A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer.

Mahnoor Naseer Gondal,Amir Faisal,Ghulam Mustafa,Safee Ullah Chaudhary,Muhammad Umer Sultan,Romena Qazi,Risham Hussain,Rida Nasir Butt,Osama Shiraz Shah,Muhammad Tariq,Zainab Nasir,Huma Khawar

doi:10.3389/fonc.2021.692592

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 therapeutic strategies. Drosophila melanogaster is a well-established animal model that is increasingly being employed to evaluate such 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 colorectal cancer patient-specific mutation data to develop an in silico Drosophila Patient Model (DPM). We employed cell-type-specific RNA-seq gene expression data from the FlyGut-seq database to annotate and then validate these networks. Next, we developed three literature-based colorectal cancer case studies to evaluate cell fate outcomes from the model. Results obtained from analyses of the proposed DPM help: (i) elucidate cell fate evolution in colorectal tumorigenesis, (ii) validate cytotoxicity of nine FDA-approved CRC drugs, and (iii) devise optimal personalized treatment combinations. The personalized network models helped identify synergistic combinations of paclitaxel-regorafenib, paclitaxel-bortezomib, docetaxel-bortezomib, and paclitaxel-imatinib for treating different colorectal cancer patients. Follow-on therapeutic screening of six colorectal cancer patients from cBioPortal using this drug combination demonstrated a 100% increase in apoptosis and a 100% decrease in proliferation. In conclusion, this work outlines a novel roadmap for decoding colorectal tumorigenesis along with the development of personalized combinatorial therapeutics for preclinical translational studies.

Highlights

Cancer development is a multistep process that is driven by a heterogeneous combination of somatic mutations at the genetic and epigenetic levels [1, 2]
Our results show that the biomolecular network of intestinal stem cells (ISCs) cells programmed apoptosis, extrusion (0.188), proliferation (0.131), and differentiation/EB fate (0.131)
We propose a novel in silico Drosophila Patient Model (DPM), a computational framework for devising personalized therapeutic combinations for colorectal cancer (CRC) patients

Summary

Introduction

Cancer development is a multistep process that is driven by a heterogeneous combination of somatic mutations at the genetic and epigenetic levels [1, 2]. Specific mutations in oncogenes [3] and tumor suppressor genes [4], that result in their activation and inactivation, respectively, manifest themselves at the tissue level in the form of polyps, multi-layering, and metastasis [1, 5, 6] These system-level properties resulting from heterogeneous biomolecular aberrations and dysregulated cellular processes are abstracted as “hallmarks of cancer” [1, 6]. The heterogeneity exhibited by cancer cells stems from factors such as genomic instability, clonal evolution, and variations in the microenvironment [7, 8] This fosters plasticity in cancer cells which lead to drug resistance – a leading impediment in the treatment of the disease [7,8,9]. Effective and seamless utilization of such patient-specific genomic data to design personalized cancer therapies is still a fledgling area

Methods

Results

Conclusion