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A three-gene resistome signature as a prognostic tool in hepatocellular carcinoma
Anabel Sanchez-Martin1, Rocio I R Macias2, Luis Muñoz-Bellvís3
1Experimental Hepatology and Drug Targeting (HEVEPHARM), Institute for Biomedical Research of Salamanca (IBSAL), University of Salamanca, Salamanca, Spain.
Introduction And Objectives:
Outcomes for patients with hepatocellular carcinoma (HCC) are generally poor, partly due to significant multidrug resistance. HCC heterogeneity decreases the accuracy of traditional prediction models. This study aimed to evaluate the prognostic significance of the HCC resistome.
Materials And Methods:
Clinical and transcriptomic data from 371 HCC cases available at TCGA were analyzed. An external dataset (604 patients from 4 cohorts) and 40 HCC samples, in which gene expression was determined by RT-qPCR, were used to validate the prognostic model.
Results:
The in silico analysis revealed two distinct clusters of patients based on the expression of resistome genes. Kaplan-Meier analysis indicated that Cluster 1 (C1) exhibited a better prognosis. Furthermore, the response to sorafenib treatment was better in patients included in C1 than in C2. Cox regression analysis identified the resistome profile as an independent prognostic factor alongside clinicopathological features such as tumor stage and ECOG status. Fifty-eight out of 81 genes examined displayed differential expression between clusters. Thirteen genes demonstrated a correlation between their expression levels and patient survival. In Cox multivariate analysis, SLC22A1, BIRC5, and ABCC1 genes emerged as independent prognostic factors, forming the basis for a risk model. BIRC5 and ABCC1 upregulation and SLC22A1 downregulation were associated with worse outcomes. Experimental results confirmed that patients with higher risk scores had a worse prognosis.
Conclusions:
A prognostic signature based on the expression levels of three resistome-associated genes has been defined and can serve as a helpful complementary tool in clinical settings to categorize HCC patients.
