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

单细胞转录组分析揭示肝细胞癌中一种与癌症相关的成纤维细胞标志基因特征,该特征可预测预后

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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.

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