Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Genomic landscape affected by allelic imbalance in the cancerization filed of normal appearing airway

ABSTRACT: Normal appearing airway samples from non-small cell lung (NSCLC) cancer patients were profiled using illumina sequencing arrays. Allelic imbalance was detected in normal-appearing large and small airway samples and affected known lung cancer driver genes. Multiple airway samples from 45 patients were analyzed using illumina sequencing arrays in order to comprehensively asses the genomic landscape of airway epithelia adjacent to NSCLC. For each patients there was at least one small airway sample, a tumor samples, as well as germline control sample (blood and/or normal uninvolved lung). In addition to these samples additional samples were analyzed for a subset of patients these included large airway, nasal, and multiple core needle biopsies from the tumor.

ORGANISM(S): Homo sapiens

SUBMITTER: Yasminka Jakubek

PROVIDER: E-GEOD-80519 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Genomic Landscape Established by Allelic Imbalance in the Cancerization Field of a Normal Appearing Airway.

Jakubek Yasminka Y Lang Wenhua W Vattathil Selina S Garcia Melinda M Xu Li L Huang Lili L Yoo Suk-Young SY Shen Li L Lu Wei W Chow Chi-Wan CW Weber Zachary Z Davies Gareth G Huang Jing J Behrens Carmen C Kalhor Neda N Moran Cesar C Fujimoto Junya J Mehran Reza R El-Zein Randa R Swisher Stephen G SG Wang Jing J Fowler Jerry J Spira Avrum E AE Ehli Erik A EA Wistuba Ignacio I II Scheet Paul P Kadara Humam H

Cancer research 20160523 13

Visually normal cells adjacent to, and extending from, tumors of the lung may carry molecular alterations characteristics of the tumor itself, an effect referred to as airway field of cancerization. This airway field has been postulated as a model for early events in lung cancer pathogenesis. Yet the genomic landscape of somatically acquired molecular alterations in airway epithelia of lung cancer patients has remained unknown. To begin to fill this void, we sought to comprehensively characteriz ...[more]

PMID: 27216194

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Project description:The tumor microenvironment strongly influences cancer development, progression and metastasis. The role of carcinoma-associated fibroblasts (CAFs) in these processes and their clinical impact has not been studied systematically in non-small cell lung carcinoma (NSCLC). We established primary cultures of CAFs and matched normal fibroblasts (NFs) from 15 resected NSCLC. We demonstrate that CAFs have greater ability than NFs to enhance the tumorigenicity of lung cancer cell lines. Microarray gene expression analysis of the 15 matched CAF and NF cell lines identified 46 differentially expressed genes, encoding for proteins that are significantly enriched for extracellular proteins regulated by the TGF-beta signaling pathway. We have identified a subset of 11 genes that formed a prognostic gene expression signature, which was validated in multiple independent NSCLC microarray datasets. Functional annotation using protein-protein interaction analyses of these and published cancer stroma-associated gene expression changes revealed prominent involvement of the focal adhesion and MAPK signalling pathways. Fourteen (30%) of the 46 genes also were differentially expressed in laser-capture micro-dissected corresponding primary tumor stroma compared to the matched normal lung. Six of these 14 genes could be induced by TGF-beta1 in NF. The results establish the prognostic impact of CAF-associated gene expression changes in NSCLC patients. This SuperSeries is composed of the following subset Series: GSE22862: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [expression profiling_CAFs] GSE22863: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [expression profiling_NSCLC stroma] GSE27284: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [methylation profiling] GSE27289: Prognostic Gene Expression Signature of Carcinoma Associated Fibroblasts in Non-Small Cell Lung Cancer [genome variation profiling]

Project description:Non-small cell lung cancer (NSCLC) is a very common solid tumor where only small advances in the reduction of relapse-free survival and overall survival have been accomplished. The issue is particularly critical for stage I patients where there are not available biomarkers, in the absence of detectable nodal or other metastatic involvement, that might indicate which high-risk patients should receive the beneficially proved adjuvant chemotherapy. We aimed to find DNA methylation markers with prognostic value that could be helpful in this regard and complement the conventional staging. A DNA methylation microarray that analyzes 450,000 CpG sites in the human genome was used to study primary tumoral DNA obtained from a multicenter cohort of 490 patients with NSCLC, corresponding to 339 adenocarcinomas, 133 squamous carcinomas and 18 large cell carcinomas, in addition to 25 normal lung epithelium samples. The obtained prognostic DNA methylation markers were validated by the development of a single methylation-pyrosequencing assay in an independent cohort of 143 patients with stage I NSCLC. The unsupervised clustering of the studied primary NSCLC distinguished two branches with distinct clinical outcomes. Those CpG sites that were the best predictors of recurrence in stage I NSCLC patients were further confirmed in the described independent cohort. Both the global DNA methylation classifier and the highly-ranked aberrantly methylated single genes improved prognostic accuracy beyond standard stagings. DNA was quantified by Quant-iT PicoGreen dsDNA Reagent (Invitrogen) and the integrity was analyzed in a 1.3% agarose gel. Bisulfite conversion of 600 ng of each sample was performed according to the manufacturer's recommendations for the Illumina Infinium Assay. Effective bisulfite conversion was checked for three controls that were converted simultaneously with the samples. 4 ul of bisulfite-converted DNA were used to hybridize on an Infinium HumanMethylation 450 BeadChip, following the Illumina Infinium HD Methylation protocol. Chip analysis was performed using the Illumina HiScan SQ fluorescent scanner. The intensities of the images were extracted using GenomeStudio (2011.2) Methylation module (1.8.5) software. The methylation score of each CpG is represented as a beta value. This dataset includes 444 patient samples.

Dataset Information

Genomic landscape affected by allelic imbalance in the cancerization filed of normal appearing airway

Publications

Genomic Landscape Established by Allelic Imbalance in the Cancerization Field of a Normal Appearing Airway.

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