Zou JY, Huang YJ, He J, Tang ZX, Qin L. Glycolytic and fatty acid oxidation genes affect the treatment and prognosis of liver cancer. World J Clin Cases 2022; 10(15): 4737-4760 [PMID: 35801051 DOI: 10.12998/wjcc.v10.i15.4737]
Corresponding Author of This Article
Lei Qin, MD, Doctor, Professor, Department of General Surgery, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou 215006, Jiangsu Province, China. qinleihbps@163.com
Research Domain of This Article
Biotechnology & Applied Microbiology
Article-Type of This Article
Clinical and Translational Research
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Cases. May 26, 2022; 10(15): 4737-4760 Published online May 26, 2022. doi: 10.12998/wjcc.v10.i15.4737
Glycolytic and fatty acid oxidation genes affect the treatment and prognosis of liver cancer
Jia-Yue Zou, Yu-Jie Huang, Jun He, Zu-Xiong Tang, Lei Qin
Jia-Yue Zou, Yu-Jie Huang, Jun He, Zu-Xiong Tang, Lei Qin, Department of General Surgery, The First Affiliated Hospital of Soochow University, Suzhou 215006, Jiangsu Province, China
Author contributions: Zou JY was responsible for data curation, methodology, and writing the original draft; Huang YJ was responsible for visualization and software; He J and Tang ZX were responsible for data collection and data curation; Qin L was responsible for writing, reviewing, and editing.
Supported bythe Project of National Natural Science Foundation of China, No. 81802365 and 81802385; the Special Project of Clinical Key Diseases Treatment Technology in Suzhou, No. LCZX2019003; the City-Level Scientific Research Projects in Jiangsu Province, No. SLT201907; Major Projects of Provincial Universities in Jiangsu Province, No. 19KJA170002; Soochow University Horizontal Research Project, No. H190168.
Conflict-of-interest statement: Authors certify that there is no conflict of interest related to the manuscript.
Data sharing statement: No additional data are available.
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: Lei Qin, MD, Doctor, Professor, Department of General Surgery, The First Affiliated Hospital of Soochow University, No. 899 Pinghai Road, Suzhou 215006, Jiangsu Province, China. qinleihbps@163.com
Received: September 13, 2021 Peer-review started: September 13, 2021 First decision: January 23, 2022 Revised: February 2, 2022 Accepted: April 2, 2022 Article in press: April 2, 2022 Published online: May 26, 2022 Processing time: 253 Days and 0.9 Hours
ARTICLE HIGHLIGHTS
Research background
Metabolic reprogramming is a feature of tumour cells and is essential to support their rapid proliferation. Lipid metabolism reprogramming enables tumour cells to meet their needs for highly proliferative growth and is an important driving force for the development of hepatocellular carcinoma (HCC).
Research motivation
We explored the influence of different metabolic subtypes of HCC and analysed their significance in guiding prognosis and treatment based on the molecular mechanism of glycolysis and fatty acid oxidation (FAO).
Research objectives
To explore the influence of different metabolic subtypes of HCC and analyse their significance in guiding prognosis and treatment.
Research methods
We utilised unsupervised consensus clustering to divide the Cancer Genome Atlas-liver hepatocellular carcinoma samples into four metabolic subgroups and compared single nucleotide polymorphism, copy number variation, tumour microenvironment, and Genomics of Drug Sensitivity in Cancer and Tumour Immune Dysfunction and Exclusion between different metabolites. In addition, we established a prognostic model based on glycolysis and FAO genes.
Research results
We established a prognostic model and found that the fatty acid oxidation group and the low-risk group had better efficacy and response to immune checkpoint blockade treatment and anti-tumour drugs.
Research conclusions
There are obvious differences in genes, chromosomes, and clinical characteristics between metabolic subgroups.
Research perspectives
The establishment of a prognostic model could predict patient prognosis and guide clinical treatment.
