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 Journal Article


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.
Article Title: 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
Abstract: 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. © 2018 by American Society of Clinical Oncology.
Journal Title: Journal of Clinical Oncology
Volume: 36
Issue: 7
ISSN: 0732-183X
Publisher: American Society of Clinical Oncology  
Date Published: 2018-03-01
Start Page: 633
End Page: 641
Language: English
DOI: 10.1200/jco.2017.75.3384
PROVIDER: scopus
PUBMED: 29337640
PMCID: PMC6075848
DOI/URL:
Notes: Article -- Export Date: 2 April 2018 -- Source: Scopus
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MSK Authors
  1. Natasha Rekhtman
    391 Rekhtman
  2. Jedd D Wolchok
    898 Wolchok
  3. Taha Merghoub
    358 Merghoub
  4. David Solit
    729 Solit
  5. Ronglai Shen
    192 Shen
  6. Marc Ladanyi
    1277 Ladanyi
  7. Jamie Erin Chaft
    256 Chaft
  8. Gregory J Riely
    571 Riely
  9. Ahmet Zehir
    336 Zehir
  10. Nicholas D Socci
    241 Socci
  11. Michael Forman Berger
    701 Berger
  12. Maria Eugenia Arcila
    618 Arcila
  13. Mark Kris
    847 Kris
  14. Matthew David Hellmann
    405 Hellmann
  15. Barry Stephen Taylor
    236 Taylor
  16. Nikolaus D Schultz
    429 Schultz
  17. Travis Jason Hollmann
    119 Hollmann
  18. Charles Rudin
    432 Rudin
  19. Karl Philip Jonsson
    50 Jonsson
  20. Ai   Ni
    99 Ni
  21. Niamh   Long
    17 Long
  22. Kathryn Cecilia Arbour
    74 Arbour
  23. Konnor C La
    9 La
  24. Hira Abbas Rizvi
    121 Rizvi
  25. Jennifer Lynn Sauter
    105 Sauter
  26. Walid Khaled Chatila
    83 Chatila