BRIP-1 germline mutation and its role in colon cancer: presentation of two case reports and review of literature.

BackgroundHereditary colon cancer is characterized by the inheritance of an abnormal gene mutation which predisposes to malignancy. Recent advances in genomic medicine have identified mutations in "novel" genes as conferring an increased risk of colorectal cancer. Mutations in the BRIP1 gene (BRCA1 Interacting Protein C- terminal helicase 1) are known to increase the risk of ovarian and breast cancers, but this genes association with colon cancer has not been previously reported.Case presentationWe describe two patients with colon cancer whose tumor tissue were found to harbor BRIP1 mutations on analysis by next-generation sequencing. These patients were confirmed by analysis of lymphocytes to carry the mutation in the germline as well.ConclusionsThese case reports highlight a previously unreported association of BRIP1 germline mutations with colon cancer predisposition

SWIM: A computational tool to unveiling crucial nodes in complex biological networks

SWItchMiner (SWIM) is a wizard-like software implementation of a procedure, previously described, able to extract information contained in complex networks. Specifically, SWIM allows unearthing the existence of a new class of hubs, called "fight-club hubs", characterized by a marked negative correlation with their first nearest neighbors. Among them, a special subset of genes, called "switch genes", appears to be characterized by an unusual pattern of intra- and inter-module connections that confers them a crucial topological role, interestingly mirrored by the evidence of their clinic-biological relevance. Here, we applied SWIM to a large panel of cancer datasets from The Cancer Genome Atlas, in order to highlight switch genes that could be critically associated with the drastic changes in the physiological state of cells or tissues induced by the cancer development. We discovered that switch genes are found in all cancers we studied and they encompass protein coding genes and non-coding RNAs, recovering many known key cancer players but also many new potential biomarkers not yet characterized in cancer context. Furthermore, SWIM is amenable to detect switch genes in different organisms and cell conditions, with the potential to uncover important players in biologically relevant scenarios, including but not limited to human cancer

Extensive evolution of cereal ribosome-inactivating proteins translates into unique structural features, activation mechanisms, and physiological roles

Ribosome-inactivating proteins (RIPs) are a class of cytotoxic enzymes that can depurinate rRNAs thereby inhibiting protein translation. Although these proteins have also been detected in bacteria, fungi, and even some insects, they are especially prevalent in the plant kingdom. This review focuses on the RIPs from cereals. Studies on the taxonomical distribution and evolution of plant RIPs suggest that cereal RIPs have evolved at an enhanced rate giving rise to a large and heterogeneous RIP gene family. Furthermore, several cereal RIP genes are characterized by a unique domain architecture and the lack of a signal peptide. This advanced evolution of cereal RIPs translates into distinct structures, activation mechanisms, and physiological roles. Several cereal RIPs are characterized by activation mechanisms that include the proteolytic removal of internal peptides from the N-glycosidase domain, a feature not documented for non-cereal RIPs. Besides their role in defense against pathogenic fungi or herbivorous insects, cereal RIPs are also involved in endogenous functions such as adaptation to abiotic stress, storage, induction of senescence, and reprogramming of the translational machinery. The unique properties of cereal RIPs are discussed in this review paper

Genetic variation in genes interacting with BRCA1/2 and risk of breast cancer in Cypriot population.

Inability to correctly repair DNA damage is known to play a role in the development of breast cancer. Single nucleotide polymorphisms (SNPs) of DNA repair genes have been identified, which modify the DNA repair capacity, which in turn may affect the risk of developing breast cancer. To assess whether alterations in DNA repair genes contribute to breast cancer, we genotyped 62 SNPs in 29 genes in 1,109 Cypriot women with breast cancer and 1,177 age-matched healthy controls. Five SNPs were associated with breast cancer. SNPs rs13312840 and rs769416 in the NBS1 gene were associated with a decrease in breast cancer risk (OR TT vs. TC/CC = 0.58; 95% CI, 0.37-0.92; P = 0.019 and OR GG vs. GT/TT = 0.23, 95% CI 0.06-0.85, P = 0.017, respectively). The variant allele of MRE11A rs556477 was also associated with a reduced risk of developing the disease (OR AA vs. AG/GG = 0.76; 95% CI, 0.64-0.91; P = 0.0022). MUS81 rs545500 and PBOV1 rs6927706 SNPs were associated with an increased risk of developing breast cancer (OR GG vs. GC/CC = 1.21, 95% CI, 1.02-1.45; P = 0.031; OR AA vs. AG/GG = 1.53, 95% CI, 1.07-2.18; P = 0.019, respectively). Finally, haplotype-based tests identified significant associations between specific haplotypes in MRE11A and NBS1 genes and breast cancer risk. Further large-scale studies are needed to confirm these results

Pairwise gene GO-based measures for biclustering of high-dimensional expression data

Background: Biclustering algorithms search for groups of genes that share the same behavior under a subset of samples in gene expression data. Nowadays, the biological knowledge available in public repositories can be used to drive these algorithms to find biclusters composed of groups of genes functionally coherent. On the other hand, a distance among genes can be defined according to their information stored in Gene Ontology (GO). Gene pairwise GO semantic similarity measures report a value for each pair of genes which establishes their functional similarity. A scatter search-based algorithm that optimizes a merit function that integrates GO information is studied in this paper. This merit function uses a term that addresses the information through a GO measure. Results: The effect of two possible different gene pairwise GO measures on the performance of the algorithm is analyzed. Firstly, three well known yeast datasets with approximately one thousand of genes are studied. Secondly, a group of human datasets related to clinical data of cancer is also explored by the algorithm. Most of these data are high-dimensional datasets composed of a huge number of genes. The resultant biclusters reveal groups of genes linked by a same functionality when the search procedure is driven by one of the proposed GO measures. Furthermore, a qualitative biological study of a group of biclusters show their relevance from a cancer disease perspective. Conclusions: It can be concluded that the integration of biological information improves the performance of the biclustering process. The two different GO measures studied show an improvement in the results obtained for the yeast dataset. However, if datasets are composed of a huge number of genes, only one of them really improves the algorithm performance. This second case constitutes a clear option to explore interesting datasets from a clinical point of view.Ministerio de Economía y Competitividad TIN2014-55894-C2-

No evidence that protein truncating variants in BRIP1 are associated with breast cancer risk: implications for gene panel testing.

BACKGROUND: BRCA1 interacting protein C-terminal helicase 1 (BRIP1) is one of the Fanconi Anaemia Complementation (FANC) group family of DNA repair proteins. Biallelic mutations in BRIP1 are responsible for FANC group J, and previous studies have also suggested that rare protein truncating variants in BRIP1 are associated with an increased risk of breast cancer. These studies have led to inclusion of BRIP1 on targeted sequencing panels for breast cancer risk prediction. METHODS: We evaluated a truncating variant, p.Arg798Ter (rs137852986), and 10 missense variants of BRIP1, in 48 144 cases and 43 607 controls of European origin, drawn from 41 studies participating in the Breast Cancer Association Consortium (BCAC). Additionally, we sequenced the coding regions of BRIP1 in 13 213 cases and 5242 controls from the UK, 1313 cases and 1123 controls from three population-based studies as part of the Breast Cancer Family Registry, and 1853 familial cases and 2001 controls from Australia. RESULTS: The rare truncating allele of rs137852986 was observed in 23 cases and 18 controls in Europeans in BCAC (OR 1.09, 95% CI 0.58 to 2.03, p=0.79). Truncating variants were found in the sequencing studies in 34 cases (0.21%) and 19 controls (0.23%) (combined OR 0.90, 95% CI 0.48 to 1.70, p=0.75). CONCLUSIONS: These results suggest that truncating variants in BRIP1, and in particular p.Arg798Ter, are not associated with a substantial increase in breast cancer risk. Such observations have important implications for the reporting of results from breast cancer screening panels.The COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175). BCAC is funded by Cancer Research UK [C1287/A10118, C1287/A12014] and by the European Community´s Seventh Framework Programme under grant agreement number 223175 (grant number HEALTH-F2-2009-223175) (COGS). Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement n° 223175 (HEALTH-F2-2009-223175) (COGS), Cancer Research UK (C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565), the National Institutes of Health (CA128978) and Post-Cancer GWAS initiative (1U19 CA148537, 1U19 16 CA148065 and 1U19 CA148112 - the GAME-ON initiative), the Department of Defense (W81XWH-10-1- 0341), the Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. This study made use of data generated by the Wellcome Trust Case Control consortium. Funding for the project was provided by the Wellcome Trust under award 076113. The results published here are in part based upon data generated by The Cancer Genome Atlas Project established by the National Cancer Institute and National Human Genome Research Institute.This is the author accepted manuscript. The final version is available from BMJ Group at http://dx.doi.org/10.1136/jmedgenet-2015-103529

CHARACTERISTICS OF INDIVIDUALS UNDERGOING PANEL GENETIC TESTING FOR PRIMARY BRAIN TUMORS

Background. Currently, there are no genetic testing guidelines for patients with a primary brain tumor (PBT). This population is largely understudied in terms of the family history, tumor grade, pathology, and their relation to genetic contribution. Our aim was to describe patient-specific characteristics and family histories across mutation-positive, negative, and variant of uncertain significance (VUS) cohorts based on cancer-panel genetic test results among patients with a PBT. Methods. Subjects were referred for multi-gene panel testing between March 2012 and June 2016. Clinical data were ascertained from test requisition forms. The incidence of pathogenic mutations (including likely pathogenic) and VUS’s were calculated for each gene and patient cohort. Results. Almost all tumors were glial (n=293, 53%) or meningeal pathology (n=222, 40%). Age of diagnosis differed significantly between glial and meningeal tumors (pCHEK2 (20/104), BRCA2 (13/104), PMS2 (10/104), TP53 (8/104), and APC (8/104). Of 165 patients with available family history information, nearly all (n=157, 95%) reported a family history of some cancer. Conclusions. Our data suggest PBTs can be the primary presenting cancer in hereditary syndromes with a known PBT risk. While pathology is helpful in narrowing down the differential diagnosis, patients’ pathology can be atypical in relation to their hereditary cancer syndrome. Family history evaluations are a beneficial risk assessment modality, particularly until testing criteria are developed for PBTs. Further research is necessary for the development of genetic testing criteria in the PBT population and more robust identification of at-risk individuals

Niraparib in ovarian cancer. results to date and clinical potential

Ovarian cancer is the first cause of death from gynaecological malignancy. Germline mutation in BRCA1 and 2, two genes involved in the mechanisms of reparation of DNA damage, are showed to be related with the incidence of breast and ovarian cancer, both sporadic and familiar. PARP is a family of enzymes involved in the base excision repair (BER) system. The introduction of inhibitors of PARP in patients with BRCA-mutated ovarian cancer is correlated with the concept of synthetic lethality. Among the PARP inhibitors introduced in clinical practice, niraparib showed interesting results in a phase III trial in the setting of maintenance treatment in ovarian cancer, after platinum-based chemotherapy. Interestingly, was niraparib showed to be efficacious not only in BRCA-mutated patients, but also in patients with other alterations of the homologous recombination (HR) system and in patients with unknown alterations. These results position niraparib as the first PARP-inhibitor with clinically and statistically significant results also in patients with no alterations in BRCA 1/2 and other genes involved in the DNA repair system. Even if the results are potentially practice-changing, the action of niraparib must be further studied and deepened

NGS Panels applied to Hereditary Cancer Syndromes

Cancer is among the leading causes of morbidity and mortality worldwide (Okur et al, 2017). Germline pathogenic variants for monogenic, highly penetrant cancer susceptibility genes are observed in 5%–10% of all cancers (Lu et al, 2014). Hereditary cancers due to monogenic causes are characterized by earlier age of onset, other associated cancers, and often a family history of specific cancers. From the clinical perspective, it is important to recognize the affected individuals to provide them the best clinical management (Hennessy et al, 2010; Ledermann et al, 2014; Pennington et al, 2014) and to identify at-risk family members who will benefit from predictive genetic testing and enhanced surveillance, including early detection and/or risk reduction measures (Kurian et al, 2010; Okur et al, 2017). Germline variants identified in major cancer susceptibility genes associated with hereditary breast or ovarian cancer (HBOC) or hereditary colorectal cancer (HCRC), also account for 5-10% of the patients with these cancers. In the last years, new susceptibility genes, with different penetrance degrees, have been identified. Variants in any of those genes are rare and classical methodologies (e.g. Sanger sequencing - SS) are time consuming and expensive. Next-generation sequencing (NGS) has several advantages compared to SS, including the simultaneous analysis of many samples and sequencing of a large set of genes, higher sensitivity (down to 1% vs 15-20% in SS), lower cost and faster turnaround time, reasons that make NGS the best approach for molecular diagnosis. It is possible nowadays to choose between whole-genome sequencing (WGS), whole-exome sequencing (WES) and NGS limited to a set of genes (NGS-Panel). In cases where a suspected genetic disease or condition has been identified, targeted sequencing of specific genes or genomic regions is preferred (Grada et al, 2013). For that reason, we use NGS-Panel approach using TruSight Cancer (Illumina) to sequence DNA extracted from blood samples of patients with personal and/or familiar history of cancer. This hereditary cancer gene panel sequences 94 genes associated with both common (e.g., breast, colorectal) and rare hereditary cancers and allows the creation of virtual gene panels according to each phenotype or disease under study. NGS workflow analysis (Figure 1) includes five steps: quality assessment of raw data, read alignment to a reference genome, variant identification/calling, variant annotation and data visualization (Pabinger et al, 2013). The establishment of the most appropriate bioinformatics pipeline is crucial in order to achieve the best results. NGS data allows the identification of several types of variants like single nucleotide variants (SNVs), small insertions/deletions, inversions and also copy number variants (CNVs).FCT - UID/BIM/0009/2016info:eu-repo/semantics/publishedVersio

Integrated analysis of germline and somatic variants in ovarian cancer

We report the first large-scale exome-wide analysis of the combined germline-somatic landscape in ovarian cancer. Here we analyze germline and somatic alterations in 429 ovarian carcinoma cases and 557 controls. We identify 3,635 high confidence, rare truncation and 22,953 missense variants with predicted functional impact. We find germline truncation variants and large deletions across Fanconi pathway genes in 20% of cases. Enrichment of rare truncations is shown in BRCA1, BRCA2, and PALB2. Additionally, we observe germline truncation variants in genes not previously associated with ovarian cancer susceptibility (NF1, MAP3K4, CDKN2B, and MLL3). Evidence for loss of heterozygosity was found in 100% and 76% of cases with germline BRCA1 and BRCA2 truncations respectively. Germline-somatic interaction analysis combined with extensive bioinformatics annotation identifies 237 candidate functional germline truncation and missense variants, including 2 pathogenic BRCA1 and 1 TP53 deleterious variants. Finally, integrated analyses of germline and somatic variants identify significantly altered pathways, including the Fanconi, MAPK, and MLL pathways