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Potential Biomarkers of Immunotherapy in NSCLC

BACKGROUND:
J.S. Ross, et al utilized CGP, PD-L1 IHC, and real world data to investigate potential biomarkers for ICPI (immunotherapy) response for advanced NSCLC.

METHODS:
CGP and IHC was performed on 1,619 FFPE NSCLC samples in the FoundationCORE database (FMI). SP142 antibody was used to capture PD-L1 tumor expression (PD-L1 TE). NSCLC patients (n=2139) in the Flatiron Health Analytic Database with CGP results from FoundationOne testing and real world IHC results for PD-L1 TE were analyzed separately (FMI-FIH).

RESULTS:

  • Correlation of PD-L1 IHC TE with TMB (FMI samples) was weak (Spearman’s ρ 0.085, p=6.16e-4).Mean TMB was 10.9 mut/Mb, median was 8.1 mut/Mb and 14.5% had high TMB (≥20 mut/Mb).
  • High TMB but not PD-L1 TE predicted longer mean duration on therapy (FMI-FIH) (p=0.001),
  • STK11 GA correlated with high TMB/low PD-L1 (FMI; p=0.0014) and negatively correlated with treatment outcome on ICPI,
  • BRAF GA, most often short variants (SV) and predominantly in adenocarcinomas, were associated with prolonged time on ICPI treatment regardless of TMB score (FMI-FIH; p=0.0073),
  • MET SV also predicted prolonged time on ICPI, but insufficient events prevented calculation of statistical significance (FMI-FIH). Analysis of the TCGA lung adenocarcinoma dataset revealed MET SV (2.8%) were linked with immune activation gene expression profiles (p<0.05) and STK11 mutations (14.2%) with immune evasion profiles (p<0.05).

CONCLUSION: 
Although TMB powerfully predicts ICPI outcome independent of tumor cell PD-L1 expression, considering GA in STK11, BRAF or MET may further increase the precision and improve outcomes when using genomics with IHC to guide to ICPI selection.

http://sgbcc.poster-submission.com/esmo2017/visitors/eposter/35767

Charmaine Ye
Senior Officer, Medical Affairs
Foundation Medicine
e-mail: charmaine.ye@roche.com