Identification of a Prognostic Transcriptome Signature for Hepatocellular Carcinoma with Lymph Node Metastasis.

Oxid Med Cell Longev

Department of Radiation Oncology, Shanghai East Hospital, School of Medicine, Tongji University, Shanghai 200120, China.

Published: July 2022


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Article Abstract

Hepatocellular carcinoma (HCC) is one of the most aggressive malignant tumors, and the prognosis of HCC patients with lymph node metastasis (LNM) is poor. However, robust biomarkers for predicting the prognosis of HCC LNM are still lacking. This study used weighted gene coexpression network analysis of GSE28248 ( = 80) microarray data to identify gene modules associated with HCC LNM and validated in GSE40367 dataset ( = 18). The prognosis-related genes in the HCC LNM module were further screened based on the prognostic curves of 371 HCC samples from TCGA. We finally developed a prognostic signature, PSG-30, as a prognostic-related biomarker in HCC LNM. The HCC subtypes identified by PSG-30-based consensus clustering analysis showed significant differences in prognosis, clinicopathological stage, m6A modification, ferroptosis activation, and immune characteristics. In addition, was selected by regression model as an independent risk factor affecting the prognosis of HCC patients with LNM, and its expression was significantly positively correlated with tumor mutational burden and microsatellite instability in high-risk subtypes. Patients with high expression had a better prognosis in the immune checkpoint inhibitor-treated cohorts but had a poor prognosis in the HCC sorafenib-treated group. The association of high expression with LNM in breast cancer (BRCA) and cholangiocarcinoma and its prognostic effect in BRCA LNM cases suggest the value of at the pancancer level. In conclusion, PSG-30 can effectively identify HCC LNM population with poor prognosis, and high-risk patients with high expression may be more suitable for immunotherapy.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9279092PMC
http://dx.doi.org/10.1155/2022/7291406DOI Listing

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