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...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2021-07-01
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| Series: | Frontiers in Oncology |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fonc.2021.692592/full |
| _version_ | 1818652705361494016 |
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| author | Mahnoor Naseer Gondal Rida Nasir Butt Osama Shiraz Shah Muhammad Umer Sultan Ghulam Mustafa Zainab Nasir Risham Hussain Huma Khawar Romena Qazi Muhammad Tariq Amir Faisal Safee Ullah Chaudhary |
| author_facet | Mahnoor Naseer Gondal Rida Nasir Butt Osama Shiraz Shah Muhammad Umer Sultan Ghulam Mustafa Zainab Nasir Risham Hussain Huma Khawar Romena Qazi Muhammad Tariq Amir Faisal Safee Ullah Chaudhary |
| author_sort | Mahnoor Naseer Gondal |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-17T02:26:15Z |
| format | Article |
| id | doaj.art-30686742519742048162c2446385e844 |
| institution | Directory Open Access Journal |
| issn | 2234-943X |
| language | English |
| last_indexed | 2024-12-17T02:26:15Z |
| publishDate | 2021-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Oncology |
| spelling | doaj.art-30686742519742048162c2446385e8442022-12-21T22:07:06ZengFrontiers Media S.A.Frontiers in Oncology2234-943X2021-07-011110.3389/fonc.2021.692592692592A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal CancerMahnoor Naseer Gondal0Rida Nasir Butt1Osama Shiraz Shah2Muhammad Umer Sultan3Ghulam Mustafa4Zainab Nasir5Risham Hussain6Huma Khawar7Romena Qazi8Muhammad Tariq9Amir Faisal10Safee Ullah Chaudhary11Biomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanBiomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanBiomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanBiomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanBiomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanBiomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanBiomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanBiomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanDepartment of Pathology, Shaukat Khanum Memorial Cancer Hospital and Research Centre, Lahore, PakistanEpigenetics Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanCancer Therapeutics Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanBiomedical Informatics Research Laboratory, Department of Biology, Lahore University of Management Sciences, Lahore, PakistanIn 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.https://www.frontiersin.org/articles/10.3389/fonc.2021.692592/fullpersonalized in silico cancer modelsBoolean network modelscancer systems biologypreclinical in silico drug screeningcombinatorial therapeutics |
| spellingShingle | Mahnoor Naseer Gondal Rida Nasir Butt Osama Shiraz Shah Muhammad Umer Sultan Ghulam Mustafa Zainab Nasir Risham Hussain Huma Khawar Romena Qazi Muhammad Tariq Amir Faisal Safee Ullah Chaudhary A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer Frontiers in Oncology personalized in silico cancer models Boolean network models cancer systems biology preclinical in silico drug screening combinatorial therapeutics |
| title | A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer |
| title_full | A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer |
| title_fullStr | A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer |
| title_full_unstemmed | A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer |
| title_short | A Personalized Therapeutics Approach Using an In Silico Drosophila Patient Model Reveals Optimal Chemo- and Targeted Therapy Combinations for Colorectal Cancer |
| title_sort | personalized therapeutics approach using an in silico drosophila patient model reveals optimal chemo and targeted therapy combinations for colorectal cancer |
| topic | personalized in silico cancer models Boolean network models cancer systems biology preclinical in silico drug screening combinatorial therapeutics |
| url | https://www.frontiersin.org/articles/10.3389/fonc.2021.692592/full |
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