Loss of Tankyrase-mediated destruction of 3BP2 is the underlying pathogenic mechanism of cherubism.

Cherubism is an autosomal-dominant syndrome characterized by inflammatory destructive bony lesions resulting in symmetrical deformities of the facial bones. Cherubism is caused by mutations in Sh3bp2, the gene that encodes the adaptor protein 3BP2. Most identified mutations in 3BP2 lie within the peptide sequence RSPPDG. A mouse model of cherubism develops hyperactive bone-remodeling osteoclasts and systemic inflammation characterized by expansion of the myelomonocytic lineage. The mechanism by which cherubism mutations alter 3BP2 function has remained obscure. Here we show that Tankyrase, a member of the poly(ADP-ribose)polymerase (PARP) family, regulates 3BP2 stability through ADP-ribosylation and subsequent ubiquitylation by the E3-ubiquitin ligase RNF146 in osteoclasts. Cherubism mutations uncouple 3BP2 from Tankyrase-mediated protein destruction, which results in its stabilization and subsequent hyperactivation of the SRC, SYK, and VAV signaling pathways.

Development and evaluation of a core genome multilocus sequence typing scheme for Paenibacillus larvae, the deadly American foulbrood pathogen of honeybees.

Paenibacillus larvae is the causative agent of the fatal American foulbrood disease in honeybees (Apis mellifera). Strain identification is vital for preventing the spread of the disease. To date, the most accessible and robust scheme to identify strains is the multilocus sequence typing (MLST) method. However, this approach has limited resolution, especially for epidemiological studies. As the cost of whole-genome sequencing has decreased and as it becomes increasingly available to most laboratories, an extended MLST based on the core genome (cgMLST) presents a valuable tool for high-resolution investigations. In this study, we present a standardized, robust cgMLST scheme for P. larvae typing using whole-genome sequencing. A total of 333 genomes were used to identify, validate and evaluate 2419 core genes. The cgMLST allowed fine-scale differentiation between samples that had the same profile using traditional MLST and allowed for the characterization of strains impossible by MLST. The scheme was successfully used to trace a localized Swedish outbreak, where a cluster of 38 isolates was linked to a country-wide beekeeping operation. cgMLST greatly enhances the power of a traditional typing scheme, while preserving the same stability and standardization for sharing results and methods across different laboratories.

Low junctional adhesion molecule-A expression is associated with an epithelial to mesenchymal transition and poorer outcomes in high-grade serous carcinoma of uterine adnexa.

High-grade serous carcinoma of uterine adnexa (HGSC) is the most frequent histotype of epithelial ovarian cancer and has a poor 5-year survival rate due to late-stage diagnosis and the poor efficacy of standard treatments. Novel biomarkers of cancer outcome are needed to identify new targetable pathways and improve personalized treatments. Cell-surface screening of 26 HGSC cell lines by high-throughput flow cytometry identified junctional adhesion molecule 1 (JAM-A, also known as F11R) as a potential biomarker. Using a multi-labeled immunofluorescent staining coupled with digital image analysis, protein levels of JAM-A were quantified in tissue microarrays from three HGSC patient cohorts: a discovery cohort (n = 101), the Canadian Ovarian Experimental Unified Resource cohort (COEUR, n = 1158), and the Canadian Cancer Trials Group OV16 cohort (n = 267). Low JAM-A level was associated with poorer outcome in the three cohorts by Kaplan-Meier (p = 0.023, p < 0.001, and p = 0.036, respectively) and was an independent marker of shorter survival in the COEUR cohort (HR = 0.517 (0.381-703), p < 0.001). When analyses were restricted to patients treated by taxane-platinum-based chemotherapy, low JAM-A protein expression was associated with poorer responses in the COEUR (p < 0.001) and OV16 cohorts (p = 0.006) by Kaplan-Meier. Decreased JAM-A gene expression was an indicator of poor outcome in gene expression datasets including The Cancer Genome Atlas (n = 606, p = 0.002) and Kaplan-Meier plotter (n = 1816, p = 0.024). Finally, we observed that tumors with decreased JAM-A expression exhibited an enhanced epithelial to mesenchymal transition (EMT) signature. Our results demonstrate that JAM-A expression is a robust prognostic biomarker of HGSC and may be used to discriminate tumors responsive to therapies targeting EMT.

Measuring error rates in genomic perturbation screens: gold standards for human functional genomics.

Technological advancement has opened the door to systematic genetics in mammalian cells. Genome-scale loss-of-function screens can assay fitness defects induced by partial gene knockdown, using RNA interference, or complete gene knockout, using new CRISPR techniques. These screens can reveal the basic blueprint required for cellular proliferation. Moreover, comparing healthy to cancerous tissue can uncover genes that are essential only in the tumor; these genes are targets for the development of specific anticancer therapies. Unfortunately, progress in this field has been hampered by off-target effects of perturbation reagents and poorly quantified error rates in large-scale screens. To improve the quality of information derived from these screens, and to provide a framework for understanding the capabilities and limitations of CRISPR technology, we derive gold-standard reference sets of essential and nonessential genes, and provide a Bayesian classifier of gene essentiality that outperforms current methods on both RNAi and CRISPR screens. Our results indicate that CRISPR technology is more sensitive than RNAi and that both techniques have nontrivial false discovery rates that can be mitigated by rigorous analytical methods.

CaPSID: a bioinformatics platform for computational pathogen sequence identification in human genomes and transcriptomes.

BACKGROUND: It is now well established that nearly 20% of human cancers are caused by infectious agents, and the list of human oncogenic pathogens will grow in the future for a variety of cancer types. Whole tumor transcriptome and genome sequencing by next-generation sequencing technologies presents an unparalleled opportunity for pathogen detection and discovery in human tissues but requires development of new genome-wide bioinformatics tools. RESULTS: Here we present CaPSID (Computational Pathogen Sequence IDentification), a comprehensive bioinformatics platform for identifying, querying and visualizing both exogenous and endogenous pathogen nucleotide sequences in tumor genomes and transcriptomes. CaPSID includes a scalable, high performance database for data storage and a web application that integrates the genome browser JBrowse. CaPSID also provides useful metrics for sequence analysis of pre-aligned BAM files, such as gene and genome coverage, and is optimized to run efficiently on multiprocessor computers with low memory usage. CONCLUSIONS: To demonstrate the usefulness and efficiency of CaPSID, we carried out a comprehensive analysis of both a simulated dataset and transcriptome samples from ovarian cancer. CaPSID correctly identified all of the human and pathogen sequences in the simulated dataset, while in the ovarian dataset CaPSID's predictions were successfully validated in vitro.

Loss, mutation and deregulation of L3MBTL4 in breast cancers.

BACKGROUND: Many alterations are involved in mammary oncogenesis, including amplifications of oncogenes and losses of tumor suppressor genes (TSG). Losses may affect almost all chromosome arms and many TSGs remain to be identified. RESULTS: We studied 307 primary breast tumors and 47 breast cancer cell lines by high resolution array comparative genomic hybridization (aCGH). We identified a region on 18p11.31 lost in about 20% of the tumors and 40% of the cell lines. The minimal common region of loss (Chr18:6,366,938-6,375,929 bp) targeted the L3MBTL4 gene. This gene was also targeted by breakage in one tumor and in two cell lines. We studied the exon sequence of L3MBTL4 in 180 primary tumor samples and 47 cell lines and found six missense and one nonsense heterozygous mutations. Compared with normal breast tissue, L3MBTL4 mRNA expression was downregulated in 73% of the tumors notably in luminal, ERBB2 and normal-like subtypes. Losses of the 18p11 region were associated with low L3MBTL4 expression level. Integrated analysis combining genome and gene expression profiles of the same tumors pointed to 14 other potential 18p TSG candidates. Downregulated expression of ZFP161, PPP4R1 and YES1 was correlated with luminal B molecular subtype. Low ZFP161 gene expression was associated with adverse clinical outcome. CONCLUSION: We have identified L3MBTL4 as a potential TSG of chromosome arm 18p. The gene is targeted by deletion, breakage and mutations and its mRNA is downregulated in breast tumors. Additional 18p TSG candidates might explain the aggressive phenotype associated with the loss of 18p in breast tumors.

Genome profiling of ERBB2-amplified breast cancers.

BACKGROUND: Around 20% of breast cancers (BC) show ERBB2 gene amplification and overexpression of the ERBB2 tyrosine kinase receptor. They are associated with a poor prognosis but can benefit from targeted therapy. A better knowledge of these BCs, genomically and biologically heterogeneous, may help understand their behavior and design new therapeutic strategies. METHODS: We defined the high resolution genome and gene expression profiles of 54 ERBB2-amplified BCs using 244K oligonucleotide array-comparative genomic hybridization and whole-genome DNA microarrays. Expression of ERBB2, phosphorylated ERBB2, EGFR, IGF1R and FOXA1 proteins was assessed by immunohistochemistry to evaluate the functional ERBB2 status and identify co-expressions. RESULTS: First, we identified the ERBB2-C17orf37-GRB7 genomic segment as the minimal common 17q12-q21 amplicon, and CRKRS and IKZF3 as the most frequent centromeric and telomeric amplicon borders, respectively. Second, GISTIC analysis identified 17 other genome regions affected by copy number aberration (CNA) (amplifications, gains, losses). The expression of 37 genes of these regions was deregulated. Third, two types of heterogeneity were observed in ERBB2-amplified BCs. The genomic profiles of estrogen receptor-positive (ER+) and negative (ER-) ERBB2-amplified BCs were different. The WNT/ß-catenin signaling pathway was involved in ER- ERBB2-amplified BCs, and PVT1 and TRPS1 were candidate oncogenes associated with ER+ ERBB2-amplified BCs. The size of the ERBB2 amplicon was different in inflammatory (IBC) and non-inflammatory BCs. ERBB2-amplified IBCs were characterized by the downregulated and upregulated mRNA expression of ten and two genes in proportion to CNA, respectively. IHC results showed (i) a linear relationship between ERBB2 gene amplification and its gene and protein expressions with a good correlation between ERBB2 expression and phosphorylation status; (ii) a potential signaling cross-talk between EGFR or IGF1R and ERBB2, which could influence response of ERBB2-positive BCs to inhibitors. FOXA1 was frequently coexpressed with ERBB2 but its expression did not impact on the outcome of patients with ERBB2-amplified tumors. CONCLUSION: We have shown that ER+ and ER- ERBB2-amplified BCs are different, distinguished ERBB2 amplicons in IBC and non-IBC, and identified genomic features that may be useful in the design of alternative therapeutical strategies.

A reason why the ERBB2 gene is amplified and not mutated in breast cancer.

Alterations of receptor-type tyrosine kinases (RTK) are frequent in human cancers. They can result from translocation, mutation or amplification. The ERBB2 RTK is encoded by a gene that is amplified in about 20% breast cancers. The question is: why is this RTK specifically subjected to this type of alteration? We propose that ERBB2 gene amplification is used to overcome repression of its expression by sequence-specific transcription factors.

Validation of quantitative real-time RT-PCR assays for the detection of six honeybee viruses.

Acute bee paralysis virus (ABPV), Black queen cell virus (BQCV), Chronic bee paralysis virus (CBPV), Deformed wing virus (DWV), Sacbrood virus (SBV) and Varroa destructor virus 1 (VDV1) are the six main honeybee viruses reported in Europe. We assessed the accuracy (trueness and precision) of reverse transcriptase quantitative TaqMan® PCR methods (RT-qPCR) for quantifying ABPV, BQCV, DWV, VDV1 and SBV loads. Once the systematic bias in quantitative results had been corrected (overestimation in ABPV and BQCV quantification and underestimation in that of SBV and VDV1), measurements were taken to determine the viral load ranges for which quantification uncertainty was below ± 1 log10 equivalent of genome copies per bee (hereafter reported as genome copies/bee). The accuracy range of RT-qPCR was found to be between 6.4 and 10.4 log10 genome copies/bee for ABPV, between 3.0 and 10.0 log10 genome copies/bee for BQCV, between 2.4 and 10.4 log10 genome copies/bee for DWV and between 3.4 and 10.4 log10 genome copies/bee for SBV. Outside these ranges, the results' uncertainty is higher. VDV1 RT-qPCR accuracy was outside accuracy limits for all viral loads. Using these RT-qPCR methods, we quantified viral loads in naturally-infected honeybees. The viral load distribution and clinical signs reported with the honeybee samples allowed us to define a threshold that could be used to differentiate between covert and overt infections. These methods will be useful in diagnosing the main viral infections impairing honeybee health.

Chromosomal Instability and mTORC1 Activation through PTEN Loss Contribute to Proteotoxic Stress in Ovarian Carcinoma.

High-grade serous ovarian carcinoma commonly arises from fallopian tube secretory epithelium and is characterized by a high level of chromosomal instability. To model the acquisition of aneuploidy during early carcinogenesis, chromosome missegregation was induced in immortalized tubal epithelial cells, which proved acutely detrimental to cellular fitness. The phenotype was characterized by accumulation of misfolded proteins, activation of the unfolded protein response (UPR), decreased protein synthesis, and enhanced vulnerability to proteasome inhibition. However, chromosome missegregation also resulted in heightened transformation potential, assessed by colony formation in soft agar. Ovarian cancer cells retained intrinsic sensitivity to proteasome inhibitors under adherent culture conditions, but acquired resistance as spheroids (recapitulating their native configuration in ascites) by downregulating protein synthesis via mTORC1 suppression. Loss of PTEN drove constitutive mTORC1 activity, enhanced proteotoxic stress, as evidenced by UPR induction, and resensitized tumor spheroids to proteasome inhibition both in vitro and in vivo. In cohorts of primary ovarian carcinomas, mTORC1 and UPR signaling pathways were closely associated. These results implicate attenuation of protein synthesis as a protective mechanism in tumor spheroids, which may explain the overall poor response to bortezomib in clinical trials of patients with advanced ovarian cancer. However, patients with PTEN-deficient tumors may represent a subpopulation potentially amenable to treatment with proteasome inhibitors or other therapeutic agents that disrupt protein homeostasis. SIGNIFICANCE: Chromosome instability and protein synthesis are important factors that determine the efficacy of proteotoxic stress-inducing agents, such as proteasome inhibitors, in the treatment of ovarian cancer.Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/79/21/5536/F1.large.jpg.

Regional perturbation of gene transcription is associated with intrachromosomal rearrangements and gene fusion transcripts in high grade ovarian cancer.

Genomic rearrangements are a hallmark of cancer biology and progression, allowing cells to rapidly transform through alterations in regulatory structures, changes in expression patterns, reprogramming of signaling pathways, and creation of novel transcripts via gene fusion events. Though functional gene fusions encoding oncogenic proteins are the most dramatic outcomes of genomic rearrangements, we investigated the relationship between rearrangements evidenced by fusion transcripts and local expression changes in cancer using transcriptome data alone. 9,953 gene fusion predictions from 418 primary serious ovarian cancer tumors were analyzed, identifying depletions of gene fusion breakpoints within coding regions of fused genes as well as an N-terminal enrichment of breakpoints within fused genes. We identified 48 genes with significant fusion-associated upregulation and furthermore demonstrate that significant regional overexpression of intact genes in patient transcriptomes occurs within 1 megabase of 78 novel gene fusions that function as central markers of these regions. We reveal that cancer transcriptomes select for gene fusions that preserve protein and protein domain coding potential. The association of gene fusion transcripts with neighboring gene overexpression supports rearrangements as mechanism through which cancer cells remodel their transcriptomes and identifies a new way to utilize gene fusions as indicators of regional expression changes in diseased cells with only transcriptomic data.

Interrogation of Functional Cell-Surface Markers Identifies CD151 Dependency in High-Grade Serous Ovarian Cancer.

The degree of genetic aberrations characteristic of high-grade serous ovarian cancer (HGSC) makes identification of the molecular features that drive tumor progression difficult. Here, we perform genome-wide RNAi screens and comprehensive expression analysis of cell-surface markers in a panel of HGSC cell lines to identify genes that are critical to their survival. We report that the tetraspanin CD151 contributes to survival of a subset of HGSC cell lines associated with a ZEB transcriptional program and supports the growth of HGSC tumors. Moreover, we show that high CD151 expression is prognostic of poor clinical outcome. This study reveals cell-surface vulnerabilities associated with HGSC, provides a framework for identifying therapeutic targets, and reports a role for CD151 in HGSC.

Comprehensive profiling of 8p11-12 amplification in breast cancer.

In human carcinomas, especially breast cancer, chromosome arm 8p is frequently involved in complex chromosomal rearrangements that combine amplification at 8p11-12, break in the 8p12-21 region, and loss of 8p21-ter. Several studies have identified putative oncogenes in the 8p11-12 amplicon. However, discrepancies and the lack of knowledge on the structure of this amplification lead us to think that the actual identity of the oncogenes is not definitively established. We present here a comprehensive study combining genomic, expression, and chromosome break analyses of the 8p11-12 region in breast cell lines and primary breast tumors. We show the existence of four amplicons at 8p11-12 using array comparative genomic hybridization. Gene expression analysis of 123 samples using DNA microarrays identified 14 genes significantly overexpressed in relation to amplification. Using fluorescence in situ hybridization analysis on tissue microarrays, we show the existence of a cluster of breakpoints spanning a region just telomeric to and associated with the amplification. Finally, we show that 8p11-12 amplification has a pejorative effect on survival in breast cancer.

Frequency, prognostic impact, and subtype association of 8p12, 8q24, 11q13, 12p13, 17q12, and 20q13 amplifications in breast cancers.

BACKGROUND: Oncogene amplification and overexpression occur in tumor cells. Amplification status may provide diagnostic and prognostic information and may lead to new treatment strategies. Chromosomal regions 8p12, 8q24, 11q13, 17q12 and 20q13 are recurrently amplified in breast cancers. METHODS: To assess the frequencies and clinical impact of amplifications, we analyzed 547 invasive breast tumors organized in a tissue microarray (TMA) by fluorescence in situ hybridization (FISH) and calculated correlations with histoclinical features and prognosis. BAC probes were designed for: (i) two 8p12 subregions centered on RAB11FIP1 and FGFR1 loci, respectively; (ii) 11q13 region centered on CCND1; (iii) 12p13 region spanning NOL1; and (iv) three 20q13 subregions centered on MYBL2, ZNF217 and AURKA, respectively. Regions 8q24 and 17q12 were analyzed with MYC and ERBB2 commercial probes, respectively. RESULTS: We observed amplification of 8p12 (amplified at RAB11FIP1 and/or FGFR1) in 22.8%, 8q24 in 6.1%, 11q13 in 19.6%, 12p13 in 4.1%, 17q12 in 9.9%, 20q13Z (amplified at ZNF217 only) in 9.9%, and 20q13Co (co-amplification of two or three 20q13 loci) in 8.5% of cases. The 8q24, 12p13, and 17q12 amplifications were correlated with high grade. The most frequent single amplifications were 8p12 (9.8%), 8q24 (3.3%) and 12p13 (3.3%), 20q13Z and 20q13Co (1.6%) regions. The 17q12 and 11q13 regions were never found amplified alone. The most frequent co-amplification was 8p12/11q13. Amplifications of 8p12 and 17q12 were associated with poor outcome. Amplification of 12p13 was associated with basal molecular subtype. CONCLUSION: Our results establish the frequencies, prognostic impacts and subtype associations of various amplifications and co-amplifications in breast cancers.

Essential gene profiles in breast, pancreatic, and ovarian cancer cells.

UNLABELLED: Genomic analyses are yielding a host of new information on the multiple genetic abnormalities associated with specific types of cancer. A comprehensive description of cancer-associated genetic abnormalities can improve our ability to classify tumors into clinically relevant subgroups and, on occasion, identify mutant genes that drive the cancer phenotype ("drivers"). More often, though, the functional significance of cancer-associated mutations is difficult to discern. Genome-wide pooled short hairpin RNA (shRNA) screens enable global identification of the genes essential for cancer cell survival and proliferation, providing a "functional genomic" map of human cancer to complement genomic studies. Using a lentiviral shRNA library targeting ~16,000 genes and a newly developed, dynamic scoring approach, we identified essential gene profiles in 72 breast, pancreatic, and ovarian cancer cell lines. Integrating our results with current and future genomic data should facilitate the systematic identification of drivers, unanticipated synthetic lethal relationships, and functional vulnerabilities of these tumor types. SIGNIFICANCE: This study presents a resource of genome-scale, pooled shRNA screens for 72 breast, pancreatic, and ovarian cancer cell lines that will serve as a functional complement to genomics data, facilitate construction of essential gene profiles, help uncover synthetic lethal relationships, and identify uncharacterized genetic vulnerabilities in these tumor types. SIGNIFICANCE: This study presents a resource of genome-scale, pooled shRNA screens for 72 breast, pancreatic, and ovarian cancer cell lines that will serve as a functional complement to genomics data, facilitate construction of essential gene profiles, help uncover synthetic lethal relationships, and identify uncharacterized genetic vulnerabilities in these tumor types.

ZNF703 gene amplification at 8p12 specifies luminal B breast cancer.

Luminal B breast cancers represent a fraction of oestrogen receptor (ER)-positive tumours associated with poor recurrence-free and disease-specific survival in all adjuvant systemic treatment categories including hormone therapy alone. Identification of specific signalling pathways driving luminal B biology is paramount to improve treatment. We have studied 100 luminal breast tumours by combined analysis of genome copy number aberrations and gene expression. We show that amplification of the ZNF703 gene, located in chromosomal region 8p12, preferentially occurs in luminal B tumours. We explored the functional role of ZNF703 in luminal B tumours by overexpressing ZNF703 in the MCF7 luminal cell line. Using mass spectrometry, we identified ZNF703 as a co-factor of a nuclear complex comprising DCAF7, PHB2 and NCOR2. ZNF703 expression results in the activation of stem cell-related gene expression leading to an increase in cancer stem cells. Moreover, we show that ZNF703 is implicated in the regulation of ER and E2F1 transcription factor. These findings point out the prominent role of ZNF703 in transcription modulation, stem cell regulation and luminal B oncogenesis.

Integrated profiling of basal and luminal breast cancers.

Basal and luminal are two molecular subtypes of breast cancer with opposite histoclinical features. We report a combined, high-resolution analysis of genome copy number and gene expression in primary basal and luminal breast cancers. First, we identified and compared genomic alterations in 45 basal and 48 luminal tumors by using 244K oligonucleotide array comparative genomic hybridization (aCGH). We found various genome gains and losses and rare high-level gene amplifications that may provide therapeutic targets. We show that gain of 10p is a new alteration in basal breast cancer and that a subregion of the 8p12 amplification is specific of luminal tumors. Rare high-level amplifications contained BCL2L2, CCNE, EGFR, FGFR2, IGF1R, NOTCH2, and PIK3CA. Potential gene breaks involved ETV6 and FLT3. Second, we analyzed both aCGH and gene expression profiles for 42 basal and 32 luminal breast cancers. The results support the existence of specific oncogenic pathways in basal and luminal breast cancers, involving several potential oncogenes and tumor suppressor genes (TSG). In basal tumors, 73 candidate oncogenes were identified in chromosome regions 1q21-23, 10p14, and 12p13 and 28 candidate TSG in regions 4q32-34 and 5q11-23. In luminal breast cancers, 33 potential oncogenes were identified in 1q21-23, 8p12-q21, 11q13, and 16p12-13 and 61 candidate TSG in 16q12-13, 16q22-24, and 17p13. HORMAD1 (P = 6.5 x 10(-5)) and ZNF703 (P = 7 x 10(-4)) were the most significant basal and luminal potential oncogenes, respectively. Finally, among 10p candidate oncogenes associated with basal subtype, we validated CDC123/C10orf7 protein as a basal marker.