Heidenblad M, Lindgren D, Veltman JA, Jonson T, Mahlamäki EH, Gorunova L, van Kessel AG, Schoenmakers EF, Höglund MMicroarray analyses reveal strong influence of DNA copy number alterations on the transcriptional patterns in pancreatic cancer: implications for the interpretation of genomic amplifications. Oncogene 24: 1794-1801
DNA copy number alterations are believed to play a major role in the development and progression of human neoplasms. Although most of these genomic imbalances have been associated with dysregulation of individual genes, their large-scale transcriptional consequences remain unclear. Pancreatic carcinomas frequently display gene copy number variation of entire chromosomes as well as of chromosomal subregions. These changes range from homozygous deletions to high-level amplifications and are believed to constitute key genetic alterations in the cellular transformation of this tumor type. To investigate the transcriptional consequences of the most drastic genomic changes, that is, genomic amplifications, and to analyse the genome-wide transcriptional effects of DNA copy number changes, we performed expression profiling of 29 pancreatic carcinoma cell lines and compared the results with matching genomic profiling data. We show that a strong association between DNA copy numbers and mRNA expression levels is present in pancreatic cancer, and demonstrate that as much as 60% of the genes within highly amplified genomic regions display associated overexpression. Consequently, we identified 67 recurrently overexpressed genes located in seven precisely mapped commonly amplified regions. The presented findings indicate that more than one putative target gene may be of importance in most pancreatic cancer amplicons.
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"Previous studies have provided insights into the importance of specific copy number alterations in the development of epithelial tumors, showing that these alterations may lead to the altered expression of critical oncogenes or tumor suppressors , , . Our study therefore confirms these previous reports and provides evidence to support that CNA represents an important factor in regulating the abnormal up or down-expression of these genes during gastric cancer carcinogenesis. "
[Show abstract][Hide abstract]ABSTRACT: Genomic instability with frequent DNA copy number alterations is one of the key hallmarks of carcinogenesis. The chromosomal regions with frequent DNA copy number gain and loss in human gastric cancer are still poorly defined. It remains unknown how the DNA copy number variations contributes to the changes of gene expression profiles, especially on the global level.
We analyzed DNA copy number alterations in 64 human gastric cancer samples and 8 gastric cancer cell lines using bacterial artificial chromosome (BAC) arrays based comparative genomic hybridization (aCGH). Statistical analysis was applied to correlate previously published gene expression data obtained from cDNA microarrays with corresponding DNA copy number variation data to identify candidate oncogenes and tumor suppressor genes. We found that gastric cancer samples showed recurrent DNA copy number variations, including gains at 5p, 8q, 20p, 20q, and losses at 4q, 9p, 18q, 21q. The most frequent regions of amplification were 20q12 (7/72), 20q12-20q13.1 (12/72), 20q13.1-20q13.2 (11/72) and 20q13.2-20q13.3 (6/72). The most frequent deleted region was 9p21 (8/72). Correlating gene expression array data with aCGH identified 321 candidate oncogenes, which were overexpressed and showed frequent DNA copy number gains; and 12 candidate tumor suppressor genes which were down-regulated and showed frequent DNA copy number losses in human gastric cancers. Three networks of significantly expressed genes in gastric cancer samples were identified by ingenuity pathway analysis.
This study provides insight into DNA copy number variations and their contribution to altered gene expression profiles during human gastric cancer development. It provides novel candidate driver oncogenes or tumor suppressor genes for human gastric cancer, useful pathway maps for the future understanding of the molecular pathogenesis of this malignancy, and the construction of new therapeutic targets.
"In cancer research, this combined approach helps filtering the large amount of array-based data and, by narrowing down the hundreds of differentially expressed genes to those whose altered expression is attributable to underlying chromosomal alterations, allows highlighting candidate genes that are actively involved in the causation or maintenance of the malignant phenotype. This approach was applied in a wide range of tumor types, including breast (Hyman, 2002; Pollack, 2002), bladder (Harding et al., 2002), prostate (Saramäki et al., 2006), pancreas (Heidenblad et al., 2005), rectal (Grade et al., 2006) and melanoma (Akavia et al., 2010), demonstrating a strong genome-wide correlation between aneuploidy-associated genomic imbalances and global gene expression levels. Most studies focused on amplified and overexpressed genes and calculated that a fraction ranging from 44% to 62% of amplified genes showed concomitant up-regulated expression levels (Hyman et al., 2002). "
"CNA and aberrations in mRNA levels separately and then match the identified aberrations to determine if alterations in mRNA levels may be attributed to CNA (Heidenblad et al., 2005; van Wieringen et al., 2006; Bicciato et al., 2009; Oudejans et al., 2009). "
[Show abstract][Hide abstract]ABSTRACT: DNA copy number aberrations (CNA) and subsequent altered gene expression profiles (mRNA levels) are characteristic features of cancerous cells. Integrative genomic analysis aims to identify recurrent CNA that may have a potential role in cancer development, assuming that gene amplification is accompanied by overexpression, while deletions give rise to downregulation of gene expression. We propose a segmented regression-based approach to identify CNA-driven alteration of gene expression profiles. Segmented regression allows to fit piecewise linear models in different domains of CNA joined by a change-point, where the mRNA-CNA relationship undergoes structural changes. Here, we illustrate the implementation and applicability of the proposed model using 1,161 chromosome fragments detected as DNA CNA in primary tumors from 97 breast cancer patients. We identified significant CNA-driven changes in gene expression levels for 341 chromosome fragments, of which 72 showed a nonlinear relationship to CNA. For 59 of 72 chromosome fragments (82%), we observed an initial increase in mRNA levels due to changes in CNA. After the change-point was passed, the mRNA levels reached a plateau, and a further increase in DNA copy numbers did not induce further elevation in mRNA levels. In contrast, for 13 chromosome fragments, the change-point marked the point where mRNA production accelerated. We conclude that segmented regression modeling may provide valuable insights into the impact CNA have on gene expression in cancer cells.
Full-text · Article · Jan 2012 · Genes Chromosomes and Cancer