7182 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