Dataset Information

Identification of networks of co-occurring, tumor-related DNA copy number changes using a genome-wide scoring approach.

ABSTRACT: Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs) are one of the ways in which cancer genes are deregulated in tumor cells. We hypothesized that synergistic interactions between cancer genes might be identified by looking for regions of co-occurring gain and/or loss. To this end we developed a scoring framework to separate truly co-occurring aberrations from passenger mutations and dominant single signals present in the data. The resulting regions of high co-occurrence can be investigated for between-region functional interactions. Analysis of high-resolution DNA copy number data from a panel of 95 hematological tumor cell lines correctly identified co-occurring recombinations at the T-cell receptor and immunoglobulin loci in T- and B-cell malignancies, respectively, showing that we can recover truly co-occurring genomic alterations. In addition, our analysis revealed networks of co-occurring genomic losses and gains that are enriched for cancer genes. These networks are also highly enriched for functional relationships between genes. We further examine sub-networks of these networks, core networks, which contain many known cancer genes. The core network for co-occurring DNA losses we find seems to be independent of the canonical cancer genes within the network. Our findings suggest that large-scale, low-intensity copy number alterations may be an important feature of cancer development or maintenance by affecting gene dosage of a large interconnected network of functionally related genes.

SUBMITTER: Klijn C

PROVIDER: S-EPMC2791203 | biostudies-literature | 2010 Jan

REPOSITORIES: biostudies-literature

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Identification of networks of co-occurring, tumor-related DNA copy number changes using a genome-wide scoring approach.

Klijn Christiaan C Bot Jan J Adams David J DJ Reinders Marcel M Wessels Lodewyk L Jonkers Jos J

PLoS computational biology 20100101 1

Tumorigenesis is a multi-step process in which normal cells transform into malignant tumors following the accumulation of genetic mutations that enable them to evade the growth control checkpoints that would normally suppress their growth or result in apoptosis. It is therefore important to identify those combinations of mutations that collaborate in cancer development and progression. DNA copy number alterations (CNAs) are one of the ways in which cancer genes are deregulated in tumor cells. We ...[more]

PMID: 20052266

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Project description:The human genome displays extensive copy-number variation (CNV). Recent discoveries have shown that large segments of DNA, ranging in size from hundreds to thousands of nucleotides, are either deleted or duplicated. This CNV may encompass genes, leading to a change in phenotype, including drug response phenotypes. Gemcitabine and 1-beta-D-arabinofuranosylcytosine (AraC) are cytidine analogues used to treat a variety of cancers. Previous studies have shown that genetic variation may influence response to these drugs. In the present study, we set out to test the hypothesis that variation in copy number might contribute to variation in cytidine analogue response phenotypes.We used a cell-based model system consisting of 197 ethnically-defined lymphoblastoid cell lines for which genome-wide SNP data were obtained using Illumina 550 and 650 K SNP arrays to study cytidine analogue cytotoxicity. 775 CNVs with allele frequencies > 1% were identified in 102 regions across the genome. 87/102 of these loci overlapped with previously identified regions of CNV. Association of CNVs with gemcitabine and AraC IC50 values identified 11 regions with permutation p-values < 0.05. Multiplex ligation-dependent probe amplification assays were performed to verify the 11 CNV regions that were associated with this phenotype; with false positive and false negative rates for the in-silico findings of 1.3% and 0.04%, respectively. We also had basal mRNA expression array data for these same 197 cell lines, which allowed us to quantify mRNA expression for 41 probesets in or near the CNV regions identified. We found that 7 of those 41 genes were highly expressed in our lymphoblastoid cell lines, and one of the seven genes (SMYD3) that was significant in the CNV association study was selected for further functional experiments. Those studies showed that knockdown of SMYD3, in pancreatic cancer cell lines increased gemcitabine and AraC resistance during cytotoxicity assay, consistent with the results of the association analysis.These results suggest that CNVs may play a role in variation in cytidine analogue effect. Therefore, association studies of CNVs with drug response phenotypes in cell-based model systems, when paired with functional characterization, might help to identify CNV that contributes to variation in drug response.

Project description:The genome?wide copy number analysis of circulating tumor cells (CTCs) provides a promising prognostic biomarker for survival in breast cancer liver metastasis (BCLM) patients. The present study aimed to confirm the prognostic value of the presence of CTCs in BCLM patients. We previously developed an assay for the genome?wide pattern differences in copy number variations (CNVs) as an adjunct test for the routine imaging and histopathologic diagnosis methods to distinguish newly diagnosed liver metastases and recurrent liver metastases. Forty?three breast cancer patients were selected for this study in which 23 newly diagnosed and 20 recurrent liver metastases were diagnosed by histopathology and 18F?FDG PET/CT imaging. CTCs were counted from all patients using the CellSearch system and were confirmed by cytomorphology and three?color immunocytochemistry. Genomic DNA of single CTCs was amplified using multiple annealing and looping based amplification cycles (MALBAC). Then, we compared the CTC numbers of newly diagnosed and recurrent BCLM patients using Illumina platforms. A high CTC frequency (>15 CTCs/7.5 ml blood) was found to be correlated with disease severity and metastatic progression, which suggests the value for CTCs in the diagnosis of BCLM in comparison with pathohistology and PET/CT imaging (P>0.05). Moreover, CTCs isolated from BCLM patients remained an independent prognostic detection factor associated with overall survival (P=0.0041). Comparison between newly diagnosed and recurrent liver metastases revealed different frequencies of CNVs (P>0.05). Notably, the CNV pattern of isolated CTCs of recurrent BCLM patients was similar to recurrent liver metastases (nearly 82% of the gain/loss regions). Functional enrichment analysis identified 25 genes as a CNV signature of BCLM. Among them, were defensin and ??defensin genes, which are significantly associated with anti?angiogenesis and immunomodulation signaling pathways. High CTC frequencies are effective in the evaluation and differentiation between newly diagnosed liver metastases from recurrent liver metastases. Future clinical studies will be necessary to fully determine the prognostic potential of CTC cluster signatures in patients with BCLM.

Dataset Information

Identification of networks of co-occurring, tumor-related DNA copy number changes using a genome-wide scoring approach.

Publications

Identification of networks of co-occurring, tumor-related DNA copy number changes using a genome-wide scoring approach.

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