Peng Shuxian, Li Xun, Liu Qin, Zhang Yingheng, Zou Liming, Gong Xiaoli, Wang Miaomiao, Ma Xiaodong
Research Center of Basic Integrative Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China.
Institute for Brain Research and Rehabilitation/Guangdong Key Laboratory of Mental Health and Cognitive Science/Center for Studies of Psychological Application, South China Normal University, Guangzhou 510631, China.
Nan Fang Yi Ke Da Xue Xue Bao. 2019 Jun 30;39(6):641-649. doi: 10.12122/j.issn.1673-4254.2019.06.03.
To analyze the differentially expressed genes (DEGs) between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) with bioinformatics analysis and search for potential biomarkers for clinical diagnosis of nonsmall cell lung cancer (NSCLC).
The gene expression profiling datasets of LUAD and LUSC were acquired. The transcriptome differences between LUAD and LUSC were identified using R language processing and t-test analysis. The differential expressions of the genes were shown by Venn diagram. The DEGs identified by GEO2R were analyzed with DAVID and Ingenuity Pathway Analysis (IPA) to identify the signaling pathways and biomarkers that could be used for differential diagnosis of LUAD and LUSC. The TCGA data and the biomarker expression data from clinical lung cancer samples were used to verify the differential expressions of the Osteoarthritis pathway and LXR/RXR between LUAD and LUSC. We further examined the differential expressions of miR-181 and its two target genes, and , in 23 clinical specimens of lung squamous cell carcinoma and the paired adjacent tissues.
GEO data analysis identified 851 DEGs (including 276 up-regulated and 575 down-regulated genes) in LUAD and 885 DEGs (including 406 up-regulated and 479 down-regulated genes) in LUSC. DAVID and IPA analysis revealed that leukocyte migration and inflammatory responses were more abundant in LUAD than in LUSC. Osteoarthritis pathway was inhibited in LUAD and activated in LUSC. IPA analysis showed that transcription factors (GATA4, RELA, YBX1, TP63 and MBD2), cytokines (WNT5A and IL1A) and microRNAs (miR-34a, miR-181b and miR-15a) differed significantly between LUAD and LUSC. miR-34a with IL-1A, miR-15a with YBX1, and miR-181b with WNT5A and MBD2 could serve as the paired microRNA and mRNA targets for differential diagnosis of NSCLC subtypes. Analysis of the clinical samples showed an increased expression of miR-181b-5p and the down-regulation of WNT5A, which could be used as molecular markers for the diagnosis of LUSC.
Through transcriptome analysis, we identified candidate genes, paired microRNAs and pathways for differentiating LUAD and LUSC, and they can provide novel differential diagnosis and therapeutic strategies for LUAD and LUSC.
通过生物信息学分析，分析肺腺癌（LUAD）和肺鳞癌（LUSC）之间的差异表达基因（DEG），并寻找非小细胞肺癌（NSCLC）临床诊断的潜在生物标志物。
获取LUAD和LUSC的基因表达谱数据集。使用R语言处理和t检验分析确定LUAD和LUSC之间的转录组差异。通过韦恩图展示基因的差异表达。对GEO2R鉴定出的DEG进行DAVID和 Ingenuity通路分析（IPA），以确定可用于LUAD和LUSC鉴别诊断的信号通路和生物标志物。利用TCGA数据和临床肺癌样本的生物标志物表达数据，验证LUAD和LUSC之间骨关节炎通路和LXR/RXR的差异表达。我们进一步检测了23例肺鳞癌临床标本及其配对的癌旁组织中miR-181及其两个靶基因的差异表达。
GEO数据分析在LUAD中鉴定出851个DEG（包括276个上调基因和575个下调基因），在LUSC中鉴定出885个DEG（包括406个上调基因和479个下调基因）。DAVID和IPA分析显示，LUAD中的白细胞迁移和炎症反应比LUSC中更丰富。骨关节炎通路在LUAD中受到抑制，在LUSC中被激活。IPA分析表明，转录因子（GATA4、RELA、YBX1、TP63和MBD2）、细胞因子（WNT5A和IL1A）和微小RNA（miR-34a、miR-181b和miR-15a）在LUAD和LUSC之间存在显著差异。miR-34a与IL-1A、miR-15a与YBX1、miR-181b与WNT5A和MBD2可作为NSCLC亚型鉴别诊断中配对的微小RNA和mRNA靶点。临床样本分析显示miR-181b-5p表达增加，WNT5A下调，可作为LUSC诊断的分子标志物。
通过转录组分析，我们鉴定出了区分LUAD和LUSC的候选基因、配对微小RNA和通路，它们可为LUAD和LUSC提供新的鉴别诊断和治疗策略。
