Predictive Biomarkers of Immune-checkpoint Inhibitors Immunotherapies in Hepatocellular Carcinomas and Gastric Cancers

Immune-checkpoint inhibitors (ICIs), including anti-cytotoxic T lymphocyte antigen 4 (CTLA-4), anti-programmed cell death 1 (PD-1) and anti-programmed cell death 1 ligand 1 (PD-L1) antibodies, have revolutionized the landscape of tumor treatment in the past decade. ICIs, especially for PD-1 blockade, have been successfully against an array of distinct metastatic malignancies. ICIs unleash T lymphocyte mediated immune responses by blocking the interaction of T cell inhibitory receptors with their cognate ligands present on tumor cell surface. However, the blocking of interaction augments immune responses that may lead to an imbalance of immune tolerance and immune-related adverse events (irAEs), which may extend to multiple organs. Approved uses of ICIs include the treatments of metastatic gastrointestinal malignancies, such as gastric, esophageal, colorectal and hepatocellular carcinomas. Despite having good efficacy and superior safety profile in early clinical trials, ICIs are clinically beneficial in only a fraction of patients with an objective response rate (ORR) of about 30%-40% in ICIs monotherapy or combination therapy. Although previous studies revealed that PD-L1 expression, microsatellite instability (MSI) status and tumor mutation burden (TMB) have some predictive values for ICIs, predictive powers of these biomarkers for ICIs treatments are still unsatisfactory and in some studies, contradictory.

This Research Topic aims at evaluating the predictive biomarkers for therapeutic efficacies of ICIs, with particular interest in hepatocellular carcinoma and gastric cancer therapies. This collection would preferentially focus on genetic or DNA and protein markers, as well as immune related cells that are implicated in modifying the tumor microenvironment (TME). Predictive biomarkers for irAEs and screening of potential drug for minimizing irAEs are also included. Submissions of high quality Original Research, Review, and Mini Review are welcome.

Note: Those consisting solely of bioinformatic investigation of publicly available genomic / transcriptomic data without experimental or in situ validation to support conclusions are not in scope for this Research Topic.