Prediction of Immunotherapy Response in Melanoma through Combined Modeling of Neoantigen Burden and Immune-Related Resistance Mechanisms
Autor: | Gabor Bartha, Jason B. Harris, Simo V. Zhang, Sean Michael Boyle, Michael Snyder, Rena McClory, Pamela Milani, Fabio C. P. Navarro, Rachel Marty Pyke, Eric Levy, Richard Chen, Zeid M. Rusan, Rose Santiago, Lee D. McDaniel, Mengyao Tan, Charles Abbott, Sekwon Jang, Dattatreya Mellacheruvu |
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Rok vydání: | 2021 |
Předmět: |
Oncology
Cancer Research medicine.medical_specialty business.industry medicine.medical_treatment Melanoma Models Immunological Immunotherapy Human leukocyte antigen medicine.disease Immune checkpoint Transcriptome Treatment Outcome Immune system Drug Resistance Neoplasm Internal medicine Humans Medicine Biomarker (medicine) business Exome Forecasting |
Zdroj: | Clinical Cancer Research. 27:4265-4276 |
ISSN: | 1557-3265 1078-0432 |
DOI: | 10.1158/1078-0432.ccr-20-4314 |
Popis: | Purpose: While immune checkpoint blockade (ICB) has become a pillar of cancer treatment, biomarkers that consistently predict patient response remain elusive due to the complex mechanisms driving immune response to tumors. We hypothesized that a multi-dimensional approach modeling both tumor and immune-related molecular mechanisms would better predict ICB response than simpler mutation-focused biomarkers, such as tumor mutational burden (TMB). Experimental Design: Tumors from a cohort of patients with late-stage melanoma (n = 51) were profiled using an immune-enhanced exome and transcriptome platform. We demonstrate increasing predictive power with deeper modeling of neoantigens and immune-related resistance mechanisms to ICB. Results: Our neoantigen burden score, which integrates both exome and transcriptome features, more significantly stratified responders and nonresponders (P = 0.016) than TMB alone (P = 0.049). Extension of this model to include immune-related resistance mechanisms affecting the antigen presentation machinery, such as HLA allele-specific LOH, resulted in a composite neoantigen presentation score (NEOPS) that demonstrated further increased association with therapy response (P = 0.002). Conclusions: NEOPS proved the statistically strongest biomarker compared with all single-gene biomarkers, expression signatures, and TMB biomarkers evaluated in this cohort. Subsequent confirmation of these findings in an independent cohort of patients (n = 110) suggests that NEOPS is a robust, novel biomarker of ICB response in melanoma. |
Databáze: | OpenAIRE |
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