Dataset Information

A large scale survey reveals that chromosomal copy-number alterations significantly affect gene modules involved in cancer initiation and progression.

ABSTRACT: Recent observations point towards the existence of a large number of neighborhoods composed of functionally-related gene modules that lie together in the genome. This local component in the distribution of the functionality across chromosomes is probably affecting the own chromosomal architecture by limiting the possibilities in which genes can be arranged and distributed across the genome. As a direct consequence of this fact it is therefore presumable that diseases such as cancer, harboring DNA copy number alterations (CNAs), will have a symptomatology strongly dependent on modules of functionally-related genes rather than on a unique "important" gene.We carried out a systematic analysis of more than 140,000 observations of CNAs in cancers and searched by enrichments in gene functional modules associated to high frequencies of loss or gains.The analysis of CNAs in cancers clearly demonstrates the existence of a significant pattern of loss of gene modules functionally related to cancer initiation and progression along with the amplification of modules of genes related to unspecific defense against xenobiotics (probably chemotherapeutical agents). With the extension of this analysis to an Array-CGH dataset (glioblastomas) from The Cancer Genome Atlas we demonstrate the validity of this approach to investigate the functional impact of CNAs.The presented results indicate promising clinical and therapeutic implications. Our findings also directly point out to the necessity of adopting a function-centric, rather a gene-centric, view in the understanding of phenotypes or diseases harboring CNAs.

SUBMITTER: Alloza E

PROVIDER: S-EPMC3112060 | biostudies-literature | 2011 May

REPOSITORIES: biostudies-literature

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A large scale survey reveals that chromosomal copy-number alterations significantly affect gene modules involved in cancer initiation and progression.

Alloza Eva E Al-Shahrour Fátima F Cigudosa Juan C JC Dopazo Joaquín J

BMC medical genomics 20110506

<h4>Background</h4>Recent observations point towards the existence of a large number of neighborhoods composed of functionally-related gene modules that lie together in the genome. This local component in the distribution of the functionality across chromosomes is probably affecting the own chromosomal architecture by limiting the possibilities in which genes can be arranged and distributed across the genome. As a direct consequence of this fact it is therefore presumable that diseases such as c ...[more]

PMID: 21548942

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Project description:BACKGROUND:Detection of DNA copy number alterations (CNAs) is critical to understand genetic diversity, genome evolution and pathological conditions such as cancer. Cancer genomes are plagued with widespread multi-level structural aberrations of chromosomes that pose challenges to discover CNAs of different length scales, and distinct biological origins and functions. Although several computational tools are available to identify CNAs using read depth (RD) signal, they fail to distinguish between large-scale and focal alterations due to inaccurate modeling of the RD signal of cancer genomes. Additionally, RD signal is affected by overdispersion-driven biases at low coverage, which significantly inflate false detection of CNA regions. RESULTS:We have developed CNAtra framework to hierarchically discover and classify 'large-scale' and 'focal' copy number gain/loss from a single whole-genome sequencing (WGS) sample. CNAtra first utilizes a multimodal-based distribution to estimate the copy number (CN) reference from the complex RD profile of the cancer genome. We implemented Savitzky-Golay smoothing filter and Modified Varri segmentation to capture the change points of the RD signal. We then developed a CN state-driven merging algorithm to identify the large segments with distinct copy numbers. Next, we identified focal alterations in each large segment using coverage-based thresholding to mitigate the adverse effects of signal variations. Using cancer cell lines and patient datasets, we confirmed CNAtra's ability to detect and distinguish the segmental aneuploidies and focal alterations. We used realistic simulated data for benchmarking the performance of CNAtra against other single-sample detection tools, where we artificially introduced CNAs in the original cancer profiles. We found that CNAtra is superior in terms of precision, recall and f-measure. CNAtra shows the highest sensitivity of 93 and 97% for detecting large-scale and focal alterations respectively. Visual inspection of CNAs revealed that CNAtra is the most robust detection tool for low-coverage cancer data. CONCLUSIONS:CNAtra is a single-sample CNA detection tool that provides an analytical and visualization framework for CNA profiling without relying on any reference control. It can detect chromosome-level segmental aneuploidies and high-confidence focal alterations, even from low-coverage data. CNAtra is an open-source software implemented in MATLAB®. It is freely available at https://github.com/AISKhalil/CNAtra.

Project description:Lymph node metastasis is an important indicator of oncologic outcome for patients with rectal cancer. Identifying predictive biomarkers of lymph node metastasis could therefore be clinically useful.The aim of this study was to assess whether chromosomal copy number alterations can assist in predicting persistent lymph node metastasis in patients with locally advanced rectal cancer treated with preoperative chemoradiation therapy.This is a nonrandomized, prospective phase II study.This study took place in a multi-institutional setting.Ninety-five patients with stage II (cT3-4, cN0) or stage III (any cT, cN1-2) rectal cancer were included.Patients were treated with preoperative chemoradiation therapy followed by total mesorectal excision. Pretreatment biopsy tumor DNA and surgical margin control DNA were extracted and analyzed by oligonucleotide array-based comparative genomic hybridization. Chromosomal copy number alterations were correlated with persistent lymph node metastasis. Finally, a model for predicting persistent lymph node metastasis was built.The primary outcomes assessed were whether chromosomal copy number alterations are associated with persistent lymph node metastasis in patients with rectal cancer and the accuracy of oligonucleotide array-based comparative genomic hybridization for predicting lymph node metastasis.Twenty-five of 95 (26%) patients had lymph node metastasis after chemoradiation. Losses of 28 chromosomal regions, most notably in chromosome 4, were significantly associated with lymph node metastasis. Our predictive model contained 65 probes and predicted persistent lymph node metastasis with 68% sensitivity, 93% specificity, and positive and negative predictive values of 77% and 89%. The use of this model accurately predicted lymph node status (positive or negative) after chemoradiation therapy in 82 of 95 patients (86%).The patient cohort was not completely homogeneous, which may have influenced their clinical outcome. In addition, although we performed rigorous, statistically sound internal validation, external validation will be important to further corroborate our findings.Copy number alterations can help identify patients with rectal cancer who are at risk of lymph node metastasis after chemoradiation.

Dataset Information

A large scale survey reveals that chromosomal copy-number alterations significantly affect gene modules involved in cancer initiation and progression.

Publications

A large scale survey reveals that chromosomal copy-number alterations significantly affect gene modules involved in cancer initiation and progression.

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