9338 results for "cancer rna-seq"

in 40.18 milliseconds.

• Smartseq2 data of single immune cells in hepatocellular carcinoma

  The immune microenvironment of hepatocellular carcinoma (HCC) is poorly characterized. Combining two single-cell RNA sequencing technologies, we produced transcriptomes of CD45+ immune cells for HCC patients from five immune-relevant sites: tumor, adjacent liver, hepatic lymph node (LN), blood, and ascites. This dataset is part of Smartseq2 data

  Dataset EGAD00001005960

• Mapping genetic variants underlying gene regulation in healthy intestinal cell types to identify novel IBD drug targets

  Biopsies from the terminal ileum and rectum of healthy individuals are digested on ice to single cells and processed for single-cell RNA-sequencing (10X Genomics and Illumina) This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/.

  Dataset EGAD00001006331

• Transcriptomic profiling of primary tumor and paired hepatic oligometastasis of PDAC

  The dataset was generated for studying metastatic mechanism of pancreatic ductal adenocarcinoma (PDAC). It is consisted of pair-end raw RNA sequencing reads of 33 fresh froze PDAC specimens, which includes 6 tumor-adjacent normal tissues (N), 13 primary tumors (PT), and 14 hepatic metastases (HM) from 14 PDAC patients (6 N-PT-HM trios, 7 PT-HM paires, and 1 HM).

  Dataset EGAD00001006598

• Stage-specific gene and transcript dynamics in human male germ cells

  To study global transcriptional dynamics during human spermatogenesis we sequenced total RNA of human testicular biopsies with 5 specific histological phenotypes: Sertoli cell-only (SCO, n=3), spermatogenic arrests at the spermatogonial (SPG, n=4), spermatocyte (SPC, n=3), and spermatid (SPD, n=3) level, as well as normal spermatogenesis (Normal, n=3).

  Dataset EGAD00001008652

• MDS primary and xenografted samples treated with LOXL inhibitor

  This dataset contains bam files mapped to hg19 (exome and panel) or hg38 (RNA) that either were primary bone marrow cells or sorted human cells after long term engraftment in NSG mice treated with LOXL inhibitor

  Dataset EGAD00001008695

• Genomics of enteropathy-associated T cell lymphoma (EATL)

  Whole exome sequencing of enteropathy-associated T cell lymphoma (EATL) tumors and paired normals, as well as RNA-sequencing of EATL tumors: including (1) 69 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples, (2) 36 exome capture, paired-end Illumina Hiseq sequencing, BAM files from EATL paired normal samples, and (3) 32 RNAseq, paired-end Illumina Hiseq sequencing, BAM files from EATL tumor samples.

  Dataset EGAD00001003284

• Single-cell RNA and TCR sequencing of 37 PBMC pools of advanced HCC patients.

  scRNAseq and scTCRseq of serial peripheral blood mononuclear cell (PBMC) samples (n=72) taken at various timepoints before and during treatment (Week 0 (W0), Week 3 (W3), Week 6 (W6)). PBMC samples were pooled together into 37 pools, loading 2 or three samples per lane in the 10X Genomics chip, in equal proportions, according to a pre-designed pooling matrix.

  Dataset EGAD00001011345

• Epigenetic Profiling of Human Colorectal Cancer

  DNA methylation, together with chromatin modifications, constitute the epigenome that functions to regulate gene expression and genome integrity. DNA methylation alterations are ubiquitous in human cancers, as many genes acquire DNA methylation in a cancer-specific manner. DNA methylation at these sites in the genome of cancer cells not only serves as a marker for tumor identification, but together with gene mutation and gene expression data, can also be used to describe subsets of tumors of the same organ source. We have previously shown distinct human colorectal cancer subtypes based on DNA methylation differences. Correlating these DNA methylation differences with clinical co-variates will serve to further understand how these distinct subtypes are generated. We have collected 100 colorectal tumor tissues (for which clinical information is known) and have obtained (unprotected) genome-wide DNA methylation and chromatin modification information for each sample for the purposes of identifying and classifying unique tumor subtypes of colorectal cancers. In addition, we have determined mutations of key genes relevant to colorectal cancer as well as gene expression profiles. We will use the clinical data for each de-identified sample to correlate with the DNA methylation, mutation and gene expression information so as to understand the driving forces behind these distinct colorectal subtypes. We have selected the most promising tumors for whole-genome bisulfite sequencing using next-generation sequencing technology to obtain complete maps of colon cancer methylomes. Researchers will be unable to identify the subjects because the samples and associated information have been de-identified and anonymized by the tissue source site. In addition, upon receipt by the USC Epigenome Center, we have assigned new random identifiers for each sample. The data generated using these new codes are not traceable to the patient identity.

  Study phs000385

• Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response

  The study 'Bladder Cancer Organoids as a Functional System to Model Different Disease Stages and Therapy Response' reports the genomic characterization at the single allele level upon Whole Exome Sequencing of Bladder Cancer (BLCa) Patient Tumor (PT) samples obtained from 18 patients and corresponding Patient Derived Organoids (PDOs), implementing the SPICE pipeline (Ciani Y et al). Our cohort included 21 PTs and 22 PDOs. In this study, we generated a unique biobank resource of BLCa organoids that encompasses a broad spectrum of disease stages. We demonstrated that PDOs retain cancer heterogeneity and mutational burden. Furthermore, we observed that BLCa PDO can have different morphologies which may reflect tumor-specific features. Indeed, a solid morphology may be associated with more advanced tumors, as supported by the high PDO genomic burden and high primary tumor stage. Moreover, with our drug screening pipeline, we demonstrated the clinical relevance and feasibility of using a BLCa PDO-based drug assay for comparing the standard of care (SOC) drugs with compounds not currently in use for BLCa. Response to SOC was highly heterogeneous with approximately 50% of non-muscle invasive bladder cancer and 33% of muscle invasive bladder cancer PDOs showing no or minimal response. The most effective targeted therapy was lapatinib. We used an integrative analysis of drug response profiles with matched PDO genomic analysis to determine enrichment thresholds for candidate markers of therapy resistance and sensitivity. Importantly, by assessing the clinical history of longitudinally sampled cases, the clonal evolution of the disease could be determined and matched with PDO drug response profiles.

  Study phs003149

• Copy numbers in resectable gastric cancer treated with surgery alone

  Purpose: Gastric cancer is a heterogeneous disease requiring stratification to recognize its underlying biology and variable clinical outcome. The Cancer Genome Atlas (TCGA) recognizes four molecular subgroups: Epstein-Barr virus positive (EBV+) and microsatellite instable (MSI) with superior survival compared to genomically stable (GS) and chromosomal instable (CIN). Since classification criteria to distinguish GS from CIN were not defined, alternative markers such as Lauren’s histopathology or CDH1/p53 immunohistochemistry are commonly applied. Here we compared survival of gastric cancer subgroups determined by four methods. Experimental Design: EBV- and microsatellite stable tumors from a total of 309 patients treated with surgery alone were assigned to subgroups by: (i) specific copy number aberrations as determined by TCGA (GS or CIN), (ii) genome instability index (GII; high or low), (iii) Lauren’s classification (diffuse or intestinal), and (iv) CDH1/p53 immunohistochemistry (IHC; aberrant CDH1, normal-, or aberrant p53 expression). Subgroups were associated with cancer-related survival (CRS). Results: Five-year CRS was 42.0% for diffuse and 49.5% for intestinal type tumors, and 57.8% for GS and 41.6% for CIN tumors. Classification by GII or CDH1/p53 IHC did not correlate with CRS. The combination of TCGA and Lauren classifications resulted in four distinct subgroups. Five-year CRS for GS-intestinal (n=24), GS-diffuse (n=57), CIN-intestinal (n=142) and CIN-diffuse (n=86) was 61.4%, 56.5%, 47.6%, and 31.5%, respectively. Conclusions: TCGA’s GS and CIN have additional prognostic value to Lauren’s diffuse and intestinal subgroups in gastric cancer. GS-intestinal, GS-diffuse, CIN-intestinal and CIN-diffuse constitute biologically distinct entities and are suggested as stratification variables for future studies.

  Study EGAS00001007394

• Genetic immune escape landscape in primary and metastatic cancer

  Immune surveillance escape is a hallmark of tumorigenesis1. Multiple studies have characterized the immune escape landscape across several untreated early-stage primary cancer types2–4. However, whether late-stage treated metastatic tumors present differences in genetic immune escape (GIE) prevalence and dynamics remains unclear. Here, we performed a pan-cancer characterization of GIE prevalence across six immune escape pathways in 6,457 uniformly processed Whole Genome Sequencing (WGS) tumor samples including 58 cancer types from 1,943 primary untreated patients and 4,514 metastatic patients. To effectively address the complexity of the Human Leukocyte Antigen (HLA-I) locus and to characterize its tumor status, we developed LILAC, an open-source integrative framework. We demonstrate that one in four tumors harbor GIE alterations, with high mechanistic and frequency variability across cancer types. GIE prevalence is highly consistent between primary and metastatic tumors for most cancer types with few exceptions such as prostate and thyroid carcinomas that have increased immune evasion frequencies in metastatic tumors. Positive selection analysis revealed that GIE alterations are frequently selected for in tumor evolution and that focal LOH of HLA-I, unlike non-focal LOH of HLA-I, tends to lose the HLA allele that presents the largest neoepitope repertoire. We also unraveled tumor genomic features contributing to immune escape incidence, including DNA repair deficiency, APOBEC activity, tobacco associated mutation load and viral DNA integration. Finally, there is a strong tendency for mid and high tumor mutation burden (TMB) tumors to preferentially select LOH of HLA-I for GIE whereas hypermutated samples favor global immune evasion strategies. Our results indicate that genetic immune escape is generally a pre-metastatic event during tumor evolution and that tumors adapt different strategies depending on their neoepitope burden.

  Study EGAS00001006123

• Analysis of T-cell receptor clonotypes in tumor micro-environment identifies shared cancer type-specific signatures

  Despite the conventional view that a truly random V(D)J recombination process should generate a highly diverse immune repertoire, emerging reports suggest that there is a certain bias towards the generation of shared/public immune receptor chains. These studies were performed in viral diseases where public T-cell receptors (TCR) appear to confer better protective responses. Selective pressures generating common TCR clonotypes are currently not well understood but it is believed that they confer a growth advantage. As very little is known about public TCR clonotypes in cancer, here we set out to determine the extent of shared TCR clonotypes in the intra-tumor microenvironments of virus- and non-virus- driven head and neck cancers using TCR sequencing. We report that tumor-infiltrating T-cell clonotypes were indeed shared across individuals with the same cancer type, where the majority of shared sequences were specific to the cancer type (ie viral versus non-viral). These shared clonotypes were not particularly enriched in EBV-associated nasopharynx cancer, but in both cancers, exhibited distinct characteristics, namely shorter CDR3 lengths, restricted V- and J-gene usages and also demonstrated convergent V(D)J recombination. Many of these shared TCRs were expressed in patients with a shared HLA background. Pattern recognition of CDR3 amino acid sequences revealed strong convergence to specific motifs that were unique to each cancer type, suggesting they may be enriched for specificity to common antigens found in the tumor microenvironment. The identification of shared TCRs in infiltrating tumor T-cells not only adds to our understanding of the tumor adaptive immune recognition but could also serve as disease-specific biomarkers and guide the development of future immunotherapies.

  Study EGAS00001005480

• The clinical utility of genomics in childhood cancer extends beyond targetable mutations

  Survival of children with relapsed cancer remains unacceptably low. Cancer genomic profiling may identify new therapeutic options, enhance diagnostic accuracy, and improve understanding of tumors’ origins and continued evolution. We deeply sequenced 864 cancer-associated genes and the complete genomes and transcriptomes for 300 pediatric and adolescent/young adult (AYA) patients with poor prognosis or rare tumors. Using integrative somatic-germline analyses, we assessed the clinical utility of cancer genomics in this population. We analyzed tumor mutational signatures and burden to interrogate the relevance of germline variants in DNA repair genes and the impact of therapeutic exposures on tumor evolution. We also evaluated the frequency of changes to tumor drivers and therapeutic targets at relapse in those with serial samples. Integrative analysis yielded clinically actionable variants in a majority of patients. Improved diagnostic accuracy led to modified management in a subset. Therapeutically targetable variants were of unanticipated timing and type, with many of these derived from the germline. Enrichment in corroborating mutational signature 3 (‘BRCAness’) in patients with germline homologous recombination defects suggests they are drivers of pediatric cancers and potential targets for PARP inhibition. We show that mutation burden, which may in part be driven by prior therapeutic exposures, was significantly elevated in a minority of patients. Over one-third of patients with sequential samples analyzed showed a change in therapeutically-targetable drivers. Comprehensive somatic-germline cancer genomic profiling is useful at multiple points in the care trajectory for pediatric/AYA patients, supporting its integration into early clinical management. Re-biopsy at the time of relapse should be considered, and specific attention to mutational burden is indicated. Defective DNA repair genes in the germline may represent important targetable drivers.

  Study EGAS00001006034

• Identification_of_synthetic_lethal_genes_by_CRISPR_Cas9_library

  Sequencing is performed on PCR products from the amplification of gRNA segments introduced into cell lines (some are commercial, some are derived by collaborators, as described in HMDMC 13/076). Cellular DNA or RNA are not sequenced. This data is defined as "Other Biological/Biochemical Assay Data" under the WTSI datasharing guidelines and consequently will be released at the time of publication and/or through faculty websites. SEQUENCING DETAILS: in October 2016 3 DNA samples will be submitted for PCR amplification and purification through CGP pipeline using Thompson's custom primer set and PCR settings and sequencing with Hiseq using a custom protocol (with 3 forward reads to read sgRNA1, sgRNA2 and the index, optimized with Illumina Bespoke Sanger team); read length 50bp. The following set of samples will be submitted in later 2016 and ealry 2017 as cell pellet to be processed through CGP Cas9 pipeline (Thompson's oligos and protocols) and sequences on Hiseq (same custom sequencing protocol described above) We are utilizing a custom CRISPR/Cas9 library to identify synthetic lethal gene pairs. Cells will be transduced with LV expressing Cas9, then infected with LV expressign the library of 42'000 sgRNA pairs. Cell pellet will be collected from the cell population at different timepoints. The samples will be processed by CGP pipeline customized for the specific protocol and then sequenced to identify the 19bp of the sgRNA and quantify their representation.

  Study EGAS00001002117

• A Multiethnic Genome-wide Scan of Prostate Cancer

  Multiple GWA studies of prostate cancer conducted in European White populations are ongoing. These studies will continue to have a dramatic impact on our understanding of the contribution of common genetic variation on inter-individual susceptibility to this common cancer. Important questions that will remain unanswered, however, are whether all common risk alleles for prostate cancer will be revealed in studies limited to populations of European ancestry. A comprehensive examination of common genetic variation in men of Japanese, Latino, and African ancestry will be required to understand population differences in disease risk and to reveal the full spectrum of causal alleles that exist in these populations. Further, genetic and environmental diversity is likely to contribute to ethnic heterogeneity of genetic effects. Elucidating gene x gene and gene x environment interactions is also likely to provide knowledge that may be critical for understanding the contribution of genetic susceptibility to racial/ethnic disparities in prostate cancer incidence and for translating the findings from GWA studies into interventions. In this study we plan to undertake a genome-wide association study (GWAS) of prostate cancer in the Multiethnic Cohort (MEC) Study. We propose the following hypotheses: (a) that inherited DNA variation influences risk of prostate cancer; (b) that many of the causal alleles will be outside known "candidate genes" requiring an agnostic, comprehensive search; and (c) that performing this search in a multi-ethnic cohort is more powerful than a study limited to a single population to reveal the full range of causal alleles relevant to the U.S. population. The version 1 release of this dataset will include genotype data for the Japanese and Latino populations in the study. The version 2 release will include data for the African ancestry population along with the Japanese and Latino subjects. The version 3 release will include fully-cleaned genotype data for all three populations. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to prostate cancer through large-scale genome-wide association studies of a well-characterized multi-ethnic cohort. Genotyping was performed at the Broad Institute of MIT and Harvard, a GENEVA genotyping center and at the University of Southern California. Data cleaning and harmonization were performed at the GEI-funded GENEVA Coordinating Center at the University of Washington. As an add-on to this GWAS we performed a targeted re-sequencing of all known prostate cancer risk loci in the samples from the MEC. Sequencing was performed in Dr. Reich's lab at Harvard Medical School.

  Study phs000306

• National Cancer Institute (NCI) TARGET: Therapeutically Applicable Research to Generate Effective Treatments

  The Therapeutically Applicable Research to Generate Effective Treatments (TARGET) Initiative seeks to accelerate research in novel marker and drug development, along with understanding the molecular basis of pediatric malignancy, through identification of genomic changes associated with the following childhood cancers: Acute Lymphoblastic Leukemia (ALL) - A fast-growing type of blood cancer in which too many immature white blood cells are found in the blood and bone marrow. Acute Myeloid Leukemia (AML), including AML Induction Failure cases (AML-IF) - Another type of blood cancer marked by too many myeloblasts, an alternate type of immature white blood cell, are found in the blood and bone marrow. Upon diagnosis, AML patients without high-risk genetic markers undergo standard chemotherapy regimen, called the primary induction phase, to eliminate most cancer cells and induce a remission state. Clear Cell Sarcoma of the Kidney (CCSK) - A rare type of kidney cancer, in which the inside of the cells looks clear when viewed under a microscope. Clear cell sarcoma can spread from the kidney to other organs, most commonly the bone, but also including the lungs, brain, and soft tissues of the body. Neuroblastoma (NBL) - Cancer of cells of the sympathetic nervous system. Cancer Model Systems (MDLS), including PPTP - MDLS includes acute leukemia cell lines and xenografts with matched primary and/or relapsed tumor information, NBL cell lines and xenografts with matched controls, kidney tumor cell lines, normal brain tissues, and embryonic stem cell lines that were sequenced for some TARGET disease projects. Osteosarcoma (OS) - A cancer of the bone that primarily affects children and adolescents. Rhabdoid Tumor (RT) - A rare, fast-growing cancer that usually forms in the kidney or central nervous system (the brain and spinal cord) but can also form in soft tissues in other areas of the body. Rhabdoid tumors tend to spread quickly, are hard to treat, and have a poor prognosis. Wilms' Tumor (WT) - A cancer of cells in the kidney that can spread to the liver, lung and lymph nodes. More information can be found about each TARGET subproject by following the links on the top of this page. Together these cancers account for the majority of the more than 10,000 childhood cancer cases diagnosed in the United States each year. TARGET has employed a set of advanced and complementary genome analysis technologies, including large scale 2nd and 3rd generation genome sequencing, to strategically characterize alterations in both gene expression and in genomic structure (such as deletions and amplification) that are involved in childhood cancers. The goal of this coordinated effort has been to create a comprehensive genomic and transcriptomic profile of each cancer. Integrated analysis of the TARGET data has identified those genes that are either altered in their expression level or mapped to the chromosome regions of deletion/amplification/translocation, as these genes represent strong candidates for therapeutic targeting. To learn more about the TARGET project, which is now completed, visit the website at https://www.cancer.gov/ccg/research/genome-sequencing/target. TARGET data is accessible at the NCI's Genomic Data Commons (GDC) via the GDC's Data Portal and from each of the TARGET Publication Pages at the GDC (Please see the "Supplemental Links" section of any TARGET publication's "Publication Information and Associated Data Files page" at the GDC.). Available datasets include raw sequencing data, datasets generated by the original TARGET research teams (fully annotated clinical information and higher-level/analyzed molecular characterization data - gene expression, copy number variation, epigenetics, targeted sequencing), as well as higher level data generated by the GDC. Please see the TARGET Use and Publication Guidelines for updated details on the sharing of any TARGET substudy data, including how to cite TARGET.

  Study phs000218

• Genome Instability in Mammary Cells of Pathogenic BRCA1/2 Mutation Carriers

  It remains unknown if inherited germline mutations in the BRCA1 or BRCA2 gene increase the risk of breast and ovarian cancer by elevating mutation rate in mammary cells. Here we show, using a single-cell whole genome sequencing approach, that mammary luminal epithelial cells isolated from tissues obtained from preventive mastectomy surgeries in women with a pathogenic BRCA1/2 germline mutation, exhibit a statistically significant, increased mutation frequency as compared to age-matched controls without genetic risk of breast cancer.

  Study phs002411

• Fixative optimisation study for BRITROC project

  The British Translational Research Ovarian Cancer Collaborative (BriTROC), spanning more than 10 centres across UK, is a prospective observational project focused on relapsed high-grade serous ovarian cancer (HGSOC). The first study, as a part of the project, is the Fixative optimisation study, which analyses the utility for next-generation sequencing of UMFIX samples compared to NBF-fixed and fresh frozen samples. Various DNA and sequencing quality analyses were performed to compare fixation methods in bulk tumour and biopsy samples.

  Study EGAS00001001433

• Multi-omics analysis of primary glioblastoma cell-lines shows recapitulation of pivotal molecular features of parental tumors

  Glioblastoma (GBM) is the deadliest primary brain cancer in adults. Emerging innovative therapies hold promise for personalized cancer treatment. Improving therapeutic options depends on research relying on relevant preclinical models. In this line we have established in the setting of the GlioTeX project (GBM and experimental therapeutics), a GBM-patient derived cell line library (GBM-PDCL). Multi-OMIC approach was used to determine the molecular landscape of PDCL and the extent to which they represent GBM tumors.

  Study EGAS00001001871

• Cachexia - Non-Cachexia Metagenome Analysis

  Cancer cachexia has been linked to gut bacterial alterations, but alterations of gut viruses, mostly bacteriophages, have not yet been explored. We performed shotgun metagenomic sequencing of DNA from stool samples of 78 cachectic and 42 non-cachectic cancer patients. K-mer-based matching to reference databases revealed abundance variations of bacteria and viruses. Beyond bacterial alterations, cachectic patients exhibited significantly lower bacteriophage abundance, predominantly affecting Caudovirales and Siphoviridae species (double-stranded DNA) but also Inoviridae and Microviridae families (single-stranded DNA).

  Study EGAS00001007156

• Genomewide copy number alteration screening of circulating plasma DNA

  Early cancer diagnosis might improve survival rates. As circulating tumor DNA (ctDNA) carries cancer-specific modifications, it has great potential as a noninvasive biomarker for detection of incipient tumors. We collected cell-free DNA (cfDNA) samples of 1002 elderly without a prior malignancy, carried out whole-genome massive parallel sequencing and scrutinized the mapped sequences for the presence of (sub)chromosomal copy number alterations (CNAs) predictive for a malignancy. When imbalances were detected, 6-monthly clinical follow-up was carried out.

  Study EGAS00001006031

• Whole genome sequencing of primary and metastatic Melanoma cases in an Australian cohort.

  Melanoma is the fourth most common cancer in Australia and the leading cause of cancer death in young adults. The Australian Melanoma Genome Project (AMGP) is analysing whole genomes from melanomas. We include the results of whole genome sequencing (WGS) for a number of datasets that include cutaneous, acral and mucosal melanoma subtypes.

  Study EGAS00001001552

• National Cancer Center Singapore

  Dac EGAC00001001550

• SMC Breast Cancer DAC

  Dac EGAC00001002381

• Breast cancer sequencing data

  Dac EGAC00001003293

• Singapore gastric cancer WGS

  Dac EGAC00001000888

• Radboudumc Cancer Genomics DAC

  Dac EGAC00001001102

• Charbonneau Cancer Institute DAC

  Dac EGAC00001001165

• DAC Barretos Cancer Hospital

  Dac EGAC00001001592

• Spatial Characterization Breast Cancer

  Dac EGAC00001001673

• PBL Cancer Data Committee

  Dac EGAC00001001870

• Charbonneau Cancer Institute DAC

  Dac EGAC00001002096

• Breast cancer bone metastases

  Dac EGAC00001002771

• Breast cancer bone metastases

  Dac EGAC00001002772

• DAC Synergie Lyon Cancer

  Dac EGAC00001002795

• Breast cancer bone metastases

  Dac EGAC00001003035

• DAC - Pediatric Solid Cancer

  Dac EGAC00001003088

• GCP study

  Study EGAS00001004959

• IBD-dysplasia

  Study EGAS00001003767

• Advancing Precision Oncology in a Humanized, Fully Autologous Mouse Model

  Progress in the early detection and treatment of cancer requires accurate model systems to further evaluate new, promising discoveries. Small animal and, in particular, mouse model systems are attractive to researchers for numerous reasons, including their ease of use and well-described platforms. The ability to grow human tumors in immune-deficient mice (so-called patient-derived xenografts, or PDXs) allows researchers to work directly with human cancer tissue in a controlled setting. However, PDX models are limited by their lack of an intact immune system. Immunotherapy has revolutionized clinical oncology, but lacks pre-clinical models of the human immune system and human cancer to investigate new modalities and limitations/toxicities of treatment regimens. The broad objective of this study is to validate an in vivo model to evaluate human tumors in the context of a complete and intact human immune system in a completely personalized and autologous fashion to study cancer immunotherapy. Herein, we will: (1) validate the ability of our humanized system to serve as a model for cancer immunotherapy treatment response and toxicity in patients with melanoma, including immunotherapy checkpoint blockade and vaccine strategies, and (2) extend our current work in melanoma by validating the ability to establish humanized mice and evaluate tumor growth and leukocyte development in autologous human pancreatic and colorectal tumors established in humanized mice. In each of these areas, we will leverage our multi-institutional team's individual expertise along with our institutional infrastructure to maximize the success of the experimental aims. The results from this project will be widely available to the general research community for future, hypothesis-driven research. Taken together, our study will meet multiple goals and address several unmet needs in cancer immunotherapy, thus significantly enhancing the applicability of a fully autologous and immunocompetent precision model system for use in translational oncology research.

  Study phs003090

• Drug-perturbation-based stratification of blood cancer

  As new generations of targeted therapies emerge and tumor genome sequencing discovers increasingly comprehensive mutation repertoires, the functional relationships of mutations to tumor phenotypes remain largely unknown. Here, we measured ex vivo sensitivity of 246 blood cancers to 63 drugs alongside genome, transcriptome, and DNA methylome analysis to understand determinants of drug response. We assembled a primary blood cancer cell encyclopedia data set that revealed disease-specific sensitivities for each cancer. Within chronic lymphocytic leukemia (CLL), responses to 62% of drugs were associated with 2 or more mutations, and linked the B cell receptor (BCR) pathway to trisomy 12, an important driver of CLL. Based on drug responses, the disease could be organized into phenotypic subgroups characterized by exploitable dependencies on BCR, mTOR, or MEK signaling and associated with mutations, gene expression, and DNA methylation. Fourteen percent of CLLs were driven by mTOR signaling in a non–BCR-dependent manner. Multivariate modeling revealed immunoglobulin heavy chain variable gene (IGHV) mutation status and trisomy 12 as the most important modulators of response to kinase inhibitors in CLL. Ex vivo drug responses were associated with outcome. This study overcomes the perception that most mutations do not influence drug response of cancer, and points to an updated approach to understanding tumor biology, with implications for biomarker discovery and cancer care.

  Study EGAS00001001746

• Detection of mutational patterns in cell free DNA (cfDNA) of colorectal cancer by custom amplicon sequencing

  Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell free (cf) DNA offers a non-invasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance. A main challenge for the application of cfDNA as a diagnostic tool is the diverse mutational landscape of cancer. Here, we developed a flexible end-to-end experimental and bioinformatics workflow to analyze mutations in cfDNA using custom amplicon sequencing. Our approach relies on open software tools to select primers suitable for multiplex PCR using minimal cfDNA as input. In addition, we developed a robust linear model to identify specific genetic alterations from sequencing data of cfDNA. We used our method to design a custom amplicon panel suitable for detection of hotspot mutations relevant for colorectal cancer and analyzed mutations in serial cfDNA samples from 34 patients with advanced colorectal cancer. Our data demonstrates that recurrent and patient-specific mutational patterns can be reliably detected for the majority of patients. Furthermore, we show that the allele frequency of mutations in cfDNA correlates well with disease progression. Finally, we demonstrate that monitoring of cfDNA can outperform the predictive power of currently used tumor markers and reveal mechanisms of resistance to anti-EGFR antibody treatment.

  Study EGAS00001003382

• Validation of SNVs found by Exome-seq in S2-SF1, -SF5 and -SF9 hiPSCs

  PCR products were obtained from each target loci using genomic DNA from human iPS cells. Subsequently, PCR products are pooled and subjected to Illumina library preparation. The library will be sequenced either by HiSeq or MiSeq. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001000631

• McGill Sperm Methylome Sequencing Data

  The study includes NGS-based WGBS on one sperm DNA sample pooled from 30 participants, and methylC-capture sequencing (MCC-Seq) on the same pooled sperm sample as well as 45 sperm DNA samples derived from both fertile and infertile individuals in two cohorts (Toronto, a fertile cohort; Montreal, an idiopathic infertility cohort). All the data were generated with 100bp paired-end reads using the Illumina HiSeq2000 or 4000 systems.

  Dataset EGAD00001004978

• Chromatin accessibility analysis of hepatocyte-like cell in vitro differentiation from iPSC in comparison to primary human hepatocytes

  Fastq files of ATAC-seq data of induced pluripotent stem cells (iPSC), definitive endoderm (DE), hepatocyte-like cells (HLC) and primary human hepatocytes (PHH). The dataset comprises data from two different in vitro differentiation protocols: Cellartis (Takara Bio, "CEL", n = 4) and as described by Wang et al. (PMID: 28287600, "HAY", n = 1), as well as from 3 PHH donors.

  Dataset EGAD00001005934

• Next-generation sequencing data derived from patient single cells or clonal colonies

  The following samples were generated from the patient samples used in the study: - Bulk DNA sequencing specifically targeting mutated sites of interest derived from clonal cell populations (288 monoclonal colonies - 2 replicates). - Targeted Muta-seq method (Patient P342: 2208 cells, Patient HRK: 1066 cells, Patient LAK: 618 cells, Patient P101: 1080 cells) - Smart-seq2 method (Patient P342 - 768 individual cells).

  Dataset EGAD00001006228

• Profiling of H3K27ac landscape in five immune cell types from rheumatoid arthritis patients and healthy controls

  We collected peripheral blood mononuclear cells (PBMC) from 6 RA patients and 4 healthy controls, as well as synovial fluid (SF) from the same RA patients. We then sorted B cells, CD4+ and CD8+ T cells, regulatory T cells and monocytes using flow cytometry and profiled regions marked with H3K27ac using CUT&Tag.

  Dataset EGAD00001007003

• McGill EMC Community projects Release 7 for cell line "lung epithelial"

  Complete reference epigenome (as defined by IHEC) of a lung epithelial cell line with non-small Cell Lung Adenocarcinoma

  Dataset EGAD00001007679

• COVID-19 Challenge Project Single Cell Profiling

  Single-cell profiling of sero-negative and sero-positive humans that were inoculated with SARS-CoV-2. The cellular response during SARS-CoV-2 is profiled using single-cell transcriptomics, CITE-seq and single cell immune profiling, by sampling PBMCs and nasal swabs before and at multiple time points during SARS-CoV-2 infection. This one-of-a-kind cellular map will give unique temporal resolution of how nasal and immune cells respond to SARS-CoV-2 exposure and infection.

  Dataset EGAD00001012227

• 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