Evaluation of anti-cancer therapy using in silico analysis of treatments for HER2+ breast cancer

Abstract

Cancer treatment has continually evolved towards the personalized selection and delivery of anticancer therapies. In this paper we evaluate the effectiveness of three treatments recommended by the NCCN guidelines for HER2-positive breast cancer using our clinical decision support tool called ChemoDSS. For our in silico analysis, we used pre-clinical data from the literature for HER2 transfected MCF7 human breast cancer xenografts in athymic mice. In particular, we analyzed the expected effects for the multi-drug treatments of AC-TH (i.e., Doxorubicin and Cyclophosphamide followed by Paclitaxel and Trastuzumab), TCH (i.e., Docetaxel, Carboplatin, and Trastuzumab), and TH (i.e., Docetaxel and Trastuzumab). Our results show that, using the pharmacokinetic (PK) and pharmacodynamic (PD) characteristics of the reported pre-clinical data, AC-TH appears to be the most effective regimen for treating this occurrence of breast cancer compared to TCH and TH. This result is consistent with literature findings for HER2 transfected MCF7 breast cancer xenografts, and demonstrates the effectiveness of various treatments recommended by the NCCN guidelines for HER2-positive breast cancer. We plan to incorporate various genetic markers into ChemoDSS, and verify existing and novel treatment regimens for different types of cancers.