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
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Purpose Treatment of advanced non-small-cell lung cancer with immune checkpoint inhibitors (ICIs) is characterized by durable responses and improved survival in a subset of patients. Clinically available tools to optimize use of ICIs and understand the molecular determinants of response are needed. Targeted next-generation sequencing (NGS) is increasingly routine, but its role in identifying predictors of response to ICIs is not known. Methods Detailed clinical annotation and response data were collected for patients with advanced non-small-cell lung cancer treated with anti-programmed death-1 or anti-programmed death-ligand 1 [anti-programmed cell death (PD)-1] therapy and profiled by targeted NGS (MSK-IMPACT; n = 240). Efficacy was assessed by Response Evaluation Criteria in Solid Tumors (RECIST) version 1.1, and durable clinical benefit (DCB) was defined as partial response/stable disease that lasted > 6 months. Tumor mutation burden (TMB), fraction of copy number-altered genome, and gene alterations were compared among patients with DCB and no durable benefit (NDB). Whole-exome sequencing (WES) was performed for 49 patients to compare quantification of TMB by targeted NGS versus WES. Results Estimates of TMB by targeted NGS correlated well with WES (ρ = 0.86; P < .001). TMB was greater in patients with DCB than with NDB ( P = .006). DCB was more common, and progression-free survival was longer in patients at increasing thresholds above versus below the 50th percentile of TMB (38.6% v 25.1%; P < .001; hazard ratio, 1.38; P = .024). The fraction of copy number-altered genome was highest in those with NDB. Variants in EGFR and STK11 associated with a lack of benefit. TMB and PD-L1 expression were independent variables, and a composite of TMB plus PD-L1 further enriched for benefit to ICIs. Conclusion Targeted NGS accurately estimates TMB and elevated TMB further improved likelihood of benefit to ICIs. TMB did not correlate with PD-L1 expression; both variables had similar predictive capacity. The incorporation of both TMB and PD-L1 expression into multivariable predictive models should result in greater predictive power.
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Limited biomarkers such as PD-L1 expression and tumor mutation load are clinically used to predict immunotherapy benefit.
“Currently, limited biomarkers, such as PD-L1 expression (88) and tumor mutation load (TMB) (89–91), are clinically used to predict the immunotherapy benefit.”
From New Horizons in KRAS-Mutant Lung Cancer: Dawn After Darkness (2019) · cites this paper as [90]
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- Authors
- Rizvi, H., Sanchez-Vega, F., La, K., Chatila, W., Jonsson, P., Halpenny, D., Plodkowski, A., Long, N., Sauter, J. L., Rekhtman, N., Hollmann, T., Schalper, K. A., Gainor, J. F., Shen, R., Ni, A., Arbour, K. C., Merghoub, T., Wolchok, J., Snyder, A., Chaft, J. E., Kris, M. G., Rudin, C. M., Socci, N. D., Berger, M. F., Taylor, B. S., Zehir, A., Solit, D. B., Arcila, M. E., Ladanyi, M., Riely, G. J., Schultz, N., & Hellmann, M. D.
- Affiliations
- Hira Rizvi, Francisco Sanchez-Vega, Konnor La, Walid Chatila, Philip Jonsson, Darragh Halpenny, Andrew Plodkowski, Niamh Long, Jennifer L. Sauter, Natasha Rekhtman, Travis Hollmann, Ronglai Shen, Ai Ni, Kathryn C. Arbour, Taha Merghoub, Jedd Wolchok, Jamie E. Chaft, Mark G. Kris, Charles M. Rudin, Nicholas D. Socci, Michael F. Berger, Barry S. Taylor, Ahmet Zehir, David B. Solit, Maria E. Arcila, Marc Ladanyi, Gregory J. Riely, Nikolaus Schultz, and Matthew D. Hellmann, Memorial Sloan Kettering Cancer...
- ORCID
- Rizvi, Hira
- Chatila, Walid
- Jonsson, Philip
- Plodkowski, Andrew
- Sauter, Jennifer L.
- Rekhtman, Natasha
- Hollmann, Travis
- Schalper, Kurt A.
- Gainor, Justin F.
- Shen, Ronglai
- Ni, Ai
- Arbour, Kathryn C.
- Merghoub, Taha
- Wolchok, Jedd
- Snyder, Alexandra
- Chaft, Jamie E.
- Kris, Mark G.
- Rudin, Charles M.
- Socci, Nicholas D.
- Berger, Michael F.
- Taylor, Barry S.
- Zehir, Ahmet
- Solit, David B.
- Arcila, Maria E.
- Ladanyi, Marc
- Riely, Gregory J.
- Schultz, Nikolaus
- Hellmann, Matthew D.
- Venue
- Journal of Clinical Oncology
- Published
- 2018-03-01
- Volume
- 36
- Issue
- 7
- Pages
- 633-641
- ISSN
- 0732-183X (ISSN-L)
- 1527-7755
- PMC
- PMC6075848
- OpenAlex
- W2783897381
- Cited by
- 1,367
- References
- 38
- Citations by year
- 2026: 42 · 2025: 77 · 2024: 130 · 2023: 171 · 2022: 189 · 2021: 239 · 2020: 248 · 2019: 174 · 2018: 95 · 2017: 2
- FWCI
- 71.70
- Type
- journal article
- Language
- en
- Update notices
- correction (2018-06-01)
- Open access
- green
- europepmc.org
- Locations
- Journal of Clinical Oncology (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Funders
- National Cancer Institute (P01CA129243, P30CA008748)
- Topics
- Health Sciences › Medicine › Oncology › Cancer Immunotherapy and Biomarkers
- Health Sciences › Medicine › Pulmonary and Respiratory Medicine › Lung Cancer Treatments and Mutations
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Cancer Research › Cancer Genomics and Diagnostics
- Keywords
- non-small cell lung cancer, immune checkpoint inhibitors, anti-PD-1 therapy, PD-L1 blockade, tumor mutational burden, PD-L1 expression, predictive biomarkers, targeted next-generation sequencing, copy number alterations, EGFR, STK11, durable clinical benefit, progression-free survival, MSK-IMPACT, treatment response
- MeSH terms
- Exome Sequencing, Carcinoma, Non-Small-Cell Lung, Humans, Lung Neoplasms, Mutation, Tumor Burden, High-Throughput Nucleotide Sequencing, B7-H1 Antigen, Programmed Cell Death 1 Receptor
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