Correlation evaluation between cancer microenvironment related genes and prognosis based on intelligent medical internet of things

• Published in: Frontiers in genetics Vol. 14; p. 1132242
• Main Authors: Ren, Shoulei, Cao, Wenli, Ma, Jianzeng, Li, Hongchun, Xia, Yutao, Zhao, Jianwen
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 09.02.2023
• Subjects: biological; correlation evaluation; Genetics; internet of things technology; smart healthcare; tumor microenvironment; correlation evaluation; biological; smart healthcare; tumor microenvironment; internet of things technology
• ISSN: 1664-8021; 1664-8021
• DOI: 10.3389/fgene.2023.1132242

The study of tumor microenvironment plays an important role in the treatment of cancer patients. In this paper, intelligent medical Internet of Things technology was used to analyze cancer tumor microenvironment-related genes. Through experiments designed and analyzed cancer-related genes, this study concluded that in cervical cancer, patients with high expression of P16 gene had a shorter life cycle and a survival rate of 35%. In addition, through investigation and interview, it was found that patients with positive expression of P16 and Twist genes had a higher recurrence rate than patients with negative expression of both genes; high expression of FDFT1, AKR1C1, and ALOX12 in colon cancer is associated with short survival; high expressions of HMGCR and CARS1 is associated with longer survival; overexpression of NDUFA12, FD6, VEZT, GDF3, PDE5A, GALNTL6, OPMR1, and AOAH in thyroid cancer is associated with shortened survival; high expressions of NR2C1, FN1, IPCEF1, and ELMO1 is associated with prolonged survival. Among the genes associated with the prognosis of liver cancer, the genes associated with shorter survival period are AGO2, DCPS, IFIT5, LARP1, NCBP2, NUDT10, and NUDT16; the genes associated with longevity are EIF4E3, EIF4G3, METTL1, NCBP1, NSUN2, NUDT11, NUDT4, and WDR4. Depending on the prognostic role of genes in different cancers, they can influence patients to achieve the effect of reducing patients' symptoms. In the process of disease analysis of cancer patients, this paper uses bioinformation technology and Internet of things technology to promote the development of medical intelligence.