16758 results for "sec+and+unspecified+malignant+neoplasm"

in 39.53 milliseconds.

• Adaptive single-KIR+NKG2C+ NK cells expanded from superdonors show potent missing-self reactivity and efficiently control HLA-mismatched acute myeloid leukemia

  Study EGAS00001006614

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Landen, Stockholm, Sweden.

  Study EGAS00001005838

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from the Netherlands (posthuma)

  Study EGAS00001005857

• Preoperative ipilimumab plus nivolumab in locoregionally advanced urothelial cancer (NABUCCO Cohorts 1 and 2)

  Study EGAS00001004521

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from the Netherlands (Ophoff)

  Study EGAS00001005853

• Whole Exome Sequencing of Bipolar cases and matched controls performed at the Broad Institute on a cohort from Stockholm, Sweden (Pedersen)

  Study EGAS00001005856

• Integrative genomic analyses of European intrahepatic cholangiocarcinoma: new ROS1 fusion gene and PBX1 as prognostic marker

  Study EGAS00001007525

• PDX WES for #87, #95, #32, #217, #86

  Exome sequencing of tumour PDX and matched patient blood

  Dataset EGAD50000000215

• mRNA profiling of human plucked hair follicle

  mRNA profiling of human plucked hair follicle from frontal and occipital scalp

  Dataset EGAD00010001501

• EGAD00010000690

  Genome-wide SNP genotyping of African rainforest hunter-gatherers and neighbouring agriculturalists by Illumina HumanOmniExpress

  Dataset EGAD00010000690

• RHD_NC_OMNI_Controls

  Healthy volunteers and missing phenotype individuals recruited in New Caledonia with higher density genotyping

  Dataset EGAD00010000962

• EGAD00010000538

  28 unlinked autosomal microsatellite loci for 20 African and 4 philippine populations

  Dataset EGAD00010000538

• Transcriptome of (monocytes and dendritic cells ), from donor S13, replicate 1 control

  Dataset EGAD00001009030

• Transcriptome of (monocytes and dendritic cells ), from donor S12, replicate 2 patient

  Dataset EGAD00001009029

• Transcriptome of (monocytes and dendritic cells ), from donor S14, replicate 1 control

  Dataset EGAD00001009032

• Transcriptome of (monocytes and dendritic cells ), from donor S14, replicate 2 control

  Dataset EGAD00001009033

• Transcriptome of (monocytes and dendritic cells ), from donor S15, replicate 1 patient

  Dataset EGAD00001009034

• Transcriptome of (monocytes and dendritic cells ), from donor S15, replicate 2 patient

  Dataset EGAD00001009035

• Transcriptome of (monocytes and dendritic cells ), from donor S16, replicate 1 patient

  Dataset EGAD00001009036

• Transcriptome of (monocytes and dendritic cells ), from donor S16, replicate 2 patient

  Dataset EGAD00001009037

• Transcriptome of (monocytes and dendritic cells ), from donor S13, replicate 2 control

  Dataset EGAD00001009031

• Transcriptome of (monocytes and dendritic cells ), from donor S12, replicate 1 patient

  Dataset EGAD00001009028

• Transcriptome of (monocytes and dendritic cells ), from donor S11, replicate 2 patient

  Dataset EGAD00001009027

• Transcriptome of (monocytes and dendritic cells ), from donor S11, replicate 1 patient

  Dataset EGAD00001009026

• Transcriptome of (monocytes and dendritic cells ), from donor S10, replicate 2 control

  Dataset EGAD00001009025

• Transcriptome of (monocytes and dendritic cells ), from donor S10, replicate 1 control

  Dataset EGAD00001009024

• Transcriptome of (monocytes and dendritic cells ), from donor S9, replicate 2 control

  Dataset EGAD00001009023

• Transcriptome of (monocytes and dendritic cells ), from donor S9, replicate 1 control

  Dataset EGAD00001009022

• Transcriptome of (monocytes and dendritic cells ), from donor S8, replicate 2 patient

  Dataset EGAD00001009021

• Transcriptome of (monocytes and dendritic cells ), from donor S8, replicate 1 patient

  Dataset EGAD00001009020

• Transcriptome of (monocytes and dendritic cells ), from donor S7, replicate 2 patient

  Dataset EGAD00001009019

• Transcriptome of (monocytes and dendritic cells ), from donor S7, replicate 1 patient

  Dataset EGAD00001009018

• Transcriptome of (monocytes and dendritic cells ), from donor S6, replicate 2 control

  Dataset EGAD00001009017

• Transcriptome of (monocytes and dendritic cells ), from donor S6, replicate 1 control

  Dataset EGAD00001009016

• Transcriptome of (monocytes and dendritic cells ), from donor S5, replicate 2 control

  Dataset EGAD00001009015

• Transcriptome of (monocytes and dendritic cells ), from donor S5, replicate 1 control

  Dataset EGAD00001009014

• Transcriptome of (monocytes and dendritic cells ), from donor S4, replicate 2 patient

  Dataset EGAD00001009013

• Transcriptome of (monocytes and dendritic cells ), from donor S4, replicate 1 patient

  Dataset EGAD00001009012

• Transcriptome of (monocytes and dendritic cells ), from donor S3, replicate 2 patient

  Dataset EGAD00001009011

• Transcriptome of (monocytes and dendritic cells ), from donor S3, replicate 1 patient

  Dataset EGAD00001009010

• Transcriptome of (monocytes and dendritic cells ), from donor S2, replicate 1 control

  Dataset EGAD00001009008

• Transcriptome of (monocytes and dendritic cells ), from donor S1, replicate 2 control

  Dataset EGAD00001009007

• Transcriptome of (monocytes and dendritic cells ), from donor S1, replicate 1 control

  Dataset EGAD00001009006

• Transcriptome of (monocytes and dendritic cells ), from donor S2, replicate 2 control

  Dataset EGAD00001009009

• Exome sequencing of nine PCC/PGL tumors

  Exome sequencing of nine PCC/PGL tumors, SF and FFPE samples

  Dataset EGAD00001001854

• RNAseq data

  RNAseq data for 10 patients: 10 tumors and 10 cell lines

  Dataset EGAD00001002691

• Genome-wide DNA Methylation Analysis Reveals a Unique Methylation Pattern for Pleural Mesothelioma Compared to Healthy Pleura and Other Lung Diseases

  Study EGAS00001007783

• Targeted Sequencing Xenturion

  Targeted sequencing of a biobank of PDOs PDXs and LMHs

  Dataset EGAD00001009653

• Biomarker Data Subset

  This dataset contains data for CBC counts and absolute protein abundance measurements from ELISA experiments.

  Dataset EGAD00001011163

• INSPIRE - Investigator-initiated Phase 2 Study of Pembrolizumab Immunological Response in Metastatic Solid Tumors

  Whole exome and RNA sequencing source data for: Clouthier, D.L., Lien, S.C., Yang, S.Y.C. et al. An interim report on the investigator-initiated phase 2 study of pembrolizumab immunological response evaluation (INSPIRE). j. immunotherapy cancer 7, 72 (2019). https://doi.org/10.1186/s40425-019-0541-0 Bratman S*, Yang SYC*, Iafolla MAJ, Liu Z, Hansen AR, Bedard P, Lheureux S, Spreafico A, Razak AA, Shchegrova S, Louie M, Billings P, Zimmerman B, Sethi H, Aleshi A, Torti D, Marsh K, Eagles J, Cirlan I, Hanna Y, Clouthier D, Lien SC, Ohashi PS, Xu W, Siu LL, Pugh TJ. Personalized circulating tumor DNA analysis as a predictive biomarker in solid tumor patients treated with pembrolizumab. Nature Cancer. 2020:1:873-881. https://doi.org/10.1038/s43018- 020-0096-5. Yang SYC, Lien SC, Wang BX, Clouthier DL, Hanna Y, Cirlan I, Zhu K, Bruce JP, El Ghamrasni S, Iafallo MAJ, Oliva M, Hansen AR, Spreafico A, Bedard PL, Lheureux S, Razak A, Speers V, Berman HK, Aleshin A, Haibe-Kains B, Brooks DG, McGaha TL, Butler MO, Bratman SV, Ohashi PS, Siu LL, and Pugh TJ. Pan-cancer analysis of longitudinal metastatic tumors reveals genomic alterations and immune landscape dynamics associated with pembrolizumab sensitivity. Nature Comm 2021:12, 5137. https://doi.org/10.1038/s41467-021-25432-7

  Study EGAS00001003280

• Extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

  A diagnostic non-invasive biomarker test for prostate cancer at an early stage, with high sensitivity and specificity, would improve diagnostic decision making. Extracellular RNAs present in seminal plasma might contain biomarker potential for the accurate detection of clinically significant prostate cancer. So far, the extracellular messenger RNA (mRNA) profile of seminal plasma has not been interrogated for its biomarker potential in the context of prostate cancer. Here, we investigate the mRNA transcriptome in seminal plasma samples obtained from prostate cancer patients (n=25), patients with benign prostate hyperplasia (n=26) and individuals without prostatic disease (n=6). Seminal plasma harbors a complex mRNA repertoire that reflects prostate as its tissue of origin. The endogenous RNA content is higher in the prostate cancer samples compared to the control samples. Prostate cancer antigen 3 (PCA3), a long non-coding RNA with prostate cancer-specific overexpression, and ATP-binding cassette transporter 1 (ABCA1), known to be involved in the prostate cancer pathogenesis, were more abundant in the prostate cancer group. In addition, twelve high confidence fusion transcripts could be detected in prostate cancer samples, including the bona-fide prostate cancer fusion transcript TMPRSS2-ERG. Our findings provide proof-of-principle that the extracellular transcriptome of seminal plasma can reveal information of an underlying prostate cancer.

  Study EGAS00001005277

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_cytoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005584

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_oncoscan)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005586

• Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

  Cancer progression is driven in part by genomic alterations located in oncogenes or tumor suppressor genes. The genomic characterization of cancers has shown a large interpatient heterogeneity regarding the driver alterations, leading to the concept that generating a genomic profiling by multigene sequencing in patients with cancer could allow selecting effective targeted therapies. While this concept has been broadly implemented in daily practice, there is no evidence that such approach improves patient outcome, and how to optimally select the therapy to administer. A genomic profiling using next generation sequencing and copy number analyses was performed 1462 patients with Her2-non overexpressing metastatic breast cancer included in SAFIR02 Breast trial. 238 of these patients were randomized in two trials between a targeted therapy matched to genomic alteration and a maintenance chemotherapy. The trial shows that targeted therapies matched to genomics improves progression free survival (PFS) when genomic alterations are classified level I/II according to ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) (adjusted HR: 0.41, 90% CI: 0.27-0.61, p<0.001), but not when alterations are classified beyond level II (unadjusted HR: 1.15, 95% CI: 0.76-1.75). This trial provides evidence that the treatment decision led by genomics should be driven by a framework of target actionability in patients with mBC.

  Study EGAS00001005587

• MutWP5: CRUK Mutographs of Cancer: Cancer Mastectomy (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 40 women who underwent mastecomies due to breast cancer. LCM and sequencing will be conducted on both normal, unaffected breast, and, where possible, tumour tissue. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue, and compare findings between the normal and associated cancer tissues. Whole-genome sequencing will be conducted on samples identified as promising from the initial targeted data. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those who are BRCA carriers. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010114

• Genomic Characterization of Metastatic Castration Resistant Prostate Cancer

  Biopsies of castration resistant prostate cancer metastases were subjected to whole genome sequencing (WGS), along with RNA-sequencing (RNA-Seq). The overarching goal of the study is to illuminate molecular mechanisms of acquired resistance to therapeutic agents, and particularly androgen signaling inhibitors, in the treatment of metastatic castration resistant prostate cancer (mCRPC).

  Study phs001648

• Contribution of Genetic Polymorphisms to the Abuse Liability of Oxycodone

  The proposed study examined the prevalence of various genetic polymorphisms thought to be involved in opioid abuse among current heroin users. In addition to providing blood samples for genetics analysis, participants completed a number of questionnaires that allowed us to learn detailed information about their current and history of opioid drug use.

  Study phs001559

• Cancer Risk Estimates Related to Susceptibility Genes (CARRIERS)

  The CARRIERS study utilized custom amplicon-based variant screening of known cancer predisposition genes in germline DNA from breast cancer cases and age matched unaffected controls taken from predominantly cohort-based breast cancer case-control studies to establish the risks of breast cancer associated with pathogenic variants in these genes.

  Study phs002820

• Whole Genome Sequencing in Psychotic Major Depression

  The goal of this case-control study, "Whole Genome Sequencing in Psychotic Major Depression", is to identify genes that contribute to the psychotic major depression phenotype. The samples herein were used as controls and were obtained from the NIMH Repository Study #108, "Sustaining Remission of Psychotic Depression".

  Study phs001625

• Genome-Wide Scan for Genetic Variants Associated with Early-Onset Prostate Cancer

  This is a genome-wide association scan of 931 early-onset prostate cancer cases of European ancestry. The samples were selected from prostate cancer studies at the University of Michigan. Controls were previously genotyped individuals selected from the Cancer Genetics Markers of Susceptibility (CGEMS) and Illumina's iControlDB database.

  Study phs001185

• Clinical Trial of COVID-19 Convalescent Plasma in Outpatients (C3PO)

  The Clinical Trial of COVID-19 Convalescent Plasma in Outpatients (C3PO) is a multicenter, randomized, single blind, two-arm, placebo controlled Phase III trial with blinded outcome assessments to establish the safety and efficacy of single dose of convalescent plasma for preventing the progression from mild to severe COVID-19 illness.

  Study phs002752

• DAC for Breast Invasive Lobular Carcinoma CDH1 study

  We developed an artificial intelligence (AI)-model applied to histological images trained using CDH1 biallelic mutations, pathognomonic for breast invasive lobular carcinoma (ILC), as ground truth. We evaluated the performance of the AI-model to predict the presence of CDH1 biallelic mutations and to diagnose ILC. Subsequently, we investigated the molecular underpinning of cases predicted by the model to harbor a CDH1 biallelic mutations but lacking these alterations according to targeted sequencing. We then subjected one ILC lacking CDH1 biallelic mutations and lacking CDH1 promoter methylation to whole genome sequencing (WGS) to determine the molecular basis of its lobular phenotype.

  Dac EGAC50000000333

• Black Representation in Genomic Research Whole Blood eQTL Study

  This dataset contains whole genome sequencing (WGS) results, as well as mRNA-seq of RNA extracted from a venous blood sample, from 23andMe research participants of African ancestry. This dataset facilitates the study of gene expression, genetic variation and the genetic architecture of gene expression in individuals of African ancestry.

  Study phs002969

• Whole genome sequence: cardiomyopathy, 1 HCM patient

  In this study, we analyzed the genomic information by whole genome sequencing using peripheral blood samples from patients with various cardiovascular diseases including severe heart failure to identify genetic variants related to the pathology of cardiovascular diseases. The purpose is to elucidate the underlying mechanism and develop new therapeutic interventions for cardiovascular disease.

  Study JGAS000704

• Whole genome sequence: cardiomyopathy, 1 ARVC patient

  In this study, we analyzed the genomic information by whole genome sequencing using peripheral blood samples from patients with various cardiovascular diseases including severe heart failure to identify genetic variants related to the pathology of cardiovascular diseases. The purpose is to elucidate the underlying mechanism and develop new therapeutic interventions for cardiovascular disease.

  Study JGAS000705

• Transcriptome analysis of Williams syndrome

  Williams syndrome (WS) is a neurodevelopmental disorder caused by microdeletion on chromosome 7q11.23, and has attracted much attention for its distinctive features, such as hypersociability. However, it remains unclear which genes are involved in the complex phenotypes of their condition. Here, we performed transcriptome analysis of peripheral blood to identify genes associated with WS.

  Study JGAS000132

• RNA-seq analysis of BMP-stimulated glioma initiating cells

  Bone morphogenetic protein (BMP) signaling has been shown to suppress progression of glioblastoma by promoting astrocytic differentiation; however, roles of BMP signaling in cell proliferation and apoptosis of glioblastoma cells remains to be elucidated. We here performed RNA-seq analysis of glioma initiating cells to identify transcriptional target(s) of BMP.

  Study JGAS000077

• Comprehensive genetic analysis of pediatric germ cell tumors

  Germ cell tumors (GCTs) are relatively rare tumors in children. Previous studies showed that adult testicular GCTs had some genomic alterations, but genetic basis of pediatric GCTs is still to be elucidated. We applied DNA methylation array analysis, whole-transcriptome sequencing, targeted capture sequencing, and SNP array analysis to fifty-one GCT samples.

  Study JGAS000204

• Somatic L1 retrotransposition dynamics in high-grade serous ovarian cancer

  Somatic L1 retrotransposition was mapped in high-grade serous carcinoma (HGSC) tumors using LDI-PCR/Nanopore-seq method. This method identifies somatic L1 insertions originating from two active L1 loci at chr22q12.1 and chrXp22.2. Multiple tumors from same patient were utilised to understand L1-mediated intrapatient heterogeneity.

  Study EGAS50000001198

• Chondrosarcoma_Targeted_Sequencing_Study

  This Study uses a focused bait pull down library method to target findings of Chondrosarcoma whole genome and whole exome sequencing studies in order to validate findings. This method will also be used on a larger set of tumour only samples in order to find precedence of these finding in a larger set of patients.

  Study EGAS00001000277

• 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

• A distinct monocyte cellular state links systemic immune dysregulation to pulmonary impairment in long COVID

  This is an independent cohort of Long COVID patients recruited from a rehabilitation centre. These patients had Long COVID from 8 months to more than 2 years since their acute COVID-19 disease. PBMC from these patients were collected and single cell transcriptomics dataset was generated.

  Study EGAS50000001216

• Molecular classification of small intestinal adenocarcinomas

  In this study we analyzed genomic and transcriptomic data from 135 small intestinal adenocarcinoma (SIA) patients. Through this analysis, we identified three distinct subtypes based on gene expression patterns, revealing the diverse molecular characteristics among SIA patients. Our findings provide comprehensive insights into the unique features of each subtype.

  Study EGAS50000001238

• LongVar low-coverage data

  This dataset includes sequencing data from participants of the LongVar study. Specifically, it comprises low-coverage whole genome sequencing (WGS) data which was derived from cell-free DNA from blood samples. These data were generated to compare imputation accuracy. 133 individuals agreed to share their data, and are healthy volunteers.

  Study EGAS50000001114

• Identifying mutations in patient-derived melanoma DCC lines

  To identify mutations that cause resistance, we analyzed two patient-derived cell lines: Mel-DCC-11 (the parental line, sensitive to the BRAF inhibitor) and Mel-DCC-11-R (resistant to the BRAF inhibitor). We employed targeted-panel sequencing to examine the coding sequences of 410 cancer-associated target genes.

  Study EGAS50000001225

• Repeated sampling

  Repeated sampling experiment – sample acquisition A repeated sampling experiment was set up to specifically evaluate the effect of increasing time after death on sample quality. Selected non-tumor and large tumor tissues (with enough material available to collect for this experiment beside routine sampling) were sampled repeatedly at 1.5-hour time intervals during the autopsy.

  Study EGAS50000000224

• Neversmoker lung adenocarcinoma

  Non-small cell lung cancer whole genome sequencing We performed whole genome sequencing of Korean never-smoker lung adenocarcinoma patients to discover novel pathway except EGFR and ALK patients. We identified estrogen signaling as a novel enriched signaling. Lastly we validated the elevated estrogen signaling through immunohistochemistry experiment in some patients which increased signaling.

  Study EGAS50000000232

• 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

• 3D genome topology distinguishes molecular subgroups of medulloblastoma

  Medulloblastoma (MB) has four molecular subtypes, but their 3D genome architecture differences are unclear. We used in situ Hi-C on 28 surgical specimens and a patient-derived xenograft to reconstruct the 3D genome architecture of MB subtypes, finding that topologically associating domain (TAD) insulation scores could distinguish MB subtypes.

  Study EGAS50000000540

• Ex vivo modeling of precision immuno-oncology responses in lung cancer

  Single-cell RNA-sequencing (scRNA-seq) data from paired lung cancer organoids and immune cells. The experiment was performed using the Single Cell 5' solution of 10X Genomics. The dataset includes 15 samples from 4 multiplexed experiments. The multiplexing was performed using the Feature Barcoding technology of 10X Genomics.

  Study EGAS50000000593

• WGS data of conditional knockout mouse model mammary tumours

  Deposited here are 56 whole-genome sequencing BAM files from 15 Trp53f/w, 12 Trp53f/f, 14 Brca1f/f Trp53f/w, and 15 Brca1f/f Trp53f/f mouse mammary tumor samples sequenced on Illumina NovaSeq PE150. An additional 6 whole genome sequencing BAM files from corresponding normal tissues of mice are also included as controls (BPC_D666, B1PC_D840, BPTC_D992, PC_D503, PC_D720_Kid, PTC_H531). All samples were used in the study “Insights into BRCA1 and TP53 associated breast cancer development from integrated whole genome analysis of mouse model mammary tumors, Huo et al., 2026.”

  Dataset EGAD50000002036

• Broad utility of ultrasensitive analysis of circulating tumor DNA (ctDNA) dynamics across solid tumors treated with immunotherapy

  Here, we applied a whole-genome, tumor-informed approach to study ctDNA in more than 202 advanced-stage cancer patients treated at VHIO. This study demonstrates the efficacy of ultrasensitive ctDNA as a broad biomarker in a large pan-cancer discovery and validation cohort, spanning 24 tumor types treated with diverse immunotherapy modalities. It demonstrates ctDNA’s potential for early response assessment, survival prediction, and distinguishing true progression from pseudoprogression, enhancing its clinical relevance. This dataset captures the plasma sequencing data from the project.

  Dataset EGAD50000001813

• RNA-Seq Profiles from the CheckMate-577 Clinical Trial

  The dataset contains RNAseq profiles of 386 patients from the CheckMate-577 (CA209-577) clinical trial whose ICF allows data deposition into a public repository. The Allprep DNA/RNA FFPE kit was used to simultaneously purify genomic DNA and total RNA from formalin-fixed, paraffin embedded (FFPE) tissue sections. RNA was analyzed using the Illumina TruSeq RNA Access method for library preparation, followed by sequencing on the Illumina NovaSeq platform with a 50bp paired-end strategy and a target read depth of 50M per sample. Fastq files are included.

  Dataset EGAD50000002394

• LongRNA_Monocytes

  This dataset consists of bulk RNA sequencing profiles generated from monocytes isolated from peripheral blood mononuclear cells (PBMCs) collected from 315 patients enrolled in the ImmunAID consortium. Each sample corresponds to a unique patient, providing a resource to investigate transcriptional variation in circulating monocytes across the cohort. PBMCs were isolated from whole blood, and monocytes were subsequently enriched using standard immunological protocols. Total RNA was extracted and libraries were prepared using the SMART-Seq mRNA Library Preparation Kit with Unique Molecular Identifiers (UMIs). Sequencing was performed on an Illumina NovaSeq 6000 platform following manufacturer-recommended protocols.

  Dataset EGAD50000002341

• WES for 45 patients with pleural mesothelioma (Matched)

  The dataset contains WES data (bam files) for 45 pleural mesothelioma samples. Nextera Flex for Enrichment solution (Illumina, San Diego, CA) in combination with SureSelect Human All Exon V7 probes (Agilent, Santa Clara, CA) was used for library preparation and generated libraries were sequenced on NovaSeq 6000 (Illumina, San Diego, CA) in 150 pair-end mode. Quality control of the raw data was conducted using fastQC (v. 0.11.8) (https://www.bioinformatics. babraham.ac.uk/projects/fastqc/). WES data were then analyzed with the DRAGEN Bio IT platform 49 (version 4.2.4) and the human GRCh38 as reference genome.

  Dataset EGAD50000002128

• WES for 42 patients with pleural mesothelioma (Not matched)

  The dataset contains WES data (bam files) for 42 pleural mesothelioma samples. Nextera Flex for Enrichment solution (Illumina, San Diego, CA) in combination with SureSelect Human All Exon V7 probes (Agilent, Santa Clara, CA) was used for library preparation and generated libraries were sequenced on NovaSeq 6000 (Illumina, San Diego, CA) in 150 pair-end mode. Quality control of the raw data was conducted using fastQC (v. 0.11.8) (https://www.bioinformatics. babraham.ac.uk/projects/fastqc/). WES data were then analyzed with the DRAGEN Bio IT platform 49 (version 4.2.4) and the human GRCh38 as reference genome.

  Dataset EGAD50000002127

• EM-seq datatset of primary human thymocyte subsets

  FASTQ-files of EM-seq experiments of 6 primary human thymocyte subsets, isolated by flow-cytometry (FACS) from neonatal thymus biopsies. All samples were sorted to be negative for the expression of the lineage surface markers CD11c, CD19, CD56, CD141 and CD303 and additionally had the following surface phenotypes: DN2 (CD4-CD8-CD7+CD1a-CD161-CD38+CD3-TCRab-); DN3 (CD4-CD8-CD7+CD1a+); ISP (CD4+CD8-CD3-TCRab-CD1a+); DPE (CD4+CD8+TCRab-CD69-); DPL (CD4+CD8+TCRab+CD69+); SP4 (CD4+CD8-). Samples were sorted from 1-2 pediatric patients undergoing heart surgery.

  Dataset EGAD50000001600

• 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

• PanelSeq IDC samples

  PDX samples of breast cancer IDC mouse models created from patient tumor material of the NKI. Genomescan prepared the samples according to the procedure for Hybridization Capture using an Agilent SureSelect custom 0.5-2.9Mb kit. The prepared libraries were sequenced with Illumina sequencing technology. The samples are in fastq format and consist of the following PDX samples: IDC025, IDC026, IDC029, IDC031, IDC032, IDC038, IDC057, IDC062, IDC065, IDC069, IDC072, IDC090B, IDC092, IDC097, IDC099, IDC107, IDC113, IDC117, IDC143, IDC152, IDC159A, IDC159B, IDC180, IDC186, IDC192, IDC197, IDC198, IDC207, IDC209, IDC216, IDC218, IDC222, IDC229, IDC232, IDC274, IDC282, IDC290, IDC299, IDC307, IDC338, IDC344, IDC346, ILC006, ILC012, ILC083 and ILC248.

  Dataset EGAD50000001149

• Human CMV-specific CD8+ T cells

  In this study we established a comprehensive workflow to collect multi-omics single-cell data using a commercially available micro-well based platform. This included whole transcriptome, cell surface markers (targeted sequencing-based cell surface proteomics), T cell specificities, adaptive immune receptor repertoire (AIRR) profiles and sample multiplexing. With this technique we identified novel paired T cell receptor sequences for three prominent human CMV epitopes. In addition, we review the ability of dCODE dextramers to detect antigenspecific T cells at low frequencies by estimating sensitivities and specificities when used as reagents for single-cell multi-omics.

  Dataset EGAD50000000894

• Long Read sequencing data from 4 tumor/germline samples with non muscle invasive bladder cancer

  A better understanding of the molecular landscape of non-muscle-invasive bladder cancer (NMIBC) is essential to improve risk assessment and identify potential therapeutic targets. Here, we perform a comprehensive genomic analysis of patients diagnosed with NMIBC based on whole-exome- (n=438), shallow whole-genome- (n=362), and total RNA-sequencing (n=414). Additionally, tumor/germline samples from 4 patients were sequenced using Oxford Nanopore technology. This dataset contains 8 BAM files corresponding to the Long read sequencing data.

  Dataset EGAD50000000731

• BELLINI clinical trial bulk RNA-Seq data: cohorts A, B & С

  RNA-Seq data of 78 breast cancer primary tumors obtained from 45 unique patients from BELLINI clinical trial. The data includes pre- and post-treatment samples. Patients in cohort A (15 patients, 25 samples) received nivolumab for 4 weeks, patients in cohort B (15 patients, 28 samples) received nivolumab + ipilimumab for 4 weeks, and patients in cohort C (15 patients, 25 samples) received nivolumab + ipilimumab for 6 weeks. The included raw transcriptome sequencing data in fastq format was generated using Illumina NovaSeq 6000.

  Dataset EGAD50000000808

• RNA-Seq data from study: Molecular underpinnings of dedifferentiation and aggressiveness in chromophobe renal cell carcinoma

  The ChRCC study RNA-Seq dataset contains raw whole transcriptome sequencing data of 16 tumor and 6 adjacent normal samples from 7 UTSW patients, who have consented to depositing their genomic data to public repository. RNA-Seq was performed using 50bp single-end on a HiSeq2500 platform (Illumina, San Diego, CA, USA). 50M reads per sample on average. The raw data is in fastq format.

  Dataset EGAD50000000416

• Bulk RNA-seq of human muscle-invasive bladder cancer tissue samples before and after platinum-based chemotherapy (Chelushkin, van Dorp, et al., 2024)

  The current dataset represents bulk RNA-Seq gene expression profiling (with an exome library preparation kit) of muscle-invasive bladder cancer tissue samples obtained before and after platinum-based chemotherapy. 89 samples are pre-treatment transurethral resection of the bladder tumor (TUR-BT) tissue at diagnosis (baseline), 86 are post-treatment cystectomy tissue (resected tumor bulk), comprising 76 pairs of samples from the same patients. FASTQ files contain gene expression data.

  Dataset EGAD50000000446

• Targeted sequencing (paired) of HR genes in primary and metastatic patient-derived xenografts (PDXs) of colorectal cancer (CRC)

  The dataset includes DNA targeted paired-wise (2 FASTQ per sample) sequencing of a manually curated panel of 44 genes with a documented role in homologous recombination (HR), a pathway of DNA damage response. Sequencing was conducted in 69 tumors from patients with metastatic colorectal cancer after serial passaging in mice (patient-derived xenografts, PDXs). For each PDX model profiled for HR gene mutations, therapeutic annotation of response to FOLFIRI (a chemotherapeutic regimen consisting of the combination of 5-fluorouracil and irinotecan) is available.

  Dataset EGAD50000000107

• AVENIO Expanded ctDNA panel sequence alignments (BAMs)

  The AVENIO ctDNA Expanded Kit is a next-generation sequencing (NGS) liquid biopsy assay with a 77 gene panel (192 kb) containing genes in U.S. National Comprehensive Cancer Network (NCCN) Guidelines and emerging cancer biomarkers. This pan-cancer assay was applied to 100 plasma samples from patients with lung cancer undergoing treatment in the OSCILLATE trial. After 150 bp paired-end sequencing, reads were aligned to the human genome reference with the AVENIO Oncology Analysis Software. These files are the sorted non-deduplicated alignments generated by the analysis software used for subsequent variant, indel and CNV calling.

  Dataset EGAD50000000138

• Exploiting evolutionary steering in cancer therapy

  This dataset contains 9 bam files of exome sequencing for an experiment of evolved resistance. Here a barcoded cell line (HCC827 - POT) has been treated under high concentrations of gefitinib (GEF) and trametinib (TRM) until resistance has evolved, as well as under control conditions (DMSO). The dataset contains exome sequencing of confluent cells for three replicates for each anti-cancer drug as well as two replicates of growth under DMSO conditions. The original barcoded cell line (POT) was also exome sequenced and is included in the cohort. Sequencing was performed on the Illumina NovaSeq platform.

  Dataset EGAD00001005782

• Whole Genome Sequencing of HCC

  The present series corresponds to 24 whole genome sequencing (12 Tumoral/Non-tumoral pairs). Hepatocellular carcinoma (HCC) accounts for more than 90% of liver cancers, and is a major health problem. It is the 3rd cause of cancer-related mortality. Advances in genomic analyses have formed a comprehensive understanding of different underlying pathobiological layers resulting in hepatocarcinogenesis. Thus, the development of next-generation sequencing technologies has made it possible to generate more comprehensive catalogues of somatic alteration events (single nucleotide substitutions, structural variations, and epigenetic changes) in liver cancer genome than ever before.

  Dataset EGAD00001003994

• Renal Cancer Exome Sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 25 renal cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 50 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Dataset EGAD00001000287

• snATAC-seq BAM files from 10x Multiome profiling of human fetal liver hematopoiesis

  This dataset provides snATAC-seq BAM files from a single-nucleus multiome study of 53 human fetal liver samples (5–18 post-conception weeks). Live CD45+CD235- cells were sorted from dissociated tissue, and isolated nuclei were processed using the Chromium Next GEM Single Cell Multiome ATAC + Gene Expression kit. Raw sequencing data were processed and aligned to GRCh38-2020-A-2.0.0 using Cell Ranger ARC v2.0.2.

  Dataset EGAD50000002571