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• cfDNA and CDX/PDX methylation profiling in SCLC

  We profiled the whole genome methylome of SCLC preclinical models and cfDNA samples. We assessed the sensitivity of cfDNA methylation profiling in detecting SCLC, especially at earlier stage of disease and the ability in discriminate among different SCLC molecular subtypes.

  Study EGAS00001005739

• Insights from genome-wide data from Thailand and Laos

  We provide the first detailed insights into the genetic profiles of Thai/Lao ethnolinguistic groups, which should be helpful for reconstructing human genetic history in MSEA and selecting populations for participation in ongoing whole genome sequence and biomedical studies

  Study EGAS00001006053

• Characterization of Leukemic Stem Cells in DNMT3Amut and NPM1mut AMLs

  Using a novel sorting strategy, we performed ultra low input RNAseq from FACS-sorted populations from diagnostic DNMT3Amut and NPM1mut AML patients. Primary samples were retrospectively collected based on their mutational profile. Samples were thawed, stained and FACS sorted using combination of lineage markers, CD34, GPR56 and NKG2DLigands. RNA was extracted and library prepared from 13 samples.

  Dataset EGAD00001009293

• Dataset of 4 WGS and 35 WES tumor and control runs linked for the ImmuNEO publication out of EGAS00001004813

  Sequencing data of 39 tumor and control runs (different tumors and blood controls), which were uploaded to EGAS00001004813 and reused in this ImmuNEO publication. The sequencing was always paired.

  Dataset EGAD00001009671

• RNA-sequencing and targeted DNA-sequecing of human thyroid tumors and normal samples

  RNA-sequencing data: 5 normal thyroid tissues, 14 papillary thyroid carcinomas, 2 lymph node metastases, 19 poorly differentiated thyroid carcinomas and 17 anaplastic thyroid carcinomas; Targeted DNA-sequencing of the 165 genes included in the “Solid and Haematological tumors” panel (BRIGHTCore, Brussels, Belgium): 2 normal thyroid tissues, 2 poorly differentiated thyroid carcinomas and 7 anaplastic thyroid carcinomas; 2 FASTQ files for each sample (paired).

  Dataset EGAD00001011678

• Spatially resolved transcriptomics reveals profound subclonal heterogeneity and T cell dysfunction in extramedullary myeloma

  Investigating the spatial architecture and microenvironment of EMD lesions in Multiple Myeloma patients using spatial whole transcriptome sequencing (10X Visium), tomography for spatially resolved transcriptomics (TOMO-seq), and single-cell RNA sequencing (scRNAseq)

  Study EGAS50000000227

• Genetic Markers of Lipids in Indians: A Validation Study of Most Relevant Findings of Genome-Wide Association Studies

  We aimed to validate the GWAS loci (identified in European populations) related to serum lipid levels (total cholesterol, triglycerides, low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C) and very low-density lipoprotein cholesterol (VLDL-C)) in the Indian population originally recruited to examine the 20-year trend of cardiometabolic risk factors in rural and urban areas around National Capital region in India. Isolated DNA was processed for genotyping of 12 established GWAS variants using multiplex Sequenom Mass ARRAY technology. We examined the association of these genetic variants with different lipid levels and found association of eight variants for lipid levels. We also derived weighted genetic risk scores (wGRAS) using the validated variants. The wGRS for triglycerides and VLDL-C was derived based on four associated variants (rs174546 at FADS1, rs17482753 at LPL, rs2293889 at TRPS1, rs4148005 at ABCA8, rs4420638 at APOC1) which was associated with 36.31 mg/dL elevated triglycerides and VLDL-C (β=0.95, SE=0.16, pTRPS1 and rs4147536 at ADH1B) was associated with 40.62 mg/dL higher total cholesterol (β=1.01, SE=0.23, pTRPS1, rs4147536 at ADH1B, rs4420638 at APOC1 and rs660240 at CELSR2). The wGRS derived from five associated variants (rs174546 and FADS1, rs17482753 at LPL, rs4148005 at ABCA8, rs4420638 at APOC1 and rs7832643 at PLEC) was associated with 10.64 mg/dL lower HDL-C (β= -0.87, SE =0.14, pThe phenotypic and genotypic data will be made available on the dbGaP portal for access.

  Study phs003469

• NCI Cancer Model Development for the Human Cancer Model Initiative (HCMI)

  The Cancer Model Development Center (CMDC) project is part of the Human Cancer Model Initiative (HCMI) and is managed by the Office of Cancer Genomics within the Center for Cancer Genomics at the National Cancer Institute (NCI). The goal of the HCMI is to generate approximately 1000 novel human "next generation" tumor-derived models as a community resource. The models aim to faithfully recapitulate the cellular complexity and heterogeneity of human tumors. The CMDCs are tasked by the NCI with producing a proportion of the cancer models. Wellcome Sanger Institute (WSI) is a contributing member of the HCMI. Models developed by HCMI are being derived from a number of tumor types and subtypes (see below), including rare adult, pediatric and understudied cancers. The number of models and the clinical sites from which patient samples are acquired is increasing. Normal tissue, originating tumor, and tumor-derived models are sequenced. The next generation cancer models are associated with rich clinical and genomic data through the NCI Genomic Data Commons for all researchers to advance cancer research. The CMDC and HCMI models will serve as excellent tools in research to provide insight into the pathways that influence tumor growth and progression, how tumors respond to therapy, etc. Ultimately, the data generated using these models will support the development of personalized oncology. There is a delay between registered IDs and model availability. The current model count is found in The HCMI Searchable Catalog which is updated when new models are available for distribution to the research community.

  Study phs001486

• Digitalis Investigation Group (DIG-BioLINCC)

  Data Access NOTE: Please refer to the “Authorized Access” section below for information about how access to the data from this accession differs from many other dbGaP accessions. Objectives To determine the effect of increasing age on mortality, hospitalizations, and digoxin side effects in patients with heart failure (HF), and to determine whether the effect of digoxin on clinical outcomes varies as a function of age. Background The incidence and prevalence of HF increase with advancing age, but there are limited data on the clinical course and response to specific interventions in elderly patients with HF. Participants A total of 302 centers in the United States and Canada enrolled 7,788 patients between February 1991 and September 1993. Design The Digitalis Investigation Group (DIG) study was a prospective, randomized clinical trial involving 7,788 patients with HF randomized to digoxin or placebo and followed for an average of 37 months. Interactions between age and the following clinical outcomes were examined: total mortality, all-cause hospitalizations, HF hospitalizations, the composite of HF death or HF hospitalizations, hospitalization for suspected digoxin toxicity and withdrawal from therapy because of side effects. Conclusions Increasing age is associated with progressively worse clinical outcomes in patients with HF. However, the beneficial effects of digoxin in reducing all-cause admissions, HF admissions, and HF death or hospitalization are independent of age. Thus, digoxin remains a useful agent to the adjunctive treatment of HF due to impaired left ventricular systolic function in patients of all ages.

  Study phs003872

• Multiple Myeloma Clinical Targeted Sequencing of Patient Samples

  Purpose: Molecular diagnostics for the risk stratification of patients with multiple myeloma (MM) have languished in the area of cytogenetics and fluorescence in situ hybidization (FISH). However, here we present the case for next generation sequencing of MM patient samples to not only identify high-risk markers, but also mutations and deletions relating to immunomodulatory drugs (IMiDs), and more importantly to guide the sequencing of immunotherapy regimens in response to intrinsic antigen escape as a means of treatment resistance and relapse. Experimental design: CD138+ cell selected samples (n=134) from bone marrow aspirates from patients with multiple myeloma were sequenced using a targeted panel in a clinical diagnostics laboratory. Data were analyzed for high-risk markers, treatment-related resistance mechanisms, and precision medicine targets to guide the future treatment of patients in the clinic. Results: High-risk markers including t(4;14), t(14;16), t(14;20), gain or amplification 1q, deletion of CDKN2C, and deletion or mutation of TP53 were identified in 15% of newly diagnosed myeloma patient samples. At relapse, alterations in the cereblon degradation pathway were found in 24.3% of IMiD treated patients. Deletions of 4p (CD38) were also enriched in patients who received anti-CD38 treatment (P=0.03) which were mostly monoallelic. Deletions and mutations were detected in TNFRSF17 encoding BCMA in patients treated with anti-BCMA regimens, and the information was used to change the treatment of the patients. Conclusions: Targeted sequencing of multiple myeloma patient diagnostic samples can be used for risk stratification, and also to monitor and adjust treatments as resistance mechanisms evolve.

  Study phs003908