11988 results for "cancer rna-seq"

in 38.95 milliseconds.

• Somatic mutations of 256 whole-genome sequenced colorectal cancer tumors.

  Somatic mutations of 256 whole-genome sequenced colorectal tumors. 234 MSS, 19 MSI and 3 POLE mutants. See Katainen R. et al. CTCF/cohesin-binding sites are frequently mutated in cancer, Nature Genetics 2015. doi:10.1038/ng.3335

  Dataset EGAD00001004329

• Metastatic breast cancer targeted gene screen (2014-09-24)

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations. This dataset contains all the data available for this study on 2014-09-24

  Dataset EGAD00001001018

• WGS on patients 5-7, study of metastatic prostate cancer

  Data from the study of subclonal metastatic expansion in prostate cancer. Whole genome shotgun sequencing of six samples, tumour and whole blood, from the three additional patients whose somatic variants were examined in depth.

  Dataset EGAD00001001344

• There are 116 liver cancer cases in this study and belong to LICA-CN project.The NGS test was performed with whole exome sequencing with HiSeq 2000 platform.

  There are 116 liver cancer cases in this study and belong to LICA-CN project

  Dataset EGAD00001003174

• Metastatic breast cancer targeted gene screen (2017-05-11)

  The samples will be sequenced for a targeted panel of cancer relevant genes (n ~ 370) and analysed for somatic mutations. This dataset contains all the data available for this study on 2017-05-11.

  Dataset EGAD00001003330

• Breast cancer sequential sampling study

  This study aims to whole genome sequence DNA derived from breast cancer patients who received neo-adjuvany chemotherapy. All patients had multiple biopsies performed before chemotherapy. Patients who had residual disease after the course of treatment underwent a further biopsy. We aim to characterise the mutations involved.

  Dataset EGAD00001000387

• dataset for esophageal cancer, 17 pairs for whole-genome sequencing and 71 pairs for whole-exome sequencing

  dataset for esophageal cancer, 17 pairs for whole-genome sequencing and 71 pairs for whole-exome sequencing

  Dataset EGAD00001000760

• Cancer-Normal chronic myeloid leukaemia sequencing data for "A comparative analysis of algorithms for somatic SNV detection in cancer", Bioinformatics 29 (2013) 2223

  This dataset contains the fastq sequencing data collected from bone marrow DNA of a chronic myeloid leukaemia patient at time of diagnosis.

  Dataset EGAD00001000967

• Multi-region sequencing of a RET fusion positive cancer patient

  Deep WGS sequencing (160x) of 2 different sites of disease of a patient with a RET fusion positive cancer. Amplicon sequencing of 19 other sites of the same patients for the RET fusion.

  Dataset EGAD00001005776

• Hyperpolarized carbon-13 MRI for very early response assessment of neoadjuvant chemotherapy in breast cancer patients

  Transcriptomic data for five patients with breast cancer undergoing neoadjuvant chemotherapy and hyperpolarised 13C-MRI for early response assessment

  Dataset EGAD00001008141

• DNA WGS Short Read Sequence (Illumina NovaSeq) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  DNA WGS Short Read Sequence (Illumina NovaSeq) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  Dataset EGAD00001015399

• LCCC1122: Defining the Triple Negative Breast Cancer Kinome Response to GSK1120212

  In this study the investigators looked at adaptive reprogramming impact on the kinome when a MEK inhibitor called GSK1120212 (trametinib) was administered in a "window of opportunity" trial. GSK1120212 is not yet approved by the FDA for use in breast cancer patients. The investigators gave GSK1120212 for a short period of time (one week) to examine MEK and the other kinase expression in cancer cells both before and after the study drug is given. The investigators gave this drug for research purposes only. The length of time it was given is not intended to treat cancer. Recently researchers at UNC developed a process that can comprehensively profile the majority of the individual kinases in the kinome and examine the impact on kinase expression of kinase inhibitors (Duncan et al, Cell 2012, PMID: 22500798). This can tell us which kinases need to be concurrently blocked to augment responsiveness and prevent acquired resistance so that the investigators can design the best combinations of kinase blocking drugs for triple negative breast cancer. This is especially important for individuals with triple negative breast cancer (TNBC) because there are no targeted drugs available that can block molecules that affect tumor growth. The investigators believe that kinase-blocking drugs have the potential to be a more effective treatment for people with TNBC. In this recently published study (Zawistowski et al, Cancer Discovery 2017, PMID: 28108460), TNBC patients treated with trametinib for 7 days resulted in a transcriptional response characterized by significant reprogramming of the tyrosine kinome, and this adaptive bypass response in human tumors was found to be similar to that seen in preclinical models including TNBC cell lines and mouse xenografts. In this study we also examined whether reprogramming differed between TNBC molecular subtypes, finding that basal-like and claudin-low human TNBC cells and mouse tumor subtypes had different adaptive transcriptional responses to MEK-ERK inhibition. Mechanistically we found that genome-wide enhancer remodeling drove the adaptive transcriptional response, suggesting that epigenetic approaches to reprogramming may be more durable than kinase inhibitor polypharmacology.

  Study phs001405

• National Institutes of Health The Cancer Genome Atlas (TCGA)

  The Cancer Genome Atlas (TCGA) is a comprehensive and coordinated effort to accelerate our understanding of the molecular basis of cancer through the application of genome analysis technologies, including large-scale genome sequencing. TCGA is a joint effort of the National Cancer Institute (NCI) and the National Human Genome Research Institute (NHGRI), which are both part of the National Institutes of Health, U.S. Department of Health and Human Services. TCGA projects are organized by cancer type or subtype. Click here for a current list of cancer types selected for study in TCGA. Data from TCGA (e.g., gene expression, copy number variation and clinical information), are available via the Genomic Data Commons (GDC). Data from TCGA projects are organized into two tiers: Open Access and Controlled Access. Open Access data tier contains data that cannot be attributed to an individual research participant. The Open Access data tier does not require user certification. Data in Open Access tier are available in the TCGA Data Portal. Controlled Access data tier contains individual-level genotype data that are unique to an individual. Access to data in the Controlled Access data tier requires user certification through dbGaP Authorized Access. Controlled Access data types consist of the following: Individual germline variant data (SNP .cel files) Primary sequence data (.bam files), which are available at GDC Clinical free text fields Exon Array files (for Glioblastoma and Ovarian projects only) NOTE: TCGA strives to release most data in the open access tier. Individual genotype or sequence files are prominent exceptions. Commonly requested files such as descriptions of somatic mutations or clinical data are open access. Please go to this page: https://tcga-data.nci.nih.gov/docs/publications/ to access all data associated with TCGA tumor specific publications. The TCGA study is utilized in the following dbGaP substudies. To view genotypes and other molecular data collected in these substudies, please click on the following substudies below or in the "Substudies" section of this top-level study page phs000178 TCGA study. phs000854 Genome-wide Analysis of Noncoding Regulatory Mutations in Cancer

  Study phs000178

• Gabriella Miller Kids First (GMKF) Pediatric Research Program in Susceptibility to Ewing Sarcoma Based on Germline Risk and Familial History of Cancer

  Ewing sarcoma (EWS) is a deadly bone cancer that occurs in children and adolescents. Mounting evidence suggests that a genetic predisposition exists for this pediatric cancer, although the specific genetic contribution has yet to be identified. EWS has never been linked to a specific cancer predisposition syndrome, although several case reports have been published that describe siblings and cousins with EWS. Furthermore, neuroectodermal tumors appear to occur more commonly in families with EWS. The two consistent epidemiology findings in EWS include a very strong Caucasian predilection and increased rates of hernia in EWS patients and their family members. Finally, the role of genetic microsatellite repeats in EWS tumorigenesis has been recently described, and these GGAA microsatellites are polymorphic in repeat size and location across the genome. The study goals of this Kids First project include (1) To identify cancer predisposition genes in EWS trios increasing disease risk, (2) To identify genome-wide GGAA microsatellite repeats in EWS trios increasing disease risk, and (3) To identity de novo mutation and structural variant rates in EWS trios reflecting underlying DNA repair defects that increase disease risk. As part of the Kids First Common Fund initiative, this study proposal will further elucidate the genetic contribution to pediatric cancer development. Around 375 of these trios were selected for whole genome sequencing as part of the Gabriella Miller Kids First fund. The EWS trios have been collected as part of the Children's Oncology Group's AEPI10N5 Study ("Genetic Epidemiology of Ewing Sarcoma"), and each trio has associated phenotypic data including a detailed family history. We will interrogate the sequence data using our genomic analysis pipeline at the University of Utah and the Utah Science Technology and Research initiative's (USTAR) Center for Genetic Discovery. We will look for the genetic contribution to EWS and the sequence data with be shared in a repository designated by the Kids First Common Fund. The WGS of these ~375 EWS trios will help us to understand the genetic origins of a deadly childhood cancer and may lead to novel strategies for prevention and treatment.

  Study phs001228

• Evolutionary Trajectories of Small Cell Lung Cancer under Therapy

  Small cell lung cancer (SCLC) is one of the deadliest human cancers with a five-years survival rate of less than 7%. The standard of care for extensive-stage SCLC consists of systemic treatment with platinum and etoposide, recently combined with PD-L1 immune checkpoint inhibitors (ICI). SCLC patients show high sensitivity to platinum-based chemotherapy, followed by rapid recurrence, which distinguishes SCLC from most human cancers. Unfortunately, second-line treatment with other chemotherapeutics or immunotherapy is only marginally effective, and patients ultimately succumb to their disease. We performed whole exome sequencing, whole genome sequencing and transcriptome sequencing of multiple tumor regions from 65 patients with SCLC. We determined tumor phylogenies at diagnosis and throughout chemotherapy and immunotherapy by multi-region sequencing of 160 tumors from 65 patients, to thus decipher the evolutionary processes underlying the remarkable sensitivity of small cell lung cancer (SCLC) to chemotherapy.

  Study EGAS50000000169

• Genomic Correlates of Response and Resistance to Immune Checkpoint Blockade in Solid Tumors

  Immune checkpoint inhibitors yield clinical benefit in many cancer types, but molecular predictors of response have not yet been robustly characterized. In this study, we pursued whole exome sequencing (WES) of pre-treatment tumors from patients treated with immune checkpoint therapies - including monoclonal antibodies targeting programmed cell death-1 (PD-1) and cytotoxic T-lymphocyte-associated protein-4 (CTLA-4). Using these data, we aim to apply computational pipelines for mutation-calling, neoantigen prediction, and other analyses to validate pre-existing hypotheses regarding response to immune checkpoint therapies and discover new relationships with greater power. Further, by pursuing genomic characterization of tumors from patients with a variety of cancer types, we hope to describe molecular features of intrinsically sensitive or resistant tumors that are both context-specific and shared across cancer types.

  Study phs001565

• The Nurses' Health Study (NHS) GWAS of Mammographic Density

  The Nurses' Health Study is an on-going prospective cohort study of women that was initiated in 1976. This specific study was part of a larger study to advance our knowledge of breast cancer etiology, expand the current knowledge of mammographic density, and clarify the relationship between mammographic density and breast cancer risk. We conducted a nested case control study of breast cancer among women who provided a blood sample. We then targeted our mammogram collection to participants that were selected as part of this nested case-control study (i.e. those who had provided a blood sample). The mammogram closest to the date of blood draw (~1989-1990) was used. We assessed mammographic breast density from digitized film images using a computer assisted thresholding method (Cumulus). The women in this study were genotyped using the Illumina Omni Express Platform.

  Study phs000975

• A benchmark of DNA methylation deconvolution methods for tumoral fraction estimation using DecoNFlow

  In cancer patients, circulating cell-free DNA (cfDNA) originates from both healthy and cancer cells, and the proportion of tumor-derived cfDNA serves as a surrogate marker of tumor burden. Tumoral cfDNA can be identified using patient-specific mutations or more general tumor-specific DNA methylation patterns that are preserved in cfDNA, enabling non-invasive cancer detection and monitoring. Accurately estimating tumor fractions remains challenging due to the heterogeneous mixture of cfDNA sources in body fluids. Computational DNA methylation deconvolution methods can address this by estimating tumoral fraction with or without reference methylomes. Here, we benchmarked 10 reference-based and 2 reference-free DNAm deconvolution tools and provide the data generated for this benchmarking, consisting of 10 neuroblastoma cell lines and one healthy cfDNA sample (pooled from 15 healthy cfDNA samples), profiled using cfRRBS.

  Study EGAS50000001529

• Whole-genome sequencing in 14 cases and whole-exome sequencing in 90 cases of Chinese ESCC

  Esophageal cancer is one of the most aggressive cancers and the sixth leading cause of cancer death worldwide1. Approximately 70% of the global esophageal cancers occur in China and over 90% histopathological forms of this disease are esophageal squamous cell carcinoma (ESCC)2-3. Currently, there are limited clinical approaches for early diagnosis and treatment for ESCC, resulting in a 10% 5-year survival rate for the patients. Meanwhile, the full repertoire of genomic events leading to the pathogenesis of ESCC remains unclear. Here we show a comprehensive genomic analysis in 158 ESCC cases, as part of the International Cancer Genome Consortium (ICGC) Research Projects (http://icgc.org/icgc/cgp/72/371/1001734). We conducted whole-genome sequencing in 14 ESCC cases and whole-exome sequencing in 90 cases.

  Study EGAS00001001487

• Genomic DNA of tumor tissues, adjacent normal tissues, and peripheral blood were extracted using QIAamp DNA mini Kit (QIAGEN, cat. #51306)

  Although genomic instability, epigenetic abnormality, and gene expression dysregulation are hallmarks of colorectal cancer, these features have not been simultaneously analyzed at single cell resolution. Using optimized single cell multiomics sequencing together with multiregional sampling of the primary tumor, lymphatic and distant metastases, we provide insights beyond intratumoral heterogeneity. Genome wide DNA methylation levels were relatively consistent within a single genetic sublineage. The genome-wide DNA demethylation patterns of cancer cells were consistent in all 10 sequenced patients. The cancer cells’ DNA demethylation degrees clearly correlated with the densities of the heterochromatin-associated histone modification H3K9me3 of normal tissue, and those of repetitive element Long Interspersed Nuclear Element 1. Our work demonstrates the feasibility of reconstructing genetic lineages, and tracing their epigenomic and transcriptomic dynamics with single cell multiomics sequencing.

  Study EGAS00001003242

• Characterization and clinical relevance of the genomic alterations defining invasive lobular breast cancer

  Background: Invasive lobular breast cancer (ILBC) is the second most common histological subtype after ductal breast cancer (IDBC). In spite of significant clinical and pathological differences, ILBC is still treated as IDBC. Here, we aimed at identifying recurrent genomic alterations in ILBC with potential clinical implications.Methods: Starting from 630 ILBC primary tumors with a median follow up of 10 years, we interrogated oncogenic substitutions and indels of 360 cancer genes and genome-wide copy number alterations in 413 and 170 ILBC samples, respectively, and correlated those findings with clinical, pathological, and outcome features. The Cancer Genome Atlas database was used for comparison of frequency estimates.Results: Besides the high mutation frequency of CDH1 in 65% of the tumors, alterations in one of the three key genes of the PI3K pathway, PIK3CA, PTEN and AKT1, were present in more than half of the cases. ERBB2 and ERBB3 were mutated in 5.1 and 3.6% of the tumors. FOXA1 mutations and ESR1 copy number gains were detected in 9% and 25% of the samples. All these alterations were more frequent in ILBC than IDBC. The histological diversity of ILBC was associated with specific genomic alterations, such as enrichment for ERBB2 mutations in the mixed, non-classic subtype, and for ARID1A mutations and ESR1 gains in the solid subtype. Finally, ERBB2 and AKT1 mutations were associated with short-term risk of relapse, and chromosome 1q and 11p gain with increased and decreased breast cancer free survival, respectively.Conclusion: ERBB2, ERBB3 and AKT1 mutations represent high prevalence therapeutic targets in ILBC. FOXA1 mutations and ESR1 gains urgently deserve dedicated clinical investigation, especially in the context of endocrine treatment.

  Dataset EGAD00001001395

• A Tumour Organoid Biobank for Mapping Cancer Cell Vulnerabilities - WGS

  Whole genome sequencing data from cancer patient-derived organoids and their matched tumour tissue samples. Part of a study to include genomic and transcriptomic sequencing data, along with CRISPR screening data from cancer patient-derived organoids and matched tumour tissues. Some organoids were developed as part of the Human Cancer Models Initiative (HCMI) in collaboration with Cancer Research UK (CRUK). The study includes organoids derived from colorectal, oesophageal, ovarian, pancreatic, and stomach cancer samples.

  Dataset EGAD00001015469

• CITE-seq AdaptNK

  CITEseq was performed as outlined in Biolegend ‘TotalSeqTM-A Antibodies and Cell Hashing with 10x Single Cell 3' Reagent Kit v3 3.1 Protocol’ with minor modifications, using Biolegend oligo-conjugated antibodies and streptavidin TotalSeq reagents. Briefly, ADAPT-NK cells were stained with CD56-biotin mAb (Miltenyi, clone REA196), followed by TotalSeq antibodies and streptavidin-PE and Live/Dead Aqua (Invitrogen). Cells were subsequently sorted for viable CD56+ cells by flow cytometry.

  Dataset EGAD50000000329

• Profiling of gene expression and epigenomics in the fetal brain

  scRNA-seq and Cut&Tag from a sample of the human fetal brain. To compare neurogenesis in the primary human brain with that in organoids, we profiled transcriptome and chromatin accessibility (10X multiome) as well as bulk Cut&Tag of histone modifications H3K27me3, H3K27ac and H3K4me3. We used a human brain sample from GW 19 for all experiments.

  Dataset EGAD50000000225

• scKaryoSeq of CRISPR-Cas9 edited primary human T cells

  To explore T cell-intrinsic driving forces of CRISPR-induced aneuploidy at the TRAC gene locus, we performed scKaryo-seq (Bolhaqueiro et al., Nature Genetics 2019). We compared the impact of the small molecule pifithrin-alpha in activated TRAC KO T cells. In a separate experiment, we determined the effect of pifithrin-alpha on non-activated T cells edited at the TRAC locus or treated with non-targeting Cas9 RNPs.

  Dataset EGAD50000000929

• smallRNA-seq of isolated pancreatic islets

  In this study we performed smallRNA-sequencing, a sequencing method designed for small noncoding RNAs, to investigate the miRNA expression profile of human islets isolated from pancreata of donors without diabetes mellitus (n=3) and donors with type 2 diabetes (n=3).

  Study EGAS50000000865

• Transcriptomic analysis of LINE1 expression in the human brain

  Twist Bioscience probes were designed to LINE1 and HERV sequences for targeted amplification. Enriched cDNA libraries were then sequenced on the PacBio Sequel II, 4 samples/SMRTcell. The available files have undergone ccs (using the default parameters except for --min-rq 0.9, which was a recommended parameter for Iso-Seq) and barcode demultiplexing. Recommended analysis follows https://isoseq.how/, starting at the primer removal and demultiplexing step with lima.

  Dataset EGAD50000000265

• miRNA seq

  miRNA Sequencing of olfactory mucosa (OM) cells derived from cognitively healthy and individuals with AD exposed to traffic-related ultrafine particles (UFPs) for 72h in submerged cultures. The UFPs used for exposures were: A0 and A20. Exposures were compared to the corresponding blank samples.

  Study EGAS50000001050

• scRNAseq of endothelial cells from human iPSC-derived kidney organoids transplanted in the coelomic cavity of chicken embryos compared to untransplanted controls

  This dataset includes scRNA-seq fastq files and Seurat counts and metadata for 6 samples of endothelial cells enriched from hiPSC-derived kidney organoids cultured in vitro or transplanted in chicken embryos. Samples were obtained at 2 timepoints: d7+13 (1 day after transplantation) and day 7+20 (8 days after transplantation).

  Dataset EGAD50000001555

• Somatic L1 retrotransposition mapping in high-grade serous ovarian carcinoma using LDI-PCR/Nanopore-sequencing

  Somatic L1 retrotransposition was mapped in high-grade serous carcinoma (HGSC) tumors using LDI-PCR/Nanopore-seq method. This method identifies somatic L1 insertions originating from two active L1 loci at chr22q12.1 and chrXp22.2. Multiple tumors from the same patient were utilised to understand L1-mediated intrapatient heterogeneity. Long-read data generated by LDI-Nanopore sequencing was aligned to the reference genome (GRCh38).

  Dataset EGAD50000001707

• Transcriptome analysis of human muscle/myofibers carrying the human nemaline myopathy type 6-associated KBTBD13-R408C variant.

  This dataset contains mRNA-seq results from eleven samples from human donors, each sample being composed of 5-10 rebulked fiber type-specific myofibers. This sample set includes; 1) Three FT-I and three FT-IIa rebulked samples from control individuals 2) Three FT-I and two FT-IIa rebulked samples from NEM6 patients with a KBTBD13R408C variant (NP_001094832.1: p.Arg408Cys)

  Dataset EGAD50000002408

• cfDNA

  The mutational status of 112 recurrently mutated genes in B-cell lymphoma was examined by targeted next-generation sequencing (NGS). Libraries were performed with 15-30 ng of cfDNA obtained from plasma using molecular-barcoded library adapters (ThruPLEX Tag-seq kit; Takara) coupled with a custom hybridization capture based method (SureSelect XT Target Enrichment System Capture strategy, Agilent Technologies Inc.) and sequenced in a MiSeq instrument (Illumina, 2x150bp).

  Dataset EGAD00001006566

• DNA-seq BAM files from 16 patients affected by acute intermittent porphyria

  Paired-end BAM files from 16 patients affected by acute intermittent porphyria. Whole genome sequencing of these samples was performed in an Illumina HiSeq 4000 instrument. Libraries were prepared using the Fisher PE Kit (Kapa Biosystems). FASTQ files were processed at the CNAG (Barcelona) using the GEM short-read aligner on the human genome version hs37d5, producing a total of 16 BAM files.

  Dataset EGAD00001006951

• Strand-seq data of primary acute myeloid leukemia patient samples with complex karyotype

  In this study, we aimed to identify somatic structural variation of acute myeloid leukemia with complex karyotype (CK-AML) at the single-cell level and to investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from four CK-AML patients. We also performed strand-specific single-cell sequencing of two patient-derived xenografts (PDXs).

  Dataset EGAD00001011172

• RNAseq and ATACseq data

  RNAseq and ATACseq data for the FMF patients and healthy control. The RNAseq data was sequenced on a BGI MGI G400 machine, with PE100 reads. ATAC-seq libraries were prepared with Illumina Nextera primers and sequenced on NovaSeq 6000 platform with 50bp paired-end sequencing, where each sample was sequenced to approximate 60 million reads.

  Dataset EGAD00001010304

• WGS of cell line MMML-seq / MALY-DE tumor_4167452

  This dataset contains the aligned whole genome sequencing data of cell line 380. This cell was established from the peripheral blood of a 15-year-old boy with acute lymphoblastic leukemia at relapse, showing an immature phenotype and carrying an IGH-MYC (t(8;14)) as well as an IGH-BCL2 (t(14;18)) chromosomal translocation. The sequencing was performed on an Illumina X-ten sequencer.

  Dataset EGAD00001004090

• Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls

  We created three technical replicates of cell-free DNA from AML patient plasma to assess batch effects and utility of spike-in controls for the cfMeDIP-seq method. Each set of samples were given to three different technicians with slightly different protocols. Details can be found in Wilson et al. "Sensitive and reproducible cell-free methylome quantification with synthetic spike-in controls".

  Dataset EGAD00001006986

• Single Cell RNA Transcriptomics of Mantle Cell Lymphoma Reveals the Presence of Treatment-Resistant Subclones at the Time of Diagnosis

  Mantle cell lymphoma is a chronically relapsing B cell neoplasm characterized by clonal heterogeneity. We implemented single cell RNA sequencing of paired tumor samples from four patients with an aggressive nodal MCL at diagnosis and after failure of standard immunochemotherapy. Clustering the cells based on the inferred CNVs showed small subclones present at diagnosis with a CNV profile similar to the major subclone at relapse. Comparison of these subclones to major subclones present at diagnosis revealed 119 upregulated pathways common for the four patient with an aggressive MCL, including NF-kappaB and PTEN signaling pathways. Additionally, we sequenced a patient with an indolent to blastoid MCL transformation with intestinal tissue involvement. In contrast to other compartments at relapse, the cells in the intestine showed strikingly different CNV profile and presence of new driver mutations including NOTCH1. In conclusion, our study demonstrates that scRNAseq can potentially detect therapy resistant subclones at diagnosis.

  Study EGAS50000000825

• Whole exome and Transcriptome sequencing of treatment-naïve esophageal adenocarcinoma biopsies and matched peripheral blood mononuclear cells

  Exome sequencing was performed on n=28 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. WES was performed on EAC biopsies at 120X average coverage, with autologous PBMCs used as germline controls at 80X average coverage. Libraries were prepared from 30 ng of input DNA using the SureSelect QXT Human All Exon V7 kit (Agilent Technologies) and sequenced on the NextSeq 550 (Illumina), 2x150 bp. BCL files were demultiplexed to FastQ files using bcl2fastq2 software (Illumina). Three paired end sequencing batches were analyzed independently (Batch1: samples 8, 10, 11, 12, 15, 17, 18; Batch2: samples 20, 24, 25, 26, 27, 29, 30, 31, 33, 34 ; Batch3: samples 35, 37, 39, 40, 41, 43, 45, 48, 54, 55, 57). RNA sequencing was performed on n=26 treatment-naïve esophageal adenocarcinoma (EACs). Three to four biopsies sampling different areas of each tumor were pooled before nucleic acid extractions to mitigate the elevated heterogeneity described for EAC. RNAseq libraries were prepared on 50 ng of total RNA (with RNA integrity index RIN >=7) with the TruSeq Stranded mRNA library preparation kit (Illumina) in accordance with low-throughput protocol. After PCR enrichment (15 cycles) and purification of adapter-ligated fragments, the concentration and length of DNA fragments were measured using D1000 Screen Tape System (Agilent), obtaining a median insert size of 311 nucleotides. Then, RNAseq libraries were sequenced using the Illumina NovaSeq platform, 1x100 bp, obtaining on average 100 million single reads per sample.

  Dataset EGAD00001010876

• Somatic Genome Dynamics of Barrett's Esophagus Patients with Non-Cancer and Cancer Outcomes

  A case-control study was designed with 80 participants diagnosed with Barrett's Esophagus (BE) selected from a larger case-cohort study (Li et al., 2014, PMID: 24253313) within the Seattle Barrett's Esophagus Program (SBEP) at the Fred Hutchinson Cancer Research Center. The study included 40 cases with BE with non-cancer outcomes, "NCO", who did not progress to esophageal adenocarcinoma (EA), and 40 controls who progressed to an endoscopically detected, incident EA (cancer outcome, "CO"). For each patient, two timepoints were evaluated (T1 and T2). NCO were matched to CO based on age at T1 (T1=first endoscopy with sufficient sample availability), and time between T1 and T2 (T2 in CO=time of diagnosis of incident EA). In 10 NCO, a third time point (T3), a mean of 13.2 years after T1, was also sequenced. Mapped endoscopic biopsies, at 1/3 and 2/3 annotated distances from the gastroesophageal junction within the Barrett's segment, were sampled per patient at each timepoint. Each biopsy was purified to separate BE epithelium from stroma, and DNA was extracted from purified epithelium for 60X WGS and 2.5M SNP array; normal control blood (N=62) or normal gastric sample (N=18) were analyzed by 30X WGS and 2.5M SNP array. An additional seven normal gastric biopsy samples in seven patients with normal control blood were also sequenced at 60X as controls. All research participants contributing clinical data and esophageal samples to this study provided written informed consent, subject to oversight by the Fred Hutchinson Cancer Research Center IRB Committee D (Reg ID 5619).

  Study phs001912

• Oncogenome of Kaposi Sarcoma

  Kaposi Sarcoma (KS) is an aggressive cancer caused by the Kaposi Sarcoma Herpesvirus (KSHV/HHV-8). Individuals with immunodeficiencies, exemplified by HIV, have an elevated risk of developing KS. However, understanding of the genetic factors contributing to KS progression is still limited. To explore potential genetic alterations in KS that could offer biological or therapeutic insights, whole exome sequencing was performed on 78 KS tumors and matching normal skin samples from 59 adults with KS (46 with HIV-associated KS and 13 with HIV-negative KS) receiving treatment at the Uganda Cancer Institute in Kampala, Uganda. Results showed a very low mutational burden in all samples except one (median = 11 mutations), which is the smallest number of mutations found across all 33 cancer types in The Cancer Genome Atlas (TCGA). No recurrent mutations were identified. Mutational signatures included impaired DNA mismatch repair and smoking. There was no evidence suggesting that multiple tumors from the same patient originated from a single clone. The number of genome copy alterations per genome was higher in tumors from individuals without HIV and those with advanced-stage disease. This suggests that lesions that take longer to develop may accumulate more alterations, although the overall number of alterations remains low compared to other cancers. These findings suggest that KS pathogenesis differs from other cancers, with KSHV viral infection and the expression of viral oncogenes being the primary drivers of carcinogenesis, rather than clonal oncogenic transformation arising from genetic alterations of cancer-related cellular genes.

  Study phs003897

• A novel breast cancer cell line derived from a metastatic bone lesion of a breast cancer patient

  Purpose: We sought to generate and characterize a novel cell line from a breast cancer bone metastasis in order to better study the progression of the disease.Methods: The cell line, P7731, was derived from a metastatic bone lesion of a breast cancer patient and assessed for marker expression. P7731 was analyzed for DNA copy number variation, somatic mutations and gene expression and compared to the primary tumor. Results: P7731 cells are negative for estrogen receptor alpha (ERα), progesterone receptor (PR) and HER2 (triple-negative), strongly express vimentin (100% of cells positive) and also express cytokeratins 8/18 and 19 but at lower frequencies. Flow cytometry indicates P7731 cells are predominantly CD44+/CD49f+/EpCAM-, consistent with a primitive, mesenchymal-like phenotype. The cell line is tumorigenic in immunocompromised mice. Exome sequencing identified a total of 45 and 76 somatic mutations in the primary tumor and cell line respectively, of which 32 were identified in both samples and included mutations in known driver genes PIK3CA, TP53 and ARID1A. P7731 retains the DNA copy number alterations present in the matching primary tumor. Homozygous deletions detected in the cell line and in the primary tumor were found in regions containing three known (CDKN2A, CDKN2B and CDKN1B) and 23 putative tumor suppressor genes. Cell line specific gene amplification coupled with mRNA expression analysis revealed genes and pathways with potential pro-metastatic functions.Conclusion: This novel human breast cancer-bone metastasis cell line will be a useful model to study aspects of breast cancer biology, particularly metastasis-related changes from breast to bone.

  Study EGAS00001002840

• Serrated Colorectal Cancer: An Emerging Disease Subtype

  This dataset represents two combined study populations. Serrated Colorectal Cancer: An Emerging Disease Subtype (called the Advanced Colorectal Cancer of Serrated Subtype Study or ACCESS Study) was a grant awarded to investigate a newly-recognized, biologically-distinct subtype of colorectal cancer (CRC) called “serrated CRC.” The objective of this project was to characterize factors related to the genetic predisposition, clinical presentation, and prognosis of serrated CRC. The study recruited incident invasive CRC cases diagnosed between April 2016 and December 2018, aged 20-74 years at diagnosis. Cases were identified through the Surveillance, Epidemiology and End Results (SEER) cancer registry serving 13 counties in western Washington State. Eligibility for all individuals was limited to those who were English-speaking and could consent. Participation included completing a baseline epidemiologic questionnaire shortly after diagnosis, optional donation of a saliva sample for genetic analysis, and optional consent to release of medical records and tissue specimens related to their diagnosis. Tumor specimens were tested for serrated CRC-defining molecular characteristics. Further, we have vital status on all participants and cause of death on those that have died since enrollment. Hormones and Colon Cancer: Epigenetic Subtypes, Risks, and Survival (called the Post-Menopausal Hormones Study or PMH Study) was a grant awarded to investigate the impact of post-menopausal hormone use on colon cancer risk, tumor molecular characteristics, and outcomes. Eligible cases were females, newly diagnosed with invasive colorectal adenocarcinoma between October 1998 and February 2002, aged 50 to 74 years. Cases were residents of 10 out of the 13 counties in western Washington State served by the Surveillance, Epidemiology and End Results (SEER) cancer registry. Eligibility for all individuals was limited to those who were English-speaking with available telephone numbers, in which they could be contacted. Unrelated population-based controls were randomly selected according to age distribution (in 5-year age intervals) of the eligible cases by using lists of licensed drivers from the Washington State Department of Licensing (for individuals aged 50 to 64 years) and rosters from the Health Care Financing Administration (now the Centers for Medicare and Medicaid, for individuals older than 64 years). Participation included completing a baseline epidemiologic questionnaire, optional donation of a saliva sample for genetic analysis, and (for cases only) optional consent to release of medical records and tissue specimens related to their diagnosis. Tumor specimens were tested for epigenetic and other molecular characteristics. The ACCESS study was supported by funding from the National Cancer Institute of the National Institutes of Health (NCI/NIH) (R01CA196337, PI: Newcomb, PA), as was the PMH Study (R01CA076366, PI: Newcomb, PA). Additional support for the PMH Study came from the Seattle site of the Colon Cancer Family Registry (SCCFR) (U01CA167551, PI: Jenkins, M, and U01/U24CA074794, PI: Newcomb, PA). Additional support for case ascertainment was provided by the Cancer Surveillance System of the Fred Hutchinson Cancer Center, which is funded by Contract Number HHSN261201300012I; NCI Control Number: N01 PC-2013-00012; Contract Number HHSN261201800004I; and NCI Control Number: N01 PC-2018-00004 from the Surveillance, Epidemiology and End Results (SEER) Program of the National Cancer Institute with additional support from the Fred Hutchinson Cancer Center and the State of Washington. This research was also supported by the Genomics and Bioinformatics, Comparative Medicine, Specialized Pathology, Collaborative Data Services, and Experimental Histopathology Shared Resources of the Fred Hutch/University of Washington Cancer Consortium (P30 CA015704).Tumor marker testing was performed using formalin-fixed paraffin-embedded diagnostic tumor tissue specimens, and DNA extracted from those specimens. Testing for microsatellite instability (MSI) was based on either a 10-gene panel (BAT25, BAT26, BAT40, MYCL, D5S346, D17S250, ACTC, D18S55, D10S197, BAT34C4) or a 4-marker immunohistochemistry panel of DNA mismatch repair proteins (MLH1, MSH2, MSH6, PMS2). CpG island methylator phenotype (CIMP) testing was based on a validated quantitative DNA methylation assay using a five-gene panel (CACNA1G, IGF2, NEUROG1, RUNX3, SOCS1) or eight-gene panel (CACNA1G, IGF2, NEUROG1, RUNX3, SOCS1, MLH1, CRABP1, CDKN2A). Somatic p.V600E BRAF mutation status was tested for using a fluorescent allele-specific PCR assay. KRAS mutations in codons 12 and 13 were also assessed through forward and reverse sequencing of amplified tumor DNA. DNA was extracted from blood/saliva samples using conventional methods. The genotyping panel completed was the Build37 OncoArray500K-C, including 1%-6% blinded duplicates to monitor the quality of the genotyping. Quality control procedures were performed to 1) make sure that there were no patterns of missing data by batch, study, or plate, 2) check for gender discrepancies and kinship, 3) complete Principal Component Analysis, and 4) test for Hardy-Weinberg equilibrium (HWE). Samples were excluded based on call rate, heterozygosity, unexpected duplicates, gender discrepancy, and unexpectedly high identity-by-descent or unexpected genotypic concordance (>65%) with another individual. In addition, variants were excluded based on call rate (98%), lack of HWE in controls (P

  Study phs002171

• Clinical Proteomic Tumor Analysis Consortium (CPTAC) Proteogenomic Confirmatory Study of Breast, Colon, Lung, and Ovarian Tumors

  Recently, significant progress has been made in characterizing and sequencing the genomic alterations in statistically robust numbers of samples from several types of cancer. For example, The Cancer Genome Atlas (TCGA), International Cancer Genome Consortium (ICGC) and other similar efforts are identifying genomic alterations associated with specific cancers (e.g., copy number aberrations, rearrangements, point mutations, epigenomic changes, etc.). The availability of these multi-dimensional data to the scientific community sets the stage for the development of new molecularly targeted cancer interventions. Understanding the comprehensive functional changes in cancer proteomes arising from genomic alterations and other factors is the next logical step in the development of high-value candidate protein biomarkers. Hence, proteomics can greatly advance the understanding of molecular mechanisms of disease pathology via the analysis of changes in protein expression, their modifications and variations, as well as protein-protein interaction, signaling pathways and networks responsible for cellular functions such as apoptosis and oncogenesis. Realizing this great potential, the NCI launched the second phase of the CPTC initiative in September 2011. Renamed the Clinical Proteomic Tumor Analysis Consortium, CPTAC is beginning to leverage its analytical outputs from Phase I to define cancer proteomes on genomically-characterized biospecimens. The purpose of this integrative approach is to provide the broad scientific community with knowledge that links genotype to proteotype and ultimately phenotype. The data contained in this dataset are derived from samples designed to confirm CPTAC findings from the TCGA samples. These confirmatory samples contain breast, ovarian, colon, and lung tumors collected via a protocol optimized for proteomics. Specifically, ischemic time of the sample was controlled and restricted to less than 30 minutes. ACGT, Inc. produced whole exome, mRNAseq, and miRNAseq for these samples. Corresponding proteomic data are available at: https://cptac-data-portal.georgetown.edu/cptacPublic/ The study design was to profile colon, breast, ovarian, and lung tumors both genomically and proteomically. Germline DNA was obtained from blood. Normal control samples for proteomics varied by organ site: adjacent colon tissue for colon cases, contralateral breast tissue for some breast cases, and Fallopian tube fimbria for some ovarian cases. Lung cases had no normal control for proteomic analysis. All cancer samples were derived from primary and untreated tumors.

  Study phs000892

• Scalable ultra-high-throughput multiplexed single-cell chromatin and RNA profiling reveals gene regulatory dynamics during stimulation time courses and CRISPR perturbation screens

  Data for 1) hiPSC-derived macrophages across a polarization time course from the naive M0-state to the M1- and M2-states, 2) Primary T-cells differentiated to helper subtypes, and 3) spontaneous differentiation of hiPSCs upon perturbation of GATA2, NR4A2 or SOX17

  Dac EGAC50000000485

• FLT3 is genetically essential for ITD-mutated leukemic stem cells but dispensable for human HSCs

  bulk RNA sequencing of AML patients It contains 18 samples from primary AML patients. Half of the samples are control samples and half of the samples are FLT3-ITD knock-out (edited for the FLT3-ITD mutation). It is using Illumina high-throughput technology

  Dataset EGAD50000000636

• Waldenström Macroglobulinemia Single-Cell Data Access Committee

  This Data Access Committee (DAC) is responsible for reviewing and approving access requests for controlled-access human single-cell sequencing data, including single-cell RNA sequencing and immune receptor profiling, generated from patients with Waldenström macroglobulinemia. The DAC ensures that all data access requests comply with the informed consent provided by study participants and are consistent with applicable ethical and regulatory requirements.

  Dac EGAC50000000863

• Whole transcriptome sequencing of C1498 cells.

  The dataset contains raw data (FASTQ) of whole transcriptome sequencing of C1498 cells (n=1 sample). Libraries were prepared with the Illumina Stranded Total RNA Prep with Ribo-Zero Plus kit (Illumina, San Diego, CA, USA) and and 100bp paired-end reads were generated on the NovaSeq 6000 Sequencing System (Illumina).

  Dataset EGAD50000002404

• Single-cell short-read transcriptomes from CH, MDS and AML patients with splicing factor mutations

  Single-cell RNA sequencing from CH (n = 2), MDS (n = 6, MDS02 in 2 replicates) and AML (n = 1, in 2 replicates) samples with mutations in splicing factors (SF3B1 - n = 8, U2AF1 n = 1). cDNA from 10x Genomics 3' V3.

  Dataset EGAD00001011283

• 20190219_EGA_MelanomaOnTreatment

  Illumina platform sequencing data for matched tumour-normal DNA samples from 77 melanoma patients participating in a study investigating response to immunotherapy. Selected cases also have RNA sequencing of the tumour.

  Dataset EGAD00001004869