15075 results for "cancer studies using rna-seq"

in 38.38 milliseconds.

• Division of Cancer Evolution National Cancer Center Research Institute Data Access Committee

  Data Access Committee for data from Division of Cancer Evolution, National Cancer Center Research Institute

  Dac EGAC50000000737

• Metagenomic Analysis of the Structure and Function of the Human Gut Microbiota in Crohn's Disease

  Inflammatory bowel diseases (IBD), such as Crohn's disease, are chronic, immunologically mediated disorders that have severe medical consequences. The current hypothesis is that these diseases are due to an overly aggressive immune response to a subset of commensal enteric bacteria. Studies to date on IBD have suggested that the disorder may be caused by a combination of bacteria and host susceptibility; however the etiologies of these diseases remain an enigma. In this application, we propose to develop and demonstrate the ability to profile Crohn's disease at an unprecedented molecular level by elucidation of specific biomarkers (bacterial strains, genes, or proteins) that correlate to disease symptoms. To achieve this goal, we will employ a multidisciplinary approach based on metagenomic and metaproteomic molecular tools to elucidate the composition of the commensal microbiota in monozygotic twins that are either healthy or exhibit Crohn's disease (for concordant, both are diseased; for discordant, one is healthy and one is diseased). The central hypotheses of this proposal are (1) that specific members and/or functional activities of the gastrointestinal (GI) microbiota differ in patients with Crohn's disease as compared to healthy individuals, and (2) that it will be possible to elucidate microbial signatures which correlate with the occurrence and progression of this disease by integration of data obtained from 16S rRNA-based molecular fingerprinting, metagenomics, and metaproteomics approaches. To address these hypotheses, three specific aims are proposed: 1) Obtain data on community gene content (metagenome) in a subset of healthy twins and twins with Crohn's Disease to assess potential differences in the metabolic capabilities of the gut microbiota associated with CD, 2) Obtain data on community protein content (metaproteome) in a subset of healthy twins and twins with Crohn's Disease to assess the state of expressed proteins associated with CD, 3) Apply various statistical clustering and classification methods to correlate/associate microbial community composition, gene and protein content with patient metadata, including metabolite profiles and clinical phenotype. The ultimate goal of these efforts is to identify novel biomarkers for non-invasive diagnostics of CD and to eventually identify drug targets (i.e. bacterial strains) for cure or suppression of disease symptoms. PUBLIC HEALTH RELEVANCE: This study aims to unravel the contribution of the bacteria that normally inhabit the human gastrointestinal tract to Crohn's disease by using a multidisciplinary approach to study changes in the structure and function of gut microbial communities in three sets of patient cohorts who have Crohn's disease. These results will be compared with those obtained from the study of healthy individuals and have the potential to identify new biomarkers of disease severity, location, and progression.

  Study phs000257

• WGS-Lung Cancer sample 30 pair

  This study includes 30 paired samples of Korean Lung Cancer paitients. 30 Lung Cancer samples are paired with each normal(Saliva derived for control) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

  Study EGAS00001001474

• Genomic analysis of Japanese gastric cancer (345 gastric cancers of NCC)

  As a contribution to the International Cancer Genome Consortium, whole exome sequencing of 345 Japanese gastric cancer (345 gastric cancers of NCC) with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer.

  Study EGAS00001002884

• MCO colorectal cancer genomics at UNSW

  This dataset contains DNA sequencing data from 95 colorectal cancer and matched-normal samples. The dataset contains targeted deep sequencing of selected regulatory elements in 95 cancer and matched-normal samples, and data for one sample that was additionally whole-genome sequenced (cancer and matched-normal).

  Study EGAS00001003450

• RNA Editing Exome

  Exome sequencing data for tumor and matched normal samples of the EGAS00001000495 project.

  Dataset EGAD00001000626

• RNA Editing AZIN1 amplicon sequencing

  AZIN1 amplicon sequencing data of the EGAS00001000495 project.

  Dataset EGAD00001000708

• Saliba Lab Data Access Committee

  DAC for data generated by Saliba Lab at Helmholtz institute for RNA-based Infection Research, Würzburg, Germany

  Dac EGAC50000000152

• UTUC RNAseq data

  RNA sequencing of upper urinary tract urothelial carcinoma

  Dataset EGAD00001007667

• Mutational anysis of breast cancer stem cells

  Exome sequences of breast cancer have been investigated for many patients. Recently it has been shown that there are intra-heterogeneity in tumor tissues. When the tumor cells were sequenced in bulk condition, only the major populations��� (clones���) mutations will be detected. Based on cancer stem theory, each populations��� cells are derived from each cancer stem cells, which their numbers are not so different among different clones. Here, we separated cancer cells into cancer stem cells and non-cancer stem cells exploiting cancer stem cell specific surface markers. By comping two groups��� mutation, we identified mutations, which were only detected in stem cell population. These mutations could be the mutations in cells of small size populations, and maybe the important mutations to understand the heterogeneity of tumor tissues, progression, and/or prediction for the outcome to therapies.

  Study JGAS000304

• 3q-capture DNA sequencing of primary AMLs with 3q26 rearrangements

  This dataset contains DNA sequencing of the chromosome 3q region in 28 primary AML cases with 3q26 rearrangements (3q26-rearranged AML). Genomic DNA was fragmented using the Covaris shearing device (Covaris), and sample libraries were assembled following the TruSeq DNA Sample Preparation Guide (Illumina). After ligation of adapters and an amplification step, target sequences of chromosomal regions 3q21.1-q26.2 were captured using custom in-solution oligonucleotide baits (Nimblegen SeqCap EZ Choice XL). The design of target sequences was based on the human genome assembly hg19: chr3q21.1:126036241-130672290 - chr3q26.2:157712147-175694147. Amplified captured sample libraries were paired-end sequenced (2x100 bp) on the HiSeq 2500 platform (Illumina) and aligned against the hg19 reference genome using the Burrows-Wheeler Aligner (BWA).

  Dataset EGAD00001006820

• Shotgun metagenome sequencing of saliva samples using PromethION

  Using PromethION, we conduct shotgun metagenome sequencing of human saliva, where both bacteria and bacteriophages are densely living, to study both microbiome and virome. We aim to explore, for example, relative abundance of bacteira and bacteriophages, distribution of contig lengh. types of phages and prophages, frequency of novel phages revealed by the long-reads and their taxonomic classification, and characteristics of genes encoded by the phages.

  Study JGAS000186

• Liver CD14+CD8+ T cells scRNAseq dataset

  Sorted single CD8+T cells expressing CD14 from human liver for SMARTSeq2. Livers processed: Kucykowicz et al STAR Prot 2022:pubmed.ncbi.nlm.nih.gov/35516846/ Published: Pallett et al Nature 2022 Tissue CD14+CD8+T-cells are reprogrammed by myeloid cells and modulated by LPS A modified SMART-seq2 protocol was performed on the single flow cytometry sorted-cells as previously described58. After cDNA generation, libraries were prepared (384 cells per library) using the Illumina Nextera XT kit (Illumina). Each library was sequenced to achieve a minimum depth of 1-2 million raw reads per cell using an Illumina HiSeq 4000 using v. 4 SBS chemistry to generate 75-bp paired-end reads.

  Dataset EGAD00001009831

• UCSF WCDT WGS/WGBS mCRPC

  This dataset contains 29 paired FASTQ files from whole-genome bisulfite sequencing (WGBS) assay performed on mCRPC tumors. Sequencing was performed using 150nt paired reads generated by a Novaseq 6000 instrument. It also contains whole-genome sequencing bam files aligned to hg38 using BWA from 36 patients, with tumor and matched tumor-adjacent normal samples. Sequencing was generated using HiSeq X Ten.

  Dataset EGAD00001009505

• H3K27ac HiChIP Dataset for 19 T-ALL patients and one normal control sample

  19 H3K27ac HICHIP from T-ALL patient samples and one healthy normal control sample. Reads were aligned to HG38 reference.

  Dataset EGAD50000000023

• scRNA-seq analysis of HGSC tumors, including immune TME, before and after NACT

  Gene expression profiles of single cells from 26 tumor and ascites samples samples from 17 patients

  Dataset EGAD50000000862

• NiCOL Study Target-seq dataset

  10 samples sequenced in Target-sequencing of a panel of 571 genes (Illumina NovaSeq 6000) - Raw FASTQ data - Annotated VCF

  Dataset EGAD00001010911

• Paired-end Whole Exome-seq analysis of the 3D spatially mapped GBM samples.

  Dataset contains 50 paired-end Whole Exome sequencing samples from 3 patients. 3 normal blood samples are also included.

  Dataset EGAD00001010289

• Bulk exome sequencing of primary GBM - SF 10360

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10360

  Dataset EGAD00001002274

• ChIPseq of neuroblastoma

  This dataset contains 4 samples (2x input and 2x H3K27ac ChIPseq) in the IC-pPDXC-63 cell line.

  Dataset EGAD00001006557

• ChIP sequencing from a collection of PFA tumors

  ChIP data from PFA (n = 10). Raw data provided as FASTQ. Data generated on Illumina NovaSeq 6000 PE50.

  Dataset EGAD00001009045

• H3K27ac ChIPseq of cohesin-mutated and wildtype adult AMLs

  ChIP-seq targeting the H3K27ac histone modification in cohesin-mutated (STAG2 or RAD21 mutation) and cohesin wildtype (CTRL-AMLs) AMLs.

  Dataset EGAD00001011204

• EGAD00010000652

  Genotyped samples using Illumina HumanOmni2.5

  Dataset EGAD00010000652

• EGAD00010000096

  DBA case samples using 250K Nsp

  Dataset EGAD00010000096

• EGAD00010000381

  MRCE sample using 300K

  Dataset EGAD00010000381

• EGAD00010000383

  MRCA sample using 100K

  Dataset EGAD00010000383

• EGAD00010000385

  MRCA sample using 300K

  Dataset EGAD00010000385

• Methylation_JMML

  Methylation JMML samples using 450K Array

  Dataset EGAD00010001450

• Methylation_Controls

  Methylation Control samples using 450K Array

  Dataset EGAD00010001449

• HUMANOMNI1QUAD_Genotyping

  samples using Illumina HUMANOMNI1QUAD

  Dataset EGAD00010000919

• HUMANOMNIEXPRESS_Genotyping

  samples using Illumina HUMANOMNIEXPRESS

  Dataset EGAD00010000920

• Gut microbiome dynamics unravelled with metagenomics sequencing

  It has been already several years since we discovered that microbial therapeutics like Faecal Microbiota Transplantation can be used to treat Clostridium difficile infection (CDI) and Inflammatory bowel disease (IBD) with great success. The concept has challenged us to test the limits of our knowledge with the perspective to improve health in the most diverse conditions like Parkinson disease, depression, autism and obesity, just to mention a few. Note: the figure belongs to the original paper and is owned by the authors. Allyson L.Bird and colleagues from Genentech Inc. (San Francisco) recently published an interesting study building up on the key concept that “As microbial therapeutics are increasingly being tested in diverse patient populations, it is essential to understand the host and environmental factors influencing the microbiome.” The authors of this work analysed 1359 gut microbiome samples using shotgun metagenomics sequencing.  The results of the comparison done between microbiota composition across the different groups showed that biological sex is the strongest driver of diversity, while aging (age range studied: 20–69) appears to be the second factor. As smartly outlined in the authors’ own graphical abstract (figure to the left), Bacteroidota species consistently increased with donors' age while Actinobacteriota species, including Bifidobacterium, decreased. This study also integrated data from oncological patients to draw cancer-related evidences. After correcting the biases for technical and geographic differences, they found that cancer patients show significantly altered gut bacterial communities compared with their healthy counterparts. Eg. E.coli was found to be increased in cancer patients together with Bacteroidota/Firmicutes ratios. By comparing sequential samples taken from the same donors (413) within short-distance time points, the authors found that in the short term, intra-individual differences were less than the inter-individual ones, indicating a certain community stability being the norm. One of the pivotal points from this interesting study is that the data proceeds from extremely well-defined and selected donors. Specifically, the data for 949 selected healthy donors came from the Milieu Intérieur (MI) Consortium and extensive metadata, including demographic variables, serological measures, dietary information, and systemic immune profiles, are available. This precise stratification allowed for the robust detection of smaller changes, compared to former works. All sequencing data has been deposited in the EGA archive under the accession number EGAS00001004437. Enjoy this amazing open access paper published in the Experimental Journal of Medicine on January 2021.

  Blog gut-microbiome-dynamics-unravelled

• DEMENTIA-SEQ: WGS in Lewy Body Dementia and Frontotemporal Dementia

  Lewy body dementia, amyotrophic lateral sclerosis/frontotemporal dementia, and multiple system atrophy are age-related, neurodegenerative syndromes that are poorly understood. Delineating the genetic risk that is driving the pathophysiology of these neurological diseases is fundamental for understanding disease mechanisms and for developing disease-modifying treatments. In version 1 of the study/dbGaP deposition, we performed a whole-genome sequencing study consisting of 7,403 total samples, including 2,633 genomes from patients with Lewy body dementia, 2,641 frontotemporal dementia patients, and 1,980 neurologically healthy controls. Of these, 6,907 were uploaded to dbGaP as the basis of the DementiaSeq, phs001963 dataset. The data relating to these samples are available on dbGaP. In version 2 of this study/dbGaP deposition, we made much of these data available on Anvil. More specifically, data for 6,254 of these samples were also uploaded to the ALS Compute platform on AnVIL. The data for the remaining 653 samples are only available on dbGaP. The dbGaP/AnVIL Table lists the availability of dbGaP and AnVIL for each individual sample: phd008475.In version 3 of the study/dbGaP deposition, we added whole-genome sequence data generated using DNA samples obtained from 683 patients diagnosed with multiple system atrophy.

  Study phs001963

• WTCCC case-control study for Hypertension - Combined Controls

  WTCCC genome-wide case-control association study for Hypertension (HT) using six disease collections together with the 1958 British Birth Cohort and the UK National Blood Service collections as controls.

  Study EGAS00000000010

• SCLC

  The aim of this study is to use sequence data generated from 500 bp paired end reads using the Illumina platform to characterise the breakpoints of chromosomal translocations, amplifications and deletions at high resolution (to the bp).

  Study EGAS00001000009

• Saliva Microbiota of Finnish children from the PANIC study

  Saliva microbiota of 407 participants of PANIC study, is profiled with 16S rRNA gene sequencing (regions V3-V4). Amplification was performed using the TruSeq-switched tail amplicons. The sequencing was performed using the 2 × 301 base-pair on the Illumina MiSeq PE300 platform. Data includes information on sex, age, and caries status of participants. File format is fastq.gz.

  Dataset EGAD50000000989

• Picuris Pueblo oral history and genomics reveal continuity in US Southwest

  Following the decision of Picuris Pueblo to study their population history using DNA, this project generated 16 ancient and 13 present-day genomes from the Pueblo, spanning 1,000 years of history.

  Study EGAS50000000855

• Comprehensive analysis of interaction between human gene expression and environmental metagenomes.

  WGS, 10x scRNA, 10X TCR, 10X BCR and CyTOF analyses were performed using blood samples collected from healthy volunteers aged 18 years or older who worked or lived in the Kashiwa-no-ha area.

  Study JGAS000321

• 419 Japanese healthy control

  Genotypes of 419 Japanese healthy individuals genotyped by using of SNP arrays (Genome-Wide Human SNP Array 6.0 and Axiom Genome-Wide ASI 1 Array). CEL files and CHP files are included in this data set.

  Study JGAS000120

• Whole exome sequencing variant data for Mendelian disorders cohort

  This dataset contains whole exome sequencing variant data (VCF files) from individuals with suspected Mendelian disorders, including sickle cell disease, muscular dystrophy, haemophilia, and Fanconi anemia. Variant calling was performed using the Illumina DRAGEN pipeline, with downstream variant prioritisation conducted using the Zi-Mendelian bioinformatics pipeline. The dataset supports research into rare genetic diseases and genomic variation in African populations.

  Dataset EGAD50000002453

• Characterization of Arabian Peninsula whole exomes

  We conducted whole exome sequencing (using the SureSelect Human All Exon V5 + UTRs target enrichment kit) of 90 individuals from AP (23 from Saudi Arabia, 24 from Yemen, 24 from Oman and 19 from UAE).

  Study EGAS00001006487

• Enhanced reduced representation bisulfite sequencing (eRRBS) on 45 multiple myeloma samples and 3 normal plasma cell

  Enhanced reduced representation bisulfite sequencing (eRRBS) on 45 multiple myeloma samples and 3 normal plasma cell. Libraries were sequenced on a HiSeqTM4000 Illumina machine using 75bp paired-end reads

  Study EGAS00001004348

• SNP array study in Autism Spectrum Disorder patients

  The aim of this study was to investigate two ancestral inversions (inv17q21.31 and inv8p23.1) in Autism Spectrum Disorder (ASD) patients. We have performed SNP array in order to genotype these inversions using the package scoreInvHap.

  Study EGAS00001005606

• CGH Array

  DNA samples were extracted from peripheral blood lymphocytes using commercially available kit (Puregene Core Kit A, Qiagen) according to manufacturer's protocol. Agilent SurePrint G3 Human CGH Microarray 180K platform was used for screening of copy number aberrations (CNAs) using array-CGH protocol recommended by manufacturer (Agilent Technologies), data mining and interpretation of array-CGH results was performed in same manner as in our previously published results.

  Dataset EGAD00001007743

• Exome sequencing data

  Exome sequencing fastq files from 6 mutation carriers and 5 non-carriers from 2 families. One µg DNA was used for library preparation using the TruSeq DNA LT Sample Prep Kit v2 according to the manufacturer’s instructions (Illumina). Hybridization was performed using Nimblegen SeqCap EZ Exome v3 (Roche) and Paired-end Sequencing (2x100 bp) on the Illumina HiSeq 2000 with TruSeq v3 chemistry (Illumina).

  Dataset EGAD00001003745

• Whole genome sequencing of metastatic cutaneous squamous cell carcinoma

  This dataset includes somatic small variant calling files derived from fifteen metastatic samples from cutaneous squamous cell carcinoma matched to normal blood samples. These samples were whole-genome sequenced by HiSeq X Ten and the resulting reads were mapped against the human genome (hg37) using BWA-MEM 0.7.10-r789. Somatic variant calling was then performed using strelka 1 (version 2.0.17).

  Dataset EGAD00001004530

• Metagenome for FINRISK2002

  The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012). The files are in FASTQ format.

  Dataset EGAD00001007035

• Comparison of WGBS, EPIC array, EM-seq, and Nanopore sequencing in assessing DNA methylation marks

  Bisulfite sequencing has long been the default method for analyzing methylation marks due to its single base resolution. However, the associated DNA degradation poses a concern for fragmented samples. Although several methods have been proposed to circumvent this issue, there has yet to be a clear consensus on which method is best suited for detecting methylation. We present an overview of the two mostly used and two alternative approaches: whole-genome bisulfite sequencing (WGBS), Illumina methylation microarray (EPIC), Enzymatic Methyl-sequencing (EM-seq) and third-generation sequencing by Oxford Nanopore Technologies (ONT). We evaluated DNA methylation levels in three human genomes derived from tissue, cell line, and whole blood.

  Study EGAS00001008014

• ABIS_1_MeDIP-seq

  We investigated changes in whole genome DNA-methylation in a group of 48 healthy five-year-old children differentiated by their hair cortisol levels. By combining this novel biomarker for chronic stress with methylated DNA immunoprecipitation sequencing (MeDIP-seq), we found that high cortisol were associated with a genome-wide decrease in DNA-methylation targeted to specific zinc finger transcription factor binding sites, repetitive elements and genes important for neurodevelopment and calcium transport. Large scale hypomethylation of repetitive regions, as well as a deficient calcium transport, have been reported in many stress related diseases, as well as in many cancers and biological aging. Thus our findings may aid in our understanding of how susceptibility to these diseases develops.

  Study EGAS00001001099

• The landscape of cancer genes and mutational processes in breast cancer

  The landscape of cancer genes and mutational processes in breast cancer

  Dataset EGAD00001000133

• Structure and Diversity of Urinary Cell-Free DNA Informative of Host-Pathogen Interactions in Human Urinary Tract Infection

  The risk of acquiring urinary tract infection (UTI) is very high for patients who have received kidney transplants; nearly half will develop bacteriuria and an eighth viruria via BK polyomavirus in the first three years following transplantation. Current methodology for diagnosing viral and bacterial infections, while well practiced, is often limited in scope. The advent of next generation sequencing of cell-free DNA has shown promise in its ability to capture multiple perspectives of human health from discovering the origin of cell-free DNA in plasma; such a diagnostic has not been readily applied to urinary cell-free DNA. In this study, we selected 141 urine samples from a cohort of kidney transplant patients, which were collected and stored at Weill Cornell Medical College - New York Presbyterian Hospital. Of these samples, 43 samples were determined to be culture positive (> 10,000 CFU) for one or more bacterial species, including E. coli, Enterococcus, Klebsiella, Haemophilus, and Raoultella. A separate 23 samples were confirmed for BK virus nephropathy, with presence of BK polyomavirus confirmed via qPCR. We also included 29 samples from 14 patients who did not develop UTIs in the first three months following transplantation, and 11 samples that were negative for BK virus nephropathy. For a full description of samples, please see the Supplementary Data 1 in https://pubmed.ncbi.nlm.nih.gov/29925834/. From these urine samples, we aimed to capture and sequence urinary cell-free DNA using a single-stranded library preparation. In addition, we performed whole-genome bisulfite sequencing to 170 plasma samples collected from 27 hematopoietic cell transplant patients who developed graft-versus host disease and BK polyomavirus infection. We also performed Sample-Intrinsic microbial DNA Found by Tagging and sequencing (SIFT-seq) on 196 cell-free DNA (cfDNA) samples (154 plasma and 42 urine) collected from five groups of subjects. For a full description of samples, please see publications in PMID: 35864089 and PMID: 35058359.

  Study phs001564

• RNA Editing Transcriptome

  Transcriptome sequencing data of tumor and 10 matched normal samples of the EGAS00001000495 project

  Dataset EGAD00001000627

• Rapid detection of expanded short tandem repeats in personal genomics using hybrid sequencing.

  Long expansions of short tandem repeats (STRs); i.e., DNA repeats of 2-6 nucleotides, are associated with some genetic diseases. Cost-efficient high throughput sequencing can quickly produce billions of short reads that would be useful for uncovering disease-associated STRs. However, enumerating STRs in short reads remains largely unexplored because of the difficulty in elucidating STRs much longer than 100 bp, the typical length of short reads. We propose ab initio procedures for sensing and locating long STRs promptly by utilizing the frequency distribution of all STRs and paired-end read information. We validated the reproducibility of this method using biological replicates and used it to locate an STR associated with a brain disease (SCA31). Subsequently, we sequenced this STR site in eleven SCA31 samples using SMRT? sequencing (Pacific Biosciences), determined 2.3-3.1 kb sequences at nucleotide resolution, and revealed that (TGGAA)- and (TAAAATAGAA)-repeat expansions determined the instability of the repeat expansions associated with SCA31. Our method could also identify common STRs, (AAAG)- and (AAAAG)-repeat expansions, which are remarkably expanded at four positions in an SCA31 sample. This is the first proposed method for rapidly finding disease-associated long STRs in personal genomes using hybrid sequencing of short and long reads.

  Study JGAS000002

• Targeted_analysis_of_chondrosarcoma_cancer_genes

  Targeted analysis of chondrosarcoma cancer genes

  Study EGAS00001001765

• ICGC PanCancer Analysis of Whole Genomes

  The Pancancer Analysis of Whole Genomes (PCAWG) study is an international collaboration to identify common patterns of mutation in more than 2,800 cancer whole genomes from the International Cancer Genome Consortium. Building upon previous work which examined cancer coding regions (Cancer Genome Atlas Research Network, The Cancer Genome Atlas Pan-Cancer analysis project, Nat. Genet. 2013 45:1113), this project is exploring the nature and consequences of somatic and germline variations in both coding and non-coding regions, with specific emphasis on cis-regulatory sites, non-coding RNAs, and large-scale structural alterations.

  Study EGAS00001001692

• Rare germline sequence variants, copy number variations, expression alterations, methylation variations and disease susceptibility in familial melanoma

  Although a number of high-risk melanoma genes have been identified, they account for melanoma risk in less than 40% of melanoma-prone families. The major goals of our research are to identify novel high-penetrance genes for familial melanoma in melanoma-prone families without known mutations and to identify modifier factors, including genetic and epigenetic, in melanoma-prone families with and without known major mutations. We are using whole exome sequencing to identify additional high-risk susceptibility genes and using targeted sequencing to follow up on the top genes in additional family members and in population-based melanoma cases and controls. We are also using RNASeq to investigate genome-wide allele-specific expression and eQTLs in these families to identify genes with expression alteration, which will provide additional information for gene discovery. In addition, we also conducted genome-wide copy number variation (CNV), methylation, and miRNA expression profiling analyses in our melanoma families with the goal of identifying genetic and epigenetic factors as disease modifiers.

  Study phs001177

• WES in HCCOs with varying Doxorubicin resistance

  We aimed to identify somatic mutations that could explain the resistance to Doxorubicin. Therefor, we purified Exomes from liver biopsies and HCC organoids using Agilent SureSelectXT (clinical research exome, HS2 V8, or Human all Exon V6 Cosmic) and performed WES. Matched non-tumoral liver biopsies served as the control for germline mutations. 12 of these samples were previously reported. Sequence reads were aligned to the reference human genome GRCh38 using Burrows-Wheeler Aligner (BWA, v0.7.17). Duplicate removal, base quality adjustment, mutation calling (Mutect2, intervals: SureSelectXT_HS_V8_S33266340, germline-recourse: gnomad.exomes.r2.1.1.sites.liftover_grch38, Panel-of-Normal: 1000g_pon.hg38), filtering of Mutect calls, and functional annotation (Funcotator, funcotator_dataSources.v1.7.20200521g) were performed using the Genome Analysis Toolkit (GATK, v4.4) according to the Broad Institute best practices in Somatic short variant discovery workflows. Mutations with a functional annotation of Deletion, Insertion, Non-stop, Splice-Site, Start-Codon and Missense mutations were kept. A list of 43 commonly mutated genes in HCC was analyzed in the HCC organoids [TCGA, Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma. Cell, 2017. 169(7): p. 1327-1341.e23].

  Study EGAS50000000043

• 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

• Using human iPSC-derived oligodendrocytes to explore t(1;11) translocation DAC

  Dac EGAC00001001694

• EGAD00010000425

  Han Chinese samples using Immunochip

  Dataset EGAD00010000425

• EGAD00010000419

  Han Chinese samples using Affymetrix (cases)

  Dataset EGAD00010000419

• EGAD00010000421

  Han Chinese samples using Affymetrix (controls)

  Dataset EGAD00010000421

• EGAD00010000452

  Chondrosarcoma case sample genotype using Affymetrix SNP6.0

  Dataset EGAD00010000452

• EGAD00010000512

  Case samples using HumanOmni1-Quad

  Dataset EGAD00010000512

• Exome_array_250K

  Argentine samples using 250K

  Dataset EGAD00010001075

• Diffuse_gastric_cancer

  Gencode control samples using SNP6.0

  Dataset EGAD00010000889

• RNA isoform repertoire of neuropsychiatric risk genes in human brain

  Neuropsychiatric disorders are highly complex conditions and the risk of developing a disorder has been tied to hundreds of genomic variants that alter the expression and/or products (isoforms) made by risk genes. However, how these genes contribute to disease risk and onset through altered expression and RNA splicing is not well understood. Here we show our current understanding of gene isoforms is far from complete and reveal the precise splicing profiles of neuropsychiatric disorder risk genes. Combining our new bioinformatic pipeline IsoLamp with nanopore long-read amplicon sequencing, we deeply profiled the RNA isoform repertoire of 31 high-confidence neuropsychiatric disorder risk genes in human brain. We show most risk genes are more complex than previously reported, identifying 443 novel isoforms and 28 novel exons, including isoforms which alter protein domains, and genes such as ATG13 and GATAD2A where most expression was from previously undiscovered isoforms. The greatest isoform diversity was present in the schizophrenia risk gene ITIH4. Mass spectrometry of brain protein isolates confirmed translation of a novel exon skipping event in ITIH4, suggesting a new regulatory mechanism for this gene in brain. Our results emphasize the widespread presence of previously undetected RNA and protein isoforms in brain and provide an effective approach to address this knowledge gap. Uncovering the isoform repertoire of neuropsychiatric risk genes will underpin future analyses of the functional impact these isoforms have on neuropsychiatric disorders, enabling the translation of genomic findings into a pathophysiological understanding of disease.

  Study EGAS00001007744

• Perceptions, Prevalence, and Patterns of Cannabis Use among Cancer Patients in NCI-Designated Cancer Centers

  This study aimed to better understand the evolving landscape of cannabis use among patients undergoing cancer treatment across diverse geographic regions. It sought to characterize patterns of use, patient perceptions, and contextual influences such as legal status and provider engagement that affect cannabis use. Given the shifting legal environment, this study addresses a critical gap in the literature by providing data on how cancer patients integrate cannabis into their care. The available delivery methods of cannabis have also undergone dramatic changes and now include edibles, oils, tinctures, topicals, and inhaled forms. State-based policy changes are rapidly changing. Yet research on cannabis use by cancer patients across a variety of geographic settings remains limited. The extent of cannabis use, the perceived and real benefits and risks of use, potential interactions with cancer treatment and other medications, and impact on comorbid conditions are uncertain. Clinicians should be aware of the extent of use in order to assess potential drug-drug interactions, side effects, and contraindications; hence, an understanding of how cancer patients and clinicians engage in discussions about cannabis use is essential. Twelve NCI-designated cancer centers were awarded supplemental funding to conduct surveys assessing cannabis use among recently diagnosed cancer patients. Selected sites were in 8 states with varied legal status for medical and recreational cannabis use at the time of the survey. The 12 cancer centers independently received approval from their institutional review boards (IRB) and collected data from September 2021 to August 2023. Eligible participants were cancer patients or survivors who resided in their respective cancer center's catchment area. Cancer centers were responsible for sampling patients within their catchment area with the goal of 1,000 completed surveys. Ten out of 12 cancer centers drew probability samples of patients from patient lists defining their catchment area with some stratifying the sample in various ways including by cancer type, by sex, by race/ethnicity or by a combination of demographic variables.

  Study phs004046

• Epigenomic profile of diverse cancer

  Epigenomic profile of diverse cancer.

  Study EGAS00001004352

• Cancer Genetic Markers of Susceptibility (CGEMS) Prostate Cancer Genome-Wide Association Study (GWAS) - Primary Scan (Stage 1) - PLCO Screening Trial

  The Cancer Genetic Markers of Susceptibility (CGEMS) prostate cancer genome-wide association study (GWAS) included genotyping approximately 550,000 SNPs (Phase 1A with HumanHap300 and Phase 1B HumanHap240, both from Illumina, San Diego, CA) in 1,172 prostate cancer patients and 1,157 controls of European ancestry from the Prostate, Lung, Colon and Ovarian (PLCO, http://www.cancer.gov/prevention/plco/) Cancer Screening Trial. The original analysis published in Nature Genetics [PMID: 17401363] included 2,282 subjects. After improvement and revisions of the original analysis, 2,252 subjects were submitted to dbGaP.

  Study phs000207

• Birth Defects: Moebius Syndrome and Related Congenital Facial Weakness Disorders

  It is estimated that about 1 in every 33 infants in the United States is born with a birth defect. Among these, the subset of birth defect syndromes associated with facial weakness and lack of facial expression can have profound implications for social interactions and psychosocial development. Moebius syndrome is defined by congenital and non-progressive facial weakness and limited eye abduction, and most cases are believed to result from dysfunction of cranial nuclei/nerves VI and VII. Although rare, this syndrome causes significant impairment because of facial weakness and associated intellectual disabilities, autism, hearing loss, difficulty swallowing and breathing, peripheral neuropathy, muscle hypotonia, heart defects, chest wall abnormalities, and limb malformations. The phenotypic spectrum and the associated genetic and environmental factors underlying Moebius syndrome are poorly understood. The goal of this research is to identify causative gene mutations for Moebius syndrome and related conditions, such as Moebius-Poland or -Robin sequence, hereditary congenital facial paresis (HCFP), and oculoauriculovertebral dysplasia (Goldenhar syndrome). This proposal builds on an ongoing collaboration among researchers at Mount Sinai Medical Center, Boston Children's Hospital, NHGRI intramural program, and the Moebius Syndrome Foundation, but aims to greatly extend that work by collaboration with investigators in the NIH Clinical Center (CC). Our groups have already defined a new autosomal dominant syndrome with Moebius syndrome, Kallmann syndrome, cyclic vomiting resulting from a TUBB3 E410K substitution. We have also identified a new autosomal recessive Moebius-related syndrome with bilateral facial palsy, hearing loss, and strabismus resulting from a HOXB1 R207C substitution. Through collaborative efforts of these extramural teams with intramural investigators, whole exome sequencing (WES) has been conducted for four families with Moebius-like features, and data analyses are ongoing. The overall goal of this new grant application will be to conduct extensive phenotype analysis on approximately 24 families per year with Moebius and other undefined syndromes with facial weakness. Studies to be conducted at the CC include neurology, psychiatry, neurocognitive, rehabilitation medicine (muscle strength, speech/language pathology), ophthalmology, audiology, and genetics evaluations; autism screening; electromyography, nerve conduction, and blink reflex studies; videoscopy of quantitative eye movement recordings; 3D-CT craniofacial imaging; MRI of the brain, orbit, internal auditory canals, posterior fossa including brain diffusion tensor imaging for tractography; and genetic counseling. Jointly with the extramural teams, WES analysis and variant confirmation will be performed. A more comprehensive definition of the phenotypic and genotypic spectrum of these birth defects will have a significant impact on our understanding of the molecular pathways underlying dysmorphologies, cranial nerve development, and more common childhood disorders such as autism. Thus, this project will lead to strategies for prevention and treatment of birth defects.

  Study phs001383

• Action to Control Cardiovascular Risk in Diabetes (ACCORD) Clinical Trial

  The Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial was a randomized, multicenter, double 2 x 2 factorial design study involving 10,251 middle-aged and older participants with type-2 diabetes who are at high risk for CVD events because of existing CVD or additional risk factors. The purpose of ACCORD was to determine if intensive glycemic control, intensive lipid management and intensive blood pressure control could prevent major cardiovascular events (myocardial infarction, stroke or cardiovascular death) in adults with type 2 diabetes mellitus. Secondary hypotheses included treatment differences in other cardiovascular outcomes, total mortality, microvascular outcomes, health-related quality of life and cost-effectiveness. The ACCORD trial failed to show a beneficial effect of intensive blood pressure or lipid therapy on the primary outcome, and intensive glycemia management actually increased mortality. The hypothesis underlying this ancillary study is that the failure of ACCORD to achieve its goal of reducing cardiovascular risk in diabetic patients through intensive management of hyperglycemia, dyslipidemia, and hypertension may be the result of variation in drug response due to genetic variation between individual participants. Benefits of intensive therapy may accrue to subsets of subjects with specific genetic variants predisposing to efficacious responses to particular therapeutic regimens, and harms may accrue to those with other variants predisposing to poor efficacy or adverse events. Identifying these variants could lead to a precision medicine approach to treating diabetes where each patient's genetic profile could identify the most efficacious treatment regimen with the lowest likelihood of adverse events. To test this hypothesis, a genome-wide genetic analysis was undertaken, incorporating both common variants distributed across the genome and rare variants targeted to exonic regions. Associations of genetic variants with short term responses to individual medicines as well as long term outcomes were investigated. The dataset is composed of genetic data from the ~6100 participants who agreed to participate in the ACCORD optional genetic studies and who allowed broad investigator access to their samples and the data derived from those samples, and from whom a DNA sample of sufficient quality was obtained. While a total of 8514 participants consented to the optional genetics studies, not all consented to broad investigator access, and those who did not are not included in this dataset, although they were also genotyped. Access to these additional genotypes can only be obtained by direct collaboration with the investigators of this study. Phenotype data used in the association analyses are derived from the ACCORD public release clinical data set, which has been made available through BioLINCC.

  Study phs001411

• Reproducibility of 10x Genomics single cell RNA sequencing method in the immune cell environment

  Study EGAS00001005905

• Human small intestinal macrophages whole transcriptome

  RNA sequencing data of human small intestinal macrophage subtypes

  Dataset EGAD00001002744

• Reference_DNA_standards_for_GCLP_pipeline

  The use of reference DNA standards generated from cancer cell lines sequenced in the Cancer Genome Project to establish the sensitivity, specificity, accuracy and reproducibility of the WTSI GCLP sequencing pipeline

  Study EGAS00001001173

• cfDNA methylation profiling in Metastatic Cancer and Cancer of Unknown Primary

  This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating cell-free DNA (cfDNA) for 143 patients with metastatic cancer of known type, 41 patients with Cancer of Unknown Primary (CUP) and 27 non-cancer controls.

  Dataset EGAD00001011178

• High volume culture initiating in vitro evolution in neuroblastoma cell lines

  Despite the advent of advanced molecular prognostic tools, it is still difficult to predict the course of disease for cancer patients at the individual level. This lack of predictability is also reflected in many experimental cancer model systems, begging the question of whether certain biological aspects of cancer (eg. growth, evolution etc.) can ever be anticipated or if there remains an inherent unpredictability to cancer, similar to other complex biological systems. We demonstrate by a combination of agent-based mathematical modelling, analysis of patient-derived xenograft systems from multiple cancer types, and in-vitro culture that certain conditions may invoke chaotic fluctuations in the clonal landscape of cancer growth. Our findings indicate that under those conditions, the cancer genome may behave as a complex dynamic system, making its long-term evolution inherently unpredictable.

  Study EGAS00001007962

• Primary human hepatocyte ATAC-seq

  Profiling the chromatin accessibility landscape of cultured primary human hepatocytes (PHH) from three female and three male adult, non-diabetic donors.

  Dataset EGAD50000001751

• β-catenin ChIP sequencing in HCC models.

  This dataset contains ChIP sequencing data for β-catenin, H3K27ac and H3K27me3 from three HCC cell lines and five tumour organoids under normal conditions and oleic acid treatment.

  Dataset EGAD50000001816

• scATAC-seq dataset of A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories

  Study describing the differentiation trajectory...

  Dataset EGAD00001015546

• Bulk exome sequencing of primary GBM - SF 10282

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10282

  Dataset EGAD00001002275

• Bulk exome sequencing of primary GBM - SF 10345

  We performed bulk exome-seq on a primary GBM and a blood sample from SF10345

  Dataset EGAD00001002273

• ChIP-Seq of human stimulated and cultured CD4+ Treg cells

  This dataset includes whole genome sequence data for ChIPmentation assays (18 H3K4me3, 20 H3K27ac and 3 input samples) of human stimulated and cultured CD4+ Treg cells.

  Dataset EGAD00001005816

• scRNA-seq dataset of A cycling, progenitor-like cell population at the root of atypical teratoid rhabdoid tumor subtype differentiation trajectories

  Study describing the differentiation trajectory...

  Dataset EGAD00001015545

• Defining T cell States Associated with Response to Checkpoint Immunotherapy in Melanoma

  Checkpoint blockade therapy using antibodies targeting CTLA4, PD1 or PDL1 have changed the way cancer patients with advanced disease are being treated, as evident by their FDA approval in a wide variety of malignancies, and their ability to induce high response rates when compared to conventional therapies (e.g. chemotherapy). However, even in melanoma, despite the high response rate, most patients are refractory to therapy or acquire resistance in 10-12 months. To identify key immunological elements coupled with response or resistance to checkpoint immunotherapy, we performed an unbiased analysis on 16,291 CD45+ immune cells from 32 patients (48 samples) treated with checkpoint therapy (anti-PD1=37; anti-PD1/CTLA4=11), using single cell transcriptomics. Initial unsupervised clustering of all CD45+ cells identified 11 clusters. When examining the association of these clusters with clinical outcome, we found that two clusters (B-cells, p=0.005; memory T-cells, p=0.03) were significantly enriched in responder lesions while 4 clusters (monocytes/macrophages, p=0.003; dendritic cells, p=0.015; exhausted CD8+ T-cells, p=0.005; and exhausted/cell-cycle lymphocytes, 1.3x10-5) are enriched in non-responder lesions. Next, by leveraging our unbiased single cell approach, we identified not only clusters but also specific markers associated with either responder lesions (PLAC8, LTB, LY9, SELL, TCF7, IGKC and CCR7) or non-responder ones (CCL3, CD38, HAVCR2, ENTPD1 and WARS), many of which were not previously reported to be associated with clinical outcome to checkpoint therapy. Due to the importance of CD8+ T-cells in controlling tumors, the significant association of T-cell states with clinical outcome, and their high abundance in melanoma tumors, we next focused our analysis on CD8+ T-cells and identified 2 main clusters CD8_G (with increased expression of genes linked to memory) and CD8_B (enriched for genes linked to cell dysfunction), that were significantly enriched in responder (CD8_G, p=1.4x10-6) and non-responder (CD8_B, p=0.005) lesions, respectively. Since cells with both states coexist in each of the responder and non-responder lesions, we decided to calculate the ratio between the number of cells in these 2 clusters and observed a significant separation between responders (CD8_G/CD8_B>1) and non-responders (CD8_G/CD8_B<1) when looking at all samples, baseline or post samples separately. Similar results were detected when looking at the expression of a single transcription factor, TCF7, in CD8 T-cells in an independent cohort (n=43) using a simple immunofluorescence assay. Additionally, we validated the identity and function of some of the newly identified cell states as well as their epigenetic landscape, and found that cells expressing the inhibitory molecules CD39 and TIM3, on top of being enriched in non-responder lesions, are likely to play a crucial role in T-cell exhaustion in melanoma. Collectively, our study provides extensive unbiased data in human tumors for discovery of predictors and therapeutic targets to checkpoint immunotherapy.

  Study phs001680

• Blood Somatic Mutations in TCGA Donors Suffering from Solid Tumors

  Blood somatic mutations identified across 8,530 solid tumor patients in TCGA cohort. We reasoned that low-coverage whole-genome sequencing of blood samples routinely carried out in cancer genomics projects may be repurposed to detect clonal hematopoiesis (CH). Thus, inspired by a previous approach to identify early mutations in the development of the hematopoietic system, we implemented a pipeline to systematically carry out this "reverse" somatic mutation calling on the paired blood/tumor samples. Blood somatic mutations were called using a 'reverse' approach, in which the tumor sample taken from each patient was used as control of their germline genome. Blood somatic mutations are thus detected as variants in the blood (with respect to the human reference genome) that are absent in the tumor sample. The variant calling was carried out in our in house cluster on downloaded blood/tumor BAM files. The matched blood and tumoral BAM files -- masked and deduplicated using GATK -- of 8,530 whole-exome patients were obtained as described above. The variant calling was carried out using Strelka2 (employing default parameters) with the blood sample as the tumoral input and the tumor sample as control (reverse calling). All variants with two or more supporting reads matching the caller PASS filter and with VAF<0.5 were kept. Mutations in lowly mappable regions as defined by the DUST algorithm (k=30) and UMAP68 (36-kmers) were excluded. Contiguous variants were merged into double-base substitutions. Variants with greater frequency across the cohorts than the DNMT3A R882H or JAK2 V617F hotspot in a cohort-specific Panel of Normals and in gnomAD v2.1 were removed. This was equivalent to discarding variants present in these datasets with an allele frequency greater than 0.008 in PoN TCGA and 0.0003 in gnomAD v2.1. Additionally, common SNPs as defined by the dbSNP 151 Common UCSC track and dbSNP were excluded. Mutations within segmental duplications, simple repeats and masked regions as defined in UCSC tracks were also removed. Finally, samples with the mutation count above the 97.5 percentile of the mutation burden across the cohort were deemed unreliable and excluded for further analyses. We call the set of variants obtained after the application of these filters the full set. A more conservative subset of somatic mutations was generated from the full set of blood somatic mutations. To this end, we applied MosaicForecast, a software designed to phase mutations to polymorphisms with the aim of identifying somatic mutations in a small number of cells and also predict mosaicism for the unphased ones with a random forest classifier. As a result, we obtained a subset of mosaic-phased mutations, and a subset of mutations likely to be somatic (mosaic set).In order to obtain access to this study, please first obtain access to TCGA study (phs000178).

  Study phs002867

• DAC for Direct Detection of Early-stage Cancers Using Circulating Tumor DNA

  Dac EGAC00001000701

• EGAD00010000612

  Celiac disease North Indian samples using Immunochip

  Dataset EGAD00010000612

• EGAD00010000688

  glioma normal samples using 250K

  Dataset EGAD00010000688

• EGAD00010000682

  glioma samples tumor using 250K

  Dataset EGAD00010000682

• EGAD00010000684

  glioma normal samples using cytoscan

  Dataset EGAD00010000684

• EGAD00010000686

  glioma samples tumor using cytoscan

  Dataset EGAD00010000686

• EGAD00010000714

  aplastic anemia samples tumor using 250K

  Dataset EGAD00010000714

• EGAD00010000395

  Myeloma case sample genotype using Affymetrix SNP6.0

  Dataset EGAD00010000395

• EGAD00010000510

  Matched control samples using HumanOmni1-Quad

  Dataset EGAD00010000510

• EGAD00010000514

  Case samples using SNP 6.0 Array

  Dataset EGAD00010000514

• EGAD00010000542

  Cusihg's syndrome normal samples using 250K

  Dataset EGAD00010000542

• EGAD00010000544

  Cusihg's syndrome tumor samples using 250K

  Dataset EGAD00010000544

• saudi_qc_data

  Genotyped case and control sampes using HumanExome Beadchip

  Dataset EGAD00010000872

• MAGE

  MAGEcontrol samples using omni 2.5M

  Dataset EGAD00010001612