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• Systematic dissection of tumor-normal single-cell ecosystems across a thousand tumors of 30 cancer types

  The complexity of the tumor microenvironment poses significant challenges in cancer therapy. Here, to comprehensively investigate the tumor-normal ecosystems, we perform an integrative analysis of 4.9 million single-cell transcriptomes from 1,070 tumor and 493 normal samples in combination with pan-cancer 137 spatial transcriptomics, 8,887 TCGA, and 1,261 checkpoint inhibitor-treated bulk tumors. We define a myriad of cell states constituting the tumor-normal ecosystems and also identify hallmark gene signatures across different cell types and organs. Our atlas characterizes distinctions between inflammatory fibroblasts marked by AKR1C1 or WNT5A in terms of cellular interactions and spatial co-localization patterns. Co-occurrence analysis reveals interferon-enriched community states including tertiary lymphoid structure (TLS) components, which exhibit differential rewiring between tumor, adjacent normal, and healthy normal tissues. The favorable response of interferon-enriched community states to immunotherapy is validated using immunotherapy-treated cancers (n=1,261) including our lung cancer cohort (n=497). Deconvolution of spatial transcriptomes discriminates TLS-enriched from non-enriched cell types among immunotherapy-favorable components. Our systematic dissection of tumor-normal ecosystems provides a deeper understanding of inter- and intra-tumoral heterogeneity.

  Study EGAS50000000324

• Clonal evolution in myeloma: the impact of maintenance lenalidomide and depth of response on the genetics and sub-clonal structure of relapsed disease in uniformly treated newly diagnosed patients

  The emergence of treatment resistant sub-clones is a key feature of relapse in multiple myeloma. Therapeutic attempts to extend remission and prevent relapse include the maximisation of response and use of maintenance therapy. We used whole exome sequencing to study the genetics of paired presentation and relapse samples from 56 newly diagnosed patients, following induction therapy, randomised to receive either lenalidomide maintenance or observation as part of the Myeloma XI trial. Patients included were considered high risk, relapsing within 30 months of maintenance randomisation. Patients achieving a complete response had predominantly branching evolutionary patterns leading to relapse, characterised by a greater mutational burden, an altered mutational profile, bi-allelic inactivation of tumour suppressor genes, and acquired structural aberrations. Conversely, in patients achieving a partial response the evolutionary features were predominantly stable with a similar mutational and structural profile. There were no significant differences between patients relapsing after maintenance lenalidomide vs observation. This study shows that the depth of response is a key determinant of the evolutionary patterns seen at relapse.

  Study EGAS00001003539

• Whole genome sequence and RNA-seq data from paired tumour and germline samples from mesothelioma patients.

  Malignant pleural mesothelioma (MPM) has a poor overall survival with few treatment options. Whole genome sequencing (WGS) combined with RNA sequencing (RNA-seq) analysis of the immune features of MPM offers the prospect of identifying changes that could inform future clinical trials. We analysed somatic mutation and RNA-seq data from 229 MPM samples, including 58 MPM samples that had undergone WGS from our own institutions, together with other published data. This combined analysis identified somatic driver genes, including newly identified candidate genes. Whole genome doubling was a frequent event that correlated with shorter survival. Mutational signature analysis revealed dominant signatures and showed that defects in homologous recombination repair were infrequent in our cohort. Within the tumour immune environment we identified high M2 macrophage infiltrate linked with MMP2, MMP14, TGFB1 and CCL2 expression, representing an immunosuppressive environment. A small subset of samples had a higher proportion of CD8 T cells and a high cytolytic score, suggesting a ‘hot’ immune environment which is independent of the somatic mutations. We propose that our findings on genomic changes and subtypes of immune microenvironments may influence therapeutic planning in the future.

  Study EGAS00001005196

• Molecular_risk_stratification_in_patients_with_T1_colorectal_cancer_WES

  The introduction of bowel cancer screening has led to a significant increase in the proportion of patients being diagnosed with asymptomatic, early-stage colorectal cancer (CRC). Although the majority of these patients are successfully treated with surgery alone, a small proportion of patients have ‘born-to-be-bad’ aggressive lesions with early dissemination leading to distant metastases. Current standard of care histological assessment is unable to distinguish between these aggressive versus non-aggressive early lesions which is essential to provide appropriate clinical management decisions. This study aims to carry out molecular and histological profiling of approximately 300 T1 CRCs in order to develop a molecular stratifier based on the risk of relapse in early-invasive CRC. This novel T1 cohort will represent the world’s largest molecularly characterised T1 cohort of samples, with digital pathology assessment alongside whole exome sequencing, copy number variation analysis and 3’ RNA-seq. This data will be used to generate a robust panel of molecular and/or histological markers applicable to formalin-fixed paraffin embedded (FFPE) archival tissue which discriminates between T1 lesions based on risk of relapse, which will ultimately be used to inform clinical management of CRC at the earliest stages of the disease.

  Study EGAS00001005734

• Data Access Commitee for the project : Methylome profiling of human mesenchymal chondrosarcoma

  Dac EGAC00001003217

• Data Access Commitee for single-cell analysis of multiple myeloma and precursors

  Dac EGAC00001002920

• Data Access Committee for the Metastatic Breast Cancer Whole-exome sequencing study

  Dac EGAC00001000434

• DAC for Direct Detection of Early-stage Cancers Using Circulating Tumor DNA

  Dac EGAC00001000701

• Data Access Committee for desmoplastic small round cell tumor (DSRCT) RNAseq data.

  Dac EGAC00001000851

• DAC for Oncogenic fate conversion by PRDM16s causes acute myeloid leukemia

  Dac EGAC00001001023

• EMBL genome biology research group for structural variation (Strand-seq application)

  Dac EGAC00001001091

• DAC for Integrated Genomic, Epigenetic, and Expression Analyses of Ovarian Cancer Cell Lines

  Dac EGAC00001001101

• Stanford Data Access Committee for Multi-Region WES of Metastatic Colorectal Cancer

  Dac EGAC00001001164

• Nicola Murray Centre for Ovarian Cancer Research Data Access Committee

  Dac EGAC00001001588

• Cancer Clinical Research Trust DAC for WES of HER2+ metastatic cancer samples

  Dac EGAC00001001632

• Data Access Commitee of the Princess Maxima Center for Pediatric Oncology

  Dac EGAC00001001948

• Data access committee for Gut microbiome of BA patients and normal controls

  Dac EGAC00001002146

• "DAC for RNAseq from regions of insitu and invasive human mammary ductal disease"

  Dac EGAC00001002538

• DAC for Tuebingen-Stuttgart cohort

  Dac EGAC00001000317

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Jackson Heart Study (JHS)

  Study phs002907

• DAC for Clonal driver neoantigen loss under EGFR TKI and immune selection pressures

  Dac EGAC00001003522

• SGMedical Data Acess Committee

  DAC for SG Medical Inc. of South Korea

  Dac EGAC50000000636

• Quantitative analysis of a novel DNA hypermethylation panel for lung cancer diagnosis

  Study EGAS00001007008

• A multi-center genome-wide association study for nasopharyngeal carcinoma

  Study EGAS00001006062

• bed_files

  Bed files as whitelist for Tapestri Insights analysis

  Dataset EGAD00010002560