Strategies for Predicting Response to Checkpoint Inhibitors

Overview

Journal Curr Hematol Malig Rep

Publisher Current Science

Specialties Hematology
Oncology

Date 2018 Aug 31

PMID 30159703

Citations 23

Authors

Roberta Zappasodi

Jedd D Wolchok

Taha Merghoub

Affiliations

Soon will be listed here.

Abstract

Purpose Of Review: Despite the clinical successes of immune checkpoint blockade across multiple tumor types, many patients do not respond to these therapies or become resistant after an initial response. This underscores the need to improve our understanding of the molecular determinants of response to guide more personalized and rational utilization of these therapies. Here, we describe available biomarkers of checkpoint blockade activity by classifying them into four major categories: tumor-intrinsic, immune microenvironmental, host-related, and dynamic factors.

Recent Findings: The clinical experience accumulated thus far with checkpoint blockade now offers the opportunity to comprehensively study the molecular and immune features associated with response. This is yielding a growing set of biomarkers whose integration will be key to more accurately predict clinical outcome. We propose a model for systematic assessment of available baseline and dynamic biomarkers in relationship with patients' outcomes. This will improve our understanding of the tumor-immune interactions and dynamics that predict a clinical response and will provide key information to develop more personalized and effective treatment strategies.

Citing Articles

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CEA-CD3 bispecific antibody cibisatamab with or without atezolizumab in patients with CEA-positive solid tumours: results of two multi-institutional Phase 1 trials.

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Inhibition of anti-tumor immunity by melanoma cell-derived Activin-A depends on STING.

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Efficacy of PD-1 checkpoint inhibitor therapy in melanoma and beyond: are peripheral T cell phenotypes the key?.

Flaherty K, Kucykowicz S, Schroth J, Traves W, Mincham K, Finney G Immunother Adv. 2023; 3(1):ltad026.

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Increased tumor glycolysis is associated with decreased immune infiltration across human solid tumors.

Cohen I, Pareja F, Socci N, Shen R, Doane A, Schwartz J Front Immunol. 2022; 13:880959.

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References

Wang W, Yu D, Sarnaik A, Yu B, Hall M, Morelli D . Biomarkers on melanoma patient T cells associated with ipilimumab treatment. J Transl Med. 2012; 10:146. PMC: 3527361. DOI: 10.1186/1479-5876-10-146. View

Mellor J, Brown M, Irving H, Zalcberg J, Dobrovic A . A critical review of the role of Fc gamma receptor polymorphisms in the response to monoclonal antibodies in cancer. J Hematol Oncol. 2013; 6:1. PMC: 3549734. DOI: 10.1186/1756-8722-6-1. View

Marzec M, Zhang Q, Goradia A, Raghunath P, Liu X, Paessler M . Oncogenic kinase NPM/ALK induces through STAT3 expression of immunosuppressive protein CD274 (PD-L1, B7-H1). Proc Natl Acad Sci U S A. 2008; 105(52):20852-7. PMC: 2634900. DOI: 10.1073/pnas.0810958105. View

Dong Z, Zhong W, Zhang X, Su J, Xie Z, Liu S . Potential Predictive Value of and Mutation Status for Response to PD-1 Blockade Immunotherapy in Lung Adenocarcinoma. Clin Cancer Res. 2017; 23(12):3012-3024. DOI: 10.1158/1078-0432.CCR-16-2554. View

Antonia S, Villegas A, Daniel D, Vicente D, Murakami S, Hui R . Durvalumab after Chemoradiotherapy in Stage III Non-Small-Cell Lung Cancer. N Engl J Med. 2017; 377(20):1919-1929. DOI: 10.1056/NEJMoa1709937. View

Snyder A, Makarov V, Merghoub T, Yuan J, Zaretsky J, Desrichard A . Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med. 2014; 371(23):2189-2199. PMC: 4315319. DOI: 10.1056/NEJMoa1406498. View

McGranahan N, Rosenthal R, Hiley C, Rowan A, Watkins T, Wilson G . Allele-Specific HLA Loss and Immune Escape in Lung Cancer Evolution. Cell. 2017; 171(6):1259-1271.e11. PMC: 5720478. DOI: 10.1016/j.cell.2017.10.001. View

Motzer R, Escudier B, Mcdermott D, George S, Hammers H, Srinivas S . Nivolumab versus Everolimus in Advanced Renal-Cell Carcinoma. N Engl J Med. 2015; 373(19):1803-13. PMC: 5719487. DOI: 10.1056/NEJMoa1510665. View

Delyon J, Mateus C, Lefeuvre D, Lanoy E, Zitvogel L, Chaput N . Experience in daily practice with ipilimumab for the treatment of patients with metastatic melanoma: an early increase in lymphocyte and eosinophil counts is associated with improved survival. Ann Oncol. 2013; 24(6):1697-703. DOI: 10.1093/annonc/mdt027. View

10.

Gettinger S, Choi J, Hastings K, Truini A, Datar I, Sowell R . Impaired HLA Class I Antigen Processing and Presentation as a Mechanism of Acquired Resistance to Immune Checkpoint Inhibitors in Lung Cancer. Cancer Discov. 2017; 7(12):1420-1435. PMC: 5718941. DOI: 10.1158/2159-8290.CD-17-0593. View

11.

Riaz N, Havel J, Makarov V, Desrichard A, Urba W, Sims J . Tumor and Microenvironment Evolution during Immunotherapy with Nivolumab. Cell. 2017; 171(4):934-949.e16. PMC: 5685550. DOI: 10.1016/j.cell.2017.09.028. View

12.

Lastwika K, Wilson 3rd W, Li Q, Norris J, Xu H, Ghazarian S . Control of PD-L1 Expression by Oncogenic Activation of the AKT-mTOR Pathway in Non-Small Cell Lung Cancer. Cancer Res. 2015; 76(2):227-38. DOI: 10.1158/0008-5472.CAN-14-3362. View

13.

Rizvi N, Hellmann M, Snyder A, Kvistborg P, Makarov V, Havel J . Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015; 348(6230):124-8. PMC: 4993154. DOI: 10.1126/science.aaa1348. View

14.

Ozcan M, Janikovits J, von Knebel Doeberitz M, Kloor M . Complex pattern of immune evasion in MSI colorectal cancer. Oncoimmunology. 2018; 7(7):e1445453. PMC: 5993484. DOI: 10.1080/2162402X.2018.1445453. View

15.

Van Allen E, Miao D, Schilling B, Shukla S, Blank C, Zimmer L . Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science. 2015; 350(6257):207-211. PMC: 5054517. DOI: 10.1126/science.aad0095. View

16.

Levine A, Oren M . The first 30 years of p53: growing ever more complex. Nat Rev Cancer. 2009; 9(10):749-58. PMC: 2771725. DOI: 10.1038/nrc2723. View

17.

Hirsch F, McElhinny A, Stanforth D, Ranger-Moore J, Jansson M, Kulangara K . PD-L1 Immunohistochemistry Assays for Lung Cancer: Results from Phase 1 of the Blueprint PD-L1 IHC Assay Comparison Project. J Thorac Oncol. 2016; 12(2):208-222. DOI: 10.1016/j.jtho.2016.11.2228. View

18.

Sade-Feldman M, Jiao Y, Chen J, Rooney M, Barzily-Rokni M, Eliane J . Resistance to checkpoint blockade therapy through inactivation of antigen presentation. Nat Commun. 2017; 8(1):1136. PMC: 5656607. DOI: 10.1038/s41467-017-01062-w. View

19.

Pages F, Mlecnik B, Marliot F, Bindea G, Ou F, Bifulco C . International validation of the consensus Immunoscore for the classification of colon cancer: a prognostic and accuracy study. Lancet. 2018; 391(10135):2128-2139. DOI: 10.1016/S0140-6736(18)30789-X. View

20.

Robinson J, Halliwell J, Hayhurst J, Flicek P, Parham P, Marsh S . The IPD and IMGT/HLA database: allele variant databases. Nucleic Acids Res. 2014; 43(Database issue):D423-31. PMC: 4383959. DOI: 10.1093/nar/gku1161. View