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Tumor microenvironment evaluation promotes precise checkpoint immunotherapy of advanced gastric cancer
Dongqiang Zeng1, Jiani Wu1, Huiyan Luo2
1Department of Oncology, Southern Medical University Nanfang Hospital, Guangzhou, Guangdong, China.
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.
Insights
A new TMEscore R package accurately predicts response to immune checkpoint blockade (ICB) in metastatic gastric cancer (mGC). This tool offers a promising biomarker for guiding precision immunotherapy in gastric cancer patients.
Area of Science:
- Oncology
- Immunotherapy
- Bioinformatics
Background:
- Durable efficacy of immune checkpoint blockade (ICB) is limited in metastatic gastric cancer (mGC).
- Biomarkers predicting response to ICB in mGC remain unclear.
- Identifying predictive biomarkers is crucial for advancing mGC treatment.
Purpose of the Study:
- To develop and validate a novel tool, TMEscore, for quantifying the tumor microenvironment (TME).
- To assess the predictive value of TMEscore for ICB response in mGC.
- To explore the underlying mechanisms of TMEscore using multi-omics data.
Main Methods:
- Development of an open-source TMEscore R package.
- Validation in two advanced gastric cancer cohorts (RNAseq, N=45; NanoString, N=48) and a broader advanced cancer cohort (N=534) treated with ICB.
- Multi-omics data analysis from TCGA-STAD and ACRG for mechanistic insights.
Main Results:
- TMEscore demonstrated strong predictive capacity in mGC cohorts treated with pembrolizumab (AUC=0.891).
- TMEscore outperformed established biomarkers including PD-L1 CPS, TMB, MSI, and EBV.
- Validation in a multicenter advanced gastric cancer cohort confirmed TMEscore's predictive value (AUC=0.877).
- Multi-omics analysis revealed TME-related mechanisms involving mutations, metabolism, and epigenetics.
Conclusions:
- TMEscore shows significant promise as a predictive biomarker for ICB in mGC.
- The TMEscore R package facilitates the quantification of the tumor microenvironment.
- Further exploration of TME in multi-omics data can drive precision immunotherapy strategies for gastric cancer.
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