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Developing biomarker-specific end points in lung cancer clinical trials

Nature Reviews Clinical Oncology volume 12, pages 135–146 (2015)Cite this article

Subjects

Key Points

  • Evaluating overall survival improvement as a cancer clinical trials end point is time-consuming and costly, but traditional radiographic measurements of tumours might not accurately reflect clinical benefit due to confounding factors

  • Molecular imaging aims to augment traditional radiographic measurements by differentiating malignant from normal tissues in order to better capture biological or molecular responses to therapy

  • Circulating tumour factors, such as proteins, DNA, and cells, hold great promise as early predictors of therapeutic response and disease recurrence

  • Tumour-derived factors present in the circulation might also enable early detection of molecular resistance markers and provide information on tumour heterogeneity

  • Pharmacodynamic biomarkers evaluate the biological, molecular, and functional effects of a drug on its target, potentially offering insights into mechanisms of action of new compounds and/or validating new targets

  • Validation of specific biomarkers requires their broad inclusion in clinical trials for assessment of performance

Abstract

In cancer-drug development, a number of different end points have been used to establish efficacy and support regulatory approval, such as overall survival, progression-free survival (PFS), and radiographic response rate. However, these traditional end points have important limitations. For example, in lung cancer clinical trials, evaluating overall survival end points is a protracted process and these end points are most reliable when crossover to the investigational therapy is not permitted. Furthermore, although radiographic surrogate end points, such as PFS and response rate, generally correlate with clinical benefit in the setting of cytotoxic chemotherapy and molecular targeted therapies, novel immunotherapies might have atypical response kinetics, which confounds radiographic interpretation. In this Review, we discuss the need to develop alternative or surrogate end points for lung cancer clinical trials, and focus on several new biomarkers that could serve as surrogate end points, including functional imaging biomarkers, circulating factors (tumour proteins, DNA, and cells), and pharmacodynamic tumour markers. By enabling the size, duration, and complexity of cancer trials to be reduced, biomarker end points hold the promise to accelerate drug development and improve patient outcomes.

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References

  1. Goodman, L. S. et al. Nitrogen mustard therapy; use of methyl-bis (beta-chloroethyl) amine hydrochloride and tris (beta-chloroethyl) amine hydrochloride for Hodgkin's disease, lymphosarcoma, leukemia and certain allied and miscellaneous disorders. J. Am. Med. Assoc. 132, 126–132 (1946).

    CAS  PubMed  Google Scholar 

  2. Farber, S. & Diamond, L. K. Temporary remissions in acute leukemia in children produced by folic acid antagonist, 4-aminopteroyl-glutamic acid. N. Engl. J. Med. 238, 787–793 (1948).

    CAS  PubMed  Google Scholar 

  3. National Comprehensive Cancer Network. NCCN guidelines for treatment of cancer by site: Non-Small Cell Lung Cancer [online], (2014).

  4. [No authors listed] Chemotherapy in non-small cell lung cancer: a meta-analysis using updated data on individual patients from 52 randomised clinical trials. Non-small Cell Lung Cancer Collaborative Group. BMJ 311, 899–909 (1995).

  5. Scagliotti, G. V. et al. Phase III study comparing cisplatin plus gemcitabine with cisplatin plus pemetrexed in chemotherapy-naive patients with advanced-stage non-small-cell lung cancer. J. Clin. Oncol. 26, 3543–3551 (2008).

    CAS  PubMed  Google Scholar 

  6. Hanna, N. et al. Randomized phase III trial of pemetrexed versus docetaxel in patients with non-small-cell lung cancer previously treated with chemotherapy. J. Clin. Oncol. 22, 1589–1597 (2004).

    CAS  PubMed  Google Scholar 

  7. Mok, T. S. et al. Gefitinib or carboplatin-paclitaxel in pulmonary adenocarcinoma. N. Engl. J. Med. 361, 947–957 (2009).

    Article  CAS  PubMed  Google Scholar 

  8. Shaw, A. T. et al. Crizotinib versus chemotherapy in advanced ALK-positive lung cancer. N. Engl. J. Med. 368, 2385–2394 (2013).

    CAS  PubMed  Google Scholar 

  9. Sacher, A. G., Le, L. W. & Leighl, N. B. Shifting patterns in the interpretation of phase III clinical trial outcomes in advanced non-small-cell lung cancer: the bar is dropping. J. Clin. Oncol. 32, 1407–1411 (2014).

    PubMed  Google Scholar 

  10. US Department of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research (CDER) and Center for Biologics Evaluation and Research (CBER). Guidance for Industry: Clinical Trial Endpoints for the Approval of Non-Small Cell Lung Cancer Drugs and Biologics; Draft Guidance [online], (2011).

  11. Kwak, E. L. et al. Anaplastic lymphoma kinase inhibition in non-small-cell lung cancer. N. Engl. J. Med. 363, 1693–1703 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. Crinò, L. et al. Initial phase II results with crizotinib in advanced ALK-positive non-small cell lung cancer (NSCLC): PROFILE 1005 [abstract]. J. Clin. Oncol. 29, a7514 (2011).

    Google Scholar 

  13. Bunn, P. et al. Food and Drug Administration: Workshop Summary on Endpoints for Approval of Cancer Drugs for Lung Cancer [online], (2003).

    Google Scholar 

  14. Eisenhauer, E. A. et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur. J. Cancer 45, 228–247 (2009).

    CAS  PubMed  Google Scholar 

  15. Miller, A. B., Hoogstraten, B., Staquet, M. & Winkler, A. Reporting results of cancer treatment. Cancer 47, 207–214 (1981).

    CAS  PubMed  Google Scholar 

  16. Oxnard, G. R. et al. Variability of lung tumor measurements on repeat computed tomography scans taken within 15 minutes. J. Clin. Oncol. 29, 3114–3119 (2011).

    PubMed  PubMed Central  Google Scholar 

  17. Mozley, P. D. et al. Measurement of tumor volumes improves RECIST-based response assessments in advanced lung cancer. Transl. Oncol. 5, 19–25 (2012).

    PubMed  PubMed Central  Google Scholar 

  18. Nishino, M. et al. CT tumor volume measurement in advanced non-small-cell lung cancer: performance characteristics of an emerging clinical tool. Acad. Radiol. 18, 54–62 (2011).

    PubMed  Google Scholar 

  19. Wolchok, J. D. et al. Guidelines for the evaluation of immune therapy activity in solid tumors: immune-related response criteria. Clin. Cancer Res. 15, 7412–7420 (2009).

    CAS  PubMed  Google Scholar 

  20. Kircher, M. F., Hricak, H. & Larson, S. M. Molecular imaging for personalized cancer care. Mol. Oncol. 6, 182–195 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  21. Cheson, B. D. Role of functional imaging in the management of lymphoma. J. Clin. Oncol. 29, 1844–1854 (2011).

    PubMed  Google Scholar 

  22. Prior, J. O. et al. Early prediction of response to sunitinib after imatinib failure by 18F-fluorodeoxyglucose positron emission tomography in patients with gastrointestinal stromal tumor. J. Clin. Oncol. 27, 439–445 (2009).

    CAS  PubMed  Google Scholar 

  23. Weber, W. A. et al. Positron emission tomography in non-small-cell lung cancer: prediction of response to chemotherapy by quantitative assessment of glucose use. J. Clin. Oncol. 21, 2651–2657 (2003).

    CAS  PubMed  Google Scholar 

  24. Mac Manus, M. P. et al. Positron emission tomography is superior to computed tomography scanning for response-assessment after radical radiotherapy or chemoradiotherapy in patients with non-small-cell lung cancer. J. Clin. Oncol. 21, 1285–1292 (2003).

    PubMed  Google Scholar 

  25. Machtay, M. et al. Prediction of survival by [18F]fluorodeoxyglucose positron emission tomography in patients with locally advanced non-small-cell lung cancer undergoing definitive chemoradiation therapy: results of the ACRIN 6668/RTOG 0235 trial. J. Clin. Oncol. 31, 3823–3830 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Cuaron, J., Dunphy, M. & Rimner, A. Role of FDG-PET scans in staging, response assessment, and follow-up care for non-small cell lung cancer. Front. Oncol. 2, 208 (2012).

    PubMed  Google Scholar 

  27. Rasey, J. S., Grierson, J. R., Wiens, L. W., Kolb, P. D. & Schwartz, J. L. Validation of FLT uptake as a measure of thymidine kinase-1 activity in A549 carcinoma cells. J. Nucl. Med. 43, 1210–1217 (2002).

    CAS  PubMed  Google Scholar 

  28. Buck, A. K. et al. 3-deoxy-3-[18F]fluorothymidine-positron emission tomography for noninvasive assessment of proliferation in pulmonary nodules. Cancer Res. 62, 3331–3334 (2002).

    CAS  PubMed  Google Scholar 

  29. Yang, W. et al. Imaging of proliferation with 18F-FLT PET/CT versus 18F-FDG PET/CT in non-small-cell lung cancer. Eur. J. Nucl. Med. Mol. Imaging 37, 1291–1299 (2010).

    PubMed  Google Scholar 

  30. Sohn, H. J. et al. [18F]Fluorothymidine positron emission tomography before and 7 days after gefitinib treatment predicts response in patients with advanced adenocarcinoma of the lung. Clin. Cancer Res. 14, 7423–7429 (2008).

    CAS  PubMed  Google Scholar 

  31. Leonard, J. P. et al. Selective CDK4/6 inhibition with tumor responses by PD0332991 in patients with mantle cell lymphoma. Blood 119, 4597–4607 (2012).

    CAS  PubMed  Google Scholar 

  32. Holland, J. P., Cumming, P. & Vasdev, N. PET of signal transduction pathways in cancer. J. Nucl. Med. 53, 1333–1336 (2012).

    CAS  PubMed  Google Scholar 

  33. Mankoff, D. A., Pryma, D. A. & Clark, A. S. Molecular imaging biomarkers for oncology clinical trials. J. Nucl. Med. 55, 525–528 (2014).

    CAS  PubMed  Google Scholar 

  34. Weber, B. et al. Erlotinib accumulation in brain metastases from non-small cell lung cancer: visualization by positron emission tomography in a patient harboring a mutation in the epidermal growth factor receptor. J. Thorac. Oncol. 6, 1287–1289 (2011).

    PubMed  Google Scholar 

  35. Memon, A. A. et al. PET imaging of patients with non-small cell lung cancer employing an EGF receptor targeting drug as tracer. Br. J. Cancer 105, 1850–1855 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  36. Bahce, I. et al. Development of [11C]erlotinib positron emission tomography for in vivo evaluation of EGF receptor mutational status. Clin. Cancer Res. 19, 183–193 (2013).

    CAS  PubMed  Google Scholar 

  37. Scher, H. I. et al. Antitumour activity of MDV3100 in castration-resistant prostate cancer: a phase 1–2 study. Lancet 375, 1437–1446 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  38. Topalian, S. L. et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N. Engl. J. Med. 366, 2443–2454 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  39. Brahmer, J. R. et al. Safety and activity of anti-PD-L1 antibody in patients with advanced cancer. N. Engl. J. Med. 366, 2455–2465 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  40. Hamid, O. et al. Safety and tumor responses with lambrolizumab (anti-PD-1) in melanoma. N. Engl. J. Med. 369, 134–144 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. US Department of Health and Human Services, Food and Drug Administration, Center for Biologics Evaluation and Research. Guidance for Industry: Clinical Considerations for Therapeutic Cancer Vaccines [online], (2011).

  42. Aarntzen, E. H. et al. In vivo imaging of therapy-induced anti-cancer immune responses in humans. Cell. Mol. Life Sci. 70, 2237–2257 (2013).

    CAS  PubMed  Google Scholar 

  43. Rustin, G. J. et al. Definitions for response and progression in ovarian cancer clinical trials incorporating RECIST 1.1 and CA 125 agreed by the Gynecological Cancer Intergroup (GCIG). Int. J. Gynecol. Cancer 21, 419–423 (2011).

    PubMed  Google Scholar 

  44. Scher, H. I. et al. Design and end points of clinical trials for patients with progressive prostate cancer and castrate levels of testosterone: recommendations of the Prostate Cancer Clinical Trials Working Group. J. Clin. Oncol. 26, 1148–1159 (2008).

    PubMed  Google Scholar 

  45. Yoshimasu, T. et al. Disappearance curves for tumor markers after resection of intrathoracic malignancies. Int. J. Biol. Markers 14, 99–105 (1999).

    CAS  PubMed  Google Scholar 

  46. Riedinger, J. M. et al. CA 125 half-life and CA 125 nadir during induction chemotherapy are independent predictors of epithelial ovarian cancer outcome: results of a French multicentric study. Ann. Oncol. 17, 1234–1238 (2006).

    CAS  PubMed  Google Scholar 

  47. Krebs, M. G. et al. Molecular analysis of circulating tumour cells-biology and biomarkers. Nat. Rev. Clin. Oncol. 11, 129–144 (2014).

    CAS  PubMed  Google Scholar 

  48. Janssen Diagnostics. CELLSEARCH® Circulating Tumor Cell Test [online], (2014).

  49. Hayes, D. F. et al. Circulating tumor cells at each follow-up time point during therapy of metastatic breast cancer patients predict progression-free and overall survival. Clin. Cancer Res. 12, 4218–4224 (2006).

    CAS  PubMed  Google Scholar 

  50. Krebs, M. G. et al. Evaluation and prognostic significance of circulating tumor cells in patients with non-small-cell lung cancer. J. Clin. Oncol. 29, 1556–1563 (2011).

    PubMed  Google Scholar 

  51. Maheswaran, S. et al. Detection of mutations in EGFR in circulating lung-cancer cells. N. Engl. J. Med. 359, 366–377 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  52. Pailler, E. et al. Detection of circulating tumor cells harboring a unique ALK rearrangement in ALK-positive non-small-cell lung cancer. J. Clin. Oncol. 31, 2273–2281 (2013).

    PubMed  Google Scholar 

  53. Punnoose, E. A. et al. Evaluation of circulating tumor cells and circulating tumor DNA in non-small cell lung cancer: association with clinical endpoints in a phase II clinical trial of pertuzumab and erlotinib. Clin. Cancer Res. 18, 2391–2401 (2012).

    CAS  PubMed  Google Scholar 

  54. Diehl, F. et al. Circulating mutant DNA to assess tumor dynamics. Nat. Med. 14, 985–990 (2008).

    CAS  PubMed  Google Scholar 

  55. Sozzi, G. et al. Quantification of free circulating DNA as a diagnostic marker in lung cancer. J. Clin. Oncol. 21, 3902–3908 (2003).

    CAS  PubMed  Google Scholar 

  56. Gautschi, O. et al. Circulating deoxyribonucleic acid as prognostic marker in non-small-cell lung cancer patients undergoing chemotherapy. J. Clin. Oncol. 22, 4157–4164 (2004).

    CAS  PubMed  Google Scholar 

  57. Kimura, H. et al. Detection of epidermal growth factor receptor mutations in serum as a predictor of the response to gefitinib in patients with non-small-cell lung cancer. Clin. Cancer Res. 12, 3915–3921 (2006).

    CAS  PubMed  Google Scholar 

  58. Kuang, Y. et al. Noninvasive detection of EGFR T790M in gefitinib or erlotinib resistant non-small cell lung cancer. Clin. Cancer Res. 15, 2630–2636 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. Rosell, R. et al. Screening for epidermal growth factor receptor mutations in lung cancer. N. Engl. J. Med. 361, 958–967 (2009).

    CAS  PubMed  Google Scholar 

  60. Taniguchi, K. et al. Quantitative detection of EGFR mutations in circulating tumor DNA derived from lung adenocarcinomas. Clin. Cancer Res. 17, 7808–7815 (2011).

    CAS  PubMed  Google Scholar 

  61. Oxnard, G. R. et al. Noninvasive detection of response and resistance in EGFR-mutant lung cancer using quantitative next-generation genotyping of cell-free plasma DNA. Clin. Cancer Res. 20, 1698–1705 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. Murtaza, M. et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 497, 108–112 (2013).

    CAS  PubMed  Google Scholar 

  63. Newman, A. M. et al. An ultrasensitive method for quantitating circulating tumor DNA with broad patient coverage. Nat. Med. 20, 548–554 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. Dawson, S. J., Rosenfeld, N. & Caldas, C. Circulating tumor DNA to monitor metastatic breast cancer. N. Engl. J. Med. 369, 93–94 (2013).

    CAS  PubMed  Google Scholar 

  65. Wang, W. et al. Biomarkers on melanoma patient T cells associated with ipilimumab treatment. J. Transl. Med. 10, 146 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. Comin-Anduix, B. et al. Detailed analysis of immunologic effects of the cytotoxic T lymphocyte-associated antigen 4-blocking monoclonal antibody tremelimumab in peripheral blood of patients with melanoma. J. Transl. Med. 6, 22 (2008).

    PubMed  PubMed Central  Google Scholar 

  67. Grosso, J. F. & Jure-Kunkel, M. N. CTLA-4 blockade in tumor models: an overview of preclinical and translational research. Cancer Immun. 13, 5 (2013).

    PubMed  PubMed Central  Google Scholar 

  68. Morse, M. A., Osada, T., Hobeika, A., Patel, S. & Lyerly, H. K. Biomarkers and correlative endpoints for immunotherapy trials. Am. Soc. Clin. Oncol. Educ. Book http://dx.doi.org/10.1200/EdBook_AM.2013.33.e287 (2013).

  69. Rojo, F., Dalmases, A., Corominas, J. M. & Albanell, J. Pharmacodynamics: biological activity of targeted therapies in clinical trials. Clin. Transl. Oncol. 9, 634–644 (2007).

    CAS  PubMed  Google Scholar 

  70. Ang, J. E., Kaye, S. & Banerji, U. Tissue-based approaches to study pharmacodynamic endpoints in early phase oncology clinical trials. Curr. Drug Targets 13, 1525–1534 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. Adjei, A. A. et al. Phase I pharmacokinetic and pharmacodynamic study of the oral, small-molecule mitogen-activated protein kinase kinase 1/2 inhibitor AZD6244 (ARRY-142886) in patients with advanced cancers. J. Clin. Oncol. 26, 2139–2146 (2008).

    CAS  PubMed  Google Scholar 

  72. Yap, T. A. et al. Phase I trial of a selective c-MET inhibitor ARQ 197 incorporating proof of mechanism pharmacodynamic studies. J. Clin. Oncol. 29, 1271–1279 (2011).

    CAS  PubMed  Google Scholar 

  73. Trunzer, K. et al. Pharmacodynamic effects and mechanisms of resistance to vemurafenib in patients with metastatic melanoma. J. Clin. Oncol. 31, 1767–1774 (2013).

    CAS  PubMed  Google Scholar 

  74. Felip, E. et al. A phase II pharmacodynamic study of erlotinib in patients with advanced non-small cell lung cancer previously treated with platinum-based chemotherapy. Clin. Cancer Res. 14, 3867–3874 (2008).

    CAS  PubMed  Google Scholar 

  75. Spector, N. L. et al. Study of the biologic effects of lapatinib, a reversible inhibitor of ErbB1 and ErbB2 tyrosine kinases, on tumor growth and survival pathways in patients with advanced malignancies. J. Clin. Oncol. 23, 2502–2512 (2005).

    CAS  PubMed  Google Scholar 

  76. Flaherty, K. T. et al. Inhibition of mutated, activated BRAF in metastatic melanoma. N. Engl. J. Med. 363, 809–819 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. Shapiro, G. I. et al. Phase I safety, pharmacokinetic, and pharmacodynamic study of SAR245408 (XL147), an oral pan-class I PI3K inhibitor, in patients with advanced solid tumors. Clin. Cancer Res. 20, 233–245 (2014).

    CAS  PubMed  Google Scholar 

  78. Armstrong, A. J. et al. A pharmacodynamic study of rapamycin in men with intermediate- to high-risk localized prostate cancer. Clin. Cancer Res. 16, 3057–3066 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. Weekes, C. D. et al. Multicenter phase I trial of the mitogen-activated protein kinase 1/2 inhibitor BAY 86–9766 in patients with advanced cancer. Clin. Cancer Res. 19, 1232–1243 (2013).

    CAS  PubMed  Google Scholar 

  80. Banerji, U. et al. Phase I pharmacokinetic and pharmacodynamic study of 17-allylamino, 17-demethoxygeldanamycin in patients with advanced malignancies. J. Clin. Oncol. 23, 4152–4161 (2005).

    CAS  PubMed  Google Scholar 

  81. Bundred, N. et al. Evaluation of the pharmacodynamics and pharmacokinetics of the PARP inhibitor olaparib: a phase I multicentre trial in patients scheduled for elective breast cancer surgery. Invest. New Drugs 31, 949–958 (2013).

    CAS  PubMed  Google Scholar 

  82. Venugopal, B. et al. A phase I study of quisinostat (JNJ-26481585), an oral hydroxamate histone deacetylase inhibitor with evidence of target modulation and antitumor activity, in patients with advanced solid tumors. Clin. Cancer Res. 19, 4262–4272 (2013).

    CAS  PubMed  Google Scholar 

  83. Gomez-Roca, C. A. et al. Sequential research-related biopsies in phase I trials: acceptance, feasibility and safety. Ann. Oncol. 23, 1301–1306 (2012).

    CAS  PubMed  Google Scholar 

  84. Dowlati, A. et al. Sequential tumor biopsies in early phase clinical trials of anticancer agents for pharmacodynamic evaluation. Clin. Cancer Res. 7, 2971–2976 (2001).

    CAS  PubMed  Google Scholar 

  85. Tam, A. L. et al. Feasibility of image-guided transthoracic core-needle biopsy in the BATTLE lung trial. J. Thorac. Oncol. 8, 436–442 (2013).

    PubMed  Google Scholar 

  86. Sequist, L. V. et al. Genotypic and histological evolution of lung cancers acquiring resistance to EGFR inhibitors. Sci. Transl. Med. 3, 75ra26 (2011).

    PubMed  PubMed Central  Google Scholar 

  87. Arcila, M. E. et al. Rebiopsy of lung cancer patients with acquired resistance to EGFR inhibitors and enhanced detection of the T790M mutation using a locked nucleic acid-based assay. Clin. Cancer Res. 17, 1169–1180 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. Katayama, R. et al. Mechanisms of acquired crizotinib resistance in ALK-rearranged lung cancers. Sci. Transl. Med. 4, 120ra117 (2012).

    Google Scholar 

  89. Doebele, R. C. et al. Mechanisms of resistance to crizotinib in patients with ALK gene rearranged non-small cell lung cancer. Clin. Cancer Res. 18, 1472–1482 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. Awad, M. M. et al. Acquired resistance to crizotinib from a mutation in CD74–ROS1. N. Engl. J. Med. 368, 2395–2401 (2013).

    CAS  PubMed  Google Scholar 

  91. Gainor, J. F. & Shaw, A. T. Emerging paradigms in the development of resistance to tyrosine kinase inhibitors in lung cancer. J. Clin. Oncol. 31, 3987–3996 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  92. US National Library of Medicine. ClinicalTrials.gov [online], (2014).

  93. Kobayashi, S. et al. EGFR mutation and resistance of non-small-cell lung cancer to gefitinib. N. Engl. J. Med. 352, 786–792 (2005).

    CAS  PubMed  Google Scholar 

  94. Lai, T. L., Lavori, P. W. & Shih, M. C. Sequential design of phase II–III cancer trials. Stat. Med. 31, 1944–1960 (2012).

    PubMed  PubMed Central  Google Scholar 

  95. Wozniak, A. J. et al. Randomized trial comparing cisplatin with cisplatin plus vinorelbine in the treatment of advanced non-small-cell lung cancer: a Southwest Oncology Group study. J. Clin. Oncol. 16, 2459–2465 (1998).

    CAS  PubMed  Google Scholar 

  96. Sandler, A. B. et al. Phase III trial of gemcitabine plus cisplatin versus cisplatin alone in patients with locally advanced or metastatic non-small-cell lung cancer. J. Clin. Oncol. 18, 122–130 (2000).

    CAS  PubMed  Google Scholar 

  97. Shepherd, F. A. et al. Erlotinib in previously treated non-small-cell lung cancer. N. Engl. J. Med. 353, 123–132 (2005).

    CAS  PubMed  Google Scholar 

  98. Shepherd, F. A. et al. Prospective randomized trial of docetaxel versus best supportive care in patients with non-small-cell lung cancer previously treated with platinum-based chemotherapy. J. Clin. Oncol. 18, 2095–2103 (2000).

    CAS  PubMed  Google Scholar 

  99. Sandler, A. et al. Paclitaxel–carboplatin alone or with bevacizumab for non-small-cell lung cancer. N. Engl. J. Med. 355, 2542–2550 (2006).

    CAS  PubMed  Google Scholar 

  100. Rosell, R. et al. Erlotinib versus standard chemotherapy as first-line treatment for European patients with advanced EGFR mutation-positive non-small-cell lung cancer (EURTAC): a multicentre, open-label, randomised phase 3 trial. Lancet Oncol. 13, 239–246 (2012).

    CAS  PubMed  Google Scholar 

  101. Sequist, L. V. et al. Phase III study of afatinib or cisplatin plus pemetrexed in patients with metastatic lung adenocarcinoma with EGFR mutations. J. Clin. Oncol. 31, 3327–3334 (2013).

    CAS  PubMed  Google Scholar 

  102. Sequist, L. V. et al. First-in-human evaluation of CO-1686, an irreversible, highly selective tyrosine kinase inhibitor of mutations of EGFR (activating and T790M) [abstract]. J. Clin. Oncol. 32 (Suppl. 5s), a8010 (2014).

    Google Scholar 

  103. Janne, P. A. et al. Clinical activity of the mutant-selective EGFR inhibitor AZD9291 in patients (pts) with EGFR inhibitor-resistant non-small cell lung cancer (NSCLC) [abstract]. J. Clin. Oncol. 32 (Suppl. 5s), a8009 (2014).

    Google Scholar 

  104. Camidge, D. R. et al. Activity and safety of crizotinib in patients with ALK-positive non-small-cell lung cancer: updated results from a phase 1 study. Lancet Oncol. 13, 1011–1019 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  105. Shaw, A. T. et al. Ceritinib in ALK-rearranged non-small-cell lung cancer. N. Engl. J. Med. 370, 1189–1197 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. Gadgeel, S. M. et al. Safety and activity of alectinib against systemic disease and brain metastases in patients with crizotinib-resistant ALK-rearranged non-small-cell lung cancer (AF-002JG): results from the dose-finding portion of a phase 1/2 study. Lancet Oncol. 15, 1119–1128 (2014).

    CAS  PubMed  Google Scholar 

  107. Planchard, D. et al. Interim results of phase II study BRF113928 of dabrafenib in BRAF V600E mutation-positive non-small cell lung cancer (NSCLC) patients [abstract]. J. Clin. Oncol. 31, a8009 (2013).

    Google Scholar 

  108. Kramer, G. M. et al. CT-perfusion versus [15O]H2O PET in lung tumors: effects of CT-perfusion methodology. Med. Phys. 40, 052502 (2013).

    CAS  PubMed  Google Scholar 

  109. Bruehlmeier, M., Roelcke, U., Schubiger, P. A. & Ametamey, S. M. Assessment of hypoxia and perfusion in human brain tumors using PET with 18F-fluoromisonidazole and 15O-H2O. J. Nucl. Med. 45, 1851–1859 (2004).

    PubMed  Google Scholar 

  110. Eschmann, S. M. et al. Prognostic impact of hypoxia imaging with 18F-misonidazole PET in non-small cell lung cancer and head and neck cancer before radiotherapy. J. Nucl. Med. 46, 253–260 (2005).

    PubMed  Google Scholar 

  111. Dehdashti, F. et al. In vivo assessment of tumor hypoxia in lung cancer with 60Cu-ATSM. Eur. J. Nucl. Med. Mol. Imaging 30, 844–850 (2003).

    CAS  PubMed  Google Scholar 

  112. Dehdashti, F. et al. Assessing tumor hypoxia in cervical cancer by positron emission tomography with 60Cu-ATSM: relationship to therapeutic response—a preliminary report. Int. J. Radiat. Oncol. Biol. Phys. 55, 1233–1238 (2003).

    PubMed  Google Scholar 

  113. Dietz, D. W. et al. Tumor hypoxia detected by positron emission tomography with 60Cu-ATSM as a predictor of response and survival in patients undergoing neoadjuvant chemoradiotherapy for rectal carcinoma: a pilot study. Dis. Colon Rectum 51, 1641–1648 (2008).

    PubMed  PubMed Central  Google Scholar 

  114. Terakawa, Y. et al. Diagnostic accuracy of 11C-methionine PET for differentiation of recurrent brain tumors from radiation necrosis after radiotherapy. J. Nucl. Med. 49, 694–699 (2008).

    PubMed  Google Scholar 

  115. Aki, T. et al. Evaluation of brain tumors using dynamic 11C-methionine-PET. J. Neurooncol. 109, 115–122 (2012).

    PubMed  Google Scholar 

  116. Pruim, J. et al. Brain tumors: L-[1-C-11]tyrosine PET for visualization and quantification of protein synthesis rate. Radiology 197, 221–226 (1995).

    CAS  PubMed  Google Scholar 

  117. de Boer, J. R. et al. L-1-11C-tyrosine PET in patients with laryngeal carcinomas: comparison of standardized uptake value and protein synthesis rate. J. Nucl. Med. 44, 341–346 (2003).

    CAS  PubMed  Google Scholar 

  118. Nguyen, Q. D., Challapalli, A., Smith, G., Fortt, R. & Aboagye, E. O. Imaging apoptosis with positron emission tomography: 'bench to bedside' development of the caspase-3/7 specific radiotracer [18F]ICMT-11. Eur. J. Cancer 48, 432–440 (2012).

    CAS  PubMed  Google Scholar 

  119. Challapalli, A. et al. 18F-ICMT-11, a caspase-3-specific PET tracer for apoptosis: biodistribution and radiation dosimetry. J. Nucl. Med. 54, 1551–1556 (2013).

    CAS  PubMed  Google Scholar 

  120. Yagle, K. J. et al. Evaluation of 18F-annexin V as a PET imaging agent in an animal model of apoptosis. J. Nucl. Med. 46, 658–666 (2005).

    CAS  PubMed  Google Scholar 

  121. Dumont, R. A. et al. Novel 64Cu- and 68Ga-labeled RGD conjugates show improved PET imaging of ανβ3 integrin expression and facile radiosynthesis. J. Nucl. Med. 52, 1276–1284 (2011).

    CAS  PubMed  Google Scholar 

  122. Beer, A. J. & Schwaiger, M. Imaging of integrin alphavbeta3 expression. Cancer Metastasis Rev. 27, 631–644 (2008).

    CAS  PubMed  Google Scholar 

  123. Wang, H. et al. A new PET tracer specific for vascular endothelial growth factor receptor 2. Eur. J. Nucl. Med. Mol. Imaging 34, 2001–2010 (2007).

    CAS  PubMed  Google Scholar 

  124. Umbehr, M. H., Müntener, M., Hany, T., Sulser, T. & Bachmann, L. M. The role of 11C-choline and 18F-fluorocholine positron emission tomography (PET) and PET/CT in prostate cancer: a systematic review and meta-analysis. Eur. Urol. 64, 106–117 (2013).

    PubMed  Google Scholar 

  125. Poeppel, T. D. et al. 68Ga-DOTATOC versus 68Ga-DOTATATE PET/CT in functional imaging of neuroendocrine tumors. J. Nucl. Med. 52, 1864–1870 (2011).

    CAS  PubMed  Google Scholar 

  126. Linden, H. M. et al. Quantitative fluoroestradiol positron emission tomography imaging predicts response to endocrine treatment in breast cancer. J. Clin. Oncol. 24, 2793–2799 (2006).

    CAS  PubMed  Google Scholar 

  127. Dijkers, E. C. et al. Biodistribution of 89Zr-trastuzumab and PET imaging of HER2-positive lesions in patients with metastatic breast cancer. Clin. Pharmacol. Ther. 87, 586–592 (2010).

    CAS  PubMed  Google Scholar 

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Acknowledgements

We thank Dr Phil Lavori for helpful discussions surrounding statistical implications of biomarker-driven clinical trials. The work of J.F.G. is funded in part by the NIH National Cancer Institute (Grant: C06CA059267). The work of A.T.S. is funded in part by the NIH National Cancer Institute (Grant: R01CA164273).

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Authors and Affiliations

  1. Department of Medicine, Division of Oncology, Stanford Cancer Institute and Stanford University School of Medicine, Stanford University, 875 Blake Wilbur Drive, Stanford, 94305, CA, USA

    Joel W. Neal

  2. Division of Hematology–Oncology, Massachusetts General Hospital Cancer Center, Massachusetts General Hospital, 32 Fruit Street, Boston, 02114, MA, USA

    Justin F. Gainor & Alice T. Shaw

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  1. Joel W. Neal
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  2. Justin F. Gainor
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  3. Alice T. Shaw
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All authors made substantial contributions to each stage of the preparation of the manuscript for submission.

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Correspondence to Alice T. Shaw.

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Competing interests

J.W.N. has received grants for research support from ArQule, Boehringer–Ingelheim, Merck and Roche/Genentech, and has acted as a consultant for Clovis Oncology. J.F.G. has acted as a consultant for Boehringer–Ingelheim, Jounce Therapeutics and Kyowa Hakko Kirin. A.T.S. has acted as a consultant for Ariad, Chugai, Genentech, Ignyta, Novartis and Pfizer, and has received honouraria for speaking for Novartis, Pfizer and Roche.

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Neal, J., Gainor, J. & Shaw, A. Developing biomarker-specific end points in lung cancer clinical trials. Nat Rev Clin Oncol 12, 135–146 (2015). https://doi.org/10.1038/nrclinonc.2014.222

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