[Identification of differentially expressed genes between lung adenocarcinoma and squamous cell carcinoma using transcriber signature analysis].
ABSTRACT: OBJECTIVE: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). METHODS: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, WNT5A and MBD2, in 23 clinical specimens of lung squamous cell carcinoma and the paired adjacent tissues. RESULTS: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. CONCLUSIONS: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.
Project description:The present study aimed to explore gene and microRNA (miRNA) expression differences between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). Differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified by analyzing mRNA and miRNA expression data in normal and cancerous lung tissues that were obtained from The Cancer Genome Atlas database. A total of 778 DEGs and 7 DEMs were identified. Altered gene functions and signaling pathways were investigated using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, which revealed that DEGs were significantly enriched in extracellular matrix organization, cell differentiation, negative regulation of toll signaling pathway, and several other terms and pathways. Transcription factor (TF)‑miRNA‑gene networks in LUAD and LUSC were predicted using the TargetScan, Miranda, and TRANSFAC databases, which revealed the regulatory links among the TFs, DEMs, and DEGs. The central TFs, i.e., the TFs in the middle of the TF‑miRNA‑gene network, of LUAD and LUSC were similar. Although LUAD and LUSC shared similar miRNAs in the predicted networks, miR‑29b‑3p was demonstrated to be upregulated only in LUAD, whereas miR‑1, miR‑105‑5p, and miR‑193b‑5p were altered in LUSC. These findings may improve our understanding of the different molecular mechanisms in non‑small cell lung cancers and may promote new and accurate strategies for prevention, diagnosis, and treatment.
Project description:Lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD) are the two major subtypes of lung cancer, with LUSC exhibits faster progression rate than LUAD. To investigate the roles of immune-response related genes (IRGs) in lung cancer progression, we used LUAD and LUSC samples at different cancer progression stages, and identified that the expression profiles of IRGs could serve as a better classification marker for cancerous tissues of both LUAD and LUSC. We found that the expression changes of IRGs were different between LUAD and LUSC. Cell cycle promoting genes, including KIFs and proteasomes, showed faster up-regulation in LUSC, whereas immune response promoting genes, including MHC molecules and chemokines, were more rapidly repressed in LUSC. Comparative pathway analysis revealed that members of the Toll-like receptor and T cell receptor signaling pathways exhibited diverged expression changes between LUAD and LUSC, especially at the early cancer stages. Our results revealed the difference of LUAD and LUSC from the immune response point of view, and provided new clues for the differential treatment of LUAD and LUSC.
Project description:BACKGROUND:Micro(mi)RNAs, potent gene expression regulators associated with tumorigenesis, are stable, abundant circulating molecules, and detectable in plasma. Thus, miRNAs could potentially be useful in early lung cancer detection. We aimed to identify circulating miRNA signatures in plasma from patients with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), and to verify whether miRNAs regulate lung oncogenesis pathways. METHODS:RNA isolated from 139 plasma samples (40 LUAD, 38 LUSC; 61 healthy/non-diseased individuals) were divided into discovery (38 patients; 21 controls for expression quantification using an 800-miRNA panel; Nanostring nCounter®) and validation (40 patients; 40 controls; TaqMan® RT-qPCR) cohorts. Elastic net, Maximizing-R-Square Analysis (MARSA), and C-Statistics were applied for miRNA signature identification. RESULTS:When compared to healthy individuals, 580 of 606 deregulated miRNAs in LUAD and 221 of 226 deregulated miRNAs in LUSC had significantly increased levels. Among the 10 most significantly overexpressed miRNAs, 6 were common to patients with LUAD and LUSC. Further analysis identified three signatures composed of 12 miRNAs. Signatures included miRNAs commonly overexpressed in patient plasma. Enriched pathways included target genes modulated by three miRNAs in the C-Statistics signature: miR-16-5p, miR-92a-3p, and miR-451a. CONCLUSIONS:The 3-miRNA signature (miR-16-5p, miR-92a-3p, miR-451a) had high specificity (100%) and sensitivity (84%) to predict cancer (LUAD and LUSC). These miRNAs are predicted to modulate genes and pathways with known roles in lung tumorigenesis, including EGFR, K-RAS, and PI3K/AKT signaling, suggesting that the 3-miRNA signature is biologically relevant in adenocarcinoma and squamous cell carcinoma of the lung.
Project description:Understanding the different genetic landscape between lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) is important for understanding the underlying molecular mechanism, which may facilitate the development of effective and precise treatments. Although previous studies have identified a number of differentially expressed genes (DEGs) responsible for lung cancer, it is unknown which of these genes are causal. The present study integrated DNA methylation, RNA sequencing, clinical characteristics and survival outcomes of patients with LUAD and LUSC from The Cancer Genome Atlas. DEGs were first identified using edgeR by comparing tumor and normal tissue, and differentially methylated probes (DMPs) were assessed using ChAMP. Candidate genes for further time-to-event instrumental variable analysis were selected as the intersecting genes between DEGs and the genes including DMP CpG sites within the transcription start site (TSS1500), with DMPs in TSS1500 region being the instrumental variables. Extensive sensitivity analyses were conducted to assess the robustness of the results. The present study identified 906 DEGs for LUAD, among which 538 also had DMPs in the TSS1500 region. In addition, 1,543 DEGs were identified for LUSC, among which 1,053 also had DMPs in the TSS1500 region. Time-to-event instrumental variable analysis detected eight potential causal genes for LUAD survival, including aryl hydrocarbon receptor nuclear translocator like 2, semaphorin 3G, serum deprivation-response protein, chloride intracellular channel protein 5, LIM zinc finger domain containing 2, epithelial membrane protein 2, carbonic anhydrase 7 and LOC116437. The results also identified that phosphatidylinositol-3,4,5-trisphosphate-dependent Rac exchange factor 2 may be a potential causal gene for LUSC. Therefore, the results of the present study suggested that there was molecular heterogeneity between these two lung cancer subtypes. Such analysis framework can be extended to other cancer genomics research.
Project description:Background:Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are the leading major histological phenotypes of all non-small cell lung cancer (NSCLC). In this study, the candidate genes and the potential tumorigenesis distinguishing between LUAD and LUSC were analyzed. Methods:The present study investigated two microarray datasets (GSE28571 and GSE10245) downloaded from the Gene Expression Omnibus (GEO) database. A protein-protein interaction (PPI) network was applied to screen out the candidate genes. In addition, differently expressed genes (DEGs) between lung adenocarcinoma and lung squamous cell carcinoma of the two datasets were functionally analyzed by Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. R 4.0.2 was used to perform Kaplan-Meier analysis of DSG3 (desmoglein 3) and KRT14 (keratin 14) by analyzing the expression and clinical data from The Cancer Genome Atlas (TCGA) database. Results:The results revealed that 47 DEGs of the two datasets were ascertained in our study. It was found that the DEGs were mainly involved in pathways related to p63 transcription factor network and validated transcriptional factor targeting TAp63, etc. Based on the analysis, we finally identified DSG3 and KRT14 as potential biomarkers for distinguishing between LUAD and LUSC. These results suggested that DSG3 and KRT14 could have the potential to play an important role in NSCLC patients, as diagnostic markers. At the same time, DSG3 or KRT14 indicated a worse prognosis in LUSC patients, which were associated with pathways relevant to the TRAIL signaling pathway and TNF receptor signaling pathway according to bioinformatic analysis. Conclusion:The DSG3 and KRT14 have the potential to be used as diagnostic markers, which presented here may facilitate improvements in distinguishing between LUAD and LUSC in advanced NSCLC patients.
Project description:Introduction: Accumulating evidence showed that a large number of microRNAs (miRNAs) are abnormally expressed in lung cancer tissues and play critical roles in cancer development and progression. The aim of this study is to identify the differentially expressed miRNAs (DEMs) between non-small cell lung cancer (NSCLC) and normal lung tissues, and evaluate the prognostic value and potential target gene functional enrichment of the DEMs. Materials and Methods: We first downloaded the high-throughput miRNA data from The Cancer Genome Atlas Project (TCGA) database, and subsequently analyzed the data using bioinformatics analysis including limma package in R, Kaplan-Meier curve and Log-rank method, and several online analysis tools. Results: A total of 125 DEMs and 138 DEMs were respectively identified in lung adenocarcinoma (LUAD) tissues and lung squamous cell carcinoma (LUSC) tissues compared with their matched normal tissues. Moreover, we found that the prognostic function of the eight miRNAs (miR-375, miR-148a, miR-29b-1 and miR-584 for LUAD; miR-4746, miR-326, miR-93 and miR-671 for LUSC). Furthermore, the two four-miRNA signatures were constructed and found to be an independent prognostic factor for LUAD and LUSC patients, respectively. Additionally, our results indicated that the target genes of eight miRNAs may be involved in various pathways related to NSCLC, including PI3K-Akt, TGF-beta, FoxO, Ras, GPI-anchor biosynthesis and metabolic, Rap1, HIF-1 and proteasome. Conclusion: Overall, eight miRNAs were closely correlated with survival of NSCLC patients, and the constructed two four-miRNA signatures could be respectively used as prognostic markers in LUAD and LUSC patients.
Project description:Purpose: This study aimed to comprehensively investigate the differential expression and prognostic indicators of the tripartite motif-containing (TRIM) gene family in non-small cell lung cancer (NSCLC). Methods: The Cancer Genome Atlas (TCGA) Research Network and three datasets from Gene Expression Omnibus (GEO) database were used to assess TRIM gene family expression patterns in NSCLC. Quantitative real-time PCR and immunohistochemistry (IHC) were conducted to confirm differentially expressed genes (DEGs). Kaplan-Meier survival analysis and univariate Cox regression analysis were carried out to analyze the association between TRIM gene expression and NSCLC prognoses. Gene set enrichment analysis (GSEA) was carried on for the predict the biological processes. Results: Of the 78 TRIM family members measured, TRIM15 was selected due to the DEGs and the prognostic value regarding NSCLC. In lung squamous cell carcinoma (LUSC), the Log2 fold change (Log2FC) of TRIM15 was 5.16 (p= 0.00575), whereas in lung adenocarcinoma (LUAD), it was 6.37 (p =6.78E-07). TRIM15 upregulation was related to poor prognoses in both LUSC (HR 1.353; 95%CI 1.023-1.789; p =0.034) and LUAD (HR 1.560; 95%CI 1.159-2.101; p =0.003). Using immunohistochemistry, TRIM15 expression was significantly higher in NSCLC tissues compared with that of matched normal tissues (p =0.0009), and similar findings were generated with tissue microarray analysis (p<0.0001). Conclusion: TRIM15 could act as a diagnostic predictor or therapeutic target for lung cancer treatments.
Project description:The main non-small-cell lung cancer (NSCLC) histopathological subtypes are lung adenocarcinomas (LUAD) and lung squamous cell carcinomas (LUSC). To identify candidate progression determinants of NSCLC subtypes, we explored the transcriptomic signatures of LUAD versus LUSC. We then investigated the prognostic impact of the identified tumor-associated determinants. This was done utilizing DNA microarray data from 2,437 NSCLC patients. An independent analysis of a case series of 994 NSCLC was conducted by next-generation sequencing, together with gene expression profiling from GEO (https://www.ncbi.nlm.nih.gov/geo/). This work led us to identify 69 distinct tumor prognostic determinants, which impact on LUAD or LUSC clinical outcome. These included key drivers of tumor growth and cell cycle, transcription factors and metabolic determinants. Such disease determinants appeared vastly different in LUAD versus LUSC, and often had opposite impact on clinical outcome. These findings indicate that distinct tumor progression pathways are at work in the two NSCLC subtypes. Notably, most prognostic determinants would go inappropriately assessed or even undetected when globally investigating unselected NSCLC. Hence, differential consideration for NSCLC subtypes should be taken into account in current clinical evaluation procedures for lung cancer.
Project description:Long non-coding RNAs (lncRNAs) have been implicated in pathogenesis of various cancers, including lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). We used cBioPortal to analyze lncRNA alteration frequencies and their ability to predict overall survival (OS) using 504 LUSC and 522 LUAD samples from The Cancer Genome Atlas (TCGA) database. In LUSC, 624 lncRNAs had alteration rates > 1% and 64 > 10%. In LUAD 625 lncRNAs had alteration rates > 1% and 36 > 10%. Among those, 620 lncRNAs had alteration frequencies > 1% in both LUSC and LUAD, while 22 were LUSC-specific and 23 were LUAD-specific. Twenty lncRNAs had alteration frequencies > 10% in both LUSC and LUAD, while 44 were LUSC-specific and 16 were LUAD specific. Genome ontology and pathway analyses produced similar results for LUSC and LUAD. Two lncRNAs (IGF2BP2-AS1 and DGCR5) correlated with better OS in LUSC, and three (MIR31HG, CDKN2A-AS1 and LINC01600) predicted poor OS in LUAD. Chip-seq and luciferase reporter assays identified potential IGF2BP2-AS1, DGCR5 and LINC01600 promoters and enhancers. This study presented lncRNA landscapes and revealed differentially expressed, highly altered lncRNAs in LUSC and LUAD. LncRNAs that act as oncogenes and lncRNA-regulating transcription factors provide novel targets for anti-lung cancer therapeutics.
Project description:Different subtypes of non-small cell lung cancer (NSCLC) have distinct sites of origin, histologies, genetic and epigenetic changes. In this study, we explored the mechanisms of ECT2 dysregulation and compared its prognostic value in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). In addition, we also investigated the enrichment of ECT2 co-expressed genes in KEGG pathways in LUAD and LUSC. Bioinformatic analysis was performed based on data from the Cancer Genome Atlas (TCGA)-LUAD and TCGA-LUSC. Results showed that ECT2 expression was significantly upregulated in both LUAD and LUSC compared with normal lung tissues. ECT2 expression was considerably higher in LUSC than in LUAD. The level of ECT2 DNA methylation was significantly lower in LUSC than in LUAD. ECT2 mutation was observed in 5% of LUAD and in 51% of LUSC cases. Amplification was the predominant alteration. LUAD patients with ECT2 amplification had significantly worse disease-free survival (p = 0.022). High ECT2 expression was associated with unfavorable overall survival (OS) (p<0.0001) and recurrence-free survival (RFS) (p = 0.001) in LUAD patients. Nevertheless, these associations were not observed in patients with LUSC. The following univariate and multivariate analysis showed that the high ECT2 expression was an independent prognostic factor for poor OS (HR: 2.039, 95%CI: 1.457-2.852, p<0.001) and RFS (HR: 1.715, 95%CI: 1.210-2.432, p = 0.002) in LUAD patients, but not in LUSC patients. Among 518 genes co-expressed with ECT2 in LUAD and 386 genes co-expressed with ECT2 in LUSC, there were only 98 genes in the overlapping cluster. Some of the genes related KEGG pathways in LUAD were not observed in LUSC. These differences might help to explain the different prognostic value of ECT2 in LUAD and LUSC, which are also worthy of further studies.