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• Transcriptomics of Liver and PBMCs in Alcohol-Associated Liver Disease

  This study was designed to characterize the transcriptome of alcohol-associated hepatitis using RNA sequencing (RNA-seq) technology for both liver tissue biopsies and peripheral blood mononuclear cells (PBMCs) extracted from blood samples, in order to identify expressed genes that are markers of the disease. To distinguish genes that differentiate alcohol-associated hepatitis from other inflammatory liver diseases, we compared the RNA-seq data generated from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, non-alcohol-associated fatty liver disease, and healthy controls. We utilized computational approaches to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to identify a small set of gene biomarkers to distinguish between these liver diseases. The raw RNA-seq data will be available through dbGaP.

  Study phs003112

• MYC Drives Progression of Small Cell Lung Cancer to a Variant Neuroendocrine Subtype with Vulnerability to Aurora Kinase Inhibition

  Loss of the tumor suppressors RB1 and TP53 and MYC amplification are frequent oncogenic events in small cell lung cancer (SCLC). We show that Myc expression cooperates with Rb1 and Trp53 loss in the mouse lung to promote aggressive, highly metastatic tumors, that are initially sensitive to chemotherapy followed by relapse, similar to human SCLC. Importantly, MYC drives a neuroendocrine-low “variant” subset of SCLC with high NEUROD1 expression corresponding to transcriptional profiles of human SCLC. Targeted drug screening reveals that SCLC with high MYC expression is vulnerable to Aurora kinase inhibition, which combined with chemotherapy strongly suppresses tumor progression and increases survival. These data identify molecular features for patient stratification and uncover a novel targeted treatment approach for MYC-driven SCLC.

  Study EGAS00001002115

• XClone for analyzing somatic copy number alterations

  Somatic copy number alterations (CNAs) are major mutations that contribute to the development and progression of various cancers. Despite a few computational methods proposed to detect CNAs from single-cell transcriptomic data, the technical sparsity of such data makes it challenging to identify allele-specific CNAs, particularly in complex clonal structures. In this study, we present a statistical method, XClone, that strengthens the signals of read depth and allelic imbalance by effective smoothing on cell neighborhood and gene coordinate graphs to detect haplotype-aware CNAs from scRNA-seq data. By applying XClone to multiple datasets with challenging compositions, we demonstrated its ability to robustly detect different types of allele-specific CNAs and potentially indicate whole genome duplication, therefore enabling the discovery of corresponding subclones and the dissection of their phenotypic impacts.

  Study EGAS00001007854

• Exome_sequencing_of_thyroid_disease_in_Val_Borbera

  The Val Borbera is a region characterized by low iodine and high prevalence of thyroid disorders, the commonest endocrine disorders in the general population. About 30% of the participants of the Val Borbera Project were affected by such disorders and were characterized by several parameters, TSH level, anti TPO antibodies, echography, family origin. Individuals with extreme phenotypes were identified and could be clustered based on family origin and genotype. We propose to exome sequence 6 of them, affected with true goiter, at high dept (40-60x) to obtain information on exonic rare variants. Due to the family structure and to the availability of whole genome sequence information on 110 individuals from the isolated population we expect to be able to identify putative causative variants for thyroid disorders that may be studied in the remaining affected individuals.

  Study EGAS00001000344

• Molecular sub-classification of hormone receptor-positive breast cancer

  Patients with estrogen and/or progesterone receptor-positive breast cancer benefit from hormonal treatment, yet high global death burdens due to high prevalence and long-term recurrence risk call for biomarkers to guide additional treatment approaches. From a prospective, observational study of postmenopausal early breast cancer patients treated with tamoxifen or aromatase inhibitors gene expression analyses of 612 tumors was performed using the NanoString® Breast Cancer 360 panel. We identified novel gene expression signatures, i.e. BRCAness and Tumor Inflammation Signature (associated with high tumor lymphocyte infiltration), that may aid to select high-risk patients in order to improve adjuvant treatment by targeting DNA repair deficiency or immune-checkpoints in addition to standard chemo-endocrine treatment. The overall goal is to foster novel concepts for a stratified early breast cancer management.

  Study EGAS00001004594

• Gene expression adaptation of metastases to their host tissue

  The adaptation of metastatic cells to their host tissue critically determines the pathogenicity of a cancer and therefore patient survival. Yet, it remains elusive to what extent the host environment drives gene expression programs in metastatic cells. Here we identify adaptive mechanisms that enable metastases to establish themselves in a novel tissue context. We performed single-cell RNA-sequencing on malignant and benign tissue samples from untreated donors with colorectal adenocarcinoma and liver metastasis to deduce tissue adaptive expression patterns. A novel computational approach identified genes and pathways that consistently adapted to the host tissue at the transition from the primary tumor to the paired metastasis across donors. This analysis revealed that the majority of expression changes in the metastasis reflect an expression signature reminiscent of benign liver epithelial cells. Cellular processes adapting to the liver environment include basic cellular functions such as energy metabolism, as well as tissue-specific pathways such as the regulation of lipid metabolism by PPAR-α. These adaptations potentially increase the pathogenicity of the metastatic cells and may provide new therapeutic strategies.

  Study EGAS50000000817

• Cystic Fibrosis Nasal Epithelium Gene Expression by RNAseq

  Cystic fibrosis (CF) is a monogenic disorder leading to multi-organ system dysfunction, with the primary cause of morbidity and mortality being lung disease. Mutations in CFTR result in defective ion channel transport leading to hyperviscous mucus, airway infection, inflammation and lung function decline. While the Phe508del mutation is the most common CFTR mutation in North American people with CF, it is well known that there is a broad range of lung disease severity even amongst Phe508del homozygotes, including twins/siblings. Heritability analyses showing the relative contribution of non-CFTR modifier genes in such differences in phenotype, have led to our genomic and transcriptomic studies of gene modifiers in CF. Complementary to two international CF GWAS studies, this study was performed to a) determine differential expression of genes relative to a quantitative lung disease severity phenotype score (KNoRMA; as used in CF GWAS studies) and b) to assess expression quantitative trait loci. To better understand genetic modification of CF lung disease severity, we analyzed gene expression (transcriptomic) profiles by mRNA sequencing from nasal mucosal biopsy specimens of 134 people with CF. Each study participants was characterized for CF lung disease severity phenotype by averaging three years of lung function data (forced expiratory volume in 1 second; FEV1), normalized to a CF-specific reference population matching for age, sex, and height. Participants completed nasal lavage and nasal curettage mucosal sampling, with directed sampling to the inferior nasal turbinate, a well validated surrogate for cellular characteristics and CFTR function of the lower CF airways. Participants were further invited to complete a second set of these sampling procedures for validation analysis. Specimen and concurrent clinical data collection occurred across four North American study sites and nasal mucosal specimens were subjected to RNASeq analysis. These data were to be made available in the dbGaP. Our association analyses of gene expression relative to quantitative CF lung disease phenotype, taken together with previously identified GWAS signals, identified biological pathways correlated with CF lung disease pathogenesis. Our further association analyses of gene expression relative to single nucleotide polymorphism variation at significant CF GWAS loci further identified potential mechanisms of genetic variants associated with CF lung disease. This resource is intended to aid researchers in characterizing airway mucosal gene expression from the CF airways for the purpose of gene expression profiling in CF and in muco-obstructive airways disease.

  Study phs002254

• Next-generation sequencing-based comprehensive genetic analysis of undiagnosed disease

  The purpose of this study is to perform comprehensive genetic analysis using next-generation sequencers to make genetic diagnosis of "undiagnosed diseases".

  Study JGAS000522

• Single_Cell_Targeted_Sequence_Capture

  This study is to ascertain whether it is feasible to extract single cell from a tumour, perform amplification, generate a library and sequence a targeted pulldown.

  Study EGAS00001000435

• Exome_sequencing_of_Bilateral_Anophthalmia_cases__Pilot_Study_

  This pilot study aims to generate pilot data to inform future study designs by resequencing the whole exomes of 10 unrelated individuals diagnosed with Bilateral Anophthalmia.

  Study EGAS00001000356