Background: Durable efficacy of immune checkpoint blockade (ICB) occurred in a small number of patients with metastatic gastric cancer (mGC) and the determinant biomarker of response to ICB remains unclear.
Methods: We developed an open-source TMEscore R package, to quantify the tumor microenvironment (TME) to aid in addressing this dilemma. Two advanced gastric cancer cohorts (RNAseq, N=45 and NanoString, N=48) and other advanced cancer (N=534) treated with ICB were leveraged to investigate the predictive value of TMEscore. Simultaneously, multi-omics data from The Cancer Genome Atlas of Stomach Adenocarcinoma (TCGA-STAD) and Asian Cancer Research Group (ACRG) were interrogated for underlying mechanisms.
Results: The predictive capacity of TMEscore was corroborated in patient with mGC cohorts treated with pembrolizumab in a prospective phase 2 clinical trial (NCT02589496, N=45, area under the curve (AUC)=0.891). Notably, TMEscore, which has a larger AUC than programmed death-ligand 1 combined positive score, tumor mutation burden, microsatellite instability, and Epstein-Barr virus, was also validated in the multicenter advanced gastric cancer cohort using NanoString technology (N=48, AUC=0.877). Exploration of the intrinsic mechanisms of TMEscore with TCGA and ACRG multi-omics data identified TME pertinent mechanisms including mutations, metabolism pathways, and epigenetic features.
Conclusions: Current study highlighted the promising predictive value of TMEscore for patients with mGC. Exploration of TME in multi-omics gastric cancer data may provide the impetus for precision immunotherapy.
Keywords: computational biology; gastrointestinal neoplasms; immunotherapy; tumor microenvironment.
© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.