Theoretical and Natural Science
- The Open Access Proceedings Series for Conferences
Theoretical and Natural Science
Vol. 16, 04 December 2023
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A tumor specific Bayesian framework reveals novel molecular subtypes in colorectal cancer
* Author to whom correspondence should be addressed.
Abstract
We applied a tumor-specific Bayesian framework to investigate the drivers and signaling mechanisms behind various subtypes of Colorectal Cancer (CRC), a highly aggressive cancer known to have diverse origins. Our approach aims to identify the cancer drivers that contribute to the development of colorectal cancer (CRC) within individual tumors. By inferring the target differentially expressed genes (DEGs) associated with these drivers, we effectively group patients into distinct molecular subtypes. We employed the tumor-specific causal inference (TCI) model to establish causal associations between somatic genome alterations (SGAs) and differentially expressed genes (DEGs) inside each colorectal cancer (CRC) tumor. Through the process of generalization, we have successfully discovered three distinct mechanism-oriented subtypes of colorectal cancer (CRC) by examining the most statistically significant SGAs and their corresponding target DEGs throughout the CRC cohort. Notably, this subtyping approach stands independently from the previously reported transcriptomic-based molecular subtyping of CRC. Additionally, our analysis successfully grouped patients based on significant prognostic outcomes, outperforming the previously reported subtyping. This research provides valuable insights into understanding the underlying drivers and molecular complexities associated with different CRC subtypes.
Keywords
Bayesian Network, CRC Subtyping, Cancer Drivers, Survival Analysis
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Data Availability
The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.
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- Volume Title
- Proceedings of the 2nd International Conference on Modern Medicine and Global Health
- ISBN (Print)
- 978-1-83558-195-7
- ISBN (Online)
- 978-1-83558-196-4
- Published Date
- 04 December 2023
- Series
- Theoretical and Natural Science
- ISSN (Print)
- 2753-8818
- ISSN (Online)
- 2753-8826
- DOI
- 10.54254/2753-8818/16/20240529
- Copyright
- 04 December 2023
- Open Access
- This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited