7073 results for "canc*"

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• Head and neck tumor organoid biobank for modelling individual responses to radiation therapy according to the TP53/ HPV status

  Head and neck cancers (HNC) represent an extremely heterogeneous group of diseases with a poorly predictable therapy outcome. Here, we have established a comprehensive molecularly and functionally characterized head and neck organoid biobank recapitulating the clinically relevant subtypes of TP53 mutant and human papillomavirus type 16 (HPV 16) infection-driven HNC. Organoids were exposed to radiotherapy and genetically engineered normal and tumor organoids were used for testing the direct functional consequences of TP53-loss and HPV infection. We identified subtype-associated transcriptomic signatures and pathological features, including sensitivity to TP53 stabilization by the MDM2 inhibitor Nutlin-3. TP53 loss-of-function alone was insufficient to promote radiation resistance, whereas HPV 16 oncogenes E6/E7 mediated radiosensitivity via induction of cell cycle arrest.

  Study EGAS50000001219

• CNA differences between RNA-based subtypes of PDAC

  Pancreatic ductal adenocarcinomas (PDAC) have a dismal prognosis with a 5-year survival of <5%. Chemoresistance and recurrences, seen in approximately 70% of PDAC patients, may partly be explained by intratumor heterogeneity (ITH) through which tumors may develop ‘escape routes’. In the Pancreas Multibiopsy (PM)-project we have obtained multiple fragments from pancreatic and other peri-ampullary carcinomas in order to reveal potential ITH and identify genetic aberrations that predict outcome after surgery and response to chemotherapy. CNA-profiles were used to complement the characterization of liabilities in PDAC that we identified previously using RNAseq in the form of epithelial, secretory, compound pancreatic, and mesenchymal subgroups that showed survival outcomes. Comparison of CNA-profiles between these transcriptomics-based subgroups (with 8, 3, 6, and 6 tumors respectively per group) showed differences, ranging from ‘quiet’(i.e. hardly any CNA) to ‘wild’(i.e. lots of CNA), but these were not statistically significant (Chi2 0.09). When differentiating between the classical and basal-like molecular subtypes of PDAC differences in CNA (high or low) were even less statistically significant (Chi2 0.292).

  Study EGAS50000001218

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

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

  Study EGAS50000001224

• Data Access Committee for Triple Negative Breast Cancer dataset

  Dac EGAC00001003584

• Microarray CDX or EDX from primary tumor and metastasis

  expression analysis of FACS sorted human cells from primary tumors and distant organs micrometastases in xenografts. Patient Derived xenografts were generated transplanting tumor cells from metastatic breast cancer patients into mammary fat pad of immunocompromised mice

  Dataset EGAD00010002711

• DAC for "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients."

  Dac EGAC00001003514

• WGS data for ctDNA monitoring for NSCLC in TRACERx

  Ultrasensitive circulating tumour DNA (ctDNA) detection can stratify clinical risk in early-stage non-small cell lung cancer (NSCLC). Here, we applied a whole-genome, tumour-informed approach to study ctDNA in more than 400 NSCLC of the TRACERx project

  Study EGAS50000001187

• BulkRNAseq - Notch Signaling Maintains a Progenitor-Like Subclass of Hepatocellular Carcinoma

  To identify the Notch signaling components expressed in both the human cancer cells and mouse stromal cells that typically comprise PDX tumors, we performed bulk RNA sequencing. Our results demonstrate that a JAG1-NOTCH2 signaling axis within the human cancer cell population drives the Notch dependency in the super-responder models, with NOTCH2 serving as the functionally relevant receptor.

  Study EGAS50000000515

• PEVOsq

  The PEVOData PEVOsq basket trial is an open-label, multi-center, phase II trial investigating the combination of pembrolizumab (an immune checkpoint inhibitor) with vorinostat (a histone deacetylase inhibitor). This trial focuses on treating patients with recurrent or metastatic squamous carcinomas, including cancers of the cervix, head and neck, anus, vulva/vagina, penis, and lung. The aim is to evaluate the efficacy and safety of this combination, with pembrolizumab administered every 3 weeks and vorinostat daily. Outcomes include overall response rate and progression-free survival.

  Study EGAS50000000731

• WGS of Five Pancreatic Cancer Patients-Tumor and Normal

  We performed whole genome sequence on tumor-derived and normal cell lines from patients who had terminal pancreatic cancer and consented for rapid autopsy upon their death. The 5 samples are from Dr. Christine Iacobuzio-Donahue's rapid autopsy program as reported in Boland et al. (PLOSOne, 2024, In Press, PMID 38352348).

  Study phs003775

• An Ultrasensitive Method for Detection of Cell-Free RNA

  Our study describes the development of a novel method for cell free RNA (cfRNA) analysis called RARE-Seq (Random priming &#38; Affinity capture of cell-free RNA fragments for Enrichment analysis by Sequencing). We find RARE-Seq improves the limit of detection for tumor-na&#239;ve cancer detection while maintaining high specificity. We explore the potential utility of RARE-Seq in diverse clinical applications, including non-invasive ctRNA genotyping, treatment resistance monitoring, and molecular characterization of non-malignant conditions.

  Study phs004091

• Pooled Mutant KRAS-Targeted Long Peptide Vaccine Combined with Nivolumab and Ipilimumab for Patients with Resected MMR-p Colorectal and Pancreatic Cancer

  We developed INtraCEllular Reverse Transcription with Sorting and sequencing (INCERTS), an approach to combine molecular indexing of receptor repertoires within intact cells and fluorescence-activated cell sorting (FACS). We demonstrate that INCERTS enables efficient processing of millions of cells from pooled human peripheral blood mononuclear cell (PBMC) samples while retaining robust association between T cell receptor (TCR) sequences and cellular phenotypes. We used INCERTS to discover antigen-specific TCRs from patients with cancer immunized with a novel mutant KRAS peptide vaccine. After ex vivo stimulation, 28 uniquely barcoded samples were pooled prior to FACS into peptide-reactive and non-reactive CD4+ and CD8+ populations. Combining complementary patient-matched single-cell RNA sequencing (scRNA-seq) data enabled retrieval of full-length, paired TCR alpha and beta chain sequences for future validation of therapeutic utility. Data available through dbGaP include scRNA-seq with matched TCR-seq.

  Study phs003425

• Single-cell RNA-seq of murine splenocytes from Bcl6tg/+ and Cd70-/-; Bcl6tg/+ diffuse large B-cell lymphoma mouse models and Cd70-/- and wild-type controls.

  Study EGAS00001007570

• Active-Seq of CRC patients

  This dataset contains 48 fastq files of samples derived from CRC patients, including colorectal cancer tissue, normal adjacent tissue and cfDNA samples, processed with the Illumina platform NovaSeq6000.

  Dataset EGAD50000001746

• Targeted panel sequencing of two patient-derived melanoma cell lines

  Targeted panel sequencing was conducted on patient-derived cell lines: Mel-DCC-11 (the parental line, sensitive to the BRAF inhibitor) and Mel-DCC-11-R (resistant to the BRAF inhibitor). The parental cell line was generated from disseminated cancer cells (DCCs) obtained from a lymph node sample of a melanoma patient. The resistant cell line was generated from the parental one through exposure to Vemurafenib. Normal peripheral blood lymphocytes from the same patient served as the control for comparison. Sequencing on NovaSeq6000. Fastq files.

  Dataset EGAD50000001745

• Health Information National Trends Survey-SEER (HINTS-SEER)

  HINTS-SEER is a cross-sectional survey that sampled cancer survivors from three different SEER cancer registries. Sampling frames of survivors from each registry were stratified by time since diagnosis and race/ethnicity, with non-malignant tumors and non-melanoma skin cancers excluded. Respondents who consented completed a self-administered questionnaire sent through the mail and resulted in a total sample of 1,234 respondents. The goal of HINTS-SEER was to better understand the communication needs and practices, information preferences, risk behaviors and cancer knowledge of cancer survivors using a modified version of the Health Information National Trends Survey (HINTS) specifically designed for cancers survivors. Demographic information on the survivors showed that over 60% of the sample was 10 or more years since diagnosis with the most common cancers being male reproductive (24.6%), female breast (23%) and melanoma (9.6%) and gastrointestinal (8.6%). De-identified data is available in SAS, SPSS, and STATA formats, as part of a data package that also includes a history document, methodology report, data analysis recommendations, and a codebook.

  Study phs004065

• Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study

  Study population The WECARE Study is an international multicenter population-based case-control study of cases with asynchronous contralateral breast cancer (CBC) and individually matched controls with unilateral breast cancer (UBC). Recruitment and data collection for the WECARE Study were conducted in two phases, herein referred to as WECARE I (2001&#8211;2004) and WECARE II (2009&#8211;2012). The study design of the first phase (WECARE I) has been described in detail elsewhere [Bernstein JL, et al 2004, PMID: 15084244]; the second phase (WECARE II) employed a nearly identical approach [Langballe R, et al 2016, PMID: 27400983]. Participants in each phase were identified through eight population-based cancer registries, including six in the United States that contribute to the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program: Los Angeles County Cancer Surveillance Program; Cancer Surveillance System of the Fred Hutchinson Cancer Center (Seattle region, WA); State Health Registry of Iowa; Cancer Surveillance Program of Orange County/San Diego-Imperial Organization for Cancer Control (Orange County/San Diego, CA); the Greater Bay Area Cancer Registry (San Francisco Bay Area region and Santa Clara region, CA); and the Sacramento and Sierra Center Registry (Sacramento region, CA). Participants were additionally identified using the Ontario Cancer Registry (Canada) and the Danish Breast Cancer Cooperative Group Registry, supplemented by data from the Danish Cancer Registry. The study protocol was approved by the institutional review or regulatory ethics boards at each study site. Data collection Study participants were interviewed by telephone using a structured questionnaire aimed at evaluating known or suspected breast cancer risk factors, including personal demographics, medical history, menstrual and reproductive history, family history of cancer, use of hormones, smoking, and alcohol intake. Risk factor status was assessed during the period prior to first diagnosis, as well as between first diagnosis and reference date (i.e., the at-risk period for CBC). Detailed data on treatment and tumor characteristics were obtained directly from cancer registry records or by abstracting medical records, including pathology and surgical reports, radiation oncology clinic notes, and systemic adjuvant treatment data. Complete medical treatment history information was collected, and for all women who received radiotherapy, the radiation dose to the contralateral breast was reconstructed using radiotherapy records and radiation measurements. Biospecimens were collected from study participants for genotyping: blood collected from WECARE I women; and saliva collected from WECARE II women.

  Study phs003945

• Childhood Cancer Data Initiative (CCDI): Texas Pediatric Patient Derived Xenograft 

  The DNA/RNA samples of patients for which PDX models were developed were from a population of children, adolescents, and young adults from South Texas. Consent was obtained for collection of malignant and non-malignant tissue samples for genetic analysis and for the development of models to study new ways to treat cancer. For additional details, please refer to these publications: PMID: 37915590; PMID: 37990009.

  Study phs003215

• MP2PRT: Evaluation of an Inflammation Polygenic Risk Score (iPRS) to Predict Cancer Related Cognitive Impairment and Fatigue in Patients Receiving Chemotherapy for Non-Metastatic Breast Cancer in URCC0701 and URCC10055

  This study is a secondary analysis of cancer related cognitive impairment (CRCI) and cancer related fatigue (CRF) among participants in URCC0701 and URCC10055 from the University of Rochester NCI Community Oncology Research Program (NCORP) Research Base. CRCI and CRF are common, troublesome, and dose-limiting toxicities reported by patients undergoing breast cancer chemotherapy that have an etiologic basis linked to low-grade systemic inflammation. Chronic, low-grade systemic inflammation is, in part, genetically determined with common single nucleotide polymorphisms (SNPs) capturing variation across individuals. This study aimed to 1) determine whether an inflammation polygenic risk score (iPRS) is associated with CRCI or CRF, 2) determine whether the relationship between the iPRS and CRCI or CRF is modified by exercise at the time of cancer treatment, 3) identify SNPs associated with serum cytokines measured at the time of cancer treatment, and 4) identify novel CRCI- and CRF-associated risk SNPs via genome-wide association analyses. We found that there was a significant inverse correlation between the iPRS and change in fatigue score from pre-chemotherapy to post-chemotherapy while there was no statistically significant association between the iPRS and cognitive impairment score. The inverse relationship between the iPRS and fatigue may be explained in part by the finding that the iPRS was also significantly associated with greater pre-chemotherapy fatigue, suggesting that women with a genetic predisposition to low-grade systemic inflammation (i.e., high iPRS) have more fatigue at the time of breast cancer diagnosis and, therefore, are less likely to worsen over the course of treatment. In contrast, women with a low iPRS had significantly less fatigue pre-chemotherapy and a significant worsening of fatigue from pre- to post-chemotherapy. The relationship between the iPRS and fatigue remained after adjustment for patient and cancer treatment covariates and was most pronounced in women who reported regularly exercising for at least 6 months prior to starting their cancer treatment. Exploratory genome-wide analysis identified a novel risk locus on chromosome chr6q27, tagged by rs9365961, associated with CRCI. This locus is upstream of TBXT, which encodes an embryonic nuclear transcription factor previously associated with susceptibility to neural tube defects. The genome-wide SNP data, patient-reported CRCI and CRF outcome measures, and covariate data used in this analysis are available through dbGaP.

  Study phs003688

• Colon Cancer Family Registry (Colon CFR)

  The Colon Cancer Family Registry Cohort (CCFRC www.coloncfr.org) is a cohort of families recruited through six study sites located in the USA, Canada, Australia, and New Zealand. The CCFRC was formed as a resource to support studies on the etiology, prevention, and clinical management of colorectal cancer. Recruitment protocols fall broadly into two main categories: population-based and clinic-based ascertainment. Between 1998 and 2013, the CCFR recruited and interviewed probands who were either recently diagnosed with colorectal cancer that was reported to state or regional population cancer registries in the United States (Washington, California, Arizona, Minnesota, Colorado, New Hampshire, North Carolina, and Hawaii), Australia (Victoria), and Canada (Ontario) or were from multiple-case families referred to family-cancer clinics in the United States (Mayo Clinic in Rochester, Minnesota, and Cleveland Clinic in Cleveland, Ohio), Australia (Melbourne, Adelaide, Perth, Brisbane, and Sydney), New Zealand (Auckland), and Canada. Cases with known familial adenomatous polyposis were excluded. Once recruited, probands were asked for permission to contact their relatives for recruitment. Collectively, we have enrolled 42,49874 participants in 15,048 families who participated in standardized protocols used to collect information regarding family cancer history and colorectal cancer risk factors and biospecimens. All participants of population-based case families (excluding control-families) and clinic-based families are asked to provide updates on their personal and family history of cancer as well as their history of surgery, cancer screening, and some risk factors every 4-5 years either by telephone interview or by self-completed questionnaire via mail or online (PMID: 17982118).

  Study phs002733

• Childhood Cancer Data Initiative (CCDI): Molecular Characterization Initiative

  The National Cancer Institute's (NCI) Childhood Cancer Data Initiative (CCDI) focuses on the critical need to collect, analyze, and share data to address the burden of cancer in children, adolescents, and young adults (AYAs). The Molecular Characterization Initiative (MCI) will further the CCDI's goals by providing access to better diagnostic tests for pediatric and AYA patients. The molecular characterizations of solid tumors, soft tissue sarcomas, and rare diseases are performed in a CLIA-certified setting as results may be used to screen for and/or confirm clinical trial eligibility, direct treatment, or otherwise contribute to the conduct of the trial. The following molecular characterization assays were performed:Tumor/Normal Whole Exome sequencing Methylation arraysArcher fusion panel Deidentified clinical reportsNote: New data will be added periodically, please check the CCDI Hub Explore site for updates.

  Study phs002790

• Identification and phenotypic characterization of neoantigen-specific cytotoxic CD4+ T cells in endometrial cancer

  Tumor-reactive CD4+ T cells often accumulate in the tumor microenvironment (TME) in human cancer, but their functions and roles in anti-tumor responses remain elusive. Here, we investigated the immunopeptidome of HLA class II (HLA-II)-positive endometrial cancer with inflamed TME using a proteogenomic approach. We identified HLA-II neoantigens, one of which induced polyclonal CD4+ tumor-infiltrating lymphocyte (TIL) responses. We experimentally demonstrate that neoantigen-specific CD4+ TILs lyse target cells in an HLA-II-dependent manner. Single cell analysis of the TME coupled with T cell receptor (TCR) sequencing revealed the presence of CD4+ T cell clusters characterized by CXCL13 expression. The CXCL13+ clusters contained two subclusters with distinct cytotoxic gene expression patterns. The identified neoantigen-specific CD4+ T cells were found exclusively in one of the CXCL13-positive subclusters characterized by GZMB and CCL5 expression. These results demonstrate the involvement of tumor reactive CD4+ T cells with cytotoxic function in immune surveillance of endometrial cancer and reveal their transcriptomic signature.

  Study JGAS000766

• Breast cancer sequencing data

  Study EGAS00001007336

• Spatial transcriptomics analysis of triple negative breast cancers

  While triple negative breast cancer (TNBC) is known to be heterogeneous at the genomic and transcriptomic levels, spatial information on tumor organization and cell composition is still lacking. Here, we investigated TNBC tumor architecture including its microenvironment using spatial transcriptomics on a series of 92 patients. We performed an in-depth characterization of tumor and stroma organization and composition using an integrative approach combining histomorphological and spatial transcriptomics. Furthermore, a detailed molecular characterization of tertiary lymphoid structures led to identify a gene signature strongly associated to disease outcome and response to immunotherapy in several tumor types beyond TNBC. A stepwise clustering analysis identified nine TNBC ecotypes, further validated in external datasets. Several ecotypes were associated with disease outcome and characterized by potentially actionable features. In this work, we provideThis is the largest TNBC series providing a comprehensive insight into the complexity of TNBC ecosystem with potential clinical relevance, opening avenues for treatment tailoring including immunotherapy. All the processed data needed to replicate the results from the publication (counts, images, clinical data, etc) are available on Zenodo: https://zenodo.org/records/14204217

  Study EGAS50000000475

• Spatial transcriptomics analysis of triple negative breast cancers

  Spatial transcriptomics analysis of triple negative breast cancers Both bulk sequencing and ST were performed Counts, images etc are available at https://zenodo.org/doi/10.5281/zenodo.8135721

  Dataset EGAD50000000686

• Human prostate cancer plasma cfRNA study - raw data

  mRNA capture sequencing on plasma sample from 132 prostate cancer patients and 48 control donors.

  Study EGAS50000001265

• prostate cancer plasma cfRNA

  Dataset contains mRNA capture sequencing data from plasma of 180 different human donors: 132 prostate cancer patients (PRAD) and 48 cancer-free controls. Samples were sequenced on a NovaSeq X and sequencing data is provided in FASTQ format.

  Dataset EGAD50000001805

• non-malignant plasma cfRNA

  Dataset contains mRNA capture sequencing data from plasma of 125 different human donors: 88 patients with a non-malignant disease and 37 cancer-free controls. Samples were sequenced on a NovaSeq X and sequencing data is provided in FASTQ format.

  Dataset EGAD50000001806

• Repertoire and clinical hierarchy of AR locus alterations in castration-resistant prostate cancer

  Somatic alterations to the androgen receptor (AR) gene are pivotal drivers of treatment resistance in metastatic castration-resistant prostate cancer (mCRPC), but their prevalence, clinical impact, and etiology remain incompletely understood. Here, we analyzed 3399 plasma cell-free DNA samples and 1988 leukocyte DNA samples from 1995 metastatic prostate cancer patients with matched clinical data and extensive AR locus coverage.

  Study EGAS50000001101

• Targeted Illumina sequencing of 3399 plasma cfDNA samples and 1988 leukocyte DNA samples from 1995 metastatic prostate cancer patients

  Blood samples were collected from eight clinical trials and a British Columbia-based biobank. All plasma cfDNA and leukocyte DNA samples were processed with uniform methodology, and underwent targeted sequencing using a custom hybridization capture panel and Illumina instruments. Four different generations of custom hybridization capture panel were used, all providing coverage of the complete coding regions of 72 prostate cancer genes, and later panel generations also providing exhaustive coverage of the AR locus (including introns and flanking regulatory regions), as well as a genome-wide SNP grid for copy number analysis.

  Dataset EGAD50000001594

• Evaluation of Local Response of Prostate Cancer to Irradiation Using Multiparametric MRI and MR-Guided Biopsies

  The purpose of this study was to determine the rate of local recurrence in patients with intermediate and high risk prostate cancer treated with radiotherapy. In this study, multiparametric MRI was first performed, and biopsy tissue was acquired from cancerous regions detected on MRI. Blood samples were also taken. DNA and RNA were extracted from tissue taken at baseline. DNA was used for whole exome sequencing (WES). RNA was used for gene expression microarray. Each patient then received radiation therapy with androgen deprivation therapy.

  Study phs001821

• Establishment and Genomic Validation of Novel Patient-Derived Xenograft Models for Drug Discovery in Gastrointestinal Stromal Tumor

  This dataset contains targeted next-generation sequencing data generated with the Illumina TruSight Oncology 500 (TSO500) assay from six gastrointestinal stromal tumors (GIST) and matched patient-derived xenograft (PDX) models established at Fox Chase Cancer Center (Philadelphia, PA). GIST are most commonly driven by activating mutations in KIT or PDGFRA, and this study focused on KIT-mutant tumors. All PDXs were derived from metastatic patient tumors previously treated with one or more tyrosine kinase inhibitors (TKIs). PDXs were maintained through series of passages and represents in vivo models of differential TKI sensitivity. The dataset represents a detailed comparison of mutational profiles between primary tumors and corresponding PDXs across passages, enabling studies of genomic stability, resistance mechanisms, and the evaluation of novel therapeutic strategies in GIST.

  Study phs004185

• Analysis of genes related to the oncogenesis, progression or effectiveness of drug therapies of urological tumors .

  To clarify the oncogenesis and the progression mechanism of urological tumors, we continuously collect tumor samples of our patients with high quality. Then we used them to comprehensive analyses such as genome sequencing or epi-genome sequencing. Through these analyses, we aim for elucidating the oncogenesis or for developing newly treatment strategies of each cancer.

  Study JGAS000737

• CLL Genome

  The Chronic Lymphocytic Leukemia (CLL) Genome Project aims to identify genetic alterations involved in the development and progression of the CLL, which are still unknown, with the objective of generating a comprehensive catalogue of genetic alterations in 500 independent tumours. The CLL Genome Project, as a contributing member of the International Cancer Genome Consortium (ICGC), has the purposes of creating diagnostic tools, discovering therapeutic targets and developing new strategies that will allow a customized therapy for CLL in order to make it more precise and effective. This study consists of two datasets. EGAD00001000023 described in the Nature paper (2011), Whole-genome sequencing identifies recurrent mutations in chronic lymphocytic leukaemia, and the dataset EGA00001000044 & & EGAD00001000083 described in the Nature (2011) paper, Exome sequencing identifies recurrent mutations of the splicing factor SF3B1 gene in chronic lymphocytic leukemia.Additional data generated within the ICGC-CLL genome project can be found in studies EGAS00001000374 and EGAS00001001306

  Study EGAS00000000092

• DNTR sequencing data of paediatric acute lymphoblastic leukemia

  This study used the DNTR-seq method in leukaemia samples to profile the whole-genome and mRNA jointly in single cells. Direct tagmentation is used in a collection of single-cell whole genome sequencing (scWGS) methods, including DNTR-seq, which provide high quality data at ultra-low to low coverage. The overall goal was to characterize the genetic and transcriptional heterogeneity of cancer samples. To infer clonal structure and evolutionary history, copy number analysis based workflows were implemented. Bone marrow mononuclear cells from pediatric acute lymphoblastic leukemia samples were FACS sorted into 384 plates to generate the DNA and RNA profiles.

  Study EGAS50000001247

• Childhood B-cell acute lymphoblastic leukemia genomic and transcriptomic data

  The aim of the two studies was: 1) to genetically characterise childhood leukemia patients that lacked established cytogenetic abnormalities (termed B-other leukemia) and assess the clinical features of recurrent genetic abnormalities. 2) Assess the accuracy of whole genome sequencing as a diagnostic genetic test in childhood leukemia, relative to other traditional methods (karyotyping, FISH, MLPA) and whole transcriptome sequencing. As a result, this study includes targeted DNA-sequencing, whole genome sequencing and whole transcriptome sequencing data on childhood leukemia patients enrolled on UK clinical trials (UKALL2003 and UKALL2011).

  Study EGAS00001006863

• Convergent evolution towards CD38 biallelic loss is a recurrent mechanism of resistance to anti-CD38 antibodies in multiple myeloma.

  Monoclonal antibodies directed against CD38 are a therapeutic mainstay in multiple myeloma (MM). While they have contributed to improved outcomes, most patients will still experience disease relapse. Despite their ubiquity, little is known about tumor-intrinsic mechanisms of resistance to these drugs. Antigen escape, whereby tumor cells alter expression of cell surface immunotherapy targets, has been proposed as a potential avenue, and has been seen with other immunotherapies in MM. Yet, it is unknown whether MM cells can develop permanent resistance to anti-CD38 antibodies by acquiring genomic events leading to biallelic disruption of the CD38 gene locus. Here, by using whole genome and whole exome sequencing data from 701 newly diagnosed patients, 72 patients at relapse with naivety to anti-CD38 antibodies, and 52 patients collected at relapse following anti-CD38 antibodies, we report biallelic inactivation of CD38 as a recurrent mechanism of resistance in 6% of patients, often via convergent evolution where distinct subclones are advantaged towards the same selective endpoint within the same patient. Monoallelic loss of the CD38 locus was seen in another 14% post-CD38-directed therapy. Three of the cases with biallelic events on CD38 presented with missense mutations and retained CD38 expression. Functional work demonstrated that two of these mutations decreased binding affinity and antibody-dependent cellular cytotoxicity of commercial antibodies Daratumumab and Isatuximab. However, the third mutation (R140G) provided relative resistance only towards one commercial product. Given that patients are often rechallenged with CD38 antibodies following disease progression, these data support the need for next generation sequencing to guide treatment selection.

  Study EGAS50000000709

• Single cell atlas of relapsed/refractory large B-cell lymphoma

  Relapsed/refractory large B-cell lymphomas (rrLBCL) are clinically and biologically diverse lymphoid malignancies with intricate microenvironments that play a key role in disease development. In this study, we used single-nucleus multiome profiling along with bulk DNA and RNA sequencing on 120 tumor and control biopsies to comprehensively characterize the various cell types and subsets found in rrLBCL tumors.

  Study EGAS50000001293

• Fluctuating DNA methylation tracks cancer evolution at clinical scale

  Long-read Nanopore data of fCpGs from Gabbutt & Duran-Ferrer (2025) for developing the EVOFLUx method to study cancer evolution via DNA methylation fluctuations.

  Study EGAS50000001192

• MorphoITH: A Framework for Deconvolving Intra-Tumor Heterogeneity Using Tissue Morphology

  This study introduces MorphoITH, a framework for deconvolving intra-tumor heterogeneity (ITH) in clear cell renal cell carcinoma (ccRCC) based on tissue morphology from histopathological slides. The study tested MorphoITH's ability to capture different aspects of morphology and to reflect genetic ITH. The data deposited here is derived from a morphology guided multi-regional sequencing dataset used to study the relationship between morphology and genetic evolution. This dataset consists of whole exome sequencing of tumor from multiple sites and adjacent normal samples which were collected from two patients treated in affiliated hospitals of the University of Texas Southwestern Medical Center (UTSW), including Parkland Hospital.

  Study EGAS50000001064

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

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

  Dataset EGAD50000001813

• WGS data from COMPASS Trial

  WGS data for pancreatic cancer samples (COMPASS Trial; Knox et al., Journal of Clinical Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=263 tumour/normal pairs).

  Dataset EGAD50000001832

• WGS data for Pancreatic Cancer samples (misc.)

  WGS data for pancreatic cancer samples. These are miscellaneous samples which are part of a tandem duplicator phenotype paper (Farooq et al, NPJ Precision Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina NovaSeq 6000 and aligned against GRCh38 (n=7 tumour/normal pairs).

  Dataset EGAD50000001833

• WGS data for Pancreatic Cancer samples (resection cohort)

  WGS data from pancreatic cancer samples. These are part of a resected cohort from a tandem duplicator phenotype paper (Farooq et al, NPJ Precision Oncology, 2025). The dataset includes tumour and normal BAM files sequenced on Illumina HiSeq/NovaSeq and aligned against GRCh38 (n=189 tumour/normal pairs).

  Dataset EGAD50000001834

• Excised DNA Circles from V(D)J Recombination Promote Relapsed Leukaemia

  In this study, we show that ESCs replicate and persist through many cell generations. High ESC copies at diagnosis of BCP-ALL strongly correlate with subsequent relapse. These data provide the first demonstration that the V(D)J recombination by-product, when replicated to elevated levels, potently associates with the V(D)J recombinase to cause adverse disease outcomes.

  Study EGAS50000000407

• Extrachromosomal DNA-driven oncogene dosage heterogeneity determines therapy response in neuroblastoma

  Characterization of ecDNA copy number-dependent plasticity of neuroblastoma patient-derived xenograft models. Data corresponds to single-cell G&T sequencing from an untreated neuroblastoma PDX and single-cell multiome ATAC + gene expression sequencing of a SHH medulloblastoma tumor.

  Study EGAS50000001040

• The Oral Mycobiome and Risk of Pancreatic Cancer

  The purpose of our study was to assess the influence of oral microbiota on the development of pancreatic cancer. Our preliminary case-control studies showed that oral carriage of a periodontal pathogen is related to increased risk for pancreatic cancer. We hypothesize that the oral bacteria and fungi are associated with risk of pancreatic cancer. We conducted a prospective study nested in two large well-established U.S. cohorts to determine whether the oral bacterial and fungal microbiome is associated with subsequent risk of pancreatic cancer.

  Study phs003994

• Center for Cancer Genomics (CCG) Cancers of Unknown Primary Project (CUPP)

  The Cancers of Unknown Primary Project (CUPP) aims to characterize difficult tumor types with the goal of determining future best treatment practices. NCI will utilize whole exome sequencing, copy-number variation, DNA methylation in conjunction with transcriptome sequencing to provide a comprehensive genomic landscape of Cancers of Unknown Primary (CUP). The samples will be processed and submitted for genomic characterization using pipelines and procedures established within the Center for Cancer Genomics (CCG).

  Study phs001801

• Target bisulfite sequencing of uterine cervical cancer

  We performed targeted bisulfite sequencing of the HLA-A promoter region in cervical tissue samples to investigate DNA methylation patterns that regulate immune recognition and antigen presentation, which may influence viral immune surveillance and malignant transformation in cervical pathology.

  Study JGAS000825

• Whole exome sequencing of uterine cervical cancer

  We conducted whole-exome sequencing of cervical tissue samples to evaluate HLA loss of heterozygosity (LOH) and B2M gene mutations, which are key mechanisms of immune evasion that allow cancer cells to escape T-cell recognition and antigen presentation.

  Study JGAS000824

• Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma - RNA validation cohort

  This reposiroty contains bulk RNA data generated by Blood Cancer Research Group (Ostrava, Czech Republic) as a part of publication named "Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma" published in Hemapshere.

  Study EGAS50000001212

• Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma - WGS validation cohort

  This reposiroty contains bulk WGS data generated by Blood Cancer Research Group (Ostrava, Czech Republic) as a part of publication named "Elevated circulating tumor cells reflect high proliferation and genomic complexity in multiple myeloma" published in Hemapshere.

  Study EGAS50000001211

• Drug Development against Tumor Microtube Networks in Glioblastoma

  Glioblastomas are aggressive brain tumors that resist current therapies by hijacking neurodevelopmental programs to invade the brain and form resilient multicellular networks. Tumor Microtubes (TMs), neurite-like processes extended by cancer cells, drive this pathobiology, but TM-inhibiting drugs are lacking. Here we developed a comprehensive, combined in vitro and in vivo drug screening approach, including novel AI-based analysis tools of TM parameters. Two Protein Kinase C (PKC) activators, TPPB and PMA, exhibited robust inhibition of TM formation in cell-based assays. Since unconnected glioblastoma cells exhibit increased sensitivity to cytotoxic therapy in vivo, brain tumor-bearing mice received TPPB, the most consistent TM-inhibiting compound, in combination with radiotherapy. Long-term intravital 2-photon microscopy confirmed anti-TM and anti-tumor effects of the co-treatment. Mechanistically, TPPB treatment inhibited several key molecular and functional components of TM-related glioblastoma cell network communication and decreased the expression of TTYH1, a key driver of invasive TMs. By establishing a novel screening pipeline for anti-TM drug development, our study identifies a druggable TM master regulator pathway and a small molecule with robust anti-TM effects. It provides a proof-of-principle that disrupting TMs and disconnecting tumor networks is a pharmacologically feasible strategy to make therapies against glioblastoma more effective.

  Study EGAS50000000477

• Liquid biopsy to identify taxane resistance in castration-resistant prostate cancer patients

  Taxanes are life-prolonging treatments for patients with advanced prostate cancer. However, treatment resistance and lethal disease invariably develops. We here used liquid biopsies to identify and characterize resistance to cabazitaxel using a targeted sequencing panel (PCF-SELECT).

  Study EGAS50000001292

• Targeted sequencing data on sequential liquid biopsy samples from mCRPC patients receiving cabazitaxel

  Sequencing data from mCRPC patients receiving cabazitaxel. Targeted sequencing data of prostate cancer relevant genes using the PCF-SELECT capture panel. cfDNA from baseline, on-treatment and progression samples taken on cabazitaxel were sequenced as well as patient match WBC DNA

  Dataset EGAD50000001840

• PCF SELECT data on liquid biopsy samples from 3 clinical studies on prostate cancer patients

  Dac EGAC50000000758

• Longitudinal analysis of bone marrow heterogeneity reveals the co-evolution of malignant B cells and their T-cell niche supporting follicular lymphoma persistence

  Follicular Lymphoma (FL) is an indolent lymphoid malignancy characterized by cycles of remission and relapse, reflecting the inability of current therapies to fully eradicate tumor cells. Our hypothesis is that rare cancer precursor/persister cells (CPCs) evade treatment by homing to a protective tumor microenvironment, particularly within the bone marrow (BM), and/or by adopting specific cellular states, and form a rare reservoir of residual cells seeding lymphoma recurrence. To adress this, we collected paired BM samples at diagnosis and one year post-therapy from a clinical trial (FLIRT trial, NCT02303119) and applied multi-modal single-cell analysis to dissect the transcriptomics determinants of rare drug-tolerant persister cells and their surrounding T-cell niche.

  Study EGAS50000001295

• germline pathogenic variants found in African patients of prostate cancer

  70 new blood samples added in this project

  Study EGAS50000001132

• 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

• an integrated molecular study of clear cell renal cell carcinoma (ccRCC) including whole-genome/exome and RNA sequencing as well as array-based gene expression/copy-number/methylation analyses

  Study EGAS00001000509

• 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&#38;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, &#8220;Daratumumab-Based Response-Adaptive Therapy for Older Adults With Newly Diagnosed Multiple Myeloma.&#8221; 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 &#8216;a') with Daratumumab and Dexamethasone, and at cycle 2 day 22 (C2D22, i.e., 60 days after induction therapy start, denoted by &#8216;b'). For three NDMM patients, we also have samples at relapse (denoted by &#8216;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

• Adaptive Therapy Exploits Fitness Deficits in Chemotherapy-Resistant Ovarian Cancer to Achieve Long-Term Tumor Control Open Access

  Drug resistance results in poor outcomes for cancer patients. Adaptive therapy is a potential strategy to address drug resistance that exploits competitive interactions between sensitive and resistant subclones. Here, we showed that adapting carboplatin dose according to tumor response (adaptive therapy) significantly prolonged survival of murine ovarian cancer models compared to standard carboplatin dosing, without increasing mean daily drug dose or toxicity. Platinum resistant ovarian cancer cells exhibited diminished fitness when drug was absent in vitro and in vivo, which caused selective decline of resistant populations due to reduced proliferation and increased apoptosis. Conversely fitter, sensitive cells re-grew when drug was withdrawn. Using a bioinformatics pipeline that exploits copy number changes to quantify the emergence of treatment resistance, analysis of cell‐free DNA obtained longitudinally from ovarian cancer patients during treatment showed subclonal selection through therapy, and measurements of resistant population growth correlated strongly with disease burden. These preclinical findings pave the way for future clinical testing of personalized adaptive therapy regimens tailored to the evolution of carboplatin resistance in individual ovarian cancer patients.

  Study EGAS50000001142

• 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

• WES dataset

  Associated with Molecular biomarkers in progression from refractory celiac disease to the lethal cancer variety enteropathy associated T cell lymphoma (EATL) Study. Whole Exome Sequencing (WES) of 63 samples. WES analysis done to detect mutations and copy number aberration predictive for progression from RCD to EATL.

  Dataset EGAD50000001164

• 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

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

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

  Study EGAS50000001313

• 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