The growing role of precision and personalized medicine for cancer treatment

Abstract

Cancer is a devastating disease that takes the lives of hundreds of thousands of people every year. Due to disease heterogeneity, standard treatments, such as chemotherapy or radiation, are effective in only a subset of the patient population. Tumors can have different underlying genetic causes and may express different proteins in one patient versus another. This inherent variability of cancer lends itself to the growing field of precision and personalized medicine (PPM). There are many ongoing efforts to acquire PPM data in order to characterize molecular differences between tumors. Some PPM products are already available to link these differences to an effective drug. It is clear that PPM cancer treatments can result in immense patient benefits, and companies and regulatory agencies have begun to recognize this. However, broader changes to the healthcare and insurance systems must be addressed if PPM is to become part of standard cancer care.

Shown for reading. Its publisher allows quoting it, not republishing it.

References 195

1. 1.

   National Cancer Institute. Cancer statistics (2018 ), https://www.cancer.gov/about-cancer/understanding/statistics

   Not in our library

2. 2.

   National Cancer Institute. Cancer types (2018 ), https://www.cancer.gov/types

   Not in our library

3. 3.

   Alizadeh AA Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403, 503–511 (2000 ).

   Not in our library10.1038/35000501

4. 4.

   Guinney J The consensus molecular subtypes of colorectal cancer. Nat. Med 21, 1350–1356 (2015 ).

   Not in our library10.1038/nm.3967

5. 5.

   Perou CM Molecular portraits of human breast tumours. Nature 406, 747–752 (2000 ).

   Not in our library10.1038/35021093

6. 6.

   Davies H Mutations of the BRAF gene in human cancer. Nature 417, 949–954 (2002 ).

   Not in our library10.1038/nature00766

7. 7.

   National Cancer Institute. Types of cancer treatment (2017 ), https://www.cancer.gov/about-cancer/treatment/types

   Not in our library

8. 8.

   Morgan G, Ward R & Barton M The contribution of cytotoxic chemotherapy to 5-year survival in adult malignancies. Clin. Oncol. (R. Coll. Radiol.) 16, 549–560 (2004 ).

   Not in our library10.1016/j.clon.2004.06.007

9. 9.

   Personalized Medicine Coalition. The personalized medicine report. Opportunity, challenges, and the future (2017 ), http://www.personalizedmedicinecoalition.org/Userfiles/PMC-Corporate/file/The_PM_Report.pdf

   Not in our library

10. 10.

    Maciejko L, Smalley M & Goldman A Cancer immunotherapy and personalized medicine: Emerging technologies and biomarker-based approaches. J. Mol. Biomark. Diagn 8, (2017 ).

    Not in our library10.4172/2155-9929.1000350

11. 11.

    Burney IA & Lakhtakia R Precision medicine: Where have we reached and where are we headed? Sultan Qaboos Univ. Med. J 17, e255–e258 (2017 ).

    Not in our library10.18295/squmj.2017.17.03.001

12. 12.

    Williams SC News feature: Capturing cancer’s complexity. Proc. Natl. Acad. Sci. U. S. A 112, 4509–4511 (2015 ).

    Not in our library10.1073/pnas.1500963112

13. 13.

    Soda M Identification of the transforming EML4-ALK fusion gene in non-small-cell lung cancer. Nature 448, 561–566 (2007 ).

    Not in our library10.1038/nature05945

14. 14.

    Ledermann J Olaparib maintenance therapy in patients with platinum-sensitive relapsed serous ovarian cancer: A preplanned retrospective analysis of outcomes by BRCA status in a randomised phase 2 trial. Lancet Oncol 15, 852–861 (2014 ).

    Not in our library10.1016/s1470-2045(14)70228-1

15. 15.
    Personalized Medicine and Cancer · 2012

    No notice
16. 16.

    Agilent. Herceptest, https://www.agilent.com/en-us/products/pharmdx/herceptest-kits/herceptest

    Not in our library

17. 17.

    Myriad. Bracanalysis, https://myriad.com/products-services/hereditary-cancers/bracanalysis/

    Not in our library

18. 18.

    U.S. Food and Drug Administration. Mobile medical applications — Guidance for industry and food and drug administration staff (2015 ), https://www.fda.gov/downloads/MedicalDevices/…/UCM263366.pdf

    Not in our library

19. 19.

    U.S. Food and Drug Administration. FDA advances precision medicine initiative by issuing draft guidances on next generation sequencing-based tests (2016 ), https://www.fda.gov/newsevents/newsroom/pressannouncements/ucm509814.htm

    Not in our library

20. 20.

    U.S. National Library of Medicine. What is the difference between precision medicine and personalized medicine? What about pharmacogenomics? (2018 ), https://ghr.nlm.nih.gov/primer/precisionmedicine/precisionvspersonalized

    Not in our library

21. 21.

    Appendix E. Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease (The National Academies Press, 2011 ), pp. 124–145.

    Not in our library

22. 22.

    Chial H DNA sequencing technologies key to the human genome project. Nat. Educ 1, (2008 ).

    Not in our library

23. 23.

    Goodwin S, McPherson JD & McCombie WR Coming of age: Ten years of next-generation sequencing technologies. Nat. Rev. Genet 17, 333–351 (2016 ).

    Not in our library10.1038/nrg.2016.49

24. 24.

    Munroe DJ & Harris TJ Third-generation sequencing fireworks at marco island. Nat. Biotechnol 28, 426 (2010 ).

    Not in our library10.1038/nbt0510-426

25. 25.
    Transcriptomics technologies · 2017

    No notice
26. 26.

    Kukurba KR & Montgomery SB RNA sequencing and analysis. Cold Spring Harb. Protoc 2015, 951–969 (2015 ).

    Not in our library10.1101/pdb.top084970

27. 27.

    Buguliskis JS Could RNA-Seq become the workhorse of precision medicine? Plowing through transcriptional variations by harnessing the powerful next-gen technique. Genet. Eng. Biotechnol. News 35, 8–9 (2015 ).

    Not in our library

28. 28.

    Larance M & Lomond AI Multidimensional proteomics for cell biology. Nat. Rev. Mol. Cell. Biol 16, 269–280 (2015 ).

    Not in our library10.1038/nrm3970

29. 29.

    Han XM, Aslanian A & Yates JR Mass spectrometry for proteomics. Curr. Opin. Chem. Biol 12, 483–490 (2008 ).

    Not in our library10.1016/j.cbpa.2008.07.024

30. 30.

    Duarte TT & Spencer CT Personalized proteomics: The future of precision medicine. Proteomes 4, (2016 ).

    Not in our library10.3390/proteomes4040029

31. 31.

    Gregorich ZR & Ge Y Top-down proteomics in health and disease: Challenges and opportunities. Proteomics 14, 1195–1210 (2014 ).

    Not in our library10.1002/pmic.201300432

32. 32.

    Sidoli S Metabolic labeling in middle-down proteomics allows for investigation of the dynamics of the histone code. Epigenetics Chromatin 10, 34 (2017 ).

    Not in our library10.1186/s13072-017-0139-z

33. 33.

    Monteiro MS, Carvalho M, Bastos ML & Guedes de Pinho P Metabolomics analysis for biomarker discovery: Advances and challenges. Curr. Med. Chem 20, 257–271 (2013 ).

    Not in our library10.2174/092986713804806621

34. 34.

    Roessner U & Bowne J What is metabolomics all about? Biotechniques 46, 363 (2009 ).

    Not in our library10.2144/000113133

35. 35.

    Everett JR, Loo RL & Pullen FS Pharmacometabonomics and personalized medicine. Ann. Clin. Biochem 50, 523–545 (2013 ).

    Not in our library10.1177/0004563213497929

36. 36.

    Eckhart AD, Beebe K & Milburn M Metabolomics as a key integrator for “omic” advancement of personalized medicine and future therapies. Clin. Transl. Sci 5, 285–288 (2012 ).

    Not in our library10.1111/j.1752-8062.2011.00388.x

37. 37.

    Prosser GA, Larrouy-Maumus G & de Carvalho LPS Metabolomic strategies for the identification of new enzyme functions and metabolic pathways. EMBO Rep 15, 657–669 (2014 ).

    Not in our library10.15252/embr.201338283

38. 38.

    Li SZ, Todor A & Luo RY Blood transcriptomics and metabolomics for personalized medicine. Comput. Struct. Biotechnol. J 14, 1–7 (2016 ).

    Not in our library10.1016/j.csbj.2015.10.005

39. 39.

    Dunn WB & Ellis DI Metabolomics: Current analytical platforms and methodologies. Trac-Trend. Anal. Chem 24, 285–294 (2005 ).

    Not in our library

40. 40.

    Kaufmann A, Butcher P, Maden K, Walker S & Widmer M Comprehensive comparison of liquid chromatography selectivity as provided by two types of liquid chromatography detectors (high resolution mass spectrometry and tandem mass spectrometry): “Where is the crossover point?”. Anal. Chim. Acta 673, 60–72 (2010 ).

    Not in our library10.1016/j.aca.2010.05.020

41. 41.

    Schrimpe-Rutledge AC, Codreanu SG, Sherrod SD & McLean JA Untargeted metabolomics strategies-challenges and emerging directions. J. Am. Soc. Mass. Spectrom 27, 1897–1905 (2016 ).

    Not in our library10.1007/s13361-016-1469-y

42. 42.

    Wanichthanarak K, Fan S, Grapov D, Barupal DK & Fiehn O Metabox: A toolbox for metabolomic data analysis, interpretation and integrative exploration. PLOS ONE 12, e0171046 (2017 ).

    Not in our library10.1371/journal.pone.0171046

43. 43.

    Kim D Using knowledge-driven genomic interactions for multi-omics data analysis: Metadimensional models for predicting clinical outcomes in ovarian carcinoma. J. Am. Med. Inform. Assoc 24, 577–587 (2017 ).

    Not in our library10.1093/jamia/ocw165

44. 44.
    More Is Better: Recent Progress in Multi-Omics Data Integration Methods · 2017

    No notice
45. 45.

    Hartmanshenn C, Scherholz M & Androulakis IP Physiologically-based pharmacokinetic models: Approaches for enabling personalized medicine. J. Pharmacokinet. Pharmacodyn 43, 481–504 (2016 ).

    Not in our library10.1007/s10928-016-9492-y

46. 46.

    Kesisoglou F, Chung J, van Asperen J & Heimbach T Physiologically based absorption modeling to impact biopharmaceutics and formulation strategies in drug development-industry case studies. J. Pharm. Sci 105, 2723–2734 (2016 ).

    Not in our library10.1016/j.xphs.2015.11.034

47. 47.

    Kesisoglou F & Mitra A Application of absorption modeling in rational design of drug product under quality-by-design paradigm. AAPS J 17, 1224–1236 (2015 ).

    Not in our library10.1208/s12248-015-9781-1

48. 48.

    Rowland M, Peck C & Tucker G Physiologically-based pharmacokinetics in drug development and regulatory science. Annu. Rev. Pharmacol. Toxicol 51, 45–73 (2011 ).

    Not in our library10.1146/annurev-pharmtox-010510-100540

49. 49.

    Reeve E, Wiese MD & Mangoni AA Alterations in drug disposition in older adults. Expert Opin. Drug Metab. Toxicol 11, 491–508 (2015 ).

    Not in our library10.1517/17425255.2015.1004310

50. 50.

    Nicholson JK Global systems biology, personalized medicine and molecular epidemiology. Mol. Syst. Biol 2, 52 (2006 ).

    Not in our library10.1038/msb4100095

51. 51.

    Mashberg A, Boffetta P, Winkelman R & Garfinkel L Tobacco smoking, alcohol drinking, and cancer of the oral cavity and oropharynx among U.S. veterans. Cancer 72, 1369–1375 (1993 ).

    Not in our library10.1002/1097-0142(19930815)72:4<1369::aid-cncr2820720436>3.0.co;2-l

52. 52.

    Khalil F & Laer S Physiologically based pharmacokinetic modeling: Methodology, applications, and limitations with a focus on its role in pediatric drug development. J. Biomed. Biotechnol 2011, 907461 (2011 ).

    Not in our library10.1155/2011/907461

53. 53.

    Rodenburg W A framework to identify physiological responses in microarray-based gene expression studies: Selection and interpretation of biologically relevant genes. Physiol. Genomics 33, 78–90 (2008 ).

    Not in our library10.1152/physiolgenomics.00167.2007

54. 54.

    National Cancer Institute and National Human Genome Research Institute. Overview of the cancer genome atlas (TCGA), https://cancergenome.nih.gov/abouttcga/overview

    Not in our library

55. 55.

    Marx V Biology: The big challenges of big data. Nature 498, 255–260 (2013 ).

    Not in our library10.1038/498255a

56. 56.

    Amazon Web Services-Government, Education, & Nonprofit Blog. Cloud-enabled innovation in personalized medical treatment, https://aws.amazon.com/blogs/publicsector/cloud-enabled-innovation-in-personalized-medical-treatment/

    Not in our library

57. 57.

    Gurwitz D, Lunshof JE & Altman RB A call for the creation of personalized medicine databases. Nat. Rev. Drug Discov 5, 23–26 (2006 ).

    Not in our library10.1038/nrd1931

58. 58.

    Pavlopoulou A, Spandidos DA & Michalopoulos I Human cancer databases (review). Oncol. Rep 33, 3–18 (2015 ).

    Not in our library10.3892/or.2014.3579

59. 59.

    Kanehisa Laboratories. KEGG database (2017 ), http://www.genome.jp/kegg/kegg1.html

    Not in our library

60. 60.

    Butcher EC, Berg EL & Kunkel EJ Systems biology in drug discovery. Nat. Biotechnol 22, 1253–1259 (2004 ).

    Not in our library10.1038/nbt1017

61. 61.

    McShane LM Criteria for the use of omics-based predictors in clinical trials: Explanation and elaboration. BMC Med 11, (2013 ).

    Not in our library10.1186/1741-7015-11-220

62. 62.

    McShane LM Criteria for the use of omics-based predictors in clinical trials. Nature 502, 317–320 (2013 ).

    Not in our library10.1038/nature12564

63. 63.

    McShane LM & Polley MY Development of omics-based clinical tests for prognosis and therapy selection: The challenge of achieving statistical robustness and clinical utility. Clin. Trials 10, 653–665 (2013 ).

    Not in our library10.1177/1740774513499458

64. 64.

    Ritchie MD, Holzinger ER, Li R, Pendergrass SA & Kim D Methods of integrating data to uncover genotype–phenotype interactions. Nat. Rev. Genet 16, 85–97 (2015 ).

    Not in our library10.1038/nrg3868

65. 65.

    Lee CH & Yoon HJ Medical big data: Promise and challenges. Kidney Res. Clin. Pract 36, 3–11 (2017 ).

    Not in our library10.23876/j.krcp.2017.36.1.3

66. 66.

    Le Tourneau C Treatment algorithms based on tumor molecular profiling: The essence of precision medicine trials. J. Natl. Cancer Inst 108, (2016 ).

    Not in our library10.1093/jnci/djv362

67. 67.

    Fan J & Liu H Statistical analysis of big data on pharmacogenomics. Adv. Drug Deliv. Rev 65, 987–1000 (2013 ).

    Not in our library10.1016/j.addr.2013.04.008

68. 68.

    Kamisoglu K Understanding physiology in the continuum: Integration of information from multiple-omics levels. Front Pharmacol 8, 91 (2017 ).

    Not in our library10.3389/fphar.2017.00091

69. 69.

    Ovacik MA Pathway modeling of microarray data: A case study of pathway activity changes in the testis following in utero exposure to dibutyl phthalate (DBP). Toxicol. Appl. Pharmacol 271, 386–394 (2013 ).

    Not in our library10.1016/j.taap.2010.09.008

70. 70.

    Ovacik MA Circadian signatures in rat liver: From gene expression to pathways. BMC Bioinformatics 11, 540 (2010 ).

    Not in our library10.1186/1471-2105-11-540

71. 71.

    Micheel CM, Nass SJ & Omenn GS Committee on the review of omics-based tests for predicting patient outcomes in clinical trials (2012 ).

    Not in our library

72. 72.

    Karczewski KJ & Snyder MP Integrative omics for health and disease. Nat. Rev. Genet 19, 299–310 (2018 ).

    Not in our library10.1038/nrg.2018.4

73. 73.

    Mackall CL Engineering a designer immunotherapy. Science 359, 990–991 (2018 ).

    Not in our library10.1126/science.aas9434

74. 74.

    Bettegowda C Detection of circulating tumor DNA in early- and late-stage human malignancies. Sci. Transl. Med 6, 224ra24 (2014 ).

    Not in our library10.1126/scitranslmed.3007094

75. 75.

    Ried K, Eng P & Sali A Screening for circulating tumour cells allows early detection of cancer and monitoring of treatment effectiveness: An observational study. Asian Pac. J. Cancer Prev 18, 2275–2285.

    Not in our library10.22034/apjcp.2017.18.8.2275

76. 76.
    The potential of liquid biopsies for the early detection of cancer · 2017

    No notice
77. 77.

    Hong B & Zu Y Detecting circulating tumor cells: Current challenges and new trends. Theranostics 3, 377–394 (2013 ).

    Not in our library10.7150/thno.5195

78. 78.

    Lang JE RNA-Seq of circulating tumor cells in stage II–III breast cancer. Ann. Surg. Oncol 25, 2261–2270 (2018 ).

    Not in our library10.1245/s10434-018-6540-4

79. 79.

    Shaw JA Mutation analysis of cell-free DNA and single circulating tumor cells in metastatic breast cancer patients with high circulating tumor cell counts. Clin. Cancer Res 23, 88 (2017 ).

    Not in our library10.1158/1078-0432.ccr-16-0825

80. 80.

    Lallo A, Schenk MW, Frese KK, Blackhall F & Dive C Circulating tumor cells and CDx models as a tool for preclinical drug development. Transl. Lung Cancer Res 6, 397–408 (2017 ).

    Not in our library10.21037/tlcr.2017.08.01

81. 81.
    Functional Characterization of Circulating Tumor Cells with a Prostate-Cancer-Specific Microfluidic Device · 2012

    Corrected
82. 82.
    Circulating Tumor DNA as Biomarkers for Cancer Detection · 2017

    No notice
83. 83.

    Dive C & Brady G Snapshot: Circulating tumor cells. Cell 168, 742–742.e1 (2017 ).

    Not in our library10.1016/j.cell.2017.01.026

84. 84.

    Aboulkheyr Es H, Montazeri L, Aref AR, Vosough M & Baharvand H Personalized cancer medicine: An organoid approach. Trends Biotechnol 36, 358–371 (2018 ).

    Not in our library10.1016/j.tibtech.2017.12.005

85. 85.

    Weeber F Preserved genetic diversity in organoids cultured from biopsies of human colorectal cancer metastases. Proc. Natl. Acad. Sci. U. S. A 112, 13308–13311 (2015 ).

    Not in our library10.1073/pnas.1516689112

86. 86.

    van de Wetering M Prospective derivation of a living organoid biobank of colorectal cancer patients. Cell 161, 933–945 (2015 ).

    Not in our library10.1016/j.cell.2015.03.053

87. 87.

    Pauli C Personalized in vitro and in vivo cancer models to guide precision medicine. Cancer Discov 7, 462–477 (2017 ).

    Not in our library10.1158/2159-8290.cd-16-1154

88. 88.

    Sun Y, Haglund TA, Rogers AJ, Ghanim AF & Sethu P Review: Microfluidics technologies for blood-based cancer liquid biopsies. Anal. Chim. Acta 1012, 10–29 (2018 ).

    Not in our library10.1016/j.aca.2017.12.050

89. 89.

    Hidalgo M A pilot clinical study of treatment guided by personalized tumorgrafts in patients with advanced cancer. Mol. Cancer Ther 10, 1311–1316 (2011 ).

    Not in our library10.1158/1535-7163.mct-11-0233

90. 90.

    Asnacios A, Naveau S & Perlemuter G Gastrointestinal toxicities of novel agents in cancer therapy. Eur. J. Cancer 45(Suppl. 1), 332–342 (2009 ).

    Not in our library10.1016/s0959-8049(09)70047-4

91. 91.

    Strevel EL & Siu LL Cardiovascular toxicity of molecularly targeted agents. Eur. J. Cancer 45(Suppl. 1), 318–331 (2009 ).

    Not in our library10.1016/s0959-8049(09)70046-2

92. 92.

    Esteva FJ Monoclonal antibodies, small molecules, and vaccines in the treatment of breast cancer. Oncologist 9(Suppl. 3), 4–9 (2004 ).

    Not in our library10.1634/theoncologist.9-suppl_3-4

93. 93.

    The American Cancer Society. Targeted therapy for breast cancer (2018 ), https://www.cancer.org/cancer/breast-cancer/treatment/targeted-therapy-for-breast-cancer.html#written_by

    Not in our library

94. 94.

    Wilson PM, Labonte MJ & Lenz HJ Molecular markers in the treatment of metastatic colorectal cancer. Cancer J 16, 262–272 (2010 ).

    Not in our library10.1097/ppo.0b013e3181e07738

95. 95.

    Tannock IF & Hickman JA Limits to personalized cancer medicine. N. Engl. J. Med 375, 1289–1294 (2016 ).

    Not in our library10.1056/nejmsb1607705

96. 96.

    Szalat R & Munshi NC Next-generation sequencing informing therapeutic decisions and personalized approaches. Am. Soc. Clin. Oncol. Educ. Book 35, e442–e448 (2016 ).

    Not in our library10.1200/edbk_159017

97. 97.

    Doostparast Torshizi A & Wang K Next-generation sequencing in drug development: Target identification and genetically stratified clinical trials. Drug Discov. Today 23, 1776–1783 (2018 ).

    Not in our library10.1016/j.drudis.2018.05.015

98. 98.

    Siu LL, Conley BA, Boerner S & LoRusso PM Next-generation sequencing to guide clinical trials. Clin. Cancer Res 21, 4536–4544 (2015 ).

    Not in our library10.1158/1078-0432.ccr-14-3215

99. 99.

    Horak P, Frohling S & Glimm H Integrating next-generation sequencing into clinical oncology: Strategies, promises and pitfalls. ESMO Open 1, e000094 (2016 ).

    Not in our library10.1136/esmoopen-2016-000094

100. 100.

     Garon EB Pembrolizumab for the treatment of non-small-cell lung cancer. N. Engl. J. Med 372, 2018–2028 (2015 ).

     Not in our library10.1056/nejmoa1501824

101. 101.

     Merck & Co., Inc. Merck’s keytruda® (pembrolizumab) plus chemotherapy significantly improved overall survival in first-line treatment of metastatic squamous non-small cell lung cancer in phase 3 keynote-407 study (2018 ), http://investors.merck.com/news/press-release-details/2018/Mercks-KEYTRUDA-pembrolizumab-Plus-Chemotherapy-Significantly-Improved-Overall-Survival-in-First-Line-Treatment-of-Metastatic-Squamous-Non-Small-Cell-Lung-Cancer-in-Phase-3-KEYNOTE-407-Study/default.aspx

     Not in our library

102. 102.

     Radhakrishnan D, Robinson A & Ogunnaike B Controlling the glycosylation profile in mAbs using time-dependent media supplementation. Antibodies 7, 1 (2018 ).

     Not in our library10.3390/antib7010001

103. 103.

     Mellman I, Coukos G & Dranoff G Cancer immunotherapy comes of age. Nature 480, 480–489 (2011 ).

     Not in our library10.1038/nature10673

104. 104.

     Chen L & Flies DB Molecular mechanisms of T cell co-stimulation and co-inhibition. Nat. Rev. Immunol 13, 227–242 (2013 ).

     Not in our library10.1038/nri3405

105. 105.

     Hargadon KM, Johnson CE & Williams CJ Immune checkpoint blockade therapy for cancer: An overview of FDA-approved immune checkpoint inhibitors. Int. Immunopharmacol 62, 29–39 (2018 ).

     Not in our library10.1016/j.intimp.2018.06.001

106. 106.

     Walunas TL CTLA-4 can function as a negative regulator of T cell activation. Immunity 1, 405–413 (1994 ).

     Not in our library10.1016/1074-7613(94)90071-x

107. 107.

     Krummel MF & Allison JP CD28 and CTLA-4 have opposing effects on the response of T cells to stimulation. J. Exp. Med 182, 459–465 (1995 ).

     Not in our library10.1084/jem.182.2.459

108. 108.

     Hodi FS Improved survival with ipilimumab in patients with metastatic melanoma. N. Engl. J. Med 363, 711–723 (2010 ).

     Not in our library10.1056/nejmoa1003466

109. 109.

     Nishimura H, Nose M, Hiai H, Minato N & Honjo T Development of lupus-like autoimmune diseases by disruption of the PD-1 gene encoding an ITIM motif-carrying immunoreceptor. Immunity 11, 141–151 (1999 ).

     Not in our library10.1016/s1074-7613(00)80089-8

110. 110.

     Wei SC Distinct cellular mechanisms underlie anti-CTLA-4 and anti-PD-1 checkpoint blockade. Cell 170, 1120–1133.e17 (2017 ).

     Not in our library10.1016/j.cell.2017.07.024

111. 111.

     Weber JS Nivolumab versus chemotherapy in patients with advanced melanoma who progressed after anti-CTLA-4 treatment (CheckMate 037): A randomised, controlled, open-label, phase 3 trial. Lancet Oncol 16, 375–384 (2015 ).

     Not in our library10.1016/s1470-2045(15)70076-8

112. 112.

     Brahmer J Nivolumab versus docetaxel in advanced squamous-cell non-small-cell lung cancer. N. Engl. J. Med 373, 123–135 (2015 ).

     Not in our library10.1056/nejmoa1504627

113. 113.

     Motzer RJ Nivolumab versus everolimus in advanced renal-cell carcinoma. N. Engl. J. Med 373, 1803–1813 (2015 ).

     Not in our library10.1056/nejmoa1510665

114. 114.

     Sharma P Nivolumab in metastatic urothelial carcinoma after platinum therapy (CheckMate 275): A multicentre, single-arm, phase 2 trial. Lancet Oncol 18, 312–322 (2017 ).

     Not in our library10.1016/s1470-2045(17)30065-7

115. 115.

     Ansell SM PD-1 blockade with nivolumab in relapsed or refractory Hodgkin’s lymphoma. N. Engl. J. Med 372, 311–319 (2015 ).

     Not in our library10.1056/nejmoa1411087

116. 116.

     Prasad V, Kaestner V & Mailankody S Cancer drugs approved based on biomarkers and not tumor type-FDA approval of pembrolizumab for mismatch repair-deficient solid cancers. JAMA Oncol 4, 157–158 (2018 ).

     Not in our library10.1001/jamaoncol.2017.4182

117. 117.

     Powles T Atezolizumab versus chemotherapy in patients with platinum-treated locally advanced or metastatic urothelial carcinoma (IMvigor211): A multicentre, open-label, phase 3 randomised controlled trial. Lancet 391, 748–757 (2018 ).

     Not in our library10.1016/s0140-6736(17)33297-x

118. 118.

     Antonia SJ Durvalumab after chemoradiotherapy in stage iii non-small-cell lung cancer. N. Engl. J. Med 377, 1919–1929 (2017 ).

     Not in our library10.1056/nejmoa1709937

119. 119.

     Zappasodi R, Merghoub T & Wolchok JD Emerging concepts for immune check-point blockade-based combination therapies. Cancer Cell 33, 581–598 (2018 ).

     Not in our library10.1016/j.ccell.2018.03.005

120. 120.

     Wang B Combination cancer immunotherapy targeting PD-1 and GITR can rescue CD8(+) T cell dysfunction and maintain memory phenotype. Sci. Immunol 3, (2018 ).

     Not in our library10.1126/sciimmunol.aat7061

121. 121.

     Wei SC, Duffy CR & Allison JP Fundamental mechanisms of immune checkpoint blockade therapy. Cancer Discov 8, 1069–1086 (2018 ).

     Not in our library10.1158/2159-8290.cd-18-0367

122. 122.

     Gibney GT, Weiner LM & Atkins MB Predictive biomarkers for checkpoint inhibitor-based immunotherapy. Lancet Oncol 17, e542–e551 (2016 ).

     Not in our library10.1016/s1470-2045(16)30406-5

123. 123.

     Ng Tang D Increased frequency of ICOS+ CD4 T cells as a pharmacodynamic biomarker for anti-CTLA-4 therapy. Cancer Immunol. Res 1, 229–234 (2013 ).

     Not in our library10.1158/2326-6066.cir-13-0020

124. 124.

     Hu Z, Ott PA & Wu CJ Towards personalized, tumour-specific, therapeutic vaccines for cancer. Nat. Rev. Immunol 18, 168–182 (2018 ).

     Not in our library10.1038/nri.2017.131

125. 125.

     Brennick CA, George MM, Corwin WL, Srivastava PK & Ebrahimi-Nik H Neoepitopes as cancer immunotherapy targets: Key challenges and opportunities. Immunotherapy 9, 361–371 (2017 ).

     Not in our library10.2217/imt-2016-0146

126. 126.
     Genomic Correlates of Immune-Cell Infiltrates in Colorectal Carcinoma · 2016

     No notice
127. 127.

     Tran E Cancer immunotherapy based on mutation-specific CD4+ T cells in a patient with epithelial cancer. Science 344, 641–645 (2014 ).

     Not in our library10.1126/science.1251102

128. 128.

     National Cancer Institute. Biological therapies for cancer (2018 ), https://www.cancer.gov/about-cancer/treatment/types/immunotherapy/bio-therapies-fact-sheet?redirect=true

     Not in our library

129. 129.

     Kantoff PW Sipuleucel-T immunotherapy for castration-resistant prostate cancer. N. Engl. J. Med 363, 411–422 (2010 ).

     Not in our library10.1056/nejmoa1001294

130. 130.

     Ye B Engineering chimeric antigen receptor-T cells for cancer treatment. Mol. Cancer 17, 32 (2018 ).

     Not in our library10.1186/s12943-018-0814-0

131. 131.

     Morris EC & Stauss HJ Optimizing T-cell receptor gene therapy for hematologic malignancies. Blood 127, 3305–3311 (2016 ).

     Not in our library10.1182/blood-2015-11-629071

132. 132.

     Porter DL, Levine BL, Kalos M, Bagg A & June CH Chimeric antigen receptor-modified T cells in chronic lymphoid leukemia. N. Engl. J. Med 365, 725–733 (2011 ).

     Not in our library10.1056/nejmoa1103849

133. 133.

     Hirawat S Novartis, CTL019 (tisagenlecleucel) in pediatric and young adult patients with relapsed/refractory B-cell acute lymphoblastic leukemia (2017 ), https://www.fda.gov/downloads/AdvisoryCommittees/CommitteesMeetingMaterials/Drugs/OncologicDrugsAdvisoryCommittee/UCM567385.pdf

     Not in our library

134. 134.

     Carroll J Endpoints News, Novartis wins a key OK for Kymriah, but continuing manufacturing woes hobble rollout — rival Gilead Car-T breaks into Europe (2018 ), https://endpts.com/novartis-wins-a-key-ok-for-kymriah-but-continuing-manufacturing-woes-afflict-their-rollout-rival-gilead-breaks-into-europe/?utm_medium=email&utm_campaign=552%20Mon%2082718%20Bottom%20line%20Novartis%20cant%20handle%20full%20CAR-T%20rollout%20Alnylam%20counterattacks%20against%20Pfizers%20tafamidis&utm_content=552%20Mon%2082718%20Bottom%20line%20Novartis%20cant%20handle%20full%20CAR-T%20rollout%20Alnylam%20counterattacks%20against%20Pfizers%20tafamidis+CID_b327e72c32bc714a5debf124c0c7606c&

     Not in our library

135. 135.

     Lawrence MS Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214–218 (2013 ).

     Not in our library10.1038/nature12213

136. 136.

     Jacobs TW, Gown AM, Yaziji H, Barnes MJ & Schnitt SJ Specificity of HercepT-est in determining HER-2/neu status of breast cancers using the United States Food and Drug Administration-approved scoring system. J. Clin. Oncol 17, 1983–1987 (1999 ).

     Not in our library10.1200/jco.1999.17.7.1983

137. 137.

     Schechter AL The neu oncogene: An erb-B-related gene encoding a 185,000-Mr tumour antigen. Nature 312, 513–516 (1984 ).

     Not in our library10.1038/312513a0

138. 138.

     Cho HS Structure of the extracellular region of HER2 alone and in complex with the Herceptin Fab. Nature 421, 756–760 (2003 ).

     Not in our library10.1038/nature01392

139. 139.

     Slamon DJ Use of chemotherapy plus a monoclonal antibody against HER2 for metastatic breast cancer that overexpresses HER2. N. Engl. J. Med 344, 783–792 (2001 ).

     Not in our library10.1056/nejm200103153441101

140. 140.

     U.S. Food and Drug Administration. List of cleared or approved companion diagnostic devices (in vitro and imaging tools) (2018 ), https://www.fda.gov/medicaldevices/productsandmedicalprocedures/invitrodiagnostics/ucm301431.htm

     Not in our library

141. 141.

     Alqahtani QM, Crowley A, Rapp S & Cushman-Vokoun AM QIAGEN therascreen KRAS RGQ assay, QIAGEN KRAS pyro assay, and dideoxy sequencing for clinical laboratory analysis of KRAS mutations in tumor specimens. Lab. Med 47, 30–38 (2016 ).

     Not in our library10.1093/labmed/lmv009

142. 142.

     U.S. Food and Drug Administration. Paving the way for personalized medicine: FDA’S role in a new era of medical product development (2013 ), https://www.fdanews.com/ext/resources/files/10/10-28-13-Personalized-Medicine.pdf

     Not in our library

143. 143.

     U.S. Food and Drug Administration. Precision medicine (2018 ), https://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/PrecisionMedicine-MedicalDevices/default.htm

     Not in our library

144. 144.

     U.S. Food and Drug Administration. 21st century cures act (2018 ), https://www.fda.gov/RegulatoryInformation/LawsEnforcedbyFDA/SignificantAmendmentstotheFDCAct/21stCenturyCuresAct/default.htm

     Not in our library

145. 145.

     Konski AF Over 30% of new drug approvals in 2017 were personalized medicines, www.personalizedmedicinebulletin.com/2018/02/19/3631/

     Not in our library

146. 146.

     Davio K FDA approved a record number of personalized medicines in 2017 (2018 ), www.ajmc.com/focus-of-the-week/fda-approved-a-record-number-of-personalized-medicines-in-2017

     Not in our library

147. 147.

     Personalized Medicine Coalition. Personalized medicine regulation pathways for oversight of diagnostics, http://www.personalizedmedicinecoalition.org/Userfiles/PMC-Corporate/file/pmc_pathways_for_oversight_diagnostics.pdf

     Not in our library

148. 148.

     Centers for Medicare & Medicaid Services. Clinical laboratory improvement amendments (CLIA) (2018 ), https://www.cms.gov/Regulations-and-Guidance/Legislation/CLIA/index.html?redirect=/CLIA

     Not in our library

149. 149.

     U.S. Food and Drug Administration. Companion diagnostics (2017 ), https://www.fda.gov/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/ucm407297.htm

     Not in our library

150. 150.

     U.S. Food and Drug Administration. Table of pharmacogenomic biomarkers in drug labeling (2018 ), https://www.fda.gov/Drugs/ScienceResearch/ucm572698.htm

     Not in our library

151. 151.

     U.S. Food and Drug Administration. In vitro diagnostics (2018 ), https://www.fda.gov/medicaldevices/productsandmedicalprocedures/invitrodiagnostics/default.htm

     Not in our library

152. 152.

     U.S. Food and Drug Administration. Discussion paper on laboratory developed tests (LDTs) (2017 ), https://www.fda.gov/downloads/MedicalDevices/ProductsandMedicalProcedures/InVitroDiagnostics/LaboratoryDevelopedTests/UCM536965.pdf

     Not in our library

153. 153.

     Kass-Hout TA & Johanson E FDA launches precisionFDA to harness the power of scientific collaboration (2015 ), https://blogs.fda.gov/fdavoice/index.php/2015/12/fda-launches-precisionfda-to-harness-the-power-of-scientific-collaboration/

     Not in our library

154. 154.

     U.S. Food and Drug Administration. Laboratory developed tests (2018 ), www.fda.gov/medicaldevices/productsandmedicalprocedures/invitrodiagnostics/laboratorydevelopedtests/default.htm

     Not in our library

155. 155.

     Mezher M Endpoints News, FDA, NIH look to streamline oversight of gene therapies (2018 ), https://endpts.com/fda-nih-look-to-streamline-oversight-of-gene-therapies/

     Not in our library

156. 156.

     Centers for Medicare & Medicaid Services. NHE fact sheet (2018 ), https://www.cms.gov/research-statistics-data-and-systems/statistics-trends-and-reports/nationalhealthexpenddata/nhe-fact-sheet.html

     Not in our library

157. 157.

     Mullin R Cost to develop new pharmaceutical drug now exceeds $2.5 b. Sci. Am 24, (2014 ).

     Not in our library

158. 158.

     Falconi A, Lopes G & Parker JL Biomarkers and receptor targeted therapies reduce clinical trial risk in non-small-cell lung cancer. J. Thorac. Oncol 9, 163–169 (2014 ).

     Not in our library10.1097/jto.0000000000000075

159. 159.

     Parker JL Impact of biomarkers on clinical trial risk in breast cancer. Breast Cancer Res. Treat 136, 179–185 (2012 ).

     Not in our library10.1007/s10549-012-2247-6

160. 160.

     Parker JL, Zhang ZY & Buckstein R Clinical trial risk in Non-Hodgkin’s lymphoma: Endpoint and target selection. J. Pharm. Pharm. Sci 14, 227–235 (2011 ).

     Not in our library10.18433/j39p45

161. 161.

     Stoekle HC Molecular tumor boards: Ethical issues in the new era of data medicine. Sci. Eng. Ethics 24, 307–322 (2018 ).

     Not in our library10.1007/s11948-017-9880-8

162. 162.

     Sultana J, Cutroneo P & Trifiro G Clinical and economic burden of adverse drug reactions. J. Pharmacol. Pharmacother 4, S73–S77 (2013 ).

     Not in our library10.4103/0976-500x.120957

163. 163.

     Jakka S & Rossbach M An economic perspective on personalized medicine. HUGO J 7, 1 (2013 ).

     Not in our library

164. 164.

     Brixner D The effect of pharmacogenetic profiling with a clinical decision support tool on healthcare resource utilization and estimated costs in the elderly exposed to polypharmacy. J. Med. Econ 19, 213–228 (2016 ).

     Not in our library10.3111/13696998.2015.1110160

165. 165.

     Marrer E & Dieterle F Biomarkers in oncology drug development: Rescuers or troublemakers? Expert Opin. Drug Metab. Toxicol 4, 1391–1402 (2008 ).

     Not in our library10.1517/17425255.4.11.1391

166. 166.

     Business Wire. Foundation medicine announces national agreement with United Healthcare for FoundationOne® in metastatic non-small cell lung cancer (2015 ), http://investors.foundationmedicine.com/news-releases/news-release-details/foundation-medicine-announces-national-agreement

     Not in our library

167. 167.

     Pocius DM Genetic tests and precision medicine start to win acceptance by some payers; pathologists and clinical laboratories have opportunity as advisors (2016 ), https://www.darkdaily.com/genetic-tests-and-precision-medicine-start-to-win-acceptance-by-some-payers-pathologists-and-clinical-laboratories-have-opportunity-as-advisors-314/

     Not in our library

168. 168.

     Centers for Medicare & Medicaid Services. CMS roadmaps overview, https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/QualityInitiativesGenInfo/Downloads/RoadmapOverview_OEA_1-16.pdf

     Not in our library

169. 169.

     Stoeklé H-C Molecular tumor boards: Ethical issues in the new era of data medicine. Sci. Eng. Ethics (2017 ).

     Not in our library10.1007/s11948-017-9880-8

170. 170.

     Mamzer MF Partnering with patients in translational oncology research: Ethical approach. J. Transl. Med 15, 74 (2017 ).

     Not in our library10.1186/s12967-017-1177-9

171. 171.

     Meslin EM & Cho MK Research ethics in the era of personalized medicine: Updating science’s contract with society. Public Health Genomics 13, 378–384 (2010 ).

     Not in our library10.1159/000319473

172. 172.

     Vogenberg FR, Barash CI & Pursel M Personalized medicine part 2: Ethical, legal, and regulatory issues. P T 35, 624–642 (2010 ).

     Not in our library

173. 173.

     Bayer R & Galea S Public health in the precision-medicine era. N. Engl. J. Med 373, 499–501 (2015 ).

     Not in our library10.1056/nejmp1506241

174. 174.

     Schwaederle M Association of biomarker-based treatment strategies with response rates and progression-free survival in refractory malignant neoplasms: A meta-analysis. JAMA Oncol 2, 1452–1459 (2016 ).

     Not in our library10.1001/jamaoncol.2016.2129

175. 175.
     Comparison of Next-Generation Sequencing Systems · 2012

     No notice
176. 176.

     Hagemann IS Chapter 1 — Overview of technical aspects and chemistries of next-generation sequencing. In Clinical Genomics (Academic Press, 2015 ), pp. 3–19.

     Not in our library

177. 177.

     University of Rhode Island Genomics and Sequencing Center, Illumina MiSeq next generation sequencer, https://web.uri.edu/gsc/illumina-miseq-next-generation-sequencer/

     Not in our library

178. 178.

     Illumina. MiSeq system (2016 ), https://www.illumina.com/documents/products/datasheets/datasheet_miseq.pdf

     Not in our library

179. 179.

     Illumina, Inc. Illumina sequencing platforms (2018 ), https://www.illumina.com/systems/sequencing-platforms.html

     Not in our library

180. 180.

     Thermo Fisher Scientific. Solid (2018 ), https://www.thermofisher.com/us/en/home/life-science/sequencing/next-generation-sequencing/solid-next-generation-sequencing/solid-next-generation-sequencing-systems-reagents-accessories.html

     Not in our library

181. 181.

     Pacific Biosciences of California, Inc. SMRT sequencing (2018 ), https://www.pacb.com/smrt-science/smrt-sequencing/

     Not in our library

182. 182.

     Zhang Y, Fonslow BR, Shan B, Baek MC & Yates JR 3rd., Protein analysis by shotgun/bottom-up proteomics. Chem. Rev 113, 2343–2394 (2013 ).

     Not in our library10.1021/cr3003533

183. 183.

     Cox J Andromeda: A peptide search engine integrated into the maxquant environment. J. Proteome Res 10, 1794–1805 (2011 ).

     Not in our library10.1021/pr101065j

184. 184.

     Kusebauch U Using PeptideAtlas, SRMAtlas, and PASSEL: Comprehensive resources for discovery and targeted proteomics. Curr. Protoc. Bioinformatics 13.25. 1–13.25. 28 (2014 ).

     Not in our library10.1002/0471250953.bi1325s46

185. 185.

     Rauniyar N & Yates JR Isobaric labeling-based relative quantification in shotgun proteomics. J. Proteome. Res 13, 5293–5309 (2014 ).

     Not in our library10.1021/pr500880b

186. 186.

     Catherman AD, Skinner OS & Kelleher NL Top down proteomics: Facts and perspectives. Biochem. Biophys. Res. Commun 445, 683–693 (2014 ).

     Not in our library10.1016/j.bbrc.2014.02.041

187. 187.

     DeHart CJ, Fellers RT, Fornelli L, Kelleher NL & Thomas PM Bioinformatics analysis of top-down mass spectrometry data with ProSight Lite. Methods Mol. Biol 381–394 (2017 ).

     Not in our library10.1007/978-1-4939-6783-4_18

188. 188.

     Cristobal A Toward an optimized workflow for middle-down proteomics. Anal. Chem 89, 3318–3325 (2017 ).

     Not in our library10.1021/acs.analchem.6b03756

189. 189.

     Want EJ Solvent-dependent metabolite distribution, clustering, and protein extraction for serum profiling with mass spectrometry. Anal. Chem 78, 743–752 (2006 ).

     Not in our library10.1021/ac051312t

190. 190.

     Yanes O, Tautenhahn R, Patti GJ & Siuzdak G Expanding coverage of the metabolome for global metabolite profiling. Anal. Chem 83, 2152–2161 (2011 ).

     Not in our library10.1021/ac102981k

191. 191.

     Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J & Nielsen J Global metabolite analysis of yeast: Evaluation of sample preparation methods. Yeast 22, 1155–1169 (2005 ).

     Not in our library10.1002/yea.1308

192. 192.

     Smith CA METLIN: A metabolite mass spectral database. Ther. Drug Monit 27, 747–751 (2005 ).

     Not in our library10.1097/01.ftd.0000179845.53213.39

193. 193.

     Wishart DS HMDB 3.0 — The Human Metabolome Database in 2013. Nucleic Acids Res 41, D801–D807 (2013 ).

     Not in our library10.1093/nar/gks1065

194. 194.

     Horai H MassBank: A public repository for sharing mass spectral data for life sciences. J. Mass Spectrom 45, 703–714 (2010 ).

     Not in our library10.1002/jms.1777

195. 195.

     Roberts LD, Souza AL, Gerszten RE & Clish CB Targeted metabolomics. Curr. Protoc. Mol. Biol 30.2.1–30.2.24 (2012 ).

     Not in our library10.1002/0471142727.mb3002s98

Cited by papers we hold 6

• Emerging Therapeutic Strategies to Overcome Drug Resistance in Cancer Cells · 2024
  No notice
• Molecular mechanisms of tumor resistance to radiotherapy · 2023
  No notice
• A scoping review of interactive and personalized web-based clinical tools to support treatment decision making in breast cancer · 2022
  Not checked
• Artificial Intelligence in Colorectal Cancer Screening, Diagnosis and Treatment. A New Era · 2021
  No notice
• Neoantigen: A New Breakthrough in Tumor Immunotherapy · 2021
  No notice
• The CCL20-CCR6 Axis in Cancer Progression · 2020
  No notice

Reads

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.