Dataset Information

Coregulation of FANCA and BRCA1 in human cells.

ABSTRACT: Fanconi anemia (FA) is a genetically heterogeneous syndrome associated with increased cancer predisposition. The underlying genes govern the FA pathway which functions to protect the genome during the S-phase of the cell cycle. While upregulation of FA genes has been linked to chemotherapy resistance, little is known about their regulation in response to proliferative stimuli. The purpose of this study was to examine how FA genes are regulated, especially in relation to the cell cycle, in order to reveal their possible participation in biochemical networks. Expression of 14 FA genes was monitored in two human cell-cycle models and in two RB1/E2F pathway-associated primary cancers, retinoblastoma and basal breast cancer. In silico studies were performed to further evaluate coregulation and identify connected networks and diseases. Only FANCA was consistently induced over 2-fold; FANCF failed to exhibit any regulatory fluctuations. Two tools exploiting public data sets indicated coregulation of FANCA with BRCA1. Upregulation of FANCA and BRCA1 correlated with upregulation of E2F3. Genes coregulated with both FANCA and BRCA1 were enriched for MeSH-Term id(s) genomic instability, microcephaly, and Bloom syndrome, and enriched for the cellular component centrosome. The regulation of FA genes appears highly divergent. In RB1-linked tumors, upregulation of FA network genes was associated with reduced expression of FANCF. FANCA and BRCA1 may jointly act in a subnetwork - supporting vital function(s) at the subcellular level (centrosome) as well as at the level of embryonic development (mechanisms controlling head circumference).

SUBMITTER: Haitjema A

PROVIDER: S-EPMC4143540 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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Coregulation of FANCA and BRCA1 in human cells.

Haitjema Anneke A Mol Berber M BM Kooi Irsan E IE Massink Maarten Pg MP Jørgensen Jens Al JA Rockx Davy Ap DA Rooimans Martin A MA de Winter Johan P JP Meijers-Heijboer Hanne H Joenje Hans H Dorsman Josephine C JC

SpringerPlus 20140728

Fanconi anemia (FA) is a genetically heterogeneous syndrome associated with increased cancer predisposition. The underlying genes govern the FA pathway which functions to protect the genome during the S-phase of the cell cycle. While upregulation of FA genes has been linked to chemotherapy resistance, little is known about their regulation in response to proliferative stimuli. The purpose of this study was to examine how FA genes are regulated, especially in relation to the cell cycle, in order ...[more]

PMID: 25161863

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Project description:The majority of genes associated with breast cancer susceptibility, including BRCA1 and BRCA2 genes, are involved in DNA repair mechanisms. Moreover, among the genes recently associated with an increased susceptibility to breast cancer, four are Fanconi Anemia (FA) genes: FANCD1/BRCA2, FANCJ/BACH1/BRIP1, FANCN/PALB2 and FANCO/RAD51C. FANCA is implicated in DNA repair and has been shown to interact directly with BRCA1. It has been proposed that the formation of FANCA/G (dependent upon the phosphorylation of FANCA) and FANCB/L sub-complexes altogether with FANCM, represent the initial step for DNA repair activation and subsequent formation of other sub-complexes leading to ubiquitination of FANCD2 and FANCI. As only approximately 25% of inherited breast cancers are attributable to BRCA1/2 mutations, FANCA therefore becomes an attractive candidate for breast cancer susceptibility. We thus analyzed FANCA gene in 97 high-risk French Canadian non-BRCA1/2 breast cancer individuals by direct sequencing as well as in 95 healthy control individuals from the same population. Among a total of 85 sequence variants found in either or both series, 28 are coding variants and 19 of them are missense variations leading to amino acid change. Three of the amino acid changes, namely Thr561Met, Cys625Ser and particularly Ser1088Phe, which has been previously reported to be associated with FA, are predicted to be damaging by the SIFT and PolyPhen softwares. cDNA amplification revealed significant expression of 4 alternative splicing events (insertion of an intronic portion of intron 10, and the skipping of exons 11, 30 and 31). In silico analyzes of relevant genomic variants have been performed in order to identify potential variations involved in the expression of these spliced transcripts. Sequence variants in FANCA could therefore be potential spoilers of the Fanconi-BRCA pathway and as a result, they could in turn have an impact in non-BRCA1/2 breast cancer families.

Project description:Transcriptional regulation is critical to cellular processes of all organisms. Regulatory mechanisms often involve more than one transcription factor (TF) from different families, binding together and attaching to the DNA as a single complex. However, only a fraction of the regulatory partners of each TF is currently known. In this paper, we present the Transcriptional Interaction and Coregulation Analyzer (TICA), a novel methodology for predicting heterotypic physical interaction of TFs. TICA employs a data-driven approach to infer interaction phenomena from chromatin immunoprecipitation and sequencing (ChIP-seq) data. Its prediction rules are based on the distribution of minimal distance couples of paired binding sites belonging to different TFs which are located closest to each other in promoter regions. Notably, TICA uses only binding site information from input ChIP-seq experiments, bypassing the need to do motif calling on sequencing data. We present our method and test it on ENCODE ChIP-seq datasets, using three cell lines as reference including HepG2, GM12878, and K562. TICA positive predictions on ENCODE ChIP-seq data are strongly enriched when compared to protein complex (CORUM) and functional interaction (BioGRID) databases. We also compare TICA against both motif/ChIP-seq based methods for physical TF-TF interaction prediction and published literature. Based on our results, TICA offers significant specificity (average 0.902) while maintaining a good recall (average 0.284) with respect to CORUM, providing a novel technique for fast analysis of regulatory effect in cell lines. Furthermore, predictions by TICA are complementary to other methods for TF-TF interaction prediction (in particular, TACO and CENTDIST). Thus, combined application of these prediction tools results in much improved sensitivity in detecting TF-TF interactions compared to TICA alone (sensitivity of 0.526 when combining TICA with TACO and 0.585 when combining with CENTDIST) with little compromise in specificity (specificity 0.760 when combining with TACO and 0.643 with CENTDIST). TICA is publicly available at http://geco.deib.polimi.it/tica/.

Dataset Information

Coregulation of FANCA and BRCA1 in human cells.

Publications

Coregulation of FANCA and BRCA1 in human cells.

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