Modeling the relationship between gene expression and mutational signature

作     者：Limin Jiang Hui Yu Yan Guo Limin Jiang;Hui Yu;Yan Guo

作者机构：Department of Internal MedicineComprehensive Cancer CenterUniversity of New Mexico AlbuquerqueNM 87109USA 

出 版 物：《Quantitative Biology》 (定量生物学（英文版）)

年 卷 期：2023年第11卷第1期

页      面：31-43页

核心收录：

学科分类：0710[理学-生物学] 07[理学] 08[工学] 09[农学] 071007[理学-遗传学] 0901[农学-作物学] 0836[工学-生物工程] 090102[农学-作物遗传育种] 

基　　金：Cancer Center Support Grant from the National Cancer Institute(P30CA118100) 

主　　题：mutational signature gene expression support vector machine random forest extreme gradient boost 

摘      要：Background:Mutational signatures computed from somatic mutations,allow an in-depth understanding of tumorigenesis and may illuminate early prevention *** studies have shown the regulation effects between somatic mutation and gene expression ***:We hypothesized that there are potential associations between mutational signature and gene *** capitalized upon RNA-seq data to model 49 established mutational signatures in 33 cancer *** accuracy and area under the curve were used as performance measures in five-fold ***:A total of 475 models using unconstrained genes,and 112 models using protein-coding genes were selected for future inference *** independent gene expression dataset on lung cancer smoking status was used for validation which achieved over 80%for both accuracy and area under the ***:These results demonstrate that the associations between gene expression and somatic mutations can translate into the associations between gene expression and mutational signatures.