ArticleWorld journal of clinical cases2024
Identification and validation of a new prognostic signature based on cancer-associated fibroblast-driven genes in breast cancer.
Article in World journal of clinical cases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundBreast cancer (BC), a leading malignant disease, affects women all over the world. Cancer associated fibroblasts (CAFs) stimulate epithelial-mesenchymal transition, and induce chemoresistance and immunosuppression.
aimTo establish a CAFs-associated prognostic signature to improve BC patient outcome estimation.
methodsWe retrieved the transcript profile and clinical data of 1072 BC samples from The Cancer Genome Atlas (TCGA) databases, and 3661 BC samples from the The Gene Expression Omnibus. CAFs and immune cell infiltrations were quantified using CIBERSORT algorithm. CAF-associated gene identification was done by weighted gene co-expression network analysis. A CAF risk signature was established
resultsEmploying an 8-gene (IL18, MYD88, GLIPR1, TNN, BHLHE41, DNAJB5, FKBP14, and XG) signature, we attempted to estimate BC patient prognosis. Based on our analysis, high-risk patients exhibited worse outcomes than low-risk patients. Multivariate analysis revealed the risk score as an independent indicator of BC patient prognosis. ROC analysis exhibited satisfactory nomogram predictability. The area under the curve showed 0.805 at 3 years, and 0.801 at 5 years in the TCGA cohort. We also demonstrated that a reduced CAF risk score was strongly associated with enhanced chemotherapeutic outcomes. CAF risk score was significantly correlated with most hallmark gene sets. Finally, the prognostic signature were further validated by qRT-PCR.
conclusionWe introduced a newly-discovered CAFs-associated gene signature, which can be employed to estimate BC patient outcomes conveniently and accurately.
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