A novel prediction model of immune signatures for colon cancer based on machine learning

VernacularTitle:基于机器学习构建新型结肠癌免疫评分模型
Author: Xuemeng SUN ^{1
,

2
,

3} ; Tianzi YAN ; Liya SU ; Mingxing HOU ; Fangyuan LIU
Author Information

1. 内蒙古医科大学附属医院临床医学研究中心,呼和浩特 010050
2. 内蒙古自治区医学细胞生物学重点实验室,呼和浩特 010050
3. 内蒙古医科大学,呼和浩特 010050
Keywords: Immune-related genes; Colon cancer; Machine learning; Immune therapy; TCGA
From: Chinese Journal of Immunology 2024;40(11):2296-2303
CountryChina
Language:Chinese
Abstract: Objective:To construct A novel scoring model of immune signatures for colon cancer based on machine learning,which improve the survival prediction and immune therapy.Methods:Screening immune signatures from 1 301 immune-related genes(IRG)by the combined strategy of Lasso+bootstrap+multi Cox to calculate IRG scores of colon cancer patients from TCGA databases,and comprehensive the differences on function,prognostic status and immune therapy between high IRG scores group and IRG scores group.Results:Groups based on IRG scores were significantly different on the prognostic status of colon cancer patients,which were validated by other independent datasets.The IRG scores also could assess the effect of immune therapy of colon cancer.Conclusion:This study provides ideas for immune therapy and researches of colon cancer based on immune genes,and IRG scores can be used to assess the prognosis of colon cancer patients.