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29 Lung-MAP composite signature for immune checkpoint inhibitor (ICI) efficacy in advanced squamous cell lung cancer (SCC)
  1. David Gandara1,
  2. Xing Hua2,
  3. Khaled Tolba3,
  4. David Fabrizio3,
  5. Lee Albacker3,
  6. Ryan Brennick3,
  7. Meagan Montesion3,
  8. Geoff Oxnard3,
  9. Stacey Adam4,
  10. Fred Hirsch5,
  11. Karen Kelly6,
  12. Roy Herbst7,
  13. Michael LeBlanc8,
  14. Mary Redman8,
  15. Michael Wu8 and
  16. David Kozono9
  1. 1University of California Davis Cancer Center, Sacramento, CA, USA
  2. 2Fred Hutchinson Org, Seattle, WA, USA
  3. 3Foundation Medicine, Cambridge, MA, USA
  4. 4Foundation for the NIH, North Bethesda, MD, USA
  5. 5Mount Sinai Health System, New York, NY, USA
  6. 6International Association for the Study, Denver, CO, USA
  7. 7Yale School of Medicine, New Haven, CT, USA
  8. 8Fred Hutchinson Cancer Center, Seattle, WA, USA
  9. 9Brigham and Women’s Hospital Harvard Med, Boston, MA, USA


Background Predictive biomarkers for ICI regimens in NSCLC, namely PD-L1 and tumor mutational burden (TMB), remain suboptimal, leaving oncologists with limited decision-making tools. We sought to develop a more comprehensive solution, integrating genomic alterations detected by comprehensive genomic profiling (CGP), to enrich for association with progression-free survival (PFS) and overall survival (OS).

Methods Lung Master Protocol (Lung-MAP) is an NCI-sponsored public-private partnership evaluating new therapies for previously-treated advanced stage NSCLC. In this analysis, 320 SCC patients from sub-studies S1400A (n=68; durvalumab) and S1400I (n=252; nivolumab ± ipilimumab) had tissue CGP data by Foundation Medicine. 204 patients from S1400A (n=43; SP263) and S1400I (n=161; 28–8 pharmDX) had PD-L1 IHC. We evaluated TMB (0–9, 10–20, >20 mut/Mb), PD-L1 IHC, HLA loss of heterozygosity (LOH) of ≥ 1 gene (evaluable for n=206), mutations in KEAP1/NFE2L2, DNA damage response genes,ARID1A, and loss of CDKN2A as potential ICI biomarkers. Wilcoxon and Fisher’s exact tests assessed association between continuous TMB/PDL1 IHC (<1%, 1–49%, ≥50%) and each binary biomarker, and between pairs of binary markers. Cox proportional hazards model evaluated the association between each biomarker and OS/PFS, adjusting for age, sex, smoking status, and stage. Based on significance (at the nominal 0.1 level without correction for multiplicity) from univariate analysis, multiple combination signatures were analyzed using a predetermined scoring system. Biomarkers in the most significant combination signature was further examined by adjusting for TMB and PD-L1, to demonstrate if they provided additional value.

Results Despite associations between TMB and ARID1A mutations (P = 0.009), PD-L1and KEAP1/NFE2L2 mutations (P = 0.007) and ARID1A mutations and KEAP1/NFE2L2 mutations (OR = 2.89; 95% CI, 1.43 – 5.91, P = 0.0016), the magnitude of correlation was modest, thus representing complementary predictors. Higher TMB (>20 vs. 10–20 vs. 0–9) was the most significant positive predictor of OS (HR=0.79; 95% CI, 0.65–0.95, p=0.01). A composite combinatorial signature (ICIsig) inclusive of TMB, PD-L1, HLA LOH, ARID1A, and KEAP1/NFE2L2 mutations was associated with better OS (HR=0.76; 95% CI, 0.63–0.92, p=0.005) and PFS (HR=0.84; 95% CI, 0.70–0.99, p=0.048). Landmark 3-year OS rates were 29% vs. 6% in ICIsig high vs. low. ICIsig high represented 39% of the evaluable population.

Conclusions We show that a composite ICIsig extending beyond TMB and PD-L1 captures NSCLC patients benefiting from ICI therapy more effectively than single biomarkers. ICIsig could inform treatment selection in today’s rapidly expanding therapeutic landscape. Validation from a large randomized Phase III trial is ongoing.

Acknowledgements We would like to acknowledge funding from: NIH/NCI grants U10CA180888, U10CA180819, U10CA180820, U10CA180821, U10CA180868; and by AstraZeneca and Bristol-Myers Squibb Company, through the Foundation for the National Institutes of Health, in partnership with Friends of Cancer Research.

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