Exploring the Molecular Mechanisms Network of Breast Cancer by Multi-omics Analysis

Overview

Journal Asia Pac J Clin Oncol

Specialty Oncology

Date 2024 Mar 13

PMID 38477438

Authors

Wei Jiang

Yanjun Zhang

Qiuqiong Wang

Affiliations

Soon will be listed here.

Abstract

Background: Breast cancer (BC), the most prevalent malignancy in women globally, still lacks comprehensive research on its molecular targets and necessitates further investigation into the underlying molecular mechanisms driving its initiation and progression.

Methods: The GSE20685 Series Matrix File downloaded from the Gene Expression Omnibus database was divided into a high-risk group (n = 49) and a low-risk group (n = 278) to construct the co-expression network.

Results: Four hub genes were identified based on the Weighted Gene Co-expression Network Analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses were performed. Hub gene immune infiltration was investigated using the Tumor Immune Estimation Resource database, and CD4+ T cell expression levels were substantially correlated with hub gene expression. Based on the CancerRxGene database (Genomics of Drug Sensitivity in Cancer database), it was found that the hub genes were highly sensitive to common chemotherapy drugs such as AKT inhibitor VIII and Erlotinib. The expression of Secreted Frizzled-Related Protein 1, melanoma-inhibiting activity (MIA), and Keratin 14 was related to tumor mutation burden, and the expression of MIA also affected the microsatellite instability of the tumor. This study employs multi-omics analysis to investigate the molecular network associated with the prognosis of BC, highlighting its intricate connection with the immune microenvironment.

Conclusion: These findings pinpoint four crucial genes in BC progression, offering targets for further research and therapy. Their connections to immune infiltration and chemotherapy sensitivity underscore complex interactions in the tumor microenvironment.

Citing Articles

Exploring the molecular mechanisms network of breast cancer by multi-omics analysis.

Jiang W, Zhang Y, Wang Q Asia Pac J Clin Oncol. 2024; 21(1):129-137.

PMID: 38477438 PMC: 11733836. DOI: 10.1111/ajco.14052.

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