In silico Drosophila Patient ModelReveals Optimal Combinatorial Therapies for Colorectal Cancer

Abstract

In silico models of biomolecular regulation in cancer, annotated with patient-specific gene expression data can aid in the development of novel personalized cancer therapeutics strategies. Drosophila melanogaster is a well-established animal model that is increasingly being employed to evaluate preclinical personalized cancer therapies. Here, we report five Boolean network models of biomolecular regulation in cells lining the Drosophila midgut epithelium and annotate them with patient-specific mutation data to develop an in silico Drosophila Patient Model (DPM). The network models were validated against cell-type-specific RNA-seq gene expression data from the FlyGut-seq database and through three literature-based case studies on colorectal cancer. The results obtained from the study help elucidate cell fate evolution in colorectal tumorigenesis, validate cytotoxicity of nine FDA-approved cancer drugs, and devise optimal personalized drug treatment combinations. The proposed personalized therapeutics approach also helped identify synergistic combinations of chemotherapy (paclitaxel) with targeted therapies (pazopanib, or ruxolitinib) for treating colorectal cancer. In conclusion, this work provides a novel roadmap for decoding colorectal tumorigenesis and in the development of personalized cancer therapeutics through a DPM.

TISON: a next-generation multi-scale modeling theatre forin silicosystems oncology

“…This feature is especially useful in predicting efficacious drug targets in light of patient's mutation data towards developing personalized cancer therapeutic combinations. Gondal et al (82) employed this feature to identify a synergistic combination of paclitaxel and pazopanib for treating colorectal cancer.…”

Navigating Multi-scale Cancer Systems Biology towards Model-driven Personalized Therapeutics

“…In particular, data-drive computational models are now acting as an enabling technology for precision medicine and personalized treatment of cancer. To date, several single and multi-scale software platforms have been reported to model biomolecular (180,(232)(233)(234)(235)(236)(237)(238)(239), environmental ( 240), cell-level (241)(242)(243), and multi-scale (244-246) information into coherent in silico cancer models (Figure 3).…”

“…This approach has been widely adopted as a tool to model gene, transcript, protein, and metabolite regulatory networks. Numerous mathematical and computational cancer models have been developed using this representation (180,(232)(233)(234)(235)(236). To facilitate the Boolean model development and analysis process, several platforms have been devised (249-251) (Supplementary Table 8).…”

“…TISON aims to develop single or multi-scale models for developing personalized cancer therapeutics. To exemplify the use case for TISON, Gondal et al employed TISON to model colorectal tumorigenesis in Drosophila melanogaster's midgut towards evaluating efficacious combinatorial therapies for individual colorectal cancer patients (236).…”