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

التفاصيل البيبلوغرافية
العنوان: A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer.
المؤلفون: Gondal MN; Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Butt RN; Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Shah OS; Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Sultan MU; Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Mustafa G; Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Nasir Z; Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Hussain R; Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Khawar H; Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Qazi R; Department of Pathology, Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, Pakistan., Tariq M; Epigenetics Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Faisal A; Cancer Therapeutics Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan., Chaudhary SU; Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, Pakistan.
المصدر: Frontiers in oncology [Front Oncol] 2021 Jul 16; Vol. 11, pp. 692592. Date of Electronic Publication: 2021 Jul 16 (Print Publication: 2021).
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Frontiers Research Foundation] Country of Publication: Switzerland NLM ID: 101568867 Publication Model: eCollection Cited Medium: Print ISSN: 2234-943X (Print) Linking ISSN: 2234943X NLM ISO Abbreviation: Front Oncol Subsets: PubMed not MEDLINE
أسماء مطبوعة: Original Publication: [Lausanne : Frontiers Research Foundation]
مستخلص: 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.
Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
(Copyright © 2021 Gondal, Butt, Shah, Sultan, Mustafa, Nasir, Hussain, Khawar, Qazi, Tariq, Faisal and Chaudhary.)
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فهرسة مساهمة: Keywords: Boolean network models; cancer systems biology; combinatorial therapeutics; personalized in silico cancer models; preclinical in silico drug screening
تواريخ الأحداث: Date Created: 20210802 Latest Revision: 20210803
رمز التحديث: 20221213
مُعرف محوري في PubMed: PMC8323493
DOI: 10.3389/fonc.2021.692592
PMID: 34336681
قاعدة البيانات: MEDLINE
الوصف
تدمد:2234-943X
DOI:10.3389/fonc.2021.692592