7189 results for "canc*"

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• Hofer et al., A specific subpopulation of cancer-associated fibroblasts promotes resistance to chemotherapy in triple-negative breast cancer by upregulating G0S2 protein

  Chemotherapy is the standard of care for patients with triple-negative breast cancer (TNBC), but the mechanisms of chemoresistance remain poorly understood. Here, we investigated the role of cancer associated fibroblasts (CAFs) in the chemotherapy response of TNBC, by combining in vivo analyses of TNBC patients with ex vivo cancer modeling, using tumor-on-chip (ToC) technology. Transcriptomic analysis revealed that the proportion of a specific CAF population, the extracellular matrix-producing myofibroblasts (ECM-myCAFs), is reduced after chemotherapy in chemo-sensitive, but not in chemo-resistant TNBC patients. In ToC devices, primary ECM-myCAFs promoted TNBC cell survival under Doxorubicin and Paclitaxel treatment. The mechanism of chemoresistance was elucidated by using single-cell RNA sequencing, advanced cell imaging and functional assays: ECM-myCAFs upregulate the G0/G1 switch 2 (G0S2) protein in TNBC cells, via activation of SRC family kinases. Altogether, our work identifies G0S2 as a new player in CAF mediated chemotherapy resistance in TNBC.

  Study EGAS50000000886

• Canadian prostate cancer samples (CPC-GENE) for PanProstate study

  CPC-GENE has sequenced the genomes of 350 intermediate risk prostate cancers to identify genetic signatures that differ in cancers that responded well to treatment compared with those that did not. CPC-GENE also has sequenced multiple regions of prostate cancer from the same gland to determine if and how the genetic make-up of prostate cancer varies within an individual man’s prostate

  Study EGAS00001003037

• Genomic analysis of high-risk prostate cancer.

  Whole genome sequencing analysis of high risk localised primary prostate cancer samples including metastatic samples was performed across 153 tumour samples with matching germline sequencing (whole blood). Samples were all fresh frozen frozen section confirmed tumour specimens and associated clinical and pathological metadata is available for these specimens.

  Study EGAS00001003088

• German early-onset prostate cancer cohort of the Pan-Prostate Cancer Genome (PPCG) project

  Prostate cancer is the most frequent malignant tumor in males and the second most frequent cause of cancer-related death. Currently, in Germany, more than 60,000 prostate cancers are diagnosed every year. Although most of these patients are treated in a curative attempt, more than 10,000 German men die from prostate cancer annually. Owing to the demographic changes of our society, a further doubling of prostate cancer incidences during the next 20 years is expected. Prostate cancer is generally considered a tumor of elderly men. However, a fraction of prostate cancers are diagnosed at the age of 55 years or less. For several reasons, these “early onset prostate cancers” may represent a key entity for the understanding of prostate cancer biology. First, it is likely that early onset prostate cancers represent a distinct molecular subgroup of prostate cancer (PCa), potentially characterized by relatively small numbers of genetic changes, some of which may be particularly strong driver mutations for PCa development. Second, a fraction of prostate cancers in young individuals could represent classical prostate cancers that are detected at a very early stage and might therefore have accumulated molecular changes/mutations occurring that are most instrumental for prostate cancer early detection. Third, PCa with hereditary backgrounds are likely to accumulate in the age group below 55 years. A comparison with other sample sets (e.g. from other ICGC consortia), a systematic genomic analysis of young men with PCa could therefore lead to the detection of mechanisms for hereditary PCa. Fourth, a better understanding of these tumors is particularly relevant as finding optimal treatment regimens is most critical in young cancer patients. We are analyzing the entire genomic DNA sequences of at least 200 PCas (and matched non-tumorous DNA) of young men (≤ 55y), to at least 30 fold coverage, and integrate single-nucleotide variants and genomic structural variations with differential methylation, mRNA and miRNA expression data.Tissues were collected at the University Medical Center Hamburg-Eppendorf. Sequencing was performed at DKFZ and NCT (Heidelberg), EMBL (Heidelberg), and MPIMG (Berlin). Data management and bioinformatic data analyses is being conducted at DKFZ.

  Study EGAS00001003373

• Delineating pediatric brain tumor progression using single-nuclei sequencing

  Pediatric brain cancers are the most common solid tumors in children with varying survival rates depending on molecular features of cancer cells and associated microenvironment. Several studies have used single-cell RNA sequencing to define transcriptional programs active in cancer cells and highlighted supportive roles of non-cancerous cells embedded in these tumors. Although application of single-cell RNA sequencing technology has expanded our understanding of intratumoral heterogeneity and underlying transcriptional mechanisms in brain tumors at diagnosis, mechanisms of disease remains elusive. Therefore, the purpose of this proposal is to characterize cellular and transcriptional states of malignant and non-malignant compartments at primary diagnosis and at relapse. In this study, we performed single-nuclei sequencing of 42 patient samples taken at various disease stages (initial diagnosis, progressive disease, and relapsed disease) from 20 patients with low-grade glioma or Atypical Teratoid Rhabdoid Tumor (ATRT). Bulk whole genome and RNA-seq data for these samples are available from the Children’s Brain Tumor Network and the Gabriella Miller Kids First Data Resource Center. Findings from our study will help define the mechanistic shifts of tumor and non-cancerous cells over course of disease progression. Collectively with the single-cell Pediatric Cancer Atlas funded, this project lays the foundation of an important data set focused on lethal relapsed cancers that can continue to be expanded to identify cancer-intrinsic and extrinsic microenvironmental factors supporting recurrence of pediatric brain tumors.

  Study EGAS50000001288

• Multiomic Landscape of Multiple Myeloma Precursor and Relapsed Disease

  Multiple myeloma (MM) is a treatable, though incurable, plasma cell malignancy. The molecular mechanisms driving disease onset and the emergence of drug resistance remain elusive. To better characterize the mutational, transcriptional, and epigenetic alterations that accompany MM disease evolution, we accessed molecular data from MM patients treated at Moffitt Cancer Center, with bone marrow biopsies collected between 2011 and 2023.We performed scMultiome (single-cell, paired RNA/ATAC-Seq, 10x Genomics) on 18 CD138+-selected bone marrow aspirate samples, including: 2 healthy donors, 3 patients with monoclonal gammopathy of undetermined significance (MGUS), 4 with smoldering myeloma (SMM), 3 with newly diagnosed MM (NDMM), 1 with early relapse MM (ERMM, 1 to 3 lines of therapy), and 5 with late relapse MM (LRMM, 4 or more lines of therapy). Our dataset includes a sequential sample: a patient with a premalignant condition ("scMultiome_SMM_4") that progressed to active myeloma ("scMultiome_NDMM_3"). These data allow for the assessment of transcriptional and epigenetic dysregulation at the cellular level. Our findings illustrate the dynamic epigenetic and transcriptional landscapes that accompany MM disease progression.We also conducted CUT&Tag analysis on 4 NDMM and 4 LRMM samples to map histone modifications, specifically H3K27ac, to investigate their role in transcriptional reprogramming observed in advanced stages of MM. This analysis revealed sample heterogeneity in terms of super-enhancer-regulated genes associated with active transcription.This cohort also includes samples from the clinical trial NCT04151667, “Daratumumab-Based Response-Adaptive Therapy for Older Adults With Newly Diagnosed Multiple Myeloma.” We performed scRNAseq (single-cell RNA sequencing, 10x Genomics) on 30 CD138+-selected bone marrow aspirate samples and 31 pre-sort samples featuring bone marrow mononuclear cells of various cell types from 5 healthy donors and 11 patients with newly diagnosed MM (NDMM). Our dataset includes sequential samples for all 11 NDMM patients, both prior to induction therapy (denoted by ‘a') with Daratumumab and Dexamethasone, and at cycle 2 day 22 (C2D22, i.e., 60 days after induction therapy start, denoted by ‘b'). For three NDMM patients, we also have samples at relapse (denoted by ‘c'). These data allow for the assessment of transcriptional dysregulation at the single-cell level in both the tumor and immune-tumor microenvironment, associated with Daratumumab treatment in NDMM patients.In addition to the molecular data, demographic, and phenotypic information for all samples is provided.

  Study phs003892

• RNA sequencing data from glioblastoma primary cell lines treated with indisulam

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The splicing-modulating drug indisulam was investigated for its potential to induce aberrant transcriptomes, potentially increasing ncTSAs, subsequently predicted by NovumRNA. Four glioblastoma primary cell lines were derived from patient Cavitron Ultrasonic Aspirator (CUSA) material, cultured as neurospheres, and treated with indisulam or vehicle control. RNA was extracted at 6 and 16 hours post-treatment and sequenced using the NovaSeq platform. The resulting RNA-seq data was analyzed with NovumRNA, using healthy brain GTEx samples as controls, to identify and validate ncTSAs induced by indisulam treatment. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000680

• RNA sequencing data from patient derived colorectal cancer organoids

  This study aimed to develop NovumRNA, a bioinformatics pipeline designed to predict non-canonical tumor-specific antigens (ncTSAs) from human tumor RNA-sequencing data, potentially broadening the target pool for cancer neo-epitope-based immunotherapies. The pipeline was utilized to analyze RNA-seq data from ten patient-derived colorectal cancer (CRC) organoids, representing seven microsatellite stable (MSS) and three microsatellite instable (MSI) tumors. The goal was to explore the ncTSA landscape in CRC, particularly in MSS cases, which typically exhibit low tumor mutational burden and limited response to current immunotherapies. The study identified comparable ncTSA burdens across MSI and MSS tumors, suggesting new avenues for immunotherapy targeting non-canonical antigens in CRC. NovumRNA is available at: https://github.com/ComputationalBiomedicineGroup/NovumRNA.

  Study EGAS50000000685

• University of Melbourne Centre for Cancer Research (UMCCR) Data Access Committee

  Dac EGAC00001003567

• Spatially resolved targetted sequencing of colorectal cancers

  Sequencing of laser-capture micro dissected colorectal tumour glands using a targeted capture panel. Tumours were previously subjected to WGS in the parent EPICC study. UMI-resolved aligned bam files, aligned to hg38.

  Dataset EGAD50000001650

• lpWGS of solid and liquid samples from female patients with metastatic breast cancer

  low-pass Whole Genome Sequencing (lpWGS) to assess the representativeness of seven body liquids from female patients with metastatic breast cancer. 20 patients. 216 liquid samples, 745 solid samples, 20 matched normal samples. 0.5X coverage. Illumina single read sequencing. Fastq files are provided. lpWGS from Richard et al., Nature Communications, 2025.

  Dataset EGAD50000001851

• WES to explore mutational landscape of blood and non blood liquids in female patients with metastatic breast cancer.

  Whole Exome Sequencing (WES) to explore mutational landscape of blood and non blood liquids in female patients with metastatic breast cancer. 11 patients. 86 liquid samples, 11 matched normal samples. Median coverage 67X. Illumina paired-end sequencing. Fastq files are provided. WES from Richard et al., Nature Communications, 2025 low-pass Whole Genome Sequencing (lpWGS) to assess the representativeness of seven body liquids from female patients with metastatic breast cancer. 216 liquid samples, 745 solid samples, 20 matched normal samples. 0.5X coverage. lpWGS from Richard et al., Nature Communications, 2025.

  Dataset EGAD50000001852

• Shallow dataset

  Associated with Molecular biomarkers in progression from refractory celiac disease to the lethal cancer variety enteropathy associated T cell lymphoma (EATL) Study. shallow Whole Genome Sequencing (sWGS) of 63 samples. sWGS was done to analyze copy number aberration.

  Dataset EGAD50000001165

• Sequencing dataset for the Predictive Endocrine ResistanCe Index (PERCI) in Breast Cancer cases

  Sequencing dataset for the Predictive Endocrine ResistanCe Index (PERCI) in Breast Cancer cases of the WSG-ADAPT trial (NCT01779206). The Oncomine Comprehensive v3 assay (ThermoFisher) and a customized amplicon-based NGS-Panel (DERv2) was performed.

  Dataset EGAD50000001595

• Mutation analysis using AVENIO Expanded in cfDNA

  High resolution mutation analysis using the AVENIO ctDNA Expanded Kit V2, which targets 77 cancer-associated genes, in cfDNA in metastatic breast cancer.

  Dataset EGAD50000001669

• Single-Gene vs. Panel Sequencing in Advanced HR+/HER2− Breast Cancer

  Background: Hormone receptor-positive (HR+)/HER2-negative (HER2−) breast cancer is the most common subtype of breast cancer, with biomarker-driven therapies improving outcomes. Liquid biopsies, which analyze circulating tumor DNA (ctDNA), are increasingly essential in clinical management, offering a minimally invasive approach to assess somatic alterations and guide therapy decisions. However, the choice of assay directly affects clinical utility and global access to validated testing platforms remains inconsistent. To address these challenges, this study aimed to compare the performance of single-gene and panel-based sequencing for detecting PIK3CA mutations in HR+/HER2− breast cancer and evaluate the added value of broader genomic profiling in guiding treatment decisions. Patients and methods: We conducted a prospective, multicenter study comparing our previously established SiMSen-Seq (SSS) assay, a single-gene method targeting PIK3CA hotspot mutations, with the AVENIO ctDNA Expanded assay, enriching for 77 clinically relevant cancer genes. Additionally, tumor fractions were estimated with mFAST-SeqS by assessing chromosomal aneuploidy. We analyzed 161 plasma samples collected from 146 patients with HR+/HER2− advanced breast cancer before starting a new line of palliative therapy. Results: High concordance (92.6%) was observed between SSS and AVENIO for PIK3CA mutation detection, with accurate variant allele frequency (VAF) quantification confirmed by Bland-Altman analysis and linear mixed-effects modeling. AVENIO identified additional PIK3CA mutations in 19% of samples as well as other actionable alterations, including ESR1 mutations (17.5%) and PI3K pathway alterations (40.6%). Panel sequencing improved the interpretation of negative liquid biopsy results by integrating tumor fraction and VAF metrics. Conclusions: Panel sequencing assays such as AVENIO provide broader genomic coverage, enhance the detection of actionable mutations and refine the interpretation of negative liquid biopsy findings. These findings support the integration of comprehensive ctDNA profiling into routine clinical practice for HR+/HER2− advanced breast cancer while highlighting the need for improved assay accessibility and expanded genomic targets.

  Study EGAS00001008200

• Aligned Low pass whole genbome sequencing of cell free and tumour DNA from 5 patients with high grade serous ovarian cancer. Samples have been aligned to hg19 and bam files uploaded

  This is the aligned bam files of 5 patients, with sequential sampltes from patients comprising cfDNA and FFPE extracted tumour DNA

  Dataset EGAD50000001632

• DAC for Liquid CNA in High Grade Serous Ovarian Cancer

  Low pass sequencing of sequential cell free and tumour DNA with matched whole genome sequencing from five patients with high grade serous ovarian cancer presented in Hockings et al Cancer Research paper, 2025.

  Dac EGAC50000000648

• DNA sequencing of sgRNAs enriched from the CRISPR-Cas9 screened HCC organoids

  There are 12 samples. The project aims to find enriched or depleted sgRNAs to identify functional genes in HCC progression and lenvatinib resistance

  Study EGAS50000001130

• Heterogeneity and evolution of DNA mutation rates in microsatellite-stable colorectal cancer

  A mutation accumulation experiment in colorectal cancer (CRC) derived tumoroids, aimed at measuring the spontaneous rates of accumulation of new single-nucleotide sequence variations in seven microsatellite stable CRCs and one microsatellite unstable CRC. Mutations accumulated over six+six months were identified via whole genome sequencing of clonal tumoroids.

  Study EGAS50000000284

• Cancer Affected Patients - Data Access Committee

  Access to the cancer cohort is made available by completing the data access agreement for review by the data access committee and will be granted to qualified investigators for appropriate use. Individuals requesting access to the data need to comply with the terms of a Data Access Agreement (DAA) and are requested to use the data only in approved and ethical ways.

  Dac EGAC50000000037

• Dac for "ARHGAP11A Maintains Cortical Progenitor Identity Through RHOA–ROCK Signalling During Human Brain Development" with Julia.ladewig@zi-mannheim.de, Department of Translational Brain Research. Moritz Mall, m.mall@dkfz-heidelberg.de, German Cancer Research Center (DKFZ). Yannick Hass, yannick.hass@zi-mannheim.de, Department of Translational Brain Research. Anne Hoffrichter, anne.hoffrichter@zi-mannheim.de, Department of Translational Brain Research, Central Institute of Mental Health

  Dac EGAC00001003603

• IDH-wildtype untreated human glioblastoma samples (GB-UK cohort), published in Noorani & Haughey et al 2025.

  Extrachromosomal DNA (ecDNA) oncogene amplification is associated with treatment resistance and shorter survival in cancer. Currently, the spatial dynamics of ecDNA, and their evolutionary impact, are poorly understood. Here, we investigate the spatiotemporal evolution of ecDNA by integrating computational modeling with samples from 94 treatment-naive human IDH wild-type glioblastoma patients. Random ecDNA segregation combined with ecDNA-conferred fitness advantages induce distinct spatial ecDNA copy number patterns which depend on ecDNA oncogenic makeup. EGFR-ecDNAs often reach high copy numbers and confer strong fitness advantages. In contrast, PDGFRA-ecDNAs reach lower copy numbers and confer weaker fitness advantages. EGFR structural variants occur exclusively on ecDNA, arise from and are intermixed with wild-type EGFR-ecDNAs. Computational modeling suggests wild-type and variant EGFR-ecDNAs often accumulate before clonal expansion. Using a genetically engineered mouse model, we confirm that the accumulation of oncogenic ecDNA prior to clonal expansion under strong positive selection is observable both in vivo and in vitro in mouse neural stem cells. Intermixed wild-type and variant ecDNAs remain prevalent at diagnosis, as less fit wild-type ecDNAs hitchhike on strongly selected variant EGFR-ecDNAs. A dN/dS analysis in the Genomics England cohort further suggests positive selection of variants on EGFR-ecDNAs but not PDGFRA-ecDNAs in glioblastoma. Overall, our results suggest ecDNA oncogenic makeup determines unique evolutionary trajectories in glioblastoma. New concepts like ecDNA tumor clonality, ecDNA heteroplasmy and multi-species ecDNAs require a refined evolutionary interpretation of genomic data in a large subset of glioblastoma patients and likely other solid cancers.

  Study EGAS00001008126

• Tumor inflammation and mutational burden are differentially associated with response to nivolumab or nivolumab plus ipilimumab in metastatic colorectal cancer

  Nivolumab alone and in combination with ipilimumab demonstrated durable clinical benefit in patients with previously treated microsatellite instability-high/mismatch repair-deficient metastatic colorectal cancer in the phase 2 CheckMate 142 study. Exploratory biomarker analyses of tumor and microbiome samples from CheckMate 142 were performed to evaluate associations between various biomarkers and the efficacy of nivolumab monotherapy and nivolumab plus ipilimumab combination in these patients. Higher expression of inflammation-related gene expression signatures was associated with improved response per investigator assessment and survival benefit with nivolumab monotherapy. In contrast, higher tumor mutational burden, tumor indel burden and degrees of microsatellite instability were associated with improved response per investigator assessment and survival benefit with nivolumab plus ipilimumab. While interpretation is limited by the exploratory nature of these analyses, they suggest that tumor antigenicity rather than baseline tumor inflammation might be important for the combinatorial efficacy. Validation of these findings in larger, randomized studies is necessary.

  Study EGAS50000000416

• DCIS Whole Exome & Whole Genome Sequencing Data

  Primary DCIS and recurrent DCIS/IBC (total n=82, ipsilateral n=78 and contralateral n=4) as well as non-recurrent DCIS (n=32) cases were identified through hospital databases from Royal Melbourne Hospital (RMH), Nottingham City Hospital (UK), the LifePool cohort and Peter MacCallum Cancer Centre (PMCC). All cases were micro-dissected from haematoxylin stained sections (range 4-20 sections) by manual micro-dissection to achieve >50% tumour tissue purity. DNA was extracted using the FFPE AllPrep kit (Qiagen, MD, USA). Depending on the success and timing of DNA extraction (Figure 1), cases were analysed by a targeted sequencing panel (n=46, samples pre-2020), whole exome sequencing (WES, n=67), or low-coverage whole genome sequencing (LCWGS). WES: DNA was processed by the Australian Genome Research Facility (AGRF) using the Twist Bioscience Human Comprehensive Exome v1 or v2 (Twist Bioscience HQ, South San Francisco, CA, USA) according to the Twist Target Enrichment Standard Hybridisation Protocol. Sequencing was performed on the Illumina NovaSeq 6000 with 150 bp paired-end reads for a median depth of 101.29x, range: 20.39-247x. Whole Genome Sequencing (WGS): Libraries for four paired samples with matched stromal DNA were made, processed and sequenced by AGRF using the IDT xGen Kit (USA) according to the manufacturer’s protocol, aiming to achieve 60x depth for tumour DNA and 30x for matched normal. File type: Paired-end FASTQ.

  Dataset EGAD50000001846

• Comprehensive peripheral blood immunoprofiling reveals five immunotypes with immunotherapy response characteristics in cancer patients

  The lack of comprehensive diagnostics and consensus analytical models for evaluating the status of a patient’s immune system has hindered a wider adoption of immunoprofiling for treatment monitoring and response prediction in cancer patients. To address this unmet need, we developed an immunoprofiling platform that uses multiparameter flow cytometry and RNA-seq to characterize immune cell heterogeneity in the peripheral blood of healthy donors and patients with advanced cancers. Using unsupervised clustering, we identified five immunotypes with unique distributions of different cell types, and gene expression profiles.

  Study EGAS50000000286

• BAP1 study

  Background: Mutations in BAP1 have been identified in many aggressive cancers. Current therapeutic strategies for BAP1-deficient tumors are not effective. Goal: Discover novel strategies for BAP1-deficient tumors. Details: In our study, we identified a potential therapeutic strategy for BAP1-deficient cancers. We used multi-omics approaches to understand the underlying mechanisms behind why the discovered potential therapeutic strategy is effective.

  Study EGAS50000000235

• End motifs analysis of circulating DNA from the plasma of patients with stage II-III breast cancer (n=50), stage I-III non-small cell lung cancer (n=56), metastatic colorectal cancer (mCRC) (n=15) and healthy individuals (n=37)..

  We have developed an algorithm designed to discriminate cancer patients and healthy individuals based on cirDNA fragment end motif analysis assisted by machine learning, using data obtained from shallow whole genome sequencing (a method we call EMA). We applied EMA to cirDNA from the plasma of patients with stage II-III breast cancer, stage I-III non-small cell lung cancer, and metastatic colorectal cancer (mCRC). CirDNA from 158 individuals was prepared following the conventional double-stranded DNA library preparation (DSP). We also performed a single-stranded DNA library preparation (SSP) using mCRC patients and healthy control cirDNA, which allowed us to make the first ever end motif analysis in the literature which compares the use of DSP and SSP.

  Study EGAS50000001319

• Multi-omics analysis of treated cancer samples

  We treated patient-derived cell lines with effective drug inhibitors that we discovered. To understand the mechanisms behind how the inhibitor can effectively inhibit tumor growth, we performed a series of RNA-Seq, Histone ChIP-Seq, TF ChIP-Seq and ATAC-Seq profiling for samples with and without treatment with the inhibitor. There are 18 RNA-Seq, 20 ATAC-Seq and 182 ChIP-Seq experiments performed. This includes 2 biological replicates. Novaseq 6000 was used to sequence the samples. Library preparation was performed in house for ChIP-Seq and ATAC-Seq, using NEB indexes, while libraries for RNA-Seq were constructed by the sequencing company hired. Total RNA was sequenced. Sequencing parameters used are PE150, bi-directional sequencing. For ATAC-Seq, sequencing was performed up to 40M reads, for ChIP-Seq, sequencing was performed up to 20M reads and for RNA-Seq, sequencing was performed up to 20M to 40M reads. Fastq files are uploaded here.

  Dataset EGAD50000000349

• cfDNA sWGS BAM — Breast cancer stage II-III (HR+/HER2−)

  Plasma cfDNA sWGS for breast cancer patients (HR+/HER2−, stage II–III), blood drawn pre-operatively (no neoadjuvant), Centre Léon Bérard/MyProbe (France). Libraries: DSP and/or SSP as recorded. Sequencing by IntegraGen (2022–2024); alignment to GRCh38 with BWA-MEM; BAMs sorted/indexed; primary mapped reads only (see analysis metadata for exact filters/MAPQ). Controlled access.

  Dataset EGAD50000001877

• cfDNA sWGS BAM — Metastatic colorectal cancer

  Plasma cirDNA sWGS for metastatic colorectal adenocarcinoma at diagnosis prior to systemic therapy. Libraries DSP/SSP (per sample). Sequencing by IntegraGen (2022–2024). Alignment: GRCh38 with BWA-MEM; BAMs sorted/indexed; delivered as primary mapped reads only (filters/MAPQ in analysis metadata). Controlled access

  Dataset EGAD50000001879

• Bevacizumab plus erlotinib in advanced solid cancers with Krebs cycle gene mutations: A multicenter phase II study

  Targeting aberrant metabolism in tumors with alterations in genes encoding Krebs cycle enzymes, a central component of glucose metabolism, is a promising therapeutic strategy. These tumors rely on aerobic glycolysis and promote VEGF-dependent angiogenesis; furthermore, EGFR signaling enhances aerobic glycolysis. This phase 2 trial evaluated bevacizumab and erlotinib in patients with solid tumors harboring Krebs cycle gene mutations.

  Study EGAS50000001243

• CASCADE tumour high-coverage whole genome sequencing data

  High coverage whole genome sequencing data (total: 22; median coverage: ~56X; range: 27X – 82X) from fresh frozen postmortem tissues harvested from patients who participated in the CASCADE rapid autopsy program and died of metastatic castration resistant prostate cancer.

  Dataset EGAD00001009491

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by targeted sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by a targeted panel for somatic mutation and sCNA analysis (7 samples), subject to cell availability. Mutation analysis was performed successfully in 6/7 samples and somatic mutations were detected in all of them.

  Dataset EGAD50000001888

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001889

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by targeted sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by a targeted panel for somatic mutation and sCNA analysis (7 samples), subject to cell availability. Mutation analysis was performed successfully in 6/7 samples and somatic mutations were detected in all of them.

  Dataset EGAD50000001890

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001891

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001892

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001893

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001894

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by shallow whole genome sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by downstream shallow whole genome sequencing (WGS) for copy number landscape profiling for 10 samples. Seven out of 10 samples (even some with low tumour content or of old age) produced good quality genomic data, detecting sCNA in all carcinoma population samples but not in the stromal populations.

  Dataset EGAD50000001895

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by targeted sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by a targeted panel for somatic mutation and sCNA analysis (7 samples), subject to cell availability. Mutation analysis was performed successfully in 6/7 samples and somatic mutations were detected in all of them.

  Dataset EGAD50000001896

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by targeted sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by a targeted panel for somatic mutation and sCNA analysis (7 samples), subject to cell availability. Mutation analysis was performed successfully in 6/7 samples and somatic mutations were detected in all of them.

  Dataset EGAD50000001897

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by targeted sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by a targeted panel for somatic mutation and sCNA analysis (7 samples), subject to cell availability. Mutation analysis was performed successfully in 6/7 samples and somatic mutations were detected in all of them.

  Dataset EGAD50000001898

• DEPArray-based sorting of pure carcinoma and stromal populations from formalin-fixed paraffin-embedded (FFPE) tissues followed by targeted sequencing

  To overcome the challenges of low DNA yields, degraded DNA by formalin fixation and diluted signal of genomic aberrations by non-carcinoma components in the heterogeneous FFPE samples, we isolated pure carcinoma and stromal cells using the DEPArray™ NxT system, a microchip-based digital sorter that allows isolation of pure, homogeneous subpopulations of cells from FFPE samples. We isolated pure carcinoma and stromal cell populations from 12 FFPE tissues, including tissues from 9 primary and metastatic breast cancer and 3 primary ovarian high-grade serous carcinomas. This was followed by a targeted panel for somatic mutation and sCNA analysis (7 samples), subject to cell availability. Mutation analysis was performed successfully in 6/7 samples and somatic mutations were detected in all of them.

  Dataset EGAD50000001899

• Circulating Biomarker Laboratory within the Division of Cancer of Imperial College London

  The purpose of the Circulating Biomarker Laboratory within the Division of Cancer of Imperial College London (ICL) is to assist ICL researchers working on solid tumours or/and haematological malignancies with a particular interest in the analysis of liquid biopsies. We are focusing on isolating and analysing single circulating tumour cells (CTCs) and cell-free circulating tumour DNA (ctDNA) from cancer patients' blood samples but also pure tumour poulations from heterogeneous Formalin-fixed paraffin-embedded (FFPE) tissue specimens with a view to monitoring tumour-related changes, such as mutations and copy number alterations at a single cell level.

  Dac EGAC50000000768

• DNA Replication Speed controls Epigenome Integrity and T Cell Fate

  Epigenetic mechanisms maintain cellular identities by enforcing stable, cell type-specific transcriptional programs while also allowing regulated plasticity for adaptations to environmental cues like differentiation signals. Dysregulation of this dual capacity has been linked to cancer and chronic inflammation, with the regulatory mechanisms remaining poorly understood. Here, we identify DNA replication speed as a physiological regulator controlling epigenome stability and plasticity. Using T-lymphocytes as a model, we demonstrate that fast DNA replication speed impaired epigenome stability, causing DNA methylation maintenance errors at cell type-specific enhancers and heterochromatin, ultimately leading to compromised cell function. However, accelerated DNA replication speed supported epigenome plasticity during differentiation, promoting successful cell-type transitions

  Study EGAS50000001273

• Clinical Utility of Breast cancer Research by Inocras, Catholic university hospital and Samsung medical center

  Breast cancer remains a major global challenge. To comprehensively characterize its genomic landscape and clinical significance, we analyzed whole genome sequences from 1,364 clinically annotated breast cancers, integrating transcriptome data from most of the tumors.

  Study EGAS50000001062

• Clinical Utility of BRCA Research by Inocras, CMC and SMC (CUBRICS)

  This dataset consists of whole-genome sequences from 1,364 Korean breast cancers, with transcriptome data available for most cases

  Dataset EGAD50000001546

• Benchmark Dataset for Somatic Mutation Calling in Cell-Free 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.

  Dataset EGAD50000001870

• SDR-seq_06_BCL

  Multiomic targeted scDNA-scRNA-seq (SDR-seq) of primary B-cell non-Hodgkin lymphomas. Aim is to link genomci variants to gene expression in single cells. Profiled two follicular lymphoma (FL) primary patient samples and one germinal center subtype diffuse large B-cell lymphoma (GCB) primary patient sample.

  Study EGAS50000000374

• Targeted capture, whole genome sequencing, and RNAseq to identify rearrangements in B-cell lymphomas

  This study contains whole genome and custom targeted capture sequencing of mature B-cell lymphomas (DLBCL, FL, BL, HGBCL-DH-BCL2, HGBCL-DH-BCL6) to identify translocation breakpoints of common oncogene rearrangements (MYC, BCL2, BCL6). It is complemented by RNAseq data where available. Complete details are available in the publication Hilton et al, 2024, Blood. Capture sequencing: 357 samples; 364 unique libraries; cram file format aligned to hg38 Whole genome sequencing: 12 samples; 12 unique libraries; cram file format aligned to grch37 RNAseq: 257 samples; 257 unique libraries; fastq file format

  Study EGAS50000000328

• DNA sequencing of sgRNAs enriched from the CRISPR-Cas9 screened HCC organoids

  Project aims to find enriched or depleted sgRNAs to identify functional genes in HCC progression and lenvatinib resistance

  Study EGAS50000000848

• Amplicon based re-sequencing of multi-region PDAC samples

  Multi-region tumor samples were cut from frozen sections or FFPEs and reviewed from microdissection and H&E staining in order to select ones with high cellularity. DNA extraction was done using DNeasy Blood & Tissue Kits for frozen samples following the manufacturer’s guideline. Extracted DNAs were processed on an Illumina HiSeq 2500 in a paired end mode (100x100) using a custom targeted panel based on the list of all unique somatic mutations from the original WES data by the Integrated Genomics Operation (IGO) at Memorial Sloan Kettering Cancer Center (New York, NY).

  Dataset EGAD50000000354

• Multiregional single nuclei RNA-seq and WGS of prostate cancer

  This study investigates the clonal evolution and metastatic dissemination of prostate cancer using multiregional single-nuclei RNA sequencing (snRNA-seq) and low-pass whole-genome sequencing (WGS) data from 43 spatially distinct tumor areas in five patients with locally advanced prostate cancer, including both primary and regional lymph node samples. We employed the Chromium Next GEM Single Cell 3’ Kit (v3/3.1, 10x Genomics) for single-nuclei transcriptome profiling and constructed bulk WGS libraries using the NEBNext Ultra II FS DNA Library Prep Kit (New England Biolabs) from the same pool of nuclei extracted from each area. snRNA-seq data were aligned to the human genome (GRCh38-1.2.0_premrna) using 10x Genomics Cell Ranger v5.0.0, while WGS reads were aligned to the human reference genome (GRCh38) with BWA MEM, achieving an average sequencing depth of 0.3X for low-pass WGS and 16X after resequencing.

  Dataset EGAD50000001357

• GeoMx DSP of NGS mRNA expression in pre-treatment biopsies from patients with metastatic triple-negative breast cancer treated with PARP inhibitors.

  This dataset contains GeoMx digital spatial profiling (DSP) data from 12 FFPE pre-treatment biopsies of metastatic HR-altered breast cancer patients subsequently treated with PARP inhibitors (Olaparib or Talazoparib). Samples were collected from primary breast tumors (n=7) and metastatic sites including lymph nodes (n=2), bone (n=2), and brain (n=1). Tissue sections were stained for pan-cytokeratin (PANCK) to selectively profile tumor cells, with NGS-based transcriptome data generated for both PANCK+ and PANCK- regions. The dataset includes raw data files (176 fastq files) along with clinical annotations.

  Dataset EGAD50000001932

• GeoMx digital spatial profiling of NGS mRNA expression in pre-treatment biopsies from patients.

  This DAC is created to define the data controller (the person that determines the purposes for which and the means by which personal data is processed) for the following study: GeoMx digital spatial profiling of NGS mRNA expression in pre-treatment biopsies from patients with metastatic triple-negative breast cancer treated with PARP inhibitors.

  Dac EGAC50000000774

• Human colorectal cancer single-cell RNA sequencing

  The aim was to investigate changes in transcriptomics following irradiation. This was studied in colorectal cancer-patient derived organoids. Analysis was performed with scRNA-seq.

  Study EGAS50000001348

• MIBC NAC2020 cohort RNA sequencing

  The dataset contains RNA sequencing data from N=48 transurethral resections of bladder tumours (TURBTs) from N=48 patients with muscle-invasive bladder cancer who were treated with neoadjuvant chemotherapy followed by radical cystectomy. All TURBTs originate from formalin-fixed paraffin embedded tissue. We used the Illumina TruSeq RNA exome kit, previously known as the TruSeq RNA Access Library Prep Kit. This kit converts total RNA into template molecules of known strand origin, followed by sequence-specific capture of coding RNA. All samples were run in an Illumina NovaSeq6000 instrument. Paired FASTQ files from all 48 patients are provided.

  Dataset EGAD50000001025

• WES analysis of tumor samples from ER+ breast cancer patients treated with CDK4/6 inhibitor

  We performed whole exome sequencing of paired fresh frozen tumor from 4 ER+ advanced breast cancer patients. Samples were obtained for each patient prior to combined CDK4/6 inhibitor and endocrine therapy and at disease progression (N=8). DNA was extracted using the Maxwell® RSC FFPE and Tissue DNA Kit (Promega). WES was performed at the Department of Molecular Medicine, Aarhus University Hospital on matched tumor DNA (derived from primary fresh frozen and FFPE tissue) and buffy coat DNA. Libraries of tumors and matching germline DNA were prepared using 50 ng DNA and captured by Twist Comprehensive Exome with custom spike-ins, sequenced on the Illumina NovaSeq 6000 platform to an average coverage of 413x (range: 148-515x). The dataset include the analysis data files (vcf files).

  Dataset EGAD50000000622

• APC-related multiple salivary gland lesions

  This study aims to investigate the genetic and molecular mechanisms underlying a novel phenotype of attenuated familial adenomatous polyposis (AFAP), where affected individuals develop multiple salivary gland tumours, including basal cell adenomas and adenocarcinomas.

  Study EGAS50000001159

• Pipeline Olympics: Continuous benchmarking of computational workflows for DNA methylation sequencing data

  DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposure, and disease. Genome-wide DNA methylation profiling is usually performed using whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods. Numerous software tools facilitate processing of raw sequencing data for DNA methylation profiling, but a comprehensive benchmarking has been lacking. In this study, we systematically compared methods and tools for processing DNA methylation sequencing data. We established a dedicated benchmarking dataset comprising genome-wide DNA methylation profiling data for four reference samples using five experimental protocols each. The results of data processing were compared to highly quantitative locus-specific DNA methylation measurements available for 46 genomic loci. Based on this gold-standard reference dataset, we identified workflows that consistently demonstrated high performance. We present our results in an interactive application that provides a “living benchmark” ready for continuous updating as new workflows are proposed and require benchmarking against existing methods. In summary, our study provides guidance for any laboratory studying DNA methylation on a genome-wide scale.

  Study EGAS50000000541

• Deep whole genome ctDNA chronology of treatment-resistant prostate cancer

  Study EGAS00001005783

• Germline WES-data of pediatric cancer patients with variants in HBOC-related genes

  This study focused on the identification of (likely) pathogenic germline variants (LP/PV) in 25 adult-onset HBOC-related genes in a cohort of 372 pediatric cancer patients. The cohort was sequenced on Illumina platforms. The files uploaded here belong to the 27 individuals with such a LP/PV.

  Study EGAS50000001073

• Recurrent intra-tumour heterogeneity is a hallmark of metastatic prostate cancer

  The evolution of cancers from low grade to metastatic disease is a major determinant of cancer mortality. Cancer evolution involves a complex interplay between cell intrinsic genetics and transcriptional alterations and the extrinsic microenvironment. To define the key mechanisms underpinning metastatic development, we focused on the most lethal form of prostate cancer, metastatic castration-resistant prostate cancer, and employed single-cell multi-omics and whole-genome sequencing to deeply profile 34 metastatic lesions from 9 patients obtained from rapid autopsy. We found that intra-tumour heterogeneity is an indicator of key evolutionary processes, characterised by recurrent tumour populations acting as critical functional components of the tumour ecosystem, irrespective of clonal and microenvironmental backgrounds. Unexpectedly, microenvironments across metastatic sites played a limited role while clonal evolution primarily promoted transcriptional noise. Intra-patient functional convergence of tumour ecosystems was observed across metastatic sites, pointing towards system-level selection pressures that drive the heterogeneity landscape of mCRPC. Our findings reveal functional evolutionary convergence of metastatic disease into units of intra-tumour heterogeneity identifying critical determinants of metastatic progression for therapeutic targeting. Note: matched WGS for some tumour single-cell experiments, as well as germline WGS for patients CA0027, CA0034, CA0035, CA0043, and CA0076, can be found in EGAS00001006598.

  Study EGAS50000001312

• Whole-genome and single-cell sequencing of lethal metastatic castration resistant prostate cancer

  Contains a total of 9 patients with whole-genome sequencing of 30 tumours or germline samples, 10X single-cell multiome RNA-seq + ATAC-seq of 24 tumours, 10X 5' single-cell RNA-seq of 10 tumours, and snPATHO-seq of 2 primary tumours. All single-cell experiments have matched whole-genome sequencing. When matched tumour (and germline) whole-genome sequencing is missing, it can be found under EGAS00001006598.

  Dataset EGAD50000001869

• Pediatric B-cell precursor acute lymphoblastic leukemia Micro-C sequencing

  This dataset included 35 childhood B-cell precursor (BCP) acute lymphoblastic leukemia Micro-C samples. All samples were subjected to Illumina pair-end sequencing.

  Study EGAS50000000764

• ICARUS-BREAST01-ExomeSeq

  Efficacy, safety and biomarker analysis of ICARUS-BREAST01: a phase 2 Study of Patritumab Deruxtecan in patients with HR+/HER2- advanced breast cancer. Whole-exome sequencing (WES) is available for 43 tumor samples and 43 blood samples collected at entry into the trial.

  Study EGAS50000000542

• Pancreatic cancer RNA sequencing

  Study EGAS00001004706

• ucfDNA workflows for molecular profiling of malignant disease

  Urinary cell-free DNA (ucfDNA) is a promising liquid biopsy analyte obtained by a non-invasive sampling method, particularly valuable in urological cancers due to the proximity of biofluids to the tumor site. However, extremely high fragmentation and low abundance of ucfDNA pose significant analytical challenges. Improper handling and storage can severely affect ucfDNA quality, necessitating optimized pre-analytical workflows for clinical applications. We evaluated multiple pre-analytical workflows, including urine stabilization approaches against unstabilized urine samples. Our results demonstrated that without stabilization, ucfDNA degraded rapidly and minimal quantities remaining after 72 hours. In contrast, urine stabilization preserved ucfDNA integrity, enabling successful downstream analyses, including digital PCR and next-generation sequencing, for mutation detection in cancer-related genes and genome wide copy number profiling. These findings underscore the critical role of stabilization for a reliable ucfDNA analysis and highlight its potential in molecular diagnostics as a complementary tool to plasma-based liquid biopsies.

  Study EGAS50000001093

• Variant analysis on FFPE specimen from NSCLC patients (OCAPlus)

  This study assessed the presence of somatic variants via the Oncomine Comprehensive Panel Plus panel (ThermoFisher) for commonly mutated cancer genes and measure tumor mutational burden using next-generation sequencing. It was performed on genomic DNA from FFPE tissue of tumor resections. Mutations were used to draw OncoPrints and to assess TMB in relation with response metrics.

  Study EGAS50000001136

• Variant analysis on FFPE specimen from NSCLC patients (FoundationOne CDx)

  This study assessed the presence of somatic variants via the FoundationOne CDx panel of commonly mutated cancer genes and measure tumor mutational burden using next-generation sequencing panels. It was performed on genomic DNA from FFPE tissue of tumor resections. Mutations were used to draw OncoPrints and to assess TMB in relation with response metrics.

  Study EGAS50000001139

• Targeted gene expression analysis on FFPE specimen from NSCLC patients

  This study measured the expression of a panel of over 300 cancer immunotherapy-relavant genes in tumors after neoadjuvant chemoimmunotherapy. It was performed on RNA from FFPE tumor tissue. Differential gene expression analysis was performed between patients achieving or not achieving an event-free survival of 12 months.

  Study EGAS50000001140

• Single cell RNA sequencing of PBMC samples from CRC patients

  This data contains scRNA-seq on 14 PBMC samples from colorectal cancer patients.

  Dataset EGAD50000000841

• RNA-seq of oropharynx cancer cases from University of Michigan

  This dataset consists of 67 bulk RNA-seq data (sorted aligned BAM files) from formalin-fixed paraffin-embedded (FFPE) oropharynx tumor samples from the University of Michigan (UM). Samples were collected as part of the UM Head and Neck SPORE between 2008-2014. Library preparation was performed using the ribo-depletion method with the FastSelect kit and sequenced on the NovaSeq 6000 at the UM Advanced Genomics Core, resulting in 150bp paired-end reads. Raw reads were trimmed using Cutadapt (v3.4) and aligned to hg38 and high-risk HPV genomes using STAR (v2.7.9a). 62 of 67 samples were determined to be HPV RNA-positive.

  Dataset EGAD50000001306

• Michigan-Georgetown Cancer DAC

  Genomics data from cancers and/or dysplasias for the collaborations between Maureen Sartor and Nisha D'Silva at the University of Michigan and Laura Rozek at Georgetown University

  Dac EGAC50000000397

• PARADIGM: Combined ctDNA and serum PSA for dynamic monitoring of metastatic prostate cancer starting first-line treatment

  The prognosis of newly-diagnosed metastatic prostate cancer is highly variable. The PARADIGM prospective cohort study evaluated predictors of survival in blood collected at the start of each of the first six treatment cycles from 114 high-volume metastatic patients starting androgen deprivation therapy combined with docetaxel or an androgen receptor pathway inhibitor.

  Study EGAS50000001357

• Targeted sequencing data on sequential liquid biopsy samples from CSPC patients

  Sequencing data from newly diagnosed high emtastatic burder prostate cancer patients receiving an AR pathway inhibitor (ARPI) or docetaxel. Targeted sequencing data of prostate cancer relevant genes using the PCF-SELECT capture panel. cfDNA from PreADT, baseline, on-treatment (Cycle1 to 6) taken on ARPI or Docetaxel were sequenced as well as patient-matched WBC DNA

  Dataset EGAD50000001960

• Integrated Single-Nucleus and Spatial Transcriptomics Elucidate Heterogeneity and Hypoxia-Driven Organization of Supratentorial Ependymoma

  Supratentorial ependymomas are often life-threatening brain tumours that are characterised by significant molecular heterogeneity. In this study, single-nucleus (n = 63) and spatial transcriptomics (n = 30) was performed to delineate the cellular and spatial landscape of supratentorial ependymoma. This study characterises the transcriptional consensus programs of this entity and connects them to clinical outcome. Two previously undescribed programs – associated with the remodelling of the extracellular matrix and the ZFTA fusion identity – are shown to be related to highly unfavourable outcome and to be exclusive to ZFTA fusion-positive tumours. Also, Hypoxia is proposed as the potential driver of spatial organisation, which may affect treatment success.

  Study EGAS50000001318

• Development of Novel Chondrosarcoma Organoid Models for Drug Discovery

  Chondrosarcoma is a rare and aggressive malignant bone tumor characterized by resistance to conventional chemotherapy and radiotherapy. Its pathogenesis remains poorly understood, although recurrent mutations such as IDH1 have been implicated in tumor development. We treated patients with chondrosarcoma at the Osaka International Cancer Institute and established two organoid cultures from resected tumor specimens using a modified air-liquid interface method. After serial passaging, the organoids were successfully xenografted into NOD-scid IL2Rgnull (NSG) mice. The established organoids retained key histological features and genetic characteristics of the original tumors. These organoid models provide a novel and reliable platform for studying the biology of chondrosarcoma and may facilitate the development of effective therapeutic strategies for this treatment-resistant tumor.

  Study JGAS000834

• Integrated Methylation and Copy Number Analysis for Non-invasive Bladder Cancer Detection in Urine

  The molecular analysis of urine cell-free DNA (cfDNA) offers a non-invasive tool to advance bladder cancer (BC) management. Assessment of somatic copy number aberrations (SCNA) and DNA methylation, as singular or complementary analysis, have emerged as promising approaches for BC detection. Here, we developed an integrated analysis to assess both SCNA and targeted methylation changes from the same template molecules, named the iSECURE (integrated SEquencing-based Copy number and methylation analysis in URinE) method.

  Study EGAS50000001350

• Single nucleus and spatial transcriptomic characterization of prostate cancer versus normal controls

  10x Genomics Visium and Chromium platforms were used for spatial and single-nuclei RNA-sequencing, respectively. Cohort consisted of 8 prostate cancer patients (8 prostate cancer + 8 paired non-malignant control samples, fresh-frozen)

  Study EGAS50000001143

• Non-invasive bladder cancer cfDNA dataset

  The dataset contains 30 primary bladder cancer patients, 28 recurrent bladder cancer patients and 31 hematuria controls. Shallow WGS of cell-free DNA enzymatic methyl sequencing libraries was performed on an Illumina Novaseq S4 PE150bp. Samples are provided as raw reads without any prior processing.

  Dataset EGAD50000001935

• snRNAseq prostate cancer

  single-nucleus RNA seq characterization of human fresh frozen prostate cancer samples and non-malignant controls for the same patients. Biopsies were sectioned in 100 micron thick sections, adjacent to those used for spatial transcriptomics.

  Dataset EGAD50000001633

• Spatial transcriptomics prostate cancer

  Spatial transcriptomic characterization of human fresh frozen prostate cancer and non-malignant regions from the same patient. 100 micron thick sections were made from the biopsies, adjacent to snRNA sequencing, and subjected to 10x Genomics Visium ST analysis.

  Dataset EGAD50000001634

• Non-invasive bladder cancer cfDNA dataset DAC

  Dac EGAC50000000790

• IRCC

  DACs of Translational Cancer Medicine laboratory of Candiolo IRCC institute

  Dac EGAC50000000068

• Combination pembrolizumab and radiotherapy induces systemic anti-tumor immune responses in immunologically-cold non-small cell lung cancer

  This data set includes sequence files from whole exome sequencing and RNA sequencing from serial tissue and blood biospecimens from a phase 2 clinical trial of stereotactic body radiation therapy (SBRT) followed by pembrolizumab in metastatic non-small cell lung cancer (NSCLC; NCT02492568).

  Study EGAS50000000277

• scRNAseq + TCRseq of n-irAE patients

  Here we performed multimodal analysis (5'scRNAseq and TCR-seq) on PBMCs from cancer patients developing or not neurological adverse events (n-irAEs) following immune checkpoint inhibition (ICI) treatment.

  Study EGAS50000000603

• Error-corrected flow-based sequencing at whole genome scale and its application to circulating cell-free DNA profiling

  Differentiating sequencing errors from true variants is a central genomics challenge calling for error suppression strategies that balance costs when sparse material or ultra-rare variants require high-accuracy methods. For example, circulating cell-free DNA (ccfDNA) sequencing for cancer monitoring is limited by sparsity of circulating tumor DNA (ctDNA), abundance of genomic material in samples, library preparation error rates and sequencing errors. Whole-genome sequencing (WGS) can overcome the low abundance of ccfDNA by integrating signal across the mutation landscape, but higher cost limits adoption compared with targeted panels, where ccfDNA abundance limits maximal coverage depths. Here we applied deep (~120x) lower-cost WGS (Ultima Genomics) with analytic error correction for tumor-informed ctDNA detection within the part-per-million range. We further developed high-coverage duplex error-corrected WGS of ccfDNA, achieving 7.7x10-8 error rates, to assess disease burden in melanoma and urothelial cancer patients without matched tumor sequencing. Together, we show that deeply sequenced error-corrected WGS accurately calls somatic variants, demonstrating the feasibility of WGS for tumor-informed and tumor-agnostic ctDNA detection.

  Study EGAS50000000844

• Dataset of 10 WES from bladders tumors and PBMC of 4 non-muscle invasive bladder cancer patients

  WES (FASTQ files) of paired tumor and PBMC samples of non-muscle-invasive bladder cancer patients. All CTRL samples originate from PBMC. For patient UC2, DNA from 3 different synchronous tumors were extracted. DNA from tumors was extracted from fresh frozen tumors,except for patient UC4 (FFPE). NB : patients aliases are the following :ROXY : UC1, OMAD : UC2, MAKI : UC3, HAPE : UC4

  Dataset EGAD50000002008

• Dataset of 2485 CD8 T cells from non-muscle-invasive bladder cancer patients in context of BCG treatment

  FASTQ files from scRNAseq (smartseq2 protocol) from 2485 CD8 T cells from 4 non-muscle-invasive bladder cancer patients who received BCG treatment (induction treatment of 6 weekly instillations). Concerning the 'phenotype' column in metadata : pre-treatment samples include tumor samples ('Tumor') and normal adjacent bladder tissue ('Extratumor'). For post-treatment samples : no residual tumor was found in the bladder of the 4 patients after the BCG treatment . The post-treatment samples with 'Tumor' as phenotype denote samples from macroscopically suspect zones, but with microscopically no tumor detected.

  Dataset EGAD50000002007

• Dataset of 5 RNAseq from 3 non-muscle-invasive bladder cancer patients

  RNAseq (FASTQ files) of 5 tumor from 3 non-muscle-invasive bladder cancer patients. For patient UC2, RNA from 3 different synchronous tumors was extracted. Relating to the other datasets from the project : no RNA was available from patient UC4. NB : patients aliases are the following : ROXY : UC1, OMAD : UC2, MAKI : UC3, HAPE : UC4

  Dataset EGAD50000002009

• Processing of tissue and cfDNA samples of CRC patients using Active-seq

  In this study, we have developed a novel technology called Active-Seq (Azide Click Tagging for In Vitro Epigenomic sequencing), a base conversion-free technology used to profile the DNA methylation status of a sample, based on the isolation of DNA containing unmodified CpG sites using a mutated bacterial methyltransferase enzyme and a synthetically prepared cofactor analogue. We procured samples from colorectal cancer (CRC) patients including tumour tissue as well as normal adjacent tissues. The data enabled us to identify CRC-specific markers that could then be used to track and monitor the presence of tumour DNA in cell-free DNA plasma (cfDNA) samples procured in the same patients. The FASTQ files of all the colorectal cancer tissues, normal adjacent tissues as wells as the cfDNA samples are available in this submission. The data made available in this study have been used to outline an approach for tumour-informed disease profiling in colorectal cancer cfDNA samples using Active-Seq.

  Study EGAS50000001226

• Transcriptome Sequencing Data of High Grade Serous Ovarian Cancer

  Study EGAS00001004714

• Genomic Signatures of Intestinal Metaplasia in Six Countries with Varying Incidence of Stomach Cancer

  Intestinal metaplasia (IM) is a pre-cancerous condition associated with gastric cancer (GC), a deadly malignancy with varying geographic incidence. Performing a genomic analysis of over 1,500 IM samples from six countries, we identified 46 significantly mutated genes. We observed IM driver genes associated with high-risk populations and worse prognosis (ARID1A), members of the KRAS/MAPK signalling pathway (KRAS, BRAF, MAP2K1, MAP3K1, MAP2K4, NF1), and altered mucosal immunity (PIGR).

  Study EGAS50000001056

• RNA sequencing of intestinal metaplasia

  We perform bulk RNA-seq of 10 and single cell RNAseq of 2 intestinal metaplasia samples. We also perform stereoseq spatial transcriptomic analysis of 4 gastric cancer samples. The dataset contain cram files from 10 bulk RNAseq samples, and raw fastq files from 2 single cell RNAseq and 4 stereo-seq samples.

  Dataset EGAD50000002010

• Longitudinal single-cell RNA-seq data of metastatic ovarian cancer

  Study EGAS00001005010

• Neoantigens in bladder cancer

  Detection of spontaneous anti-neoepitope T-cell responses in non-metastatic bladder cancer patients

  Dac EGAC50000000740

• The data access committee for "Validation of cfDNA fragmentome analyses for early detection of liver cancer"

  Dac EGAC00001003543