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Human rDNA copy number is unstable in metastatic breast cancers.

ABSTRACT: Chromatin-mediated silencing, including the formation of heterochromatin, silent chromosome territories, and repressed gene promoters, acts to stabilize patterns of gene regulation and the physical structure of the genome. Reduction of chromatin-mediated silencing can result in genome rearrangements, particularly at intrinsically unstable regions of the genome such as transposons, satellite repeats, and repetitive gene clusters including the rRNA gene clusters (rDNA). It is thus expected that mutational or environmental conditions that compromise heterochromatin function might cause genome instability, and diseases associated with decreased epigenetic stability might exhibit genome changes as part of their aetiology. We find the support of this hypothesis in invasive ductal breast carcinoma, in which reduced epigenetic silencing has been previously described, by using a facile method to quantify rDNA copy number in biopsied breast tumours and pair-matched healthy tissue. We found that rDNA and satellite DNA sequences had significant copy number variation - both losses and gains of copies - compared to healthy tissue, arguing that these genome rearrangements are common in developing breast cancer. Thus, any proposed aetiology onset or progression of breast cancer should consider alterations to the epigenome, but must also accommodate concomitant changes to genome sequence at heterochromatic loci.

SUBMITTER: Valori V

PROVIDER: S-EPMC6961696 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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.

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Human rDNA copy number is unstable in metastatic breast cancers.

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