Clinical and Translational Research
Copyright ©The Author(s) 2024. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Oncol. Mar 24, 2024; 15(3): 434-446
Published online Mar 24, 2024. doi: 10.5306/wjco.v15.i3.434
Establishment of a prognosis predictive model for liver cancer based on expression of genes involved in the ubiquitin-proteasome pathway
Hua Li, Yi-Po Ma, Hai-Long Wang, Cai-Juan Tian, Yi-Xian Guo, Hong-Bo Zhang, Xiao-Min Liu, Peng-Fei Liu
Hua Li, Department of Endoscopy, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy of Tianjin, Tianjin’s Clinical Research Center for Cancer, Tianjin 300060, China
Yi-Po Ma, Department of Critical Care Medicine, Dingzhou City People’s Hospital, Dingzhou 073000, Hebei Province, China
Hai-Long Wang, Peng-Fei Liu, Department of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, Tianjin 300120, China
Cai-Juan Tian, Hong-Bo Zhang, Tianjin Marvel Medical Laboratory, Tianjin Marvelbio Technology Co., Ltd, Tianjin 300180, China
Yi-Xian Guo, Department of Intelligent Technology, Tianjin Yunquan Intelligent Technology Co., Ltd, Tianjin 300381, China
Xiao-Min Liu, Department of Oncology, Tianjin Huanhu Hospital, Tianjin 300350, China
Co-first authors: Hua Li and Yi-Po Ma.
Co-corresponding authors: Xiao-Min Liu and Peng-Fei Liu.
Author contributions: Liu XM and Liu PF conceptualized and designed the research; Li H and Ma YP collected the data and wrote the manuscript; Wang HL conducted the data mining and prepared the figures; Tian CJ, Guo YX, and Zhang HB conducted the bioinformatics analysis; all authors were involved in the critical review of the results and have contributed to, read, and approved the final manuscript. Li H and Ma YP contributed equally to this work and are the co-first authors. Liu XM and Liu PF contributed equally to this study and are the co-corresponding authors. There are two primary reasons behind appointing Li H and Ma YP as co-first authors, and Liu XM and Liu PF as co-corresponding authors. First, our research was conducted through a collaborative effort, and the selection of first and corresponding authors aptly mirrors the distribution of responsibilities and the shared commitment of time and effort needed to carry out the study and produce the resulting paper. This approach ensures effective communication and facilitates the management of post-submission matters, ultimately enhancing the paper's overall quality and reliability. Second, each of these researchers made substantial and equal contributions throughout the entire research process. Designating them as co-first authors or co-corresponding authors not only acknowledges and respects their equivalent input but also highlights the spirit of teamwork and collaboration that characterized this study. In summary, the choice to designate Li H and Ma YP as co-first authors, and Liu XM and Liu PF as co-corresponding authors is appropriate for our manuscript as it accurately reflects our team's collaborative ethos and equal contributions.
Supported by the Tianjin Municipal Natural Science Foundation, No. 21JCYBJC01110.
Institutional review board statement: TCGA is a public database. The patients involved in the database have obtained ethical approval. Users can download relevant data for free for research and publish relevant articles. Our study was based on open-source data, so there are no statements on ethics approval and consent.
Informed consent statement: Our study is based on open-source data, so there are no statements on informed consent.
Conflict-of-interest statement: All authors declare that they have no competing interests to disclose.
Data sharing statement: Publicly available datasets were analyzed in this study, and these can be found in the TCGA database (http://portal.gdc.cancer.gov/).
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Peng-Fei Liu, MD, Chief Doctor, Surgical Oncologist, Department of Oncology, Tianjin Academy of Traditional Chinese Medicine Affiliated Hospital, No. 354 North Road, Hongqiao District, Tianjin 300120, China. liupengfeitj@163.com
Received: October 11, 2023
Peer-review started: October 11, 2023
First decision: December 7, 2023
Revised: December 27, 2023
Accepted: February 5, 2024
Article in press: February 5, 2024
Published online: March 24, 2024
Processing time: 163 Days and 5.6 Hours
ARTICLE HIGHLIGHTS
Research background

The ubiquitin-proteasome pathway (UPP) is crucial for selective protein degradation, and its dysfunction is linked to various diseases, including cancer. Proteasome inhibitors are emerging as potential anti-tumor drugs. This study explored the association between UPP gene expression and liver cancer prognosis, aiming to identify key genes and develop a predictive model. By doing so, the research seeks to offer novel insights into the role and potential mechanisms of the UPP in liver cancer development, contributing to the ongoing exploration of effective therapeutic strategies for liver cancer.

Research motivation

Due to the high tumor heterogeneity, effective surveillance and predication of the prognosis of liver cancer still face multiple challenges. This study was performed to analyze the relationship between the expression of genes in the UPP and the prognosis of liver cancer and construct a prognosis predictive model for this malignancy.

Research objectives

The study aimed to investigate the prognostic significance of genes in the UPP in liver cancer. Using gene expression data from The Cancer Genome Atlas (TCGA) and gene expression comprehensive (GEO) databases, the study identified key genes involved in the UPP, constructed a prognostic predictive model for liver cancer, and explored the associations of the model with immune cell infiltration and clinical parameters, in order to enhance liver cancer prognosis prediction and provide insights into the role and potential mechanisms of the UPP in liver cancer development, contributing valuable information for precision medicine in the context of liver cancer management.

Research methods

The research employed diverse methodologies, utilizing UPP-related gene sets and patient data from TCGA and GEO databases. A prognostic model was constructed using univariate and multivariate regression analyses, involving five key genes (ATG10, PSMA8, PSMB2, USP17L2, and USP8). The model demonstrated robust predictive abilities for liver cancer prognosis. Immunocyte infiltration analysis and correlation studies with clinical parameters provided additional insights. Differentially expressed genes and enrichment analyses shed light on relevant pathways. The study's comprehensive approach contributes a nuanced understanding of UPP gene implications in liver cancer prognosis.

Research results

This study investigated the role of the UPP in liver cancer, identifying five key genes (ATG10, PSMA8, PSMB2, USP17L2, and USP8) associated with prognosis. A predictive model was constructed and validated using TCGA and GEO datasets. The study highlighted differential gene expression between the high- and low-risk groups and enriched relevant pathways. Additionally, differentially expressed genes in the E3 gene set (CDC20, KBTBD11, and DCAF4L2) were identified as significant. The findings provide valuable insights into liver cancer prognosis, immunology, and potential therapeutic targets.

Research conclusions

We have used gene expression data in TCGA to screen genes in the UPP that significantly correlated with the prognosis of liver cancer. Our findings indicate that the UPP plays an important role in the development of liver cancer, which provides new insights into the early prediction of prognosis and precision medicine in liver cancer.

Research perspectives

This is a preliminary study, and the results reported are exploratory. We intend to validate these results and the detailed mechanisms in future studies.