MicroRNA-dependent regulation of transcription in lung cancer
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE43000 | GEO | 2013/04/15
SECONDARY ACCESSION(S): PRJNA184034
REPOSITORIES: GEO
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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)).
2013-04-15 | E-GEOD-43000 | biostudies-arrayexpress
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Project description:Adenosquamous lung tumors may result from cellular plasticity. We demonstrate lineage switching of KRAS+ lung adenocarcinomas (ADC) to squamous cell carcinoma (SCC) through deletion of Lkb1 (Stk11) in autochthonous and transplant models. Chromatin analysis reveals loss of H3K27me3 and gain of H3K27ac and H3K4me3 at squamous lineage genes, included Sox2, ΔNp63 and Ngfr. SCC lesions have higher levels of the H3K27 methyltransferase EZH2 than the ADC lesions, but there is a clear lack of the essential Polycomb Repressive Complex 2 (PRC2) subunit EED in the SCC lesions.
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Project description:Identifying biomarkers predictive for early esophageal cancer detection is critical considering the dismal survival rates. We investigated the involvement of microRNAs (miRNAs), their utility as biomarkers, and their association with survival in esophageal cancer, including Barrett’s associated and sporadic adenocarcinoma (ADC), and squamous cell carcinoma (SCC). MiRNA expression was measured in cancerous and adjacent non-cancerous tissue pairs collected from 76 US and Japanese patients enrolled in 3 distinct cohorts. In ADC patients, miR-21, miR-194, miR-293, and miR-223 expression was elevated, while miR-375 and miR-203 expression was reduced in cancerous tissue compared to non-cancerous tissue. Increased levels of miR-192 and miR-194 were observed in Barrett’s associated compared to sporadic ADC cancerous tissue. In SCC patients, miR-21, miR-181b, miR-155, and miR-146b expression was elevated while miR-375 and miR-203 levels were reduced in cancerous tissue compared to non-cancerous tissue. Significantly, elevated mir-21 expression in non-cancerous tissue was strongly associated with worse prognosis, independent of nodal status and age. Sample classification using miRNA expression yielded accuracies as high as 86% for diagnosis and 78% for Barrett’s esophagus status. Our results highlight that miRNAs are deregulated in esophageal carcinogenesis and Barrett’s esophagus, and that their expression is associated with survival in cancer patients. Sample classification using miRNA expression demonstrates their potential utility as biomarkers for esophageal carcinoma diagnosis. MiRNA microarray expression was measured using miRNA microarray chips version 3 (Ohio State University) in 44 SCC cases and 32 ADC cases, of which 18 were also diagnosed with Barrett’s esophagus.
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Project description:The objective is to establish robust transcriptional regulation differences between lung cancer (LC) and chronic obstructive pulmonary disease (COPD) by studying miRNA and concurrent transcriptional profiles
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Project description:Gene expression profiling comparing biological mechanisms for lymphatic metastases in lung adenocarcinoma and squamous cell carcinoma Two-condition comparison: primary invasive tumors (TN+), without lymph node metastasis (TN-), matched tumor cells in metastatic lymph nodes (MT) in ADC and SCC separately
2011-08-30 | E-GEOD-29827 | biostudies-arrayexpress
Project description:Background: The development of a more refined prognostic methodology for early non-small cell lung cancer (NSCLC) is an unmet clinical need. An accurate prognostic tool might help to select patients at early stages for adjuvant therapies. Results: A new integrated bioinformatics searching strategy, that combines gene copy number alterations and expression, together with clinical parameters was applied to derive two prognostic genomic signatures. The proposed methodology combines data from patients with and without clinical data with a priori information on the ability of a gene to be a prognostic marker. Two initial candidate sets of 513 and 150 genes for lung adenocarcinoma (ADC) and squamous cell carcinoma (SCC), respectively, were generated by identifying genes which have both: a) significant correlation between copy number and gene expression, and b) significant prognostic value at the gene expression level in external databases. From these candidates, two panels of 7 (ADC) and 5 (SCC) genes were further identified via semi-supervised learning. These panels, together with clinical data (stage, age and sex), were used to construct the ADC and SCC hazard scores combining clinical and genomic data. The signatures were validated in two independent datasets (n=73 for ADC, n=97 for SCC), confirming that the prognostic value of both clinical-genomic models is robust, statistically significant (P=0.008 for ADC and P=0.019 for SCC) and outperforms both the clinical models (P=0.060 for ADC and P=0.121 for SCC) and the genomic models applied separately (P=0.350 for ADC and P=0.269 for SCC). Conclusion: The present work provides a methodology to generate a robust signature using copy number data that can be potentially used to any cancer. Using it, we found new prognostic scores based on DNA s that, jointly with clinical information, are able to predict overall survival (OS) in patients with early-stage ADC and SCC.
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