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Prediction of pathological complete response and prognosis in patients with neoadjuvant treatment for triple-negative breast cancer.

ABSTRACT: BACKGROUND:It has been reported that pathological complete response is an important surrogate marker for disease-free survival and overall survival in patients with triple-negative breast cancer. This study investigates predictors of the response to neoadjuvant platinum-based or anthracycline-based treatment, and of the prognosis, in patients with triple-negative breast cancer. METHODS:A total of 121 patients with triple-negative breast cancer received neoadjuvant treatment with either platinum or anthracycline between 2008 and 2013. Pathological complete response was assessed relative to different treatments using logistic regression models with age, clinical tumor stage, grading, and Ki-67 as predictors and interaction terms, to obtain adjusted and subgroup-specific results. The impact of the pathological complete response rate on disease-free survival and overall survival was also analyzed. RESULTS:The pathological complete response rate was higher after platinum/taxane treatment compared with anthracycline/taxane (50.0% vs. 41.8%), but this was not significant in the adjusted analysis (OR 1.44; 95% CI, 0.68 to 3.09). A high histological grade (G3) was a predictor for higher pathological complete response in platinum-based therapy (OR 2.27; 95% CI, 1.00 to 5.30). The effect of neoadjuvant chemotherapy on pathological complete response was significantly different for G1-2 vs. G3 (Pinteraction?=?0.013), and additional subgroup-specific differences were noted. Pathological complete response was a predictor for improved disease-free survival and overall survival in both treatment groups, with and without platinum chemotherapy. CONCLUSIONS:This retrospective study of patients with triple-negative breast cancer adds to the evidence that the treatment effect of platinum may be greatest particularly in G3 tumors. In addition, the effect of pathological complete response on the prognosis does not depend on the treatment used.

SUBMITTER: Gass P

PROVIDER: S-EPMC6206705 | biostudies-literature | 2018 Oct

REPOSITORIES: biostudies-literature

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Prediction of pathological complete response and prognosis in patients with neoadjuvant treatment for triple-negative breast cancer.

Gass Paul P Lux Michael P MP Rauh Claudia C Hein Alexander A Bani Mayada R MR Fiessler Cornelia C Hartmann Arndt A Häberle Lothar L Pretscher Jutta J Erber Ramona R Wachter David L DL Schulz-Wendtland Rüdiger R Beckmann Matthias W MW Fasching Peter A PA Wunderle Marius M

BMC cancer 20181029 1

<h4>Background</h4>It has been reported that pathological complete response is an important surrogate marker for disease-free survival and overall survival in patients with triple-negative breast cancer. This study investigates predictors of the response to neoadjuvant platinum-based or anthracycline-based treatment, and of the prognosis, in patients with triple-negative breast cancer.<h4>Methods</h4>A total of 121 patients with triple-negative breast cancer received neoadjuvant treatment with e ...[more]

PMID: 30373556

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Project description:Objective: To develop and validate a prediction model for the pathological complete response (pCR) to neoadjuvant chemotherapy (NCT) of triple-negative breast cancer (TNBC). Methods: We systematically searched Gene Expression Omnibus, ArrayExpress, and PubMed for the gene expression profiles of operable TNBC accessible to NCT. Molecular heterogeneity was detected with hierarchical clustering method, and the biological profiles of differentially expressed genes were investigated by Gene Ontology, Kyoto Encyclopedia of Genes and Genomes analyses, and Gene Set Enrichment Analysis (GSEA). Next, machine-learning algorithms including random-forest analysis and least absolute shrinkage and selection operator (LASSO) analysis were synchronously performed and, then, the intersected proportion of significant genes was undergone binary logistic regression to fulfill variables selection. The predictive response score (pRS) system was built as the product of the gene expression and coefficient obtained from the logistic analysis. Last, the cohorts were randomly divided in a 7:3 ratio into training cohort and validation cohort for the introduction of a robust model, and a nomogram was constructed with the independent predictors for pCR rate. Results: A total of 217 individuals from four cohort datasets (GSE32646, GSE25065, GSE25055, GSE21974) with complete clinicopathological information were included. Based on the microarray data, a six-gene panel (ATP4B, FBXO22, FCN2, RRP8, SMERK2, TET3) was identified. A robust nomogram, adopting pRS and clinical tumor size stage, was established and the performance was successively validated by calibration curves and receiver operating characteristic curves with the area under curve 0.704 and 0.756, respectively. Results of GSEA revealed that the biological processes including apoptosis, hypoxia, mTORC1 signaling and myogenesis, and oncogenic features of EGFR and RAF were in proactivity to attribute to an inferior response. Conclusions: This study provided a robust prediction model for pCR rate and revealed potential mechanisms of distinct response to NCT in TNBC, which were promising and warranted to further validate in the perspective.

Dataset Information

Prediction of pathological complete response and prognosis in patients with neoadjuvant treatment for triple-negative breast cancer.

Publications

Prediction of pathological complete response and prognosis in patients with neoadjuvant treatment for triple-negative breast cancer.

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