Zhang X, Mi ZH. Identification of potential diagnostic and prognostic biomarkers for breast cancer based on gene expression omnibus. World J Clin Cases 2023; 11(27): 6344-6362 [PMID: 37900246 DOI: 10.12998/wjcc.v11.i27.6344]
Corresponding Author of This Article
Zhi-Hui Mi, MD, Senior Researcher, Department of Research and Marketing, Inner Mongolia Di An Feng Xin Medical Technology Co., LTD, Ru Yi Development Zone, Huhhot 010010, Nei Monggol Autonomous Region, China. zhihui_mi@sina.com
Research Domain of This Article
Biology
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. Sep 26, 2023; 11(27): 6344-6362 Published online Sep 26, 2023. doi: 10.12998/wjcc.v11.i27.6344
Identification of potential diagnostic and prognostic biomarkers for breast cancer based on gene expression omnibus
Xiong Zhang, Zhi-Hui Mi
Xiong Zhang, Department of Pathology, HuLunBuir Peoples’s Hospital, HuLunBuir 010018, Nei Monggol Autonomous Region, China
Zhi-Hui Mi, Department of Research and Marketing, Inner Mongolia Di An Feng Xin Medical Technology Co., LTD, Huhhot 010010, Nei Monggol Autonomous Region, China
Author contributions: Zhang X designed and directed the research; Mi ZH collected data and wrote the manuscript; all authors have read and approved the final manuscript.
Supported bythe Natural Science Foundation of Inner Mongolia, No. 2021GG0298.
Institutional review board statement: The data for the study came from public databases and did not involve blood or tissue samples from humans or animals. Therefore, there were no ethical issues involved in the study.
Informed consent statement: The data for the study came from public databases and did not involve blood or tissue samples from humans or animals. Therefore, the study did not involve any informed consent issues.
Conflict-of-interest statement: All the authors declare that they have no competing interests.
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: Zhi-Hui Mi, MD, Senior Researcher, Department of Research and Marketing, Inner Mongolia Di An Feng Xin Medical Technology Co., LTD, Ru Yi Development Zone, Huhhot 010010, Nei Monggol Autonomous Region, China. zhihui_mi@sina.com
Received: June 24, 2023 Peer-review started: June 24, 2023 First decision: August 9, 2023 Revised: August 18, 2023 Accepted: August 31, 2023 Article in press: August 31, 2023 Published online: September 26, 2023 Processing time: 88 Days and 4.2 Hours
Abstract
BACKGROUND
Breast cancer is regarded as a highly malignant neoplasm in the female population, posing a significant risk to women’s overall well-being. The prevalence of breast cancer has been observed to rise in China, accompanied by an earlier age of onset when compared to Western countries. Breast cancer continues to be a prominent contributor to cancer-related mortality and morbidity among women, primarily due to its limited responsiveness to conventional treatment modalities. The diagnostic process is challenging due to the presence of non-specific clinical manifestations and the suboptimal precision of conventional diagnostic tests. There is a prevailing uncertainty regarding the most effective screening method and target populations, as well as the specificities and execution of screening programs.
AIM
To identify diagnostic and prognostic biomarkers for breast cancer.
METHODS
Overlapping differentially expressed genes were screened based on Gene Expression Omnibus (GSE36765, GSE10810, and GSE20086) and The Cancer Genome Atlas datasets. A protein-protein interaction network was applied to excavate the hub genes among these differentially expressed genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses, as well as gene set enrichment analyses, were conducted to examine the functions of these genes and their potential mechanisms in the development of breast cancer. For clarification of the diagnostic and prognostic roles of these genes, Kaplan–Meier and Cox proportional hazards analyses were conducted.
RESULTS
This study demonstrated that calreticulin, heat shock protein family B member 1, insulin-like growth Factor 1, interleukin-1 receptor 1, Krüppel-like factor 4, suppressor of cytokine signaling 3, and triosephosphate isomerase 1 are potential diagnostic biomarkers of breast cancer as well as potential treatment targets with clinical implications.
CONCLUSION
The screening of biomarkers is of guiding significance for the diagnosis and prognosis of the diseases.
Core Tip: Breast cancer is one of the most common malignant tumors in women, according to statistics, the incidence of this disease accounts for 7%-10% of all kinds of malignant tumors in the whole body. However, the treatment of breast cancer is still not optimistic, and it is crucial to reveal the pathogenesis and biomarkers. Therefore, this study used bioinformatics statistics to mine the characteristic markers of breast cancer based on the database, in order to provide a more solid foundation for the treatment of the disease.
