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• Immuno-genomic Profiling of Biopsy Specimens Predicts Neoadjuvant Chemotherapy Response in Esophageal Squamous Cell Carcinoma

  Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive cancers and is primarily treated with platinum-based neoadjuvant chemotherapy (NAC). Some ESCCs respond well to NAC. However, biomarkers to predict NAC sensitivity and their response mechanism in ESCC remain unclear. We introduce a model by machine learning and validated its potential to predict the NAC response in ESCC. To create this model, we performed whole genome sequencing and RNA-seq analysis on totally 141 ESCC biopsy specimens before NAC treatment and analyzed their immuno-genomic features and association with NAC response. Neutrophils infiltration could play an important role in ESCC response to NAC. We also demonstrated that specific copy number alterations and copy number signatures in the ESCC genome were significantly associated with NAC response. The interactions between the tumor genome and immune features of ESCC are likely to be a new indicator of therapeutic capability and a new therapeutic target for ESCC, and machine learning prediction for NAC response is useful.

  Study JGAS000535

• FetalQuant-SD: Accurate quantification of fetal DNA fraction by shallow-depth sequencing of maternal plasma DNA

  Noninvasive prenatal testing using massively parallel sequencing of maternal plasma DNA has been rapidly adopted in clinical use worldwide. Fetal DNA fraction in a maternal plasma sample is an important parameter for accurate interpretations of these tests. However, there is a lack of methods involving low-sequencing depth and yet would allow a robust and accurate determination of fetal DNA fraction in maternal plasma for all pregnancies. In this study, we have developed a new method to accurately quantify the fetal DNA fraction by analysing the maternal genotypes and sequencing data of maternal plasma DNA. Fetal DNA fraction was calculated based on the proportion of non-maternal alleles at single-nucleotide polymorphisms where the mother is homozygous. This new approach achieves a median deviation of 0.6% between predicted fetal DNA fraction and the actual fetal DNA fraction using as low as 0.03-fold sequencing coverage of the human genome. We believe that this method will further enhance the clinical interpretations of noninvasive prenatal testing using genome-wide random sequencing.

  Study EGAS00001001611

• Genome-wide mutational consequences of nucleotide excision repair-deficiency through XPC deletion in a human adult stem cell culture

  Nucleotide excision repair (NER) is one of the main DNA repair pathways that protect cells against genomic damage. Deficiency in this pathway can contribute to the development of cancer and accelerate aging. NER-deficiency is an important determinant for cancer treatment outcome, as NER-deficient tumors are selectively sensitive to cisplatin treatment. While NER-deficiency has been linked to mutational Signature 5, not all NER-deficient tumors are characterized by a high Signature 5 contribution, illustrating the importance to further characterize the mutational consequences of NER-deficiency. Here, we analyzed the mutational profile of a human adult stem cell (organoid) culture that is deficient in NER through XPC deletion by CRISPR-Cas9 gene-editing, and subsequent whole-genome sequencing analysis of a clonally derived organoid. We found that XPC deletion results in an increase in base substitution load and specifically induces Signature 8 mutations, a mutational signature with previously unknown etiology. Presence of Signature 8 may, therefore, serve as a novel biomarker for NER-deficient tumors and could improve personalized treatment strategies.

  Study EGAS00001002681

• Single cell and spatial transcriptomics of adult human adrenal glands

  The data set is composed of single cell transcriptomics data for adrenal glands from 11 deceased organ donors (10x 3') and spatial transcriptomic data for adrenal glands from 4 deceased organ donors (10x Visium).

  Dataset EGAD50000000394

• Oncoprint GSCCs

  This dataset contains DNA sequencing data from 7 GSCCs (data for BT569 is not available). We performed focused exome sequencing (43 most mutated genes in GBM), combined with OneSeq analysis (Agilent) on the GSCCs and identified both shared and GSCC-specific mutations. For CME038, whole genome sequencing was performed.

  Dataset EGAD00001011276

• Genotyping of GM samples

  This dataset contains a vcf file for 99 GM individuals genotyped on the Illumina HumanOmni2.5 array . The vcf file is originated after imputation (IMPUTE2) and filtering for minor allele frequency MAF≥0.05, imputation confidence score INFO of >0.4 and Hardy-Weinberg Equilibrium (HWE) p>1e-06, yielding ~6.3 million variants.

  Dataset EGAD00001010255

• Varieties of Impulsivity in Opiate and Stimulant Users

  The study was conducted in Bulgaria as a collaboration between Virginia Commonwealth University (Richmond, VA, USA), the Bulgarian Addictions Institute (Sofia, Bulgaria), the Molecular Medicine Center/Medical University (Sofia, Bulgaria), and Indiana University (Bloomington, IN, USA). The overall aim of this study is to investigate the role of impulsivity as an endophenotype for drug addiction. Although impulsivity is considered one of the strongest candidate endophenotypes for addiction, progress in the field is hampered by the heterogeneity of impulsivity, characterized by multiple personality, psychiatric, and neurocognitive dimensions, rarely examined concurrently in the same population; and the heterogeneity of addiction phenotypes, due in part to the high rates of polysubstance dependence among substance users. To address these challenges, we have developed a program of addiction research in Bulgaria, a key transit country for heroin trafficking due to its strategic geographical location on the "Balkan Drug Route" and a major European center for production of synthetic amphetamine-type stimulants. This has allowed us to access rare populations of predominantly mono-substance dependent heroin and amphetamine users, many in protracted abstinence. Our preliminary results reveal a complex relationship between trait and neurocognitive (state) dimensions of impulsivity, often manifested in opposite directions in heroin and amphetamine dependent individuals. Pilot computational modeling analyses of decision-making, a central neurocognitive aspect of impulsivity, have proved particularly informative by indicating that different mechanisms may underlie the impaired decision-making of opiate and stimulant users. A different modeling approach, i.e. phenotypic modeling, holds significant promise to address the pervasive "missing heritability" problem in genetic studies. While genetic heterogeneity is often invoked as an explanation, the manner in which complex phenotypic traits are measured and modeled is equally important contributor to the missing heritability problem but has received much less attention in the literature. Despite the multidimensionality of traits measured by psychometric, diagnostic, and neurocognitive instruments, most GWAS studies typically use aggregate sum scores that do not reflect the underlying phenotypic multidimensionality. Therefore, at least part of the missing heritability problem may originate in misspecification of the phenotypic models. Consequently, sample sizes requirements may increase from ~800 subjects in correctly specified models to 6,000-16,000 subjects in incorrectly specified models. The current study aims to increase our understanding of the complex relationship between multiple putative impulsivity endophenotypes to help redefine endophenotypes as multi-level combination of measures that could inform multivariate multilevel models of complex phenotypes. The specific aims of the study are to: (1) Assess the utility of various personality, psychiatric, and neurocognitive indices of impulsivity (either individually or in combination) as candidate endophenotype(s) for drug addiction in general and for opiate and stimulant addictions in particular; (2) Evaluate the viability of computational model parameters modeling various neurocognitive dimensions of impulsivity as novel endophenotype(s) for addiction; and (3) Test the external validity of the optimal endophenotype(s) by evaluating their associations with HIV and other risk behaviors in opiate and stimulant users in protracted abstinence, a question of critical importance for prevention and intervention efforts in this much less-well understood stage of the addiction cycle.

  Study phs001647

• DAC Johns Hopkins University - AML scRNAseq study

  This is the Data Access Committee (DAC) from Johns Hopkins University for the study scRNAseq of acute myeloid leukemia

  Dac EGAC50000000242

• CNCD Recall by Genotypes

  This is a DAC to handle recall by genotype studies by the conducted by the Center for Non-Communicable Disease Karachi, Pakistan.

  Dac EGAC50000000937

• MPNST exome and genome

  This is the complete dataset (exome and genome) for the EGAS00001000974 study.

  Dataset EGAD00001001040