Single-cell transcriptome analysis reveals a cancer-associated fibroblast marker gene signature in hepatocellular carcinoma that predicts prognosis

Abstract

Background and aims

Hepatocellular carcinoma (HCC) is one of the leading causes of cancer death. Multi-pathway combination therapy is used to treat HCC, and immunotherapy is also a routine part of treatment. As a major component of the tumor microenvironment (TME), cancer-associated fibroblasts (CAFs) actively participate in cancer progression through complex functions. However, because CAFs dynamically change during cancer development, most of the current treatment strategies targeting CAFs fail. We created a prognostic CAF marker gene signature (CAFMGS) to investigate the utility of CAFs as a prognostic factor and therapeutic target.

Methods

Gene Expression Omnibus (GEO) single-cell RNA sequencing (Sc-RNA-seq) data were analyzed to identify CAF marker genes in HCC. The Cancer Genome Atlas (TCGA) database was used as a training cohort to construct the CAFMGS model and the International Cancer Genome Consortium (ICGC) dataset was used to validate the CAFMGS.

Results

Marker genes in the CAFMGS model were (0.0001-SPP1), (0.0084-VCX3A), (0.0015-HMGA1), (0.0082-PLOD2), and (0.0075-CACYBP). The CAFMGS_score was separated into high-risk and low-risk groups based on the median of the patients’ OS. Univariate and multivariate analyses confirmed that CAFMGS_score was an independent prognostic factor in the training group. CAFMGS_score was a more accurate prognostic indicator compared with clinicopathological score and tumor mutational burden score.

Conclusion

CAFMGS offers a fresh perspective on stromal cell marker genes in HCC prognosis and expands our knowledge of CAF heterogeneity and functional diversity, perhaps paving the way for CAF-targeted immunotherapy in HCC patients.