Homo sapiens
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ABSTRACT:
PROVIDER: PRJNA302278 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:DNA methylation profiling of lung adenocarcinomas and patient-matched non-malignant lung
| PRJNA578118 | ENA
Project description:Background: Non-small cell lung cancers (NSCLCs) consist of adenocarcinoma (ADC), squamous cell carcinoma (SCC) and other types. Since most NSCLCs are now diagnosed from small biopsies or cytology materials, classification is not always accurate. This is a problem as many therapy regimens and clinical trials are histology-dependent. Specific Aim: To develop an RNA expression signature as an adjunct test for routine histo-pathological classification of NSCLCs. Methods: A microarray dataset of resected ADC and SCC cases was used as the learning set for an ADC-SCC signature. The Cancer Genome Atlas (TCGA) lung RNAseq dataset was used as a validation set. Another microarray dataset of ADCs and non-malignant lung was used as the learning set for a Tumor-Nonmalignant signature. The classifiers were selected as the most differentially expressed genes and sample classification was determined by a nearest distance approach. Results: We developed a 42-gene expression signature that contained many genes used in immunostains for NSCLC typing. Testing of the TCGA and other public datasets resulted in high accuracies (93-95%). We also observed that most non-malignant lung samples were classified as â??adenocarcinomasâ??, so we added 20 genes to differentiate tumor from non-malignant lung. Together, the 62-gene signature can discriminate ADC, SCC, and non-malignant lung. Additionally, a prediction score was derived that correlated both with histologic grading and survival. Summary and significance: Our histologic classifier provides a non-subjective method to aid in the pathological diagnosis of lung cancer and assist enrollment onto histology-based clinical trials 83 lung adenocarcinomas and 83 matched adjacent non-malignant lung were profiled on Illumina WG6-V3 expression arrays
2016-06-01 | E-GEOD-75037 | biostudies-arrayexpress
Project description:DNA copy number profiling of lung adenocarcinomas and patient-matched non-malignant lung
| PRJNA579164 | ENA
Project description:Lung cancer occurs in never-smokers. Epigenetic changes in lung cancer potentially represent important diagnostic, prognostic, and therapeutic targets. We compared DNA methylation profiles of 28 adenocarcinomas of the lungs of never-smokers with paired adjacent nonmalignant lung tissue. We correlated differential methylation changes with gene expression changes from the same 28 samples. We observed a distinct separation in methylation profiles between tumor and adjacent nonmalignant lung tissue using principal component analysis. Tumors were generally hypomethylated compared with adjacent nonmalignant tissue. Of 1,906 differentially methylated CpG sites between tumor and nonmalignant tissue, 1,198 were within classically defined CpG islands where tumors were hypermethylated compared with nonmalignant tissue. A total of 708 sites were outside CpG islands where tumors were hypomethylated compared with nonmalignant tissue. There were significant differences in expression of 351 genes (23%) of the 1,522 genes matched to the differentially methylated CpG sites. Genes that were not significantly differentially expressed and were hypermethylated within CpG sites were enriched for homeobox genes. These results suggest that the methylation profiles of lung adenocarcinomas of never-smokers and adjacent nonmalignant lung tissue are significantly different. Despite the differential methylation of homeobox genes, no significant changes in expression of these genes were detected. Twenty eight pairs of tumor and adjacent normal lungs were profiled for lung adenocarcinoma patients by gene expression and DNA methylation microarray
2015-02-03 | E-GEOD-62948 | biostudies-arrayexpress
Project description:Lung cancer occurs in never-smokers. Epigenetic changes in lung cancer potentially represent important diagnostic, prognostic, and therapeutic targets. We compared DNA methylation profiles of 28 adenocarcinomas of the lungs of never-smokers with paired adjacent nonmalignant lung tissue. We correlated differential methylation changes with gene expression changes from the same 28 samples. We observed a distinct separation in methylation profiles between tumor and adjacent nonmalignant lung tissue using principal component analysis. Tumors were generally hypomethylated compared with adjacent nonmalignant tissue. Of 1,906 differentially methylated CpG sites between tumor and nonmalignant tissue, 1,198 were within classically defined CpG islands where tumors were hypermethylated compared with nonmalignant tissue. A total of 708 sites were outside CpG islands where tumors were hypomethylated compared with nonmalignant tissue. There were significant differences in expression of 351 genes (23%) of the 1,522 genes matched to the differentially methylated CpG sites. Genes that were not significantly differentially expressed and were hypermethylated within CpG sites were enriched for homeobox genes. These results suggest that the methylation profiles of lung adenocarcinomas of never-smokers and adjacent nonmalignant lung tissue are significantly different. Despite the differential methylation of homeobox genes, no significant changes in expression of these genes were detected. Twenty eight pairs of tumor and adjacent normal lungs were profiled for lung adenocarcinoma patients by gene expression and DNA methylation microarray
2015-02-03 | E-GEOD-62949 | biostudies-arrayexpress
Project description:Chronic obstructive pulmonary disease (COPD) is a known risk factor for developing lung cancer suggesting that the COPD stroma contains factors supporting tumorigenesis. Since cancer initiation is complex we used a multi-omic approach to identify gene expression patterns that distinguish COPD stroma in patients with or without lung cancer. Our overall objective is the identification of gene expression pathways and levels of regulation in lung stroma of patients with COPD that harbor lung cancer. We obtained lung tissue from patients with COPD and lung cancer (tumor and adjacent non-malignant tissue) and those with COPD without lung cancer for proteomic and mRNA (cytoplasmic and polyribosomal) profiling. We used the joint and individual variation explained (JIVE) method to integrate and analysis across the three datasets. JIVE identified eight latent patterns that robustly distinguished and separated the three groups of tissue samples. Predictive variables that associated with the tumor, compared to adjacent stroma, were mainly represented in the transcriptomic data, whereas, predictive variables associated with adjacent tissue compared to controls was represented at the translatomic level. Kyoto Encyclopedia of Genes and Genome (KEGG) pathway analysis revealed extracellular matrix (ECM) and PI3K-Akt signaling pathways as important signals in the pre-malignant stroma. COPD stroma adjacent to lung cancer is unique and differs from non-malignant COPD tissue and is distinguished by the extracellular matrix and PI3K-Akt signaling pathways.
2019-05-28 | PXD007919 | Pride
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.
2011-03-01 | E-MEXP-2644 | biostudies-arrayexpress
Project description:We demonstrate that miR-708 is one of the most highly overexpressed miRNAs in non-small cell lung cancer. High level of miR-708 in tumor is also associated with a reduced overall survival in lung adenocarcinomas from never smokers. Functionally, miR-708 overexpression increases the proliferation, migration, and invasion in cultured cells and down regulates TMEM88, a negative regulator of Wnt signaling. Jointly, our results support an oncogenic role of miR-708 by activating Wnt signaling pathway to promote lung cancer progression. We performed miRNA expression profiling in matched lung adenocarcinoma and uninvolved lung using 47 pairs from formalin-fixed, paraffin-embedded [FFPE] tissues from never smokers. We performed miRNA expression profiling in matched lung adenocarcinoma and uninvolved lung using 56 pairs of fresh-frozen [FF] samples from never smokers.
2012-08-02 | E-GEOD-36681 | biostudies-arrayexpress
Project description:We investigated whether the miRNA expression could distinguish lung cancers from normal tissues, examining 116 pairs of primary lung cancers with their corresponding adjacent normal lung tissues collected a minimum of 5 cm from the tumor. Our analysis identified a five microRNA classifier could distinguish malignant lung cancer lesions from adjacent normal tissues. SCLC could be distinguished from non small lung cancer by microRNAs profiling. Survival associations were examined with the SCC and adenocarcinoma subtypes. High hsa-miR-31 expression was associated with poor survival in SCC, and the association was confirmed in 20 independent SCC patients by qRT-PCR assays. Overall these findings may help advance the use of microRNA profiling in personalized diagnosis of lung cancers. Key Words: microRNA; lung cancer; microarray; diagnosis; prognosis cancer vs adjacent normal tissues
2010-02-10 | E-GEOD-15008 | biostudies-arrayexpress
Project description:Gene expression analysis of lung adenocarcinoma and matched adjacent non-tumor lung tissue
| PRJNA154393 | ENA