Development of tumor mutation burden as an immunotherapy biomarker: utility for the oncology clinic

T A Chan, M Yarchoan, E Jaffee, C Swanton, S A Quezada, A Stenzinger, S Peters, T A Chan, M Yarchoan, E Jaffee, C Swanton, S A Quezada, A Stenzinger, S Peters

Abstract

Background: Treatment with immune checkpoint blockade (ICB) with agents such as anti-programmed cell death protein 1 (PD-1), anti-programmed death-ligand 1 (PD-L1), and/or anti-cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) can result in impressive response rates and durable disease remission but only in a subset of patients with cancer. Expression of PD-L1 has demonstrated utility in selecting patients for response to ICB and has proven to be an important biomarker for patient selection. Tumor mutation burden (TMB) is emerging as a potential biomarker. However, refinement of interpretation and contextualization is required.

Materials and methods: In this review, we outline the evolution of TMB as a biomarker in oncology, delineate how TMB can be applied in the clinic, discuss current limitations as a diagnostic test, and highlight mechanistic insights unveiled by the study of TMB. We review available data to date studying TMB as a biomarker for response to ICB by tumor type, focusing on studies proposing a threshold for TMB as a predictive biomarker for ICB activity.

Results: High TMB consistently selects for benefit with ICB therapy. In lung, bladder and head and neck cancers, the current predictive TMB thresholds proposed approximate 200 non-synonymous somatic mutations by whole exome sequencing (WES). PD-L1 expression influences response to ICB in high TMB tumors with single agent PD-(L)1 antibodies; however, response may not be dependent on PD-L1 expression in the setting of anti-CTLA4 or anti-PD-1/CTLA-4 combination therapy. Disease-specific TMB thresholds for effective prediction of response in various other malignancies are not well established.

Conclusions: TMB, in concert with PD-L1 expression, has been demonstrated to be a useful biomarker for ICB selection across some cancer types; however, further prospective validation studies are required. TMB determination by selected targeted panels has been correlated with WES. Calibration and harmonization will be required for optimal utility and alignment across all platforms currently used internationally. Key challenges will need to be addressed before broader use in different tumor types.

Figures

Figure 1.
Figure 1.
The evolution of tumor mutation burden as an immunotherapy biomarker. Major studies that are important in the development of TMB as a biomarker are shown. Color coding indicates type of study. The studies are ordered as a function of time, with the year indicated in the timeline. ICB, immune checkpoint blockade; 1L, first line; 2L, second line; +, and others; I-O, immune-oncology agent; IPI, ipilimumab; NIVO, nivolumab; NSCLC, non-small cell lung cancer; SCLC, small cell lung cancer; TMB, tumor mutational burden. 1. Snyder A et al. N Engl J Med 2014; 371(23): 2189–2199. 2. Rooney MS et al. Cell 2015; 160(1–2): 48–61. 3. Rizvi NA et al. Science 2015; 348(6230): 124–128. 4. Rosenberg JE et al. Lancet 2016; 387(10031): 1909–1920. 5. Kowanetz M et al. Poster presentation at ESMO 2016. Abstract 77P. 6. Kowanetz M et al. Oral presentation at WCLC 2016. Abstract 6149. 7. Balar AV et al. Lancet 2017; 389(10064): 67–76. 8. Seiwert TW et al. J Clin Oncol 2018; 36(suppl 5S; abstract 25). 9. Chalmers ZR et al. Genome Med 2017; 9(1): 34. 10. Zehir A et al. Nat Med 2017; 23(6): 703–713. 11. Carbone DP et al. N Engl J Med 2017; 376(25): 2415–2426. 12 Galsky MD et al. Poster presentation at ESMO 2017. Abstract 848PD. 13. Gandara DR et al. Oral presentation at ESMO 2017. Abstract 1295O. 14. Fabrizio DA et al. Poster presentation at ESMO 2017. Abstract 102P. 15. Mok T et al. Poster presentation at ESMO 2017. Abstract 1383TiP. 16. Antonia SJ et al. Oral presentation at WCLC 2017. Abstract 11063. 17. Riaz N et al. Cell 2017; 171(4): 934–949. 18. Foundation Medicine. http://investors.foundationmedicine.com/releasedetail.cfm?ReleaseID=1050380 (11 December 2017, date last accessed). 19. US Food and Drug Administration. https://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm585347.htm (1 December 2017, date last accessed). 20. Hellmann MD et al. N Engl J Med 2018, doi: 10.1056/NEJMoa1801946. 21. Forde PM et al. N Engl J Med 2018, doi: 10.1056/NEJMoa1716078. 22. Cristescu et al. Science 2018; 362(6411).
Figure 2.
Figure 2.
Target regions and sizes of four different hypothetical gene panels (P1–P4). Depending on the size and territory of the exome that is captured by P1–P4, respectively, TMB counts will differ. Other parameters, e.g. filtering of germline variants and cut points for allelic frequencies (blue circles), discussed in this review will influence TMB measurement further.
Figure 3.
Figure 3.
Mutations, neoantigens, and immune checkpoint blockade. Somatic mutations can generate neopeptides that are presented by MHC molecules. Both inflamed and non-inflamed tumors, as well as PD-L1 positive or negative tumors, can respond to immune checkpoint blockade therapy. TMB, tumor mutation burden; MMR, mismatch repair.
Figure 4.
Figure 4.
Impact of TMB pan-cancer: percent of solid tumors with TMB ≥10 mut/Mb. Analysis of top 30 solid tumor types selected from 104,814 total cases sorted by percent of cases with TMB ≥10 mut/Mb according to the Foundation Medicine database. TMB is defined as the number of somatic synonymous and non-synonymous base substitutions and indels divided by the region over which it was counted. Only cancer types with at least 100 total cases are reported. The average across all solid tumor types was 13.3%.

References

    1. Hodi FS, O'Day SJ, McDermott DF. et al. Improved survival with ipilimumab in patients with metastatic melanoma. N Engl J Med 2010; 363: 711–723.
    1. Borghaei H, Paz-Ares L, Horn L. et al. Nivolumab versus docetaxel in advanced nonsquamous non-small-cell lung cancer. N Engl J Med 2015; 373(17): 1627–1639.
    1. Motzer RJ, Escudier B, McDermott DF. et al. Nivolumab versus everolimus in advanced renal-cell carcinoma. N Engl J Med 2015; 373(19): 1803–1813.
    1. Rosenberg JE, Hoffman-Censits J, Powles T. et al. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. Lancet 2016; 387(10031): 1909–1920.
    1. Wolchok JD, Kluger H, Callahan MK. et al. Nivolumab plus ipilimumab in advanced melanoma. N Engl J Med 2013; 369(2): 122–133.
    1. Motzer RJ, Tannir NM, McDermott DF. et al. Nivolumab plus ipilimumab versus sunitinib in advanced renal-cell carcinoma. N Engl J Med 2018; 378(14): 1277–1290.
    1. Antonia SJ, Villegas A, Daniel D. et al. Durvalumab after chemoradiotherapy in stage III non-small-cell lung cancer. N Engl J Med 2017; 377(20): 1919–1929.
    1. Nghiem PT, Bhatia S, Lipson EJ. et al. PD-1 blockade with pembrolizumab in advanced Merkel-cell carcinoma. N Engl J Med 2016; 374(26): 2542–2552.
    1. Krummel MF, Allison JP.. CD28 and CTLA-4 have opposing effects on the response of T cells to stimulation. J Exp Med 1995; 182(2): 459–465.
    1. Brown KE, Freeman GJ, Wherry EJ, Sharpe AH.. Role of PD-1 in regulating acute infections. Curr Opin Immunol 2010; 22(3): 397–401.
    1. Iwai Y, Ishida M, Tanaka Y. et al. Involvement of PD-L1 on tumor cells in the escape from host immune system and tumor immunotherapy by PD-L1 blockade. Proc Natl Acad Sci USA 2002; 99(19): 12293–12297.
    1. Dunn GP, Old LJ, Schreiber RD.. The immunobiology of cancer immunosurveillance and immunoediting. Immunity 2004; 21(2): 137–148.
    1. Leach DR, Krummel MF, Allison JP.. Enhancement of antitumor immunity by CTLA-4 blockade. Science 1996; 271(5256): 1734–1736.
    1. Pardoll DM. The blockade of immune checkpoints in cancer immunotherapy. Nat Rev Cancer 2012; 12(4): 252–264.
    1. Reck M, Rodriguez-Abreu D, Robinson AG. et al. Pembrolizumab versus chemotherapy for PD-L1-positive non-small-cell lung cancer. N Engl J Med 2016; 375(19): 1823–1833.
    1. Herbst RS, Baas P, Kim DW. et al. Pembrolizumab versus docetaxel for previously treated, PD-L1-positive, advanced non-small-cell lung cancer (KEYNOTE-010): a randomised controlled trial. Lancet 2016; 387(10027): 1540–1550.
    1. Bellmunt J, de Wit R, Vaughn DJ. et al. Pembrolizumab as second-line therapy for advanced urothelial carcinoma. N Engl J Med 2017; 376(11): 1015–1026.
    1. Muro K, Chung HC, Shankaran V. et al. Pembrolizumab for patients with PD-L1-positive advanced gastric cancer (KEYNOTE-012): a multicentre, open-label, phase 1b trial. Lancet Oncol 2016; 17(6): 717–726.
    1. Fuchs CS, Doi T, Jang RW. et al. Safety and efficacy of pembrolizumab monotherapy in patients with previously treated advanced gastric and gastroesophageal junction cancer: phase 2 Clinical KEYNOTE-059 Trial. JAMA Oncol 2018; 4(5): e180013..
    1. Chung HC, Schellens JHM, Delord JP. et al. Pembrolizumab treatment of advanced cervical cancer: updated results from the phase 2 KEYNOTE-158 study. JCO 2018; 36(Suppl 15): 5522–5522.
    1. Powles T, Duran I, van der Heijden MS. et al. 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 2018; 391(10122): 748–757.
    1. Ferris RL, Blumenschein G Jr, Fayette J. et al. Nivolumab for recurrent squamous-cell carcinoma of the head and neck. N Engl J Med 2016; 375(19): 1856–1867.
    1. Ott PA, Elez E, Hiret S. et al. Pembrolizumab in patients with extensive-stage small-cell lung cancer: results from the phase Ib KEYNOTE-028 Study. J Clin Oncol 2017; 35(34): 3823–3829.
    1. Tumeh PC, Harview CL, Yearley JH. et al. PD-1 blockade induces responses by inhibiting adaptive immune resistance. Nature 2014; 515(7528): 568–571.
    1. Fridman WH, Pages F, Sautes-Fridman C, Galon J.. The immune contexture in human tumours: impact on clinical outcome. Nat Rev Cancer 2012; 12(4): 298–306.
    1. Cristescu R, Mogg R, Ayers M. et al. Pan-tumor genomic biomarkers for PD-1 checkpoint blockade-based immunotherapy. Science 2018; 362 (6411): doi: 10.1126/science.aar3593.
    1. Auslander N, Zhang G, Lee JS. et al. Robust prediction of response to immune checkpoint blockade therapy in metastatic melanoma. Nat Med 2018; 24(10): 1545–1549.
    1. Jiang P, Gu S, Pan D. et al. Signatures of T cell dysfunction and exclusion predict cancer immunotherapy response. Nat Med 2018; 24(10): 1550–1558.
    1. Roy S, Trinchieri G.. Microbiota: a key orchestrator of cancer therapy. Nat Rev Cancer 2017; 17(5): 271–285.
    1. Routy B, Le Chatelier E, Derosa L. et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 2018; 359(6371): 91–97.
    1. Gopalakrishnan V, Spencer CN, Nezi L. et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 2018; 359(6371): 97–103.
    1. Sjoblom T, Jones S, Wood LD. et al. The consensus coding sequences of human breast and colorectal cancers. Science 2006; 314(5797): 268–274.
    1. Wood LD, Parsons DW, Jones S. et al. The genomic landscapes of human breast and colorectal cancers. Science 2007; 318(5853): 1108–1113.
    1. Kinzler KW, Vogelstein B.. Landscaping the cancer terrain. Science 1998; 280(5366): 1036–1037.
    1. Lawrence MS, Stojanov P, Polak P. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 2013; 499(7457): 214–218.
    1. Ciriello G, Miller ML, Aksoy BA. et al. Emerging landscape of oncogenic signatures across human cancers. Nat Genet 2013; 45(10): 1127–1133.
    1. Chalmers ZR, Connelly CF, Fabrizio D. et al. Analysis of 100, 000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med 2017; 9(1): 34.
    1. Zehir A, Benayed R, Shah RH. et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med 2017; 23(6): 703–713.
    1. Snyder A, Makarov V, Merghoub T. et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med 2014; 371(23): 2189–2199.
    1. Rizvi NA, Hellmann MD, Snyder A. et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 2015; 348(6230): 124–128.
    1. Hugo W, Zaretsky JM, Sun L. et al. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell 2016; 165(1): 35–44.
    1. Carbone DP, Reck M, Paz-Ares L. et al. First-line nivolumab in stage IV or recurrent non-small-cell lung cancer. N Engl J Med 2017; 376(25): 2415–2426.
    1. Matsushita H, Vesely MD, Koboldt DC. et al. Cancer exome analysis reveals a T-cell-dependent mechanism of cancer immunoediting. Nature 2012; 482(7385): 400–404.
    1. Riaz N, Morris L, Havel JJ. et al. The role of neoantigens in response to immune checkpoint blockade. Int Immunol 2016; 28(8): 411–419.
    1. Ott PA, Hu Z, Keskin DB. et al. An immunogenic personal neoantigen vaccine for patients with melanoma. Nature 2017; 547(7662): 217–221.
    1. Cohen CJ, Gartner JJ, Horovitz-Fried M. et al. Isolation of neoantigen-specific T cells from tumor and peripheral lymphocytes. J Clin Invest 2015; 125(10): 3981–3991.
    1. Coulie PG, Van den Eynde BJ, van der Bruggen P, Boon T.. Tumour antigens recognized by T lymphocytes: at the core of cancer immunotherapy. Nat Rev Cancer 2014; 14(2): 135–146.
    1. Carreno BM, Magrini V, Becker-Hapak M. et al. Cancer immunotherapy. A dendritic cell vaccine increases the breadth and diversity of melanoma neoantigen-specific T cells. Science 2015; 348(6236): 803–808.
    1. Bassani-Sternberg M, Braunlein E, Klar R. et al. Direct identification of clinically relevant neoepitopes presented on native human melanoma tissue by mass spectrometry. Nat Commun 2016; 7: 13404..
    1. Snyder A, Chan TA.. Immunogenic peptide discovery in cancer genomes. Curr Opin Genet Dev 2015; 30: 7–16.
    1. Zaretsky JM, Garcia-Diaz A, Shin DS. et al. Mutations associated with acquired resistance to PD-1 blockade in melanoma. N Engl J Med 2016; 375(9): 819–829.
    1. Skoulidis F, Goldberg ME, Greenawalt DM. et al. STK11/LKB1 mutations and PD-1 inhibitor resistance in KRAS-mutant lung adenocarcinoma. Cancer Discov 2018; 8(7): 822–835.
    1. Alexandrov LB, Nik-Zainal S, Wedge DC. et al. Signatures of mutational processes in human cancer. Nature 2013; 500(7463): 415–421.
    1. Jamal-Hanjani M, Wilson GA, McGranahan N. et al. Tracking the evolution of non-small-cell lung cancer. N Engl J Med 2017; 376(22): 2109–2121.
    1. McGranahan N, Favero F, de Bruin EC. et al. Clonal status of actionable driver events and the timing of mutational processes in cancer evolution. Sci Transl Med 2015; 7: 283ra254.
    1. McGranahan N, Furness AJ, Rosenthal R. et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 2016; 351(6280): 1463–1469.
    1. Murugaesu N, Wilson GA, Birkbak NJ. et al. Tracking the genomic evolution of esophageal adenocarcinoma through neoadjuvant chemotherapy. Cancer Discov 2015; 5(8): 821–831.
    1. Morris LG, Riaz N, Desrichard A. et al. Pan-cancer analysis of intratumor heterogeneity as a prognostic determinant of survival. Oncotarget 2016; 7: 10051–10063.
    1. Peggs KS, Segal NH, Allison JP.. Targeting immunosupportive cancer therapies: accentuate the positive, eliminate the negative. Cancer Cell 2007; 12(3): 192–199.
    1. Segal NH, Parsons DW, Peggs KS. et al. Epitope landscape in breast and colorectal cancer. Cancer Res 2008; 68(3): 889–892.
    1. Van Allen EM, Miao D, Schilling B. et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science 2015; 350(6257): 207–211.
    1. Hellmann MD, Nathanson T, Rizvi H. et al. Genomic features of response to combination immunotherapy in patients with advanced non-small-cell lung cancer. Cancer Cell 2018; 33(5): 843–852.
    1. Antonia SC, Callahan MK, Awad MM. et al. Impact of tumor mutation burden on the efficacy of nivolumab or nivolumab+ipilimumab in small cell lung cancer: an exploratory analysis of CheckMate 032. In World Conference on Lung Cancer, 2017; Abstract OA 07.03a.
    1. Riaz N, Havel JJ, Makarov V. et al. Tumor and microenvironment evolution during immunotherapy with nivolumab. Cell 2017; 171(4): 934–949.e915.
    1. Weber J, Horak C, Hodi FS. et al. Baseline tumor T cell receptor (TcR) sequencing analysis and neo antigen load is associated with benefit in melanoma patients receiving sequential nivolumab and ipilimumab. Ann Oncol 2016; 27 (Suppl 6). doi: 10.1093/annonc/mdw378.01.
    1. Li MM, Datto M, Duncavage EJ. et al. Standards and guidelines for the interpretation and reporting of sequence variants in cancer: a joint consensus recommendation of the association for molecular pathology, American Society of Clinical Oncology, and College of American Pathologists. J Mol Diagn 2017; 19(1): 4–23.
    1. McKenna A, Hanna M, Banks E. et al. The genome analysis Toolkit: a MapReduce framework for analyzing next-generation DNA sequencing data. Genome Res 2010; 20(9): 1297–1303.
    1. Rizvi H, Sanchez-Vega F, La K. et al. Molecular determinants of response to anti-programmed cell death (PD)-1 and anti-programmed death-ligand 1 (PD-L1) blockade in patients with non-small-cell lung cancer profiled with targeted next-generation sequencing. JCO 2018; 36(7): 633–641.
    1. Garofalo A, Sholl L, Reardon B. et al. The impact of tumor profiling approaches and genomic data strategies for cancer precision medicine. Genome Med 2016; 8: 79.
    1. Kowanetz M, Zou W, Shames DS. et al. Tumor mutation load assessed by FoundationOne (FM1) is associated with improved efficacy of atezolizumab (atezo) in patients with advanced NSCLC. Ann Oncol 2016; 27 (Suppl 6). doi: 10.1093/annonc/mdw363.25.
    1. Ramalingam S, Hellmann MD, Awad MM. et al. Tumor mutational burden (TMB) as a biomarker for clinical benefit from dual immune checkpoint blockade with nivolumab+ipilimumab in first-line non-small cell lung cancer: identification of TMB cutoff from Checkmate 568. In AACR Annual Meeting 2018; Abstract #11317.
    1. Balar AV, Galsky MD, Rosenberg JE. et al. Atezolizumab as first-line treatment in cisplatin-ineligible patients with locally advanced and metastatic urothelial carcinoma: a single-arm, multicentre, phase 2 trial. Lancet 2017; 389(10064): 67–76.
    1. Powles T, Loriot Y, Ravaud A. et al. Atezolizumab vs chemotherapy in platinum-treated locally advanced or metastatic urothelial carcinoma: immune biomarkers, tumor mutational burden and clinical outcomes from the phase III IMvigor211 Study. In 2018 Genitourinary Cancer Symposium.
    1. Buchhalter I, Rempel E, Endris V. et al. Size matters: dissecting key parameters for panel-based tumor mutational burden (TMB) analysis. Int J Cancer 2018. Sep 21 [Epub ahead of print], doi: 10.1002/ijc.31878.
    1. Garon EB, Rizvi NA, Hui R. et al. Pembrolizumab for the treatment of non-small-cell lung cancer. N Engl J Med 2015; 372(21): 2018–2028.
    1. McLaughlin J, Han G, Schalper KA. et al. Quantitative assessment of the heterogeneity of PD-L1 expression in non-small-cell lung cancer. JAMA Oncol 2016; 2(1): 46–54.
    1. Hellmann MD, Ciuleanu TE, Pluzanski A. et al. Nivolumab plus ipilimumab in lung cancer with a high tumor mutational burden. N Engl J Med 2018; 378(22): 2093–2104.
    1. Galsky M, Saci A, Szabo P. et al. Impact of tumor mutation burden on nivolumab efficacy in secondline urothelial carcinoma patients: exploratory analysis of the phase ii checkmate 275 study. Ann Oncol 2017; 28: ESMO Annual Meeting Abstract.
    1. Goodman AM, Kato S, Bazhenova L. et al. Tumor mutational burden as an independent predictor of response to immunotherapy in diverse cancers. Mol Cancer Ther 2017; 16(11): 2598–2608.
    1. Kowanetz M, Zou W, Shames D. et al. Tumor mutation burden (TMB) is associated with improved efficacy of atezolizumab in 1L and 2L+ NSCLC patients. J Thoracic Oncol 2017; 12(1): S321–S322.
    1. Cristescu R, Mogg R, Ayers M. et al. Mutational load (ML) and T-cell-inflamed microenvironment as predictors of response to pembrolizumab. J Clin Oncol 2017; 35, Abstract 1.
    1. Peters S, Gettinger S, Johnson ML. et al. Phase II trial of atezolizumab as first-line or subsequent therapy for patients with programmed death-ligand 1-selected advanced non-small-cell lung cancer (BIRCH). J Clin Oncol 2017; 35(24): 2781.
    1. Seiwert T, Haddad R, Bauml J. Biomarkers predictive of response to pembrolizumab in head and neck cancer (HNSCC). In AACR Annual Meeting Oral Presentation 2018; Minisymposium: Late-Breaking Research.
    1. Hellmann MD, Ciuleanu TE, Pluzanski A. et al. Nivolumab plus ipilimumab in lung cancer with a high tumor mutational burden. N Engl J Med 2018; 378(22); 2093–2104.
    1. Arce Vargas F, Furness AJS, Litchfield K. et al. Fc effector function contributes to the activity of human anti-CTLA-4 antibodies. Cancer Cell 2018; 33(4): 649–663.e644.
    1. Lauss M, Donia M, Harbst K. et al. Mutational and putative neoantigen load predict clinical benefit of adoptive T cell therapy in melanoma. Nat Commun 2017; 8(1): 1738.
    1. Topalian SL, Hodi FS, Brahmer JR. et al. Safety, activity, and immune correlates of anti-PD-1 antibody in cancer. N Engl J Med 2012; 366(26): 2443–2454.
    1. Brahmer JR, Drake CG, Wollner I. et al. Phase I study of single-agent anti-programmed death-1 (MDX-1106) in refractory solid tumors: safety, clinical activity, pharmacodynamics, and immunologic correlates. JCO 2010; 28(19): 3167–3175.
    1. Le DT, Uram JN, Wang H. et al. PD-1 blockade in tumors with mismatch-repair deficiency. N Engl J Med 2015; 372(26): 2509–2520.
    1. Le DT, Durham JN, Smith KN. et al. Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade. Science 2017; 357(6349): 409–413.
    1. Middha S, Zhang L, Nafa K. et al. Reliable Pan-cancer microsatellite instability assessment by using targeted next-generation sequencing data. JCO Precis Oncol 2017; 2017(1): 1.
    1. Lemery S, Keegan P, Pazdur R.. First FDA approval agnostic of cancer site—when a biomarker defines the indication. N Engl J Med 2017; 377(15): 1409–1412.
    1. Goh G, Walradt T, Markarov V. et al. Mutational landscape of MCPyV-positive and MCPyV-negative Merkel cell carcinomas with implications for immunotherapy. Oncotarget 2016; 7: 3403–3415.
    1. Yarchoan M, Hopkins A, Jaffee EM.. Tumor mutational burden and response rate to PD-1 inhibition. N Engl J Med 2017; 377(25): 2500–2501.
    1. Hammers HJ, Plimack ER, Infante JR. et al. Safety and Efficacy of nivolumab in combination with ipilimumab in metastatic renal cell carcinoma: the CheckMate 016 Study. J Clin Oncol 2017; 35(34): 3851–3858.
    1. Gunjur A. Nivolumab plus ipilimumab in advanced renal-cell carcinoma. Lancet Oncol 2018; 19(5): e232.
    1. Turajlic S, Litchfield K, Xu H. et al. Insertion-and-deletion-derived tumour-specific neoantigens and the immunogenic phenotype: a pan-cancer analysis. Lancet Oncol 2017; 18(8): 1009–1021.
    1. Riaz N, Havel JJ, Kendall SM. et al. Recurrent SERPINB3 and SERPINB4 mutations in patients who respond to anti-CTLA4 immunotherapy. Nat Genet 2016; 48(11): 1327–1329.
    1. Forde PM, Chaft JE, Smith KN. et al. Neoadjuvant PD-1 blockade in resectable lung cancer. N Engl J Med 2018; 378(21): 1976–1986.
    1. Mariathasan S, Turley SJ, Nickles D. et al. attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells. Nature 2018; 554(7693): 544–548. TGFbeta
    1. Banerjee T, Duhadaway JB, Gaspari P. et al. A key in vivo antitumor mechanism of action of natural product-based Brassinins is inhibition of indoleamine 2,3-dioxygenase. Oncogene 2008; 27(20): 2851–2857.
    1. Shariat SF, Kattan MW, Vickers AJ. et al. Critical review of prostate cancer predictive tools. Future Oncol 2009; 5(10): 1555–1584.
    1. Oakman C, Santarpia L, Di Leo A.. Breast cancer assessment tools and optimizing adjuvant therapy. Nat Rev Clin Oncol 2010; 7(12): 725–732.
    1. Olivotto IA, Bajdik CD, Ravdin PM. et al. Population-based validation of the prognostic model ADJUVANT! for early breast cancer. J Clin Oncol 2005; 23(12): 2716–2725.
    1. Long GV, Dummer R, Hamid O. et al. Epacadostat (E) plus pembrolizumab (P) versus pembrolizumab alone in patients (pts) with unresectable or metastatic melanoma: results of the phase 3 ECHO-301/KEYNOTE-252 study. JCO 2018; 36(Suppl 15): 108; Abstr 2018.
    1. Chowell D, Morris LGT, Grigg CM. et al. Patient HLA class I genotype influences cancer response to checkpoint blockade immunotherapy. Science 2018; 359(6375): 582–587.

Source: PubMed

Sponsors en medewerkers

Medische omstandigheden

Geneesmiddelinterventies

3
Abonneren