Multi-omics-driven personalized management of advanced HCC.

Authors

Jianpeng Sheng, Jinyuan Song, Lin Wang, Junlei Zhang, Wei Zhang, Hang Shi, Yaxing Zhao, Chengxiang Guo, Jianghui Tang, Yongtao Ji, Taohong Li, Wei Shao, Xueli Bai, Qing Li, Tingbo Liang

Published in

Cell reports. Medicine. Pages 103085. Oct 02, 2026. Epub Oct 02, 2026.

Abstract

Hepatocellular carcinoma (HCC) management is challenging due to its complex tumor microenvironment and poor treatment responses. Here, using tumor specimens from a prospective clinical trial of combined transarterial chemoembolization (TACE) with immune checkpoint blockade (ICB), we perform exhaustive multi-omics analysis including spatial proteomics and transcriptomics, single-cell RNA sequencing, and bulk transcriptomics. These analyses reveal that treatment response is associated with enrichment of anti-tumor T cell regions that are regulated by cGAS-STING activation within immune-suppressive epithelial cells. Conversely, fibrotic processes impede these pro-response processes. Based on these insights, we test triple combination therapy consisting of cGAS activation, immune checkpoint blockade, and anti-fibrosis strategies, which shows improved efficacy over dual therapy. To identify patients who would benefit, we construct a predictive model using a group sparse learning algorithm. Our findings provide a blueprint for crafting personalized HCC therapies using next-generation biomarkers.

PMID:
42826719
Bibliographic data and abstract were imported from PubMed on 03 Oct 2026.

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