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• Transcriptome of CD4+ T cells and CD8+ T cells in glioblastoma multiforme

  Patients included in this study were over 18 years of age and had a histology-confirmed diagnosis of glioblastoma multiforme (GBM). Exclusion criteria were the previous administration of any anti-tumor therapy including radiation therapy. All patients gave written informed consent. The study was approved by the local ethics committee (TUM Medical school) and conducted following the Declaration of Helsinki. During resection of the tumors, tumor tissue and tissue from normal appearing brain within the operative channel was collected. Blood was drawn during the surgical procedure. Single cell suspensions were prepared from the tumor tissue, the normal appearing brain, and the blood. CD4+ T cells and CD8+ T cells were sorted by flow cytometry. Only patients with a complete set of specimens (CD4+ tumor infiltrating lymphocytes (TIL), CD8+ TIL, CD4+ T cells from normal appearing brain, CD8+ T cells from normal appearing brain, blood-derived CD4+ and CD8+ T cells) containing a minimum of 1000 cells in each sorted sample were further analyzed (n=9). Total RNA was isolated from sorted cell populations using the RNAeasy Plus micro kit (Qiagen, 74034). Quality and integrity of total RNA was controlled on a Bioanalyzer 2100 (Agilent Technologies). Library preparation for bulk-sequencing of poly(A)-RNA was done as described previously (Parekh et al., 2016). Briefly, barcoded cDNA of each sample was generated with a Maxima RT polymerase (ThermoFisher Scientific, EP0742) using oligo-dT primer containing barcodes, unique molecular identifiers (UMIs) and an adaptor. Ends of the cDNAs were extended by a template switch oligo (TSO) and full-length cDNA was amplified with primers binding to the TSO-site and the adaptor. NEB UltraII FS kit was used to fragment cDNA. After end repair and A-tailing, a TruSeq adapter was ligated and 3'-end-fragments were finally amplified using primers with Illumina P5 and P7 overhangs. In comparison to previous descriptions (Parekh et al., 2016), the P5 and P7 sites were exchanged to allow sequencing of the cDNA in read 1 and barcodes and UMIs in read 2 to achieve a better cluster recognition. The library was sequenced on a NextSeq 500 (Illumina) with 59 cycles for the cDNA in read 1 and 16 cycles for the barcodes and UMIs in read 2. Data were processed using the published Drop-seq pipeline (v1.0) to generate sample- and gene-wise UMI tables (Macosko et al., 2015). Reference genome (GRCh38) was used for alignment. Transcript and gene definitions were used according to the Genecode Annotation Version 35.

  Study EGAS50000000156

• Admixture histories of São Tomé e Príncipe.

  In this study, we aim to reconstruct the complex genetic admixture histories of the population of São Tomé e Príncipe, an archipelago in the Gulf of Guinea that experienced successive waves of forced and deliberate migration from Africa since the 15th century, during and after the Trans-Atlantic Slave Trade.

  Study EGAS50000000920

• Somatic_mutation_and_clonal_evolution_in_the_human_pancreas___WGS

  In this study we aim to characterise the landscape of mutation and clonal selection in the human pancreas. The study combines targeted sequencing and whole-genome sequencing of microbiopsies from the pancreas. The range of patients studied will include healthy individuals, both smokers and non-smokers, and patients with pancreatic ductal adenocarcinoma.

  Study EGAS00001002626

• Acquired Copy Number Alterations in Adult Acute Myeloid Leukemia Genomes

  We performed genome-wide copy number analysis with paired normal and tumor DNA obtained from 86 adult patients with de novo AML using the Affymetrix Genome-Wide Human SNP array 6.0 containing 1.85 million features. Acquired copy number alterations (CNA) were confirmed using an independent, higher resolution, custom array comparative genomic hybridization platform. A total of 201 somatic CNA were found in the 86 AML genomes (mean 2.34 CNA/genome), with FAB M6 and M7 AML genomes containing the most changes (10-29 CNA/genome). Twenty-four percent of AML patients with normal cytogenetics had CNA, while 40% of patients with an abnormal karyotype had additional CNA detected by SNP array, and several regions contained CNA in multiple AML genomes. The mRNA expression levels of 57 genes were significantly altered in 27 of 50 recurrent CNA regions <5 megabases in size. Array data are available online at http://www.ncbi.nlm.nih.gov/geo/ as GEO accession #GSE10358. A total of 8 uniparental disomy (UPD) segments were identified in the 86 genomes and 6/8 UPD regions occurred in samples with a normal karyotype. Collectively, 40% of AML genomes contained alterations not found with cytogenetics, and 96% of these regions contained known or novel AML associated genes. 43/86 AML genomes had no CNA or UPD at this level of resolution. The number of CNA per genome was not associated with overall survival, independent of cytogenetic classification. In this study of 86 adult AML genomes, subcytogenetic CNAs or UPD did not add prognostic information to standard cytogenetics. However, arrays identified many somatically mutated oncogenes and tumor suppressor genes, and also genes not previously implicated in AML that may be relevant for pathogenesis. AML CNA segments from 86 adult AML patients are available through dbVar at ftp://ftp.ncbi.nlm.nih.gov/pub/dbVar/data/Homo_sapiens/nstd11_Walter_et_al_2009.

  Study phs000201

• Whole Exome Sequencing Data

  This dataset includes: whole exome sequencing data for a total of 23 BCP-ALL patients - BAM files

  Dataset EGAD50000001519

• HMO-microbiome study dataset, 16S sequencing

  This dataset contains 16S sequencing of fecal and milk samples for HMO-microbiome Lifelines NEXT study

  Dataset EGAD50000000532

• Data from Shea et al Can Research 2025

  This dataset contains single cell RNA sequencing (192 fastq files for 59 samples), whole exome sequencing (20 BAM files -hg38- for 20 samples) and bulk RNA sequencing (138 paired-end fastq files and 17 single-end fastq files for 8 samples)

  Dataset EGAD50000001334

• Dataset-linking-WGS-via-README-for-EGAS00001004884

  This dataset contains 139 Tumor and Control WGS files for samples for Gerhauser et al.,Cancer Cell, 2018, 34:996-1011. WGS and sequencing protocol was earlier described in Weischenfeldt et al, Cancer Cell, 2013.

  Dataset EGAD00001007669

• Demultiplexed FASTQs for each volunteer

  This submission consists of 15 volunteer FASTQs, split by chemistry: Chemistry v1.1: 7 FASTQ sets, one set for each volunteer (RA1-7) Chemistry v2: 16 FASTQ sets, two for each volunteer (RA8-15; FASTQ set 1: Gene Expression (GEX); FASTQ set 2: TCR enrichment (VDJ))

  Dataset EGAD00001007586

• Molecular determinants of response to PD-L1 blockade across tumor types

  Immune checkpoint inhibitors targeting the PD-1/PD-L1 axis lead to durable clinical responses in subsets of cancer patients across multiple indications, including non-small cell lung cancer (NSCLC), urothelial carcinoma (UC) and renal cell carcinoma (RCC). Herein, we complement PD-L1 immunohistochemistry (IHC) and tumor mutation burden (TMB) with RNA-seq in 366 patients to identify unifying and indication-specific molecular profiles that can predict response to checkpoint blockade across these tumor types. Multiple machine learning approaches failed to identify a baseline transcriptional signature highly predictive of response across these indications. Signatures described previously for immune checkpoint inhibitors also failed to validate. At the pathway level, significant heterogeneity was observed between indications, in particular within the PD-L1+ tumors. mUC and NSCLC were molecularly aligned, with cell cycle and DNA damage repair genes associated with response in PD-L1- tumors. At the gene level, the CDK4/6 inhibitor CDKN2A was identified as a significant transcriptional correlate of response, highlighting the association of non-immune pathways to the outcome of checkpoint blockade. This cross-indication analysis revealed molecular heterogeneity between mUC, NSCLC and RCC tumors, suggesting that indication-specific molecular approaches should be prioritized to formulate treatment strategies.

  Study EGAS00001004343