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• Neoantigen study samples for prostate cancer

  Whole exome sequencing and RNA sequencing data from 30 patients with prostate cancer.

  Dataset EGAD00001005713

• Hyperpolarized 13C MRI in breast cancer

  Transcriptomics for samples obtained from six patients (MBR01, MBR03, MBR05, MBR07, MBR10, MBR11)

  Dataset EGAD00001005760

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_005A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_005A for Lymph node patient sample RLN_03_5Prime

  Dataset EGAD00001010238

• DLP+ Single Cell Genomic Library 98211

  DLP+ Single Cell Genomic Library 98211 for Diffuse large B-cell lymphoma patient sample TFRIPAIR11_DLBCL

  Dataset EGAD00001010239

• Reference epigenome KNIH004 WGBS data generated from KEP study

  A KNIH004 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002752

• Reference epigenome KNIH002 WGBS data generated from KEP study

  A KNIH002 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002750

• Glioblastoma stem cell lines RNA-seq

  RNA-seq data for three Glioblastoma stem cell (GSC) lines exposed to PRMT5 inhibitor and control samples.

  Dataset EGAD00001006095

• 10x Single Cell Gene Expression Library SCRNA10X_CS_CHIP0198_004A

  10x Single Cell Gene Expression library SCRNA10X_CS_CHIP0198_004A for Lymph node patient sample RLN_02_5Prime

  Dataset EGAD00001010237

• Reference epigenome KNIH009 WGBS data generated from KEP study

  A KNIH009 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for preadipocytes

  Dataset EGAD00001002757

• FPKM expression values of the CUP/reference/validation cohort (H021)

  FPKM expression values of the CUP/reference/validation cohort used for tissue-of-origin prediction based on transcriptomic data

  Dataset EGAD00001008638

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0741_SA609X6

  55 samples; filetype=bam

  Dataset EGAD00001004822

• Single-nucleus RNA-sequencing of meningiomas

  Single-nucleus RNA-sequencing of meningiomas for integrative molecular classification

  Dataset EGAD00001007677

• Raw count matrix for 418 baseline samples

  Count matrix from 418 pre-treatment (Ven-Obi or Clb-Obi) CD19+ B cells

  Dataset EGAD00001009501

• Reference epigenome KNIH006 WGBS data generated from KEP study

  A KNIH006 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for beta cells

  Dataset EGAD00001002754

• Reference epigenome KNIH007 WGBS data generated from KEP study

  A KNIH007 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for adipocytes

  Dataset EGAD00001002755

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0472_SA501X7A

  50 samples; filetype=bam

  Dataset EGAD00001004814

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0582_SA501X10A

  45 samples; filetype=bam

  Dataset EGAD00001004815

• Hi-C of cohesin-mutated and wildtype adult AMLs

  High-throughput chromosome conformation capture (Hi-C) data generated for cohesin-mutated (STAG2 or RAD21) and cohesin-wildtype AMLs.

  Dataset EGAD00001011198

• Sputum metagenome for COPD patients and healthy controls

  This dataset contains the sputum metagenome from 99 COPD patients and 36 healthy individuals in China.

  Dataset EGAD00001009063

• FMI data

  This dataset contains somatic alteration calls summarized at the gene level for 715 patients profiled by FoundationOne (Foundation Medicine).

  Dataset EGAD00001006616

• DLP+ Single Cell Genomic Library A98167

  DLP+ Single Cell Genomic Library A98167 for Diffuse large B-cell lymphoma patient sample TFRIPAIR4_DLBCL

  Dataset EGAD00001010249

• 7 samples RNA-seq raw data

  Dataset comprising raw paired RNA-seq data in fastq.gz format for 7 samples of rosette forming brain tumors

  Dataset EGAD00001009265

• Epiclomal: probabilistic clustering of sparse single-cell DNA methylation data for library px0544_SA532X6

  68 samples; filetype=bam

  Dataset EGAD00001004817

• Reference epigenome KNIH001 WGBS data generated from KEP study

  A KNIH001 Whole-Genome Bisulfite Sequencing(WGBS) paired end data for islet cells

  Dataset EGAD00001002749

• CYP2C19 long-read sequencing

  We have assessed the added value of long-read sequencing for PGx focusing on the clinically important and highly polymorphic CYP2C19 gene within 48 samples.

  Dataset EGAD00001009883

• DLP+ Single Cell Genomic Library A98203

  DLP+ Single Cell Genomic Library A98203 for Diffuse large B-cell lymphoma patient sample TFRIPAIR8_DLBCL

  Dataset EGAD00001010242

• DLP+ Single Cell Genomic Library A98180

  DLP+ Single Cell Genomic Library A98180 for Diffuse large B-cell lymphoma patient sample TFRI_Pair_13_DLBCL

  Dataset EGAD00001010240

• DLP+ Single Cell Genomic Library A98225

  DLP+ Single Cell Genomic Library A98225 for Diffuse large B-cell lymphoma patient sample TFRIPAIR12_DLBCL_rel

  Dataset EGAD00001010246

• KCL PRECSION lpWGS

  KCL lpWGS samples for copy number analysis

  Dataset EGAD00001008380

• Reference epigenome ADMSC02_smRNA-Seq data generated from KEP study

  A ADMSC02_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003868

• Reference epigenome ADMSC03_smRNA-Seq data generated from KEP study

  A ADMSC03_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003869

• Reference epigenome DB31_N_Alpha_smRNA-Seq data generated from KEP study

  A DB31_N_Alpha_smRNA-Seq single end data for alpha cells(PSA-NCAM(-), pancreas)

  Dataset EGAD00001003494

• RNA-Seq Single End

  RNA analysis of six patients 34, 35, 36, 37, 38 and 39 with WGS done on Illumina HiSeq2500. For research purpose and authorised user only.

  Dataset EGAD00001003430

• Reference epigenome DB31_N_Alpha_mRNA-Seq data generated from KEP study

  A DB31_N_Alpha_mRNA-Seq paired end data for alpha cells(PSA-NCAM(-), pancreas)

  Dataset EGAD00001003485

• Reference epigenome ADMSC01_smRNA-Seq data generated from KEP study

  A ADMSC01_smRNA-Seq single end data for adipose-derived mesenchymal stroaml cells

  Dataset EGAD00001003867

• Whole exome sequencing of inflammatory bowel disease cases

  Whole exome sequencing of around 700 inflammatory bowel disease cases.This data can only be used for the identification of IBD/immune-mediated disease loci.

  Dataset EGAD00001001354

• Exome sequencing of relapsed/refractory DLBCL

  This dataset consists of the exome sequencing data for 30 tumour and germline DNA pairs derived from relapsed/refractory DLBCL.

  Dataset EGAD00001003395

• Myeloma Follow up Pilot

  Targeted capture of exonic and intronic regions of interest for the study of genomic alterations in multiple myeloma.

  Dataset EGAD00001000998

• Genome-wide data Iberian Roma

  VCF file with genome-wide data for 62 Iberian Roma samples.

  Dataset EGAD00001006358

• Biomarker data

  Biomarker data for KATHERINE: Biomarker data include RNA-seq time point, Percent of tumor content, PAM50 subtypes, normalized gene expression of ERBB2, CD8 and CD274, normalized immune signature expression.

  Dataset EGAD00001008786

• Colon cancer targeted sequencing study contaning WBCs, primary tumor tissue and plasma samples

  In the setting of localized colon cancer (CC), circulating tumor DNA (ctDNA) monitoring in plasma has shown potential for detecting minimal residual disease (MRD) and predicting higher risk of recurrence. With the tumor-only sequencing approach, however, germline variants may be misidentified as somatic variations, precluding the possibility of tracking in up to 11% of patients due to a lack of known somatic mutations. In this study comprising 148 prospectively recruited localized CC patients, a custom 29-gene panel was utilized to sequence both tumor tissue and matched white blood cells (WBCs) to enhance the accuracy of sequencing results. Performing targeted sequencing of paired tumor tissue and WBCs samples detected additional somatic mutations and increased the number of patients eligible for MRD tracking in plasma, although MRD detection sensitivity was not increased. Furthermore, the germline testing approach revealed the presence of pathogenic germline variants, thereby helping identify patients at elevated risk of hereditary cancer syndromes.

  Study EGAS50000000059

• Integrated Single-Cell Genetic and Transcriptional Analysis Suggests Novel Drivers of Chronic Lymphocytic Leukemia

  Intratumoral genetic heterogeneity has been characterized across cancers by genome sequencing of bulk tumors, including chronic lymphocytic leukemia (CLL). In order to more accurately identify subclones, define phylogenetic relationships, and probe genotype-phenotype relationships, we developed methods for targeted mutation detection in DNA and RNA isolated from thousands of single cells from five CLL samples. By clearly resolving phylogenic relationships, we uncovered mutated LCP1 and WNK1 as novel CLL drivers, supported by functional evidence demonstrating their impact on CLL pathways. Integrative analysis of somatic mutations with transcriptional states prompts the idea that convergent evolution generates phenotypically similar cells in distinct genetic branches, thus creating a cohesive expression profile in each CLL sample despite the presence of genetic heterogeneity. Our study highlights the potential for single-cell RNA-based targeted analysis to sensitively determine transcriptional and mutational profiles of individual cancer cells leading to increased understanding of driving events in malignancy. Reprinted from Genome Research, with permission from Publisher.

  Study phs001372

• The Etiological Bases of Giftedness: Epidemiological Study of Cognitive Ability in Children in Saudi Arabia

  Recent studies of genetic foundations of cognitive ability rely on large samples (hundreds of thousands) of individuals from relatively outbred populations of mostly European ancestry. Hypothesizing that the genetic foundation of cognitive ability depends on the broader population-specific genetic context, we performed a genome-wide association study and homozygosity mapping of cognitive ability estimates obtained through latent variable modeling in a sample of 354 children from the consanguineous population of Saudi Arabia. Approximately half of the sample demonstrated significantly elevated homozygosity levels indicative of inbreeding, and among those with elevated homozygosity, it was negatively associated with cognitive ability. Further homozygosity mapping identified a specific run, inclusive of the GRIA4 gene, that survived corrections for multiple testing for association with cognitive ability. The results suggest that in a consanguineous population, a notable proportion of the variance in cognitive ability in the normal range in children might be regulated by population-specific mechanisms such as patterns of elevated autozygosity.

  Study phs001884

• Direct genetic transformation bypasses tumor-associated DNA methylation alterations

  Tumors represent dynamically evolving populations of mutant cells, and many advances have been made in understanding the biology of their progression. However, key unresolved questions remain about the conditions that support their initial transformation, which cannot be easily captured in patient populations but are instead modeled using transgenic cellular or animal systems. Here, we used extensive patient atlas data to define common features of the tumor DNA methylation landscape as they compare to healthy human cells and used this benchmark to screen 21 engineered human and mouse models for their ability to reproduce these patterns. Notably, we find that genetically induced cellular transformation can trigger global changes in DNA methylation levels that are consistent with extensive proliferation but rarely recapitulate the widespread de novo methylation of Polycomb targets as found in clinical samples. Our results raise pertinent questions about the relationship between genetic and epigenetic aspects of tumorigenesis and provide an important molecular reference for evaluating existing as well as newer tumor models.

  Study EGAS50000000902

• Patient-Derived Lung Cancer Organoid

  Lung cancer shows substantial genetic and phenotypic heterogeneity across individuals, driving a need for personalized medicine. Here we report lung cancer organoids and normal bronchial organoids established from patients tissues comprising five histological subtypes of lung cancer and non-neoplastic bronchial mucosa as in vitro models representing individual patient. The lung cancer organoids recapitulate the tissue architecture of the primary lung tumours and maintain the genomic alterations of the original tumours during long-term expansion in vitro. The normal bronchial organoids maintain cellular components of normal bronchial mucosa. Lung cancer organoids respond to drugs based on their genomic alterations: a BRCA2 mutant organoid to olaparib, an EGFR mutant organoid to erlotinib, and an EGFR mutant/MET amplified organoid to crizotinib. Considering the short length of time from organoid establishment to drug testing, our newly developed model may prove useful for predicting patient-specific drug responses through in vitro patient-specific drug trials.

  Study EGAS00001003786

• Exome sequencing of hepatocellular carcinomas identifies new mutational signatures and potential therapeutic targets

  Genomic analyses promise to improve tumor characterization in order to optimize personalized treatment for patients with hepatocellular carcinoma (HCC). Exome sequencing analysis of 243 liver tumors revealed mutational signatures associated with specific risk factors, mainly combined alcohol/tobacco consumption, aflatoxin B1 and HBV infection. We identified 161 putative driver genes associated with 11 recurrent pathways. Associations of mutations defined 3 groups of genes related to risk factors and centered on CTNNB1 (alcohol), TP53 (HBV) and AXIN1. Analyses according to tumor stage progression revealed TERT promoter mutation as an early event whereas FGF/CCND1 amplification, TP53 and CDKN2A alterations appeared at more advanced stages in aggressive tumors. In 24% of the tumors, we identified genetic alterations potentially targetable by FDA-approved drugs. In conclusion, we identified risk factor–specific mutational signatures and defined the extensive landscape of altered genes and pathways in HCC, which will be useful to design clinical trials for targeted therapy.

  Study EGAS00001001002

• DNA Methylation loss coupled with mitotic cell division promotes immune evasion of tumours with high mutation load

  Mitotic cell division increases tumour mutation burden and copy number load with a positive and inverse correlation, respectively, with the clinical benefit of immunotherapy. Markers of cell division correlate also with genomic demethylation involving methylation loss in late-replicating partial methylation domains. Here we find that immunomodulatory pathway genes are concentrated in these domains and transcriptionally repressed in demethylated tumours with CpG island promoter hypermethylation. Global methylation loss correlated with immune evasion signatures independently of mutation burden and aneuploidy. Methylome data of our cohort (n = 60) and a published cohort (n = 81) in lung cancer and a melanoma cohort (n = 40) consistently demonstrated that genomic methylation alterations counteract the contribution of high mutation burden and increase immunotherapeutic resistance. Higher predictive power was observed for methylation loss than mutation burden. We also found that genomic hypomethylation correlates with the immune escape signatures of aneuploid tumours. Hence, DNA methylation alterations implicate epigenetic modulation as a combination regimens for precision immunotherapy.

  Study EGAS00001003731

• Immune trajectory of response and adverse effect in immunotherapy-treated hepatocellular carcinoma

  Whilst anti-PD1 immune checkpoint blockade (ICB) has revolutionised treatment for many cancers, its response rates in hepatocellular carcinoma (HCC) remain modest, coupled with common incidences of immune-related adverse events (irAEs). To identify biomarkers and decipher the mechanisms for response and irAEs, we performed multi-dimensional immunoprofiling on peripheral blood and tissue collected before and during anti-PD1 ICB treatment from HCC patients. Single-cell analyses enabled us to identify peripheral biomarkers, in particular, CD11c+ antigen-presenting cells with varying degrees of HLA-DR expression and CD8 effector memory (EM) T cells with CXCR3 tissue-homing capability that are associated with both response and irAEs. We also dissected the mechanisms behind how these immune subsets interface between response and toxicity, showing their intersecting yet diverging trajectories leading to these distinct clinical fates. This study offers new insights on the mechanisms and potentially novel strategies to enhance response and ameliorate irAEs in cancer immunotherapy.

  Study EGAS00001004843

• New Brain Tumor Entities Emerge from Molecular Classification of CNS-PNETs

  Primitive neuroectodermal tumors of the central nervous system (CNS-PNETs) are highly aggressive, poorly differentiated embryonal tumors occurring predominantly in young children but also affecting adolescents and adults. Herein we demonstrate that a significant proportion of institutionally diagnosed CNS-PNETs display molecular profiles indistinguishable from those of various other well defined CNS tumor entities, facilitating diagnosis and appropriate therapy for patients with these tumors. From the remaining fraction of CNS-PNETs we identify four new CNS tumor entities, each associated with a recurrent genetic alteration and distinct histopathological and clinical features. These new molecular entities, designated “CNS neuroblastoma with FOXR2 activation (CNS NB-FOXR2)”, “CNS Ewing sarcoma family tumor with CIC alteration (CNS EFT-CIC)”, “CNS high grade neuroepithelial tumor with MN1 alteration (CNS HGNET-MN1)”, and “CNS high grade neuroepithelial tumor with BCOR alteration (CNS HGNET-BCOR)”, will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by poorly differentiated CNS tumors.

  Study EGAS00001001632

• Multimodal Genomic Features Predict Outcome of Immune Checkpoint Blockade in Non-small Cell Lung Cancer

  Despite progress in immunotherapy, identifying patients that respond has remained a challenge. Through analysis of whole-exome and targeted sequence data from 5,449 tumors, we found a significant correlation between tumor mutation burden (TMB) and tumor purity, suggesting that low tumor purity tumors are likely to have inaccurate TMB estimates. We developed a new method to estimate a corrected TMB (cTMB) that was adjusted for tumor purity and more accurately predicted outcome to immune checkpoint blockade (ICB). To identify improved predictive markers together with cTMB, we performed whole-exome sequencing for 104 lung tumors treated with ICB. Through comprehensive analyses of sequence and structural alterations, we discovered a significant enrichment in activating mutations in receptor tyrosine kinase (RTK) genes in non-responding tumors in three immunotherapy-treated cohorts. An integrated multivariable model incorporating cTMB, RTK mutations, smoking-related mutational signature, and HLA status provided an improved predictor of response to immunotherapy that was independently validated.

  Study EGAS00001003892