ArticleThe breast journal2026
Development and Validation of a Cuproptosis-Based Risk Score Model for Predicting Neoadjuvant Chemotherapy Response in Breast Cancer: A Transcriptomic Analysis.
Article in The breast journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
Abstract
objectiveThis study developed a cuproptosis-related transcriptomic risk score model to predict neoadjuvant chemotherapy (NAC) response in breast cancer (BC) patients and explored its association with the tumor immune microenvironment.
methodsAnalysis of transcriptomic and clinical data from TCGA and GEO revealed differentially expressed cuproptosis-related genes. LASSO-based Cox regression was used to build the risk score. Model performance was evaluated using Kaplan-Meier survival, ROC curves, and GSEA/GSVA in the training cohort and further validated in an independent external cohort. Drug sensitivity was predicted using the oncoPredict tool, and RT-qPCR was used to validate key gene expression.
resultsA 10-gene prognostic model was developed based on the identification of 71 cuproptosis-related genes. The risk score correlated with survival outcomes, PAM50 subtypes, tumor stage, and pathologic response. It showed good predictive performance in both training (AUC = 0.719) and testing (AUC = 0.689) cohorts. Key genes (CIRBP, INPP4B, IL6ST, and CCL20) were validated and linked to NAC response.
conclusionThe cuproptosis-based risk score model effectively predicts NAC response and may guide personalized treatment in BC. It also reveals the relevance of cuproptosis-related genes in immune modulation and chemotherapy sensitivity.
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