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• Somatic Mutations and Their Etiological Determinants for Breast Cancer in African American Women (B-CAUSE Study)

  The breast cancer health disparity between women of African ancestry (AA) and European ancestry (EA) remains a major public health challenge in the United States. AA women are afflicted by higher rate of triple-negative breast cancer (TNBC) and bear the highest mortality rate of all populations from the disease. Even within TNBC, some data suggest that AA women have poorer outcomes than EA women. Mounting evidence points to population differences in cancer biology, a fundamental question that remains unsettled. The disparity also manifests in representativeness in tumor sequencing projects, due to the low inclusion of AAs in genomic studies. A recent analysis of The Cancer Genome Atlas (TCGA) data revealed that the number of AA cases sequenced was sufficient only for studying frequently mutated genes (≥10%), and the power was worse for TNBC as a separate disease entity. As a result, the breast tumor mutational landscape elucidated to date is derived mostly from EA cases, and may not necessarily represent AA cancer genomes. Moreover, as discovery potential for new driver genes has come close to a plateau, cancer in AAs derived from distinct genetic and environmental contexts may provide a powerful venue for discovering mutations that are rare in EA cases. This is showcased in recent studies in colon and prostate cancer. Thus, we carried out a collaborative project, B-CAUSE, to characterize the mutational landscape of AA breast cancer genomes by pooling resources from five established studies, including the Women's Circle of Health Study (WCHS), the Black Women's Health Study (BWHS), the Southern Community Cohort Study (SCCS), the Nashville Breast Health Study (NBHS), and the Southern Tri-State Breast Health Study (STSBHS). This effort has created the largest AA-specific breast tumor mutation dataset to date in an efficient manner. The data deposited here are from the whole-exome sequencing (WES) of matched tumor-normal pairs of 462 TNBC in AA women from the B-CAUSE Study.

  Study phs003962

• Nala GSI GSAv3 PGx Study

  Background: Microarrays are a well-established and widely adopted technology capable of interrogating hundreds of thousands of loci across the human genome. Combined with imputation to cover common variants not included in the chip design, they offer a cost-effective solution for large-scale genetic studies. Beyond research applications, this technology can be applied for testing pharmacogenomics, nutrigenetics, and complex disease risk prediction. However, establishing clinical reporting workflows requires a thorough evaluation of the assay's performance, which is achieved through validation studies. In this study, we performed pre-clinical validation of a genetic testing workflow based on the Illumina Global Screening Array for 25 pharmacogenomic-related genes. Methods: To evaluate the accuracy of our workflow, we conducted multiple pre-clinical validation studies. Here, we present the results of accuracy and precision assessments, involving a total of 73 cell lines. These assessments encompass reference materials from the Genome-In-A-Bottle (GIAB), the Genetic Testing Reference Material Coordination Program (GeT-RM) projects, as well as additional samples from the 1000 Genomes project (1KGP). We conducted an accuracy assessment of genotype calls for target loci in each indication against established truth sets. Results: In our per-sample analysis, we observed a mean analytical sensitivity of 99.39% and specificity 99.98%. We further assessed the accuracy of star-allele calls by relying on established diplotypes in the GeT-RM catalogue or calls made based on 1KGP genotyping. On average, we detected a diplotype concordance rate of 96.47% across 14 pharmacogenomic-related genes with star allele-calls. Lastly, we evaluated the reproducibility of our findings across replicates and observed 99.48% diplotype and 100 % phenotype inter-run concordance. Conclusion: Our comprehensive validation study demonstrates the robustness and reliability of the developed workflow, supporting its readiness for further development for applied testing.

  Study EGAS00001007710

• Emirati Genome Project subset of 43,608 WGS samples for population-scale variant discovery and allele frequency mapping.

  Here, we present a comprehensive genomic characterization of a cohort of 43,608 Emirati genomes sequenced as part of the Emirati Genome Program (EGP). This study identified more than 421 million single nucleotide variants and indels and more than 600 million copy number- and structural variants. Small variants had 756 million molecular effects annotated. Of the identified variants, 69.04% were observed with more than one allele. Of 7.7 million polymorphic variants having an allele frequency (AF) of more than 5% in EGP, 1,348 have a predicted deleterious effect on a protein. Characterization of global variation reveals that EGP represents a genetic continuum encompassing the range of African, Asian, and European populations. It is best described by two Arabian, an Eurasian, and an African component, with the predominant Arabian component linked to mitochondrial haplogroups J and T, which are commonly attributed to the Middle East. Various aneuploidies of sex chromosomes were detected in 93 individuals overall and of chromosome 21 in 41 individuals. The median inbreeding coefficient and cumulative runs of homozygosity (ROHs) lengths were increased due to extensive consanguinity, being largest in the groups with Arabian main ancestry components and higher than reported for Qatar. Families were identified based on genetic relatedness and classified into 264 families with unrelated parents and 247 families with third- and fourth-degree consanguineous parents. Representative consanguineous pedigrees of families in EGP were outlined. Cumulative ROHs were affected by the main ancestry component and significantly increased in offspring of consanguineous parents, with a pronounced difference between 3rd and 4th-degree relatedness. Investigation of cumulative AFs of variants causing Mendelian diseases highlighted genes related to alpha- and beta-thalassemia (HBB, HBA2). It showed a high burden of variants causing severe recessive diseases, metabolic and retinal disorders, and hearing loss. In summary, EGP represents a landmark effort in characterizing the genetic diversity of the Emirati population, leveraging the largest Middle Eastern cohort reported to date.

  Study EGAS50000001071

• Liver biopsy derived induced pluripotent stem cells provide an unlimited supply for the generation of patient-specific hepatocyte-like cells

  Background: Hepatocyte-like cells (HLCs) differentiated from induced pluripotent stem cells (iPSCs) have emerged as a promising cell culture model to study metabolism, biotransformation, viral infections and genetic liver diseases. However the derivation of iPSCs is restricted by ethical and procedural constraints. Furthermore, incomplete HLC differentiation remains a major challenge. iPSC may carry-on a tissue of origin dependent expression memory influencing iPSC differentiation into different cell types. If liver derived iPSCs (Li-iPSCs) maintain a liver specific gene expression profile is not known. It is also not known, if Li-iPSCs would allow the generation of more fully differentiated HLCs.Methods: Primary liver cells (PLCs) were expanded from liver needle biopsies and reprogrammed into Li-iPSCs using a non-integrative Sendai virus-based system. Li-iPSCs were differentiated into HLCs using established differentiation protocols. The HLC phenotype was characterized at the protein, functional and transcriptional level. RNA sequencing data were generated from the originating liver biopsies, the Li-iPSCs, fibroblast derived iPSCs, and differentiated HLCs, and used to characterize and compare their transcriptome profiles.Results: PLCs were obtained from small pieces of liver biopsies and could be reprogrammed into Li-iPSCs. Li-iPSCs indeed retain a liver specific transcriptional footprint. Li-iPSCs can be propagated to provide an unlimited supply of cells for differentiation into Li-HLCs. Similar to HLCs derived from fibroblasts, Li-HLCs could not be fully differentiated into hepatocytes. Relative to the originating liver, Li-HLCs showed lower expression of liver specific transcription factors and increased expression of genes involved in the differentiation of other tissues.Conclusions: PLCs and Li-iPSCs obtained from small pieces of human needle liver biopsies constitute a novel unlimited source for the production of HLCs. Despite the preservation of a liver specific gene expression footprint in Li-iPSCs, the generation of fully differentiated hepatocytes cannot be achieved with the current differentiation protocols.

  Study EGAS00001002676

• Whole exome sequencing of germline DNA was performed and subsequent polymorphisms in genes known and putatively involved in the innate immune response to fungi were identified

  Disease can be conceptualized as the result of interactions between infecting microbe and holobiont, the combination of a host and its microbial communities. It is likely that genomic variation in the host, infecting microbe, and commensal microbiota are key determinants of infectious disease clinical outcomes. However, until recently, simultaneous, multiomic investigation of infecting microbe and holobiont components has rarely been explored. Herein, we characterized the infecting microbe, host, micro- and mycobiomes leading up to infection onset in a leukemia patient that developed invasive mucormycosis. We discovered that the patient was infected with a strain of the recently described Mucor velutinosus species which we determined was hypervirulent in a Drosophila challenge model and has a predisposition for skin dissemination. After completing the infecting M. velutinosus genome and genomes from four other Mucor species, comparative pathogenomics was performed and assisted in identifying 66 M. velutinosus-specific putatively secreted proteins, including multiple novel secreted aspartyl proteinases which may contribute to the unique clinical presentation of skin dissemination. Whole exome sequencing of the patient revealed multiple non-synonymous polymorphisms in genes critical to control of fungal proliferation, such as TLR6 and PTX3. Moreover, the patient had a non-synonymous polymorphism in the NOD2 gene and a missense mutation in FUT2, which have been linked to microbial dysbiosis and microbiome diversity maintenance during physiologic stress, respectively. In concert with host genetic polymorphism data, the micro- and mycobiome analyses revealed that the infection developed amid a dysbiotic microbiome with low α-diversity, dominated by staphylococci. Additionally, longitudinal mycobiome data showed that M. velutinosus DNA was detectable in oral samples preceding disease onset. Our genome-level study of the host-infecting microbe-commensal triad extends the concept of personalized genomic medicine to the holobiont-infecting microbe interface thereby offering novel opportunities for using synergistic genetic methods to increase understanding of infectious diseases pathogenesis and clinical outcomes.

  Study EGAS00001001542

• Bulk-RNA Sequencing of high-grade pancreatic and non-pancreatic Neuroendocrine Neoplasms

  Therapeutic decisions in oncology depend on a precise pathological classification of individual neoplasms. Recent years have seen an intensification of research activities aimed at the extraction of clinically relevant information from patient-derived 'omics' data based on Machine-Learning models. However, a comprehensive training of Machine-Learning models requires sufficiently large numbers of training samples, which are usually not available for rare cancer types. The problem is worsened when individual tissues segregate into different cancer subtypes, as their discrimination would require even more training samples. Methods: Here, we report on a new data-augmentation technique to support the training of Machine-Learning models on ‘omics’ data from pancreatic neuroendocrine neoplasms (panNEN). PanNENs display all properties described above: Only about 2-3% of all pancreatic neoplasms are neuroendocrine and they fall into different subtypes with distinctly different prognosis, which makes the precise classification of such samples both difficult and important for therapy decisions. The approach reconstructs a given transcriptome based on healthy pancreatic cell type signatures and creates a Machine-Learning model that integrates the observed reconstruction error and predicted cell type proportions as features. Results: A benchmark of the deconvolution model predictions with the ground-truth found that the model could efficiently predict the sample grading, disease-related patient survival time, and differentiate between different subtypes in four panNEN and one mixed panNEN and non-pancreatic NENs dataset. We compared the predictive performance of the deconvolution-trained model to that of a model trained directly on the transcriptomic data, under inclusion of the Ki-67 classification gold standard biomarker, and found the performances to be comparable. Conclusion: Our approach serves as a data-augmentation technique to facilitate the training of Machine Learning models for rare cancer types via utilization of data from healthy origin. Additionally, the deconvolution results were clinically interpretable and further research can render the deconvolution approach an effective complementary asset for the clinical classification of neoplasms.

  Study EGAS00001004861

• ctDNA to predict risk of progression and death after trifluridin/tipiracil therapy

  Background. Late-line treatment in metastatic colorectal cancer (mCRC) can improve the prognosis. However, not every patient has a benefit and may experience severe side effects. Thus, predictive/prognostic biomarkers are urgently needed. Despite many promising results, the role of circulating tumor DNA (ctDNA) analysis in trifluridin/tipiracil (FTD/TPI) treated mCRC patients is so far still elusive. Study design. This prospective non-interventional translational biomarker phase II study enrolled 30 metastatic CRC patients treated with FTD/TPI. The primary study aim was to identify a molecular biomarker to predict overall survival (OS) benefit upon FTD/TPI treatment. Methods. mCRC patients (60% male, 40% female) with FTD/TPI therapy were included. Molecular profiling in cell-free DNA from plasma was performed prior to treatment and on average 4, 8 and 12 weeks after FTD/TPI initiation. Tumor levels were assessed as the highest variant allele frequency (hVAF) and correlated with OS. Uni- and multivariate analyses for survival were performed with clinical variables. Multivariate analyses for survival and treatment efficacy were adjusted to age, gender and ECOG performance status. Results. Compared to previous data, our disease control rate of 30% was lower with a median OS of 8.1 months and a median PFS of 3.2 months. At baseline (BL) and the first two follow-ups (FU), a hVAF cut-off of 7.5% was most discriminative (BL HR 0.39 95% CI 0.16 - 0.98 P=0.0212, FU1 HR 0.30 95% CI 0.12 -0.77 P=0.0021, FU2 HR 0.23 95% CI 0.08-0.70 P=0.0004) whereas at the last follow-up the stratification was most pronounced at a 15% cut-off. An elevated hVAF trajectory over time was associated with a higher risk of death. Conclusion. ctDNA is detectable in a high proportion of mCRC patients. Changes in ctDNA levels are associated with survival among FTD/TPI therapy and may identify patients who benefit most from treatment in these late-stage disease.

  Study EGAS00001006883

• Exome_sequencing_of_EBV_driven_lymphoma

  Exome sequencing of a case of lethal EBV-driven LPD

  Study EGAS00001001021

• scD&D-seq of mobilized PBMC from a healthy individual having IDH2 R140Q CHIP

  Single-cell D&D-seq profiles from a mobilized CHIP (clonal hematopoiesis of indeterminate potential) PBMC sample (2 replicates) co-profiled with IDH2 R140Q GoT-ChA.

  Study EGAS50000001590

• Whole Exome Sequencing of a Chinese Cataract Girl

  Whole exome sequencing of a Chinese girl with congenital cataract. The dataset contains one sample with two fastq files. The novel PAX6 mutation (c.221G>A) is associated with congenital cataract, and the WFS1 mutation (c.2070_2079del) interactively aggravates this process.

  Dataset EGAD00001008267