已发表论文

单细胞 RNA 测序和批量 RNA 测序的整合分析鉴定出浆细胞相关基因并构建肝细胞癌预后模型

 

Authors Tang M, Xu Y, Pan M

Received 24 December 2024

Accepted for publication 21 February 2025

Published 26 February 2025 Volume 2025:12 Pages 427—444

DOI https://doi.org/10.2147/JHC.S509749

Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 2

Editor who approved publication: Dr Ali Hosni

Mingyang Tang, Yuyan Xu, Mingxin Pan

General Surgery Center, Department of Hepatobiliary Surgery II, Zhujiang Hospital, Southern Medical University, Guangzhou, 510000, People’s Republic of China

Correspondence: Mingxin Pan, Department of Hepatobiliary Surgery II, Zhujiang Hospital, Southern Medical University, Guangzhou, 510000, People’s Republic of China, Email panmx@smu.edu.cn

Purpose: The complexity and heterogeneity of the tumor immune microenvironment (TIME) are linked to the development and poor prognosis of hepatocellular carcinoma (HCC). However, the cell type within the TIME that is most closely associated with HCC development remains unclear. Herein, we aimed to identify cell clusters that significantly contribute to HCC development and their underlying mechanisms.
Method and Results: Using single-cell RNA sequencing (scRNA-seq), we analyzed changes in the TIME of normal and tumor tissues, identifying plasma cells as the key cluster in HCC development. Based on plasma cell-related genes (PCRGs), we constructed and validated an eight-gene prognostic model (ST6GALNAC4, SEC61A1, SSR3, RPN2, PRDX4, TRAM1, SPCS2, CD79A) using internal and external datasets and a nomogram. Functional enrichment, miRNA network construction, and transcriptional regulation analyses were performed to explore underlying mechanisms. TIDE scores and the GDSC database were used to predict immunotherapy and chemotherapy sensitivity in different risk groups. Finally, SSR3’s biological function was validated in vitro in HCC cell lines.
Conclusion: Plasma cells are key clusters in HCC development. A prognostic model based on the PCRGs can accurately predict the prognosis of patients with HCC and guide clinical treatment.

Keywords: hepatocellular carcinoma, prognosis model, scRNA-seq, tumor immune microenvironment