Project description:Non-small cell lung cancer (NSCLC) can be classified into the major subtypes adenocarcinoma (AC) and squamous cell carcinoma (SCC) subtypes. Although explicit molecular, histological and clinical characteristics have been reported for both subtypes, no specific therapy exists so far. However, the characterization of suitable molecular targets holds great promises to develop novel therapies in NSCLC. In the present study, global gene expression profiling of 58 human high grade NSCLC specimens revealed large transcriptomic differences between AC and SCC subtypes: More than 1.700 genes were found to be differentially expressed. Experiment Overall Design: The NSCLC patient collective was composed of the histological subtype adenocarcinoma (n=40) and squamous cell carcinoma (n=18). We subjected gene expression profiles of 40 AC and 18 SCC samples into further analysis. Unsupervised hierarchical clustering of all 58 NSCLC tumors using the 500 most variably expressed transcripts revealed two different clusters, which were strongly associated with the histological subtypes AC and SCC of NSCLC. Our result indicated that the major impact on global transcriptional changes was due to the NSCLC histology.
Project description:Non-small cell lung cancer (NSCLC) can be classified into the major subtypes adenocarcinoma (AC) and squamous cell carcinoma (SCC) subtypes. Although explicit molecular, histological and clinical characteristics have been reported for both subtypes, no specific therapy exists so far. However, the characterization of suitable molecular targets holds great promises to develop novel therapies in NSCLC. In the present study, global gene expression profiling of 58 human high grade NSCLC specimens revealed large transcriptomic differences between AC and SCC subtypes: More than 1.700 genes were found to be differentially expressed. Keywords: disease subtype analysis
Project description:We performed a pilot proteogenomic study to compare lung adenocarcinoma to lung squamous cell carcinoma using quantitative proteomics (6-plex TMT) combined with a customized Affymetrix GeneChip. Using MaxQuant software, we identified 51,001 unique peptides that mapped to 7,241 unique proteins and from these identified 6,373 genes with matching protein expression for further analysis. We found a minor correlation between gene expression and protein expression; both datasets were able to independently recapitulate known differences between the adenocarcinoma and squamous cell carcinoma subtypes. We found 565 proteins and 629 genes to be differentially expressed between adenocarcinoma and squamous cell carcinoma, with 113 of these consistently differentially expressed at both the gene and protein levels. We then compared our results to published adenocarcinoma versus squamous cell carcinoma proteomic data that we also processed with MaxQuant. We selected two proteins consistently overexpressed in squamous cell carcinoma in all studies, MCT1 (SLC16A1) and GLUT1 (SLC2A1), for further investigation. We found differential expression of these same proteins at the gene level in our study as well as in other public gene expression datasets. These findings combined with survival analysis of public datasets suggest that MCT1 and GLUT1 may be potential prognostic markers in adenocarcinoma and druggable targets in squamous cell carcinoma.
Project description:Affymetrix exon array data set (HuEx-1.0_st) derived from matched pairs of non-small cell lung cancer (NSCLC) and normal adjacent lung tissue (NAT). This data set includes both the adenocarcinoma (AdCa) as well as the squamous cell carcinoma (SCC) subtype of NSCLC.
Project description:Non-small cell lung cancer (NSCLC, n=22) and normal adjacent control biopsies (n=18) from patients with lung cancer were obtained for Affymetrix GeneChip analysis. NSCLC samples were grouped into squamous cell carcinoma (SCC, n=11) and adenocarcinoma (AC, n=11) samples.
Project description:Lung cancer is the leading cause of preventable death globally and is broadly classified into adenocarcinoma and squamous cell carcinoma depending upon cell type. In this study, we carried out mass spectrometry based quantitative proteomic analysis of lung adenocarcinoma and squamous cell carcinoma primary tissue by employing the isobaric tags for relative and absolute quantitation (iTRAQ) approach. Proteomic data was analyzed using SEQUEST search algorithm which resulted in identification of 25,998 peptides corresponding to 4,342 proteins of which 610 proteins were differentially expressed (≥ 2-fold) between adenocarcinoma and squamous cell carcinoma samples. These differentially expressed proteins were further classified by gene ontology for their localizations and biological processes. Pathway analysis of differentially expressed proteins revealed distinct alterations in networks and pathways in both adenocarcinoma and squamous cell carcinoma samples. In this study, we identified a subset of proteins that shows converse expression between lung adenocarcinoma and squamous cell carcinoma samples. Such proteins may serve as signature markers to distinguish between the two subtypes.
Project description:The objective is to establish robust transcriptional regulation differences between squamous cell carcinoma (SCC) and adenocarcinoma (ADC) by studying miRNA and concurrent transcriptional profiles. This series represents the miRNA profiles only (not mRNA). The related mRNA data is in Series GSE42998. The present study was performed in 44 tumour samples following surgical resection for clinical early stage NSCLC (20 lung adenocarcinoma and 24 squamous cell lung cancer). Mature human miRNA expression was detected and quantified using the TaqMan® Low Density Arrays (TLDA). The Human MicroRNA Card Set v2.0 array is a two card set containing a total of 384 TaqMan® MicroRNA Assays per card to enable accurate quantification of 667 human microRNAs, all catalogued in the miRBase database.Expression of target miRNAs was normalized in relation to the expression of RNU48. Cycle threshold (Ct) values were calculated using the SDS software v.2.3 using automatic baseline settings and a threshold of 0.2. Relative quantification of miRNA expression was calculated by the 2−ΔCt method (Applied Biosystems user bulletin no. 2 (P/N 4303859)).
Project description:Non-small-cell lung cancer (NSCLC), which is comprised mainly of adenocarcinoma and squamous cell carcinoma (SCC), is the cause of 80% of all lung cancer deaths in the US. NSCLC is also associated with a high rate of relapse following clinical treatment and therefore requires robust prognostic markers to better manage therapy options. The aim of this study was to identify miRNA expression profiles in squamous cell carcinoma (SSC) of the lung that would better predict prognosis.
Project description:The composition and remodelling of the extracellular matrix (ECM) are important factors in the development and progression of cancers, and the ECM is implicated in promoting tumour growth and restricting anti-tumour therapies through multiple mechanisms. The characterisation of differences in ECM composition between normal and diseased tissues may aid in identifying novel diagnostic markers, prognostic indicators and therapeutic targets for drug development. Using tissue from non-small cell lung cancer (NSCLC) patients undergoing curative intent surgery, we characterised quantitative tumour-specific ECM proteome signatures by mass spectrometry, identifying 161 matrisome proteins differentially regulated between tumour tissue and nearby non-malignant lung tissue. We defined a collagen hydroxylation functional protein network that is enriched in the lung tumour microenvironment. We validated two novel putative extracellular markers of NSCLC, the collagen cross-linking enzyme peroxidasin and a disintegrin and metalloproteinase with thrombospondin motifs 16 (ADAMTS16), for discrimination of malignant and non-malignant lung tissue. These proteins were up-regulated in lung tumour samples, and high PXDN and ADAMTS16 gene expression was associated with shorter survival of lung adenocarcinoma and squamous cell carcinoma patients, respectively. These data reveal tumour matrisome signatures in human NSCLC.