Genome-wide association analysis identifies 13 new risk loci for schizophrenia

Schizophrenia is an idiopathic mental disorder with a heritable component and a substantial public health impact. We conducted a multi-stage genome-wide association study (GWAS) for schizophrenia beginning with a Swedish national sample (5,001 cases and 6,243 controls) followed by meta-analysis with previous schizophrenia GWAS (8,832 cases and 12,067 controls) and finally by replication of SNPs in 168 genomic regions in independent samples (7,413 cases, 19,762 controls and 581 parent-offspring trios). We identified 22 loci associated at genome-wide significance; 13 of these are new, and 1 was previously implicated in bipolar disorder. Examination of candidate genes at these loci suggests the involvement of neuronal calcium signaling. We estimate that 8,300 independent, mostly common SNPs (95% credible interval of 6,300-10,200 SNPs) contribute to risk for schizophrenia and that these collectively account for at least 32% of the variance in liability. Common genetic variation has an important role in the etiology of schizophrenia, and larger studies will allow more detailed understanding of this disorder.

Model selection for prognostic time-to-event gene signature discovery with applications in early breast cancer data

Model selection between competing models is a key consideration in the discovery of prognostic multigene signatures. The use of appropriate statistical performance measures as well as verification of biological significance of the signatures is imperative to maximise the chance of external validation of the generated signatures. Current approaches in time-to-event studies often use only a single measure of performance in model selection, such as logrank test p-values, or dichotomise the follow-up times at some phase of the study to facilitate signature discovery. In this study we improve the prognostic signature discovery process through the application of the multivariate partial Cox model combined with the concordance index, hazard ratio of predictions, independence from available clinical covariates and biological enrichment as measures of signature performance. The proposed framework was applied to discover prognostic multigene signatures from early breast cancer data. The partial Cox model combined with the multiple performance measures were used in both guiding the selection of the optimal panel of prognostic genes and prediction of risk within cross validation without dichotomising the follow-up times at any stage. The signatures were successfully externally cross validated in independent breast cancer datasets, yielding a hazard ratio of 2.55 [1.44, 4.51] for the top ranking signature.

Identification and Validation of an Anthracycline/Cyclophosphamide–Based Chemotherapy Response Assay in Breast Cancer

Background: There is no method routinely used to predict response to anthracycline and cyclophosphamide–based chemotherapy in the clinic; therefore patients often receive treatment for breast cancer with no benefit. Loss of the Fanconi anemia/BRCA (FA/BRCA) DNA damage response (DDR) pathway occurs in approximately 25% of breast cancer patients through several mechanisms and results in sensitization to DNA-damaging agents. The aim of this study was to develop an assay to detect DDR-deficient tumors associated with loss of the FA/BRCA pathway, for the purpose of treatment selection.r/>r/>Methods: DNA microarray data from 21 FA patients and 11 control subjects were analyzed to identify genetic processes associated with a deficiency in DDR. Unsupervised hierarchical clustering was then performed using 60 BRCA1/2 mutant and 47 sporadic tumor samples, and a molecular subgroup was identified that was defined by the molecular processes represented within FA patients. A 44-gene microarray-based assay (the DDR deficiency assay) was developed to prospectively identify this subgroup from formalin-fixed, paraffin-embedded samples. All statistical tests were two-sided.r/>r/>Results: In a publicly available independent cohort of 203 patients, the assay predicted complete pathologic response vs residual disease after neoadjuvant DNA-damaging chemotherapy (5-fluorouracil, anthracycline, and cyclophosphamide) with an odds ratio of 3.96 (95% confidence interval [Cl] =1.67 to 9.41; P = .002). In a new independent cohort of 191 breast cancer patients treated with adjuvant 5-fluorouracil, epirubicin, and cyclophosphamide, a positive assay result predicted 5-year relapse-free survival with a hazard ratio of 0.37 (95% Cl = 0.15 to 0.88; P = .03) compared with the assay negative population.r/>r/>Conclusions: A formalin-fixed, paraffin-embedded tissue-based assay has been developed and independently validated as a predictor of response and prognosis after anthracycline/cyclophosphamide–based chemotherapy in the neoadjuvant and adjuvant settings. These findings warrant further validation in a prospective clinical study.

IntCal13 and Marine13 Radiocarbon Age Calibration Curves 0-50,000 Years Cal BP

The IntCal09 and Marine09 radiocarbon calibration curves have been revised utilizing newly available and updated data sets from C measurements on tree rings, plant macrofossils, speleothems, corals, and foraminifera. The calibration curves were derived from the data using the random walk model (RWM) used to generate IntCal09 and Marine09, which has been revised to account for additional uncertainties and error structures. The new curves were ratified at the 21st International Radiocarbon conference in July 2012 and are available as Supplemental Material at www.radiocarbon.org. The database can be accessed at http://intcal.qub.ac.uk/intcal13/.

Novel GlyT1 inhibitor chemotypes by scaffold hopping. Part 1: Development of a potent and CNS penetrant [3.1.0]-based lead

This Letter describes the development and SAR of a novel series of GlyT1 inhibitors derived from a scaffold hopping approach that provided a robust intellectual property position, in lieu of a traditional, expensive HTS campaign. Members within this new [3.1.0]​-​based series displayed excellent GlyT1 potency, selectivity, free fraction, CNS penetration and efficacy in a preclin. model of schizophrenia (prepulse inhibition)​. r/>

TBX2 represses CST6 resulting in uncontrolled legumain activity to sustain breast cancer proliferation: a novel cancer-selective target pathway with therapeutic opportunities.

TBX2 is an oncogenic transcription factor known to drive breast cancer proliferation. We have identified the cysteine protease inhibitor Cystatin 6 (CST6) as a consistently repressed TBX2 target gene, co-repressed through a mechanism involving Early Growth Response 1 (EGR1). Exogenous expression of CST6 in TBX2-expressing breast cancer cells resulted in significant apoptosis whilst non-tumorigenic breast cells remained unaffected. CST6 is an important tumor suppressor in multiple tissues, acting as a dual protease inhibitor of both papain-like cathepsins and asparaginyl endopeptidases (AEPs) such as Legumain (LGMN). Mutation of the CST6 LGMN-inhibitory domain completely abrogated its ability to induce apoptosis in TBX2-expressing breast cancer cells, whilst mutation of the cathepsin-inhibitory domain or treatment with a pan-cathepsin inhibitor had no effect, suggesting that LGMN is the key oncogenic driver enzyme. LGMN activity assays confirmed the observed growth inhibitory effects were consistent with CST6 inhibition of LGMN. Knockdown of LGMN and the only other known AEP enzyme (GPI8) by siRNA confirmed that LGMN was the enzyme responsible for maintaining breast cancer proliferation. CST6 did not require secretion or glycosylation to elicit its cell killing effects, suggesting an intracellular mode of action. Finally, we show that TBX2 and CST6 displayed reciprocal expression in a cohort of primary breast cancers with increased TBX2 expression associating with increased metastases. We have also noted that tumors with altered TBX2/CST6 expression show poor overall survival. This novel TBX2-CST6-LGMN signaling pathway, therefore, represents an exciting opportunity for the development of novel therapies to target TBX2 driven breast cancers.

Genetically Engineered Crops' Authorizations in the US and the EU: a Struggle Against the Clock

The regulation of genetically engineered crops is important for society: ensuring their safety for humans and the environment. Their authorization starts with a scientific step and ends with a political step. Trends in the time taken for their authorization in the European Union are that they are decreasing, but in the United States there is a break in the overall trend: initially it decreased until 1998 after which it increased.

Preferred Reporting Items for a Systematic Review and Meta-analysis of Individual Participant Data The PRISMA-IPD Statement

IMPORTANCE Systematic reviews and meta-analyses of individual participant data (IPD) aim to collect, check, and reanalyze individual-level data from all studies addressing a particular research question and are therefore considered a gold standard approach to evidence synthesis. They are likely to be used with increasing frequency as current initiatives to share clinical trial data gain momentum and may be particularly important in reviewing controversial therapeutic areas.

OBJECTIVE To develop PRISMA-IPD as a stand-alone extension to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) Statement, tailored to the specific requirements of reporting systematic reviews and meta-analyses of IPD. Although developed primarily for reviews of randomized trials, many items will apply in other contexts, including reviews of diagnosis and prognosis.

DESIGN Development of PRISMA-IPD followed the EQUATOR Network framework guidance and used the existing standard PRISMA Statement as a starting point to draft additional relevant material. A web-based survey informed discussion at an international workshop that included researchers, clinicians, methodologists experienced in conducting systematic reviews and meta-analyses of IPD, and journal editors. The statement was drafted and iterative refinements were made by the project, advisory, and development groups. The PRISMA-IPD Development Group reached agreement on the PRISMA-IPD checklist and flow diagram by consensus.

FINDINGS Compared with standard PRISMA, the PRISMA-IPD checklist includes 3 new items that address (1) methods of checking the integrity of the IPD (such as pattern of randomization, data consistency, baseline imbalance, and missing data), (2) reporting any important issues that emerge, and (3) exploring variation (such as whether certain types of individual benefit more from the intervention than others). A further additional item was created by reorganization of standard PRISMA items relating to interpreting results. Wording was modified in 23 items to reflect the IPD approach.

CONCLUSIONS AND RELEVANCE PRISMA-IPD provides guidelines for reporting systematic reviews and meta-analyses of IPD.

Mechanistic Rationale to Target PTEN-Deficient Tumor Cells with Inhibitors of the DNA Damage Response Kinase ATM

Ataxia telangiectasia mutated (ATM) is an important signaling molecule in the DNA damage response (DDR). ATM loss of function can produce a synthetic lethal phenotype in combination with tumor-associated mutations in FA/BRCA pathway components. In this study, we took an siRNA screening strategy to identify other tumor suppressors that, when inhibited, similarly sensitized cells to ATM inhibition. In this manner, we determined that PTEN and ATM were synthetically lethal when jointly inhibited. PTEN-deficient cells exhibited elevated levels of reactive oxygen species, increased endogenous DNA damage, and constitutive ATM activation. ATM inhibition caused catastrophic DNA damage, mitotic cell cycle arrest, and apoptosis specifically in PTEN-deficient cells in comparison with wild-type cells. Antioxidants abrogated the increase in DNA damage and ATM activation in PTEN-deficient cells, suggesting a requirement for oxidative DNA damage in the mechanism of cell death. Lastly, the ATM inhibitor KU-60019 was specifically toxic to PTEN mutant cancer cells in tumor xenografts and reversible by reintroduction of wild-type PTEN. Together, our results offer a mechanistic rationale for clinical evaluation of ATM inhibitors in PTEN-deficient tumors.

Abstract 1905: Defining a therapeutic classification of breast cancer by actionable targets

Breast cancer remains a frequent cause of female cancer death despite the great strides in elucidation of biological subtypes and their reported clinical and prognostic significance. We have defined a general cohort of breast cancers in terms of putative actionable targets, involving growth and proliferative factors, the cell cycle, and apoptotic pathways, both as single biomarkers across a general cohort and within intrinsic molecular subtypes.r/>r/>We identified 293 patients treated with adjuvant chemotherapy. Additional hormonal therapy and trastuzumab was administered depending on hormonal and HER2 status respectively. We performed immunohistochemistry for ER, PR, HER2, MM1, CK5/6, p53, TOP2A, EGFR, IGF1R, PTEN, p-mTOR and e-cadherin. The cohort was classified into luminal (62%) and non-luminal (38%) tumors as well as luminal A (27%), luminal B HER2 negative (22%) and positive (12%), HER2 enriched (14%) and triple negative (25%). Patients with luminal tumors and co-overexpression of TOP2A or IGF1R loss displayed worse overall survival (p=0.0251 and p=0.0008 respectively). Non-luminal tumors had much greater heterogeneous expression profiles with no individual markers of prognostic significance. Non-luminal tumors were characterised by EGFR and TOP2A overexpression, IGF1R, PTEN and p-mTOR negativity and extreme p53 expression.r/>r/>Our results indicate that only a minority of intrinsic subtype tumors purely express single novel actionable targets. This lack of pure biomarker expression is particular prevalent in the triple negative subgroup and may allude to the mechanism of targeted therapy inaction and myriad disappointing trial results. Utilising a combinatorial biomarker approach may enhance studies of targeted therapies providing additional information during design and patient selection while also helping decipher negative trial results.

PICan: An integromics framework for dynamic cancer biomarker discovery

Modern cancer research on prognostic and predictive biomarkers demands the integration of established and emerging high-throughput technologies. However, these data are meaningless unless carefully integrated with patient clinical outcome and epidemiological information. Integrated datasets hold the key to discovering new biomarkers and therapeutic targets in cancer. We have developed a novel approach and set of methods for integrating and interrogating phenomic, genomic and clinical data sets to facilitate cancer biomarker discovery and patient stratification. Applied to a known paradigm, the biological and clinical relevance of TP53, PICan was able to recapitulate the known biomarker status and prognostic significance at a DNA, RNA and protein levels.

Factors influencing success of clinical genome sequencing across a broad spectrum of disorders

To assess factors influencing the success of whole-genome sequencing for mainstream clinical diagnosis, we sequenced 217 individuals from 156 independent cases or families across a broad spectrum of disorders in whom previous screening had identified no pathogenic variants. We quantified the number of candidate variants identified using different strategies for variant calling, filtering, annotation and prioritization. We found that jointly calling variants across samples, filtering against both local and external databases, deploying multiple annotation tools and using familial transmission above biological plausibility contributed to accuracy. Overall, we identified disease-causing variants in 21% of cases, with the proportion increasing to 34% (23/68) for mendelian disorders and 57% (8/14) in family trios. We also discovered 32 potentially clinically actionable variants in 18 genes unrelated to the referral disorder, although only 4 were ultimately considered reportable. Our results demonstrate the value of genome sequencing for routine clinical diagnosis but also highlight many outstanding challenges.