Machine learning algorithm to construct cuproptosis- and immune-related prognosis prediction model for colon cancer.

Autor:	Huang YY; Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China.; Department of Clinical Medicine, The First Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China., Bao TY; Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China.; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China., Huang XQ; Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China.; Department of Clinical Medicine, The Sixth Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China., Lan QW; Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China.; Department of Medical Imageology, The Second Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China., Huang ZM; Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China.; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China., Chen YH; Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China.; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China., Hu ZD; Department of Laboratory Medicine, The Affiliated Hospital of Inner Mongolia Medical University, Hohhot 010010, Inner Mongolia Autonomous Region, China., Guo XG; Department of Clinical Laboratory Medicine, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China.; Department of Clinical Medicine, The Third Clinical School of Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China.; Guangdong Provincial Key Laboratory of Major Obstetric Diseases, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China.; Key Laboratory of Reproduction and Genetics of Guangdong Higher Education Institutes, The Third Affiliated Hospital of Guangzhou Medical University, Guangzhou 510150, Guangdong Province, China.; Guangzhou Key Laboratory for Clinical Rapid Diagnosis and Early Warning of Infectious Diseases, King Med School of Laboratory Medicine, Guangzhou Medical University, Guangzhou 511436, Guangdong Province, China. gysygxg@gmail.com.
Jazyk:	angličtina
Zdroj:	World journal of gastrointestinal oncology [World J Gastrointest Oncol] 2023 Mar 15; Vol. 15 (3), pp. 372-388.
DOI:	10.4251/wjgo.v15.i3.372
Abstrakt:	Background: Over the past few years, research into the pathogenesis of colon cancer has progressed rapidly, and cuproptosis is an emerging mode of cellular apoptosis. Exploring the relationship between colon cancer and cuproptosis benefits in identifying novel biomarkers and even improving the outcome of the disease. Aim: To look at the prognostic relationship between colon cancer and the genes associated with cuproptosis and the immune system in patients. The main purpose was to assess whether reasonable induction of these biomarkers reduces mortality among patients with colon cancers. Method: Data obtained from The Cancer Genome Atlas and Gene Expression Omnibus and the Genotype-Tissue Expression were used in differential analysis to explore differential expression genes associated with cuproptosis and immune activation. The least absolute shrinkage and selection operator and Cox regression algorithm was applied to build a cuproptosis- and immune-related combination model, and the model was utilized for principal component analysis and survival analysis to observe the survival and prognosis of the patients. A series of statistically meaningful transcriptional analysis results demonstrated an intrinsic relationship between cuproptosis and the micro-environment of colon cancer. Results: Once prognostic characteristics were obtained, the CDKN2A and DLAT genes related to cuproptosis were strongly linked to colon cancer: The first was a risk factor, whereas the second was a protective factor. The finding of the validation analysis showed that the comprehensive model associated with cuproptosis and immunity was statistically significant. Within the component expressions, the expressions of HSPA1A, CDKN2A, and UCN3 differed markedly. Transcription analysis primarily reflects the differential activation of related immune cells and pathways. Furthermore, genes linked to immune checkpoint inhibitors were expressed differently between the subgroups, which may reveal the mechanism of worse prognosis and the different sensitivities of chemotherapy. Conclusion: The prognosis of the high-risk group evaluated in the combined model was poorer, and cuproptosis was highly correlated with the prognosis of colon cancer. It is possible that we may be able to improve patients' prognosis by regulating the gene expression to intervene the risk score. Competing Interests: Conflict-of-interest statement: The authors report having no conflict of interest. (©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.)
Databáze:	MEDLINE
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