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• exploration of biomarkers discriminating squamous cell carcinoma from other lung cancers

  Targeted therapies based on the molecular and histological features of cancer types are becoming standard practice. The most effective regimen in lung cancers is different between squamous cell carcinoma (SCC) and adenocarcinoma (AD). Therefore a precise diagnosis is crucial, but this has been difficult, particularly for poorly differentiated SCC (PDSCC) and AD without a lepidic growth component (non-lepidic AD). Biomarkers enabling a precise diagnosis are therefore urgently needed. To achieve this goal, we initially performed CAGE (Cap Analysis of Gene Expression) to quantify promoter activities on 97 frozen tissues from surgically resected lung cancers (22 SCC and 75 AD). We furhter expanded the transcriptome profiling to cover additional 48 malignant neoplasm of bronchus and lung, including mesothelioma and metastatic lung cancers derived from other tissues.

  Study JGAS000488

• Adeno-associated virus in the liver: natural history and consequences in tumor development

  Adeno-associated virus (AAV) is a defective mono-stranded DNA virus, endemic in human population (40-80%). AAV infection has long been considered as non-pathogenic1, however few years ago we reported for the first time recurrent clonal AAV2 insertion in the pathogenesis of human hepatocellular carcinoma (HCC) developed on normal liver. These clonal viral insertions target cancer driver genes, including CCNA2, CCNE1, TERT, TNFSF10 and MLL4, leading to their overexpression. The viral inserted sequences involved in almost all the cases the 3’ inverse tandem repeat (ITR) of AAV2, which is important for virus integration in host DNA and exhibits a promoter/enhancer activity. Here, we used RNA sequencing (RNA-seq) to investigate their functional impact on the tissue, such as fusion transcript generation events.

  Study EGAS00001003310

• Multiregional sequencing of IDH-WT glioblastoma reveals high genetic heterogeneity and a dynamic evolutionary history

  Glioblastoma is the most common and aggressive primary brain malignancy in adults. In addi-tion to extensive inter-patient heterogeneity, glioblastoma shows intra-tumor extensive cellular and molecular heterogeneity, both spatially and temporally. This heterogeneity is one of the main reasons for the poor prognosis and overall survival. Moreover, it raises the important question of whether the molecular characterization of a single bioptic sample, as performed in standard di-agnostics, actually represents the entire lesion. In this study, we sequenced the whole-exome of nine spatially different cancer regions of three primary glioblastomas. We characterized their mutational profiles and copy number alterations, with implications for our understanding of tu-mor biology in relation to clonal architecture and evolutionary dynamics, as well as therapeuti-cally relevant alterations.

  Study EGAS00001005128

• Longitudinal_Cambridge_Study_COVID19

  Investigating tissue immune responses to SARSCoV-2 in live and deceased donors This project is part of a longitudinal clinical study that will be run from Cambridge University Medical School (Joseph Cheriyen) studying covid-19 infected patients. The Clatworthy project would use single cell approaches to study severe fatal versus non-fatal in old and old versus young patients and will also provide some information on male versus female. This work will provide single cell resolution insights into immune response to the virus, providing vital information on the biology of covid-19 infection. 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 EGAS00001004488

• A sequence-based genetic dissection of human immune cell types and implications for immune-related disease.

  The immune system is an intricate biological network mediating interactions with other organisms while preserving the integrity of our tissues. By mounting appropriate responses it protects us from a vast range of pathogens while inadvertent immune system attacks on self result in autoimmune diseases. The project aims to discover whether and to what extent the behaviour of the immune system is genetically regulated and to detect the relationships of diverse immune cells with autoimmunity. The project consists of the genetic analysis using up to ~8.2 Million variants, deriving from high density genotyping data and low pass whole genome sequencing, and quantitative levels of 95 cell types encompassing 272 immune traits, in a cohort of 1,629 individuals from four clustered Sardinian villages belonging to the SardiNIA/ProgeNIA study.

  Study EGAS00001000574

• Single cell transcriptomics of human adrenal gland reveal chromosomal alterations in adrenocortical cells

  Adrenocortical cells get replenished throughout our lifetime and as such they are a cellular population of high interest in relation to adrenocortical tumours. Single cell transcriptomics of human adrenal gland were performed to identify rare subpopulations of cells, dynamics of cellular turnover and clone expansions in the adrenal cortex. The adrenal gland of this particular individual is characterized by the presence of mutant clone charecterized by aneuploidy in chromosomes 8, 9, 13 and 22, occupying the zona glomerulosa and zona fasciculata. Differential expression analysis of the mutant cells revealed upregulation of MC2R (adrenocorticotropic hormone receptor), CYP21A2, HSD3B2 genes (enzymes involved in cortisol production). Overall, this donor sample is an example of clonal tissue expansions carrying chromosomal rearrangements that likely impact organ morphology and function but are seemingly benign.

  Study EGAS00001007488

• ICGC PedBrain: Deep-sequencing of childhood brain tumors.

  Brain tumors constitute the childhood tumors with the highest mortality rates and survival is often associated with severe long-term sequelae due to intensive multimodal treatment regimens. Thus, the PedBrainTumor network aims at the identification of robust biomarkers for clinical management and novel molecular targets for therapeutic interventions. Using massively parallel whole-genome sequencing, and transcriptome and methylome sequencing for subsets of cases, we aim to decipher the molecular causes of medulloblastoma as well as low-grade astrocytoma, and to identify markers to stratify patients for specialized treatment. As the PedBrain network is affiliated with clinical trials in medulloblastoma and pilocytic astrocytoma, validation cohorts for the translation of key findings into clinical settings are readily available.

  Study EGAS00001000215

• Genome-wide association analysis on five isolated populations - Erasmus Rucphen Family (ERF) Study

  ERF is embedded in the Genetic Research in Isolated Population (GRIP) program. Genealogy of GRIP is available from its founding (1600-1650). For ERF, we selected 22 related (first and second degree, non-consanguineous) couples living in GRIP between 1850-1900, and having at least six children baptized in the community church. All living descendants of those couples were invited to participate in ERF1. About 4,000 relatives included in the study form a very complex pedigree, which consists of more than 23,000 members. The participants aged between 18-20 years constitute a unique single family spanning over 23 generations. Around 3,000 individuals have been extensively phenotyped for several psychiatric and somatic traits. All phenotyped individuals are genotyped on genome-wide genotyping arrays.

  Study EGAS00001001134

• Genome_Diversity_in_Africa_Project___ancient_samples___standard_libraries

  Given the central importance of Africa to studies of human origins, genetic diversity and disease susceptibility, large-scale and representative characterisation of genetic diversity in Africa is needed. Analyses of ancient DNA from Africa would complement sequencing of modern African populations and provide unique opportunities to transform our understanding of the pre-history of the region. This approach would greatly refine our understanding of population structure and gene flow in Africa and globally, including genetic signatures of ancient admixture. This low coverage sequencing experiment will allow us to test and refine our pipeline for ancient DNA sequencing.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 EGAS00001001182

• Single-cell RNA sequencing of 22 Hodgkin lymphoma tumors and 5 reactive lymph nodes

  Hodgkin lymphoma (HL) is characterized by an extensively dominant tumor microenvironment (TME) composed of different types of non-cancerous immune cells with rare malignant cells. Characterization of the cellular components and their spatial relationship is crucial to understanding crosstalk and therapeutic targeting in the TME. We performed single-cell RNA sequencing of more than 127,000 cells from 22 HL tissue specimens and 5 reactive lymph nodes, profiling for the first time the phenotype of the HL-specific immune microenvironment at single-cell resolution. Library preparation was performed using the 10x Genomics Chromium system, and Illumina sequencing was used to generate 3' gene expression data for every cell. Downstream analysis was performed in R to identify HL-specific microenvironment patterns and identify novel cell populations.

  Study EGAS00001004085

• Microbiota 16S sequencing study in NSCLC patients eligible for surgery without neoadjuvant treatment

  18 non-small cell lung cancer patients eligible for surgery without neaodjuvant treatment were included in the study at Centre Jean Perrin (France). Patients did not take any antibiotics, food supplements or immunostimulants 2 months prior to inclusion. During surgery, patients underwent partial or complete lobectomy where samples of non-malignant lung tissue, peritumoural tissue and tumour were resected from the removed lobe. This was preceeded by the washing of the removed lobe and obtaining the broncho-alveolar lavage fluid. These four sample types were analysed by 16S sequencing in 17 from 18 patients. The study is a part of the project "Characterization of Microbiota (Intestinal, From Lungs, and Upper Airways) in Patients With Non-small Cell Lung Carcinoma: Exploratory Study " which is registered under ref. NCT03068663 (clinicaltrials.gov).

  Study EGAS00001004728

• Persistent Mutation Burden Drives Sustained Anti-Tumor Immune Responses

  Tumor mutation burden is an imperfect proxy of tumor foreignness and has therefore failed to consistently demonstrate clinical utility in predicting responses in the context of immunotherapy. We evaluated mutations in regions of the genome that are unlikely to undergo loss and discovered that clonal mutations in single-copy regions and those present in multiple copies per cell constitute a persistent tumor mutation burden (pTMB) that is linked with therapeutic response to immune checkpoint blockade. Persistent mutations were retained in the context of tumor evolution under selective pressure of immunotherapy and tumors with a high pTMB content were characterized by a more inflamed tumor microenvironment. pTMB imposes an evolutionary bottleneck that cancer cells cannot overcome and may thus drive sustained immunologic tumor control in the context of immunotherapy.

  Study EGAS00001006660

• Single-cell multi-omics of relapse/refractory multiple myeloma patients (Hipo K08K/H067/K43R)

  Therapy resistance in cancers is ingrained in complex clonal dynamics. While the major clonal population in a tumour might respond well to the employed intervention, minor clones will eventually mutate, consequently acquiring a selective advantage and drug resistance. Hence, to improve cancer therapy, it is crucial to understand the mechanisms behind clonal evolution. Here, we applied single-cell transcriptomics and epigenomics, as well as whole-genome sequencing to 15 patients with relapsed/refractory multiple myeloma (RRMM). By profiling longitudinal samples throughout varying treatment regimens, we were able to interrogate patterns of evolution across patients. In particular, by defining clones based on copy number aberrations (CNAs), we found evidence for the majority of clones being diminished but not fully eradicated during treatment.

  Study EGAS00001006538

• EGAD00010000666

  Purified plasma cells from tonsil of Healthy donor

  Dataset EGAD00010000666

• EGAD00010000704

  610k genotyping imputed on Hapmap 3 and 1000G Phase 1 CEU

  Dataset EGAD00010000704

• EGAD00010000827

  Illumina Infinium 450K array data

  Dataset EGAD00010000827

• LIFESTYLE atlas - dietary intervention - methylation data - buccal sample

  Dataset EGAD00010002674

• LIFESTYLE atlas - dietary intervention - methylation data - blood sample

  Dataset EGAD00010002675

• LIFESTYLE atlas - dietary intervention - methylation data - cervical pellet

  Dataset EGAD00010002676

• LIFESTYLE atlas - smoking cessation intervention - methylation data - buccal sample

  Dataset EGAD00010002698

• LIFESTYLE atlas - smoking cessation intervention - methylation data - blood sample

  Dataset EGAD00010002699

• LIFESTYLE atlas - smoking cessation intervention - methylation data - cervical pellet

  Dataset EGAD00010002700

• LP2100100-DNA_C03

  LP2100100-DNA_C03

  Dataset EGAD00001009978

• LP2100030-DNA_A05

  LP2100030-DNA_A05

  Dataset EGAD00001009880

• LP2100082-DNA_G02

  LP2100082-DNA_G02

  Dataset EGAD00001009926

• LP2100030-DNA_A04

  LP2100030-DNA_A04

  Dataset EGAD00001009881

• LP2100082-DNA_G03

  LP2100082-DNA_G03

  Dataset EGAD00001009927

• LP2100082-DNA_H02

  LP2100082-DNA_H02

  Dataset EGAD00001009929

• LP2100098-DNA_C03

  LP2100098-DNA_C03

  Dataset EGAD00001009944

• LP2100098-DNA_C05

  LP2100098-DNA_C05

  Dataset EGAD00001009945

• LP2100098-DNA_D09

  LP2100098-DNA_D09

  Dataset EGAD00001009952

• LP2100098-DNA_E03

  LP2100098-DNA_E03

  Dataset EGAD00001009953

• LP2100098-DNA_E07

  LP2100098-DNA_E07

  Dataset EGAD00001009955

• LP2100098-DNA_F01

  LP2100098-DNA_F01

  Dataset EGAD00001009957

• LP2100082-DNA_F02

  LP2100082-DNA_F02

  Dataset EGAD00001009920

• LP2100030-DNA_A02

  LP2100030-DNA_A02

  Dataset EGAD00001009872

• LP2100098-DNA_C09

  LP2100098-DNA_C09

  Dataset EGAD00001009947

• LP2100098-DNA_D03

  LP2100098-DNA_D03

  Dataset EGAD00001009949

• LP2100082-DNA_A05

  LP2100082-DNA_A05

  Dataset EGAD00001009894

• LP2100100-DNA_G01

  LP2100100-DNA_G01

  Dataset EGAD00001009981

• LP2100100-DNA_G03

  LP2100100-DNA_G03

  Dataset EGAD00001009982

• Lifelines-CH: core phenotypic variables

  Core phenotypic variables

  Dataset EGAD00001010145

• LP2100082-DNA_B02

  LP2100082-DNA_B02

  Dataset EGAD00001009898

• LP2100082-DNA_B03

  LP2100082-DNA_B03

  Dataset EGAD00001009899

• LP2100082-DNA_B04

  LP2100082-DNA_B04

  Dataset EGAD00001009900

• LP2100100-DNA_H03

  LP2100100-DNA_H03

  Dataset EGAD00001009983

• LP2100098-DNA_G01

  LP2100098-DNA_G01

  Dataset EGAD00001009961

• LP2100098-DNA_E09

  LP2100098-DNA_E09

  Dataset EGAD00001009956

• LP2100030-DNA_A07

  LP2100030-DNA_A07

  Dataset EGAD00001009876

• LP2100030-DNA_A03

  LP2100030-DNA_A03

  Dataset EGAD00001009878