| Literature DB >> 28617445 |
Stefan Meyer1,2,3,4, Adam Stevens2,5, Roberto Paredes1,2, Marion Schneider1,2, Michael J Walker1,2, Andrew J K Williamson1,2, Maria-Belen Gonzalez-Sanchez1,2, Stephanie Smetsers6, Vineet Dalal1,2, Hsiang Ying Teng1,2, Daniel J White1,2, Sam Taylor1,2, Joanne Muter1,2, Andrew Pierce1,2, Chiara de Leonibus2,5, Davy A P Rockx6, Martin A Rooimans6, Elaine Spooncer1,2, Stacey Stauffer7, Kajal Biswas7, Barbara Godthelp8, Josephine Dorsman6, Peter E Clayton2,5, Shyam K Sharan7, Anthony D Whetton1,2,9.
Abstract
BRCA2 encodes a protein with a fundamental role in homologous recombination that is essential for normal development. Carrier status of mutations in BRCA2 is associated with familial breast and ovarian cancer, while bi-allelic BRCA2 mutations can cause Fanconi anemia (FA), a cancer predisposition syndrome with cellular cross-linker hypersensitivity. Cancers associated with BRCA2 mutations can acquire chemo-resistance on relapse. We modeled acquired cross-linker resistance with an FA-derived BRCA2-mutated acute myeloid leukemia (AML) platform. Associated with acquired cross-linker resistance was the expression of a functional BRCA2 protein variant lacking exon 5 and exon 7 (BRCA2ΔE5+7), implying a role for BRCA2 splicing for acquired chemo-resistance. Integrated network analysis of transcriptomic and proteomic differences for phenotyping of BRCA2 disruption infers impact on transcription and chromatin remodeling in addition to the DNA damage response. The striking overlap with transcriptional profiles of FA patient hematopoiesis and BRCA mutation associated ovarian cancer helps define and explicate the 'BRCAness' profile.Entities:
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Year: 2017 PMID: 28617445 PMCID: PMC5520920 DOI: 10.1038/cddis.2017.264
Source DB: PubMed Journal: Cell Death Dis Impact factor: 8.469
Figure 1(a) MMC growth inhibition. FA-derived AML cells SB1690CB and progeny cell line SBRes were grown with increasing MMC concentrations and without MMC, and counted when untreated cultures had undergone three population doublings. Cell cultures with an IC50 of 10 nM or less were considered MMC sensitive in the FA range. Dose response analysis of sensitive and resistant cells to camptothecin (b) and cisplatin (c). Statistical analysis: Two way-ANOVA and Bonferroni post-test, *P<0.05. **P<0.01, ***P<0.001. FANCD2-mutated FA-disrupted CB1665 cells, and BRCA2-competent K562 cells were used as controls
Figure 2(a) Immunofluorescence (IF) analysis of RAD51. RAD1 foci induction by IF after MMC treatment in MMC sensitive SB1690CB, MMC-resistant SBRes and BRCA2 competent K562 control cells. Absence of foci in SB1690CB, and presence of foci in SBRes and control K562 cells as indicated. γH2AX foci formation as control for DNA damage. (b) Numerical evaluation of RAD51 foci induction after MMC comparing sensitive SB1690CB cells and resistant SBRes cells (statistical analysis: One way-ANOVA and Tukey post-test *P<0.05, **P<0.01). Increase of γH2AX foci formation after MMC as control for DNA damage. (c) Western blot analysis of BRCA2. Antibody recognizing the BRCA2 epitope as indicated (upper panel) for western blot analysis of BRCA2 in MMC sensitive SB1690CB cells, SRes cells with acquired MMC résistance. HEK293 as BRCA2-WT and CAPAN1 cells as negative control for full-length BRCA2. (d) Quantification of BRCA2 signal from four biological repeats (statistical analysis: T-test, **P<0.01)
Figure 3(a) Electrophoresis of cDNA amplicons of IVS7 transcripts. Primer oligonucleotides flanking exon 2 and 9 were used to amplify cDNA from SB1690CB (right lane)[12] and MMC-resistant pedigree SBRes (middle lane). Additional band (Del E5+7), indicating an additional dominant transcript in SBRes, and a dominant smaller transcript in SB1690CB, Del 4–7. (b) cDNA sequence of BRCA2Δ5+7 showing exon/exon boundaries between exon 4 and 6, and 6 and 8
Figure 4BRCA2 Δ5+7 expression and functional analysis in mouse ES cells. (a) Sequence of the region containing exons 5 and 7 and the flanking intronic regions deleted from BRCA2. (b) RT-PCR analysis of BRCA2 transcripts in mouse ES cells expressing WT and Δ5+7 BRCA2 transgene using primers from exons 2 and 9. (c) Sequence analysis of the 623bp RT-PCR fragment that lacks exons 5 and 7. (d) Southern blot analysis of HATr ES cell colonies obtained after Cre-mediated deletion of the conditional of BRCA2. The upper band corresponds to the conditional allele (cko), and the lower band corresponds to the mutant allele (ko). The sizes of the bands are shown on the left. (e) Detection of conditionally expressed BRCA2 by immunoblot. (f) XTT assay of cells expressing WT or Δ5+7 mutant BRCA2 (C4/F4 and D1/D3) following 48 h of treatment with MMC, cisplatin, camptothecin, MMS and γ-irradiation (IR) to examine their sensitivity to these DNA-damaging agents. (g) Efficiency of homologous recombination (HR) measure by using DR-GFP reporter after generation of I-SceI induced double strand break. Graph shows the percentage of GFP positive cells in WT and two Δ5+7 mutant clones (C4/F4 and D1/D3)
Figure 5Mass spectrometric detection of the BRCA2Δ5+7 protein. (a) Schematic illustration of WT-BRCA2 (upper panel) and BRCA2Δ5+7 protein (lower panel) with putative unique trypsin digestion sites. Amino acid sequence derived for the shifted reading frame of the exon 6 is indicated in purple. (b) Gel electrophoresis and gel slice selection (dotted square) of chromatin fractions of SBRes used for trypsin digestion, tryptic peptides isolation and subsequent mass spectrometry analysis. (c) Targeted mass spectrometry SRM spectrum for the splice variant-specific peptide MDQADDVSCPLLNSCLSESGMWEFVSYTK detecting ten co-eluting fragment ions (color coded lines, left insert). A reconstituted spectrum using the SRM data is also shown (right insert). b ions (blue) and y ions (red) are annotated related to the peptide sequence
Figure 6Expression phenotype of acquired MMC resistance. (a) Heat map illustration of differential gene expression between MMC-resistant and MMC-sensitive cells with and without MMC treatment (2MMol). 3828 differentially expressed genes (group ANOVA P<0.05) were identified. Clustering of the data within the heat map delineated distinct groups of gene expression patterns differentiating the MMC-resistant and sensitive states as indicated (total of 510 genes). Corresponding lists are provided in Supplementary Tables. (b) Numerical Venn diagram illustration of transcriptomic analysis (left, P<0.01), proteomic (middle) and phosphoproteomic (right) analysis comparing sensitive and resistant cell lines with and without MMC split into up and downregulated transcripts/proteins/phosphopeptides. Corresponding lists are provided in Supplementary Material
Figure 7Integrated analysis defining differences between resistant and sensitive cells untreated and in response to Mitomycin C (MMC). (a) Network modules delineated by inferred interactions from integrated analysis of transcriptional, proteomic and phosphoproteomic differences between untreated sensitive and resistant cells. The network modules were delineated and ranked by network centrality applying the Moduland community clustering approach. (b) Quantitative characterization of network modules delineated from integrated analysis of acquired cross-linker resistance, by defining differences in observed connectivity in relation to the expected connectivity in the human interactome (BioGRID). Odds ratio, 95% confidence intervals and p-values generated using Fisher’s exact test. (c) Network dimensions and changes in response to MMC. Changes affecting the three dimensions of the integrated data (transcriptome, upper level; proteome, middle level; phosphoproteome, lower level) of untreated cells (left panel) were mapped to the central units of each network module in hierarchical order; downregulated transcription and decreased protein expression/phosphorylation in green; up-regulated transcription, higher levels of protein expression and presence of phosphorylation in red. Cartoon besides panels: In response to environmental changes modules can remain, but the position in the hierarchy can change, split into new clusters or dissolve. The effects on the network of MMC treatment are illustrated (right panel), with delineation of novel clusters dominated by SUMO, AKT1, EP300, YWHAC and SMARCA2, splitting and resoling clusters as indicated. (d) Statistical and ontological characterization of clusters and dominating network modules for untreated cells (upper panel) and in response to MMC (lower panel)
Figure 8Evaluation of BRCA2 disruption-associated transcriptional phenotype with transcriptional patterns of clinical samples. (a) Heat map showing expression of transcripts relating to dominating transcriptional network modules delineated in gene expression data of bone marrow samples from FA patients compared with unaffected controls as GEO data set GSE16334.[21] (b) Analysis of these transcripts in FA-derived MMC sensitive SB1690CB cells and their resistant SBRes progeny. (c) Heat map showing BRCA disruption-associated genes in clinical ovarian cancer[6] in sensitive SB1690CB Cells compared with their resistant SBRes progeny. Significantly differentially expressed transcripts framed in yellow boxes