Identification of molecular subtypes and prognostic signatures based on transient receptor potential channel-related genes to predict the prognostic risk of hepatocellular carcinoma: A review. Issue 10 (10th March 2023)

• Record Type: Journal Article
• Authors: Wu, Dongyang; Cai, Qingshan; Liu, Dong; Zuo, Ganggang; Li, Shudong; Liu, Liyou; Zheng, Jianxing
• Is Part Of: Medicine. Volume 102:Issue 10(2023)
• Page Start: e33228
• Publication Date: 2023-03-10
• Subjects: hepatocellular carcinoma -- molecular subtypes -- prognostic model -- transient receptor potential channel; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000033228
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abnormal transient receptor potential (TRP) channel function interferes with intracellular calcium-based signaling and causes malignant phenotypes. However, the effects of TRP channel-related genes on hepatocellular carcinoma (HCC) remain unclear. This study aimed to identify HCC molecular subtypes and prognostic signatures based on TRP channel-related genes to predict prognostic risks. Unsupervised hierarchical clustering was applied to identify HCC molecular subtypes using the expression data of TRP channel-related genes. This was followed by a comparison of the clinical and immune microenvironment characteristics between the resulting subtypes. After screening for differentially expressed genes among subtypes, prognostic signatures were identified to construct risk score-based prognostic and nomogram models and predict HCC survival. Finally, tumor drug sensitivities were predicted and compared between the risk groups. Sixteen TRP channel-related genes that were differentially expressed between HCC and non-tumorous tissues were used to identify 2 subtypes. Cluster 1 had higher TRP scores, better survival status, and lower levels of clinical malignancy. Immune-related analyses also revealed higher infiltration of M1 macrophages and higher immune and stromal scores in Cluster 1 than in Cluster 2. After screening differentially expressed genes between subtypes, 6 prognostic signatures were identified to construct prognostic and nomogram models. The potential of these models to assess the prognostic risk of HCC was further validated. Furthermore, Cluster 1 was more distributed in the low-risk group, with higher drug sensitivities. Two HCC subtypes were identified, of which Cluster 1 was associated with a favorable prognosis. Prognostic signatures related to TRP channel genes and molecular subtypes can be used to predict HCC risk.