Dataset Information

Identification of proteomic differences between squamous cell carcinoma of the lung and bronchial epithelium.

ABSTRACT: Proteins that exhibit different expression levels in normal and malignant lung cells are good candidate biomarkers to improve early diagnosis and intervention. We used a quantitative approach and compared the proteome of microdissected cells from normal human bronchial epithelium and squamous cell carcinoma tumors of histopathological grades G2 and G3. DIGE analysis and subsequent MS-based protein identification revealed that 32 non-redundant proteins were differentially regulated between the respective tissue types. These proteins are mainly involved in energy pathways, cell growth or maintenance mechanisms, protein metabolism, and the regulation of DNA and RNA metabolism. The expression of some of these proteins was analyzed by immunohistochemistry using tissue microarrays containing tissue specimen of 55 patients, including normal bronchial epithelium, squamous cell carcinomas, adenocarcinomas, and large cell carcinomas. The results of the immunohistochemical studies correlated with the proteome study data and revealed that particularly HSP47 and a group of cytokeratins (i.e. cytokeratins 6a, 16, and 17) are significantly co-regulated in squamous cell carcinoma. Furthermore cytokeratin 17 showed significantly higher abundance in G2 grade compared with G3 grade squamous cell carcinomas in both the gel-based and the immunohistochemical analysis. Therefore this protein might be used as a marker for stratification between different tumor grades.

SUBMITTER: Poschmann G

PROVIDER: S-EPMC2689775 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

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Identification of proteomic differences between squamous cell carcinoma of the lung and bronchial epithelium.

Poschmann Gereon G Sitek Barbara B Sipos Bence B Ulrich Anna A Wiese Sebastian S Stephan Christian C Warscheid Bettina B Klöppel Günter G Vander Borght Ann A Ramaekers Frans C S FC Meyer Helmut E HE Stühler Kai K

Molecular & cellular proteomics : MCP 20090127 5

Proteins that exhibit different expression levels in normal and malignant lung cells are good candidate biomarkers to improve early diagnosis and intervention. We used a quantitative approach and compared the proteome of microdissected cells from normal human bronchial epithelium and squamous cell carcinoma tumors of histopathological grades G2 and G3. DIGE analysis and subsequent MS-based protein identification revealed that 32 non-redundant proteins were differentially regulated between the re ...[more]

PMID: 19176476

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Project description:Lung cancer is the second most frequently diagnosed cancer type and responsible for the highest number of cancer deaths worldwide. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) are subtypes of non-small-cell lung cancer which has the highest frequency of lung cancer cases. We aimed to analyze genomic and transcriptomic variations including simple nucleotide variations (SNVs), copy number variations (CNVs) and differential expressed genes (DEGs) in order to find key genes and pathways for diagnostic and prognostic prediction for lung adenocarcinoma and lung squamous cell carcinoma. We performed a univariate Cox model and then lasso-regularized Cox model with leave-one-out cross-validation using The Cancer Genome Atlas (TCGA) gene expression data in tumor samples. We generated 35- and 33-gene signatures for prognostic risk prediction based on the overall survival time of the patients with LUAD and LUSC, respectively. When we clustered patients into high- and low-risk groups, the survival analysis showed highly significant results with high prediction power for both training and test datasets. Then, we characterized the differences including significant SNVs, CNVs, DEGs, active subnetworks, and the pathways. We described the results for the risk groups and cancer subtypes separately to identify specific genomic alterations between both high-risk groups and cancer subtypes. Both LUAD and LUSC high-risk groups have more downregulated immune pathways and upregulated metabolic pathways. On the other hand, low-risk groups have both up- and downregulated genes on cancer-related pathways. Both LUAD and LUSC have important gene alterations such as CDKN2A and CDKN2B deletions with different frequencies. SOX2 amplification occurs in LUSC and PSMD4 amplification in LUAD. EGFR and KRAS mutations are mutually exclusive in LUAD samples. EGFR, MGA, SMARCA4, ATM, RBM10, and KDM5C genes are mutated only in LUAD but not in LUSC. CDKN2A, PTEN, and HRAS genes are mutated only in LUSC samples. The low-risk groups of both LUAD and LUSC tend to have a higher number of SNVs, CNVs, and DEGs. The signature genes and altered genes have the potential to be used as diagnostic and prognostic biomarkers for personalized oncology.

Project description: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.

Dataset Information

Identification of proteomic differences between squamous cell carcinoma of the lung and bronchial epithelium.

Publications

Identification of proteomic differences between squamous cell carcinoma of the lung and bronchial epithelium.

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