文献类型：期刊文献

英文题名：Identification of Npas4 as a biomarker for CICI by transcriptomics combined with bioinformatics and machine learning approaches

作者：He, Zhenyu[1,2];Ma, Huanhuan[1,2];Zhang, Yu[1,2];Chen, Liping[1,2];Pang, Yueling[1,2];Ding, Xiaoshan[1,2];Wang, Yanan[1,2];Liu, Yongqi[1,2];Li, Ling[1,2];Li, Jiawei[1,2,3]

第一作者：He, Zhenyu

通信作者：Liu, YQ[1];Li, L[1];Li, JW[1]

机构：[1]Gansu Univ Chinese Med, Gansu Univ, Key Lab Mol Med & Chinese Med Prevent & Treatment, Lanzhou, Peoples R China;[2]Gansu Univ Chinese Med, Key Lab Dunhuang Med & Transformat, Minist Educ Peoples Republ China, Lanzhou, Peoples R China;[3]Gansu Univ Chinese Med, Sci Res & Expt Ctr, Lanzhou, Peoples R China

第一机构：甘肃中医药大学

通信机构：[1]corresponding author), Gansu Univ Chinese Med, Sch Basic Med Sci, Lanzhou 730050, Peoples R China.|[107351d2d02a88e1f325f]甘肃中医药大学基础医学院（敦煌医学研究所）;[10735]甘肃中医药大学;

年份：2025

卷号：391

外文期刊名：EXPERIMENTAL NEUROLOGY

收录：;Scopus(收录号：2-s2.0-105005260802);WOS:【SCI-EXPANDED(收录号:WOS:001497817600001)】；

基金：This study was supported by the National Natural Science Foundation of China (No. 82160896/82205318) ; Research Project of Gansu Provincial Administration of Traditional Chinese Medicine (GZKP-2022-38) ; Gansu University of Chinese Medicine 2024 College Students' Innovation and Entrepreneurship Training Program Project (2023-14/19) .

语种：英文

外文关键词：CICI; LASSO; SVM-REF; RF; Npas4; Molecular structure; Biomarker

摘要：Chemotherapy is one of the most successful strategies for treating cancer. Unfortunately, up to 70 % of cancer survivors develop cognitive impairment during or after chemotherapy, which severely affects their quality of life. We first established a mouse model of CICI and combined bioinformatics, machine learning, and transcriptome sequencing to screen diagnostic genes associated with CICI. Relevant DEGs were screened by differential analysis, and potential biological functions of DEGs were explored by GO and KEGG analysis. WGCNA analysis was then used to find the most relevant modules for CICI. The diagnostic gene Npas4 was screened by combining the three machine learning methods; its diagnostic value was proved by ROC analysis, GSEA analyzed its potential biological function, and then we preliminarily explored the chemicals associated with Npas4. Our study found that Npas4 can be used as an early diagnostic gene for CICI, which provides a theoretical basis for further research.