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• Chemotherapy induces myeloid-driven spatial T-cell exhaustion in ovarian cancer

  Gene expression profiles of single cells from 26 chemo-naïve and IDS tumor tissue and ascites samples from 17 HGSC patients

  Study EGAS50000000607

• dataset1

  Contains 14 control samples and 26 case samples.

  Dataset EGAD00001008576

• BLUEPRINT release August 2015, ChIP-Seq for CD8-positive, alpha-beta T cell, on genome GRCh38

  ChIP-Seq data for 5 CD8-positive, alpha-beta T cell sample(s). 26 run(s), 26 experiment(s), 26 alignment(s) on human genome GRCh38. Part of BLUEPRINT release August 2015. Analysis documentation available at http://ftp.ebi.ac.uk/pub/databases/blueprint/releases/20150820/homo_sapiens/README_chipseq_analysis_ebi_20150820

  Dataset EGAD00001001513

• Genome-wide cell-free DNA mutational integration enables ultra-sensitive cancer monitoring

  In many areas of oncology, we lack sensitive tools to track low burden disease. While cell-free DNA (cfDNA) shows promise in detecting cancer mutations, we found that the combination of low tumor fraction (TF) and limited number of DNA fragments restricts low disease burden monitoring through the prevailing deep targeted sequencing paradigm. We reasoned that breadth may supplant depth of sequencing to overcome the barrier of cfDNA abundance. Whole genome sequencing (WGS) of cfDNA allowed ultra-sensitive detection, capitalizing on the cumulative signal of thousands of somatic mutations observed in solid malignancies, with TF detection sensitivity as low as 10-5. The WGS approach enabled dynamic tumor burden tracking and post-operative residual disease detection, associated with adverse outcome. Thus, we present an orthogonal framework for cfDNA cancer monitoring via genome wide mutational integration, enabling ultra-sensitive detection, overcoming the limitation of cfDNA abundance, and empowering treatment optimization in low-disease burden oncology care

  Study EGAS00001004406

• IMCISION DNAseq

  Standard-of-care (SOC) surgery for locoregionally advanced head and neck squamous cell carcinoma (HNSCC) is intensive and results in 30‒50% five-year overall survival. Anti-PD1 immune checkpoint blockade (ICB) durably improves survival rates in recurrent/metastatic HNSCC. We report on the non-randomized phase Ib/IIa IMCISION trial (NCT03003637) of 32 HNSCC patients treated with two doses neoadjuvant nivolumab (NIVO MONO, n=6, phase Ib arm A) or two doses of nivolumab plus a single dose of ipilimumab (COMBO, n=26, 6 in phase Ib arm B and 20 in phase IIa) prior to surgery and, if indicated, adjuvant radiotherapy. Neoadjuvant ICB was feasible in all phase Ib patients, meeting the phase Ib primary feasibility endpoint. One phase IIa patient had progressive disease precluding surgery. Primary tumor pathological response (phase IIa primary endpoint), defined as the % change in viable tumor cells from baseline biopsy to on-treatment resection, was evaluable in 29 patients. . We observed a major pathological response (MPR, 90‒100% response) in 8/23 (35%) evaluable COMBO and 1/6 (17%) NIVO MONO patients. None of the patients with MPR after NIVO MONO or COMBO developed a tumor relapse after 24.0 months median follow-up. FDG-PET-based total lesion glycolysis identified MPR patients prior to surgery. A baseline AID/APOBEC-associated mutational profile and an on-treatment decrease in hypoxia signature expression were observed in MPR patients. Our data indicate that neoadjuvant NIVO MONO and COMBO are safe in HNSCC, and that particularly COMBO ICB shows encouraging effectivity. IMCISION provides rationales for future HNSCC trials aiming to pre-operatively select patients with a likely MPR after neoadjuvant ICB for de-escalation of SOC.

  Study EGAS00001005466

• DKTK Berlin partner site data access committee

  Dac EGAC00001000573

• DAC for EGA study: "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma"

  This DAC regulates access to the whole-exome sequence data for the study "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma".

  Dac EGAC50000000706

• POT1 splice site mutant analysis

  We are interested in the contribution mutations in the Shelterin complex protein POT1 may have to the development of melanoma. We have identified a patient who carries a splice site mutation in POT1 and as part of our analysis of this gene we aim to sequence the transcriptome of this patient to see how this mutation influences splicing. RNA has been obtained from lymphocytes collected from the patient.

  Dataset EGAD00001000786

• Germline Pan-cancer Lynch syndrome sequencing dataset from India

  The dataset consists of germline whole exome sequencing data generated on the Illumina NovaSeq X Plus platform for 48 patients with MSI-high/ MMRd gastro-intestinal and genito-urinary cancers, in order to detect Lynch syndrome.

  Dataset EGAD50000002088

• The dataset for "ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma”

  The dataset for the study “ctDNA residual disease analyses during perioperative nivolumab or nivolumab plus ipilimumab in resectable diffuse pleural mesothelioma” includes 169 bam files from whole genome sequencing on the Illumina NovaSeq6000 platform. The samples analyzed include tumor (n=28) and normal (n=28) DNA samples, and serial plasma cfDNA (n=113) samples from 28 individuals with resectable diffuse pleural mesothelioma, treated with nivolumab or nivolumab plus ipilimumab on the NCT03918252 trial.

  Dataset EGAD50000001701

• RNA sequencing of pretreatment, on-treatment and posttreatment gastric and gastroesophageal junction tumors treated with neoadjuvant anti-PD-L1 plus chemotherapy

  This set contains a total of 78 files cram files with RNA sequencing data from 20 patients included in the PANDA study treated with 1 cycle of monotherapy atezolizumab and 4 cycles atezolizumab plus chemotherapy (docetaxel, oxaliplatin and capecitabine). RNA was isolated from fresh frozen material and sequenced at 4 timepoints baseline, after monotherapy atezolizumab, after combination atezolizumab plus chemotherapy and at resection (due to 2 missing samples, there is a total of 78 samples).

  Dataset EGAD50000000241

• Ultra-sensitive tumor-informed ctDNA monitoring of treatment response in advanced esophagogastric cancer patients

  To explore whether ultra-sensitive circulating tumor DNA (ctDNA) profiling enables earlier prediction of treatment response and detection of disease progression, we applied NeXT Personal, an ultra-sensitive bespoke tumor-informed liquid biopsy platform, to profile tumor samples from the KeyLargo study, a phase II trial in which metastatic esophagogastric cancer (mEGC) patients received capecitabine, oxaliplatin, and pembrolizumab. A total of 24 patients were evaluated, and all were ctDNA-positive at baseline. ctDNA levels varied from 406,067 down to 1.5 parts per million (PPM) with a median limit of detection of 2.03 PPM. ctDNA dynamics were highly correlated with changes in tumor size (ρ = 0.59, p = 7.3×10-9). Lack of early molecular response (50% or greater decrease in ctDNA levels at first available time point after 30 days, C2D1 or C4D1) was associated with worse overall survival (OS) (HR 6.6, 95% CI 1.8-24.1, p = 0.005) and progression-free survival (PFS) (HR 15.4, 95% CI 2.7-87.0, p = 0.002). Lack of molecular clearance of ctDNA was associated with worse OS (HR 6.9, 95% CI 1.5-30.8, p = 0.012) and PFS (HR 19.2, 95% CI 2.4-152.8, p = 0.005). Molecular progression (ctDNA increase) preceded imaging-derived progression by a median lead time of 65 days. These results suggest that ultra-sensitive liquid biopsy approaches could improve treatment decision-making for mEGC patients receiving chemotherapy and immunotherapy.

  Study EGAS50000001224

• Sequencing files for "Transcriptional Mechanisms of Resistance to Anti-PD-1 Therapy"

  Files from whole exome sequencing of 26 tumors and two matched normals from one melanoma patient. The 26 tumors include the untreated primary, cutaneous metastases and distant metastases to internal organs.

  Dataset EGAD00001003200

• Ultra-deep targeted sequencing for studying the accumulation of somatic mutations in cancer-free human skin

  Study EGAS00001004279

• BAM files of mapped reads from scDNAsequencing

  scDNAseq at low coverage of samples with different levels of ploidy: Low, High, Near and diploid (normal) plus a pool of Healthy HSPCs cells

  Study EGAS50000000019

• DLBCL gene expression

  DLBCL gene expression data using 133.plus.2 Affymetrix array

  Dataset EGAD00010001976

• Ex vivo RNA-seq in moderate COVID-19 monocytes

  This dataset was used to compare gene expression profiles of ex vivo isolated classical CD14+ monocytes from patients with moderate COVID-19 to those of healthy individuals. Blood samples were taken from patients with moderate COVID-19 admitted to hospitals in London (Hammersmith Hospital, Charing Cross Hospital, Saint Mary’s Hospital) 3-14 days after disease onset and 0-2 days after hospitalization and positive PCR, and before study treatment initiation. Moderate patients displayed mild or moderate COVID-19 pneumonia, defined as grade 3 or 4 WHO severity. Samples were collected from March 2020 to February 2021. Healthy donors were Imperial College staff with no prior diagnosis of or recent symptoms consistent with COVID-19, and where possible, were matched in age and sex distribution with COVID-19 patients. None of the participants of this study were COVID-19 vaccinated. Peripheral blood mononuclear cells (PBMCs) were isolated by Ficoll Hypaque (GE Healthcare) gradient centrifugation <4 hours after blood collection. CD14+ monocytes were isolated using a positive selection magnetic sorting kit (StemCell Technologies, UK) from total PBMC and stimulated with vehicle, UV-inactivated SARS-CoV-2 (CoV-2). RNA was isolated using the RNeasy Micro Plus Kit (QIAGEN) following the manufacturer’s guidelines. RNA-sequencing was performed by the Oxford Genomics Centre. PolyA-enriched strand- specific libraries were prepared using NEBNext Ultra II Directional RNA Library Prep Kits (Illumina). All samples were pooled together and 150bp PE reads were sequenced on a Novaseq 6000 system.

  Dataset EGAD00001009800

• Non-coding mutations reveal cancer driver cistromes in luminal breast cancer

  A dataset of ER+PR+ breast tumor samples that were analyzed in order to identify mutation enrichment in cis-regulatory elements and cistrome. The repository includes sequencing data from 88 patients. 26/88 were sequenced using ATAC-seq

  Dataset EGAD00001007650

• Characterization of Clonal Evolution in Microsatellite Unstable Metastatic Cancers through Multi-Regional Tumor Sequencing

  Whole exome sequencing was performed on blood and multiple tumor samples from six patients with known microsatellite unstable tumors. Subclones within each tumor site were identified and within each subclone, differing microsatellite instability was characterized.

  Study phs001925

• Whole genomes sequencing BAM files (blood and lung brushings) of COPD cases and controls (EvA)

  Dataset of 27 whole genome sequencing files (BAM), which cover 12 individuals out of which four suffer from COPD. From 9 individuals, there are sequencing data from blood and from lung brushings at one single site available, from another 3 there is additionally a lung brushing sequencing file from a second site available. Comparison of blood with lung brushings allows the calling of somatic mutations within a tissue.

  Dataset EGAD00001004535

• Whole Exome Sequencing of a Melanoma Patient with Acquired Resistance to MEK plus CDK4/6 Inhibition

  Longitudinal biopsies from a melanoma patient who initially responded to MEK plus CDK4/6 inhibitor therapy were whole exome sequenced to identify potential resistance mutations. The biopsies included normal tissue, pre-treatment, on-treatment, and several post-resistance timepoints.

  Dataset EGAD00001003989

• Ultra-deep sequencing of cell-free DNA derived from reference materials and a patient with asymmetric overgrowth

  This dataset contains: Ultra-deep sequencing data using the Duplex sequencing technology of: 1.) SeraSeq cfDNA reference materials with spike-in variants with allele frequencies from 0% to 5% 2.) One cfDNA sample from a CRC patient 3.) One cfDNA sample from a patient with asymmetric overgrowth Paired-end sequencing was performed with 2x151 bp reads on the NextSeq 500 system. Data is provided as mapped .bam files (aligned to GRCh38/hg38).

  Dataset EGAD00001009784

• Sequencing data for Clinical Trial

  This study is a tri-institutional Phase 1/randomized Phase 2 trial, bevacizumab-naïve rHGA patients were randomized to either LITT (laser interstitial thermal therapy) plus pembrolizumab (LITT+PEM) or non-LITT surgery plus pembrolizumab (NLS+PEM). Randomization ceased after 21 patients when emerging data showed limited adjuvant ICI (immune checkpoint inhibitors) benefit, and the next 24 patients all received LITT+PEM. The goal of the trial is to use LITT, a minimally invasive cytoreductive approach, to prime these “cold” tumors for enhanced ICI response. rHGA= high-grade astrocytoma

  Study EGAS50000001144

• Multi-omics datasets (WES, RNA-seq) of mesothelioma MIST2 study, a phase II CDK4/6 (abemaciclib) clinical trial

  This study comprises 26 mesothelioma patients with whole exome and RNA sequencing, to to assess potential sensitivity to CDK4/6 inhibition in p16ink4A-negative mesothelioma.

  Study EGAS50000001823

• Long-read data (PacBio)

  The goal of this project was to perform long-read RNA sequencing (LR-seq, PacBio) in combination with short-read RNA-seq for systematic characterization of the isoform diversity in primary breast tumor samples. We sequenced the full-length transcriptomes of 26 breast tumors and 4 normal breast samples.

  Dataset EGAD00001006597

• Drug Perturbation of Primary Lymphoma Patient Samples and RNA Sequencing

  This submission contains 3'-end-based shallow-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule drugs (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). The samples were sequenced after 48 hours. The total data set consists of 1476 RNA sequencing samples from 6 batches (pilot, batch 1, batch 1 replicate, batch 2, batch 3, batch 4).

  Study EGAS50000001500

• Lymphoma_primary_patient_drug_perturbed_RNASeq_samples

  3'-end low-depth RNA sequencing data from 108 patients with chronic lymphocytic leukemia and 8 patients with lymphoma. Each primary patient sample was treated in vitro with DMSO as a control and with up to ten small-molecule inhibitors (ibrutinib, duvelisib, everolimus, trametinib, nutlin-3a, I-BET-762, MK2206, selinexor, compound 26, and a combination of ibrutinib and compound 26). Sequencing was performed on the Illumina HiSeq4000. The dataset contains FASTQ files.

  Dac EGAC50000000578

• DAC monitoring the usage of ultra-low-coverage MinION nanopore sequencing results of NA12877 and NA12878 from NIGMS Human Genetic Cell Repository.

  Dac EGAC00001000876

• scMultiome (snRNA + snATAC) data of 26 regionally sampled GBM tissue from 6 patients

  This dataset contains snRNA-seq data of 26 regionally sampled GBM tissue (peritumoral region, tumor edge, and tumor core). Regionally sampled GBM patient tissue was dissociated and nuclei were processed unsorted or by sorting with 7AAD to remove debris and dead cells. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit. Single-nuclei suspension was prepared following the nuclei isolation protocol Single Cell Multiome ATAC + Gene Expression Sequencing protocol using Chromium Nuclei Isolation Kit, nuclei were barcoded and RNA and ATAC libraries were constructed, allowing for simultaneous capture of transcriptome and epigenome from the same cells.

  Dataset EGAD50000001838

• GTestimate: Improving relative gene expression estimation in scRNA-seq using the Good-Turing estimator

  This study introduces a novel scRNA-seq normalization method, which takes unobserved genes into account. To validate GTestimate we designed a cell targeted amplification strategy, enabling us to sequence a small set of cells twice, once at a "typical" sequencing depth and once at a "ultra-deep" sequencing depth.

  Study EGAS50000000915

• Multiple paralogues and recombination mechanisms contribute to the high incidence of 22q11.2 Deletion Syndrome

  To enable haplotype-specific assembly and rearrangement mapping in LCR22 clusters, we combined fiber-FISH optical mapping with whole genome (ultra-)long read sequencing or rearrangement-specific long-range PCR on 254 duos families (22q11.2DS patient and parent-of-origin) comprising several different LCR22-mediated rearrangements.

  Study EGAS50000000601

• Duplex sequencing of selected breast cancer patients

  This study assessed the variant profiles of 22 samples from 11 breast cancer patients with adverse survival outcomes, including paired uninvolved mammary gland samples collected at various distances from primary lesions. Ultra-deep sequencing was performed to identify the presence of low-frequency pathogenic post-zygotic variants in PIK3CA and TP53 genes.

  Study EGAS50000000538

• WGS data of paediatric hyperdiploid B cell acute lymphoblastic leukemia (set4)

  The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of one hyperdiploid ALL patient (ALLK-134). Sequencing libraries were made using Novogene NGS DNA Library Prep Set (Cat No. PT004). Both diagnostic (90x) and remission (30x) samples were sequenced using Illumina NovaSeq X Plus.

  Dataset EGAD50000002429

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set6)

  The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of one B-other ALL patients (ALLK-138). Sequencing library was made using Novogene NGS DNA Library Prep Set. Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

  Dataset EGAD50000002161

• Comprehensive benchmarking of methods for mutation calling in circulating tumor DNA

  This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

  Study EGAS50000001313

• 463 newly diagnosed patients with Multiple Myeloma underwent whole exome sequencing of tumour and peripheral blood DNA.

  463 newly diagnosed patients from the UK Myeloma XI clinical trial (NCT01554852) underwent whole exome sequencing plus targeted capture of the IGH/K/L and MYC loci. 200 ng of DNA were processed using NEBNext DNA library prepartion kit and hybridised to the SureSelect Human All Exon V5 Plus. Four samples were pooled and run on one lane of a HiSeq 2000 using 76-bp paired end reads. DNA from CD138+ selected bone marrow cells (myeloma tumour) as well as peripheral white blood cells were analysed and somatic mutations detected.

  Study EGAS00001001147

• Exome-sequencing of human B cell lymphoma cell lines

  26 cell lines derived from human Diffuse Large B Cell lymphomas (DLBCL) or Burkit Lymphomas (BL) were subjected to whole exome sequencing. Exome capture was carried out using the SeqCap EZ Exome Library 2.0 kit (Roche/Nimblegen) and 100 bp single-read sequencing was performed on a HiSeq2500 (Illumina). 82% of the coding region was covered at least 30x.

  Dataset EGAD00001002262

• Upcycling and merging data to challenge the dogma and identify new therapeutic targets for Glioblastoma

  Glioblastoma is the most common brain tumour. Characterised by a poor prognosis and its recurrence after multimodal treatments, the search for preventable risk factors has been mainly inconclusive up to date. Recently, the data merge from datasetsdeposited at the EGA allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. Challenges in glioblastoma research As for virtually all cancer types, many efforts have been made to unveil the molecular features responsible of the disease, and several cellular pathways have indeed been identified as being frequently mutated in glioblastoma. Nonetheless, targeted therapies based on identified genes have so far failed to improve outcome, thus survival mostly relies on a standard treatment unchanged since 2005. This is a frustrating situation for both the scientific and medical communities, and above all for the patients, still facing a dreadful path. Some researchers hypothesised that this may be due to the inability to efficiently target cancer stem cells, the originators of the other cell types, thus inducing cancer relapse. In 2019 Charles P. Couturier and colleagues sequenced RNA from single cells of freshly excised glioblastomas of 16 patients, and demonstrated that glioblastoma cells replicate normal brain cell development with a conserved neural cancer cell hierarchy centered around glial progenitor-like cells. In this way, they helped identify the possible target cells to improve efficacy and durability of treatment. Data upcycling at the EGA: the glioblastoma case study Single cell RNA sequencing is generated with a laborious and expensive protocol. The quality of the starting material is crucial (cells sample freshly extracted from the patients) and often several attempts are needed before producing reliable quality sequencing results. Collecting big numbers of patients is also challenging. The sequencing data produced by Kevin Petrecca’s group in Montreal, Canada and deposited at the EGA (EGAS00001004422) was recently upcycled by Lin Wang in San Francisco, California and pooled with their freshly produced ones, and then deposited at the EGA as Dataset EGAS00001004909 The data merge allowed Aaron Diaz’s team to discover that the glioblastoma cells shift toward a mesenchymal phenotype when the tumour is recurring. They profiled 86 primary-recurrent patient-matched paired glioblastoma samples with single-nucleus RNA, among other techniques. These very comprehensive results lead the team to challenge the findings from several other cancer fields where chemotherapy standard chemo-radiation therapy selection pressure at the level of genomic alterations; this is indeed not the case for glioblastoma, where the pressure results in phenotypic transition between cellular states. Several technical controls were made to ensure that the merge of the data was not introducing a bias in the results, and an Inter-table analysis demonstrated nearly equal contribution to overall variance from each of the studies included, indicating that the findings were not due to inter-laboratory technical effect. A novel principal-component analysis showed that the largest contribution to variation in primary glioblastoma neoplastic cells was an axis between MES (mesenchymal) and proneural expression programs. In summary, treating glioblastoma often makes a MES, as commented by Lucy Stead about this remarkable work. Check Aaron Diaz’s team Nature Cancer paper, with strong technical tools, state of the art analysis and data from different sources converging to the same outcomes that made possible a significant step toward a better handling of a frightful cancer. References Couturier, C.P., Ayyadhury, S., Le, P.U. et al. Single-cell RNA-seq reveals that glioblastoma recapitulates a normal neurodevelopmental hierarchy. Nat Commun 11, 3406 (2020). Stead, L.F. Treating glioblastoma often makes a MES. Nat Cancer 3, 1446–1448 (2022). Wang, L., Jung, J., Babikir, H. et al. A single-cell atlas of glioblastoma evolution under therapy reveals cell-intrinsic and cell-extrinsic therapeutic targets. Nat Cancer 3, 1534–1552 (2022). Related links: Kevin Petrecca’s group dataset deposited at the EGA: EGAS00001004422 Lin Wang dataset deposited at the EGA: EGAS00001004909

  Blog upcycling-and-merging-data-to-challenge-glioblastoma

• Genetic analysis of HLA and immune escape genes in Diffuse Large B-cell Lymphoma

  We performed genetic analysis of HLA and immune escape genes in samples from 44 patients sequenced by whole exome sequencing (34 tumor samples, 32 normal samples) and whole genome sequencing (10 tumor samples, 12 normal samples). We also performed HLA targeted sequencing in 26/44 patients (26 tumor samples, 26 normal samples).

  Dataset EGAD00001007565

• RNA sequencing data of pediatric ETV6::RUNX1 acute lymphoblastic leukemia (set 4)

  The dataset includes RNA sequencing FASTQ files from a diagnostic tumor sample of one ETV6::RUNX1 ALL patient (ALLK-132). Novogene's internal method was used in directional library preparation including rRNA removal. The diagnostic tumor sample was sequenced using Illumina Novaseq X Plus, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002590

• InsPIRE islets

  We explored the relationship between genetic variants influencing predisposition to type 2 diabetes (T2D) and related glycemic traits, and human pancreatic islet transcription using RNA-Seq and genotyping data from 420 islet donors and 26 FAC sorted beta-cells.

  Study EGAS00001003997

• Machine learning to detect the SINEs of cancer

  We previously described an approach called RealSeqS to evaluate aneuploidy in plasma cell-free DNA (cfDNA) through the amplification of ~350,000 repeated elements with a single primer. We hypothesized that an unbiased evaluation of the large amount of sequencing data obtained with RealSeqS might reveal other differences between plasma samples from patients with and without cancer. This hypothesis was tested through the development of a novel machine-learning approach called Alu Profile Learning Using Sequencing (A-PLUS) and its application to samples from 5108 individuals, 2037 with cancer and the remainder without cancer. Samples from cancer patients and controls were pre-specified into four cohorts used for: 1) model training, 2) analyte integration and threshold determination, 3) validation, and 4) reproducibility. A-PLUS alone provided a sensitivity of 40.5% across 11 different cancer types in the Validation Cohort, at a specificity of 98.5%. Combining A-PLUS with aneuploidy and 8 common protein biomarkers detected 51% of 1167 cancers at 98.9% specificity. We found that part of the power of A-PLUS could be ascribed to a single feature – the global reduction of AluS sub-family elements in the circulating DNA of cancer patients. We confirmed this reduction through the analysis of another independent dataset obtained with a very different approach (whole genome sequencing). The evaluation of Alu elements therefore has the potential to enhance the performance of several methods designed for the earlier detection of cancer.

  Study EGAS00001007169

• Molecular Genetics of Histiocytic Sarcoma

  This is a comprehensive genomic analysis of a rare set of histiocytic sarcomas from the consult service of the Hematopathology section of the Laboratory of Pathology, NCI, NIH. The study identifies two distinct groupings of these tumors based on the site of disease, their mutational spectrum, and proliferation signature.

  Study phs001748

• Patient Microbiome and Surgical Site Infection in Spine Surgery

  Single center, prospective cohort study on the contribution of the preoperative patient microbiome and resistome to surgical site infection (SSI) and resistance to surgical antibiotic prophylaxis in spine surgery. The samples in this entry comprise a subset of patients for whom paired preoperative microbiome samples and postoperative wound culture isolates were obtained. These samples were analyzed by Illumina-based sequencing of metagenomic libraries enriched for the SSI pathogen of interest using the GenCap-Seq methodology (PMID: 36121157) to identify instances of endogenous infection with strains present in the preoperative microbiome.

  Study phs003358

• WGS data of paediatric BCR::ABL1 acute lymphoblastic leukemia

  The dataset includes FASTQ and CRAM files from diagnostic and matched remission (control) samples of one BCR::ABL1 ALL patient (ALLT-399). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set Kit (Cat No. PT004). Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

  Dataset EGAD50000002185

• WGS data of paediatric B-other B cell acute lymphoblastic leukemia (set5)

  The dataset includes FASTQ and BAM/CRAM files from diagnostic and matched remission (control) samples of two B-other ALL patients (ALLT-396, ALLK-131). Sequencing library was made using PCR free-based WGS library preparation (PCR-), using Novogene NGS DNA Library Prep Set. Both diagnostic (90x) and remission (30x) samples were sequenced using NovaSeqX Plus.

  Dataset EGAD50000002160

• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia (set 6)

  The dataset includes RNA sequencing FASTQ files from diagnostic tumor samples of three B-other ALL patients (ALLT-311, ALLK-131, ALLK-138). Novogene's internal method was used in directional library preparation including rRNA removal. The diagnostic tumor samples were sequenced using Illumina Novaseq X Plus, and the target sequencing depth was 21 Gb.

  Dataset EGAD50000002602

• WGS Fastq files from the CPC-Gene project in support of PRAD-CA, DCC Release 26

  PRAD-CA, DCC Release 26 : This dataset contains fastq files with Whole genome sequencing data for the CPC-Gene Project. Data from each sample was generated using multiple whole genome libraries and sequenced across multiple runs

  Dataset EGAD00001003706

• Melanoma multi site metastases

  These are caveman, pindel and sequenza calls for the metastatic melanoma exomes within this study.

  Dataset EGAD00001005487

• Bulk RNA-sequencing data of advanced hepatocellular carcinoma (HCC) patients treated with atezolizumab plus bevacizumab.

  The dataset includes FASTq files and normalised gene expression counts from bulk RNA-sequencing of pre-treatment tumour (n=39) and adjacent non-tumour tissue samples (n=13) from advanced hepatocellular carcinoma (HCC) patients treated with atezolizumab plus bevacizumab. Specifically, RNA was extracted from the FFPE tumour tissue using RNeasy Plus Mini Kit (Qiagen), according to the manufacturer’s instructions. RNA quality and quantity were evaluated using Agilent RNA 600 Pico Chips (Agilent Technologies). Sequencing libraries were prepared using the SMARTer Stranded Total RNA-seq kit v3 (Takara Bio). Sequencing was performed on an Illumina NovaSeq 6000 system. After obtaining the Fastq files, read 2 UMIs and adapters were trimmed using seqtk (v1.2), reads were aligned using STAR (v2.7.7a) to the human reference genome (GRCh38) and quantified with HTSeq (v2.0.2).

  Dataset EGAD50000001227