A novel prognostic model for Hedgehog signaling pathway-related genes predicts the prognosis of hepatocellular carcinoma

TL;DR

This study creates a five-gene model based on the Hedgehog signaling pathway to predict outcomes in liver cancer patients and guide immunotherapy.

Contribution

A novel five-gene prognostic model for hepatocellular carcinoma based on Hedgehog signaling pathway-related genes is developed.

Findings

The five-gene model (BMP2, CSNK1D, CSNK1E, ZIC2, PRKACB) is a robust predictor of overall survival in HCC patients.

Risk scores correlate with immune microenvironment features like immune cell infiltration and checkpoint expression.

qRT-PCR confirmed higher expression of the five genes in HCC tissues compared to normal tissues.

Abstract

The Hedgehog signaling pathway is involved in the carcinogenesis and development of hepatocellular carcinoma(HCC); however, few studies on the prognostic model of the Hedgehog signaling pathway have been found.

First, we selected 56 Hedgehog signaling pathway-related genes from the UALCAN database and used the DESeq2 method to screen out differentially expressed genes in HCC and normal liver samples. Validation was performed using quantitative real-time PCR (qRT-PCR) of HCC and normal tissues. Second, the differentially expressed genes were analyzed using Cox and Lasso regression, and a five-gene prognostic risk model was established. Risk scores were divided into high-risk and low-risk groups, and their correlation with clinical indicators and immunity was analyzed. Univariate and multivariate regression analyses were performed for risk scores. Finally, a comparative functional enrichment analysis was conducted to delineate the biological pathway disparities between the high- and low-risk groups. The effectiveness of the model was validated using the ICGC database.

The prognostic risk model of five genes(BMP2,CSNK1D,CSNK1E, ZIC2, and PRKACB) was obtained after screening 56 Hedgehog signaling pathway-related genes. Risk scores emerged as robust independent predictors of overall survival through univariate and multivariate analyses, independent of other clinicopathological parameters, in TCGA and ICGC cohorts. A significant correlation was observed between risk scores and immune microenvironment characteristics, including immune cell infiltration and immune checkpoint expression levels. qRT-PCR analysis confirmed that the expression of the five genes in the prognostic model was higher in HCC tissues than in normal tissues. Moreover, some functional pathways were identified in the high-risk group in the low-risk group.

We developed a novel five-gene prognostic model centered on Hedgehog signaling pathway-related genes, which holds potential as a valuable prognostic tool for HCC and may provide guidance for immunotherapy selection.

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