Dataset Information

Signatures of selection in fusion transcripts resulting from chromosomal translocations in human cancer.

ABSTRACT: BACKGROUND: The recurrence and non-random distribution of translocation breakpoints in human tumors are usually attributed to local sequence features present in the vicinity of the breakpoints. However, it has also been suggested that functional constraints might contribute to delimit the position of translocation breakpoints within the genes involved, but a quantitative analysis of such contribution has been lacking. METHODOLOGY: We have analyzed two well-known signatures of functional selection, such as reading-frame compatibility and non-random combinations of protein domains, on an extensive dataset of fusion proteins resulting from chromosomal translocations in cancer. CONCLUSIONS: Our data provide strong experimental support for the concept that the position of translocation breakpoints in the genome of cancer cells is determined, to a large extent, by the need to combine certain protein domains and to keep an intact reading frame in fusion transcripts. Additionally, the information that we have assembled affords a global view of the oncogenic mechanisms and domain architectures that are used by fusion proteins. This can be used to assess the functional impact of novel chromosomal translocations and to predict the position of breakpoints in the genes involved.

SUBMITTER: Ortiz de Mendibil I

PROVIDER: S-EPMC2653638 | biostudies-literature | 2009

REPOSITORIES: biostudies-literature

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Signatures of selection in fusion transcripts resulting from chromosomal translocations in human cancer.

Ortiz de Mendíbil Iñigo I Vizmanos José L JL Novo Francisco J FJ

PloS one 20090312 3

<h4>Background</h4>The recurrence and non-random distribution of translocation breakpoints in human tumors are usually attributed to local sequence features present in the vicinity of the breakpoints. However, it has also been suggested that functional constraints might contribute to delimit the position of translocation breakpoints within the genes involved, but a quantitative analysis of such contribution has been lacking.<h4>Methodology</h4>We have analyzed two well-known signatures of functi ...[more]

PMID: 19279687

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Project description:Reciprocal chromosomal translocations (RCTs) leading to the formation of fusion genes are important drivers of hematological cancers. Although the general requirements for breakage and fusion are fairly well understood, quantitative support for a general mechanism of RCT formation is still lacking. The aim of this paper is to analyze available high-throughput datasets with computational and robust statistical methods, in order to identify genomic hallmarks of translocation partner genes (TPGs). Our results show that fusion genes are generally overexpressed due to increased promoter activity of 5' TPGs and to more stable 3'-UTR regions of 3' TPGs. Furthermore, expression profiling of 5' TPGs and of interaction partners of 3' TPGs indicates that these features can help to explain tissue specificity of hematological translocations. Analysis of protein domains retained in fusion proteins shows that the co-occurrence of specific domain combinations is non-random and that distinct functional classes of fusion proteins tend to be associated with different components of the gene fusion network. This indicates that the configuration of fusion proteins plays an important role in determining which 5' and 3' TPGs will combine in specific fusion genes. It is generally accepted that chromosomal proximity in the nucleus can explain the specific pairing of 5' and 3' TPGS and the recurrence of hematological translocations. Using recently available data for chromosomal contact probabilities (Hi-C) we show that TPGs are preferentially located in early replicated regions and occupy distinct clusters in the nucleus. However, our data suggest that, in general, nuclear position of TPGs in hematological cancers explains neither TPG pairing nor clinical frequency. Taken together, our results support a model in which genomic features related to regulation of expression and replication timing determine the set of candidate genes more likely to be translocated in hematological tissues, with functional constraints being responsible for specific gene combinations.

Dataset Information

Signatures of selection in fusion transcripts resulting from chromosomal translocations in human cancer.

Publications

Signatures of selection in fusion transcripts resulting from chromosomal translocations in human cancer.

Similar Datasets

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