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• Interethnic comparability in blood pressure GWAS

  We carried out a genome-wide association and replication study for blood pressure in a two-stage approach (max N = 289,038) with a discovery stage sample of 130,777 East Asian individuals, identifying 19 new genetic loci. We found a significant genetic heterogeneity between East Asian and European-descent populations at several blood pressure loci, conforming to “a common ancestry-specific variant association model”. At 6 unique loci, distinct non-rare (or common) ancestry-specific variants co-localized within the same linkage disequilibrium block despite the significantly discordant direction of effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect sizes is 0.898 and 0.851 for systolic and diastolic blood pressure, respectively. Some of the ancestry-specific association signals were also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in the occurrence of ethnic differences in complex traits such as blood pressure.

  Study EGAS00001002991

• SARS‐CoV‐2 receptor ACE2 and TMPRSS2 are primarily expressed in bronchial transient secretory cells

  The SARS‐CoV‐2 pandemic affecting the human respiratory system severely challenges public health and urgently demands for increasing our understanding of COVID‐19 pathogenesis, especially host factors facilitating virus infection and replication. SARS‐CoV‐2 was reported to enter cells via binding to ACE2, followed by its priming by TMPRSS2. Here, we investigate ACE2 and TMPRSS2 expression levels and their distribution across cell types in lung tissue (twelve donors, 39,778 cells) and in cells derived from subsegmental bronchial branches (four donors, 17,521 cells) by single nuclei and single cell RNA sequencing, respectively. While TMPRSS2 is strongly expressed in both tissues, in the subsegmental bronchial branches ACE2 is predominantly expressed in a transient secretory cell type. Interestingly, these transiently differentiating cells show an enrichment for pathways related to RHO GTPase function and viral processes suggesting increased vulnerability for SARS‐CoV‐2 infection. Our data provide a rich resource for future investigations of COVID‐19 infection and pathogenesis.

  Study EGAS00001004419

• GRIDSS, PURPLE, LINX: Unscrambling the tumor genome via integrated analysis of structural variation and copy number

  We have developed a novel, integrated and comprehensive purity, ploidy, structural variant and copy number somatic analysis toolkit for whole genome sequencing data of paired tumor/normal samples. We show that the combination of using GRIDSS for somatic structural variant calling and PURPLE for somatic copy number alteration calling allows highly sensitive, precise and consistent copy number and structural variant determination, as well as providing novel insights for short structural variants and regions of complex local topology. LINX, an interpretation tool, leverages the integrated structural variant and copy number calling to cluster individual structural variants into higher order events and chains them together to predict local derivative chromosome structure. LINX classifies and extensively annotates genomic rearrangements including simple and reciprocal breaks, LINE, viral and pseudogene insertions, and complex events such as chromothripsis. LINX also comprehensively calls genic fusions including chained fusions. Finally, our toolkit provides novel visualisation methods providing insight into complex genomic rearrangements.

  Study EGAS00001004034

• A microRNA-signature that correlates with cognition and is a target against cognitive decline

  While some individuals age without pathological memory impairments, others develop age-associated cognitive diseases. Since changes in cognitive function develop slowly over time in these patients, they are often diagnosed at an advanced stage of molecular pathology, a time point when causative treatments fail. Thus, there is great need for the identification of inexpensive and minimal invasive approaches that could be used for screening with the aim to to identify individuals at risk for cognitive decline that can then undergo further diagnostics and eventually stratified therapies. In this study we use an integrative approach combining the analysis of human data and mechanistic studies in model systems to identify a circulating 3-microRNA signature that reflect key processes linked to neural homeostasis and informs about cognitive status. We furthermore provide evidence that expression changes of this signature represent multiple mechanisms de-regulated in the aging and diseased brain and are a suitable target for RNA therapeutics.

  Study EGAS00001005627

• Robust detection of translocations in lymphoma FFPE samples using Targeted Locus Capture-based sequencing - NGS targeted capture control cohort

  In routine diagnostic pathology, cancer biopsies are preserved by Formalin-Fixed, Paraffin-Embedding (FFPE) procedures for examination of (intra-) cellular morphology. Such procedures inadvertently induce DNA fragmentation, which compromises sequencing-based analyses of chromosomal rearrangements. Yet, rearrangements drive many types of hematolymphoid malignancies and solid tumors, and their manifestation is instructive for diagnosis, prognosis and treatment. Here, we present FFPE-Targeted Locus Capture (FFPE-TLC) for targeted sequencing of proximity-ligation products formed in FFPE tissue blocks, and PLIER, a computational framework that allows automated identification and characterization of rearrangements involving selected, clinically-relevant, loci. FFPE-TLC, blindly applied to 149 lymphoma and control FFPE samples, identifies the known and novel rearrangement partners. It outperforms fluorescence in situ hybridization (FISH) in sensitivity and specificity, and shows clear advantages over standard capture-NGS methods, finding rearrangements involving repetitive sequences which they typically miss. FFPE-TLC is therefore a powerful clinical diagnostics tool for accurate targeted rearrangement detection in FFPE specimens.

  Study EGAS00001005325

• Human genome-wide variations in the Massim region

  The Massim, a cultural region encompassing the southeastern tip of mainland Papua New Guinea (PNG) and nearby islands, is famous for the Kula trading network, in which different valuables circulate in different directions among the islands. To explore Massim genetic history, we generated genome-wide data from across the region and found variable levels of Papuan-related (indigenous) ancestry, including a novel ancestry associated with Rossel Island, and Austronesian-related ancestry that arrived later. We find genetic evidence for different patterns of contact across PNG, the Massim, and the Bismarck and Solomon Archipelagoes for Austronesian-related vs. Papuan-related ancestry, with more geographic restriction for the latter. Moreover, Kula-practicing groups share more genetic similarity than do other groups, and this likely predates the origin of Kula, suggesting that high between-group contact facilitated the formation of Kula. Our study provides the first comprehensive genome-wide assessment of Massim inhabitants and new insights into the fascinating Kula system.

  Study EGAS00001006010

• Serial TERT rearrangement breakpoint quantification in circulating tumor DNA enables minimal residual disease monitoring in patients with neuroblastoma

  Approximately 30% of high-risk neuroblastomas harbor genomic TERT rearrangements at diagnosis, resulting in high TERT transcript levels and active telomerase. Combined with mutations in the RAS/MAPK/ALK signaling transduction network, these patients have a dismal prognosis. Our objective was to establish a liquid biopsy-based monitoring strategy for this particularly vulnerable patient subgroup, for whom no in-time molecular diagnostic tools exist to date. Detection and quantification of TERT rearrangement breakpoints in cell-free tumor DNA circulating in peripheral blood and bone marrow plasma from patients with TERT-driven neuroblastoma improved minimal residual disease monitoring and early relapse detection in individual patients. TERT rearrangement breakpoints, as a single marker or combined with mutations in the RAS/MAPK/ALK signaling transduction network, can be reliably analyzed from 1ng DNA using droplet digital PCR assays fit for clinical routine use. TERT rearrangement breakpoints are reflected in cell-free tumor DNA and can serve as robust biomarkers for disease activity.

  Study EGAS00001007365

• Identification of gene mutations and fusion genes in patients with Sézary Syndrome

  Sezary syndrome (SS) is a leukemic form of cutaneous T-cell lymphoma (CTCL) with an aggressive clinical course. The goal of our study is to understand the genetic basis of the disease by looking for driver gene mutations and fusion genes in 15 erythrodermic patients with circulating Sezary cels, fourteen of them fulfilling the diagnostic criteria of SS. Peripheral blood samples were collected for each patient and CD4+ T-lymphocytes and Granulocytes were isolated. DNA and RNA was extracted for matched normal and tumor materials. Whole exome sequencing was performed on matched normal and tumor tissues of 12 patients and RNA sequencing was performed on 10 patients. For 7 of these patients, we have both exome as well as RNA sequencing data. In this study, we present a complex genomic landscape of Sezary syndrome with several point mutations, copy number variations and fusion events which could contribute to the pathogenesis of SS.

  Study EGAS00001001706

• Sequencing data from MethylScan assay on plasma

  Machine learning models in biomedical research are often hindered by demographic imbalances in clinical datasets, leading to biased predictions that disadvantage minority populations. Existing bias correction methods face limitations in handling the heterogeneity of biomedical data and the complexity of demographic influences. Here, we present DeBias, a computational framework for mitigating demographic biases in high-dimensional biomedical datasets. DeBias eliminates bias-associated subspaces within the entire feature space using control samples and enables global bias correction across all features, effectively preserving disease-specific signals while minimizing demographic distortions. To demonstrate its effectiveness, we applied DeBias to cfDNA methylation data for cancer detection. It achieved a >6-fold reduction in the number of features containing biases and outperformed existing methods in improving the cancer detection performance for minority populations. Our method represented a promising step toward developing machine learning models that are more accurate, reliable, and equitable for minority populations.

  Study EGAS00001008127

• Gene Expression Signatures Characterized by Longitudinal Stability and Inter-Individual Variability Delineate Baseline Phenotypic Groups with Distinct Responses to Immune Stimulation

  RNA sequencing (RNAseq) of peripheral blood lymphocytes was used to develop a means to assess immune function in a way that can be used in discovery science and applied to patients individually in clinical settings. The premise is that profiles of RNA present in immune cells is reflective of the combined influence of genetic and environmental variation on immune potential of individuals and that this potential can be tapped to understand human immunity in a variety of biological contexts. CD4+ cells were isolated from fresh whole blood via positive magnetic bead selection and cell lysates were prepared using Qiazol (QIAGEN) and stored at -80ºC for 3 to 8 months. RNA was extracted in batches for cDNA library preparation and RNA-Seq. For this study, we developed standard operating procedures for handling human blood samples and determined: a) the best way to enrich for CD4+ T cells from whole blood and yield high quality RNA, b) the sensitivity of this RNA profiling strategy, and c) the reproducibility of generated immune profiles from healthy subjects. We then developed bioinformatics processes to establish immune response signatures and immune response phenotypes within cohorts of individuals.

  Study phs001512

• National Eye Institute (NEI) Exfoliation Genotyping Study

  The overall goal of our research is to elucidate the pathogenesis of exfoliation syndrome and the associated glaucoma, making it possible to implement effective screening and prevention strategies and to develop novel therapies. Cases genotyped for this project are from the Nurses Health Study (NHS), the Health Professionals Follow-up Study (HPFS), the Women's Genome Health Study (WGHS), the Massachusetts Eye and Ear Infirmary (MEEI), Mayo Clinic, the University of Iowa, the University of Miami and Duke University Medical Center. Exfoliation syndrome (XFS) is a common condition that is a major risk factor for high-tension open-angle glaucoma, pre-mature cataract formation, and increased risk of complications during cataract surgery. Previous studies suggest that exfoliation syndrome and the related glaucoma (XFG) are genetically complex, and one gene, LOXL1, has been identified as a major genetic risk factor. LOXL1 variants are found in up to 98% of affected patients; however, these same variants are also present in up to 80% of unaffected individuals, indicating that additional genetic and/or environmental factors are necessary for disease development. Samples genotyped for this study are a case set (1,096 samples) and 24 pedigrees (98 samples). Controls for association analyses are selected from the NEIGHBORHOOD study.

  Study phs001053

• Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants and parents), NIDDK

  Genetics of Kidneys in Diabetes (GoKinD) study is an initiative aimed at identifying susceptibility genes for diabetic nephropathy in type 1 diabetes. A large number of individuals with type 1 diabetes were screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents were also enrolled to form family trios. Altogether, GoKinD includes 3043 participants comprising 931 cases, 944 singletons, 268 pairs of parents of cases, and 316 pairs of parents of control. Accessible as a GAIN database are 905 of the cases, 890 of the controls, 10 pairs of parents of cases and 10 pairs of parents of controls (dbGaP phs000018 Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants), GAIN). The other parents and the remaining cases and controls are available by a separate application process through NIDDK. Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form available at http://www.niddkrepository.org or by contacting the Juvenile Diabetes Research Foundation.

  Study phs000088

• Cross-Species Single-Cell Analysis of Pancreatic Ductal Adenocarcinoma Reveals Antigen-Presenting Cancer-Associated Fibroblasts

  Cancer-associated fibroblasts (CAFs) are major players in the progression and drug resistance of pancreatic ductal adenocarcinoma (PDAC). CAFs constitute a diverse cell population consisting of several recently described subtypes, although the extent of CAF heterogeneity has remained undefined. Here we employ single-cell RNA-sequencing to thoroughly characterize the neoplastic and tumor microenvironment content of human PDAC tumors. Six human PDAC tumor specimens from six patients were collected, and processed for single-cell RNA-sequencing analysis. Adjacent-normal pancreas tissue was also collected from two of the patients. Tumor samples were digested, and fluorescence-activated cell sorting was used to isolate viable cells. For one tumor sample, viable, CD45-negative, CD31-negative, and EpCAM-negative cells were also isolated to enrich for CAFs. The 10X Chromium platform was then used to isolate single cells for RNA-sequencing analysis. This work has demonstrated the differences in immune cell populations between adjacent-normal and tumor tissues, and identified subpopulations of epithelial cells and CAFs present in PDAC tumors. This high-throughput analysis is a resource to better understand the cell populations present in PDAC, and may ultimately aid in the development of more effective therapies for this deadly malignancy.

  Study phs001840

• CIDR: Genome Wide Association Study in Familial Parkinson Disease (PD)

  This proposal brings together the two largest NIH funded genetic studies focused on the identification of novel genes that influence the risk of PD. These two studies, PROGENI (PI: Tatiana Foroud; R01NS037167) and GenePD (PI: Richard Myers; R01NS036711) have been evaluating and recruiting families with two or more PD affected members for more than 8 years and represent the largest such cohorts world-wide. The combined sample has more than 1,000 PD families. Each study has used rigorous clinical criteria to assess their study participants. Unlike previous genome wide association studies (GWAS) in PD, all the PD cases in this proposal have a positive family history of disease. In the vast majority of these families, the index PD case has at least one sibling with the disease. Thus, the sample is unique for having substantial evidence for a genetic contribution to disease. The control group for this study consists of samples previously collected and maintained by the NINDS Repository. Genome-wide, single nucleotide polymorphism (SNP) genotyping services were provided by the Center for Inherited Disease Research (CIDR). Data analyses will focus on the identification of SNPs associated with PD susceptibility and the age of onset of disease.

  Study phs000126

• Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants), GAIN

  Genetics of Kidneys in Diabetes (GoKinD) study is an initiative aimed at identifying susceptibility genes for diabetic nephropathy in type 1 diabetes. A large number of individuals with type 1 diabetes were screened to identify two subsets, one with clear-cut kidney disease and another with normal renal status despite long-term diabetes. Those who met additional entry criteria and consented to participate were enrolled. When possible, both parents were also enrolled to form family trios. Altogether, GoKinD includes 3043 participants comprising 931 cases, 944 singletons, 268 pairs of parents of cases, and 316 pairs of parents of control. Accessible as a GAIN database are 905 of the cases, 890 of the controls, 10 pairs of parents of cases and 10 pairs of parents of controls. The other parents and the remaining cases and controls are available by a separate application process through NIDDK (dbGaP phs000088 Search for Susceptibility Genes for Diabetic Nephropathy in Type 1 Diabetes (GoKinD study participants and parents), NIDDK). Interested investigators may request the DNA collection and corresponding clinical data for GoKinD participants using the instructions and application form available at Juvenile Diabetes Research Foundation. Consent groups and participant set Diabetic complications only (DCO): 1825 (904 cases, 881 controls, 40 others)

  Study phs000018

• DEMENTIA-SEQ: WGS in Lewy Body Dementia and Frontotemporal Dementia

  Lewy body dementia, amyotrophic lateral sclerosis/frontotemporal dementia, and multiple system atrophy are age-related, neurodegenerative syndromes that are poorly understood. Delineating the genetic risk that is driving the pathophysiology of these neurological diseases is fundamental for understanding disease mechanisms and for developing disease-modifying treatments. In version 1 of the study/dbGaP deposition, we performed a whole-genome sequencing study consisting of 7,403 total samples, including 2,633 genomes from patients with Lewy body dementia, 2,641 frontotemporal dementia patients, and 1,980 neurologically healthy controls. Of these, 6,907 were uploaded to dbGaP as the basis of the DementiaSeq, phs001963 dataset. The data relating to these samples are available on dbGaP. In version 2 of this study/dbGaP deposition, we made much of these data available on Anvil. More specifically, data for 6,254 of these samples were also uploaded to the ALS Compute platform on AnVIL. The data for the remaining 653 samples are only available on dbGaP. The dbGaP/AnVIL Table lists the availability of dbGaP and AnVIL for each individual sample: phd008475.In version 3 of the study/dbGaP deposition, we added whole-genome sequence data generated using DNA samples obtained from 683 patients diagnosed with multiple system atrophy.

  Study phs001963

• Botswana 15 autosomal unlinked microsatellites

  Population structure was investigated in 990 Botswana individuals according to ethno-linguistics, Bantu and Khoisan, and geography (the nine administrative districts) using the AmpFLSTR Identifiler autosomal microsatellite markers. Genetic diversity and forensic parameters were calculated for the overall population, and according to ethno-linguistics and geography. The overall combined power of exclusion (CPE) was 0.9999965412 and the combined match probability 6,28 x 10-19. CPE was highest for the Khoisan Tuu ethnolinguistic group and the Northeast District at 0.9999582029 and 0.9999922652 respectively. CMP ranged from 6.28 x 10-19 (Khoisan Tuu) to 1,02 x 10-18 (Northwest district). Using pairwise genetic distances (FST), analysis of molecular variance (AMOVA), factorial correspondence analysis (FCA), and the unsupervised Bayesian clustering method found in STRUCTURE and landscape genetics software TESS, ethno-linguistics were found to have a greater influence on population structure than geography. FCA showed clustering between Bantu and Khoisan, and within the Bantu. This Bantu sub-structuring was not seen with STRUCTURE and TESS, which detected clustering only between Bantu and Khoisan. The patterns of population structure revealed highlight the need for regional reference databases that include ethno-linguistic and geographic location information. These markers have important potential for bio-anthropological studies as well as for forensic applications.

  Study EGAS00001002380

• Whole exome sequencing on primary retinoblastoma tissues and matching lymphocyte DNA.

  Retinoblastoma is a rare childhood cancer initiated by RB1 mutation or MYCN amplification, while additional alterations may be required for tumor development. However, the view on single nucleotide variants is very limited. To better understand oncogenesis, we determined the genomic landscape of retinoblastoma. We performed exome sequencing of 71 retinoblastomas and matched blood DNA. Next, we determined the presence of single nucleotide variants, copy number alterations and viruses. Aside from RB1, recurrent gene mutations were very rare. Only a limited fraction of tumors showed BCOR (7/71, 10%) or CREBBP alterations (3/71, 4%). No evidence was found for the presence of viruses. Instead, specific somatic copy number alterations were more common, particularly in patients diagnosed at later age. Recurrent alterations of chromosomal arms often involved less than one copy, also in highly pure tumor samples, suggesting within-tumor heterogeneity. Our results show that retinoblastoma is among the least mutated cancers and signify the extreme sensitivity of the childhood retina for RB1 loss. We hypothesize that retinoblastomas arising later in retinal development benefit more from subclonal secondary alterations and therefore, these alterations are more selected for in these tumors. Targeted therapy based on these subclonal events might be insufficient for complete tumor control.

  Study EGAS00001001690

• Unifying recovery dynamics in heterogeneous diseases exemplified by COVID-19

  Studying the recovery dynamics in different diseases poses many difficulties, as patients often display high heterogeneity in their recovery courses. Moreover, most attempts to study disease dynamics focus on disease progression rather than disease recovery mechanisms. To model recovery dynamics, using severe COVID-19 as the example, we align heterogeneous recovery trajectories via a novel computational scheme applied to longitudinally sampled blood transcriptomes. We thus generate pseudotime trajectories, which we then link to cellular and molecular mechanisms based on cell deconvolution analysis and molecular pathway prediction, thus presenting a unique framework for studying recovery processes over time. Specifically, mature neutrophils displayed a gradual decrease during recovery, allowing superior useability for outcome prediction compared to currently used clinical markers. Further, we discovered a recovery-related regulatory change in gene programs resulting in immune rebalancing between interferon and NFkB activity and the restoration of cell homeostasis. We thus propose regulatory mechanisms governing COVID-19 recovery and suggest mature neutrophils and additional gene markers, as novel clinical biomarkers for disease outcome. Overall, we present a novel clinically relevant computational framework for modeling disease recovery, paving the way for future studies of the recovery dynamics in other diseases and tissues.

  Study EGAS00001005735

• Cardiovascular disease biomarkers derived from circulating cell-free DNA methylation

  Acute coronary syndrome (ACS) remains a major cause of worldwide mortality. The syndrome occurs when blood flow to the heart muscle is decreased or blocked, causing muscle tissues to die or malfunction. There are three main types of ACS: Non-ST-elevation myocardial infarction, ST-elevation myocardial infarction, and unstable angina. The treatment depends on the type of ACS, and this is decided by a combination of clinical findings, such as electrocardiogram and plasma biomarkers. Circulating cell-free DNA (ccfDNA) is proposed as an additional marker for ACS since the damaged tissues can release DNA to the bloodstream. We used ccfDNA methylation profiles for differentiating between the ACS types and provided computational tools to repeat similar analysis for other diseases. We leveraged cell type specificity of DNA methylation to deconvolute the ccfDNA cell types of origin and to find methylation-based biomarkers that stratify patients. We identified hundreds of methylation markers associated with ACS types and validated them in an independent cohort. Many such markers were associated with genes involved in cardiovascular conditions and inflammation. ccfDNA methylation showed promise as a non-invasive diagnostic for acute coronary events. These methods are not limited to acute events, and may be used for chronic cardiovascular diseases as well.

  Study EGAS00001007263

• Host pathogen interaction long read transcriptome

  Our incomplete knowledge of the human transcriptome impairs the detection of disease-causing variants, in particular in transcripts only expressed under certain conditions. These transcripts are often lacking from reference transcript sets, such as Ensembl/GENCODE and RefSeq, and could be relevant for establishing genetic diagnoses. We present SUsPECT (Solving Unsolved Patient Exomes/gEnomes using Custom Transcriptomes), a pipeline based on the Ensembl Variant Effect Predictor (VEP) to predict variant impact on custom transcript sets, such as those generated by long-read RNA-sequencing, for downstream prioritization. Our pipeline predicts the functional consequence and likely deleteriousness scores for missense variants in the context of novel open reading frames predicted from any transcriptome. We demonstrate the utility of SUsPECT by uncovering potential mutational mechanisms of pathogenic variants in ClinVar that are predicted to be benign using the reference transcript annotation. In further support of SUsPECT’s utility, we identified an enrichment of immune-related variants predicted to have a more severe molecular consequence when annotating with a newly generated transcriptome from stimulated immune cells instead of the reference transcriptome. Our pipeline outputs crucial information for further prioritization of potentially disease-causing variants for any disease and will become increasingly useful as more long-read RNA sequencing datasets become available.

  Study EGAS00001006779

• Integrative Multi-Omics and Drug Sensitivity Profiling Reveals Potential Predictive Biomarkers in Pediatric Solid Tumors from the INFORM Registry

  Cure rates for childhood malignancies using established therapy protocols have increased to an average of 80% but have reached a plateau. Moreover, survival rates are particularly low for some pediatric tumors (such as high-risk Group3 medulloblastomas, osteosarcomas, Ewing sarcomas, high-risk neuroblastomas and high-grade gliomas) and dismal for patients with relapsed malignancies. A functional drug response profiling platform for pediatric solid and brain tumors has been established within the INFORM program to identify patient-specific vulnerabilities, biomarkers and unravel molecular mechanisms associated with drug response profiles for clinical translation. Here, we perform a multi-omics analysis using drug sensitivity profiles, genomic, and transcriptomic data of 81 pediatric solid tumor samples. The integrative analysis revealed two multi-omics signatures with high drug sensitivity predictivity. One signature highlighted neuroblastoma samples with sensitivity to navitoclax (a BCL-2 family inhibitor). A second signature was significantly specific to a subset of Wilms tumors harboring the SIX1 (Q177R) hotspot mutation, which had high expression of MGAM, PTPN14, STAT4 and KDM2B and high sensitivity to MEK inhibitors. A patient-specific causal interaction network analysis elucidated the potential biological mechanism of action between MEK inhibitors and the SIX1 mutation in n = 6 Wilms tumor samples.

  Study EGAS00001008249

• Identification of biomarkers of response to preoperative talazoparib monotherapy in treatment naïve gBRCA+ breast cancers

  Germline mutations in BRCA1 or BRCA2 exist in ~2-7% of breast cancer patients, which has led to the approval of PARP inhibitors in the advanced setting. We have previously reported a phase II neoadjuvant trial of single agent talazoparib for patients with germline BRCA pathogenic variants with a pathologic complete response (pCR) rate of 53%. As nearly half of the patients treated did not have pCR, better strategies are needed to overcome treatment resistance. To this end, we conducted multi-omic analysis of 13 treatment naïve breast cancer tumors from patients that went on to receive single-agent neoadjuvant talazoparib. We looked for biomarkers that were predictive of response (assessed by residual cancer burden) after 6 months of therapy. We found that all resistant tumors exhibited either the loss of SHLD2, expression of a hypoxia signature, or expression of a stem cell signature. These results indicate that the deep analysis of pre-treatment tumors can identify biomarkers that are predictive of response to talazoparib and potentially other PARP inhibitors, and provides a framework that will allow for better selection of patients for treatment, as well as a roadmap for the development of novel combination therapies to prevent emergence of resistance.

  Study EGAS00001005676

• PASCAL-MID Data Access Committee

  DAC for the center of Personalized Approach to Genome Editing of Stem Cells for Autotransplantation of Monogenic Immunodeficiencies (PASCAL-MID) at Aarhus University and Aarhus University Hospital

  Dac EGAC50000000680

• DATA FILES FOR SJPHALL

  DATA FILES FOR SJPHALL

  Dataset EGAD00001000163