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Bioinformatics analysis identifies potential chemoresistance-associated genes across multiple types of cancer
Jingsheng Yuan1, Lulu Tan1, Zhijie Yin1
1Department of Gastrointestinal Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, P.R. China.
Abstract:
Despite the fact that studies have revealed mechanisms underlying tumor chemoresistance, the functions of numerous potential chemoresistance-associated genes have yet to be elucidated. A bioinformatics analysis was conducted to screen differentially expressed genes (DEGs) across four types of chemoresistant tumors and functional enrichment analysis was used to examine the biological significance of these genes. Furthermore, a gene network was constructed using weighted gene co-expression network analysis to identify hub genes. A total of 6,015, 2,074, 2,141 and 954 differentially expressed genes were identified in estrogen receptor-negative breast cancer, ovarian cancer, rectal cancer and gastric cancer, respectively; however, only five of these DEGs were dysregulated in all four types of cancer. Functional enrichment analysis of the DEGs suggested that genomic stability and immune response are crucial determinants of tumor chemoresistance. In addition, 14, 8, 6 and 1 co-expressed gene modules were identified in estrogen receptor-negative breast cancer, ovarian cancer, rectal cancer and gastric cancer, respectively, and protein-protein interaction networks were created. The analysis identified only calcium-calmodulin-dependent protein kinase kinase 2, erythropoietin receptor, mitochondrial poly(A) RNA polymerase, α-parvin, and zinc finger and BTB domain-containing protein 44 to be dysregulated in all four cancer types, indicating varying mechanisms of chemoresistance in different tumor types. Furthermore, our analysis suggests that type I collagen α1, fibroblast growth factor 14 and major histocompatibility complex, class II, DR β1 potentially serve key roles in the development of chemoresistance. In conclusion, the present study proposes a simple and effective strategy for identifying genes involved in chemoresistance and predicting their potential functional roles, which may guide subsequent experimental studies.
Insights
This study identifies key genes involved in chemoresistance across four cancer types using bioinformatics. Genomic stability and immune response are crucial, with specific genes like type I collagen α1 potentially driving resistance.
Area of Science:
- Oncology
- Bioinformatics
- Genomics
Background:
- Mechanisms of tumor chemoresistance are partially understood, but many associated genes remain uncharacterized.
- Identifying novel chemoresistance-associated genes is crucial for developing effective cancer therapies.
Purpose of the Study:
- To screen differentially expressed genes (DEGs) in four chemoresistant tumor types using bioinformatics.
- To elucidate the biological significance of DEGs through functional enrichment analysis.
- To identify key genes and pathways involved in tumor chemoresistance.
Main Methods:
- Differential gene expression analysis across estrogen receptor-negative breast cancer, ovarian cancer, rectal cancer, and gastric cancer.
- Functional enrichment analysis to determine biological roles of DEGs.
- Weighted gene co-expression network analysis (WGCNA) to construct gene networks and identify hub genes.
Main Results:
- Over 6,000 DEGs found in estrogen receptor-negative breast cancer, with thousands more in other cancers; only five DEGs were common across all four.
- Functional enrichment highlighted genomic stability and immune response as critical factors in chemoresistance.
- Specific genes including type I collagen α1, fibroblast growth factor 14, and MHC class II DR β1 were implicated in chemoresistance development.
Conclusions:
- A bioinformatics strategy effectively identifies chemoresistance-associated genes and predicts their functions.
- Genomic stability and immune response pathways are vital in chemoresistance.
- The study provides insights into varying chemoresistance mechanisms and potential therapeutic targets across different cancer types.
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