Computational Biology and ChemistryCancer BiologyPeer-reviewed journal article
Targeting Colorectal Cancer Liver Metastasis Through Repurposing Metabolic and Immune Inhibitors : A Theoretical Study
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Abstract
Liver metastasis from colorectal cancer is a major cause of death in patients with advanced colorectal cancer (CRC) and remains a difficult challenge in oncology. Inspite of commnedable developments in medical inventions, the complexity and poor prognosis of metastatic stage, alliterative strategies are required to address Colorectal cancer liver metastasis (CRLM). This paper presents a computational study on drug repurposing for CRLM using a Boolean Network model. We comprehensively analyze CRLM signaling pathways such as WNT, PI3K/AKT/mTOR, MAPK, Hedgehog, TGF-{beta}, NF-kB, NOTCH and HGF and target them with metabolic and immune inhibitors. This study utilizes a computational analysis to evaluate single and multi-agent treatments across scenarios involving single and multiple genetic mutations. Our findings highlights the efficacy of metabolic inhibitors such as Simvastatin, Metformin, and predict compatible partner drugs to enhance their effiacy. Additionaly, we predict possible improvements for CRLM treatment using an immunotherapy drug like Pembrolizumab. Overall, this paper provides new insights into drug repurposing to improve CRLM treatment outcomes.
- organism: human
- assay: bulk RNA-seq
- research focus: drug response / drug discovery
- research focus: gene regulatory network inference
- approach: deep learning
- approach: statistical model
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