Ontology highlight
ABSTRACT:
PROVIDER: PRJNA145473 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Lung cancer, of which more than 80% is non-small cell, is the leading cause of cancer-related death in the United States. Copy number alterations (CNAs) in lung cancer have been shown to be positionally clustered in certain genomic regions. However, it remains unclear whether genes with copy number changes are functionally clustered. Using a dense single nucleotide polymorphism array, we performed genome-wide copy number analyses of a large collection of non-small cell lung tumors (n = 301). We proposed a formal statistical test for CNAs between different groups (e.g., noninvolved lung vs. tumors, early vs. late stage tumors). We also customized the gene set enrichment analysis (GSEA) algorithm to investigate the overrepresentation of genes with CNAs in predefined biological pathways and gene sets (i.e., functional clustering). We found that CNAs events increase substantially from germline, early stage to late stage tumor. In addition to genomic position, CNAs tend to occur away from the gene locations, especially in germline, noninvolved tissue and early stage tumors. Such tendency decreases from germline to early stage and then to late stage tumors, suggesting a relaxation of selection during tumor progression. Furthermore, genes with CNAs in non-small cell lung tumors were enriched in certain gene sets and biological pathways that play crucial roles in oncogenesis and cancer progression, demonstrating the functional aspect of CNAs in the context of biological pathways that were overlooked previously. We conclude that CNAs increase with disease progression and CNAs are both positionally and functionally clustered. The potential functional capabilities acquired via CNAs may be sufficient for normal cells to transform into malignant cells. Copy number analysis was performed on 301 non-small cell lung cancer tumor samples using Affymetrix 250K Nsp GeneChip
2011-12-06 | E-GEOD-34140 | biostudies-arrayexpress
Project description:Genome-wide DNA copy number profiling of gastric tumors and matched non-maligant samples. The affymetrix SNP6 array was used to obtain DNA copy number profiles in 193 gastric tumors and 98 matched gastric non-malignant samples.
2012-02-10 | GSE31168 | GEO
Project description:This SuperSeries is composed of the following subset Series: GSE28571: Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer (expression data) GSE28572: Gene Copy Number Aberrations are Associated with Survival in Histological Subgroups of Non-Small Cell Lung Cancer (copy number data) Refer to individual Series
2011-11-01 | E-GEOD-28582 | biostudies-arrayexpress
Project description:PURPOSE: Bone marrow (BM) is a common homing organ for early disseminated tumor cells (DTC) and their presence can predict the subsequent occurrence of overt metastasis and survival in lung cancer. It is still unclear whether the shedding of DTC from the primary tumor is a random process or a selective release driven by a specific genomic pattern. EXPERIMENTAL DESIGN: DTCs were identified in BM from lung cancer patients by an immunocytochemical cytokeratin assay. Genomic aberrations and expression profiles of the respective primary tumors were assessed by microarrays and FISH analyses. The most significant results were validated on an independent set of primary lung tumors and brain metastases. RESULTS: Combination of DNA copy number profiles (array CGH) with gene expression profiles identified five chromosomal regions differentiating BM-negative from BM-positive patients (4q12-q32, 10p12-p11, 10q21-q22, 17q21 and 20q11-q13). Copy number changes of 4q12-q32 were the most prominent finding, containing the highest number of differentially expressed genes irrespective of chromosomal size (p=0.018). FISH analyses on further primary lung tumor samples confirmed the association between loss of 4q and the BM-positive status. In BM-positive patients 4q was frequently lost (37% vs. 7%), whereas gains could be commonly found among BM-negative patients (7% vs. 17%). The same loss was also found to be common in brain metastases from both small and non-small-cell lung cancer patients (39%). CONCLUSIONS: Thus, our data indicates for the first time that early hematogeneous dissemination of tumor cells might be driven by a specific pattern of genomic changes.
2009-10-05 | GSE13191 | GEO
Project description:Lung cancer, of which more than 80% is non-small cell, is the leading cause of cancer-related death in the United States. Copy number alterations (CNAs) in lung cancer have been shown to be positionally clustered in certain genomic regions. However, it remains unclear whether genes with copy number changes are functionally clustered. Using a dense single nucleotide polymorphism array, we performed genome-wide copy number analyses of a large collection of non-small cell lung tumors (n = 301). We proposed a formal statistical test for CNAs between different groups (e.g., noninvolved lung vs. tumors, early vs. late stage tumors). We also customized the gene set enrichment analysis (GSEA) algorithm to investigate the overrepresentation of genes with CNAs in predefined biological pathways and gene sets (i.e., functional clustering). We found that CNAs events increase substantially from germline, early stage to late stage tumor. In addition to genomic position, CNAs tend to occur away from the gene locations, especially in germline, noninvolved tissue and early stage tumors. Such tendency decreases from germline to early stage and then to late stage tumors, suggesting a relaxation of selection during tumor progression. Furthermore, genes with CNAs in non-small cell lung tumors were enriched in certain gene sets and biological pathways that play crucial roles in oncogenesis and cancer progression, demonstrating the functional aspect of CNAs in the context of biological pathways that were overlooked previously. We conclude that CNAs increase with disease progression and CNAs are both positionally and functionally clustered. The potential functional capabilities acquired via CNAs may be sufficient for normal cells to transform into malignant cells.
2011-12-06 | GSE34140 | GEO
Project description:microRNAs are small, non-coding, single-stranded RNAs between 18-22 nucleotides long that regulate gene expression. Expression of microRNAs is altered in tumor compared to normal tissue; there is some evidence that these changes may be reflected in the serum of cancer cases compared to healthy individuals. Several case-control studies have found evidence of differential levels of serum miRNAs in early stage non-small cell lung cancer (NSCLC) patients but with little consensus on specific miRNAs. Similarly, it is unclear whether miRNAs that show differential levels in tumors are the same miRNAs that are found in serum, and whether surgical resection of tumors leads to normalization of serum miRNA levels in cases. We used Affymetrix arrays to examine serum miRNA expression profiles in a small series of surgically resected non-small cell lung cancer cases to investigate circulating levels of miRNAs.
2014-12-30 | GSE46729 | GEO
Project description:DNA from 136 resected breast cancer tissues from patients exposed to ioinising radiation and non-exposed controls was analysed for genomic copy number alterations. The two groups were compared for the delination of genomic copy number changes associated with exposure status.
2018-04-02 | E-MTAB-6176 | biostudies-arrayexpress
Project description:DNA from resected colon cancer primary tumour tissue was analyzed for association between tumour dissemination and copy number alterations.
2014-12-01 | GSE62875 | GEO
Project description:Cancer is a heterogeneous disease caused by genomic aberrations and characterized by significant variability in clinical outcome and response to therapies. Several subtypes of common cancer types have been identified based on alterations of individual cancer genes, such as HER2, EGFR, and others. However, cancer is a complex disease driven by the interaction of multiple genes, so the copy number status of individual genes is not sufficient to define cancer subtypes and predict the response to treatments. A classification based on genome-wide copy number patterns would be better suited for this purpose. To develop a more comprehensive cancer taxonomy based on genome-wide patterns of copy number abnormalities, we designed an unsupervised gNMF-based classification algorithm that identifies genomic subgroups of tumors. The algorithm was subjected to a stability test and validated by demonstrating clinical differences between samples assigned to different clusters. Our algorithm demonstrated better performance in the stability test when compared with other clustering methods. Most importantly, it yielded better separation between groups of samples with distinct clinical outcomes, implying that it classifies samples into clinically relevant subgroups. We propose using this methodology to identify unknown subtypes of cancers and to assemble panels of pre-clinical testing models that would represent different subtypes of cancers. Affymetrix SNP arrays were performed according to the manufacturer's directions. Copy number analysis of Affymetrix 100K SNP arrays was performed for 40 non-small cell lung carcinoma cell lines, 205 non-small cell lung carcinoma primary tumors, 35 colorectal cancer cell lines, and 101 colorectal cancer primary tumors.
2010-08-06 | E-GEOD-20481 | biostudies-arrayexpress