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Modeling Reactive Species Metabolism in Colorectal Cancer for Identifying Metabolic Targets and Devising Therapeutics

Prerna Bhalla, Subasree Sridhar, Justin Kullu, Sriya Veerapaneni, View ORCID ProfileSwagatika Sahoo, View ORCID ProfileNirav Bhatt, View ORCID ProfileGK Suraishkumar
doi: https://doi.org/10.1101/2022.05.03.490417
Prerna Bhalla
1Department of Chemical Engineering, Indian Institute of Technology Madras, Chennai - 600036, India
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Subasree Sridhar
2Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Building - 1, Indian Institute of Technology Madras, Chennai - 600 036, India
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Justin Kullu
2Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Building - 1, Indian Institute of Technology Madras, Chennai - 600 036, India
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Sriya Veerapaneni
2Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Building - 1, Indian Institute of Technology Madras, Chennai - 600 036, India
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Swagatika Sahoo
3International Research Initiative, Global Engagement, Indian Institute of Technology - Madras, Chennai - 600 036, India
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Nirav Bhatt
2Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Building - 1, Indian Institute of Technology Madras, Chennai - 600 036, India
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GK Suraishkumar
2Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Building - 1, Indian Institute of Technology Madras, Chennai - 600 036, India
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  • For correspondence: gk@iitm.ac.in
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Abstract

Reactive species (RS) are known to play significant roles in cancer development as well as in treating or managing cancer. On the other hand, genome scale metabolic models are being used to understand cell metabolism in disease contexts including cancer, and also in planning strategies to handle diseases. Despite their crucial roles in cancers, the reactive species have not been adequately modeled in the genome scale metabolic models (GSMMs) when probing disease models for their metabolism or detection of drug targets. In this work, we have developed a module of reactive species reactions, which is scalable - it can be integrated with any human metabolic model as it is, or with any metabolic model with fine-tuning. When integrated with a cancer (colorectal cancer in this case) metabolic model, the RS module highlighted the deregulation occurring in important CRC pathways such as fatty acid metabolism, cholesterol metabolism, arachidonic acid and eicosanoid metabolism. We show that the RS module helps in better deciphering crucial metabolic targets for devising better therapeutics such as FDFT1, FADS2 and GUK1 by taking into account the effects mediated by reactive species during colorectal cancer progression. The results from this reactive species integrated CRC metabolic model reinforces ferroptosis as a potential target for colorectal cancer therapy.

Competing Interest Statement

The authors have declared no competing interest.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted May 04, 2022.
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Modeling Reactive Species Metabolism in Colorectal Cancer for Identifying Metabolic Targets and Devising Therapeutics
Prerna Bhalla, Subasree Sridhar, Justin Kullu, Sriya Veerapaneni, Swagatika Sahoo, Nirav Bhatt, GK Suraishkumar
bioRxiv 2022.05.03.490417; doi: https://doi.org/10.1101/2022.05.03.490417
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Modeling Reactive Species Metabolism in Colorectal Cancer for Identifying Metabolic Targets and Devising Therapeutics
Prerna Bhalla, Subasree Sridhar, Justin Kullu, Sriya Veerapaneni, Swagatika Sahoo, Nirav Bhatt, GK Suraishkumar
bioRxiv 2022.05.03.490417; doi: https://doi.org/10.1101/2022.05.03.490417

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