failed in the IMPASSION131 trial., Single-cell analyses revealed that baseline CXCL13+ T cell largely determined the clinical response in TNBC treatment. Further studies are warranted to explore the exact mechanisms of different combination strategies to be able to pin-point patients with higher therapeutic potential. Furthermore, novel combination methods are emerging. For example, a bioengineered platelet was designed that combines an inner-loaded doxorubicin and outer-anchored anti-PDL1-crosslinked nanogels. This composite design was reported to have the potential to reduce the recurrence and metastasis rate of postsurgical tumors.
Despite some optimistic reports, the safety profile of combination therapies with ICB remains poorly understood and controversial. In NSCLC treatment, an increased incidence of interstitial lung disease-like events was observed in the combination treatment of osimertinib and durvalumab in the CAURAL (38%) and TATTON (22%) trial.– Severe hepatotoxicity was observed in another clinical trial (CheckMate370) investigating the combined effect of nivolumab and crizotininb. Similar hepatic and immune-related adverse events were also observed in combined treatment with ICBs in melanoma.–
These described studies imply that a combination with ICB can improve therapeutic outcomes for therapy-resistant patients compared with either therapy alone. The clinical feasibility of the combined strategy warrants further exploration, and the safety profile should be carefully documented. Table 1 provides a list of some relevant clinical trials evaluating the combination therapy with ICB mentioned above.
With EMT-modulating agents
Because EMT plays an essential role in TCP and drug resistance, EMT-targeting compounds hold great potential as novel drugs in reversing drug resistance. However, investigation in this field is limited.
EMT-TFs play an essential role in TCP, and drugs directly targeting these transcription factors might have the potential to halt or reverse the plasticity and become a novel therapeutic approach to repress drug resistance. However, due to the redundancy of overlapping pathways and multitude of factors, it is hard to target and control TCP effectively. Direct targeting of these EMT-TFs is very challenging and there is not yet known EMT-TF-targeting molecule. Nevertheless, some related molecules involved in redundant EMT pathways have been investigated for clinical use. As a downstream target of YAP and EMT-TF Snail2, anexelekto (AXL) represents an ideal focus of EMT control., AXL-targeting inhibitors (SGI-7079 / Foretinib [XL-880] / Bemcentinib [BGB324] / 20G7-D9 / MYD1-72) have been reported to have an outstanding synergistic effect with erlotinib in NSCLC,, and advanced pancreatic and ovarian cancers, BRAF inhibitors in melanoma, and temozolomide with radiation in glioblastoma. Multitarget AXL inhibitors like SGI-7079 and sunitinib have also shown prominent clinical value in reversing therapeutic resistance.,, Moreover, secreted clusterin, an EMT-related protein which was shown to be significantly upregulated in EMT progression and HCC migration, is a candidate target for HCC therapy.– An antibody against secreted clusterin, termed as AB-16B5, was assessed in a phase II clinical trial in combination with docetaxel for the treatment of metastatic NSCLC (Table 2).
Inhibition of EMT-related pathways is a theoretically feasible approach to control TCP. TGF-β, a widely accepted key promoter of EMT and sustainer of mesenchymal and CSC states, contributes to the induction of immunosuppressive TME via hijacking Tregs and NK cells.,, A small molecule inhibitor of TGF-β receptor 1 named galunisertib (LY2157299 monohydrate) is attracting attention. One preclinical evaluation of galunisertib showed an inhibition of TGF-β-mediated downregulation of E-cadherin in mouse pancreatic cancer cell line, indicating an anti-EMT effect. A recent study by Song et al. demonstrated a synergistic effect in castration resistant PC using enzalutamide combined with galunisertib. The combinatorial galunisertib treatment successfully sensitized PC cells to traditional androgen deprivation therapy (ADT) and provided a novel therapeutic strategy for control of lineage transdifferentiation. Other studies tested the efficacy of galunisertib in HCC and indicated a prolonged OS using a combination of galunisertib and sorafenib. Melisi et al. stated in a phase Ib/II clinical trial that a galunisertib-gemcitabine combination therapy could significantly improve OS in patients with unresectable pancreatic cancer compared with monotherapy with gemcitabine. The same result was found in myelodysplastic syndromes (MDS); galunsertib treatment was associated with hematologic improvement in patients with signs of blockage of early stem cell differentiation. However, some other clinical trials failed to prove the efficacy of galunisertib in HCC, metastatic pancreatic cancer, or glioma.– Though such novel drugs can manipulate TCP and potentially re-sensitize tumor cells to immune-mediated cell death, further clinical trials are needed to validate their efficacy in different types of tumors. The ongoing clinical trials investigating the combination treatment with galunisertib are shown in Table 2.
Additionally, a combined immunotherapy of ICB and TGF-β blockade is also promising. In a murine model of metastatic intestinal tumor, the combination of anti-TGF-β and anti-PD-L1 showed an impressive antitumor response compared to either monotherapy. Currently, new approaches for simultaneous inhibition of TGF-β and PD-L1 are under evaluation. Bintrafusp alfa (also known as M7824) is a recently developed anti-PD-L1/ TGF-βRII fusion protein, which showed superior inhibition of tumor growth in multiple murine models., Other fusion drugs such as anti-CTLA4-TGF-βRII also showed promising efficacy in stimulating antitumor responses. Several early-phase trials showed encouraging clinical efficacy and manageable safety in different types of cancers.– Several ongoing clinical trials are testing the efficacy and safety of bintrafusp alfa (Table 2).
Wnt inhibitors including ETC-1922159 and Ipafricept (also known as OMP-54F28) were also employed in clinical control of various types of solid tumors.– Ipafricept combined with chemotherapy showed reasonable tolerance in early-phase clinical trials, and remains a therapeutic target of interest.,, ETC-1922159 is now under assessment in an ongoing clinical trial to test its efficacy as a pembrolizumab combination (Table 2).
With other therapy
The close interaction between inflammatory TME and EMT is well established and is regarded as a promising target for therapeutic use. Since TCP drives a highly inflamed TME, neutralizing monoclonal antibodies targeting IL-8 were developed to reverse TCP. HuMax-IL8 (also known as BMS-986253), a neutralizing anti-IL8 antibody that was designed to sequester IL-8 signaling, successfully inhibited the mesenchymal transition in human TNBC cell lines in vitro. Blockade of IL-8 enhanced the tumor cell-killing effect mediated by NK and T cells. Another in vivo study in NSCLC found that IL-8 neutralizing antibodies reversed the tumor plasticity and sensitized tumor cells to erlotinib. Currently, multiple ongoing clinical trials in phase I/II are examining the safety and efficacy of HuMax-IL8 as a combination therapy in various cancer types, including prostate and pancreatic cancer, HCC, NSCLC, and other solid tumors (Table 3). SX-682, another novel drug targeting the inflammatory EMT, was proposed to prevent polymorphonuclear (PMN)-MDSC migration and cooperate well with ICB treatment., Early-phase clinical trials of SX-682 in combination with ICBs (e.g., pembrolizumab and nivolumab) are currently recruiting participants (Table 3).
Hypoxia signaling contributes significantly to EMT and subsequent therapy resistance. Hypoxia-induced factor (HIF), a transcriptional regulator, was reported to be recruited to the hypoxia-responsive element of several EMT-related genes, including Twist, Snail, Vimentin, and TGF-β. HIF-1α promoted EMT via multiple signaling pathways, including PI3K/Akt, Notch, Wnt, and NF-κB., Treatments targeting hypoxia pathway are deemed as promising blockades against TCP. For example, by blocking the nuclear translocation of HIF-1α, 6-gingerol successfully inhibits the EMT pathway and suppresses proliferation and metastasis of lung cancer. Salidroside enhances antitumor efficacy of platinum drugs in HCC by promoting the degradation of HIF-1α, thereby inhibiting the EMT of HCC cells. Similarly in lung cancer, by inhibiting hypoxia-activated NF-κB signaling pathway and EMT, a ginseng-extracted 20(R)-Ginsenoside (Rg3) increases the susceptibility of cancer cells to cisplatin treatment.
Conclusion and perspectives
Here, we present a comprehensive description of TCP development and cancer cell evasion from targeted therapy. We delineate the non-genetic mechanisms of targeted drug-induced TCP in various types of tumors and provide insights into TCP contribution to acquired drug resistance. Owing to the rapid development of experimental techniques, dynamic changes of tumor cells in response to treatments can be observed in high resolution images. The ceaseless change of tumor cells indicates that living things even as simple as single cells show amazing adaptability under ambient pressure. Continuous monitoring of phenotypic switching can be of great help in designing specific dynamic therapeutic regimens and developing such monitoring techniques is worth exploring. We have been able to look into some pathways, like EMT, CSC, and transdifferentiation, that facilitate transformation of tumor cells; however, we still cannot visualize all the mechanisms contributing to TCP.
Research and development for new treatment is never-ending. As an old saying goes, a coin has two sides. In spite of TCP-related therapy escape, TCP also allows therapeutic reprogramming and possibly reversal of tissue attrition. In this review, we summarize new therapeutic strategies that aim to inhibit or reverse TCP and discuss related combination treatment regimens. We note that regulation of plasticity-related TME with ICB or direct imposition of EMT-modulating agents will not bring revolutionary improvement in cancer treatment. However, each small step forward against cancer is worth trying, and the concept of TCP remains valuable for further development of novel therapeutic strategies. Inhibition of unexpected TCP is theoretically feasible by holding the tumor cell unchanged. On the other hand, effective manipulation of TCP also holds great potential, and converting diverse tumor cells into a unified and susceptible state could be an alternative. The basket trial design should be continued to probe new treatment opportunities for different types of cancers, and special attention should be given to searching for new targets to better manipulate TCP.
As for future research on TCP, modern technologies could be of great help. For example, omics technique and capacity of dealing with “big data” has largely broadened our knowledge of the molecular landscape of tumor tissues. Recently developed technologies could enable a simultaneous acquisition of multiple omics data at a single-cell level, and several analytic models have been established to interpret the high-dimensional multimodal data., Single-cell level multi-omics could precisely trace the therapy-induced responses of each cell in heterogeneous tumors from the aspects of transcriptomics, proteomics, epigenomics, even in combination with their spatial distribution. The innovative analytical modalities provide deep and comprehensive information at single-cell resolution and could help to explore yet unrecognized cellular activity both intracellularly and intercellularly. In addition, single-cell techniques could also help to identify biomarkers to determine TCP, tumor response to targeted therapy, as well as prognosis. Artificial intelligence could also be employed to capture the underlying regularities of such an unwieldly mass of data. It was expected that one day, with the help of big data and the corresponding interpreting capacity, complete cures could be achieved by personalized treatment strategies decided by molecules at single-cell level.
In the face of such capricious, unpredictable, and threatening disease, scientific research will be always on the way to distill the complexity of cancer into an increasingly logical science. The attempts to get a better understanding of TCP in targeted therapy hold great promise for future blockade against therapy evasion, which may promote realization of long-lasting curative effects and even complete cure in cancer patients. Ongoing clinical trials using conventional treatments combined with plasticity-regulating treatment also indicate new opportunities for achieving the goal of complete cancer cure.
References 374
- 1.
- 2.
Paksa A, Rajagopal J. The epigenetic basis of cellular plasticity. Curr. Opin. Cell Biol. 2017;49:116-122.
Not in our library10.1016/j.ceb.2018.01.003 (opens in a new tab)
- 3.
Waddington CH. Embryology, epigenetics and biogenetics. Nature. 1956;177:1241-1241.
Not in our library10.1038/1771241a0 (opens in a new tab)
- 4.
Tata PR, Rajagopal J. Cellular plasticity: 1712 to the present day. Curr. Opin. Cell Biol. 2016;43:46-54.
Not in our library10.1016/j.ceb.2016.07.005 (opens in a new tab)
- 5.
Castranova D, et al. Live Imaging of Intracranial Lymphatics in the Zebrafish. Circ. Res. 2021;128:42-58.
Not in our library10.1161/circresaha.120.317372 (opens in a new tab)
- 6.
Bower NI, et al. Mural lymphatic endothelial cells regulate meningeal angiogenesis in the zebrafish. Nat. Neurosci. 2017;20:774-783.
Not in our library10.1038/nn.4558 (opens in a new tab)
- 7.
Gunawan F, Gentile A, Gauvrit S, Stainier DYR, Bensimon-Brito A. Nfatc1 Promotes Interstitial Cell Formation During Cardiac Valve Development in Zebrafish. Circ. Res. 2020;126:968-984.
Not in our library10.1161/circresaha.119.315992 (opens in a new tab)
- 8.
Matsumoto T, Wakefield L, Tarlow BD, Grompe M. In Vivo Lineage Tracing of Polyploid Hepatocytes Reveals Extensive Proliferation during Liver Regeneration. Cell Stem Cell. 2020;26:34-47 e33.
Not in our library10.1016/j.stem.2019.11.014 (opens in a new tab)
- 9.
Chen F, et al. Broad Distribution of Hepatocyte Proliferation in Liver Homeostasis and Regeneration. Cell Stem Cell. 2020;26:27-33 e24.
Not in our library10.1016/j.stem.2019.11.001 (opens in a new tab)
- 10.
Schaub JR, et al. De novo formation of the biliary system by TGFbeta-mediated hepatocyte transdifferentiation. Nature. 2018;557:247-251.
Not in our library10.1038/s41586-018-0075-5 (opens in a new tab)
- 11.
Takahashi K, et al. Induction of pluripotent stem cells from adult human fibroblasts by defined factors. Cell. 2007;131:861-872.
Not in our library10.1016/j.cell.2007.11.019 (opens in a new tab)
- 12.
Saha S, et al. Aspirin Suppresses the Acquisition of Chemoresistance in Breast Cancer by Disrupting an NFkappaB-IL6 Signaling Axis Responsible for the Generation of Cancer Stem Cells. Cancer Res. 2016;76:2000-2012.
Not in our library10.1158/0008-5472.can-15-1360 (opens in a new tab)
- 13.
Francescangeli F, et al. A pre-existing population of ZEB2(+) quiescent cells with stemness and mesenchymal features dictate chemoresistance in colorectal cancer. J. Exp. Clin. Cancer Res. 2020;39:2.
Not in our library10.1186/s13046-019-1505-4 (opens in a new tab)
- 14.
Boumahdi S, de Sauvage FJ. The great escape: tumour cell plasticity in resistance to targeted therapy. Nat. Rev. Drug Discov. 2020;19:39-56.
Not in our library10.1038/s41573-019-0044-1 (opens in a new tab)
- 15.
- 16.
Shaffer SM, et al. Rare cell variability and drug-induced reprogramming as a mode of cancer drug resistance. Nature. 2017;546:431-435.
Not in our library10.1038/nature22794 (opens in a new tab)
- 17.
Kurata T, et al. Effect of re-treatment with gefitinib (‘Iressa’, ZD1839) after acquisition of resistance. Ann. Oncol. 2004;15:173-174.
Not in our library10.1093/annonc/mdh006 (opens in a new tab)
- 18.
Davies AH, Beltran H, Zoubeidi A. Cellular plasticity and the neuroendocrine phenotype in prostate cancer. Nat. Rev. Urol. 2018;15:271-286.
Not in our library10.1038/nrurol.2018.22 (opens in a new tab)
- 19.
Horn LA, Fousek K, Palena C. Tumor Plasticity and Resistance to Immunotherapy. Trends Cancer. 2020;6:432-441.
Not in our library10.1016/j.trecan.2020.02.001 (opens in a new tab)
- 20.
- 21.
Shibue T, Weinberg RA. EMT, CSCs, and drug resistance: the mechanistic link and clinical implications. Nat. Rev. Clin. Oncol. 2017;14:611-629.
Not in our library10.1038/nrclinonc.2017.44 (opens in a new tab)
- 22.
Hass R, von der Ohe J, Ungefroren H. The Intimate Relationship Among EMT, MET and TME: A T(ransdifferentiation) E(nhancing) M(ix) to Be Exploited for Therapeutic Purposes. Cancers (Basel). 2020;12:3674.
Not in our library10.3390/cancers12123674 (opens in a new tab)
- 23.
Gregory PA, et al. An autocrine TGF-beta/ZEB/miR-200 signaling network regulates establishment and maintenance of epithelial-mesenchymal transition. Mol. Biol. Cell. 2011;22:1686-1698.
Not in our library10.1091/mbc.e11-02-0103 (opens in a new tab)
- 24.
Siemens H, et al. miR-34 and SNAIL form a double-negative feedback loop to regulate epithelial-mesenchymal transitions. Cell Cycle. 2011;10:4256-4271.
Not in our library10.4161/cc.10.24.18552 (opens in a new tab)
- 25.
Martin P, et al. Prostate epithelial Pten/TP53 loss leads to transformation of multipotential progenitors and epithelial to mesenchymal transition. Am. J. Pathol. 2011;179:422-435.
Not in our library10.1016/j.ajpath.2011.03.035 (opens in a new tab)
- 26.
Yamasaki J, et al. MEK inhibition suppresses metastatic progression of KRAS-mutated gastric cancer. Cancer Sci. 2022;113:916-925.
Not in our library10.1111/cas.15244 (opens in a new tab)
- 27.
Luond F, et al. Distinct contributions of partial and full EMT to breast cancer malignancy. Dev. Cell. 2021;56:3203-3221 e3211.
Not in our library10.1016/j.devcel.2021.11.006 (opens in a new tab)
- 28.
Pastushenko I, et al. Identification of the tumour transition states occurring during EMT. Nature. 2018;556:463-468.
Not in our library10.1038/s41586-018-0040-3 (opens in a new tab)
- 29.
Lytle NK, Barber AG, Reya T. Stem cell fate in cancer growth, progression and therapy resistance. Nat. Rev. Cancer. 2018;18:669-680.
Not in our library10.1038/s41568-018-0056-x (opens in a new tab)
- 30.
Panchy N, Azeredo-Tseng C, Luo M, Randall N, Hong T. Integrative Transcriptomic Analysis Reveals a Multiphasic Epithelial-Mesenchymal Spectrum in Cancer and Non-tumorigenic Cells. Front. Oncol. 2019;9:1479.
Not in our library10.3389/fonc.2019.01479 (opens in a new tab)
- 31.
Bakir B, Chiarella AM, Pitarresi JR, Rustgi AK. EMT, MET, Plasticity, and Tumor Metastasis. Trends Cell Biol. 2020;30:764-776.
Not in our library10.1016/j.tcb.2020.07.003 (opens in a new tab)
- 32.
Yang J, et al. Twist, a master regulator of morphogenesis, plays an essential role in tumor metastasis. Cell. 2004;117:927-939.
Not in our library10.1016/j.cell.2004.06.006 (opens in a new tab)
- 33.
Addison JB, et al. Functional Hierarchy and Cooperation of EMT Master Transcription Factors in Breast Cancer Metastasis. Mol. Cancer Res. 2021;19:784-798.
Not in our library10.1158/1541-7786.mcr-20-0532 (opens in a new tab)
- 34.
Krebs AM, et al. The EMT-activator Zeb1 is a key factor for cell plasticity and promotes metastasis in pancreatic cancer. Nat. Cell Biol. 2017;19:518-529.
Not in our library10.1038/ncb3513 (opens in a new tab)
- 35.
Lambert AW, Pattabiraman DR, Weinberg RA. Emerging Biological Principles of Metastasis. Cell. 2017;168:670-691.
Not in our library10.1016/j.cell.2016.11.037 (opens in a new tab)
- 36.
Esposito M, et al. Bone vascular niche E-selectin induces mesenchymal-epithelial transition and Wnt activation in cancer cells to promote bone metastasis. Nat. Cell Biol. 2019;21:627-639.
Not in our library10.1038/s41556-019-0309-2 (opens in a new tab)
- 37.
Pastushenko I, Blanpain C. EMT Transition States during Tumor Progression and Metastasis. Trends Cell Biol. 2019;29:212-226.
Not in our library10.1016/j.tcb.2018.12.001 (opens in a new tab)
- 38.
- 39.
Culig Z. Epithelial mesenchymal transition and resistance in endocrine-related cancers. Biochim Biophys. Acta Mol. Cell Res. 2019;1866:1368-1375.
Not in our library10.1016/j.bbamcr.2019.05.003 (opens in a new tab)
- 40.
Byers LA, et al. An epithelial-mesenchymal transition gene signature predicts resistance to EGFR and PI3K inhibitors and identifies Axl as a therapeutic target for overcoming EGFR inhibitor resistance. Clin. Cancer Res. 2013;19:279-290.
Not in our library10.1158/1078-0432.ccr-12-1558 (opens in a new tab)
- 41.
Paulitschke V, et al. Proteomic identification of a marker signature for MAPKi resistance in melanoma. EMBO J. 2019;38:e95874.
Not in our library10.15252/embj.201695874 (opens in a new tab)
- 42.
Farmer P, et al. A stroma-related gene signature predicts resistance to neoadjuvant chemotherapy in breast cancer. Nat. Med. 2009;15:68-74.
Not in our library10.1038/nm.1908 (opens in a new tab)
- 43.
Zhang M, et al. Pyruvate dehydrogenase kinase 1 contributes to cisplatin resistance of ovarian cancer through EGFR activation. J. Cell. Physiol. 2019;234:6361-6370.
Not in our library10.1002/jcp.27369 (opens in a new tab)
- 44.
Liu M, Li S, Li MO. TGF-beta Control of Adaptive Immune Tolerance: A Break From Treg Cells. Bioessays. 2018;40:e1800063.
Not in our library10.1002/bies.201800063 (opens in a new tab)
- 45.
Viel S, et al. TGF-beta inhibits the activation and functions of NK cells by repressing the mTOR pathway. Sci. Signal. 2016;9:ra19.
Not in our library10.1126/scisignal.aad1884 (opens in a new tab)
- 46.
Saxena M, Stephens MA, Pathak H, Rangarajan A. Transcription factors that mediate epithelial-mesenchymal transition lead to multidrug resistance by upregulating ABC transporters. Cell Death Dis. 2011;2:e179.
Not in our library10.1038/cddis.2011.61 (opens in a new tab)
- 47.
Merrell AJ, Stanger BZ. Adult cell plasticity in vivo: de-differentiation and transdifferentiation are back in style. Nat. Rev. Mol. Cell Biol. 2016;17:413-425.
Not in our library10.1038/nrm.2016.24 (opens in a new tab)
- 48.
Rubin MA, Bristow RG, Thienger PD, Dive C, Imielinski M. Impact of Lineage Plasticity to and from a Neuroendocrine Phenotype on Progression and Response in Prostate and Lung Cancers. Mol. Cell. 2020;80:562-577.
Not in our library10.1016/j.molcel.2020.10.033 (opens in a new tab)
- 49.
Fang D, et al. A tumorigenic subpopulation with stem cell properties in melanomas. Cancer Res. 2005;65:9328-9337.
Not in our library10.1158/0008-5472.can-05-1343 (opens in a new tab)
- 50.
Tang JY, et al. Inhibition of the hedgehog pathway in patients with basal-cell nevus syndrome: final results from the multicentre, randomised, double-blind, placebo-controlled, phase 2 trial. Lancet Oncol. 2016;17:1720-1731.
Not in our library10.1016/s1470-2045(16)30566-6 (opens in a new tab)
- 51.
Sofen H, et al. A phase II, multicenter, open-label, 3-cohort trial evaluating the efficacy and safety of vismodegib in operable basal cell carcinoma. J. Am. Acad. Dermatol. 2015;73:99-105 e101.
Not in our library10.1016/j.jaad.2015.03.013 (opens in a new tab)
- 52.
Biehs B, et al. A cell identity switch allows residual BCC to survive Hedgehog pathway inhibition. Nature. 2018;562:429-433.
Not in our library10.1038/s41586-018-0596-y (opens in a new tab)
- 53.
Sanchez-Danes A, et al. A slow-cycling LGR5 tumour population mediates basal cell carcinoma relapse after therapy. Nature. 2018;562:434-438.
Not in our library10.1038/s41586-018-0603-3 (opens in a new tab)
- 54.
Konieczkowski DJ, Johannessen CM, Garraway LA. A Convergence-Based Framework for Cancer Drug Resistance. Cancer Cell. 2018;33:801-815.
Not in our library10.1016/j.ccell.2018.03.025 (opens in a new tab)
- 55.
Zou M, et al. Transdifferentiation as a Mechanism of Treatment Resistance in a Mouse Model of Castration-Resistant Prostate Cancer. Cancer Disco. 2017;7:736-749.
Not in our library10.1158/2159-8290.cd-16-1174 (opens in a new tab)
- 56.
Conteduca V, et al. Circulating tumor cell heterogeneity in neuroendocrine prostate cancer by single cell copy number analysis. NPJ Precis Oncol. 2021;5:76.
Not in our library10.1038/s41698-021-00211-1 (opens in a new tab)
- 57.
Epstein JI, et al. Proposed morphologic classification of prostate cancer with neuroendocrine differentiation. Am. J. Surg. Pathol. 2014;38:756-767.
Not in our library10.1097/pas.0000000000000208 (opens in a new tab)
- 58.
Conteduca V, et al. Clinical features of neuroendocrine prostate cancer. Eur. J. Cancer. 2019;121:7-18.
Not in our library10.1016/j.ejca.2019.08.011 (opens in a new tab)
- 59.
Wang Y, et al. Molecular events in neuroendocrine prostate cancer development. Nat. Rev. Urol. 2021;18:581-596.
Not in our library10.1038/s41585-021-00490-0 (opens in a new tab)
- 60.
Quintanal-Villalonga A, et al. Lineage plasticity in cancer: a shared pathway of therapeutic resistance. Nat. Rev. Clin. Oncol. 2020;17:360-371.
Not in our library10.1038/s41571-020-0340-z (opens in a new tab)
- 61.
Ku SY, et al. Rb1 and Trp53 cooperate to suppress prostate cancer lineage plasticity, metastasis, and antiandrogen resistance. Science. 2017;355:78-83.
Not in our library10.1126/science.aah4199 (opens in a new tab)
- 62.
Mu P, et al. SOX2 promotes lineage plasticity and antiandrogen resistance in TP53- and RB1-deficient prostate cancer. Science. 2017;355:84-88.
Not in our library10.1126/science.aah4307 (opens in a new tab)
- 63.
Svensson C, et al. REST mediates androgen receptor actions on gene repression and predicts early recurrence of prostate cancer. Nucleic Acids Res. 2014;42:999-1015.
Not in our library10.1093/nar/gkt921 (opens in a new tab)
- 64.
Merkens L, et al. Aggressive variants of prostate cancer: underlying mechanisms of neuroendocrine transdifferentiation. J. Exp. Clin. Cancer Res. 2022;41:46.
Not in our library10.1186/s13046-022-02255-y (opens in a new tab)
- 65.
- 66.
Balanis NG, et al. Pan-cancer Convergence to a Small-Cell Neuroendocrine Phenotype that Shares Susceptibilities with Hematological Malignancies. Cancer Cell. 2019;36:17-34.e17.
Not in our library10.1016/j.ccell.2019.06.005 (opens in a new tab)
- 67.
Ferrer L, et al. A Brief Report of Transformation From NSCLC to SCLC: Molecular and Therapeutic Characteristics. J. Thorac. Oncol. 2019;14:130-134.
Not in our library10.1016/j.jtho.2018.08.2028 (opens in a new tab)
- 68.
Oser MG, Niederst MJ, Sequist LV, Engelman JA. Transformation from non-small-cell lung cancer to small-cell lung cancer: molecular drivers and cells of origin. Lancet Oncol. 2015;16:e165-172.
Not in our library10.1016/s1470-2045(14)71180-5 (opens in a new tab)
- 69.
Lee JK, et al. Clonal History and Genetic Predictors of Transformation Into Small-Cell Carcinomas From Lung Adenocarcinomas. J. Clin. Oncol. 2017;35:3065-3074.
Not in our library10.1200/jco.2016.71.9096 (opens in a new tab)
- 70.
Offin M, et al. Concurrent RB1 and TP53 Alterations Define a Subset of EGFR-Mutant Lung Cancers at risk for Histologic Transformation and Inferior Clinical Outcomes. J. Thorac. Oncol. 2019;14:1784-1793.
Not in our library10.1016/j.jtho.2019.06.002 (opens in a new tab)
- 71.
Mahadevan NR, et al. Intrinsic Immunogenicity of Small Cell Lung Carcinoma Revealed by Its Cellular Plasticity. Cancer Disco. 2021;11:1952-1969.
Not in our library10.1158/2159-8290.cd-20-0913 (opens in a new tab)
- 72.
Shaurova T, Zhang L, Goodrich DW, Hershberger PA. Understanding Lineage Plasticity as a Path to Targeted Therapy Failure in EGFR-Mutant Non-small Cell Lung Cancer. Front Genet. 2020;11:281.
Not in our library10.3389/fgene.2020.00281 (opens in a new tab)
- 73.
- 74.
Das M, Law S. Role of tumor microenvironment in cancer stem cell chemoresistance and recurrence. Int. J. Biochem. Cell Biol. 2018;103:115-124.
Not in our library10.1016/j.biocel.2018.08.011 (opens in a new tab)
- 75.
- 76.
Kusienicka A, et al. Heme Oxygenase-1 Has a Greater Effect on Melanoma Stem Cell Properties Than the Expression of Melanoma-Initiating Cell Markers. Int. J. Mol. Sci. 2022;23:3596.
Not in our library10.3390/ijms23073596 (opens in a new tab)
- 77.
Lee WK, et al. Regulation of cancer stem cell activity by thyroid hormone receptor β. Oncogene. 2022;41:2315-2325.
Not in our library10.1038/s41388-022-02242-9 (opens in a new tab)
- 78.
- 79.
Correia C, et al. Uncovering Pharmacological Opportunities for Cancer Stem Cells-A Systems Biology View. Front Cell Dev. Biol. 2022;10:752326.
Not in our library10.3389/fcell.2022.752326 (opens in a new tab)
- 80.
Santoro A, Vlachou T, Carminati M, Pelicci PG, Mapelli M. Molecular mechanisms of asymmetric divisions in mammary stem cells. EMBO Rep. 2016;17:1700-1720.
Not in our library10.15252/embr.201643021 (opens in a new tab)
- 81.
- 82.
Najafi M, Mortezaee K, Ahadi R. Cancer stem cell (a)symmetry & plasticity: Tumorigenesis and therapy relevance. Life Sci. 2019;231:116520.
Not in our library10.1016/j.lfs.2019.05.076 (opens in a new tab)
- 83.
Wu M, et al. Imaging hematopoietic precursor division in real time. Cell Stem Cell. 2007;1:541-554.
Not in our library10.1016/j.stem.2007.08.009 (opens in a new tab)
- 84.
Liu D, et al. Asymmetric Division Gene Neurl2 Mediates Twist2 Regulation of Self-Renewal of Mouse Lewis Lung Cancer Stem Cells. J. Cancer. 2019;10:3381-3388.
Not in our library10.7150/jca.31553 (opens in a new tab)
- 85.
Poli V, Fagnocchi L, Zippo A. Tumorigenic Cell Reprogramming and Cancer Plasticity: Interplay between Signaling, Microenvironment, and Epigenetics. Stem Cells Int. 2018;2018:4598195.
Not in our library10.1155/2018/4598195 (opens in a new tab)
- 86.
- 87.
Grillet F, et al. Circulating tumour cells from patients with colorectal cancer have cancer stem cell hallmarks in ex vivo culture. Gut. 2017;66:1802-1810.
Not in our library10.1136/gutjnl-2016-311447 (opens in a new tab)
- 88.
Lambert AW, Weinberg RA. Linking EMT programmes to normal and neoplastic epithelial stem cells. Nat. Rev. Cancer. 2021;21:325-338.
Not in our library10.1038/s41568-021-00332-6 (opens in a new tab)
- 89.
Obermayr E, et al. Cancer Stem Cell-Like Circulating Tumor Cells Are Prognostic in Non-Small Cell Lung Cancer. J. Pers. Med. 2021;11:1225.
Not in our library10.3390/jpm11111225 (opens in a new tab)
- 90.
Jiang W, et al. Combating multidrug resistance and metastasis of breast cancer by endoplasmic reticulum stress and cell-nucleus penetration enhanced immunochemotherapy. Theranostics. 2022;12:2987-3006.
Not in our library10.7150/thno.71693 (opens in a new tab)
- 91.
Hirschmann-Jax C, et al. A distinct “side population” of cells with high drug efflux capacity in human tumor cells. Proc. Natl Acad. Sci. U. S. A. 2004;101:14228-14233.
Not in our library10.1073/pnas.0400067101 (opens in a new tab)
- 92.
Xu J, et al. Disruption of DNA Repair and Survival Pathways through Heat Shock Protein Inhibition by Onalespib to Sensitize Malignant Gliomas to Chemoradiation Therapy. Clin. Cancer Res. 2022;28:1979-1990.
Not in our library10.1158/1078-0432.ccr-20-0468 (opens in a new tab)
- 93.
Ouellette MM, Zhou S, Yan Y. Cell Signaling Pathways That Promote Radioresistance of Cancer Cells. Diagnostics (Basel). 2022;12:656.
Not in our library10.3390/diagnostics12030656 (opens in a new tab)
- 94.
Wozny AS, et al. Involvement of HIF-1alpha in the Detection, Signaling, and Repair of DNA Double-Strand Breaks after Photon and Carbon-Ion Irradiation. Cancers (Basel). 2021;13:3833.
Not in our library10.3390/cancers13153833 (opens in a new tab)
- 95.
Zaretsky JM, et al. Mutations Associated with Acquired Resistance to PD-1 Blockade in Melanoma. N. Engl. J. Med. 2016;375:819-829.
Not in our library10.1056/nejmoa1604958 (opens in a new tab)
- 96.
Su S, et al. CD10(+)GPR77(+) Cancer-Associated Fibroblasts Promote Cancer Formation and Chemoresistance by Sustaining Cancer Stemness. Cell. 2018;172:841-856 e816.
Not in our library10.1016/j.cell.2018.01.009 (opens in a new tab)
- 97.
Wang X, et al. Reciprocal Signaling between Glioblastoma Stem Cells and Differentiated Tumor Cells Promotes Malignant Progression. Cell Stem Cell. 2018;22:514-528.e515.
Not in our library10.1016/j.stem.2018.03.011 (opens in a new tab)
- 98.
Tammela T, et al. A Wnt-producing niche drives proliferative potential and progression in lung adenocarcinoma. Nature. 2017;545:355-359.
Not in our library10.1038/nature22334 (opens in a new tab)
- 99.
Guo L, Lee YT, Zhou Y, Huang Y. Targeting epigenetic regulatory machinery to overcome cancer therapy resistance. Semin. Cancer Biol. 2021;83:487-502.
Not in our library10.1016/j.semcancer.2020.12.022 (opens in a new tab)
- 100.
Tan T, et al. Epigenetic modification regulates tumor progression and metastasis through EMT (Review). Int. J. Oncol. 2022;60:70.
Not in our library10.3892/ijo.2022.5360 (opens in a new tab)
- 101.
Allis CD, Jenuwein T. The molecular hallmarks of epigenetic control. Nat. Rev. Genet. 2016;17:487-500.
Not in our library10.1038/nrg.2016.59 (opens in a new tab)
- 102.
Yosifov DY, et al. DNA methylation of chronic lymphocytic leukemia with differential response to chemotherapy. Sci. Data. 2020;7:133.
Not in our library10.1038/s41597-020-0456-0 (opens in a new tab)
- 103.
Cardenas H, et al. Methylomic Signatures of High Grade Serous Ovarian Cancer. Epigenetics. 2021;16:1201-1216.
Not in our library10.1080/15592294.2020.1853402 (opens in a new tab)
- 104.
Selli C, et al. Molecular changes during extended neoadjuvant letrozole treatment of breast cancer: distinguishing acquired resistance from dormant tumours. Breast Cancer Res. 2019;21:2.
Not in our library10.1186/s13058-018-1089-5 (opens in a new tab)
- 105.
- 106.
Reina-Campos M, et al. Increased Serine and One-Carbon Pathway Metabolism by PKClambda/iota Deficiency Promotes Neuroendocrine Prostate Cancer. Cancer Cell. 2019;35:385-400 e389.
Not in our library10.1016/j.ccell.2019.01.018 (opens in a new tab)
- 107.
Nachiyappan A, Gupta N, Taneja R. EHMT1/EHMT2 in EMT, cancer stemness and drug resistance: emerging evidence and mechanisms. FEBS J. 2022;289:1329-1351.
Not in our library10.1111/febs.16334 (opens in a new tab)
- 108.
Wang Z, et al. SETD5-Coordinated Chromatin Reprogramming Regulates Adaptive Resistance to Targeted Pancreatic Cancer Therapy. Cancer Cell. 2020;37:834-849 e813.
Not in our library10.1016/j.ccell.2020.04.014 (opens in a new tab)
- 109.
Knoechel B, et al. An epigenetic mechanism of resistance to targeted therapy in T cell acute lymphoblastic leukemia. Nat. Genet. 2014;46:364-370.
Not in our library10.1038/ng.2913 (opens in a new tab)
- 110.
Zawistowski JS, et al. Enhancer Remodeling during Adaptive Bypass to MEK Inhibition Is Attenuated by Pharmacologic Targeting of the P-TEFb Complex. Cancer Disco. 2017;7:302-321.
Not in our library10.1158/2159-8290.cd-16-0653 (opens in a new tab)
- 111.
Zheng X, et al. Epithelial-to-mesenchymal transition is dispensable for metastasis but induces chemoresistance in pancreatic cancer. Nature. 2015;527:525-530.
Not in our library10.1038/nature16064 (opens in a new tab)
- 112.
Yochum ZA, et al. Targeting the EMT transcription factor TWIST1 overcomes resistance to EGFR inhibitors in EGFR-mutant non-small-cell lung cancer. Oncogene. 2019;38:656-670.
Not in our library10.1038/s41388-018-0482-y (opens in a new tab)
- 113.
Dai C, Heemers H, Sharifi N. Androgen Signaling in Prostate Cancer. Cold Spring Harb. Perspect. Med. 2017;7:a030452.
Not in our library10.1101/cshperspect.a030452 (opens in a new tab)
- 114.
Masiello D, Cheng S, Bubley GJ, Lu ML, Balk SP. Bicalutamide functions as an androgen receptor antagonist by assembly of a transcriptionally inactive receptor. J. Biol. Chem. 2002;277:26321-26326.
Not in our library10.1074/jbc.m203310200 (opens in a new tab)
- 115.
Ito Y, Sadar MD. Enzalutamide and blocking androgen receptor in advanced prostate cancer: lessons learnt from the history of drug development of antiandrogens. Res Rep. Urol. 2018;10:23-32.
Not in our library10.2147/rru.s157116 (opens in a new tab)
- 116.
Fujita K, Nonomura N. Role of Androgen Receptor in Prostate Cancer: A Review. World J. Mens. Health. 2019;37:288-295.
Not in our library10.5534/wjmh.180040 (opens in a new tab)
- 117.
Lee H, Jeong AJ, Ye SK. Highlighted STAT3 as a potential drug target for cancer therapy. BMB Rep. 2019;52:415-423.
Not in our library10.5483/bmbrep.2019.52.7.152 (opens in a new tab)
- 118.
Wang H, et al. MicroRNA-181d-5p-Containing Exosomes Derived from CAFs Promote EMT by Regulating CDX2/HOXA5 in Breast Cancer. Mol. Ther. Nucleic Acids. 2020;19:654-667.
Not in our library10.1016/j.omtn.2019.11.024 (opens in a new tab)
- 119.
East MP, Johnson GL. Adaptive chromatin remodeling and transcriptional changes of the functional kinome in tumor cells in response to targeted kinase inhibition. J. Biol. Chem. 2022;298:101525.
Not in our library10.1016/j.jbc.2021.101525 (opens in a new tab)
- 120.
Wessely A, Steeb T, Berking C, Heppt MV. How Neural Crest Transcription Factors Contribute to Melanoma Heterogeneity, Cellular Plasticity, and Treatment Resistance. Int. J. Mol. Sci. 2021;22:5761.
Not in our library10.3390/ijms22115761 (opens in a new tab)
- 121.
Yang C, Tian C, Hoffman TE, Jacobsen NK, Spencer SL. Melanoma subpopulations that rapidly escape MAPK pathway inhibition incur DNA damage and rely on stress signalling. Nat. Commun. 2021;12:1747.
Not in our library10.1038/s41467-021-21549-x (opens in a new tab)
- 122.
Sachindra, et al. New role of ID3 in melanoma adaptive drug-resistance. Oncotarget. 2017;8:110166-110175.
Not in our library10.18632/oncotarget.22698 (opens in a new tab)
- 123.
Sun C, et al. Reversible and adaptive resistance to BRAF(V600E) inhibition in melanoma. Nature. 2014;508:118-122.
Not in our library10.1038/nature13121 (opens in a new tab)
- 124.
Hartman ML, Sztiller-Sikorska M, Gajos-Michniewicz A, Czyz M. Dissecting Mechanisms of Melanoma Resistance to BRAF and MEK Inhibitors Revealed Genetic and Non-Genetic Patient- and Drug-Specific Alterations and Remarkable Phenotypic Plasticity. Cells. 2020;9:142.
Not in our library10.3390/cells9010142 (opens in a new tab)
- 125.
Salaritabar A, et al. Targeting Hedgehog signaling pathway: Paving the road for cancer therapy. Pharmacol. Res. 2019;141:466-480.
Not in our library10.1016/j.phrs.2019.01.014 (opens in a new tab)
- 126.
Choi JI, et al. Cancer-initiating cells in human pancreatic cancer organoids are maintained by interactions with endothelial cells. Cancer Lett. 2021;498:42-53.
Not in our library10.1016/j.canlet.2020.10.012 (opens in a new tab)
- 127.
- 128.
Yang X, et al. Wnt signaling in triple-negative breast cancers: Its roles in molecular subtyping and cancer cell stemness and its crosstalk with non-coding RNAs. Life Sci. 2022;300:120565.
Not in our library10.1016/j.lfs.2022.120565 (opens in a new tab)
- 129.
Giroux-Leprieur E, Costantini A, Ding VW, He B. Hedgehog Signaling in Lung Cancer: From Oncogenesis to Cancer Treatment Resistance. Int. J. Mol. Sci. 2018;19:2835.
Not in our library10.3390/ijms19092835 (opens in a new tab)
- 130.
Bhateja P, Cherian M, Majumder S, Ramaswamy B. The Hedgehog Signaling Pathway: A Viable Target in Breast Cancer? Cancers (Basel). 2019;11:1126.
Not in our library10.3390/cancers11081126 (opens in a new tab)
- 131.
Monkkonen T, Lewis MT. New paradigms for the Hedgehog signaling network in mammary gland development and breast Cancer. Biochim Biophys. Acta Rev. Cancer. 2017;1868:315-332.
Not in our library10.1016/j.bbcan.2017.06.003 (opens in a new tab)
- 132.
Song J, et al. Noncoding RNAs related to the hedgehog pathway in cancer: clinical implications and future perspectives. Mol. Cancer. 2022;21:115.
Not in our library10.1186/s12943-022-01591-z (opens in a new tab)
- 133.
Cortes JE, Gutzmer R, Kieran MW, Solomon JA. Hedgehog signaling inhibitors in solid and hematological cancers. Cancer Treat. Rev. 2019;76:41-50.
Not in our library10.1016/j.ctrv.2019.04.005 (opens in a new tab)
- 134.
Xie Y, et al. Proteasome inhibitor induced SIRT1 deacetylates GLI2 to enhance hedgehog signaling activity and drug resistance in multiple myeloma. Oncogene. 2020;39:922-934.
Not in our library10.1038/s41388-019-1037-6 (opens in a new tab)
- 135.
Merchant AA, Matsui W. Targeting Hedgehog-a cancer stem cell pathway. Clin. Cancer Res. 2010;16:3130-3140.
Not in our library10.1158/1078-0432.ccr-09-2846 (opens in a new tab)
- 136.
- 137.
- 138.
Wang J, et al. Cinobufacini Inhibits Colon Cancer Invasion and Metastasis via Suppressing Wnt/β-Catenin Signaling Pathway and EMT. Am. J. Chin. Med. 2020;48:703-718.
Not in our library10.1142/s0192415x20500354 (opens in a new tab)
- 139.
Moon JH, Lee SH, Lim YC. Wnt/β-catenin/Slug pathway contributes to tumor invasion and lymph node metastasis in head and neck squamous cell carcinoma. Clin. Exp. Metastasis. 2021;38:163-174.
Not in our library10.1007/s10585-021-10081-3 (opens in a new tab)
- 140.
Sun Y, Song GD, Sun N, Chen JQ, Yang SS. Slug overexpression induces stemness and promotes hepatocellular carcinoma cell invasion and metastasis. Oncol. Lett. 2014;7:1936-1940.
Not in our library10.3892/ol.2014.2037 (opens in a new tab)
- 141.
- 142.
Howe LR, Watanabe O, Leonard J, Brown AM. Twist is up-regulated in response to Wnt1 and inhibits mouse mammary cell differentiation. Cancer Res. 2003;63:1906-1913.
Not in our library
- 143.
Zhu QQ, Ma C, Wang Q, Song Y, Lv T. The role of TWIST1 in epithelial-mesenchymal transition and cancers. Tumour Biol. 2016;37:185-197.
Not in our library10.1007/s13277-015-4450-7 (opens in a new tab)
- 144.
Liu X, et al. Cellular retinol binding protein-1 inhibits cancer stemness via upregulating WIF1 to suppress Wnt/beta-catenin pathway in hepatocellular carcinoma. BMC Cancer. 2021;21:1224.
Not in our library10.1186/s12885-021-08967-2 (opens in a new tab)
- 145.
Suda T, et al. Dickkopf-1 Promotes Angiogenesis and is a Biomarker for Hepatic Stem Cell-like Hepatocellular Carcinoma. Int. J. Mol. Sci. 2022;23:2801.
Not in our library10.3390/ijms23052801 (opens in a new tab)
- 146.
Rong L, Xu Y, Zhang K, Jin L, Liu X. HNRNPA2B1 inhibited SFRP2 and activated Wnt-beta/catenin via m6A-mediated miR-106b-5p processing to aggravate stemness in lung adenocarcinoma. Pathol. Res. Pract. 2022;233:153794.
Not in our library10.1016/j.prp.2022.153794 (opens in a new tab)
- 147.
Vermeulen L, et al. Wnt activity defines colon cancer stem cells and is regulated by the microenvironment. Nat. Cell Biol. 2010;12:468-476.
Not in our library10.1038/ncb2048 (opens in a new tab)
- 148.
Deldar Abad Paskeh M, Mirzaei S, Ashrafizadeh M, Zarrabi A, Sethi G. Wnt/β-Catenin Signaling as a Driver of Hepatocellular Carcinoma Progression: An Emphasis on Molecular Pathways. J. Hepatocell. Carcinoma. 2021;8:1415-1444.
Not in our library10.2147/jhc.s336858 (opens in a new tab)
- 149.
- 150.
Debeb BG, et al. Histone deacetylase inhibitors stimulate dedifferentiation of human breast cancer cells through WNT/β-catenin signaling. Stem Cells. 2012;30:2366-2377.
Not in our library10.1002/stem.1219 (opens in a new tab)
- 151.
De Santis F, et al. BCL6 and the Notch pathway: a signaling axis leading to a novel druggable biotarget in triple negative breast cancer. Cell. Oncol. (Dordr.). 2022;45:257-274.
Not in our library10.1007/s13402-022-00663-y (opens in a new tab)
- 152.
Buyuk B, Jin S, Ye K. Epithelial-to-Mesenchymal Transition Signaling Pathways Responsible for Breast Cancer Metastasis. Cell. Mol. Bioeng. 2022;15:1-13.
Not in our library10.1007/s12195-021-00694-9 (opens in a new tab)
- 153.
Wang LL, Wan XY, Liu CQ, Zheng FM. NDR1 increases NOTCH1 signaling activity by impairing Fbw7 mediated NICD degradation to enhance breast cancer stem cell properties. Mol. Med. 2022;28:49.
Not in our library10.1186/s10020-022-00480-x (opens in a new tab)
- 154.
Koba H, et al. NOTCH alteration in EGFR-mutated lung adenocarcinoma leads to histological small-cell carcinoma transformation under EGFR-TKI treatment. Transl. Lung Cancer Res. 2021;10:4161-4173.
Not in our library10.21037/tlcr-21-536 (opens in a new tab)
- 155.
Anobile DP, et al. Splicing deregulation, microRNA and notch aberrations: fighting the three-headed dog to overcome drug resistance in malignant mesothelioma. Expert Rev. Clin. Pharmacol. 2022;15:305-322.
Not in our library10.1080/17512433.2022.2074835 (opens in a new tab)
- 156.
Uramoto H, Shimokawa H, Hanagiri T, Kuwano M, Ono M. Expression of selected gene for acquired drug resistance to EGFR-TKI in lung adenocarcinoma. Lung Cancer. 2011;73:361-365.
Not in our library10.1016/j.lungcan.2011.01.008 (opens in a new tab)
- 157.
Xie M, et al. Activation of Notch-1 enhances epithelial-mesenchymal transition in gefitinib-acquired resistant lung cancer cells. J. Cell. Biochem. 2012;113:1501-1513.
Not in our library10.1002/jcb.24019 (opens in a new tab)
- 158.
- 159.
von Arx C, et al. Updates on the Role of Molecular Alterations and NOTCH Signalling in the Development of Neuroendocrine Neoplasms. J. Clin. Med. 2019;8:1277.
Not in our library10.3390/jcm8091277 (opens in a new tab)
- 160.
- 161.
Zeng D, et al. Inhibition of Notch1 reverses EMT and chemoresistance to cisplatin via direct downregulation of MCAM in triple-negative breast cancer cells. Int. J. Cancer. 2020;147:490-504.
Not in our library10.1002/ijc.32911 (opens in a new tab)
- 162.
Saad S, Stanners SR, Yong R, Tang O, Pollock CA. Notch mediated epithelial to mesenchymal transformation is associated with increased expression of the Snail transcription factor. Int. J. Biochem. Cell Biol. 2010;42:1115-1122.
Not in our library10.1016/j.biocel.2010.03.016 (opens in a new tab)
- 163.
Deshmukh AP, et al. Identification of EMT signaling cross-talk and gene regulatory networks by single-cell RNA sequencing. Proc. Natl Acad. Sci. U. S. A. 2021;118:e2102050118.
Not in our library10.1073/pnas.2102050118 (opens in a new tab)
- 164.
- 165.
Zheng X, Yu C, Xu M. Linking Tumor Microenvironment to Plasticity of Cancer Stem Cells: Mechanisms and Application in Cancer Therapy. Front. Oncol. 2021;11:678333.
Not in our library10.3389/fonc.2021.678333 (opens in a new tab)
- 166.
Capparelli C, et al. Targeting SOX10-deficient cells to reduce the dormant-invasive phenotype state in melanoma. Nat. Commun. 2022;13:1381.
Not in our library10.1038/s41467-022-28801-y (opens in a new tab)
- 167.
Zhou F, et al. Tumor Microenvironment-Activatable Prodrug Vesicles for Nanoenabled Cancer Chemoimmunotherapy Combining Immunogenic Cell Death Induction and CD47 Blockade. Adv. Mater. 2019;31:e1805888.
Not in our library10.1002/adma.201805888 (opens in a new tab)
- 168.
Kalluri R, Zeisberg M. Fibroblasts in cancer. Nat. Rev. Cancer. 2006;6:392-401.
Not in our library10.1038/nrc1877 (opens in a new tab)
- 169.
Luque M, et al. Targeted Therapy Modulates the Secretome of Cancer-Associated Fibroblasts to Induce Resistance in HER2-Positive Breast Cancer. Int. J. Mol. Sci. 2021;22:13297.
Not in our library10.3390/ijms222413297 (opens in a new tab)
- 170.
Huang TX, Guan XY, Fu L. Therapeutic targeting of the crosstalk between cancer-associated fibroblasts and cancer stem cells. Am. J. Cancer Res. 2019;9:1889-1904.
Not in our library
- 171.
- 172.
Yu Y, et al. Cancer-associated fibroblasts induce epithelial-mesenchymal transition of breast cancer cells through paracrine TGF-β signalling. Br. J. Cancer. 2014;110:724-732.
Not in our library10.1038/bjc.2013.768 (opens in a new tab)
- 173.
Luo H, Tu G, Liu Z, Liu M. Cancer-associated fibroblasts: a multifaceted driver of breast cancer progression. Cancer Lett. 2015;361:155-163.
Not in our library10.1016/j.canlet.2015.02.018 (opens in a new tab)
- 174.
Apicella M, et al. Increased Lactate Secretion by Cancer Cells Sustains Non-cell-autonomous Adaptive Resistance to MET and EGFR Targeted Therapies. Cell Metab. 2018;28:848-865 e846.
Not in our library10.1016/j.cmet.2018.08.006 (opens in a new tab)
- 175.
Gkountakos A, et al. Identification of Targetable Liabilities in the Dynamic Metabolic Profile of EGFR-Mutant Lung Adenocarcinoma: Thinking beyond Genomics for Overcoming EGFR TKI Resistance. Biomedicines. 2022;10:277.
Not in our library10.3390/biomedicines10020277 (opens in a new tab)
- 176.
Straussman R, et al. Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion. Nature. 2012;487:500-504.
Not in our library10.1038/nature11183 (opens in a new tab)
- 177.
Wilson TR, et al. Widespread potential for growth-factor-driven resistance to anticancer kinase inhibitors. Nature. 2012;487:505-509.
Not in our library10.1038/nature11249 (opens in a new tab)
- 178.
Mahaweni NM, Bos GMJ, Mitsiades CS, Tilanus MGJ, Wieten L. Daratumumab augments alloreactive natural killer cell cytotoxicity towards CD38+ multiple myeloma cell lines in a biochemical context mimicking tumour microenvironment conditions. Cancer Immunol. Immunother. 2018;67:861-872.
Not in our library10.1007/s00262-018-2140-1 (opens in a new tab)
- 179.
Ikeda S, Tagawa H. Impact of hypoxia on the pathogenesis and therapy resistance in multiple myeloma. Cancer Sci. 2021;112:3995-4004.
Not in our library10.1111/cas.15087 (opens in a new tab)
- 180.
Barr TA, et al. B cell depletion therapy ameliorates autoimmune disease through ablation of IL-6-producing B cells. J. Exp. Med. 2012;209:1001-1010.
Not in our library10.1084/jem.20111675 (opens in a new tab)
- 181.
Jung BG, et al. Early Secreted Antigenic Target of 6-kDa of Mycobacterium tuberculosis Stimulates IL-6 Production by Macrophages through Activation of STAT3. Sci. Rep. 2017;7:40984.
Not in our library10.1038/srep40984 (opens in a new tab)
- 182.
Shintani Y, et al. IL-6 Secreted from Cancer-Associated Fibroblasts Mediates Chemoresistance in NSCLC by Increasing Epithelial-Mesenchymal Transition Signaling. J. Thorac. Oncol. 2016;11:1482-1492.
Not in our library10.1016/j.jtho.2016.05.025 (opens in a new tab)
- 183.
- 184.
Ju X, et al. IL-6 regulates extracellular matrix remodeling associated with aortic dilation in a fibrillin-1 hypomorphic mgR/mgR mouse model of severe Marfan syndrome. J. Am. Heart Assoc. 2014;3:e000476.
Not in our library10.1161/jaha.113.000476 (opens in a new tab)
- 185.
Zoeller JJ, Bronson RT, Selfors LM, Mills GB, Brugge JS. Niche-localized tumor cells are protected from HER2-targeted therapy via upregulation of an anti-apoptotic program in vivo. NPJ Breast Cancer. 2017;3:18.
Not in our library10.1038/s41523-017-0020-z (opens in a new tab)
- 186.
Fu Y, et al. Abnormally activated OPN/integrin αVβ3/FAK signalling is responsible for EGFR-TKI resistance in EGFR mutant non-small-cell lung cancer. J. Hematol. Oncol. 2020;13:169.
Not in our library10.1186/s13045-020-01009-7 (opens in a new tab)
- 187.
Despeaux M, et al. Critical features of FAK-expressing AML bone marrow microenvironment through leukemia stem cell hijacking of mesenchymal stromal cells. Leukemia. 2011;25:1789-1793.
Not in our library10.1038/leu.2011.145 (opens in a new tab)
- 188.
Namba K, et al. Activation of AXL as a Preclinical Acquired Resistance Mechanism Against Osimertinib Treatment in EGFR-Mutant Non-Small Cell Lung Cancer Cells. Mol. Cancer Res. 2019;17:499-507.
Not in our library10.1158/1541-7786.mcr-18-0628 (opens in a new tab)
- 189.
Lee A-F, et al. Reverse epithelial-mesenchymal transition contributes to the regain of drug sensitivity in tyrosine kinase inhibitor-resistant non-small cell lung cancer cells. PLoS One. 2017;12:e0180383.
Not in our library10.1371/journal.pone.0180383 (opens in a new tab)
- 190.
Wu DM, et al. The PAX6-ZEB2 axis promotes metastasis and cisplatin resistance in non-small cell lung cancer through PI3K/AKT signaling. Cell Death Dis. 2019;10:349.
Not in our library10.1038/s41419-019-1591-4 (opens in a new tab)
- 191.
Raoof S, et al. Targeting FGFR overcomes EMT-mediated resistance in EGFR mutant non-small cell lung cancer. Oncogene. 2019;38:6399-6413.
Not in our library10.1038/s41388-019-0887-2 (opens in a new tab)
- 192.
Nieszporek A, Skrzypek K, Adamek G, Majka M. Molecular mechanisms of epithelial to mesenchymal transition in tumor metastasis. Acta Biochim. Pol. 2019;66:509-520.
Not in our library10.18388/abp.2019_2899 (opens in a new tab)
- 193.
Chang TH, et al. Slug confers resistance to the epidermal growth factor receptor tyrosine kinase inhibitor. Am. J. Respir. Crit. Care Med. 2011;183:1071-1079.
Not in our library10.1164/rccm.201009-1440oc (opens in a new tab)
- 194.
- 195.
- 196.
Santamaria PG, Moreno-Bueno G, Cano A. Contribution of Epithelial Plasticity to Therapy Resistance. J. Clin. Med. 2019;8:676.
Not in our library10.3390/jcm8050676 (opens in a new tab)
- 197.
Colak S, Ten Dijke P. Targeting TGF-β Signaling in Cancer. Trends Cancer. 2017;3:56-71.
Not in our library10.1016/j.trecan.2016.11.008 (opens in a new tab)
- 198.
Xu W, Yang Z, Lu N. A new role for the PI3K/Akt signaling pathway in the epithelial-mesenchymal transition. Cell Adh Migr. 2015;9:317-324.
Not in our library10.1080/19336918.2015.1016686 (opens in a new tab)
- 199.
Lee MK, et al. TGF-beta activates Erk MAP kinase signalling through direct phosphorylation of ShcA. EMBO J. 2007;26:3957-3967.
Not in our library10.1038/sj.emboj.7601818 (opens in a new tab)
- 200.
Katsuno Y, et al. Chronic TGF-β exposure drives stabilized EMT, tumor stemness, and cancer drug resistance with vulnerability to bitopic mTOR inhibition. Sci. Signal. 2019;12:eaau8544.
Not in our library10.1126/scisignal.aau8544 (opens in a new tab)
- 201.
Pan G, Liu Y, Shang L, Zhou F, Yang S. EMT-associated microRNAs and their roles in cancer stemness and drug resistance. Cancer Commun. (Lond.). 2021;41:199-217.
Not in our library10.1002/cac2.12138 (opens in a new tab)
- 202.
Zhang J, Ma L. MicroRNA control of epithelial-mesenchymal transition and metastasis. Cancer Metastasis Rev. 2012;31:653-662.
Not in our library10.1007/s10555-012-9368-6 (opens in a new tab)
- 203.
Li J, Yu H, Xi M, Ma D, Lu X. The SNAI1 3’UTR functions as a sponge for multiple migration-/invasion-related microRNAs. Tumour Biol. 2015;36:1067-1072.
Not in our library10.1007/s13277-014-2733-z (opens in a new tab)
- 204.
Xiao B, Shi X, Bai J. miR-30a regulates the proliferation and invasion of breast cancer cells by targeting Snail. Oncol. Lett. 2019;17:406-413.
Not in our library10.3892/ol.2018.9552 (opens in a new tab)
- 205.
Liu YN, et al. MiR-1 and miR-200 inhibit EMT via Slug-dependent and tumorigenesis via Slug-independent mechanisms. Oncogene. 2013;32:296-306.
Not in our library10.1038/onc.2012.58 (opens in a new tab)
- 206.
- 207.
Lu N, et al. miRNA‑490‑3p promotes the metastatic progression of invasive ductal carcinoma. Oncol. Rep. 2021;45:706-716.
Not in our library10.3892/or.2020.7880 (opens in a new tab)
- 208.
Li Y, Long X, Wang J, Peng J, Shen K. miRNA-128 modulates bone neoplasms cells proliferation and migration through the WNT/β-catenin and EMT signal pathways. J. Orthop. Surg. Res. 2021;16:71.
Not in our library10.1186/s13018-020-02164-w (opens in a new tab)
- 209.
Wang D, et al. MiRNA-155-5p inhibits epithelium-to-mesenchymal transition (EMT) by targeting GSK-3β during radiation-induced pulmonary fibrosis. Arch. Biochem. Biophys. 2021;697:108699.
Not in our library10.1016/j.abb.2020.108699 (opens in a new tab)
- 210.
Dagogo-Jack I, Shaw AT. Tumour heterogeneity and resistance to cancer therapies. Nat. Rev. Clin. Oncol. 2018;15:81-94.
Not in our library10.1038/nrclinonc.2017.166 (opens in a new tab)
- 211.
Fanelli GN, Naccarato AG, Scatena C. Recent Advances in Cancer Plasticity: Cellular Mechanisms, Surveillance Strategies, and Therapeutic Optimization. Front Oncol. 2020;10:569.
Not in our library10.3389/fonc.2020.00569 (opens in a new tab)
- 212.
- 213.
Nimmakayala RK, et al. Metabolic programming of distinct cancer stem cells promotes metastasis of pancreatic ductal adenocarcinoma. Oncogene. 2021;40:215-231.
Not in our library10.1038/s41388-020-01518-2 (opens in a new tab)
- 214.
Lei X, et al. Cancer stem cells in colorectal cancer and the association with chemotherapy resistance. Med. Oncol. 2021;38:43.
Not in our library10.1007/s12032-021-01488-9 (opens in a new tab)
- 215.
Lam K-H, Ma S. Noncellular components in the liver cancer stem cell niche: Biology and potential clinical implications. Hepatology. 2022;21:1-15.
Not in our library10.1002/hep.32629 (opens in a new tab)
- 216.
Quintana E, et al. Phenotypic heterogeneity among tumorigenic melanoma cells from patients that is reversible and not hierarchically organized. Cancer Cell. 2010;18:510-523.
Not in our library10.1016/j.ccr.2010.10.012 (opens in a new tab)
- 217.
Boiko AD, et al. Human melanoma-initiating cells express neural crest nerve growth factor receptor CD271. Nature. 2010;466:133-137.
Not in our library10.1038/nature09161 (opens in a new tab)
- 218.
Charles N, et al. Perivascular nitric oxide activates notch signaling and promotes stem-like character in PDGF-induced glioma cells. Cell Stem Cell. 2010;6:141-152.
Not in our library10.1016/j.stem.2010.01.001 (opens in a new tab)
- 219.
Nakano M, et al. Dedifferentiation process driven by TGF-beta signaling enhances stem cell properties in human colorectal cancer. Oncogene. 2019;38:780-793.
Not in our library10.1038/s41388-018-0480-0 (opens in a new tab)
- 220.
de Sousa e Melo F, et al. A distinct role for Lgr5+ stem cells in primary and metastatic colon cancer. Nature. 2017;543:676-680.
Not in our library10.1038/nature21713 (opens in a new tab)
- 221.
Oxnard GR, et al. Association Between Plasma Genotyping and Outcomes of Treatment With Osimertinib (AZD9291) in Advanced Non-Small-Cell Lung Cancer. J. Clin. Oncol. 2016;34:3375-3382.
Not in our library10.1200/jco.2016.66.7162 (opens in a new tab)
- 222.
- 223.
Suda K, et al. Heterogeneity in resistance mechanisms causes shorter duration of epidermal growth factor receptor kinase inhibitor treatment in lung cancer. Lung Cancer. 2016;91:36-40.
Not in our library10.1016/j.lungcan.2015.11.016 (opens in a new tab)
- 224.
Le Magnen C, Shen MM, Abate-Shen C. Lineage Plasticity in Cancer Progression and Treatment. Annu Rev. Cancer Biol. 2018;2:271-289.
Not in our library10.1146/annurev-cancerbio-030617-050224 (opens in a new tab)
- 225.
Easwaran H, et al. A DNA hypermethylation module for the stem/progenitor cell signature of cancer. Genome Res. 2012;22:837-849.
Not in our library10.1101/gr.131169.111 (opens in a new tab)
- 226.
Xiao Y, Yu D. Tumor microenvironment as a therapeutic target in cancer. Pharm. Ther. 2021;221:107753.
Not in our library10.1016/j.pharmthera.2020.107753 (opens in a new tab)
- 227.
Anderson NM, Simon MC. The tumor microenvironment. Curr. Biol. 2020;30:R921-r925.
Not in our library10.1016/j.cub.2020.06.081 (opens in a new tab)
- 228.
Hanahan D, Coussens LM. Accessories to the crime: functions of cells recruited to the tumor microenvironment. Cancer Cell. 2012;21:309-322.
Not in our library10.1016/j.ccr.2012.02.022 (opens in a new tab)
- 229.
- 230.
Lequeux A, et al. Impact of hypoxic tumor microenvironment and tumor cell plasticity on the expression of immune checkpoints. Cancer Lett. 2019;458:13-20.
Not in our library10.1016/j.canlet.2019.05.021 (opens in a new tab)
- 231.
Paolicchi E, et al. Targeting hypoxic response for cancer therapy. Oncotarget. 2016;7:13464-13478.
Not in our library10.18632/oncotarget.7229 (opens in a new tab)
- 232.
Bae HJ, Liu S, Jin P, Stroncek D. Mesenchymal stromal cell plasticity and the tumor microenvironment. Emerg. Top. Life Sci. 2017;1:487-492.
Not in our library10.1042/etls20170141 (opens in a new tab)
- 233.
- 234.
Reynolds TY, Rockwell S, Glazer PM. Genetic instability induced by the tumor microenvironment. Cancer Res. 1996;56:5754-5757.
Not in our library
- 235.
- 236.
Rambow F, et al. Toward minimal residual disease-directed therapy in melanoma. Cell. 2018;174:843-855. e819.
Not in our library10.1016/j.cell.2018.06.025 (opens in a new tab)
- 237.
- 238.
Tan C-S, Gilligan D, Pacey S. Treatment approaches for EGFR-inhibitor-resistant patients with non-small-cell lung cancer. Lancet Oncol. 2015;16:e447-e459.
Not in our library10.1016/s1470-2045(15)00246-6 (opens in a new tab)
- 239.
Winder M, Virós A. Mechanisms of drug resistance in melanoma. Handb. Exp. Pharm. 2018;249:91-108.
Not in our library10.1007/164_2017_17 (opens in a new tab)
- 240.
Sharma SV, et al. A chromatin-mediated reversible drug-tolerant state in cancer cell subpopulations. Cell. 2010;141:69-80.
Not in our library10.1016/j.cell.2010.02.027 (opens in a new tab)
- 241.
Ravindran Menon D, et al. A stress-induced early innate response causes multidrug tolerance in melanoma. Oncogene. 2015;34:4448-4459.
Not in our library10.1038/onc.2014.372 (opens in a new tab)
- 242.
Liau BB, et al. Adaptive chromatin remodeling drives glioblastoma stem cell plasticity and drug tolerance. cell stem cell. 2017;20:233-246. e237.
Not in our library10.1016/j.stem.2016.11.003 (opens in a new tab)
- 243.
Kruidenier L, et al. A selective jumonji H3K27 demethylase inhibitor modulates the proinflammatory macrophage response. Nature. 2012;488:404-408.
Not in our library10.1038/nature11262 (opens in a new tab)
- 244.
Heinemann B, et al. Inhibition of demethylases by GSK-J1/J4. Nature. 2014;514:E1-E2.
Not in our library10.1038/nature13688 (opens in a new tab)
- 245.
Johansson C, et al. Structural analysis of human KDM5B guides histone demethylase inhibitor development. Nat. Chem. Biol. 2016;12:539-545.
Not in our library10.1038/nchembio.2087 (opens in a new tab)
- 246.
Yang GJ, et al. Selective inhibition of lysine‐specific demethylase 5A (KDM5A) using a rhodium (III) complex for triple‐negative breast cancer therapy. Angew. Chem. Int Ed. Engl. 2018;57:13091-13095.
Not in our library10.1002/anie.201807305 (opens in a new tab)
- 247.
Liu J, et al. Targeting Wnt-driven cancer through the inhibition of Porcupine by LGK974. Proc. Natl Acad. Sci. U. S. A. 2013;110:20224-20229.
Not in our library10.1073/pnas.1314239110 (opens in a new tab)
- 248.
Liang X, Lin A, Wang Q, Zhang J, Luo P. Cell plasticity in patients with NSCLC: The controversial origins of transformed SCLC. Biomed. Pharmacother. 2022;149:112909.
Not in our library10.1016/j.biopha.2022.112909 (opens in a new tab)
- 249.
Marcoux N, et al. EGFR-mutant adenocarcinomas that transform to small-cell lung cancer and other neuroendocrine carcinomas: clinical outcomes. J. Clin. Oncol. 2019;37:278.
Not in our library10.1200/jco.18.01585 (opens in a new tab)
- 250.
Hangauer MJ, et al. Drug-tolerant persister cancer cells are vulnerable to GPX4 inhibition. Nature. 2017;551:247-250.
Not in our library10.1038/nature24297 (opens in a new tab)
- 251.
Friedmann Angeli JP, et al. Inactivation of the ferroptosis regulator Gpx4 triggers acute renal failure in mice. Nat. Cell Biol. 2014;16:1180-1191.
Not in our library10.1038/ncb3064 (opens in a new tab)
- 252.
Yoo S-E, et al. Gpx4 ablation in adult mice results in a lethal phenotype accompanied by neuronal loss in brain. Free Radic. Biol. Med. 2012;52:1820-1827.
Not in our library10.1016/j.freeradbiomed.2012.02.043 (opens in a new tab)
- 253.
Eaton JK, et al. Selective covalent targeting of GPX4 using masked nitrile-oxide electrophiles. Nat. Chem. Biol. 2020;16:497-506.
Not in our library10.1038/s41589-020-0501-5 (opens in a new tab)
- 254.
- 255.
Voon DC, Huang RY, Jackson RA, Thiery JP. The EMT spectrum and therapeutic opportunities. Mol. Oncol. 2017;11:878-891.
Not in our library10.1002/1878-0261.12082 (opens in a new tab)
- 256.
- 257.
Hasan T, et al. Interleukin-8/CXCR2 signaling regulates therapy-induced plasticity and enhances tumorigenicity in glioblastoma. Cell Death Dis. 2019;10:1-17.
Not in our library10.1038/s41419-019-1387-6 (opens in a new tab)
- 258.
Fousek K, Horn LA, Palena C. Interleukin-8: A chemokine at the intersection of cancer plasticity, angiogenesis, and immune suppression. Pharmacol. Ther. 2021;219:107692.
Not in our library10.1016/j.pharmthera.2020.107692 (opens in a new tab)
- 259.
Xiao P, et al. Neurotensin/IL-8 pathway orchestrates local inflammatory response and tumor invasion by inducing M2 polarization of Tumor-Associated macrophages and epithelial-mesenchymal transition of hepatocellular carcinoma cells. Oncoimmunology. 2018;7:e1440166.
Not in our library10.1080/2162402x.2018.1440166 (opens in a new tab)
- 260.
Kahraman DC, Kahraman T, Cetin-Atalay R. Targeting PI3K/Akt/mTOR pathway identifies differential expression and functional role of IL8 in liver cancer stem cell enrichment. Mol. Cancer Ther. 2019;18:2146-2157.
Not in our library10.1158/1535-7163.mct-19-0004 (opens in a new tab)
- 261.
Dominguez C, McCampbell KK, David JM, Palena C. Neutralization of IL-8 decreases tumor PMN-MDSCs and reduces mesenchymalization of claudin-low triple-negative breast cancer. JCI insight. 2017;2:e94296.
Not in our library10.1172/jci.insight.94296 (opens in a new tab)
- 262.
Fernando RI, et al. IL-8 signaling is involved in resistance of lung carcinoma cells to erlotinib. Oncotarget. 2016;7:42031.
Not in our library10.18632/oncotarget.9662 (opens in a new tab)
- 263.
Devapatla B, Sharma A, Woo S. CXCR2 inhibition combined with sorafenib improved antitumor and antiangiogenic response in preclinical models of ovarian cancer. PLoS One. 2015;10:e0139237.
Not in our library10.1371/journal.pone.0139237 (opens in a new tab)
- 264.
Xu J, Lamouille S, Derynck R. TGF-β-induced epithelial to mesenchymal transition. Cell Res. 2009;19:156-172.
Not in our library10.1038/cr.2009.5 (opens in a new tab)
- 265.
- 266.
Massagué J. TGFβ signalling in context. Nat. Rev. Mol. 2012;13:616-630.
Not in our library10.1038/nrm3434 (opens in a new tab)
- 267.
Akhurst RJ, Hata A. Targeting the TGFβ signalling pathway in disease. Nat. Rev. Drug Disco. 2012;11:790-811.
Not in our library10.1038/nrd3810 (opens in a new tab)
- 268.
de Gramont A, Faivre S, Raymond E. Novel TGF-β inhibitors ready for prime time in onco-immunology. Oncoimmunology. 2017;6:e1257453.
Not in our library10.1080/2162402x.2016.1257453 (opens in a new tab)
- 269.
Pattabiraman DR, et al. Activation of PKA leads to mesenchymal-to-epithelial transition and loss of tumor-initiating ability. Science. 2016;351:aad3680.
Not in our library10.1126/science.aad3680 (opens in a new tab)
- 270.
- 271.
- 272.
- 273.
Xing Y, et al. Therapeutic efficacy and mechanism of CD73-TGFβ dual-blockade in a mouse model of triple-negative breast cancer. Acta Pharmacol. Sin. 2022;43:2410-2418.
Not in our library10.1038/s41401-021-00840-z (opens in a new tab)
- 274.
- 275.
Gallardo A, et al. EZH2 endorses cell plasticity to carcinoma cells facilitating mesenchymal to epithelial transition and tumour colonization. Oncogene. 2022;41:3611-3624.
Not in our library10.1038/s41388-022-02375-x (opens in a new tab)
- 276.
Dardenne E, et al. N-Myc induces an EZH2-mediated transcriptional program driving neuroendocrine prostate cancer. Cancer Cell. 2016;30:563-577.
Not in our library10.1016/j.ccell.2016.09.005 (opens in a new tab)
- 277.
Knutson SK, et al. Selective inhibition of EZH2 by EPZ-6438 leads to potent antitumor activity in EZH2-mutant non-Hodgkin lymphoma. Mol. Cancer Ther. 2014;13:842-854.
Not in our library10.1158/1535-7163.mct-13-0773 (opens in a new tab)
- 278.
Vaswani RG, et al. Identification of (R)-N-((4-Methoxy-6-methyl-2-oxo-1, 2-dihydropyridin-3-yl) methyl)-2-methyl-1-(1-(1-(2,2,2-trifluoroethyl) piperidin-4-yl) ethyl)-1 H-indole-3-carboxamide (CPI-1205), a Potent and Selective Inhibitor of Histone Methyltransferase EZH2, Suitable for Phase I Clinical Trials for B-Cell Lymphomas. J. Med. Chem. 2016;59:9928-9941.
Not in our library10.1021/acs.jmedchem.6b01315 (opens in a new tab)
- 279.
- 280.
Igarashi K, Nishizawa H, Saiki Y, Matsumoto M. The transcription factor BACH1 at the crossroads of cancer biology: From epithelial-mesenchymal transition to ferroptosis. J. Biol. Chem. 2021;297:101032.
Not in our library10.1016/j.jbc.2021.101032 (opens in a new tab)
- 281.
Xie J, et al. Targeting cancer cell plasticity by HDAC inhibition to reverse EBV-induced dedifferentiation in nasopharyngeal carcinoma. Signal Transduct. Target Ther. 2021;6:333.
Not in our library10.1038/s41392-021-00702-4 (opens in a new tab)
- 282.
Liu Y, et al. Yap-Sox9 signaling determines hepatocyte plasticity and lineage-specific hepatocarcinogenesis. J. Hepatol. 2022;76:652-664.
Not in our library10.1016/j.jhep.2021.11.010 (opens in a new tab)
- 283.
Pei J, et al. Targeting lysosomal degradation pathways: new strategies and techniques for drug discovery. J. Med. Chem. 2021;64:3493-3507.
Not in our library10.1021/acs.jmedchem.0c01689 (opens in a new tab)
- 284.
Sievers QL, et al. Defining the human C2H2 zinc finger degrome targeted by thalidomide analogs through CRBN. Science. 2018;362:eaat0572.
Not in our library10.1126/science.aat0572 (opens in a new tab)
- 285.
Kong F-E, et al. Targeting tumor lineage plasticity in hepatocellular carcinoma using an anti-CLDN6 antibody-drug conjugate. Sci. Transl. Med. 2021;13:eabb6282.
Not in our library10.1126/scitranslmed.abb6282 (opens in a new tab)
- 286.
Huang F, et al. Inhibiting the MNK1/2-eIF4E axis impairs melanoma phenotype switching and potentiates antitumor immune responses. J. Clin. Investig. 2021;131:e140752.
Not in our library10.1172/jci140752 (opens in a new tab)
- 287.
- 288.
Lou Y, et al. Epithelial-Mesenchymal Transition Is Associated with a Distinct Tumor Microenvironment Including Elevation of Inflammatory Signals and Multiple Immune Checkpoints in Lung Adenocarcinoma. Clin. Cancer Res. 2016;22:3630-3642.
Not in our library10.1158/1078-0432.ccr-15-1434 (opens in a new tab)
- 289.
Wu T, et al. PD-L1-Mediated Immunosuppression in Oral Squamous Cell Carcinoma: Relationship With Macrophage Infiltration and Epithelial to Mesenchymal Transition Markers. Front. Immunol. 2021;12:693881.
Not in our library10.3389/fimmu.2021.693881 (opens in a new tab)
- 290.
Guo Y, et al. Zeb1 induces immune checkpoints to form an immunosuppressive envelope around invading cancer cells. Sci. Adv. 2021;7:eabd7455.
Not in our library10.1126/sciadv.abd7455 (opens in a new tab)
- 291.
Zhao K, et al. TIGIT blockade enhances tumor response to radiotherapy via a CD103 + dendritic cell-dependent mechanism. Cancer Immunol. Immunother. 2023;72:193-209.
Not in our library10.1007/s00262-022-03227-z (opens in a new tab)
- 292.
Mahmoudian RA, et al. Correlation between the immune checkpoints and EMT genes proposes potential prognostic and therapeutic targets in ESCC. J. Mol. Histol. 2021;52:597-609.
Not in our library10.1007/s10735-021-09971-3 (opens in a new tab)
- 293.
Chen X, et al. eEF2K promotes PD-L1 stabilization through inactivating GSK3β in melanoma. J. Immunother. Cancer. 2022;10:e004026.
Not in our library10.1136/jitc-2021-004026 (opens in a new tab)
- 294.
Wu Y, et al. Effect of ISM1 on the Immune Microenvironment and Epithelial-Mesenchymal Transition in Colorectal Cancer. Front Cell Dev. Biol. 2021;9:681240.
Not in our library10.3389/fcell.2021.681240 (opens in a new tab)
- 295.
Dongre A, et al. Epithelial-to-Mesenchymal Transition Contributes to Immunosuppression in Breast Carcinomas. Cancer Res. 2017;77:3982-3989.
Not in our library10.1158/0008-5472.can-16-3292 (opens in a new tab)
- 296.
Wu Q, et al. MAGE-C3 promotes cancer metastasis by inducing epithelial-mesenchymal transition and immunosuppression in esophageal squamous cell carcinoma. Cancer Commun. (Lond.). 2021;41:1354-1372.
Not in our library10.1002/cac2.12203 (opens in a new tab)
- 297.
Kim S, et al. PD-L1 expression is associated with epithelial-to-mesenchymal transition in adenocarcinoma of the lung. Hum. Pathol. 2016;58:7-14.
Not in our library10.1016/j.humpath.2016.07.007 (opens in a new tab)
- 298.
Cui M, et al. Development and Validation of a Tumor Mutation Burden-Related Immune Prognostic Signature for Ovarian Cancers. Front Genet. 2021;12:688207.
Not in our library10.3389/fgene.2021.688207 (opens in a new tab)
- 299.
Cao L, et al. Exploring Immune-Related Prognostic Signatures in the Tumor Microenvironment of Colon Cancer. Front Genet. 2022;13:801484.
Not in our library10.3389/fgene.2022.801484 (opens in a new tab)
- 300.
Song J, et al. Pan-cancer analysis reveals RIPK2 predicts prognosis and promotes immune therapy resistance via triggering cytotoxic T lymphocytes dysfunction. Mol. Med. 2022;28:47.
Not in our library10.1186/s10020-022-00475-8 (opens in a new tab)
- 301.
Yang CY, et al. Association between programmed death-ligand 1 expression, immune microenvironments, and clinical outcomes in epidermal growth factor receptor mutant lung adenocarcinoma patients treated with tyrosine kinase inhibitors. Eur. J. Cancer. 2020;124:110-122.
Not in our library10.1016/j.ejca.2019.10.019 (opens in a new tab)
- 302.
Isomoto K, et al. Impact of EGFR-TKI Treatment on the Tumor Immune Microenvironment in EGFR Mutation-Positive Non-Small Cell Lung Cancer. Clin. Cancer Res. 2020;26:2037-2046.
Not in our library10.1158/1078-0432.ccr-19-2027 (opens in a new tab)
- 303.
Haratani K, et al. Tumor immune microenvironment and nivolumab efficacy in EGFR mutation-positive non-small-cell lung cancer based on T790M status after disease progression during EGFR-TKI treatment. Ann. Oncol. 2017;28:1532-1539.
Not in our library10.1093/annonc/mdx183 (opens in a new tab)
- 304.
Jia Y, et al. EGFR-targeted therapy alters the tumor microenvironment in EGFR-driven lung tumors: Implications for combination therapies. Int. J. Cancer. 2019;145:1432-1444.
Not in our library10.1002/ijc.32191 (opens in a new tab)
- 305.
Tian T, et al. Front-Line ICI-Based Combination Therapy Post-TKI Resistance May Improve Survival in NSCLC Patients With EGFR Mutation. Front. Oncol. 2021;11:739090.
Not in our library10.3389/fonc.2021.739090 (opens in a new tab)
- 306.
Chen Y, et al. Immunotherapy-based combination strategies for treatment of EGFR-TKI-resistant non-small-cell lung cancer. Future Oncol. 2022;18:1757-1775.
Not in our library10.2217/fon-2021-0862 (opens in a new tab)
- 307.
- 308.
Liu S, et al. Patients With Short PFS to EGFR-TKIs Predicted Better Response to Subsequent Anti-PD-1/PD-L1 Based Immunotherapy in EGFR Common Mutation NSCLC. Front. Oncol. 2021;11:639947.
Not in our library10.3389/fonc.2021.639947 (opens in a new tab)
- 309.
Greten TF, Lai CW, Li G, Staveley-O’Carroll KF. Targeted and Immune-Based Therapies for Hepatocellular Carcinoma. Gastroenterology. 2019;156:510-524.
Not in our library10.1053/j.gastro.2018.09.051 (opens in a new tab)
- 310.
Shemesh CS, et al. Atezolizumab and Bevacizumab in Patients with Unresectable Hepatocellular Carcinoma: Pharmacokinetic and Safety Assessments Based on Hepatic Impairment Status and Geographic Region. Liver Cancer. 2021;10:485-499.
Not in our library10.1159/000515817 (opens in a new tab)
- 311.
Qin S, et al. Atezolizumab plus Bevacizumab versus Sorafenib in the Chinese Subpopulation with Unresectable Hepatocellular Carcinoma: Phase 3 Randomized, Open-Label IMbrave150 Study. Liver Cancer. 2021;10:296-308.
Not in our library10.1159/000513486 (opens in a new tab)
- 312.
Rizzo A, Ricci AD, Gadaleta-Caldarola G, Brandi G. First-line immune checkpoint inhibitor-based combinations in unresectable hepatocellular carcinoma: current management and future challenges. Expert Rev. Gastroenterol. Hepatol. 2021;15:1245-1251.
Not in our library10.1080/17474124.2021.1973431 (opens in a new tab)
- 313.
Cheng AL, et al. Updated efficacy and safety data from IMbrave150: Atezolizumab plus bevacizumab vs. sorafenib for unresectable hepatocellular carcinoma. J. Hepatol. 2022;76:862-873.
Not in our library10.1016/j.jhep.2021.11.030 (opens in a new tab)
- 314.
Tang Z, et al. ATR Inhibition Induces CDK1-SPOP Signaling and Enhances Anti-PD-L1 Cytotoxicity in Prostate Cancer. Clin. Cancer Res. 2021;27:4898-4909.
Not in our library10.1158/1078-0432.ccr-21-1010 (opens in a new tab)
- 315.
- 316.
Guan X, et al. Androgen receptor activity in T cells limits checkpoint blockade efficacy. Nature. 2022;606:791-796.
Not in our library10.1038/s41586-022-04522-6 (opens in a new tab)
- 317.
Wang Y, Ma X, Wei Y, Ma D, Gong P. Effect of platinum-based chemotherapy on EGFR gene mutation status in lung adenocarcinoma. Med. (Baltim.). 2018;97:e9602.
Not in our library10.1097/md.0000000000009602 (opens in a new tab)
- 318.
Leonetti A, et al. Molecular basis and rationale for combining immune checkpoint inhibitors with chemotherapy in non-small cell lung cancer. Drug Resist Updat. 2019;46:100644.
Not in our library10.1016/j.drup.2019.100644 (opens in a new tab)
- 319.
Borghaei H, et al. Pembrolizumab plus chemotherapy versus chemotherapy alone in patients with advanced non-small cell lung cancer without tumor PD-L1 expression: A pooled analysis of 3 randomized controlled trials. Cancer. 2020;126:4867-4877.
Not in our library10.1002/cncr.33142 (opens in a new tab)
- 320.
Zhang J, et al. MA11.06 A PII Study of Toripalimab, a PD-1 mAb, in Combination with Chemotherapy in EGFR+ Advanced NSCLC Patients Failed to Prior EGFR TKI Therapies. J. Thorac. Oncol. 2019;14:s292.
Not in our library10.1016/j.jtho.2019.08.587 (opens in a new tab)
- 321.
Reck M, et al. Atezolizumab plus bevacizumab and chemotherapy in non-small-cell lung cancer (IMpower150): key subgroup analyses of patients with EGFR mutations or baseline liver metastases in a randomised, open-label phase 3 trial. Lancet Respir. Med. 2019;7:387-401.
Not in our library10.1016/s2213-2600(19)30084-0 (opens in a new tab)
- 322.
Janjigian YY, et al. First-line nivolumab plus chemotherapy versus chemotherapy alone for advanced gastric, gastro-oesophageal junction, and oesophageal adenocarcinoma (CheckMate 649): a randomised, open-label, phase 3 trial. Lancet. 2021;398:27-40.
Not in our library10.1016/s0140-6736(21)00797-2 (opens in a new tab)
- 323.
Janjigian YY, et al. The KEYNOTE-811 trial of dual PD-1 and HER2 blockade in HER2-positive gastric cancer. Nature. 2021;600:727-730.
Not in our library10.1038/s41586-021-04161-3 (opens in a new tab)
- 324.
Miles D, et al. Primary results from IMpassion131, a double-blind, placebo-controlled, randomised phase III trial of first-line paclitaxel with or without atezolizumab for unresectable locally advanced/metastatic triple-negative breast cancer. Ann. Oncol. 2021;32:994-1004.
Not in our library10.1016/j.annonc.2021.05.801 (opens in a new tab)
- 325.
Schmid P, et al. Atezolizumab and Nab-Paclitaxel in Advanced Triple-Negative Breast Cancer. N. Engl. J. Med. 2018;379:2108-2121.
Not in our library10.1056/nejmoa1809615 (opens in a new tab)
- 326.
Zhang Y, et al. Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancer. Cancer Cell. 2021;39:1578-1593 e1578.
Not in our library10.1016/j.ccell.2021.09.010 (opens in a new tab)
- 327.
Lu Q, et al. Bioengineered Platelets Combining Chemotherapy and Immunotherapy for Postsurgical Melanoma Treatment: Internal Core-Loaded Doxorubicin and External Surface-Anchored Anti-PD-L1 Antibody Backpacks. Nano Lett. 2022;22:3141-3150.
Not in our library10.1021/acs.nanolett.2c00907 (opens in a new tab)
- 328.
Ahn MJ, Sun JM, Lee SH, Ahn JS, Park K. EGFR TKI combination with immunotherapy in non-small cell lung cancer. Expert Opin. Drug Saf. 2017;16:465-469.
Not in our library10.1080/14740338.2017.1300656 (opens in a new tab)
- 329.
Yang JC, et al. Osimertinib Plus Durvalumab versus Osimertinib Monotherapy in EGFR T790M-Positive NSCLC following Previous EGFR TKI Therapy: CAURAL Brief Report. J. Thorac. Oncol. 2019;14:933-939.
Not in our library10.1016/j.jtho.2019.02.001 (opens in a new tab)
- 330.
Oxnard GR, et al. TATTON: a multi-arm, phase Ib trial of osimertinib combined with selumetinib, savolitinib, or durvalumab in EGFR-mutant lung cancer. Ann. Oncol. 2020;31:507-516.
Not in our library10.1016/j.annonc.2020.01.013 (opens in a new tab)
- 331.
Oshima Y, Tanimoto T, Yuji K, Tojo A. EGFR-TKI-Associated Interstitial Pneumonitis in Nivolumab-Treated Patients With Non-Small Cell Lung Cancer. JAMA Oncol. 2018;4:1112-1115.
Not in our library10.1001/jamaoncol.2017.4526 (opens in a new tab)
- 332.
Jia Y, et al. Impact of EGFR-TKIs combined with PD-L1 antibody on the lung tissue of EGFR-driven tumor-bearing mice. Lung Cancer. 2019;137:85-93.
Not in our library10.1016/j.lungcan.2019.09.016 (opens in a new tab)
- 333.
Schoenfeld AJ, et al. Severe immune-related adverse events are common with sequential PD-(L)1 blockade and osimertinib. Ann. Oncol. 2019;30:839-844.
Not in our library10.1093/annonc/mdz077 (opens in a new tab)
- 334.
Ribas A, Hodi FS, Callahan M, Konto C, Wolchok J. Hepatotoxicity with combination of vemurafenib and ipilimumab. N. Engl. J. Med. 2013;368:1365-1366.
Not in our library10.1056/nejmc1302338 (opens in a new tab)
- 335.
Yu Y. Multi-target combinatory strategy to overcome tumor immune escape. Front. Med. 2022;16:208-215.
Not in our library10.1007/s11684-022-0922-5 (opens in a new tab)
- 336.
Wolchok JD, et al. Overall Survival with Combined Nivolumab and Ipilimumab in Advanced Melanoma. N. Engl. J. Med. 2017;377:1345-1356.
Not in our library10.1056/nejmoa1709684 (opens in a new tab)
- 337.
Kariolis MS, et al. Inhibition of the GAS6/AXL pathway augments the efficacy of chemotherapies. J. Clin. Invest. 2017;127:183-198.
Not in our library10.1172/jci85610 (opens in a new tab)
- 338.
Leconet W, et al. Therapeutic Activity of Anti-AXL Antibody against Triple-Negative Breast Cancer Patient-Derived Xenografts and Metastasis. Clin. Cancer Res. 2017;23:2806-2816.
Not in our library10.1158/1078-0432.ccr-16-1316 (opens in a new tab)
- 339.
- 340.
Yu M, et al. YAP1 contributes to NSCLC invasion and migration by promoting Slug transcription via the transcription co-factor TEAD. Cell Death Dis. 2018;9:464.
Not in our library10.1038/s41419-018-0515-z (opens in a new tab)
- 341.
- 342.
Scherschinski L, et al. Regulation of the Receptor Tyrosine Kinase AXL in Response to Therapy and Its Role in Therapy Resistance in Glioblastoma. Int. J. Mol. Sci. 2022;23:982.
Not in our library10.3390/ijms23020982 (opens in a new tab)
- 343.
Shen Y, Chen X, He J, Liao D, Zu X. Axl inhibitors as novel cancer therapeutic agents. Life Sci. 2018;198:99-111.
Not in our library10.1016/j.lfs.2018.02.033 (opens in a new tab)
- 344.
Myers SH, Brunton VG, Unciti-Broceta A. AXL Inhibitors in Cancer: A Medicinal Chemistry Perspective. J. Med. Chem. 2016;59:3593-3608.
Not in our library10.1021/acs.jmedchem.5b01273 (opens in a new tab)
- 345.
Wang J, et al. Ginsenoside Rg3 sensitizes hypoxic lung cancer cells to cisplatin via blocking of NF-κB mediated epithelial-mesenchymal transition and stemness. Cancer Lett. 2018;415:73-85.
Not in our library10.1016/j.canlet.2017.11.037 (opens in a new tab)
- 346.
Wang C, et al. Tumor-derived secretory clusterin induces epithelial-mesenchymal transition and facilitates hepatocellular carcinoma metastasis. Int. J. Biochem. Cell Biol. 2012;44:2308-2320.
Not in our library10.1016/j.biocel.2012.09.012 (opens in a new tab)
- 347.
Praharaj PP, Patra S, Panigrahi DP, Patra SK, Bhutia SK. Clusterin as modulator of carcinogenesis: A potential avenue for targeted cancer therapy. Biochim Biophys. Acta Rev. Cancer. 2021;1875:188500.
Not in our library10.1016/j.bbcan.2020.188500 (opens in a new tab)
- 348.
Shahbaz S, et al. CD71+VISTA+ erythroid cells promote the development and function of regulatory T cells through TGF-β. PLoS Biol. 2018;16:e2006649.
Not in our library10.1371/journal.pbio.2006649 (opens in a new tab)
- 349.
- 350.
Song B, et al. Targeting FOXA1-mediated repression of TGF-beta signaling suppresses castration-resistant prostate cancer progression. J. Clin. Invest. 2019;129:569-582.
Not in our library10.1172/jci122367 (opens in a new tab)
- 351.
Kelley RK, et al. A Phase 2 Study of Galunisertib (TGF-beta1 Receptor Type I Inhibitor) and Sorafenib in Patients With Advanced Hepatocellular Carcinoma. Clin. Transl. Gastroenterol. 2019;10:e00056.
Not in our library10.14309/ctg.0000000000000056 (opens in a new tab)
- 352.
Harding JJ, et al. Phase 1b study of galunisertib and ramucirumab in patients with advanced hepatocellular carcinoma. Cancer Med. 2021;10:3059-3067.
Not in our library10.1002/cam4.3880 (opens in a new tab)
- 353.
- 354.
Melisi D, et al. Safety and activity of the TGFbeta receptor I kinase inhibitor galunisertib plus the anti-PD-L1 antibody durvalumab in metastatic pancreatic cancer. J. Immunother. Cancer. 2021;9:e002068.
Not in our library10.1136/jitc-2020-002068 (opens in a new tab)
- 355.
Tauriello DVF, et al. TGFbeta drives immune evasion in genetically reconstituted colon cancer metastasis. Nature. 2018;554:538-543.
Not in our library10.1038/nature25492 (opens in a new tab)
- 356.
Lan Y, et al. Enhanced preclinical antitumor activity of M7824, a bifunctional fusion protein simultaneously targeting PD-L1 and TGF-beta. Sci. Transl. Med. 2018;10:eaan5488.
Not in our library10.1126/scitranslmed.aan5488 (opens in a new tab)
- 357.
- 358.
- 359.
Strauss J, et al. Bintrafusp alfa, a bifunctional fusion protein targeting TGF-beta and PD-L1, in patients with human papillomavirus-associated malignancies. J. Immunother. Cancer. 2020;8:e001395.
Not in our library10.1136/jitc-2020-001395 (opens in a new tab)
- 360.
Tan B, et al. Bintrafusp Alfa, a Bifunctional Fusion Protein Targeting TGF-β and PD-L1, in Patients with Esophageal Adenocarcinoma: Results from a Phase 1 Cohort. Target. Oncol. 2021;16:435-446.
Not in our library10.1007/s11523-021-00809-2 (opens in a new tab)
- 361.
Yoo C, et al. Phase I study of bintrafusp alfa, a bifunctional fusion protein targeting TGF-beta and PD-L1, in patients with pretreated biliary tract cancer. J. Immunother. Cancer. 2020;8:e000564.
Not in our library10.1136/jitc-2020-000564 (opens in a new tab)
- 362.
Ma F, et al. Autocrine Canonical Wnt Signaling Primes Noncanonical Signaling through ROR1 in Metastatic Castration-Resistant Prostate Cancer. Cancer Res. 2022;82:1518-1533.
Not in our library10.1158/0008-5472.can-21-1807 (opens in a new tab)
- 363.
Moore KN, et al. A phase 1b dose escalation study of ipafricept (OMP54F28) in combination with paclitaxel and carboplatin in patients with recurrent platinum-sensitive ovarian cancer. Gynecol. Oncol. 2019;154:294-301.
Not in our library10.1016/j.ygyno.2019.04.001 (opens in a new tab)
- 364.
Dotan E, et al. Phase Ib Study of Wnt Inhibitor Ipafricept with Gemcitabine and nab-paclitaxel in Patients with Previously Untreated Stage IV Pancreatic Cancer. Clin. Cancer Res. 2020;26:5348-5357.
Not in our library10.1158/1078-0432.ccr-20-0489 (opens in a new tab)
- 365.
Kaur A, et al. WNT inhibition creates a BRCA-like state in Wnt-addicted cancer. EMBO Mol. Med. 2021;13:e13349.
Not in our library10.15252/emmm.202013349 (opens in a new tab)
- 366.
Le PN, et al. Wnt signaling dynamics in head and neck squamous cell cancer tumor-stroma interactions. Mol. Carcinog. 2019;58:398-410.
Not in our library10.1002/mc.22937 (opens in a new tab)
- 367.
Sun L, et al. Inhibiting myeloid-derived suppressor cell trafficking enhances T cell immunotherapy. JCI Insight. 2019;4:e126853.
Not in our library10.1172/jci.insight.126853 (opens in a new tab)
- 368.
Greene S, et al. Inhibition of MDSC Trafficking with SX-682, a CXCR1/2 Inhibitor, Enhances NK-Cell Immunotherapy in Head and Neck Cancer Models. Clin. Cancer Res. 2020;26:1420-1431.
Not in our library10.1158/1078-0432.ccr-19-2625 (opens in a new tab)
- 369.
Kim MJ, et al. Reduced HIF-1α Stability Induced by 6-Gingerol Inhibits Lung Cancer Growth through the Induction of Cell Death. Molecules. 2022;27:2106.
Not in our library10.3390/molecules27072106 (opens in a new tab)
- 370.
- 371.
Qin Y, et al. Salidroside improves the hypoxic tumor microenvironment and reverses the drug resistance of platinum drugs via HIF-1α signaling pathway. EBioMedicine. 2018;38:25-36.
Not in our library10.1016/j.ebiom.2018.10.069 (opens in a new tab)
- 372.
Minoura K, Abe K, Nam H, Nishikawa H, Shimamura T. A mixture-of-experts deep generative model for integrated analysis of single-cell multiomics data. Cell Rep. Methods. 2021;1:100071.
Not in our library10.1016/j.crmeth.2021.100071 (opens in a new tab)
- 373.
Longo SK, Guo MG, Ji AL, Khavari PA. Integrating single-cell and spatial transcriptomics to elucidate intercellular tissue dynamics. Nat. Rev. Genet. 2021;22:627-644.
Not in our library10.1038/s41576-021-00370-8 (opens in a new tab)
- 374.
Cited by papers we hold 4
- Invasion and metastasis in cancer: molecular insights and therapeutic targets · 2025No notice
- Targeting epigenetic regulators as a promising avenue to overcome cancer therapy resistance · 2025No notice
- Unveiling the mechanisms and challenges of cancer drug resistance · 2024No notice
- Potentials and future perspectives of multi-target drugs in cancer treatment: the next generation anti-cancer agents · 2024No notice
Questions about this paper
We email you if it is retracted, withdrawn, corrected or flagged.
Reads
Read by people on this page
None yet.
Checked or read by AI through naulon
None yet.
A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.
Are you an author?
Is this your paper?
Claim it to add your note and be paid when agents cite it. Free.