Decoding Gastric Cancer: Machine Learning Insights Into The Significance Of COMMDs Family In Immunotherapy And Diagnosis

作者：Rong Wan, Lujuan Pan, Qi Wang, Guanliang Shen, RuoNan Guo, Yueqiu Qin, Xu‐Feng Huang, Ruo Wang, Xin Fan · 发表于：Journal of Cancer · 年份：2024 · DOI：10.7150/jca.94360 · 被引用次数：35 · 研究领域：Ferroptosis and cancer prognosis、Gastric Cancer Management and Outcomes、Helicobacter pylori-related gastroenterology studies

Copper, an indispensable trace element for the human body, serves not only as a crucial auxiliary factor in redox reactions within the organism but also as a significant constituent of numerous key metabolic enzymes. The COMMD family plays a vital role in regulating copper at both the cellular and systemic levels, particularly in the realm of tumor research, an area notably deficient in gastric cancer investigations. With the advancement of precision medical techniques, individualized and precise screening and treatment have become paramount considerations in the contemporary medical landscape for gastric cancer therapy. In light of this, we meticulously scrutinized existing transcriptomic datasets for gastric cancer, validating the expression levels and prognostic value of COMMD family genes. Simultaneously, employing the ssGSEA algorithm, we devised the COMMDs score. Enrichment analysis, gene mutations, and clinical features were incorporated into the assessment of this score. Furthermore, we contextualized the COMMDs score within the framework of the immune microenvironment, evaluating the relationship between the COMMDs family and immune factors as well as immune cells. The results suggest a correlation between the COMMDs score and various immune-related features. Based on this foundation, multiple machine learning approaches indicated Logistic Regression, with a remarkable ROC of 0.972, as the optimal diagnostic model. To accentuate the translational medical value of the...