药物数据库
药物重新定位
生物
内海
结直肠癌
毒理基因组学
癌症研究
生物信息学
癌症
医学
计算生物学
基因
基因表达
药品
受体
药理学
遗传学
旁分泌信号
作者
Leili Rejali,Ehsan Nazemalhosseini‐Mojarad,Laura Valle,Mazaher Maghsoudloo,Hamid Asadzadeh Aghdaei,Hadis Mohammadpoor,Mohammad Reza Zali,Binazir Khanabadi,Maliheh Entezari,Kiavash Hushmandi,Afshin Taheriazam,Mehrdad Hashemi
标识
DOI:10.1016/j.envres.2023.117117
摘要
Colorectal cancer (CRC) is one of the most malignant tumors and in which various efforts for screening is inconclusive.The intracrine FGF panel, the non-tyrosine kinase receptors (NTKR) FGFs and affiliated antisenses play a pivotal role in FGF signaling.The expression levels of coding and non-coding intracrine FGFs were assessed in CRC donors.Also, substantial costs and slow pace of drug discovery give high attraction to repurpose of previously discovered drugs to new opportunities.The aim of present study was to evaluate the potential role of the coding and non-coding intracrine FGFs as a new biomarkers for CRC cases and defining drug repurposing to alleviate FGF down regulation.RNA-seq data of colon adenocarcinomas (COAD) was downloaded using TCGA biolinks package in R.The DrugBank database (https://go.drugbank.com/) was used to extract interactions between drugs and candidate genes. A total of 200 CRC patients with detailed criteria were enrolled.RNAs were extracted with TRIzol-based protocol and amplified via LightCycler® instrument.FGF11 and FGF13 proteins validation was performed by used of immunohistochemistry technique in tumor and non-tumoral samples.Pearson's correlation analysis and ROC curve plotted by Prism 8.0 software.RNA-seq data from TCGA was analyzed by normalizing with edgeR.Differentially expressed gene (DEG) analysis was generated. WCC algorithm extracted the most significant genes with a total of 47 genes. Expression elevation of iFGF antisenses (12AS,13As,14AS) compared with the normal colon tissue were observed (P = 0.0003,P = 0.042,P = 0.026, respectively). Moreover,a significant decrease in expression of the corresponding sense iFGF genes was detected (P < 0.0001).Plotted receiver operating characteristic (ROC) curves for iFGF components' expression showed an area of over 0.70 (FGF11-13: 0.71% and FGF12-14: 0.78%, P < 0.001) for sense mRNA expression, with the highest sensitivity for FGF12 (92.8%) and lowest for FGF11 (61.41%).The artificial intelligence (AI) revealed the valproic acid as a repurposing drug to relief the down regulation of FGF12 and 13 in CRC patients.Intracrine FGFs panel was down regulated versus up regulation of dependent antisenses. Thus, developing novel biomarkers based on iFGF can be considered as a promising strategy for CRC screening.In advanced, valporic acid detected by AI as a repurposing drug which may be applied in clinical trials for CRC treatment.
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