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• Transcriptional profiling of ovarian tumours and cell lines

  Purpose: Endogenous retroviruses (ERVs) play a role in a variety of biological processes, including embryogenesis and cancer. DNA methyltransferase inhibitors (DNMTi)-induced ERV expression triggers interferon responses in ovarian cancer cells via the viral sensing machinery. Baseline expression of ERVs also occurs in cancer cells, though this process is poorly understood and previously unexplored in epithelial ovarian cancer (EOC). Here, the prognostic and immunomodulatory consequences of baseline ERV expression was assessed in EOC. Experimental Design: ERV expression was assessed using EOC transcriptional data from TCGA and from an independent cohort (HH), as well as from untreated or DNMTi-treated EOC cell lines. LASSO logistic regression defined an ERV expression score to predict patient prognosis. Immunohistochemistry (IHC) was conducted on the HH cohort. Combination of DNMTi treatment with γδ T cells was tested in vitro, using EOC cell lines and patient-derived tumor cells. Results: ERV expression was found to define clinically relevant subsets of EOC patients. An ERV prognostic score was successfully generated in TCGA and validated in the independent cohort. In EOC patients from this cohort, a high ERV score was associated with better survival (log-rank p=0.0009) and correlated with infiltration of CD8+PD1+ T cells (r=0.46, p=0.0001). In vitro, baseline ERV expression dictates the level of ERV induction in response to DNMTi. Manipulation of ERV expression by DNMTi resulted in improved EOC cell killing by cytotoxic immune cells. Conclusions: These findings uncover the potential for baseline ERV expression to robustly inform EOC patient prognosis, influence tumor immune infiltration and affect anti-tumor immunity.

  Study EGAS00001004814

• Transcriptomic intra-tumor heterogeneity of colorectal cancer varies depending on tumor location within the colorectum

  Background; Intra-tumor heterogeneity (ITH) of colorectal cancer (CRC) complicates molecular tumor classification, such as transcriptional subtyping. Differences in cellular states, biopsy cell composition, and tumor microenvironment may all lead to ITH. Here we analyze ITH at the transcriptomic and proteomic levels to ascertain whether subtype discordance between multiregional biopsies reflects relevant biological ITH or lack of classifier robustness. Further, we study the impact of tumor location on ITH.MethodsMultiregional biopsies from stage II and III CRC tumors were analyzed by RNA sequencing (41 biopsies, 14 tumors) and multiplex immune protein analysis (89 biopsies, 29 tumors). CRC subtyping were performed using consensus molecular subtypes (CMS), CRC intrinsic subtypes (CRIS), and TUMOR types. ITH-scores and network maps were defined to determine the origin of heterogeneity. A validation cohort was used with one biopsy per tumor (162 tumors).ResultsOverall, inter-tumor transcriptional variation exceeded ITH, and subtyping calls were frequently concordant between multiregional biopsies. Still, some tumors had high ITH and were classified discordantly. Proximal tumors showed ITH related to differences in the microenvironment, while ITH within distal tumors were cancer-cell related. This subtype discordancy reflected actual molecular ITH within the tumors. The relevance of the subtypes was reflected at protein level where several inflammation markers were significantly increased in immune related transcriptional subtypes, which was verified in an independent cohort (Wilcoxon rank sum test; p<0.05).ConclusionOur transcriptomic and proteomic analyses show that the tumor location along the colorectum influence the ITH of CRC, which again influence the concordance of subtyping.

  Study EGAS00001004668

• Analysis of recent shared ancestry in a familial cohort identifies coding and noncoding autism spectrum disorder variants

  Autism spectrum disorder (ASD) is a collection of neurodevelopmental disorders characterized by deficits in social communication and restricted, repetitive patterns of behavior or interests. ASD is highly heritable, but genetically and phenotypically heterogeneous, reducing the power to identify causative genes. We performed whole genome sequencing (WGS) in an ASD cohort of 68 individuals from 22 families enriched for recent shared ancestry. We identified an average of 3.07 million variants per genome, of which an average of 112,512 were rare. We mapped runs of homozygosity (ROHs) in affected individuals and found an average genomic homozygosity of 9.65%, consistent with expectations for multiple generations of consanguineous unions. We identified potentially pathogenic rare exonic or splice site variants in 12 known (including KMT2C, SCN1A, SPTBN1, SYNE1, ZNF292) and 12 candidate (including CHD5, GRB10, PPP1R13B) ASD genes. Furthermore, we annotated noncoding variants in ROHs with brain-specific regulatory elements and identified putative disease-causing variants within brain-specific promoters and enhancers for 5 known ASD and neurodevelopmental disease genes (ACTG1, AUTS2, CTNND2, CNTNAP4, SPTBN4). We also identified copy number variants in two known ASD and neurodevelopmental disease loci in two affected individuals. In total we identified potentially etiological variants in known ASD or neurodevelopmental disease genes for ~61% (14/23) of affected individuals. We combined WGS with homozygosity mapping and regulatory element annotations to identify candidate ASD variants. Our analyses add to the growing number of ASD genes and variants and emphasize the importance of leveraging recent shared ancestry to map disease variants in complex neurodevelopmental disorders.

  Study EGAS00001006058

• RaScALL: Rapid screening of RNA-seq in acute lymphoblastic leukaemia

  RNA-sequencing (RNA-seq) efforts in acute lymphoblastic leukaemia (ALL) have identified numerous prognostically significant genomic alterations which can guide diagnostic risk stratification and treatment choices when detected early. However, a full RNA-seq Bioinformatics workflow is time-consuming and costly in a clinical setting where rapid detection and accurate reporting of clinically relevant alterations are essential. To accelerate the identification of ALL-specific alterations (including gene fusions, single nucleotide variants and focal gene deletions), we developed the rapid screening tool RaScALL, capable of identifying more than 100 prognostically significant lesions directly from raw sequencing reads. RaScALL uses the k-mer based targeted detection tool km and known ALL variant information to achieve a high degree of accuracy for reporting subtype defining genomic alterations compared to standard alignment-based pipelines. Gene fusions, including difficult to detect fusions involving EPOR and DUX4, were accurately identified in 98% (164 samples) of reported cases in a 180-patient Australian study cohort and 95% (n=63) of samples in a North American validation cohort. Pathogenic sequence variants were correctly identified in 75% of tested samples, including all cases involving subtype defining variants PAX5 p.P80R (n=12) and IKZF1 p.N159Y (n=4). Accurate detection of intragenic IKZF1 deletions resulting in aberrant transcript isoforms was also detectable with 98% accuracy. Importantly, the median analysis time for detection of all targeted alterations averaged 22 minutes per sample, significantly shorter than standard alignment-based approaches, ensuring accerelated risk-stratification and therapeutic triage.

  Study EGAS00001006460

• Chronic lymphocytic leukemia IGHV somatic hypermutation detection by targeted capture next-generation sequencing

  Somatic hypermutation (SHM) status of the immunoglobulin heavy variable (IGHV) gene locus plays a crucial role in determining the prognosis and treatment of patients with chronic lymphocytic leukemia (CLL). A common approach for determining SHM status is multiplex PCR of the IGH gene followed by Sanger sequencing; however, this technique is low throughput, vulnerable to failure, and does not allow multiplexing with other molecular diagnostic assays. Here we designed and validated a DNA targeted capture approach that allows the assessment of IGHV SHM status as a sub-module of a larger next-generation sequencing (NGS) assay. We developed an end-to-end assay that takes as input raw FASTQ files and outputs a report containing IGHV SHM status and V-allele usage following the guidelines of the European Research Initiative on CLL (ERIC). We validated the approach on 35 CLL patient samples, 34 of which were previously characterized using Sanger sequencing. The targeted capture NGS panel identified the SHM status of 34 of 35 CLL patients. We showed 100% sensitivity and specificity among the 33 CLL samples with both NGS and Sanger calls. Furthermore, we demonstrated that this panel can be combined with additional targeted capture panels to detect common and prognostically important CLL single nucleotide variants (SNV) and insertion/deletion (indel) variants as well as copy number variants (del17p). Thus, a targeted capture approach to IGHV SHM detection can be easily integrated into broader sequencing panels, allowing broad CLL prognostication in a single molecular assay.

  Study EGAS00001006887

• A Machine Learning Tool Integrating Circulating Cell-Free DNA Methylation with Clinical Variables for Non-Invasive Diagnosis of Liver Graft Pathology

  Liver Transplant Recipients (LTRs) with elevated liver enzymes can develop graft injury due to various etiologies, such as T-cell mediated rejection (TCMR) and NASH (NASH-LT). While liver biopsy is the gold standard method for diagnosis of graft pathology, it is invasive and is associated with risks. The goal of our study was to develop a Machine Learning (ML) tool integrating clinical variables with methylation patterns on circulating DNA in plasma as a non-invasive diagnostic tool of graft injury. We generated methylation profiles of circulating DNA in a pilot study of 43 LTRs (11 NASH-LT, 19 TCMR, and 13 Control-LT), and developed an L2 multinomial logistic regression ML approach across 101 bootstrapped models to distinguish between the graft conditions. NASH was associated with distinctive methylation patterns on genes involved in fatty acid metabolism, while methylation of platelet-derived growth factors was identified in patients with TCMR. Our ML model achieved a mean multi-classification accuracy of 0.91, with mean specificity and sensitivity of 0.94 and 0.91, respectively. The model was found to be particularly adept at detecting TCMR and Control-LT, with true positive rates (TPRs) of 95% and 90%, and areas under the curve (AUROC) of 0.992 and 0.985, respectively. For NASH-LT, the models achieved a performance with a TPR of 82% and an AUROC of 0.991. These preliminary results suggest that our newly developed ML tool, leveraging cell-free DNA methylation and clinical variables, is a promising non-invasive classifier of graft pathology.

  Study EGAS00001007171

• Clinical relevance of somatic copy-number alterations in plasma circulating tumor DNA from advanced EGFR-mutated NSCLC patients treated with osimertinib

  Background: Somatic copy-number alterations (SCNAs) are associated with drug resistance in patients with advanced epidermal growth factor receptor (EGFR)-mutated non-small cell lung cancer (NSCLC) treated with EGFR-tyrosine kinase inhibitors (TKIs). The purpose of our study was to assess the clinical relevance and development of genome-wide SCNAs in plasma circulating tumor DNA (ctDNA) under osimertinib therapy.Methods: We included 43 patients with advanced EGFR T790M-positive lung adenocarcinoma who were treated with osimertinib after progression under previous EGFR-TKI therapy. We performed genomic profiling of ctDNA in plasma samples from each patient obtained pre-osimertinib and after patients developed resistance to osimertinib. SCNAs were detected by shallow whole-genome plasma sequencing and EGFR mutations were assessed by droplet digital PCR.Results: SCNAs in resistance-related genes (rrSCNAs) were detected in 10 out of 39 (25.6%) evaluable patients before start of osimertinib. The presence of rrSCNAs in plasma before initiation of osimertinib therapy was associated with a lower response rate to osimertinib (50% versus 86%, p=0.02) and was an independent predictor for shorter progression-free survival (adjusted HR 3.26, 95% CI 1.37-7.75, p=0.008) and overall survival (adjusted HR 2.41, 95% CI 1.09-5.34, p=0.03).Conclusions: Genomic profiling of plasma ctDNA is clinically relevant and affects the efficacy and clinical outcome of osimertinib. Our approach allows comprehensive assessment of SCNAs in plasma samples of lung adenocarcinoma patients and may help to guide genotype-specific therapeutic strategies in the future.

  Study EGAS00001004539

• FHIR Test Study BETA

  FHIR Test Study BETA. This study was created with 3 consent groups to simulate an actual study for FHIR API testing project. The data herein is simulated and are intended for development of FHIR representation of dbGaP phenotype data.

  Study phs002410

• Developmental Maturation of Hematopoietic Stem and Progenitor Cells Mediated by Lin28b/Let-7/Cbx2

  This study encompasses two human cell lines used to profile polycomb repressive complex markers during hematopoietic maturation.  This study includes epigenomic mark sequencing data obtained via the CUT&RUN protocol.

  Study phs002507

• Major Depression: Stage 1 Genomewide Association in Population-Based Samples

  Identification of genomic regions that confer susceptibility to or protection from major depressive disorder (MDD) via genomewide association. Consent groups and participant set Psychiatric and Related Somatic Conditions (PRSC): 3741 (1821 cases, 1822 controls, 98 others)

  Study phs000020