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

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...

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Bibliographic Details
Published in:	Frontiers in oncology Vol. 11; p. 692592
Main Authors:	Gondal, Mahnoor Naseer, Butt, Rida Nasir, Shah, Osama Shiraz, Sultan, Muhammad Umer, Mustafa, Ghulam, Nasir, Zainab, Hussain, Risham, Khawar, Huma, Qazi, Romena, Tariq, Muhammad, Faisal, Amir, Chaudhary, Safee Ullah
Format:	Journal Article
Language:	English
Published:	Frontiers Media S.A 16-07-2021
Subjects:	Boolean network models cancer systems biology combinatorial therapeutics Oncology personalized in silico cancer models preclinical in silico drug screening
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Summary:	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.
Bibliography:	ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 This article was submitted to Pharmacology of Anti-Cancer Drugs, a section of the journal Frontiers in Oncology Reviewed by: Yiorgos Apidianakis, University of Cyprus, Cyprus; Dakang Xu, Shanghai Jiao Tong University, China Edited by: Aniello Cerrato, Istituto per l’Endocrinologia e l’oncologia “Gaetano Salvatore, Consiglio Nazionale Delle Ricerche (CNR), Italy
ISSN:	2234-943X 2234-943X
DOI:	10.3389/fonc.2021.692592