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Classification of human cancers based on DNA copy number amplification modeling.

ABSTRACT: BACKGROUND: DNA amplifications alter gene dosage in cancer genomes by multiplying the gene copy number. Amplifications are quintessential in a considerable number of advanced cancers of various anatomical locations. The aims of this study were to classify human cancers based on their amplification patterns, explore the biological and clinical fundamentals behind their amplification-pattern based classification, and understand the characteristics in human genomic architecture that associate with amplification mechanisms. METHODS: We applied a machine learning approach to model DNA copy number amplifications using a data set of binary amplification records at chromosome sub-band resolution from 4400 cases that represent 82 cancer types. Amplification data was fused with background data: clinical, histological and biological classifications, and cytogenetic annotations. Statistical hypothesis testing was used to mine associations between the data sets. RESULTS: Probabilistic clustering of each chromosome identified 111 amplification models and divided the cancer cases into clusters. The distribution of classification terms in the amplification-model based clustering of cancer cases revealed cancer classes that were associated with specific DNA copy number amplification models. Amplification patterns - finite or bounded descriptions of the ranges of the amplifications in the chromosome - were extracted from the clustered data and expressed according to the original cytogenetic nomenclature. This was achieved by maximal frequent itemset mining using the cluster-specific data sets. The boundaries of amplification patterns were shown to be enriched with fragile sites, telomeres, centromeres, and light chromosome bands. CONCLUSIONS: Our results demonstrate that amplifications are non-random chromosomal changes and specifically selected in tumor tissue microenvironment. Furthermore, statistical evidence showed that specific chromosomal features co-localize with amplification breakpoints and link them in the amplification process.

SUBMITTER: Myllykangas S

PROVIDER: S-EPMC2397431 | biostudies-literature | 2008

REPOSITORIES: biostudies-literature

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Classification of human cancers based on DNA copy number amplification modeling.

Myllykangas Samuel S Tikka Jarkko J Böhling Tom T Knuutila Sakari S Hollmén Jaakko J

BMC medical genomics 20080514

<h4>Background</h4>DNA amplifications alter gene dosage in cancer genomes by multiplying the gene copy number. Amplifications are quintessential in a considerable number of advanced cancers of various anatomical locations. The aims of this study were to classify human cancers based on their amplification patterns, explore the biological and clinical fundamentals behind their amplification-pattern based classification, and understand the characteristics in human genomic architecture that associat ...[more]

PMID: 18477412

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Project description:Rationale: Loss of DNA damage repair (DDR) in the tumor is an established hallmark of sensitivity to DNA damaging agents such as chemotherapy. However, there has been scant investigation into gain-of-function alterations of DDR genes in cancer. This study aims to investigate to what extent copy number amplification of DDR genes occurs in cancer, and what are their impacts on tumor genome instability, patient prognosis and therapy outcome. Methods: Retrospective analysis was performed on the clinical, genomics, and pharmacogenomics data from 10,489 tumors, matched peripheral blood samples, and 1,005 cancer cell lines. The key discoveries were verified by an independent patient cohort and experimental validations. Results: This study revealed that 13 of the 80 core DDR genes were significantly amplified and overexpressed across the pan-cancer scale. Tumors harboring DDR gene amplification exhibited decreased global mutation load and mechanism-specific mutation signature scores, suggesting an increased DDR proficiency in the DDR amplified tumors. Clinically, patients with DDR gene amplification showed poor prognosis in multiple cancer types. The most frequent Nibrin (NBN) gene amplification in ovarian cancer tumors was observed in 15 out of 31 independent ovarian cancer patients. NBN overexpression in breast and ovarian cancer cells leads to BRCA1-dependent olaparib resistance by promoting the phosphorylation of ATM-S1981 and homology-dependent recombination efficiency. Finally, integration of the cancer pharmacogenomics database of 37 genome-instability targeting drugs across 505 cancer cell lines revealed significant correlations between DDR gene copy number amplification and DDR drug resistance, suggesting candidate targets for increasing patient treatment response. Principal Conclusions: DDR gene amplification can lead to chemotherapy resistance and poor overall survival by augmenting DDR. These amplified DDR genes may serve as actionable clinical biomarkers for cancer management.

Dataset Information

Classification of human cancers based on DNA copy number amplification modeling.

Publications

Classification of human cancers based on DNA copy number amplification modeling.

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