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• Molecular_diagnosis_of_albinism

  Albinism is genetically heterogeneous rare genetic condition affecting 1:17000 in the Western world (but more frequent in Africa) whose main feature is a profound visual impairment, characterised by foveal hypoplasia, abnormal chiasmatic connections, nystagmus and photofobia. All these features result in severly altered visual acuity (<0,1), absent depth perception and poor night vision. People with albinism are primarily visually handicapped. In addition, for some types of albinism, the visual phenotype can be presented with partial or total hypopigmentation, hence resulting in a secondary phenotype which can lead to skin cancer if skin is not adequately protected. Recently a new syndrome has been described, FHONDA, with the same visual abnormalities of albinism but without pigment alteration. The traditional classification differentiates Oculoculatenous albinism (OCA), where hypopigmentation involves hair, skin and eyes versus Ocular Albinism (OA), where hypopigmentation only affects the eyes. These are non-sydrimic types of albinism. Some syndromic forms (Hermansky-Pudlak=HPS, Chediak-Higashi=CHS) affect cells beyond pigment cells, present in the lungs, immune system, platelets and intestines, resulting in more severe phenotypes that can be fatal. Mutations in at least 19 genes are assocaited with the corresponding types of albinism. Most hospitals will only diagnose the most frequent cases using traditional Sanger, MLPA approaches. Some will use CGH arrays. We aim to diagnose all cases of albinism through the Albinochip proposal, which combines a Sequenom first step of known mutations combined with subsequent NGS approaches. In some cases we fail to find a second mutation, these are good candidates for further full exome analyses. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001002068

• UK10K NEURO IMGSAC

  In the UK10K project we propose a series of complementary genetic approaches to find new low frequency/rare variants contributing to disease phenotypes. These will be based on obtaining the genome wide sequence of 4000 samples from the TwinsUK and ALSPAC cohorts (at 6x sequence coverage), and the exome sequence (protein coding regions and related conserved sequence) of 6000 samples selected for extreme phenotypes. Our studies will focus primarily on cardiovascular-related quantitative traits, obesity and related metabolic traits, neurodevelopmental disorders and a limited number of extreme clinical phenotypes that will provide proof-of-concept for future familial trait sequencing. We will analyse directly quantitative traits in the cohorts and the selected traits in the extreme samples, and also use imputation down to 0.1% allele frequency to extend the analyses to further sample sets with genome wide genotype data. In each case we will investigate indels and larger structural variants as well as SNPs, and use statistical methods that combine rare variants in a locus or pathway as well as single-variant approaches.The IMGSAC cohort is an international collection of families containing children ascertained for ASDs (autism spectrum disorders). The affected individuals are have been phenotyped, including using the ADI-R and ADOS instruments. Individuals with a past or current medical disorder of probable etiological significance or TSC have been excluded. Where possible, karyotyping has been performed on one affected individual per family to exclude Fragile X syndrome. Many of the samples have been genotyped, using the Affymetrix 10k and Illumina 1M platforms. All samples to be included in the current study are of UK origin.For further information on this cohort please contact Jeremy Parr (jeremy.parr@newcastle.ac.uk).

  Study EGAS00001000120

• Sequencing of paediatric High Grade Gliomas and DIPG

  Paediatric high grade glioma (pHGG) and diffuse intrinsic pontine glioma (DIPG) are a phenotypically diverse collection of tumours which molecular profiling studies have refined into age- and location-based subgroups driven by unique genetic and epigenetic alterations. Despite this, the rarity of these tumours means individual studies are underpowered to investigate subgroup-specific changes and to identify low frequency events recurrently targeting specific pathways. We have collated genomic data from 143 unpublished cases up to 30 years of age along with those from 18 previously published datasets in an integrated analysis comprising 1067 unique patients across all anatomical compartments of the CNS, with histone mutation status available for 893 cases (n=67 H3.3G34R/V, n=316 H3.3K27M, n=68 H3.1/H3.2K27M). Distinct clinicopathological and molecular subgroups are defined by these histone mutations, with several novel co-segregating mutations identified through these aggregated analyses, including loss of FBXW7 in H3.3G34R/V, TOP3A rearrangements in H3.3K27M, and BCOR mutations in H3.1K27M. Histone wild-type subgroups can be further refined by the presence of key oncogenic events (PDGFRA or EGFR amplification/mutations) or methylation profiles which molecularly more closely resemble pleomorphic xanthoastrocytoma or other low grade gliomas. The burden of genomic aberrations decreases with age, highlighting the infant population as biologically and clinically distinct. Across the whole cohort, we identify novel previously unrecognised pathway dysregulation in small subsets of tumours (e.g. splicing, WNT, immune response) which make up the umbrella classification of paediatric diffusely infiltrating gliomas. The integrated dataset helps to further define the molecular diversity of the disease, opening up novel avenues for biological study and providing a basis for functionally defined future treatment stratification.

  Study EGAS00001002314

• Histone chaperone CHAF1A promotes proliferation and tumorigenicity in gastric cancer and impacts prognosis via context-depedent regulation of gene expression

  The histone chaperone CHAF1A is associated with some tumors, but its mechanisms in tumor biology remain elusive. Gastric cancer (GC) has significant heterogeneity among patients, and novel prognostic markers and therapeutic targets may improve its outcomes. The role of CHAF1A in GC is unknown. In this study, we demonstrated that CHAF1A was overexpressed in GC tissues accompanied by low expression of wild-type P53 and high expression of the proliferation marker MKI67. In vitro, CHAF1A knockdown inhibited cell proliferation, induced cell cycle arrest and promoted apoptosis, while CHAF1A overexpression had contrary effects. In vivo, CHAF1A knockdown inhibited tumorigenicity of GC cells. A microarray assay with CHAF1A inhibition and a PathScan signaling antibody array with CHAF1A overexpression showed that CHAF1A inhibited the P53 pathway, activated stress response and induced glycolytic metabolism. In 665 patients, the expression level of CHAF1A protein was an independent predictor for overall survival and disease-free survival in non-cardia GC and also had survival associations in patients with small or perineural invasion-negative tumors. Tumor mRNA analyses based on next-generation sequencing in patients indicated that CHAF1A promoted the Warburg effect by depressing oxidative phosphorylation and increasing glycolysis. Furthermore, the heterogeneous clinical significance of CHAF1A among patient subgroups was associated with its differential regulation of gene expression involved with glycolysis and cell proliferation and survival, indicating that the role of CHAF1A is depended on patient characteristics. These results reveal critical roles and clinical values for CHAF1A in GC. CHAF1A may have context-dependent effects in GC, which increases understandings for GC heterogeneity.

  Study EGAS00001003064

• The light chain IgLV3-21 defines a new poor prognostic subgroup in Chronic Lymphocytic Leukemia: results from a multicenter study

  Purpose: Unmutated (UM) immunoglobulin heavy chain region (IgHV) status or IgHV3-21 gene usage is associated with poor prognosis in chronic lymphocytic leukemia (CLL). Interestingly, IgHV3-21 is often co-expressed with light chain IgLV3-21 which is potentially able to trigger cell-autonomous BCR-mediated signaling. However this light chain has never been characterized independently of the heavy chain IgHV3-21.Experimental Design: we performed total RNA sequencing to characterize IgLV3-21 patients (n=32) and investigated IgLV3-21 prognostic impact in terms of treatment-free (TFS) and overall (OS) survival in 3 other independent cohorts for a total of 813 patients where IgLV3-21 presence was tested by real-time PCR and confirmed by Sanger sequencing.Results: Using total RNA sequencing to characterize 32 patients with high-risk CLL, we found a high frequency (28%) of IgLV3-21 rearrangements. Gene set enrichment analysis revealed that these patients present higher expression of genes responsible for ribosome biogenesis and translation initiation (P<0.0001) and MYC target genes (P=0.0003). Patients with IgLV3-21 rearrangements displayed a significantly shorter TFS and OS (P<0.05), in particular in IgHV mutated patients. In each of the 3 independent validation cohorts (n=813), we showed that IgLV3-21 rearrangements -similar to UM IgHV status- conferred poor prognosis compared to mutated IgHV (P<0.0001). Importantly, we confirmed in multivariate analysis that this was independent of IgHV mutational status or subset #2 stereotyped receptor (P<0.0001). Conclusions: We therefore demonstrate for the first time that a light chain can impact on CLL prognosis and that IgLV3-21 light chain usage defines a new poor prognostic subgroup in CLL.

  Study EGAS00001002894

• Integrated Genomic, Epigenetic, and Expression Analyses of Ovarian Cancer Cell Lines

  Epithelial ovarian carcinoma of all subtypes has one of the worst outcomes of any human cancer. To improve our understanding of underlying biology and therapeutic possibilities in this disease, we performed whole genome sequencing, methylation, and expression analyses of a comprehensive set of 47 ovarian cancer cell lines representing different histologic tumor subtypes. Given the challenges of genomic analyses in tumors without matched normal samples, we developed novel approaches for detection of somatic alterations and used these to identify sequence, copy number, and rearrangement changes and integrated these with genome-wide epigenetic and expression alterations. Ovarian cancer cell lines had molecular changes in genes involved in cell cycle, PI3K, RAS, BRCA, chromatin regulating, and p53 pathways, and displayed global mutation and methylation changes similar to primary ovarian carcinoma. We identified alterations not previously implicated in ovarian cancer including amplification or overexpression of ASXL1 and H3F3B, deletion or underexpression of CDC73 and members of the TGF beta receptor pathway, including TGFBR2, SMAD3 and SMAD4, in-frame rearrangements of YAP1-MAML2 and IKZF2-ERBB4, and fusions involving MET, NF1, FBXW7 and CCND1. Integrating cell line alterations with dose-response data using three targeted therapies revealed novel molecular dependencies, including increased sensitivity of tumors with PIK3CA and PPP2R1A alterations to PI3K inhibitor GNE-493, those with MYC amplifications to PARP inhibitor BMN673, and SMAD4 alterations to MEK inhibitor MEK162. Genome-wide analyses revealed intrachromosomal rearrangements as an improved measure of sensitivity to PARP inhibition compared to the homologous recombination defect (HRD) score. This study provides a comprehensive resource of molecular information for ovarian cancer cell line models and a pharmacogenomic platform for developing rational cancer therapeutic strategies.

  Study EGAS00001002998

• Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

  Most patients with late stage high-grade serous ovarian cancer (HGSOC) initially respond to chemotherapy but inevitably relapse and develop resistance, highlighting the need for novel therapies to improve patient outcomes. The MEK/ERK pathway is activated in a large subset of HGSOC, thus making it an attractive therapeutic target. Here, we systematically evaluated the extent of MEK/ERK pathway activation and efficacy of pathway inhibition in a large panel of well-annotated HGSOC patient-derived xenograft (PDX) models. The vast majority of models were nonresponsive to the MEK inhibitor cobimetinib (GDC-0973) despite effective pathway inhibition. Proteomic analyses of adaptive responses to GDC-0973 revealed that GDC-0973 upregulated the pro-apoptotic protein BIM, thus priming the cells for apoptosis regulated by BCL2-family proteins. Indeed, combination of both MEK inhibitor and dual BCL-2/XL inhibitor (ABT-263) significantly reduced cell number, increased cell death and displayed synergy in vitro in most models. In vivo, the GDC-0973 and ABT-263 combination was well tolerated and resulted in greater tumor growth inhibition than single agents. Detailed proteomic and correlation analyses identified two subsets of responsive models – those with high BIM at baseline that was increased with MEK inhibition and those with low basal Bim and high pERK levels. Models with low BIM and low pERK were non-responsive. Our findings demonstrate that combined MEK and BCL-2/XL inhibition has therapeutic activity in HGSOC models and provide a mechanistic rationale for clinical evaluation of this drug combination as well as the assessment of the extent to which BIM and/or pERK levels predict drug combination effectiveness in chemoresistant HGSOC.

  Study EGAS00001003427

• Ischemic stroke in a Swedish case-control study.

  Background. Genetic risk scores (GRS), summing up the total effect of several single nucleotide polymorphisms (SNPs) in genes associated with either coronary risk or cardiovascular risk factors, have been tested for association with ischemic stroke with conflicting results. Recently an association was found between a GRS, based on 29 SNPs discovered by genome-wide association studies (GWAS) and hypertension. The aim of our study was to investigate the possible association of the same GRS with ischemic stroke on top of other “traditional risk factors”, also testing its potential improvement in indices of discrimination and reclassification, in a Swedish case-control study. Methods and results. Twenty-nine SNPs were genotyped in 3,677 stroke cases and 2,415 controls included in the Lund Stroke Register (LSR), the Malmö Diet and Cancer (MDC) study and the Sahlgrenska Academy Study on Ischemic Stroke (SAHLSIS). The analysis was conducted in the entire material, and separately for the three samples. After adjustment for hypertension, diabetes mellitus and smoking habits, the GRS was associated with ischemic stroke in the entire material [OR (95% CI) 1.086 (1.029-1.147) per SD increase in the GRS p=0.003] with similar trends in all three samples; LSR [1.050 (0.967-1.140)]; p=0.25], MDC [1.168 (1.060-1.288); p=0.002] and SAHLSIS [1.124 (0.997-1.267); P=0.055]. Measures of discrimination and reclassification improved marginally using the GRS. Conclusions. A blood pressure GRS is independently associated with ischemic stroke risk in three Swedish case-control studies, however, the effect size is low and adds marginally to prediction of stroke on top of traditional risk factors including hypertension.

  Study EGAS00001000936

• Post_Mortem_Tissue_COVID19_RNA

  Single cell analysis of post mortem tissue samples from SARS-CoV2-infected patients We aim to directly identify the human cell types infected by SARS-CoV-2 and measure the cellular response to COVID19 infection across 20 different tissues from infected patient autopsies. We have examined the expression pattern of viral entry receptors across healthy human tissues to predict several candidate target cell types across the airway and heart. In addition, high prevalence of cardiac failure and abnormal renal function in COVID19 patients implicates heart and kidney involvement, but the pathogenesis of organ specific damage - whether via a direct cytopathic mechanism or an indirect inflammatory response - remains unknown . Currently, we lack confirmation of target cell types and cellular processes in infected tissues as autopsies are discouraged in most countries due to health and safety risks. Our collaborators Drs Michael Osborn and Brian Hanley (Imperial College) have outlined guidelines to perform post-mortem in COVID19 patients (Hanley et al., 2020) and have established a programme of autopsies for research to be performed in a high-risk facility at Westminster Public Mortuary. Here, we propose to identify infected cell types and aberrant molecular pathologies in this precious tissue resource using single cell and spatial genomics. We will prioritise three organ systems: the human airway, heart and the kidney. We will directly examine the cellular identities of SARS-CoV-2 infected cell types and identify the cellular responses to infection across these organs. This fundamental knowledge will help guide future treatment choices for COVID19. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001004442

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Lung cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Study EGAS00001004447