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• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one TCF3::PBX1 ALL patient (ALLT-335). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002577

• RNA sequencing data of pediatric TCF3::PBX1 acute lymphoblastic leukemia (set 2)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one TCF3::PBX1 ALL patient (ALLT-376). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002578

• RNA sequencing data of pediatric BCR::ABL1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one BCR::ABL1 ALL patient (ALLT-343). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002579

• RNA sequencing data of pediatric KMT2A-rearranged acute lymphoblastic leukemia (set 3)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one KMT2A-r ALL patient (ALLT-375). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002581

• RNA sequencing data of pediatric ETV6::RUNX1 acute lymphoblastic leukemia (set 1)

  The dataset includes RNA sequencing FASTQ files from a relapse sample of one ETV6::RUNX1 ALL patient (ALLT-341). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and Globin-Zero Gold rRNA Removal Kit (Illumina) was utilized for rRNA removal. The relapse sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002588

• RNA sequencing data of pediatric ETV6::RUNX1 acute lymphoblastic leukemia (set 5)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one ETV6::RUNX1 ALL patient (ALLT-380). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002591

• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia (set 3)

  The dataset includes RNA sequencing FASTQ files from diagnostic tumor samples of two B-other ALL patients (ALLT-369, ALLT-378). NEBNext Ultra Directional RNA Library Prep Kit (New England Biolabs) was used in library preparation, and TruSeq Stranded Total RNA Library Prep (Illumina) kit was utilized for rRNA removal. The diagnostic tumor samples were sequenced using Illumina Novaseq 6000, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002600

• ProstOmics: spatial and bulk multi-omics of prostate cancer

  In this ERC-funded ProstOmics project we have used spatial and bulk multi-omics on fresh frozen prostate cancer samples to investigate cancer biology and find for biomarkers to improve patient treatment. All tissue material were collected from prostate cancer patients undergoing radical prostatectomy who had not received any prior cancer-specific treatment.Of the 498 prostate tissue samples (114 patients) included in our project, 176 samples (N=37 patients) have been analyzed with bulk transcriptomics (RNA-seq). Some of these 176 samples were also analyzed with spatial transcriptomics (n=32, N=8, Visium 10x RNA-seq) and DNA methylomics (n=96, N=24, array). All datasets include metadata for histopathological evaluation. Patient metadata include information of age at surgery, time (months) until reported relapse, pre-surgery PSA and post-surgery T-stage.

  Study EGAS50000000413

• Integrative understanding of human immune system by functional genomics and development of intervention strategies for the prevention of autoimmune diseases

  To elucidate the feature of age-associated helper T (ThA) cells and its contribution to autoimmune diseases, single-cell RNA-sequencing analysis of peripheral blood CD4+ T cells from healthy control, CD4+ T cells in muscles and bronchoalveolar lavage fluid (BALF) from patients with idiopathic inflammatory myopathy were conducted.

  Study JGAS000648

• Longitudinal monitoring of cell-free DNA methylation in ALK-positive non-small cell lung cancer patients

  Here, we performed genome-wide 5-mC profiling in plasma of metastatic ALK-rearranged non-small cell lung cancer (NSCLC) patients receiving tyrosine kinase inhibitor therapy. We established a strategy to identify ALK-specific 5-mC changes from cfDNA and demonstrated the suitability of the identified markers for cancer detection, prognosis and therapy monitoring. Longitudinal plasma samples (n = 79) of 21 ALK-positive NSCLC patients and 13 healthy donors were collected alongside 15 ALK-positive tumor tissue and 10 healthy lung tissue specimens. All plasma and tissue samples were analyzed by cell-free DNA methylation immunoprecipitation sequencing to generate genome-wide 5-mC profiles. Information on genomic alterations (i.e., somatic mutations/fusions and copy number alterations) determined in matched plasma samples were available from previous studies.

  Study EGAS00001006573

• Raw bulk TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008118

• Single cell TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008161

• Targeted Sequencing of 173 genes

  Targeted sequencing of 173 genes in 2433 primary breast tumours. Data includes 2433 tumour samples, 523 adjacent normal (breast) samples and 127 blood samples. Libraries were prepared with Illumina's Nextera custom enrichment kit targetting all the exons of the most frequently mutated breast cancer genes. Libraries were multiplexed (48 libraries per lane) and sequenced on Illumina HiSeq 2000 (100bp paired-end reads). Somatic mutations were calling with a custom pipeline. We identified 40 mutation-driver (Mut-driver) genes, and determined associations between mutations, driver CNA profiles, clinical-pathological parameters and survival. We assessed the clonal states of Mut-driver mutations, and estimated levels of intra-tumour heterogeneity using mutant-allele fractions. The results emphasize the importance of genome-based stratification of breast cancer, and have important implications for designing therapeutic strategies. Referece: Pereira et al. (2016) The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes. Nature Communications

  Dataset EGAD00001002115

• Genomic profiling of ovarian adult type granulosa cell tumors

  To investigate the genomic landscape of primary and recurrent ovarian adult type granulosa cell tumors, we first identified an exploratory cohort comprised of cryopreserved surgical biopsies from 24 patients (primary, n = 8; recurrent, n = 16) with 20 having matched normal tissue or peripheral blood samples. We performed whole exome sequencing (WES) on these tumor samples at 200X target coverage (mean 226; range 165-296) and also performed WES on the available normal samples. In addition, we performed cancer gene panel sequencing using the T200.1 hybrid capture platform on FFPE tissue from 55 additional patients (primary, n = 27; recurrent, n = 28), of which we sequenced matched normal tissue for a total of 44.

  Study EGAS00001002833

• Single-cell landscapes of primary glioblastomas and matched organoids and cell lines reveal variable retention of inter- and intra-tumor heterogeneity

  Glioblastomas (GBMs) are aggressive primary malignant brain tumors characterized by extensive levels of inter- and intra-tumor genetic and phenotypic heterogeneity. Patient-derived organoids (PDOs) have recently emerged as useful models to study such heterogeneity. Here, we present bulk exome as well as single-cell genome and transcriptome profiles of primary IDH wild type GBMs from ten patients, including two recurrent tumors, as well as PDOs and brain tumor-initiating cell (BTIC) lines derived from these patients. We find that PDOs are genetically similar to and variably retain gene expression characteristics of their parent tumors. At the phenotypic level, PDOs appear to exhibit similar levels of transcriptional heterogeneity as their parent tumors, whereas BTIC lines tend to be enriched for cells in a more uniform transcriptional state. The datasets introduced here will provide a valuable resource to help guide experiments using GBM-derived organoids, especially in the context of studying cellular heterogeneity.

  Study EGAS00001005227

• Copy-number signatures and mutational processes in ovarian carcinoma

  This study contains the data underlying our approach for copy-number signature identification in high-grade serous ovarian cancer. The samples studied are part of the BriTROC-1 consortium, a national study into relapsed high-grade serous ovarian cancer. The dataset consists of shallow-whole genome sequencing of 300 samples from 143 patients with match tagged-amplicon sequencing of TP53. The study also contains deeper whole-genome sequencing of 48 cases.

  Study EGAS00001002557

• Distinct genomic profile and specific targeted drug responses in adult cerebellar glioblastoma

  Only a few studies have reported the molecular characteristics of adult cerebellar glioblastoma (C-GBM), a subtype comprising 1% of glioblastoma cases located within the infratentorial brain region due to the rarity. By identifying genomic profiles from 19 adult C-GBM samples, we revealed the genetic intertumoral heterogeneity in C-GBM as well as distinct genomic characteristics from those of supratentorial glioblastomas (S-GBMs), emphasizing the need of individualized therapies for C-GBM patients.

  Study EGAS00001002517

• Laser Capture Microscopy (LCM)-RNAseq for Topological Mapping of Synovial Pathology during Rheumatoid Arthritis

  Synovial tissue from the hip or knee was collected from rheumatoid arthritis (RA) and osteoarthritis (OA) patients at the time of joint replacement surgery. Samples were analyzed using laser capture microdissection (LCM) followed by RNA-seq to evaluate the transcriptome in distinct synovial compartments. Results indicated that synovial compartments have both shared and distinct transcriptional signatures that correspond to key pathways relevant to RA pathogenesis.

  Study phs003587

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC -- CA209-009

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Study EGAS00001004290

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC -- CA209-010

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Study EGAS00001004291

• Interplay of somatic alterations and immune infiltration modulates response to PD-1 blockade in advanced clear cell RCC-- CA209-025

  Immune checkpoint inhibitors targeting the PD-1 pathway have transformed the management of many advanced malignancies, including clear cell renal cell carcinoma (ccRCC), but the drivers and resistors of PD-1 response remain incompletely elucidated. Here, we analyzed 592 tumors collected from advanced ccRCC patients enrolled in prospective clinical trials of treatment with PD-1 blockade (or mTOR inhibition as control arm) by whole-exome and RNA-sequencing, integrated with immunofluorescence analysis, to define the somatic alteration landscape of late-stage ccRCC and to uncover the immunogenomic determinants of therapeutic response. While conventional genomic markers (tumor mutation burden, neoantigen load) and degree of CD8+ T cell infiltration were not associated with clinical response, we discovered numerous chromosomal alterations in advanced ccRCC associated with response or resistance to PD-1 blockade. These advanced tumors were highly CD8+ T cell infiltrated, with only 22% and 5% with an immune desert and immune excluded phenotype, respectively. Our analysis revealed that CD8+ infiltrated tumors are depleted of favorable PBRM1 mutations and are enriched for unfavorable chromosomal losses of 9p21.3 when compared to non-infiltrated tumors. These data demonstrate how the interplay of somatic alterations and immunophenotypes impacts therapeutic efficacy.

  Study EGAS00001004292

• Single-Cell Transcriptomic Analysis of Kaposi Sarcoma

  Summary: Single-cell transcriptome analysis of skin and blood samples from individuals with Kaposi's sarcoma Aims: Elucidate the cellular composition and gene expression profiles of Kaposi sarcoma herpesvirus (KSHV) infected cells and non-infected tumor infiltrating cells, and peripheral blood samples from the same individuals, with or without specific therapies, such as antiretroviral therapy for HIV, immunotherapies (such as immune checkpoint inhibitors and immune modulator drugs like pomalidomide), or angiogenesis inhibitory agents. Population: Age 18 and older, both genders, including individuals from North America and other areas of the world (including Africa). Individuals with or without HIV are included. Molecular Technologies: Single-cell RNAseq using 10x Genomics Principal Findings: Two distinct populations of endothelial cells were found infected with KSHV, one CD34+ and one CD34-Both clusters include lytic and latent KSHV gene expressionThe KSHV infected cell clusters differ in expression of housekeeping genes, proliferative markers, ribosomal and secretory vesicle genesBiomarkers of KSHV infected cells were identified, including sodium channel SCN9A Changes in cell composition with therapy are noted Clonal amplification of TCR+ T-cells were noted in the skin and blood Data Available through dbGaP: scRNA-seq data

  Study phs003800

• SNP genotyping of the HLA and T cell receptor regions

  This dataset contains genotype information (vcf files) for genotyped SNPs within or near (within 1 million bases) the HLA and TCR (TRA and TRB) loci of 187 individuals (98 controls and 89 subjects with coeliac disease). SNPs were genotyped using an Axiom Human Genotyping SARS-CoV-2 Research Array (Thermo Fisher) and the data was processed with the Axiom Analysis Suite using the “Best Practices Workflow” pipeline. The genotyped SNPs include 6791 SNPs within/near the HLA region on Chr6, 685 SNPs within/near TRA on Chr14, and 262 SNPs within/near TRB on Chr7 passing quality control. The dataset also contains a metadata file (csv) describing sample phenotypes and providing links to genotype sample names.

  Dataset EGAD50000002728

• banfora_20150706_autosomes

  Genotype data (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 355 individuals from the VAC050 trial performed in Banfora, Burkina Faso - autosomes.

  Dataset EGAD00010002581

• GIS-LUNGTCR1-2016_VAL-BAM

  This dataset contains BAM files of targeted Amplicon deep-sequencing data, for validation of the mutations found in WES. There are 16 patients and 95 samples in total, including 16 controls and 79 tumors.

  Dataset EGAD00001001980