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Recent Patents on Anti-Cancer Drug Discovery

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ISSN (Print): 1574-8928
ISSN (Online): 2212-3970

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Research Article

Integrating Bioinformatics and Drug Sensitivity Analyses to Identify Molecular Characteristics Associated with Targeting Necroptosis in Breast Cancer and their Clinical Prognostic Significance

Author(s): Chang Zheng, Hanbin Guo, Yongpan Mo and Guowen Liu*

Volume 19, Issue 5, 2024

Published on: 05 October, 2023

Page: [681 - 694] Pages: 14

DOI: 10.2174/1574892819666230831112815

Price: $65

Abstract

Background: Breast cancer accounts for over 1.8 million new cases worldwide annually, and prompt diagnosis and treatment are imperative to prevent mortality. Necroptosis, a form of programmed cell death, is thought to be a critical pathway for cancer cell apoptosis, yet, its relationship with breast cancer progression and molecular mechanisms remains largely unexplored.

Objectives: Our study aims to investigate the molecular characteristics and clinical prognostic value of necroptosis-related genes in breast cancer using a comprehensive approach that involves integrated bioinformatics analysis along with drug sensitivity assessment.

Methods: Transcriptional, clinical, and tumor mutation burden (TMB) data related to breast cancer from the TCGA and GEO databases were integrated, and the necroptosis gene set was downloaded from the GSEA website for analysis. The screening conditions were set as adjusted p < 0.05 and |log2FC(fold change)| > 0.585 to screen for differential expression genes related to breast cancer necroptosis. Survival prognosis analysis was conducted on breast cancer necroptosis genes. Further analysis was conducted on prognosis-related necroptosis genes, including immune infiltration analysis and GO/KEGG enrichment analysis, to explore the potential biological functions and signaling pathway mechanisms of breast cancer necroptosis genes. Drug sensitivity screening was conducted on the prognosis-related necroptosis to identify potential drugs that target the promotion of necroptosis gene expression, and ultimately, single-gene analysis was performed on the core target genes obtained.

Results: Through integrated bioinformatics analysis, 29 differentially expressed mRNAs related to BRCA-Necroptosis were identified, including 18 upregulated mRNAs and 11 downregulated mRNAs. In addition, single-factor analysis of differential genes showed that the expression of HSPA4, PLK1, TNFRSF1B, FLT3, and LEF1 was closely related to BRCA survival prognosis. Based on the expression of these genes, a breast cancer prognosis model was constructed, and it was found that the area under the curve (AUC) of the curve of the risk genes for necroptosis was the largest, indicating that these genes have a certain clinical predictive significance for the occurrence and prognosis of BRCA. Additionally, there were significant differences in clinical characteristics of BRCA patients with different necroptosis gene expressions. Furthermore, GSVA and immune infiltration analysis revealed that Necroptosis-DEGs mainly affect the occurrence and progression of BRCA by participating in immune functions such as APC co-inhibition, APC costimulation, CCR, checkpoint, as well as infiltrating immune cells such as B cells naive, plasma cells, and T cells CD8. Moreover, the necroptosis gene group column chart indicated a 1-year survival rate of 0.979, a 3-year survival rate of 0.883, and a 5-year survival rate of 0.774. The necroptosis gene group and column chart are important indicators for evaluating BRCA prognosis. Finally, drug sensitivity screening of BRCA-Necroptosis genes showed that compounds such as A- 770041, AC220, AP-24534, Bexarotene, and BMS-509744 have certain effects as potential targeted drugs for the treatment of BRCA necroptosis genes.

Conclusion: Necroptosis genes are implicated in the pathogenesis and progression of breast cancer and are thought to impact the prognosis and response to drug treatments in individuals with BRCA. Consequently, understanding the role of these genes in breast cancer may aid in identifying more precise and efficacious therapeutic targets.

Keywords: Breast cancer, necroptosis, integrated bioinformatics analysis, survival prognosis analysis, drug sensitivity, pathogenesis.

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