Machine Learning Identification of TSPAN7 as a Key Target Linking Type 2 Diabetes Mellitus and Colorectal Cancer DOI Creative Commons
Feng Yu,

Sung-Woo Yang,

Yan Dong

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Дек. 19, 2024

Abstract Background Type 2 Diabetes Mellitus (T2DM) and Colorectal Cancer (CRC) are significant global public health challenges with a notable epidemiological association. This study aims to explore the molecular mechanism behind this Methods Weighted Gene Co-expression Network Analysis (WGCNA) differential expression gene (DEG) analysis were conducted identify shared genes between T2DM CRC. Machine learning algorithms, including LASSO, Random Forest, Support Vector (SVM), employed hub genes. IOBR clusterProfiler packages used for immunoinfiltration assessment enrichment analysis, respectively. Results We identified 27 CRC, TSPAN7 emerging as key linking two conditions. was significantly lower in disease groups compared control across multiple cohorts, demonstrating excellent diagnostic accuracy. Enrichment revealed involvement of these various metabolic activities pathways, sulfur metabolism, selenium renin secretion, pantothenate CoA biosynthesis, TRP channel regulation, efferocytosis. Conclusion provides new insights into mechanisms underlying association CRC by identifying target. The findings offer theoretical evidence developing markers therapeutic strategies diseases.

Язык: Английский

Food-Derived Micronutrients as Alleviators of Age-Related Dysfunction: A Dive into Their Effects and Cellular Mechanisms DOI Creative Commons
Yasser Fakri Mustafa,

Ayman Faris Faisal,

Marwa Mohammed Alshaher

и другие.

Indian Journal of Clinical Biochemistry, Год журнала: 2025, Номер unknown

Опубликована: Янв. 13, 2025

Язык: Английский

Процитировано

3
Research progress on selenium system in cancer therapy: Focus on interface modifications and improvement of interactions DOI
Hui He,

Dingding Huang,

Peng Xie

и другие.

Surfaces and Interfaces, Год журнала: 2024, Номер unknown, С. 105642 - 105642

Опубликована: Дек. 1, 2024

Язык: Английский

Процитировано

2
Machine Learning Identification of TSPAN7 as a Key Target Linking Type 2 Diabetes Mellitus and Colorectal Cancer DOI Creative Commons
Feng Yu,

Sung-Woo Yang,

Yan Dong

и другие.

Research Square (Research Square), Год журнала: 2024, Номер unknown

Опубликована: Дек. 19, 2024

Abstract Background Type 2 Diabetes Mellitus (T2DM) and Colorectal Cancer (CRC) are significant global public health challenges with a notable epidemiological association. This study aims to explore the molecular mechanism behind this Methods Weighted Gene Co-expression Network Analysis (WGCNA) differential expression gene (DEG) analysis were conducted identify shared genes between T2DM CRC. Machine learning algorithms, including LASSO, Random Forest, Support Vector (SVM), employed hub genes. IOBR clusterProfiler packages used for immunoinfiltration assessment enrichment analysis, respectively. Results We identified 27 CRC, TSPAN7 emerging as key linking two conditions. was significantly lower in disease groups compared control across multiple cohorts, demonstrating excellent diagnostic accuracy. Enrichment revealed involvement of these various metabolic activities pathways, sulfur metabolism, selenium renin secretion, pantothenate CoA biosynthesis, TRP channel regulation, efferocytosis. Conclusion provides new insights into mechanisms underlying association CRC by identifying target. The findings offer theoretical evidence developing markers therapeutic strategies diseases.

Язык: Английский

Процитировано

0