ArticleFrontiers in immunology2021
An Immune-Associated Genomic Signature Effectively Predicts Pathologic Complete Response to Neoadjuvant Paclitaxel and Anthracycline-Based Chemotherapy in Breast Cancer.
Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Article
- Artificial neural network-based immune biomarker signature predicts pathological complete response to neoadjuvant chemotherapy in HER2-negative breast cancer.Frontiers in oncology · 2026Article
- Unveiling immune-related gene signatures in triple negative breast cancer through integrated transcriptomic analysis.BioMedicine · 2026Article
- Resistance to neoadjuvant chemotherapy in breast cancers: a metabolic perspective.Journal of experimental & clinical cancer research : CR · 2025Review
- Immune Subtyping Identifies Patients With Hormone Receptor-Positive Early-Stage Breast Cancer Who Respond to Neoadjuvant Immunotherapy (IO): Results From Five IO Arms of the I-SPY2 Trial.JCO precision oncology · 2025Article
- GSDME-mediated pyroptosis promotes anti-tumor immunity of neoadjuvant chemotherapy in breast cancer.Cancer immunology, immunotherapy : CII · 2024Article
- Application of triple evaluation method in predicting the efficacy of neoadjuvant therapy for breast cancer.World journal of surgical oncology · 2023Article
- Identifying biomarkers of differential chemotherapy response in TNBC patient-derived xenografts with a CTD/WGCNA approach.iScience · 2023Article
- High-accuracy prediction of colorectal cancer chemotherapy efficacy using machine learning applied to gene expression data.Frontiers in physiology · 2023Article
- GSTP1 c.313A > G mutation is an independent risk factor for neutropenia hematotoxicity induced by anthracycline-/paclitaxel-based chemotherapy in breast cancer patients.World journal of surgical oncology · 2022Article
- Article
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8 authors.
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Abstract
Breast cancer is now the leading cause of cancer morbidity and mortality among women worldwide. Paclitaxel and anthracycline-based neoadjuvant chemotherapy is widely used for the treatment of breast cancer, but its sensitivity remains difficult to predict for clinical use. In our study, a LASSO logistic regression method was applied to develop a genomic classifier for predicting pathologic complete response (pCR) to neoadjuvant chemotherapy in breast cancer. The predictive accuracy of the signature classifier was further evaluated using four other independent test sets. Also, functional enrichment analysis of genes in the signature was performed, and the correlations between the prediction score of the signature classifier and immune characteristics were explored. We found a 25-gene signature classifier through the modeling, which showed a strong ability to predict pCR to neoadjuvant chemotherapy in breast cancer. For T/FAC-based training and test sets, and a T/AC-based test set, the AUC of the signature classifier is 1.0, 0.9071, 0.9683, 0.9151, and 0.7350, respectively, indicating that it has good predictive ability for both T/FAC and T/AC schemes. The multivariate model showed that 25-gene signature was far superior to other clinical parameters as independent predictor. Functional enrichment analysis indicated that genes in the signature are mainly enriched in immune-related biological processes. The prediction score of the classifier was significantly positively correlated with the immune score. There were also significant differences in immune cell types between pCR and residual disease (RD) samples. Conclusively, we developed a 25-gene signature classifier that can effectively predict pCR to paclitaxel and anthracycline-based neoadjuvant chemotherapy in breast cancer. Our study also suggests that the immune ecosystem is actively involved in modulating clinical response to neoadjuvant chemotherapy and is beneficial to patient outcomes.
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