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• Dataset for "CutNRun" sequencing of 12 samples of patients with colorectal cancer

  This dataset contains 12 "CutNRun" sequencing samples of patients with colorectal cancer. The sequencing was performed on Illumina NextSeq 550 using Cell Signaling TechnologyDNA Library Prep _Kit for Illumina Systems. The sequencing was always paired.

  Dataset EGAD00001015694

• Dynamic Evolution of Fibroblasts Revealed by Single Cell RNA Sequencing of Human Pancreatic Cancer

  Understanding the constituents of the pancreatic ductal adenocarcinoma (PDAC) microenvironment may illuminate more efficacious targets for treating this aggressive malignancy. However, the compositional changes occurring in untreated and treated PDAC relative to both normal and inflamed pancreas have not been well characterized. To provide a more comprehensive understanding of the PDAC tumor microenvironment relative to the non-cancerous pancreas, we performed single-cell expression profiling (10X Genomics Chromium) on samples of upfront resectable PDAC, FOLFIRINOX-based treated PDAC, chronic pancreatitis, and normal pancreas specimens from 19 patients. Spatial gene expression profiling (10X Genomics Visium) was performed to gain additional insight into cell populations. Our analysis revealed that fibroblasts are central mediators of cell-cell communication in both inflamed and malignant settings and defined unique roles for these cell populations in different disease contexts.

  Study phs003751

• Single-cell RNA sequencing of T-LGLL patients

  Single-cell RNA sequencing was performed on viably frozen cells from 11 T-LGLL samples from 9 T-LGLL patients and 6 age-matched healthy samples. The raw data is available as fastq files.

  Dataset EGAD00001008409

• ICU_transcriptomics__Assessing_the_role_of_the_host_immune_response_in_patients_with_ventilator_associated_pneumonia

  The aim of the proposed project is to provide transcriptomic sequencing data analysis of cells isolated from bronchioalveolar lavage and blood samples from critically ill patients with pneumonia on an intensive care unit in order to investigate the host contribution to disease. The lung microbiome of these patients will be analysed in parallel by deep sequencing and 16S sequencing. These data will provide important information to the development of strategies aimed at improving patient outcomes, reducing the development of antimicrobial resistance and facilitating infection control measures in hospital. Specifically, the proposed work will be a proof of principle study of 100 patients. We will use transcriptomic data to define the host contribution to the symptoms of these critically ill patients diagnosed with pneumonia. The data will be correlated with cytokine/chemokine concentrations, routine microbiology analysis and pathogen genomic data from the same samples to determine the ecology of the lungs of these patients. We will look for associations between clinical features, host response and pathogen genomics in order to identify new diagnostic markers. This study should provide important information to improve the speed and accuracy of diagnosis - resulting in more targeted and successful treatment of critically ill patients in the ICU. 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/

  Study EGAS00001003074

• RNA sequencing of Ewing sarcoma and CIC-DUX4 sarcoma

  RNA sequencing of a collection of 6 Ewing sarcoma and 3 CIC-DUX4 sarcoma tumoroids plus 3 matched patient tumors. Tumoroids were established from digested patient tumor material as 3D culture in Matrigel. After 2-3 month of growth, RNA was isolated from individual tumoroid models using the RNeasy Kit (Qiagen) and used for whole exome sequencing. RNA from corresponding patient tumors was tested in parallel, if available.

  Dataset EGAD50000000557

• Inherited Genetic Variation and Predisposition to Testicular Germ Cell Tumor: UPenn Local TGCT Study

  Testicular germ cell tumors (TGCT) are the most common cancer in men ages 20-40. The incidence of TGCT has more than doubled over the past forty years, without clear etiology. Both genetic effects and environmental exposures, specifically during the pre-natal period, are likely to play an important role in determining TGCT susceptibility. TGCT is known to develop from primordial germ cells (PGCs). We hypothesize that variation in genes that impact upon the differentiation and maturation of PGCs will be important determinants of TGCT susceptibility and based on this hypothesis have selected three important pathways for study, i) male germ cell development, ii) androgen and estrogen biosynthesis and metabolism, and iii) IGF signaling. The proteins involved in early male germ cell development, normally only expressed in PGCs, are markers of and are overexpressed in TGCT. Markers of increased exposure to estrogen (or relatively decreased exposure to androgen) in utero and exogenous estrogen exposures, such as endocrine disruptors, have been associated with TGCT case status in multiple studies. IGF signaling is necessary for testis differentiation and maturation in mice and interacts synergistically with the estrogen signaling pathway. Additionally, we are interested in examining genetic factors predisposing to TGCT in an unbiased fashion, and thus will conduct a Genome Wide Association Study. As well disease susceptiblity, genetics are likely to play a role in disease progression, disease outcomes and response to treatement. We will also assess association of inherited genetics with these outcomes. We will analyze the contribution of genetic variants in these pathways to TGCT risk using a population-based case-control study in the Philadelphia metropolitian area. Our goal is the collection of 550 TGCT cases and 1100 age, race and cell phone use matched controls without a history of TGCT, which will yield 500 and 1000 white cases and controls, respectively, available for final analyses. All cases will be enumerated through the New Jersey and Pennsylvania state cancer registries. We will use a two-tiered approach for case recruitment: hospital clinic-based followed by registry-based. Hospital based cases will be identified within the Univeristy of Pennsylvania Health System and the University of Pennsylvania Cancer Network. All cases identified through this mechanism will be recruited irregardless of diagnosis date. The remaining cases will be identified through the New Jersey and Pennsylvania cancer registries and contacted following their protocols. Controls will be identified through random digit dialing and address based sampling. Both cases and controls will complete a questionnaire addressing known, presumed, and hypothesized risk factors for TGCT and provide a biospecimen. Pathological slides will be reviewed to cases to confirm diagnostic sub-type of TGCT. Haplotypes and functional SNPs will be typed in the genes of interest, as well as throughout the genome. Analyses will be conducted for specific variants, common haplotypes, alone and in conjunction with each other and exposure data after appropriate adjustment for potential confounders. The findings from this study will greatly contribute to our understanding of determinants of TGCT susceptibility.

  Study phs001307

• MAESTRO-Pool Enables Highly Parallel and Specific Mutation-Enrichment Sequencing for Minimal Residual Disease Detection in Cohort Studies

  MAESTRO-Pool builds upon the technology MAESTRO (Minor Allele Enriched Sequencing Through Recognition Oligonucleotides) by pooling tumor-specific MAESTRO probes from multiple patients and applying these to all samples from all patients. In this study, MAESTRO-Pool was applied to a cohort of 9 melanoma patients where 98 plasma samples were screened for 22,333 mutations. Additionally, a new dynamic minimal residual disease (MRD) caller was used to estimate the likelihood of MRD detection based on the number mutations and cell-free DNA molecules interrogated which allowed each bespoke MRD test to be properly calibrated against false detection. These developments led to sensitive detection in patient-matched samples down to 0.78 parts per million (ppm) while limiting false detection in negative controls to 1/784 (tumor fraction=2.7 ppm). MAESTRO-Pool and the dynamic MRD caller enable a unique blend of sensitivity, specificity, and efficiency, which will improve the ability to detect MRD.The data contained in this repository consists of:Tumor and normal whole genome sequencing data used to call patient-specific tumor mutations and design the MRD Tracker and MAESTRO-Pool fingerprintsMAESTRO-Pool data (enriched duplex sequencing via hybrid capture) of tumor gDNA, normal gDNA and cfDNA MRD Tracker data (duplex sequencing via hybrid capture) of tumor gDNA, normal gDNA and cfDNA

  Study phs003447

• Dynamics of tumor ecosystems and microbiome in response to neoadjuvant atezolizumab, bevacizumab, and FOLFOX treatment in patients with unresectable colorectal cancer with liver metastasis

  This study aims to explore the effects of neoadjuvant atezolizumab, bevacizumab, leucovorin, 5-fluorouracil, and oxaliplatin (ABFOLFOX) in patients with unresectable colorectal liver metastases (CRLM), focusing on the molecular dynamics of tumor ecosystems (TE) of CRLM and their impact on treatment outcomes. The study comprises two cohorts with CRLM tissue samples analyzed with RNA sequencing and immunohistochemical staining: cross-sectional cohort A (n = 60, CRLM treated with or without neoadjuvant chemotherapy) and prospective cohort B (n = 20 with serial sampling and treated with ABFOLFOX). Shotgun metagenomic sequencing was done for stool samples from cohort B.

  Study EGAS50000000677

• Somatic mutations predict an aggressive phenotype in meningioma but do not drive grade progression

  A subset of meningiomas progress in histopathological grade and drivers of progression are poorly understood. We aimed to identify somatic mutations and copy number alterations (CNAs) associated with grade progression in a unique matched tumour dataset. Utilising a prospective database, we identified 10 patients with meningiomas that had undergone grade progression and for whom matched pre- and post-progression tissue (n=50 samples) was available for targeted next-generation sequencing. Mutations in NF2 were identified in 4/10 patients, 94% were non-skull base tumours. In one patient, three different NF2 mutations were identified in four tumours. NF2 mutated tumours showed large scale CNAs, with highly recurrent losses in 1p, 10, 22q, and frequent CNAs on chromosomes 2, 3 and 4. There was a correlation between grade and CNAs in a subset of patients. In two patients with sphenoid wing Grade III tumours without detected NF2 mutations, a STAT6-NAB2 inversion was identified. Two patients with tumours without detected NF2 mutations showed a combination of loss and high gain on chromosome 17q. Mutations in SETD2, TP53, TERT promoter and NF2 were not uniform across recurrent tumours and did not correspond with grade progression. Meningiomas that progress in grade generally have a mutational profile already detectable in the pre-progressed tumour, suggesting an aggressive phenotype . CNA profiling shows frequent alterations in NF2 mutated tumours compared to non NF2 mutated tumours and the pattern of CNAs may be associated with grade progression in a subset of cases.

  Study EGAS00001006585

• Brazilian biorepository to support genome-wide association studies of colorectal, breast, and cervical cancer

  This study established a large-scale Brazilian biorepository to support cancer GWAS, replication studies, and polygenic risk score (PRS) evaluation for colorectal, breast, and cervical cancers. 4,062 participants have been enrolled, including cancer cases and cancer-free controls. Genotyping was performed in 2,844 participants using the Axiom 850K PMDA Array. Genetic ancestry inference confirmed Brazil’s highly admixed genetic background, with predominant European, followed by African, Native American, and Asian contributions. This biorepository provides a scalable resource to enable replication of genetic associations, assess the transferability of polygenic risk scores, and advance precision medicine in underrepresented populations.

  Study EGAS00001008408