ArticleTechnology in cancer research & treatment
Transcriptomics and Prognosis Analysis to Identify Critical Biomarkers in Invasive Breast Carcinoma.
Article in Technology in cancer research & treatment. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Identification of modules and key genes associated with breast cancer subtypes through network analysis.Scientific reports · 2024Article
- The Prognostic Hub Gene POLE2 Promotes BLCA Cell Growth via the PI3K/AKT Signaling Pathway.Combinatorial chemistry & high throughput screening · 2024Article
- A novel 5-gene prognostic signature to improve risk stratification of cytogenetically normal acute myeloid leukemia.Journal of cancer research and clinical oncology · 2023Article
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveInvasive breast cancer (BRCA) is one of the prevalent types of invasive tumors with high mortality worldwide. Due to the lack of effective treatment to control the recurrence of distant metastases, the prognosis of BRCA is still very unsatisfactory. We aimed to find some biomarkers by bioinformatics analysis for survival prediction.
methodsDifferentially expressed genes (DEGs) were screened out based on tumor group and normal group. Then, the weighted gene correlation network analysis (WGCNA) was employed to identify the clinically associated gene sets. Meanwhile, the enrichment analyses were performed for the functional annotation of the critical genes. The Kaplan Meier analysis calculated the essential genes' prognostic value.
resultsAfter threshold screening, 1655 DEGs were obtained for subsequent analysis. 51 out of 1655 DEGs were significantly associated with BRCA patients' estrogen receptor status via WGCNA. Three genes (FABP7, CXCL3, and LOC284578) out of the 51 genes were associated with overall survival, and 3 genes were relapse-free survival associated. Finally, we obtained 5 essential prognostic associated genes (FABP7, CXCL3, LOC284578, CAPN6, and NRG2), which could be used as prognostic factors for BRCA.
conclusionOur findings obtained a gene module associated with BRCA clinical trait and several key genes that acted as essential components in the prognostic of cancer, which may improve its treatment.
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