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The CURELUNG Project from the Epigenetics Side (Patients dataset)

ABSTRACT: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE39279 | GEO | 2013/10/03

SECONDARY ACCESSION(S): PRJNA170473

REPOSITORIES: GEO

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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.

Project description:Background: Accurate survival stratification in early-stage NSCLC could inform the use of adjuvant therapy. We developed a clinically-implementable mortality risk score incorporating distinct tumor microenvironmental gene expression signatures and clinical variables. Methods: Gene expression profiles from 1106 non-squamous NSCLCs were used for generation and internal validation of a 9-gene molecular prognostic index (MPI). Expression of the MPI genes was determined within sorted tumor cell subpopulations. A quantitative PCR (qPCR) assay was developed and validated on an independent cohort of FFPE tissues. A prognostic score using clinical variables was generated using Surveillance Epidemiology and End Results (SEER) data and combined with the MPI. Results: The MPI stratified stage I patients into prognostic categories in four independent validation datasets, including three microarray and one FFPE qPCR cohorts (HR=2.4, 95% CI, 1.8-3.3, P=7x10-9 in the largest microarray cohort; and HR=2.5, 95% CI 1.1-6.0, P=.03 in stage I patients of the qPCR validation cohort). Prognostic genes were expressed in distinct tumor cell subpopulations and expression of genes implicated in cellular proliferation and stem cells portended poor outcomes, while expression of genes involved in normal lung differentiation and immune infiltration was associated with superior survival. Integrating the MPI with clinical variables conferred greatest prognostic power (HR=3.3, 95% CI 2.4-4.6; P=2x10-15 in the largest microarray cohort; and HR=3.6, 95% CI 1.5-8.8, P=.003 in stage I patients of the qPCR validation cohort). Finally, the MPI was prognostic irrespective of somatic alterations in EGFR, KRAS, TP53, and ALK. Conclusion: The MPI incorporates genes expressed in the tumor and its microenvironment, and designates risk of death for patients with early-stage non-squamous NSCLC. The MPI can be implemented clinically using qPCR assays on FFPE tissues and a composite model integrating the MPI with clinical variables provides the most accurate risk stratification.

Project description:Epigenetic changes largely contribute to the regulation of gene expression in cancer cells. DNA methylation is part of the epigenetic gene regulation complex which is relevant for the pathogenesis of cancer. We performed a genome-wide search for methylated CpG islands in tumors and corresponding non-malignant lung tissue samples of 101 stage I-III non-small cell lung cancer (NSCLC) patients by combining methylated DNA immunoprecipitation and microarray analysis using NimbleGenM-BM-4s 385K Human CpG Island plus Promoter arrays. By testing for differences in methylation between tumors and corresponding non-malignant lung tissues, we identified 298 tumor-specifically methylated genes. From many of these genes epigenetic regulation was unknown so far. Gene Ontology analysis revealed an over-representation of genes involved in regulation of gene expression and cell adhesion. Expression of 182 of 298 genes was found to be upregulated after 5-aza-2M-BM-4-deoxycytidine (Aza-dC) and/or trichostatin A (TSA) treatment of 3 NSCLC cell lines by Affymetrix microarray analysis. In addition, methylation of selected genes in primary NSCLCs and corresponding non-malignant lung tissue samples were analyzed by methylation-sensitive high resolution melting analysis (MS-HRM). Our results obtained by MS-HRM analysis confirmed our data obtained by MeDIP-chip analysis. Moreover, by comparing methylation results from MeDIP-chip analysis with clinico-pathological parameters of the patients we observed methylation of HOXA2 as potential parameter for shorter disease-free survival of NSCLC patients. In conclusion, using a genome-wide approach we identified a large number of tumor-specifically methylated genes in NSCLC patients. Our results stress the importance of DNA methylation for the pathogenesis of NSCLCs. Overall, samples of 3 untreated, with Aza-dC treated and with Aza-dC/TSA treated NSCLC cell lines were hybridized to Affymetrix HG-U133_plus_2.0 microarrays (18 in total).

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The CURELUNG Project from the Epigenetics Side (Patients dataset)

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