Gradient boosting reveals spatially diverse cholesterol gene signatures in colon cancer.

Autor:	Yang X; Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States., Chatterjee D; Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States., Couetil JL; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States., Liu Z; Department of Statistics, Purdue University, West Lafayette, IN, United States., Ardon VD; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States., Chen C; Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, United States., Zhang J; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States., Huang K; Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States.; Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, United States.; Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United States., Johnson TS; Department of Biostatistics and Health Data Science, Indiana University School of Medicine, Indianapolis, IN, United States.; Indiana University Melvin and Bren Simon Comprehensive Cancer Center, Indianapolis, IN, United States.; Indiana Biosciences Research Institute, Indianapolis, IN, United States.
Jazyk:	angličtina
Zdroj:	Frontiers in genetics [Front Genet] 2024 Nov 29; Vol. 15, pp. 1410353. Date of Electronic Publication: 2024 Nov 29 (Print Publication: 2024).
DOI:	10.3389/fgene.2024.1410353
Abstrakt:	Colon cancer (CC) is the second most common cause of cancer deaths and the fourth most prevalent cancer in the United States. Recently cholesterol metabolism has been identified as a potential therapeutic avenue due to its consistent association with tumor treatment effects and overall prognosis. We conducted differential gene analysis and KEGG pathway analysis on paired tumor and adjacent-normal samples from the TCGA Colon Adenocarcinoma project, identifying that bile secretion was the only significantly downregulated pathway. To evaluate the relationship between cholesterol metabolism and CC prognosis, we used the genes from this pathway in several statistical models like Cox proportional Hazard (CPH), Random Forest (RF), Lasso Regression (LR), and the eXtreme Gradient Boosting (XGBoost) to identify the genes which contributed highly to the predictive ability of all models, ADCY5, and SLC2A1. We demonstrate that using cholesterol metabolism genes with XGBoost models improves stratification of CC patients into low and high-risk groups compared with traditional CPH, RF and LR models. Spatial transcriptomics (ST) revealed that SLC2A1 (glucose transporter 1, GLUT1) colocalized with small blood vessels. ADCY5 localized to stromal regions in both the ST and protein immunohistochemistry. Interestingly, both these significant genes are expressed in tissues other than the tumor itself, highlighting the complex interplay between the tumor and microenvironment, and that druggable targets may be found in the ability to modify how "normal" tissue interacts with tumors. 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. The author(s) declared that they were an editorial board member of Frontiers, at the time of submission. This had no impact on the peer review process and the final decision. (Copyright © 2024 Yang, Chatterjee, Couetil, Liu, Ardon, Chen, Zhang, Huang and Johnson.)
Databáze:	MEDLINE
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