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肌層浸潤(rùn)性膀胱癌亞型的生物信息學(xué)分析

Bioinformatics analysis of the muscle-invasive bladder cancer subtypes

作者: 徐文彬  鄭衛(wèi)英  夏翃  華琳 
單位:<span style="font-family: 宋體;">首都醫(yī)科大學(xué)生物醫(yī)學(xué)工程學(xué)院(北京</span>100069<span style="font-family: 宋體;">)</span>
關(guān)鍵詞: 膀胱癌;分子亞型;差異表達(dá)基因;富集分析;蛋白質(zhì)互作網(wǎng)絡(luò) 
分類號(hào):R318.04
出版年·卷·期(頁(yè)碼):2018·37·1(51-56)
摘要:

目的 通過生物信息學(xué)分析研究?jī)煞N膀胱癌亞型(基底樣膀胱癌和管腔型膀胱癌)之間不同的分子調(diào)控機(jī)制和分子特性,為更準(zhǔn)確地區(qū)分膀胱癌亞型和探索潛在的治療靶點(diǎn)提供幫助.方法 利用穩(wěn)健的多芯片平均算法將由22個(gè)基底樣膀胱癌和132管腔型膀胱癌樣本組成的數(shù)據(jù)集進(jìn)行標(biāo)準(zhǔn)化,并選擇其中前1000個(gè)具有最高標(biāo)準(zhǔn)差的基因進(jìn)行兩種亞型的差異表達(dá)基因分析.將得到的差異表達(dá)基因進(jìn)行GO功能注釋和KEGG通路富集分析.此外,選擇前100個(gè)差異表達(dá)基因構(gòu)建蛋白質(zhì)互作網(wǎng)絡(luò).結(jié)果 得到基底樣和管腔型膀胱癌差異表達(dá)基因共742,其中基底樣亞型上調(diào)的基因405個(gè),下調(diào)的基因337個(gè).GO富集分析顯示差異表達(dá)基因顯著富集在細(xì)胞外區(qū)基質(zhì)、趨化性、炎癥等功能上,KEGG通路富集顯示差異表達(dá)基因顯著富集在細(xì)胞外基質(zhì)受體相互作用的通路上.構(gòu)建的蛋白質(zhì)互作網(wǎng)絡(luò)顯示重要的hub蛋白質(zhì)為L(zhǎng)NX1、MSN和PPARG.結(jié)論 本研究得到的基底樣和管腔型膀胱癌亞型分子機(jī)制的區(qū)別主要體現(xiàn)在細(xì)胞外區(qū)域的分子作用機(jī)制、細(xì)胞趨化性和炎癥反應(yīng)等,基因LNX1、MSN和PPARG為區(qū)別兩種膀胱癌亞型的特征基因.

Objective In order to improve the accuracy in distinguishing subtypes of bladder cancer and to explore its potential therapeutic targets we identify differences between two kinds of bladder cancer subtypes (basal-like and luminal) in molecular mechanism and molecular characteristics based on the bioinformatics analysis. Methods In this study, the RMA (robust multichip averaging) was applied to normalize the mRNA profile which included 22 samples from basal-like subtype and 132 from luminal subtype, and the differential expression analysis of genes with top 1000 highest standard deviation was performed. Then, the Gene Ontology and KEGG pathway enrichment analysis of differentially expressed genes was performed. In addition, the protein-protein interactions networks analysis for the top 100 most significant differentially expressed genes was performed. Results A total of 742 differentially expressed genes distinguishing basal-like and luminal subtypes were found, of which 405 were up-regulated and 337 genes were down-regulated in basal-like subtype. GO enrichment analysis showed that differentially expressed genes were significantly enriched in the extracellular matrix, chemotaxis and inflammatory response. KEGG pathway enrichment analysis showed that the differentially expressed genes were significantly enriched in the pathway of extracellular matrix receptor interaction. The hub proteins we founded in protein-protein interaction networks were LNX1, MSN and PPARG. Conclusions In this study, the mainly difference of molecular mechanism between basal-like and luminal subtypes are alteration in extracellular matrix region, cell chemotaxis and inflammatory response. Genes such as LNX1, MSN and PPARG were forecast to play important roles in the classification of bladder carcinoma subtypes.

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