Mechanisms of resistance and predictive biomarkers of response to targeted therapies and immunotherapies in metastatic melanoma.
Antineoplastic Agents, Immunological
/ pharmacology
Biomarkers, Tumor
/ metabolism
Drug Resistance, Neoplasm
Humans
Immunotherapy
/ methods
Melanoma
/ drug therapy
Mitogen-Activated Protein Kinases
/ antagonists & inhibitors
Molecular Targeted Therapy
Neoplasm Metastasis
Predictive Value of Tests
Protein Kinase Inhibitors
/ pharmacology
Journal
Current opinion in oncology
ISSN: 1531-703X
Titre abrégé: Curr Opin Oncol
Pays: United States
ID NLM: 9007265
Informations de publication
Date de publication:
03 2020
03 2020
Historique:
pubmed:
14
12
2019
medline:
20
9
2020
entrez:
14
12
2019
Statut:
ppublish
Résumé
Thanks to mitogen-activated protein kinase inhibitors (MAPKi) and immune checkpoint inhibitors (ICI), major progress has been made in the field of melanoma treatment. However, long-term success is still scarce because of the development of resistance. Understanding these mechanisms of resistance and identifying predictive genomic biomarkers are now key points in the therapeutic management of melanoma patients. Multiple and complex mechanisms of resistance to MAPKi or ICI have been uncovered in the past few years. The lack of response can be driven by mutations and nonmutational events in tumor cells, as well as by changes in the tumor microenvironment. Melanoma cells are also capable of rapidly switching their molecular and cellular phenotype, leading to an initial drug-tolerant favorizing melanoma resistance. Tumor molecular profiling and circulating tumor cell analyses are of high interest as predictive biomarkers as well as studying immunogenic changes and microbiome in ICI-treated patients. Resistance to MAPKi and ICI is a key point in therapeutic management of metastatic melanoma patients. Validated biomarkers predicting response to therapy are urgently needed to move toward personalized medicine. Combinatory treatments guided by the understanding of resistance mechanisms will be of major importance in the future of melanoma therapy.
Identifiants
pubmed: 31833956
doi: 10.1097/CCO.0000000000000603
pii: 00001622-202003000-00004
doi:
Substances chimiques
Antineoplastic Agents, Immunological
0
Biomarkers, Tumor
0
Protein Kinase Inhibitors
0
Mitogen-Activated Protein Kinases
EC 2.7.11.24
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
91-97Références
Salgia R, Kulkarni P. The genetic/nongenetic duality of drug ‘resistance’ in cancer. Trends Cancer 2018; 4:110–118.
Moriceau G, Hugo W, Hong A, et al. Tunable-combinatorial mechanisms of acquired resistance limit the efficacy of BRAF/MEK cotargeting but result in melanoma drug addiction. Cancer Cell 2015; 27:240–256.
Dietrich P, Kuphal S, Spruss T, et al. Wild-type KRAS is a novel therapeutic target for melanoma contributing to primary and acquired resistance to BRAF inhibition. Oncogene 2018; 37:897–911.
Stark MS, Bonazzi VF, Boyle GM, et al. miR-514a regulates the tumour suppressor NF1 and modulates BRAFi sensitivity in melanoma. Oncotarget 2015; 6:17753–17763.
Doudican NA, Orlow SJ. Inhibition of the CRAF/prohibitin interaction reverses CRAF-dependent resistance to vemurafenib. Oncogene 2017; 36:423–428.
Johannessen CM, Boehm JS, Kim SY, et al. COT drives resistance to RAF inhibition through MAP kinase pathway reactivation. Nature 2010; 468:968–972.
Gruosso T, Garnier C, Abelanet S, et al. MAP3K8/TPL-2/COT is a potential predictive marker for MEK inhibitor treatment in high-grade serous ovarian carcinomas. Nat Commun 2015; 6:8583.
Wagle N, Van Allen EM, Treacy DJ, et al. MAP kinase pathway alterations in BRAF-mutant melanoma patients with acquired resistance to combined RAF/MEK inhibition. Cancer Discov 2014; 4:61–68.
Long GV, Stroyakovskiy D, Gogas H, et al. Combined BRAF and MEK inhibition versus BRAF inhibition alone in melanoma. N Engl J Med 2014; 371:1877–1888.
Zuo Q, Liu J, Huang L, et al. AXL/AKT axis mediated-resistance to BRAF inhibitor depends on PTEN status in melanoma. Oncogene 2018; 37:3275–3289.
Paraiso KHT, Xiang Y, Rebecca VW, et al. PTEN loss confers BRAF inhibitor resistance to melanoma cells through the suppression of BIM expression. Cancer Res 2011; 71:2750–2760.
Villanueva J, Vultur A, Lee JT, et al. Acquired resistance to BRAF inhibitors mediated by a RAF kinase switch in melanoma can be overcome by cotargeting MEK and IGF-1R/PI3K. Cancer Cell 2010; 18:683–695.
Boussemart L, Malka-Mahieu H, Girault I, et al. eIF4F is a nexus of resistance to anti-BRAF and anti-MEK cancer therapies. Nature 2014; 513:105–109.
Gajos-Michniewicz A, Czyz M. Role of miRNAs in melanoma metastasis. Cancers 2019; 11:326.
Díaz-Martínez M, Benito-Jardón L, Alonso L, et al. miR-204-5p and miR-211-5p contribute to BRAF inhibitor resistance in melanoma. Cancer Res 2018; 78:1017–1030.
Fattore L, Ruggiero CF, Pisanu ME, et al. Reprogramming miRNAs global expression orchestrates development of drug resistance in BRAF mutated melanoma. Cell Death Differ 2019; 26:1267–1282.
Fattore L, Costantini S, Malpicci D, et al. MicroRNAs in melanoma development and resistance to target therapy. Oncotarget 2017; 8:22262–22278.
Liu X, Wu J, Qin H, Xu J. The role of autophagy in the resistance to BRAF inhibition in BRAF-mutated melanoma. Targ Oncol 2018; 13:437–446.
Ma XH, Piao SF, Dey S, et al. Targeting ER stress–induced autophagy overcomes BRAF inhibitor resistance in melanoma. J Clin Invest 2014; 124:1406–1417.
Cerezo M, Rocchi S. New anticancer molecules targeting HSPA5/BIP to induce endoplasmic reticulum stress, autophagy and apoptosis. Autophagy 2017; 13:216–217.
Wang L, Leite de Oliveira R, Huijberts S, et al. An acquired vulnerability of drug-resistant melanoma with therapeutic potential. Cell 2018; 173:1413–1425.e14.
Ahmed F, Haass NK. Microenvironment-driven dynamic heterogeneity and phenotypic plasticity as a mechanism of melanoma therapy resistance. Front Oncol 2018; 8:173.
Gray-Schopfer VC, Karasarides M, Hayward R, Marais R. Tumor necrosis factor-α blocks apoptosis in melanoma cells when BRAF signaling is inhibited. Cancer Res 2007; 67:122–129.
Straussman R, Morikawa T, Shee K, et al. Tumour micro-environment elicits innate resistance to RAF inhibitors through HGF secretion. Nature 2012; 487:500–504.
Kaur A, Webster MR, Marchbank K, et al. sFRP2 in the aged microenvironment drives melanoma metastasis and therapy resistance. Nature 2016; 532:250–254.
Hirata E, Girotti MR, Viros A, et al. Intravital imaging reveals how BRAF inhibition generates drug-tolerant microenvironments with high integrin β1/FAK signaling. Cancer Cell 2015; 27:574–588.
Boshuizen J, Koopman LA, Krijgsman O, et al. Cooperative targeting of melanoma heterogeneity with an AXL antibody-drug conjugate and BRAF/MEK inhibitors. Nat Med 2018; 24:203–212.
Miskolczi Z, Smith MP, Rowling EJ, et al. Collagen abundance controls melanoma phenotypes through lineage-specific microenvironment sensing. Oncogene 2018; 37:3166–3182.
Fisher ML, Grun D, Adhikary G, et al. Inhibition of YAP function overcomes BRAF inhibitor resistance in melanoma cancer stem cells. Oncotarget 2017; 8:110257–110272.
Smith MP, Rowling EJ, Miskolczi Z, et al. Targeting endothelin receptor signalling overcomes heterogeneity driven therapy failure. EMBO Mol Med 2017; 9:1011–1029.
Tsoi J, Robert L, Paraiso K, et al. Multistage differentiation defines melanoma subtypes with differential vulnerability to drug-induced iron-dependent oxidative stress. Cancer Cell 2018; 33:890–904.e5.
Rambow F, Rogiers A, Marin-Bejar O, et al. Toward minimal residual disease-directed therapy in melanoma. Cell 2018; 174:843–855.e19.
Chapman PB, Hauschild A, Robert C, et al. Improved survival with vemurafenib in melanoma with BRAF V600E mutation. N Engl J Med 2011; 364:2507–2516.
Hauschild A, Grob JJ, Demidov LV, et al. Dabrafenib in BRAF-mutated metastatic melanoma: a multicentre, open-label, phase 3 randomised controlled trial. Lancet 2012; 380:358–365.
Long GV, Stroyakovskiy D, Gogas H, et al. Dabrafenib and trametinib versus dabrafenib and placebo for Val600 BRAF-mutant melanoma: a multicentre, double-blind, phase 3 randomised controlled trial. Lancet 2015; 386:444–451.
Trunzer K, Pavlick AC, Schuchter L, et al. Pharmacodynamic effects and mechanisms of resistance to vemurafenib in patients with metastatic melanoma. J Clin Oncol 2013; 31:1767–1774.
Wagle MC, Kirouac D, Klijn C, et al. A transcriptional MAPK Pathway Activity Score (MPAS) is a clinically relevant biomarker in multiple cancer types. NPJ Precis Oncol 2018; 2:7.
Louveau B, Delyon J, De Moura CR, et al. A targeted genomic alteration analysis predicts survival of melanoma patients under BRAF inhibitors. Oncotarget 2019; 10:1669–1687.
Wongchenko MJ, McArthur GA, Dréno B, et al. Gene expression profiling in BRAF-mutated melanoma reveals patient subgroups with poor outcomes to vemurafenib that may be overcome by cobimetinib plus vemurafenib. Clin Cancer Res 2017; 23:5238–5245.
Yan Y, Wongchenko MJ, Robert C, et al. Genomic features of exceptional response in vemurafenib ± cobimetinib-treated patients with BRAFV600-mutated metastatic melanoma. Clin Cancer Res 2019; 25:3239–3246.
Louveau B, Jouenne F, Reger de Moura C, et al. Baseline genomic features in BRAFV600-mutated metastatic melanoma patients treated with BRAF inhibitor + MEK inhibitor in routine care. Cancers 2019; 11:1203.
Santiago-Walker A, Gagnon R, Mazumdar J, et al. Correlation of BRAF mutation status in circulating-free DNA and tumor and association with clinical outcome across four BRAFi and MEKi clinical trials. Clin Cancer Res 2016; 22:567–574.
Louveau B, Tost J, Mauger F, et al. Clinical value of early detection of circulating tumour DNA-BRAF(V600mut) in patients with metastatic melanoma treated with a BRAF inhibitor. ESMO Open 2017; 2:e000173.
Sanmamed MF, Fernández-Landázuri S, Rodríguez C, et al. Quantitative cell-free circulating BRAFV600E mutation analysis by use of droplet digital PCR in the follow-up of patients with melanoma being treated with BRAF inhibitors. Clin Chem 2015; 61:297–304.
Knol AC, Vallée A, Herbreteau G, et al. Clinical significance of BRAF mutation status in circulating tumor DNA of metastatic melanoma patients at baseline. Exp Dermatol 2016; 25:783–788.
Gray ES, Rizos H, Reid AL, et al. Circulating tumor DNA to monitor treatment response and detect acquired resistance in patients with metastatic melanoma. Oncotarget 2015; 6:42008–42018.
Sharma P, Hu-Lieskovan S, Wargo JA, Ribas A. Primary, adaptive, and acquired resistance to cancer immunotherapy. Cell 2017; 168:707–723.
McGranahan N, Furness AJS, Rosenthal R, et al. Clonal neoantigens elicit T cell immunoreactivity and sensitivity to immune checkpoint blockade. Science 2016; 351:1463–1469.
Sade-Feldman M, Jiao YJ, Chen JH, et al. Resistance to checkpoint blockade therapy through inactivation of antigen presentation. Nat Commun 2017; 8:1136.
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; 375:819–829.
Shukla SA, Rooney MS, Rajasagi M, et al. Comprehensive analysis of cancer-associated somatic mutations in class I HLA genes. Nat Biotechnol 2015; 33:1152–1158.
Giannakis M, Mu XJ, Shukla SA, et al. Genomic correlates of immune-cell infiltrates in colorectal carcinoma. Cell Rep 2016; 15:857–865.
Hugo W, Zaretsky JM, Sun L, et al. Genomic and transcriptomic features of response to anti-PD-1 therapy in metastatic melanoma. Cell 2016; 165:35–44.
Rizvi NA, Hellmann MD, Snyder A, et al. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science 2015; 348:124–128.
Samstein RM, Lee CH, Shoushtari AN, et al. Tumor mutational load predicts survival after immunotherapy across multiple cancer types. Nat Genet 2019; 51:202–206.
Spranger S, Bao R, Gajewski TF. Melanoma-intrinsic β-catenin signalling prevents antitumour immunity. Nature 2015; 523:231–235.
Manguso RT, Pope HW, Zimmer MD, et al. In vivo CRISPR screening identifies Ptpn2 as a cancer immunotherapy target. Nature 2017; 547:413–418.
Thommen DS, Schreiner J, Muller P, et al. Progression of lung cancer is associated with increased dysfunction of T cells defined by coexpression of multiple inhibitory receptors. Cancer Immunol Res 2015; 3:1344–1355.
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. J Clin Oncol 2010; 28:3167–3175.
Daud AI, Wolchok JD, Robert C, et al. Programmed death-ligand 1 expression and response to the anti-programmed death 1 antibody pembrolizumab in melanoma. J Clin Oncol 2016; 34:4102–4109.
Larkin J, Hodi FS, Wolchok JD. Combined nivolumab and ipilimumab or monotherapy in untreated melanoma. N Engl J Med 2015; 373:1270–1271.
Weber JS, D’Angelo SP, Minor D, et al. 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 2015; 16:375–384.
Madore J, Vilain RE, Menzies AM, et al. PD-L1 expression in melanoma shows marked heterogeneity within and between patients: implications for anti-PD-1/PD-L1 clinical trials. Pigment Cell Melanoma Res 2015; 28:245–253.
Yearley JH, Gibson C, Yu N, et al. PD-L2 expression in human tumors: relevance to anti-PD-1 therapy in cancer. Clin Cancer Res 2017; 23:3158–3167.
Shin DS, Zaretsky JM, Escuin-Ordinas H, et al. Primary resistance to PD-1 blockade mediated by JAK1/2 mutations. Cancer Discov 2017; 7:188–201.
Ascierto ML, Makohon-Moore A, Lipson EJ, et al. Transcriptional mechanisms of resistance to anti-PD-1 therapy. Clin Cancer Res 2017; 23:3168–3180.
Huang AC, Postow MA, Orlowski RJ, et al. T-cell invigoration to tumour burden ratio associated with anti-PD-1 response. Nature 2017; 545:60–65.
Sade-Feldman M, Yizhak K, Bjorgaard SL, et al. Defining T cell states associated with response to checkpoint immunotherapy in melanoma. Cell 2018; 175:998–1013.e20.
Van Allen EM, Miao D, Schilling B, et al. Genomic correlates of response to CTLA-4 blockade in metastatic melanoma. Science 2015; 350:207–211.
Snyder A, Makarov V, Merghoub T, et al. Genetic basis for clinical response to CTLA-4 blockade in melanoma. N Engl J Med 2014; 371:2189–2199.
Johnson DB, Frampton GM, Rioth MJ, et al. Targeted next generation sequencing identifies markers of response to PD-1 blockade. Cancer Immunol Res 2016; 4:959–967.
Roh W, Chen PL, Reuben A, et al. Integrated molecular analysis of tumor biopsies on sequential CTLA-4 and PD-1 blockade reveals markers of response and resistance. Sci Transl Med 2017; 9: 379, eaah3560.
Buchhalter I, Rempel E, Endris V, et al. Size matters: dissecting key parameters for panel-based tumor mutational burden analysis: panel-based TMB detection. Int J Cancer 2019; 144:848–858.
Forschner A, Battke F, Hadaschik D, et al. Tumor mutation burden and circulating tumor DNA in combined CTLA-4 and PD-1 antibody therapy in metastatic melanoma – results of a prospective biomarker study. J Immunother Cancer 2019; 7:180.
Pitt JM, Vétizou M, Daillère R, et al. Resistance mechanisms to immune-checkpoint blockade in cancer: tumor-intrinsic and -extrinsic factors. Immunity 2016; 44:1255–1269.
Routy B, Le Chatelier E, Derosa L, et al. Gut microbiome influences efficacy of PD-1-based immunotherapy against epithelial tumors. Science 2018; 359:91–97.
Gopalakrishnan V, Spencer CN, Nezi L, et al. Gut microbiome modulates response to anti-PD-1 immunotherapy in melanoma patients. Science 2018; 359:97–103.
Matson V, Fessler J, Bao R, et al. The commensal microbiome is associated with anti-PD-1 efficacy in metastatic melanoma patients. Science 2018; 359:104–108.
Lee JH, Long GV, Boyd S, et al. Circulating tumour DNA predicts response to anti-PD1 antibodies in metastatic melanoma. Ann Oncol 2017; 28:1130–1136.
Herbreteau G, Vallée A, Knol AC, et al. Quantitative monitoring of circulating tumor DNA predicts response of cutaneous metastatic melanoma to anti-PD1 immunotherapy. Oncotarget 2018; 9:25265–25276.