A pharmacophore-based classification better predicts the outcomes of HER2-negative breast cancer patients receiving the anthracycline- and/or taxane-based neoadjuvant chemotherapy

Abstract

Aims: Prognosis of patients for human epidermal growth factor receptor 2 (HER2)-negative breast cancer post neoadjuvant chemotherapy is not well understood. The aim of this study was to develop a novel pharmacophore-based signature to better classify and predict the risk of HER2-negative patients after anthracycline-and/or taxane-based neoadjuvant chemotherapy (NACT). Main methods: Anthracycline and taxane pharmacophore-based genes were obtained from PharmMapper. Drug-targeted genes (DTG) related clinical and bioinformatic analyses were undertaken in four GEO datasets. Key findings: We used 12 genes from the pharmacophore to develop a DTG score (DTG-S). The DTG-S classification exhibited significant prognostic ability with respect to disease free survival (DFS) for HER2-negative patients who receive at least one type of neoadjuvant chemotherapy that included anthracycline and/or taxane. DTG-S associated with a high predictive ability for pathological complete response (pCR) as well as for prognosis of breast cancer. Using the DTG-S classification in other prediction models may improve the reclassification accuracy for DFS. Combining the DTG-S with other clinicopathological factors may further improve its predictive ability of patients’ outcomes. Gene ontology and KEGG pathway analysis showed that the biological processes of DTG-S high group were associated with the cell cycle, cell migration, and cell signal transduction pathways. Targeted drug analysis shows that some CDK inhibitors and PI3K-AKT pathway inhibitors may be useful for high DTG-S patients. Significance: The DTG-S classification adds prognostic and predictive information to classical parameters for HER2-negative patients who receive anthracycline-and/or taxane-based NACT, which could improve the patients’ risk stratification and may help guide adjuvant treatment.