7073 results for "canc*"

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• A Phase II Study: CRS207/GVAX Plus Anti-PD1 and Anti-CTLA4 Recruits Mesothelin- and KRAS-Specific T cells into PDAC

  This study examined immunologic correlatives from a phase II study evaluating CRS207/GVAX vaccines in combination with anti-PD1 and anti-CTLA4 in metastatic pancreatic cancer (NCT03190265). Arm A received CRS207/GVAX with anti-PD1 and anti-CTLA4 therapy; Arm B received CRS207 with anti-PD1 and anti-CTLA4 therapy. Patients undergoing treatment in this trial had peripheral blood mononuclear cells (PBMCs) and tumor tissue biopsied serially at pre-treatment and on-treatment timepoints. Single-cell RNA/TCR sequencing was employed on PBMCs. Bulk RNA/TCR sequencing was employed on tumor tissues. We identified treatment-enriched inflammatory pathways as well as T cell repertoires.

  Study phs003798

• Whole Genome Sequencing for Metastatic Mutational Burden in Extraskeletal Myxoid Chondrosarcoma

  Extraskeletal myxoid chondrosarcoma (EMC) is an ultra-rare cancer. Though it has a favorable prognosis and an indolent course, it has high rates of local recurrence and metastasis to the lungs. EMC is most often characterized by a translocation involving the NR4A3 gene most often fusing with EWSR1, leading to constitutive expression of NR4A3, the biological significance of which is unknown. Our study presents a case of EMC with case-matched lung and advanced pelvic metastases. We conducted Whole Genome Sequencing to examine differences in the mutational landscape at two different stages of metastasis. This is the first study to our knowledge to analyze mega-base scale structural variants (SVs) in EMC. Our data validates copy number variants (CNVs) found in previous studies. While the primary tumor and lung metastasis had similar somatic variations and CNVs, the pelvic metastasis had more SVs with especially increased mutational burden of SVs in chromosome 2. This suggests that different molecular drivers appear in more advanced, relapsing EMC compared with the primary tumor and early lung metastasis. The sequencing data is available through dbGaP.

  Study phs003305

• CSER: Exome Sequencing in Diverse Populations in Colorado and Oregon/CHARM Cancer Health Assessments Reaching Many

  The CHARM (Cancer Health Assessment Reaching Many) study, part of the Clinical Sequencing Evidence-Generating Research (CS.ER2) effort, aimed to assess the utility of clinical exome sequencing and how it affects care in diverse populations. The study population included adults at risk for hereditary cancer syndromes. The primary objective was the implementation of a hereditary cancer risk assessment program in healthy 18-49 year-olds in primary care settings within a vertically integrated health delivery system (Kaiser Permanente) and a federal qualified health center (Denver Health). The investigators aimed to assess clinical exome sequencing implementation and interpretation, as well as tailored interactions for low health literacy including a contextualized consent process, and a modified approach to results disclosure and genetic counseling. The investigators were also assessing the clinical utility (healthcare utilization and adherence to recommended care) and personal utility of primary and additional results from clinical exome sequencing, and evaluate the ethical and policy implications of considering personal utility of genomic information decisions for health care coverage.Sequencing and analysis for CHARM was conducted at the Northwest Clinical Genomics Laboratory, University of Washington, Seattle (https://nwgc.gs.washington.edu/).

  Study phs002111

• Genomic and Immune Profiling of Breast Cancer Brain Metastases

  Previous work has shown that breast cancer brain metastases (BCBrM) can have unique molecular profiles compared to extracranial tumors (ECTs), resulting in some patients demonstrating subtype switching between primary/extracranial tumors and brain metastases. Description of the biology of BCBrM and associations between biological features and clinical outcomes, particularly between molecular intrinsic subtypes, will facilitate the design of rational therapies for patients with BCBrM. To better characterize the molecular profiles of BCBrM, we conducted whole exome sequencing (WES) and total RNA sequencing (RNA-Seq) on BCBrM tissues, regardless of clinical or molecular subtype, obtained from a cohort of 42 patients from Duke University Medical Center. This cohort adds valuable patient samples to the field and enables strengthened investigation of somatic mutations, copy number alterations, gene expression profiles, and immune populations within and between BCBrM patients and other similar cohorts. The Duke BCBrM cohort includes clinical and molecular annotation of the 42 patient specimens and their associated WES and RNA-Seq data. Clinical and molecular (PAM50) intrinsic subtypes in ECTs and brain metastases were largely concordant within patients. There were observed differences in intrinsic subtype calls between frozen and FFPE specimens of the same tissue, with discordance mostly observed with LumB calls. Copy number alterations in chromosomal regions included clinically relevant genes, and somatic alterations were largely conserved within patients across matched samples, with few genes, including TP53, being recurrently altered in the majority of patient specimens. In matched FFPE brain metastasis and ECT samples, we observed differentially expressed genes and pathways that had increased or decreased expression in brain metastasis, including in oxidative phosphorylation and DNA repair. Survival outcomes for patients differed by intrinsic molecular subtypes, with some association between expression of select gene pathways and survival. Data available through dbGaP will be the sequencing data and sample attributes from BCBrM tissues obtained from 42 patients from Duke University Medical Center.

  Study phs003673

• MSK SPECTRUM - SPatiotemporal Evolution of Cancer Traced Using Multimodalities

  MSK SPECTRUM is a multi-modal, interdisciplinary prospective study of spatiotemporal determinants of high-grade serous ovarian cancer (HGSOC) evolution, treatment and response. Accounting for ~80% of ovarian cancers, HGSOC is the most lethal gynecological malignancy and is a cancer of major unmet clinical need. Challenges in disease management relate to several unresolved questions about disease biology and diagnostic modalities. Prospective longitudinal collection of tissues and blood from laparoscopic biopsies and debulking surgeries enable multi-modal molecular measurements. The program brings together formidable expertise at Memorial Sloan Kettering Cancer Center (MSKCC) across the disciplines of high-resolution genomics and computer science, radiology and radiomics, surgery, tissue banking and sample preparation, medical oncology, immuno-oncology and high-resolution tissue profiling to generate a comprehensive and integrative dataset that will allow us to address the following major aims: i) characterize malignant and immune diversity at diagnosis, ii) survey the co-evolution of malignant cells and the immune response, and iii) stratify patients on standard-of-care and investigational compounds based on their genomic and transcriptomic signatures and changes to relevant genes (TP53, CCNE1, BRCA1/2, CDK12). The goal is to create a framework to utilize integrated multi-modal data as a route to advanced diagnostics and to ultimately establish a proof-of-concept for integrated diagnostics.

  Study phs002857

• Coding and regulatory somatic profiling of triple-negative breast cancer in Sub-Saharan African patients

  The burden of triple-negative breast cancer (TNBC) may be shaped by genetic factors, particularly inherited and somatic mutation profiles. However, data on this topic remain limited, especially for the African continent, where a higher TNBC incidence is observed. In the age of precision medicine, cataloguing TNBC diversity in African patients becomes imperative. We performed whole exome sequencing, including untranslated regions, on 30 samples from Angola and Cape Verde, which allowed to ascertain on potential regulatory mutations in TNBC for the first time. A high somatic burden was observed for the African cohort, with 86% of variants being so far unreported. Recurring to predictive functional algorithms, 17% of the somatic single nucleotide variants were predicted to be deleterious at the protein level, and 20% overlapped with candidate cis-regulatory elements controlling gene expression. Several of these somatic functionally-impactful mutations and copy number variation (mainly in 1q, 8q, 6 and 10p) occur in known BC- and all cancer-driver genes, enriched for several cancer mechanisms, including response to radiation and related DNA repair mechanisms. TP53 is the top of these known BC-driver genes, but our results identified possible novel TNBC driver genes that may play a main role in the African context, as TTN, CEACAM7, DEFB132, COPZ2 and GAS1. These findings emphasize the need to expand cancer omics screenings across the African continent, the region of the globe with highest genomic diversity, accelerating the discovery of new somatic mutations and cancer-related pathways.

  Study EGAS50000001013

• WES in Angolan and Cape Verdean triple-negative breast cancer samples

  WES (using the SureSelect Human All Exon V5 + UTRs target enrichment kit) in 23 Angolan and 7 Cape Verdean triple-negative breast cancer samples

  Dataset EGAD50000001482

• WES in Angolan and Cape Verdean triple-negative breast cancer samples

  WES in 23 Angolan and 7 Cape Verdean triple-negative breast cancer samples

  Dac EGAC50000000486

• Liquid Biopsy Detection of Tumor-specific Structural Variants in High Grade Serous Ovarian Cancer

  WGS Liquid Biopsy. Recurrence is frequent for most patients with high grade serous ovarian cancer (HGSOC), even after effective chemotherapy induced remission. However, after achievement of complete clinical response, the minimal residual disease is often insufficient for genomic analysis. Therefore, methods to interrogate the clonal composition and molecular properties of minimal residual disease are needed to better understand the mechanisms of HGSOC relapse. To address this unmet need, we developed and validated a novel cfDNA-based approach for tracking disease burden using NGS-informed tumor specific structural variants (SVs). Methods: The optimization of the methodology was first performed using synthetic cfDNA generated by ultrasonication of gDNA from ovarian cancer cell lines. Following the optimized workflow, whole genome sequencing of multisite biopsies from pre-treatment HGSOC patients were performed and high confidence SVs were called by consensus of multiple published SV callers. Real-time PCR and digital droplet PCR (ddPCR) were used for assays development.

  Study EGAS50000001044

• Liquid Biopsy High Grade Serous Ovarian Cancer WGS

  Liquid Biopsy High Grade Serous Ovarian Cancer WGS.

  Dataset EGAD50000001520

• Localised colon cancer WES study contaning WBCs, tissue and plasma samples at different time points

  Decision-making based on circulating tumor DNA (ctDNA) status following curative-intent surgery in stage II-III colon cancer (CC) is where the strongest clinical evidence lies. Commercial or academic assays are predominantly used to detect ctDNA, aiming to reveal minimal residual disease (MRD) and identify patients at high risk of recurrence. However, while current tests demonstrate exceptional specificity in detecting MRD among patients who later experience recurrence, their sensitivity is notably limited, particularly immediately after surgery when decisions regarding ACT are crucial. Additionally, up to 70% of patients with stage II-III colon cancer fail to clear ctDNA after standard adjuvant treatment (ACT) and subsequently experience recurrence. In this study, we performed whole exome sequencing (WES) of ctDNA at different timepoints in relapsed CC patients using two independent cohorts, alongside transcriptomic and proteomic analyses of metastases to gain a deeper understanding of progression mechanisms. An assay based on a tumor-agnostic approach from WES could enhance sensitivity in detecting MRD disease compared to current assays. Immune evasion appears to be the primary driver of progression in the localized CC setting, facilitated by a functional mutational burden at relapse. This suggests that immunotherapy could extend its efficacy to patients with microsatellite stability, broadening treatment options. Moreover, organoid modeling affirms the promising potential of targeted therapy to surpass conventional treatments in eradicating MRD.

  Study EGAS50000000204

• Assessing gene expression profiling from FFPE Patient Samples: A Comparison of Two Library Preparation Approaches and Recommendations

  Next-Generation Sequencing (NGS) has transformed cancer research and clinical practice, with Whole Exome Sequencing (WES) driving advances in mutational profiling and personalized oncology. Yet, transcriptomic signatures remain essential for understanding disease mechanisms, including therapy resistance pathways. RNA sequencing (RNA-seq), however, faces unique challenges when dealing with low-input or degraded RNA, as often found in archival formalin-fixed paraffin-embedded (FFPE) tissues. Although previous studies have compared library preparation protocols, rapidly evolving technologies call for updated evaluations. Here, we present a direct comparison of two FFPE-compatible stranded RNA-seq library preparation kits: TaKaRa™ SMARTer® Stranded Total RNA-Seq Kit v2 (Kit A) and Illumina Stranded Total RNA Prep Ligation with Ribo-Zero Plus (Kit B). Both kits generated high-quality RNA-seq data, yet important differences emerged. Notably, Kit A achieved comparable gene expression quantification to Kit B while requiring 20-fold less RNA input, a crucial advantage for limited samples, albeit with increased sequencing depth. We critically discuss these results in relation to RNA availability, technical performance, cost-effectiveness, processing time, and automation potential, offering practical guidance for selecting optimal RNA-seq strategies in clinical and translational research settings

  Study EGAS50000001066

• High volume culture initiating in vitro evolution in neuroblastoma cell lines

  Despite the advent of advanced molecular prognostic tools, it is still difficult to predict the course of disease for cancer patients at the individual level. This lack of predictability is also reflected in many experimental cancer model systems, begging the question of whether certain biological aspects of cancer (eg. growth, evolution etc.) can ever be anticipated or if there remains an inherent unpredictability to cancer, similar to other complex biological systems. We demonstrate by a combination of agent-based mathematical modelling, analysis of patient-derived xenograft systems from multiple cancer types, and in-vitro culture that certain conditions may invoke chaotic fluctuations in the clonal landscape of cancer growth. Our findings indicate that under those conditions, the cancer genome may behave as a complex dynamic system, making its long-term evolution inherently unpredictable.

  Study EGAS00001007962

• Genomic Characterization CS-MATCH-0007 Arm Q

  The CS-MATCH-0007 protocol is part of a collaboration between the Center for Cancer Genomics (CCG) and the Division of Cancer Treatment and Diagnosis (DCTD) to perform whole-exome sequencing and RNA sequencing using pre-and post-treatment tumor biopsy specimens from patients enrolled on a treatment arm of the NCI-MATCH Clinical Trial (EAY131). The goal of this study is to identify the molecular basis for response and resistance to targeted therapies that are matched to specific genomic alterations found in their cancers. Arm Q is one of the treatment sub-protocols within the NCI-MATCH Clinical Trial (EAY131) where patients with HER2 amplification are treated with Kadcyla® (ado-trastuzumab emtansine). This subprotocol is one of the treatment arms included in the CS-MATCH-0007 protocol and will provide specimens for the program including tumor tissue and whole blood.

  Study phs001926

• International Cancer Proteogenome Consortium (ICPC): Proteogenomics of Early Stage Lung Adenocarcinoma in Taiwan

  Lung cancer in East Asia is characterized by a high percentage of never-smokers with early-onset adenocarcinoma, predominantly with EGFR mutations. To provide an insight into the molecular phenotype of this demographically distinct disease, we have performed a proteogenomics study on a prospectively collected cohort representing early stage lung adenocarcinoma in Taiwan. The distinct mutational profile revealed a high prevalence of the APOBEC mutational signature in early-onset females, implicating differential regulation of APOBEC enzymes and DNA damage pathways, as well as enrichment of mutational signatures congruent with environmental carcinogens over-represented in the genomic location of EGFR. We delineate the proteogenomic hallmarks of tumor progression and propose a proteomics-informed classification that resolves the EGFR mutation heterogeneity associated with survival within the early stages. Functional annotation of the molecular subtypes by protein network analysis highlights candidate biomarkers for patient stratification. Our integrative analysis reveals the molecular architecture of lung cancer in East Asia and enables the path for precision medicine.

  Study phs001954

• Investigation of BK Polyomavirus (BKPyV) and Molecular Signatures in UC specimens from Taiwan

  Urothelial carcinoma (UC) is the most prevalent cancer of kidney transplant recipients in some regions. The integration of BK polyomavirus (BKPyV) genome into the human genome is observed in some cases of UC. The prevalence of aristolochic acid (AA) mutational signatures in urothelial carcinoma is high in the general population of Taiwan. To better understand the mechanisms of UC carcinogenesis in kidney transplant recipients, 19 UC specimens were analyzed by whole genome sequencing (WGS) and Hybrid Sequencing.

  Study EGAS50000001063

• Cancer Discovery Hub (CDH), National Cancer Center Singapore

  This is a DAC for data deposited into EGA generated by Cancer Discover Hub, NCCS. The use of datasets in this portal is solely for research and academic use only, uses other than the have to be approved by the relevant DAC members.

  Dac EGAC50000000039

• Oncogenic and immunological targets for matched therapy of pediatric blood cancer patients: Dutch iTHER study experience

  Study EGAS00001008218

• B cell receptor silencing reveals origin and dependencies of high-grade B cell lymphomas with MYC and BCL2 rearrangements

  High-grade B cell lymphomas with MYC and BCL2 rearrangements (HGBCL-DH-BCL2) represent highly aggressive Germinal center (GC) derived B cell malignancies with dismal prognosis and limited therapeutic options. In the present study, we investigated the expression of BCR complex components, including immunoglobulin (IG) heavy (H) and light (L) chains, and CD79A and CD79B signaling subunits in HGBCL-DH-BCL2, scoring 65% of cases with undetectable IGH immunoreactivity (IGHUND). Transcriptomics (bulk RNA-seq) and genetic (whole exome/genome sequencing) analyses indicated that IGHUND and IGH+ HGBCL-DH-BCL2 lymphomas represent distinct biological entities. Specifically, IGHUND HGBCL-DH-BCL2 exhibit a GC DZ-like molecular program, and select subset-specific gene mutations pointing to distinct evolutionary trajectories respect to the IGH+ counterparts. IG profiling revealed that IGHUND HGBCL-DH-BCL2 preserved potentially productive, hypermutated IGH variable (V) gene rearrangements, indicating a selective advantage conferred to the malignant B cells by residual IGH molecules. Accordingly, disruption of the productively rearranged IGHG1 gene in BCRnull HGBCL-DH-BCL2 cell line model confirmed the dependency on IGH expression for optimal fitness. Using transcriptomics and in situ RNA-scope analysis, we reported that IGHUND HGBCL-DH-BCL2 originated from IG-class switched GC B cells, while IGH-expressing tumors were selected for continuous IGM expression. Moreover, while IGH+ HGBCL-DH-BCL2 favor IGM/IG-Kappa expression, IGHUND counterparts complete IG-Lambda light chain rearrangements. Notably, BCR silencing, caused by accelerated IGH turnover and reduced IGH expression, precedes HGBCL-DH-BCL2 onset, inducing RAG1/2-dependent IG light chain editing and eventually facilitating t(8;22)/IGL::MYC translocations. Finally, IGH silencing observed in HGBCL-DH-BCL2 cell models, which leads to intracellular retention/silencing of CD79B, results in reduced sensitivity to the CD79B-targeting antibody-drug conjugate Polatuzumab-vedotin. Collectively, HGBCL-DH-BCL2 originates from isotype-switched t(14;18)+ GC B cells that undergo IG light chain editing fuelling intra-clonal diversification, BCR silencing, and the acquisition of t(8;22) translocation, while preserving IGH dependency.

  Study EGAS50000001047

• Genomic determinants of response and resistance to inotuzumab in B-ALL

  Inotuzumab Ozogamicin (InO) is an antibody-drug conjugate which delivers calicheamicin to CD22-expressing cells. In a retrospective cohort of InO treated B-cell acute lymphoblastic leukemia (B-ALL) patients, we sought to understand the genomic determinants of response to InO. Acquired CD22 mutations were observed in 11% (3/27) of post-InO relapsed samples. CD22 mutation types were diverse (frameshift, nonsense, missense and stoploss) and we identified multiple mechanisms of mutation induced CD22 escape, including protein truncation, protein destabilization, and epitope alteration. Accelerated acquisition of mutations by error-prone DNA damage repair could drive CD22 mutation and escape. Acquired loss-of-function mutations in TP53, ATM and CDKN2A were observed, suggesting compromise of the G1/S DNA damage checkpoint as a mechanism of evading InO-induced apoptosis. In conclusion, genetic alterations modulating CD22 expression and DNA damage response influence InO efficacy. The diverse mechanisms of CD22 escape advocates for a refined approach for monitoring CD22-targeted therapy.

  Study EGAS50000000067

• Pyjacker identifies enhancer hijacking events in acute myeloid leukemia including MNX1 activation via deletion 7q

  Acute myeloid leukemia with complex karyotype (ckAML) is characterized by high genomic complexity, including frequent TP53 mutations and chromothripsis. We hypothesized that the numerous genomic rearrangements could reposition active enhancers near proto-oncogenes, leading to their aberrant expression. We developed pyjacker, a computational tool for the detection of enhancer hijacking events, and applied it to a cohort of 39 ckAML samples. Pyjacker identified motor neuron and pancreas homeobox 1 (MNX1), a gene aberrantly expressed in 1.4% of AML patients, often as a result of del(7)(q22q36) associated with hijacking of a CDK6 enhancer. MNX1-activated cases show significant co-occurrence with BCOR mutations and a gene signature shared with t(7;12)(q36;p13) pediatric AML. We demonstrated that MNX1 is a dependency gene, as its knockdown in a xenograft model reduces leukemia cell fitness. In conclusion, enhancer hijacking is a frequent mechanism for oncogene activation in AML.

  Study EGAS50000000743

• DHODH is a synthetic-lethal vulnerability in BCOR-deficient acute myeloid leukemia

  Acute Myeloid Leukemia (AML) remains challenging to treat, especially in cases with mutations in the BCL-6 co- repressor (BCOR), which are associated with poor prognosis and chemo-resistance. In this study, we reveal a synthetic lethal interaction between BCOR and dihydroorotate dehydrogenase (DHODH). We demonstrate that BCOR-deficient cells have a heightened sensitivity to DHODH inhibitors such as brequinar and leflunomide, that are already in clinical use. We confirm that DHODH inhibition selectively induces cell death in BCOR-mutant cells in multiple cellular models, in malignant and non-malignant cells, through chemical and genetic manipulation. Interestingly, we find that the dependency on DHODH does not stem from its role in de novo pyrimidine biosynthesis disruption. Rather, DHODH’s role in the electron transport chain, essential for mitigating reactive oxygen species, may be the physiological vulnerability that pushes BCOR-mutant cells toward cell death when DHODH is inhibited. DHODH inhibitors could be repurposed as targeted therapies for BCOR-mutant tumors, offering a promising strategy for precision medicine in AML and other cancers.

  Study EGAS50000001108

• Somatic Mutation in Normal Bladder Study

  Adult human somatic tissues are landscapes of mutant clones, but little is known about how these landscapes are shaped by known cancer risk factors. The goal of this study was to determine how the main bladder cancer risk factors (sex and smoking) change the mutational landscape of the normal urothelium. We collected normal urothelium from 45 donors at autopsy by brushing ~2cm² of the surface epithelium in the upper part (dome) and lower part (trigone) of the bladder (79 samples total). To identify mutations with high sensitivity we employed ultradeep (~5000x) DNA error-correcting duplex-sequencing on a panel of 15 protein coding genes and the TERT promoter, previously described to be under positive selection in normal urothelium or relevant to bladder cancer. We identified thousands of clonal driver mutations, which demonstrate pervasive positive selection in the normal urothelium. Males showed a significantly higher number of driver truncating mutations in RBM10, CDKN1A and ARID1A, despite similar rates of non-coding mutations, indicating stronger positive selection and clonal expansion in the male urothelium. We also discovered clonal expansions driven by activating TERT promoter mutations in the normal bladder, which were strongly associated with age and smoking. These results demonstrate that sex and smoking shape the clonal landscape of the normal bladder and indicate that the high mutational content of normal tissues might be leveraged to study the effect of mutations in vivo (i.e. natural saturation mutagenesis). We will deposit in dbGaP de-identified relevant clinical information from the 45 donors and the fastq files derived from duplex sequencing of the 79 samples in the study. We will also deposit fastq files derived from duplex sequencing of 3 control cord blood samples.

  Study phs004105

• Epigenetic Control of Topoisomerase 1 by MacroH2A1.1

  DNA transactions introduce torsional constraints that pose an inherent risk to genome integrity. While topoisomerase 1 (TOP1) activity is essential for removing DNA supercoiling, aberrant stabilization of TOP1:DNA cleavage complexes (TOP1ccs) can result in cytotoxic single-stranded DNA lesions (SSLs). What protects the genome from aberrant TOP1 activity remains unknown. Using a combination of CUT&RUN and TOP1 Covalent Adduct Detection (CAD) Seq in MDA-MB-231 breast cancer cells (American Type Culture Collection, ATCC), we identified chromatin context as an essential means to ensure TOP1cc resolution at TOP1 hot spots. Through its ability to bind poly(ADP-ribose) (PAR), a protein modification required for TOP1cc repair, the histone variant macroH2A1.1 establishes a TOP1-permissive chromatin environment, while the alternatively spliced macroH2A1.2 isoform is unable to bind PAR or protect from TOP1ccs. MacroH2A1 isoform-specific analyses were based on reconstitution of macroH2A1.1 knockout cells with wild-type or PAR binding-deficient FLAG-tagged macroH2A1.1 in human breast cancer cells. Mechanistically, we find that macroH2A1.1 facilitates the recruitment of the TOP1cc repair factor XRCC1 in response to both endogenous and drug-induced topological stress. Impaired macroH2A1.1 splicing, a frequent cancer feature, was predictive of increased sensitivity to TOP1 poisons in a pharmaco-genomic screen in breast cancer cells, and macroH2A1.1 inactivation mirrored this effect in breast and ovarian cancer cells. Consistent with this, low macroH2A1.1 expression correlated with improved survival in cancer patients treated with TOP1 inhibitors (TOP1i). We propose that macroH2A1 alternative splicing serves as an epigenetic modulator of TOP1-associated genome maintenance and a potential cancer vulnerability.

  Study phs003729

• Genomic Characterization of Duke Melanoma Brain Metastases

  Previous work has shown that melanoma brain metastases (MBM) have a unique molecular profile compared to extracranial metastases (ECM). Description of the biology of MBM and associations between biological features and clinical outcomes will facilitate the design of rational therapies for patients with MBM. To better characterize the molecular profile of MBM, we conducted whole exome sequencing (WES) and total RNA sequencing on MBM tissues obtained from an independent cohort of 14 patients from Duke University Medical Center. This cohort adds valuable patient samples to the field and enables strengthened investigation of somatic mutations and gene expression profiles within and between cohorts. The mutational landscape and gene expression of MBM from the Duke cohort resembled those previously reported in a previously published dataset of WES and RNA sequencing in MBM and matched ECM tissues from UT MD Anderson Cancer Center (Fischer et al., 2019 30787016). Duke MBM demonstrated similar rates of mutations in genes associated with melanoma, including BRAF, NRAS, and PTEN, as the MD Anderson cohort. Immune populations in MBM were similar between Duke and MD Anderson MBM, though Duke samples demonstrated more resting CD4+ memory T cells. The ratio of M2 to M1 macrophages in the Duke cohort was similar to that of the MD Anderson cohort. In MBM, a higher M2:M1 ratio may contribute to an immune-suppressive tumor microenvironment. Sequencing data and sample attributes from MBM tissues obtained from 14 patients from Duke University Medical Center will be available through dbGaP.

  Study phs003009

• Nanopore whole-genome sequencing of human sarcomas

  We performed single and multi-region nanopore whole-genome sequencing on human sarcoma samples from adult and paediatric patients.

  Study EGAS50000000651

• Myeloid cell networks govern re-establishment of original immune landscapes in recurrent ovarian cancer

  Immunotherapy has produced disappointing results in recurrent ovarian cancer (OC). However, the prognostic value of tumour-infiltrating lymphocytes (TILs) is largely based on the analysis of treatment-naive tumours. To understand the immunobiology of recurrent cancers, and their evolution, we profiled a total of 697 OC tumour samples (566 primary and 131 recurrent including 69 patient-matched samples) from 595 patients of five independent multi-institutional cohorts. By capturing heterogeneous TIL distributions, we identified four immune phenotypes associated with differential prognosis, TILs states and TILs:myeloid networks, which dictate malignant progression after chemotherapy and recurrence. Notably, recurrent tumours recapitulate the immunogenic landscapes of original cancers. Mirroring inflamed human OC, preclinical recurrent Brca1mut tumours maintained activated TILs:dendritic cells (DCs) niches but evaded immune control through COX/PGE2 signaling upregulation. Conversely, recurrent Brca1wt tumours displayed loss of TILs:DCs niches and accumulated immunosuppressive myeloid networks featuring Trem2/ApoEhigh TAMs and Nduf4l2high/Galectin3high malignant states. Our study highlights that persistent immunogenicity in recurrent OC is governed by the BRCA-dependent crosstalk between dissimilar myeloid cells and TILs. We propose new targets to modulate the malignant and TAM compartments which improve efficacy of standard of care chemotherapy in mouse OC models with HR deficiency.

  Study EGAS50000001069

• RNAseq dataset of ovarian cancer patients

  Dataset of transcriptomics data from a cohort of individuals diagnosed with ovarian cancer. This dataset includes RNAseq sequencing data from 68 individuals. A total of 109 tumor samples were sequenced. Samples were prepared with the Illumina TruSeq Stranded RNA library. Sequencing data are paired end.

  Dataset EGAD50000001556

• Methylation Array of pre- and post-5ZA-treated head and neck cancer patients refractory to anto-PD-1 therapy

  Illumina MethylationEpic Beachip data generated from tissue samples collected from head and neck cancer patients refractory to anti-PD-1 therapy, collected before and after the 5AZA treatment

  Dataset EGAD00010002718

• Yale Policy for head and neck cancer and HPV clinical trials

  Dac EGAC00001003519

• DHODH is a synthetic-lethal vulnerability in BCOR-deficient acute myeloid leukemia

  Acute Myeloid Leukemia (AML) remains challenging to treat, especially in cases with mutations in the BCL-6 co- repressor (BCOR), which are associated with poor prognosis and chemo-resistance. In this study, we reveal a synthetic lethal interaction between BCOR and dihydroorotate dehydrogenase (DHODH). We demonstrate that BCOR-deficient cells have a heightened sensitivity to DHODH inhibitors such as brequinar and leflunomide, that are already in clinical use. We confirm that DHODH inhibition selectively induces cell death in BCOR-mutant cells in multiple cellular models, in malignant and non-malignant cells, through chemical and genetic manipulation. Interestingly, we find that the dependency on DHODH does not stem from its role in de novo pyrimidine biosynthesis disruption. Rather, DHODH’s role in the electron transport chain, essential for mitigating reactive oxygen species, may be the physiological vulnerability that pushes BCOR-mutant cells toward cell death when DHODH is inhibited. DHODH inhibitors could be repurposed as targeted therapies for BCOR-mutant tumors, offering a promising strategy for precision medicine in AML and other cancers.

  Study EGAS50000001060

• Targeted pancancer RNA-Seq

  This dataset contains targeted RNA-Seq generated with the Illumina RNA Pan-Cancer panel. It comprises 2200 cancers from children and adults. The cancers represent a wide range of CNS, solid and haematopoeitic tumours. Samples are from pathology specimens including FFPE, fresh frozen, bone marrow aspirate and peripheral blood.The data is used for tumour driver identification. SNVs, indels and fusion detection.

  Study EGAS50000000700

• Targeted RNA-Seq

  This dataset contains targeted RNA-Seq generated with the Illumina RNA Pan-Cancer panel. It comprises 2200 cancers from children and adults. The cancers represent a wide range of CNS, solid and haematopoietic tumours. Samples are from pathology specimens including FFPE, fresh frozen, bone marrow aspirate and peripheral blood. Samples were tested in a clinical diagnostic lab to identify relevant SNVs, indels and gene fusions.

  Dataset EGAD50000000980

• Clinical Outcomes of 344 Diffuse Large B-Cell Lymphoma patients

  This study examines clinical outcomes of patients with diffuse large B-cell lymphoma (DLBCL). We analyzed a cohort of 344 patients from the German High-Grade Non-Hodgkin Lymphoma Study Group (DSHNHL). To protect patient confidentiality, all samples were pseudonymized. The dataset includes clinical key characteristics, such as patient age at diagnosis, sex, ECOG performance status, disease stage, serum lactate dehydrogenase levels, bulky disease, bone marrow involvement, extranodal involvement, and B-symptoms. We used these data alongside proteomic and transcriptomic profiles to explore relationships between clinical features and molecular signatures, reconstructing regulatory networks. Insights from this integrative analysis aim to identify key pathological drivers and biomarkers of DLBCL progression, ultimately informing improved risk stratification and targeted therapeutic approaches.

  Study EGAS50000001054

• Colorectal cancer peritoneal metastasis

  This dataset consist of 72 samples profiled on whole exome sequencing and 94 samples profiled on whole transcriptome sequencing. The Agilent SureSelect Human All Exon v6 kit (Agilent Technologies) was used for whole exome sequencing. For RNA-seq experiments, library preparation was conducted using the Tru-Seq Stranded Total RNA with Ribo-Zero Gold kit protocol (Illumina). Libraries were sequenced on a HiSeq4000 sequencer using the paired-end 150 bp read option. Sequences in cram format was provided.

  Dataset EGAD50000001199

• CITE-seq for peripheral blood samples of 5 breast cancer patients

  Study EGAS00001006241

• Spatial Transcriptomics Uncovers Tumor Microenvironment-Based Subtypes in Invasive Lobular Carcinoma

  Invasive lobular carcinoma (ILC) is the second most common histological subtype of breast cancer (BC); however, little is known about its tumor microenvironment (TME). Here, we investigated the spatial architecture of 43 hormone-receptor-positive, HER2-negative (HR+/HER2-) primary ILC samples, using spatial transcriptomics and detailed morphological annotation. By integrating morphology, spatial, and single-cell data, we mapped TME-related cell types, exploring their proximity to tumor cells and their enrichment in specific compartments. Clustering of spatial transcriptomics spots revealed significant inter- and intra-tumor heterogeneity, identifying pathways and cell types linked with disease outcomes. Morphological and gene expression data were finally integrated with a multimodal approach, leading to the identification of 4 new ILC subtypes based on TME heterogeneity. By using derived, specific gene expression signatures, these subtypes were identified and validated in external bulk RNA-seq/microarray datasets (SCAN-B and METABRIC), where differences in prognosis emerged.

  Study EGAS50000001001

• ST lobular manuscript dataset

  Spatial transcriptomics analysis for 43 breast cancer lobular samples. Note that there are 2 runs per sample Images and read counts will be made availalble on Zenodo upon publication.

  Dataset EGAD50000001467

• PD1-targeted delivery of an IL-2 variant induces a multifaceted anti-tumoral T cell response in human lung cancer

  To explore PD1-IL2v-specific effects on CD8 and CD4 T cells at a transcriptomic level, we performed single-cell RNA sequencing of patient-derived tumor fragments (PDTFs) which were treated with either Isotype (DP47), Isotype-IL2v (DP47-IL2v), anti-PD1 (PembroPGLALA) or PD1-IL2v (PembroPGLALA-IL2v) for 48 hours.

  Study EGAS50000000396

• p200503_fn2

  RNA-Sequencing data of Fusobacterium nucleatum (Fna 71) treated CRC patient derived (CAF180, CAF181) and CAF05 cancer associated fibroblasts (CAFs).

  Study EGAS50000001121

• RNA-Sequencing data of Fusobacterium nucleatum treated CAFs and HT-29 tumor spheroid exposed to Fusobacterium nucleatum treated CAFs conditioned medium.

  RNA-Sequencing data of CAFs (patient derived CAF180 and CAF181 as well as the CT5.3 CAF cell line) and HT-29 tumor spheroid samples performed in the context of the study of the interaction of Fusobacterium nucleatum with CRC CAFs. Fusobacterium nucleatum interacts with cancer-associated fibroblasts to enhance colorectal cancer progression

  Dataset EGAD50000001614

• Batches 1-3 prostatectomy analysis

  Whole Genome Sequencing Illumina HiSeq data from 95 men with prostate cancer. Samples were taken from primary tissue obtained at prostatectomy (target sequencing depth 50X) with matched blood control (target sequencing depth 30X). This data is from batches 1 to 3 and is the bulk of the data used in Wedge et al, Nature Genetics 2018 (PMID: 29662167). As of September 2020, some of the studies using these data include: Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001001116

• The Oral Microbiome and Head and Neck Cancer

  Oral microbiota may influence head and neck squamous cell carcinoma (HNSCC) development, potentially related to carcinogen metabolism. The human oral cavity hosts a diverse microbiota, including bacteria and fungi. We performed shotgun sequencing and ITS1 sequencing on 236 HNSCC case participants who developed HNSCC during a mean follow-up of 5.1 years and 458 matched controls who remained HNSCC-free. Oral samples were obtained from a prospective nested case-control study within three epidemiological cohorts: the American Cancer Society Cancer Prevention Study II Nutrition Cohort (ACS CPS-II), the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO), and the Southern Community Cohort Study (SCCS). Control participants were selected using 2:1 frequency matching based on cohort, age, sex, race and ethnicity, and time since oral sample collection.

  Study phs004018

• Oncogenome of Kaposi Sarcoma

  Kaposi Sarcoma (KS) is an aggressive cancer caused by the Kaposi Sarcoma Herpesvirus (KSHV/HHV-8). Individuals with immunodeficiencies, exemplified by HIV, have an elevated risk of developing KS. However, understanding of the genetic factors contributing to KS progression is still limited. To explore potential genetic alterations in KS that could offer biological or therapeutic insights, whole exome sequencing was performed on 78 KS tumors and matching normal skin samples from 59 adults with KS (46 with HIV-associated KS and 13 with HIV-negative KS) receiving treatment at the Uganda Cancer Institute in Kampala, Uganda. Results showed a very low mutational burden in all samples except one (median = 11 mutations), which is the smallest number of mutations found across all 33 cancer types in The Cancer Genome Atlas (TCGA). No recurrent mutations were identified. Mutational signatures included impaired DNA mismatch repair and smoking. There was no evidence suggesting that multiple tumors from the same patient originated from a single clone. The number of genome copy alterations per genome was higher in tumors from individuals without HIV and those with advanced-stage disease. This suggests that lesions that take longer to develop may accumulate more alterations, although the overall number of alterations remains low compared to other cancers. These findings suggest that KS pathogenesis differs from other cancers, with KSHV viral infection and the expression of viral oncogenes being the primary drivers of carcinogenesis, rather than clonal oncogenic transformation arising from genetic alterations of cancer-related cellular genes.

  Study phs003897

• PE-CGS: Optimizing Engagement of Hispanic Colorectal Cancer Patients in Cancer Genomic Characterization Studies

  Colorectal Cancer (CRC) is the second leading cause of cancer death in the US. Hispanic/Latinos (H/L) are the largest and fasting growing ethnic group in the US, and cancer is the leading cause of death among H/L in the US. Therefore, we need to fully understand the full complexity of the molecular etiology of cancer in this ethnic group. For instance, although incidence rates of CRC are lower among Latinos as compared to Whites or African Americans, Hispanics with metastatic disease have shorter overall survival when adjusted for health care setting, demographics, disease characteristics and treatment factors. H/L also tend to be diagnosed at a younger age and with higher stage, and we have previously reported that Mexican H/L in California have the greatest proportion of young (The Cancer Genome Atlas has provided a deep overview of the molecular taxonomy of CRC in 594 cases, however, less than 1% of the cases (n=5) were H/L. Therefore, it is imperative for us to take more detailed assessment of the molecular genomic landscape of CRC in H/L. One of the major issues likely limiting our ability to perform these large genomic initiatives in minority patients is that Patient or Participant Engagement practices may not be investigated to identify best practices for accruing and consenting patients into clinical translational biomedical research studies. This concept of Participant Engagement is critically important for both the patients and the translational cancer research community. Optimizing and improving our approaches for directly engaging patients at initial contact, throughout the course of a translational genomic study, and during the time of return of results is likely to lead to stronger relationships between the medical community and patients, but could also lead to significant improvement in outcomes for patients and for the cancer care community as a whole. As such, we propose the creation of the USC Center for Optimization of Participant Engagement in Cancer Characterization (COPECC) with a focus on optimizing the engagement of Latinos in CRC Genomic Characterization research studies. USC COPECC would serve as a member of the NCI U2C Participant Engagement and Cancer Genome Sequencing (PE-CGS) Network. Our investigative team includes experts in all relevant areas of research for genomic characterization, participant engagement, and engagement optimization. We have an established platform for consenting patients into cancer genomics studies that will serve as a standard process. The overall goal of USC COPECC is to generate results on participant engagement optimization and CRC genomic research that will be shared with the broader community to distribute best practices for engaging Latinos in hopes of improving overall outcomes for CRC in this underserved population.

  Study phs003985

• Collagen XVII Promotes Pancreatic Cancer Through Regulation of PIK3R5

  Pancreatic ductal adenocarcinoma (PDAC) contains a desmoplastic stroma that promotes the aggressive biology of this disease. While the varied mechanisms by which fibrillar collagens contribute to PDAC have been defined, little is known about the contribution of transmembrane collagens. Among this class of collagens, Collagen XVII uniquely contains an extensive intracellular domain that connects intracellular cytoplasmic components with the extracellular matrix. Collagen XVII is best characterized as the defining component of the type I hemidesmosome, an anchoring complex that attaches epithelial cells to the underlying basement membrane. In this study, we characterize the expression of collagen XVII in PDAC and the mechanisms by which it contributes to PDAC biology. We demonstrate that crosstalk between PDAC cells and cancer associated fibroblasts drive collagen XVII expression in vitro and xenograft tumor models in vivo. Genetic depletion of collagen XVII in low-passage patient derived cell lines diminishes their metastatic potential and ability to form tumors in mice. Whole transcriptome sequencing of tumors formed by cells with diminished collagen XVII levels revealed dramatically lower levels of PIK3R5, a regulatory subunit of class IB phosphatidylinositol-3-kinase (PI3K) that interacts with G protein-coupled receptors. Consistent with this, collagen XVII-deficient tumors exhibited lower levels of phosphorylated AKT, a downstream effector of PI3K. The studies highlight the importance of collagen XVII signaling in PDAC and define a novel mechanism by which collagen XVII mediates activation of PI3K.

  Study phs003641

• KAT6A and KAT7 Histone Acetyltransferase Complexes Are Molecular Dependencies and Therapeutic Targets in NUP98-Rearranged Acute Myeloid Leukemia

  NUP98 fusion oncoproteins (FOs) are a hallmark of childhood acute myeloid leukemia (AML). NUP98 FOs drive leukemogenesis through phase-separated condensate formation and maintenance of an active chromatin landscape at stem cell-associated genes in cooperation with epigenetic regulators. Here we show that MYST family histone acetyltransferase (HAT) complex proteins including KAT6A/MOZ, KAT7/HBO1, and the common KAT6A/7 complex subunit BRPF1 associate with NUP98 FOs on chromatin and within condensates. MYST HATs are molecular dependencies in NUP98-rearranged (NUP98-r) leukemia, and genetic inactivation or pharmacologic inhibition of Kat6a and Kat7 impairs NUP98-r cell fitness. KAT6A/7 inhibition decreased global H3K23ac levels, displaced NUP98::HOXA9 from chromatin at the Meis1 locus, and led to myeloid cell differentiation. Additionally, KAT6A/7 inhibition decreased leukemic burden in multiple NUP98-r leukemia xenograft mouse models, synergized with Menin inhibitor treatment, and was efficacious in Menin inhibitor-resistant cells. In summary, we show that MYST family HATs are therapeutically actionable dependencies in NUP98-r AML.

  Study EGAS50000001075

• Multi-omics analysis of an individual with multiple pancreatic neuroendocrine tumours (panNETs)

  Study EGAS00001006722

• Dataset with WGBS data of CRC and colon tissue

  This dataset contains WGBS data from 20 samples, which are either from colorectal cancer or control colon tissue. Sequencing was performed on either Illumina HiSeq 2000 or HiSeq X and the sequences are paired.

  Dataset EGAD50000000772

• Whole-genome and transcriptome versus panel sequencing in precision oncology: A translational-clinical comparison

  Precision oncology offers new cancer treatment options. While the use of whole-genome (WGS) and transcriptome (TS) sequencing remains often confined to specific clinical programs, molecular analysis with gene panels is more common clinical practice. Methods: Twenty patients with rare or advanced tumors sequenced by WGS/TS within the DKFZ/NCT/DKTK-MASTER program from 2015 to 2020 (MASTER 1) were additionally sequenced with the TSO500 DNA and TST170 RNA Assay by Illumina. Original Molecular Tumor Board (MTB) therapy recommendations (TR) were juxtaposed with TR from NGS panel data analysis (comparison 1). To mitigate temporal differences between the two sequencings, WGS/TS was bioinformatically reanalyzed (MASTER 2), and new TR were again compared (comparison 2). Results: In comparison 1, 47.1% of the MASTER 1’s TR and 62.8% of the panel’s TR were identical, as were 45.9% of the TR of MASTER 2 and 54.9% of the panel in comparison 2. In both MASTER 1 and MASTER 2, 26.5% and 36.1% of TR, respectively, relied on Biomarkers (BM) which were not covered by the panel. Eight of the ten MTB-derived therapy implementations were also supported in the panel, the two remaining ones being based on BM absent from the panel. Conclusions: About half of the TR in WGS/TS and panel sequencing were identical. Around a third of TR issued by WGS/TS were based on BM which are not covered by the panel, leading to therapy implementations. The presented data underscores the clinical value of comprehensive molecular analyses in individuals with advanced cancers.

  Study EGAS50000000431

• High-grade B-cell lymphoma, not otherwise specified: an LLMPP study

  Molecular characterization of high-grade B-cell lymphoma, not otherwise specified (HGBCL-NOS), is hindered by its rarity, evolving definition, and poor diagnostic reproducibility. To address this challenge, we analyzed 92 HGBCL-NOS tumors collected across Lymphoma/Leukemia Molecular Profiling Project sites. These tumors were profiled using whole-genome sequencing (WGS) or whole-exome sequencing (WES) to identify somatic mutations, WGS or low-pass WGS to detect copy number alterations, targeted capture sequencing to assess MYC and BCL2 structural variants, and RNA sequencing. The genetic features of HGBCL-NOS were compared to those of diffuse large B-cell lymphoma (DLBCL-NOS) and EBV-negative adult Burkitt lymphoma (BL). DLBCL-NOS tumors underwent targeted capture sequencing using a panel of 125 genes recurrently mutated in aggressive B-cell lymphomas. BL biopsies were drawn from the Burkitt Lymphoma Genome Sequencing Project and had available WGS (dbGaP Study Accession: phs000527.v18.p6).

  Study EGAS50000000932

• Germline WES of serrated polyposis syndrome

  The serrated polyposis syndrome (SPS) is a disease with a mainly unknown inherited genetic basis characterized by the presence of multiple and/or large serrated polyps in the colon and a higher associated risk for colorectal cancer (CRC). The objective of the present study was to identify new SPS/CRC germline predisposition genes by using whole-exome sequencing in two affected SPS patients from the same family.

  Study EGAS50000000765

• ACUITI

  This study assessed the feasibility and performance of a tumor-informed circulating tumor DNA (ctDNA) assay in patients with metastatic HR+/HER2- breast cancer receiving endocrine therapy and CDK4/6 inhibitors.

  Study EGAS50000000962

• Evaluation of the ERa binding region activity in breast and endometrial cancer

  Evaluate the activity of ERa binding site activity in breast and endometrial cancer.

  Study EGAS50000000009

• STARR-seq of ERa binding sites in MCF7 and Ishikawa cell lines

  A oligo-captured STARR-seq library was generated using as targets ERa binding regions indetified by ChIP-seq in Ishikawa (Endometrial cancer) and T47D (breast cancer) cell lines and, breast cancer primary tissues. STARR-seq assays have been performed in MCF-7 and Ishikawa cell lines. Cells have been cultured for 3 days in hormone deprivated (phenol-red free) media and stimulated for 6 hours by 10nM estradiol (E2) or DMSO (negative control).

  Dataset EGAD50000000015

• ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer - WGS

  Whole genome sequencing data related to the publication "ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer." ERBB2 alterations, usually amplifications or activating mutations, are seen in up to 20% of urothelial carcinoma and can be targeted by monoclonal antibodies, small molecule inhibitors, and most recently, antibody-drug conjugates. Here, we perform targeted and whole-genome sequencing of cell-free DNA and archival FFPE of mUC with and without ERBB2 alterations to identify unique genomic and clinical features of ERBB2-altered cancers, accompanied by IHC, FISH, and detailed clinical outcomes.

  Study EGAS50000001082

• ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer - Targeted

  Targeted sequencing data related to the publication titled "ERBB2/HER2 alterations in ctDNA and metachronous tissues of patients with metastatic urothelial cancer." ERBB2 alterations, usually amplifications or activating mutations, are seen in up to 20% of urothelial carcinoma and can be targeted by monoclonal antibodies, small molecule inhibitors, and most recently, antibody-drug conjugates. Here, we perform targeted and whole-genome sequencing of cell-free DNA and archival FFPE of mUC with and without ERBB2 alterations to identify unique genomic and clinical features of ERBB2-altered cancers, accompanied by IHC, FISH, and detailed clinical outcomes.

  Study EGAS50000001081

• After the completion of CINECA, EUCANCan, and euCanSHare. What's next?

  CINECA, EUCANCan, and euCanSHare were part of the EUCAN Cluster, made up of six projects that received funding under the same Horizon 2020 call. All EUCAN projects (CINECA, EUCANCan, EUCAN-Connect, euCanSHare, Receptor Plus, and ReCoDID) were aimed at facilitating data reuse and knowledge discovery by enhancing data exchange and long-term collaboration in the health field. Here are some highlights about EGA’s contribution to these projects. CINECA: advances in Federated discovery and infrastructure for cohorts CINECA (Common Infrastructure for National Cohorts in Europe, Canada, and Africa) developed a federated cloud-based infrastructure for making genomic and biomolecular data accessible. The project has assembled a virtual cohort of 1.4 million individuals from sources such as the EGA, CanDIG and H3Africa. The EGA–CRG co-leaded a work package Work Package 1 on Federated Data Discovery and Querying. Beacon v2, championed by Jordi Rambla and Lauren Fromont, has been one of the central elements for the discovery of human genetic and phenotypic data. The EGA-CRG contributed to the development of a model for cohort discovery inside the Beacon v2 model. The team also delivered a Discovery Portal was implemented to explore cohorts and individuals of synthetic data. It is a UI that gathers a network of Beacons, a service for query expansion, and a visualisation tool. Have a look at the Discovery Portal UI, gathering a network of Beacons. You will find entities such as the Barcelona Supercomputing Center (BSC), BioData.pt and the European Genomic Data Infrastructure (GDI), among others. euCanSHare: facilitation of data access management This joint EU-Canada project aimed to build a European and Canadian FAIR platform for cardiovascular data sharing and analysis. The EGA’s tasks contributed to the development of the data management plan and data flows, main web-portal and interoperability protocols. An important part of the EuCanShare platform is the data access manager, a tool for the data owners to control the access to their sensitive datasets. We built a user-friendly interface for data access committees (data owners) to easily manage their data requests and access credentials. The data access portal facilitates the creation and internal organization of the data access committees as well as the linkage of data usage conditions to specific datasets. The interface includes filters for browsing requests and page to visualize the request history helping with the handling of data access requests. EUCANCan: toward a federation of clinical institutions in oncology The EUropean-CAnadian CANcer Network worked towards building a federated network to advance personalized medicine in oncology, by promoting the standard analysis, management and sharing of harmonized genomic and phenotypic data. The EGA led tasks on defining data flows and preparing an adapted infrastructure for long-term data storage and sharing. One of the key contributions was the conception of the EGA communities, offering standard and interoperable solutions for data discovery, processing, and sharing to projects and institutions that would like to manage and share data in the context of the EGA ecosystem. What's Next? The participation in projects such as CINECA, EUCANCan, and euCanSHare provide us with experience for future projects. We are happy to enhance data sharing and reuse, vital for advancing clinical and genomic research. The Discovery Portal is a wonderful proof of concept for the Beacon network. Next, we will finalise both the network and the user interface, and make sure it can be applied to more clinically-centred settings like hospitals. Most data hosted at the EGA are about cancer research. Currently, we contribute to building tools and infrastructure to empower oncology research in several European projects such as EUCAIM, EUCANIMAGE and EOSC4Cancer. We also do not lose sight of initiatives in the field such as the International Cancer Genome Consortium (ICGC) with the project ARGO, whose data model was adopted in EUCanCan.

  Blog cineca-eucancan-and-eucanshare-were-concluded-in-june

• Beacon v2 and Federated EGA, part of the GDI project Starter Kit to enable access to genomic and phenotypic data across borders

  The European Genomic Data Infrastructure project has released a ‘Starter Kit’ based on the rare disease and cancer proof-of-concepts from the Beyond 1 Million Genomes (B1MG) project. The Starter Kit, freely available to any interested parties, contains a set of software applications and components co-developed by the 20 GDI nodes and based on open community standards from the Global Alliance for Genomics and Health (GA4GH). Products in the Starter Kit give all countries the technical capability to access synthetic genomic and phenotypic data across borders. The image above shows the full workflow of the GDI Starter Kit user journey. The dotted circles are not included in the Starter Kit yet The EGA’s work is represented in the Starter Kit with Beacon v2 and Federated EGA among the software applications and components. About Beacon v2 Beacon is a protocol for data discovery. This API allows the search of genomic variants and associated information without breaching the datasets privacy. The European Genome-phenome Archive (EGA) is a key contributor to the Beacon v2 Protocol, the Beacon v2 Reference Implementation (B2RI) and the EGA Beacon(s). About Federated EGA The Federated EGA network offers a tool for data storage and sharing. Officially launched in 2022, this network of connected resources enables transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. The Federated EGA Onboarding Website contains all the information related to the establishment of a Federated Node.

  Blog beacon-v2-and-federated-ega-part-of-the-gdi-project-starter-kit

• The EGA joins EUCAIM, the European project powering AI and imaging in cancer research

  EUCAIM (EUropean Federation for CAncer IMages) is the cornerstone of the European Cancer Imaging Initiative, one of the flagships of the Europe’s Beating Cancer Plan (EBCP). The European Genome-Phenome Archive (EGA), as member of the EUCAIM consortium, attended the kick-off meeting organized this week in Brussels for the launch of the Initiative. The EGA will contribute to the project with the experience gained in the deployment of our federated network, the Federated EGA (FEGA), and the experience gained as partners of EuCanImage (AI4HI initiative) contributing to the definition of common data models, ontologies and data standards. The ultimate goal of the project is to unlock the power of imaging and Artificial Intelligence for the benefit of cancer patients, clinicians and researchers. The consortium will deploy a pan-European digital federated infrastructure hosting cancer-related images, and associated pathology, molecular and laboratory data from Real-World. This endeavour will provide a comprehensive dashboard for imaging data discovery, federated search, metadata harvesting, annotation and distributed data processing. EUCAIM joins 76 partners, gathering the experience and previous effort made by the different repositories of the AI4HI initiative, European Research Infrastructures and national/regional repositories. Find out more information about the EUCAIM launch here

  Blog the-ega-joins-eucaim

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

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

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

• Providing safe access to sensitive human data across borders: Federated EGA becomes a reality

  Enabling discovery and access to sensitive data across national boundaries is vital for improving human health. It enables more powerful and efficient research by increasing the volume and diversity of data available for analysis. It allows us to better understand the causes of diseases – cancer, rare diseases, infectious diseases like COVID-19 – and develop new medicines and treatments. Sensitive human omics data are typically generated by research initiatives and shared using specialist repositories which provide services for data submission, discovery, and access. The EGA is one such repository. Established in 2008 at EMBL’s European Bioinformatics Institute (EMBL-EBI) in the UK, since 2012 the EGA (“Central EGA”) has been jointly managed by EMBL-EBI and the Centre for Genomic Regulation (CRG) in Spain. Many countries have emerging personalised medicine programmes which generate data from national initiatives. These programmes are driving a transition in human genomics from being research-driven to receiving funding through healthcare. Data generated in a clinical context are subject to stricter governance than research data and must follow national data protection legislation. To solve these challenges, the Federated EGA provides a network of connected resources to enable transnational discovery of and access to human omics data for research, while also respecting jurisdictional data protection regulations. In this way, the Federated EGA infrastructure supports the goals of European initiatives such as the 1+ Million Genomes initiative (1+MG), the European Health Data Space, and a number of EU-funded 1+MG implementation projects including Beyond 1 Million Genomes. The Federated EGA is made up of “Nodes” – typically nationally funded and operated – which store and manage data locally while allowing global discovery within the Federated EGA network. Since 2016, multiple parallel efforts, supported by ELIXIR and other transnational and national initiatives, have created technical and legal frameworks for establishing the Federated EGA. In 2022, the first five Nodes – Finland, Germany, Norway, Spain, and Sweden – officially joined the Federated EGA by signing Federated EGA Collaboration Agreements with Central EGA. The Finnish FEGA Node is operated by CSC - IT Center for Science and provides data management services according to national laws and the requirements of the EU General Data Protection Regulation (GDPR). These services provide tools and support for the whole life-cycle of sensitive research data from collating to analysis, publication, and authorised re-use. The development of the services has been a joint effort with the other Nordic nodes within NeIC's Tryggve and Heilsa projects, and funded by Finnish Ministry of Education and Culture and projects coordinated by ELIXIR Finland. Read more about Finnish FEGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. The German Human Genome-Phenome Archive (GHGA) strives to provide a national infrastructure as well as an ethical and legal framework that balances FAIR omics data usage and data protection needs for Germany. As a Germany-wide consortium funded by the German Research Foundation under the umbrella of the NFDI association, GHGA combines the expertise of 21 universities and research institutions to form a federated national infrastructure. Read more about GHGA signing. In Norway, a key component of the infrastructure is the services of The Sensitive Data Service (TSD) offered by USIT at University of Oslo. The Federated EGA Norway Node is developed by ELIXIR Norway and operated by the University of Oslo as the responsible legal entity. Core software modules are developed jointly with the other Nordic nodes in the NeIC Tryggve and Heilsa projects. Read more about FEGA Norway signing. The Spanish FEGA (es-FEGA) is a national service for storing sensitive biomedical data in Spain. Supported by the Spanish Institute of Bioinformatics (INB) in collaboration with Central EGA, sensitive research datasets are primarily hosted at the Barcelona Supercomputing Centre facilities. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. The Swedish Sensitive Data Archive is a secure data archive and sharing platform for sensitive datasets. It was developed by the National Bioinformatics Infrastructure Sweden (NBIS) in collaboration with other Nordic ELIXIR Nodes through the Tryggve and Heilsa projects funded by NeIC and coordinated with Central EGA through ELIXIR. Read more about the Swedish Node signing. By providing a solution for secure and efficient management of human omics data, the Federated EGA aims to foster data reuse, enable reproducibility, accelerate biomedical research, and improve human health. Find out more Interested in setting up your own Federated EGA Node? Check out the FEGA Onboarding Knowledge Base for more information. The ELIXIR Federated Human Data Community is a great entry point for anyone interested in learning more about the Federated EGA. You can: Join the ELIXIR Federated Human Data Community mailing list (select “Human Data”) Attend the ELIXIR Federated Human Data Community calls

  Blog safe-access-to-sensitive-human-data-federated-ega

• How upcycled prostate cancer sequences enabled key findings on telomeres length

  The length of telomeres, the chromosomes’ end tails, as depicted in the figure below, physiologically shorten with aging. This means that younger cells have longer telomeres compared to their aged counterparts; one could say that the length of cells’ telomeres is a measure of their replicative power. Cancer cells are known to be able to turn this into their favour, and expand their replicative immortality through telomere lengthening and maintenance. Despite being a well-studied pan-cancer hallmark, the relation of the telomeres length to specific cancer genomic features is poorly understood. Julia Livingstone and her colleagues from P.C. Boutros' team in Los Angeles focused their work on prostate cancer. To investigate the relations between telomere length and the clinico-genomics of prostate tumours, they used whole genome sequencing (WGS) of 392 published tumour–reference pairs previously deposited at the EGA under accession numbers EGAS00001000400 and EGAS00001000900. Their work was published on Nature Communications in November 2021. They determined the telomere length of the sequencing sample, from both tumour and non-tumour adjacent tissues, and subsequently ran statistical analysis to investigate possible correlation between the telomeres length with several cancer features. The team discovered that telomeres length does not correlate with any specific driver gene mutation, but it does with the overall frequency of single nucleotides variants in a sample. This finding suggests that tumours with shorter telomeres accumulate more mutations without strong selective pressures for specific ones. While proliferation rate did not correlate directly with telomere length, methylation of almost half of all genes strongly did. The team’s results are massive and reveal a complicated and fascinating relation of different clinical and genomic features of prostate cancer with telomere length. In the paper discussion, they smartly consider different possibilities. As noted above, all these amazing results have been obtained analysing previously sequenced samples. Remarkably, the researchers who generated the samples did not focus at all on telomeres length. They indeed studied specific genes mutations and the features of early and late-onset prostate cancer. This proves, once again, the power of sequencing data re-use. This data is tremendously rich in information, and can hardly be exhausted with any number of analyses. Generating sequencing data, especially Whole Genome Sequencing, even better if tumor-reference paired, is like shopping every last article at the grocery store. You can then cook several recipes, or prepare a seven-course dinner, and still have ingredients left for someone else to borrow and cook something you have not thought about, a recipe that is just not in your cookbook. Noteworthy, the data retrieved from the EGA for this paper is associated with rich and complete metadata, meaning pheno-clinical information regarding the sample donors. As Julia Livingstone and her team wrote, using rich clinical annotations enabled them to assess the relationship between telomere length and patients outcome. This highlights once again the importance of reporting and annotating metadata correctly; It might feel like extra work for the researchers depositing their data, but it really has a huge value. Our team at the EGA is currently working to improve the metadata annotation process, with the aim to maximize the benefits for the scientific community.

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• EuCANCan: EUropean-CANadian Cancer network

  The EUropean-CANadian Cancer network (EuCANCan) is a project aiming to develop a federated network of aligned and interoperable infrastructures for the homogeneous analysis, management and sharing of genomic oncology data for Personalized Medicine. This initiative, funded by the European Commission and the Canadian Institutes of Health and coordinated by the Barcelona Supercomputing Center (BSC), is expected to process and provide the scientific community with around 30-35 thousand patient samples from different types of cancer, coming from different nodes involved in this project, during the four years of the project. Data generated as part of primary studies, often in small hospitals or research centers, is hardly reused by other projects or groups. EuCANCan is proposed to foster the homogenisation and discoverability of cancer samples from very different sources for the whole community. These efforts will help paving the way to future standardised and global genomics projects, specially for those participant countries that eventually integrate the methodology and infrastructure generated during the project. “The more data we have access to the more and better discoveries. We attempt to overcome the legal and technical limitations in order to generate, gather and exploit bigger datasets as well as answer more ambitious questions”. These were some of the words Dr. David Torrents, main coordinator of the project, shared with a regional radio during the kick-off meeting of the project, on February 11th, 2019. The EUCANCan network will be composed of reference nodes in Amsterdam, Barcelona, Berlin, Heidelberg, Paris and Toronto which have established strong research and clinical programs in the field of genomic oncology. The Centre for Genomic Regulation (CRG), specifically the European Genome-phenome Archive (EGA), is among the leading institutions. Its exhaustive experience in biomedical data archival and secure distribution is considered key for crucial developments within the project. It is also notable the recent inclusion of EUCANCan in the list of GA4GH driver projects. Further information and details can be found in the following links: InsideHPC BSC official description Techweek (Spanish)

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• The last addition to the list of clonal evolution studies in the EGA

  Tumours of different types may arise from a single cell with at least one malignant mutation. Accumulation of subsequent hits generates lineages of cells with different cancer transformation power; thus, every clone follows an autonomous evolution, and several clones may co-exist into the same solid or liquid tumour. Clonal evolution studies are not new: the conceptual power of this approach has been recognized since the early ’80, especially in leukaemia patients. Nonetheless, these studies greatly benefit from recent technological improvements -machineries and protocols-, which enable ever-increasing sequencing depth, allowing the detection of low frequency variants and consequently more tumour clones. Note: the figure belongs to the original paper and is owned by the authors. Researchers at the University of Kyoto in Japan, have indeed used state of the art knowledge to investigate the clonal evolution of chronic myeloid leukemia (CML) in a large panel of patients. CML progresses from a majoritarian benign chronic phase into an often fatal blast crisis phase. It is nowadays known that blast crisis are triggered by genetic instability and disrupted DNA repair, which lead to accumulation of DNA mutations. The use of thyrosine kinase inhibitors targeting the Philadelphia chromosome have enormously improved the treatment of blast crisis, nonetheless resistant patients are still a medical challenge. Yotaro Ochi and collegues used Whole Exome Sequencing of paired chronic phase and blast crisis samples to depict the genetic landscape of progression from the first to the second stage of the disease (as illustrated in their figure). Their results were published in Nature Communication on this May 2021. They used a dataset previously deposited at the EGA (EGAS00001003071) and their new generated data have been made available under accession number EGAS00001005075. Their analysis of the occurring mutations contribute to understanding the mechanisms of CML evolution and therefore develop a protocol for early management of patients with a TKI resistance signature. Up to date, the EGA hosts 99 clonal evolution studies, developed in several cancer types, including myeloma, renal carcinomas and ovarian cancer, in addition to various leukaemia subtypes, where this approach has been more widely applied and produced important results and seminal papers. From a pan-cancer point of view, the definition of tumour architecture through clonal evolution studies is instrumental to unravel the mechanisms of disease progression and treatment-resistance insource. At the EGA, we are honoured to contribute to exciting and important science advances with our service!

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• Data Use Ontology (DUO) at EGA

  For those of you that follow the updates of GA4GH you will have seen the unanimous approval of the steering committee for DUO to be included in its suite of technical standards for the sharing of genomic and health related data. DUO has three main features: Each term has been generated by the community and includes a human readable definition that can be expanded where necessary. It is a machine-readable file that encodes how that data can be used and how a researcher intends to use the data. Can be implemented alongside an advanced search algorithm which would allow authenticated users to query and gain access to datasets pertaining to their research. e.g., an industry researcher working on cancer could potentially be matched to any dataset that is allowed for commercial use and for cancer research and offered the opportunity to fetch them automatically. So, what does this mean for EGA? EGA as a driver project has adopted this standard and will be utilizing it for two main purposes in the first instance. i) It will allow EGA users to instantly identify what terms they will need to agree to as part of any Data Access Agreements. This will save valuable time for both applicants and Data Access Committees alike - as you will be able to see if you are likely to be able to access the data based on your research intentions and working background. ii) In the future it will allow users to be able to search for data based on Data Use Ontology terms e.g., you could search for all data that can be used for General Research Use (GRU). As EGA moves forwards submitters will be asked to align their data access policies with DUO so that their dataset(s) can be tagged appropriately on our web pages. If you would like to add DUO to any of your existing datasets, or to any future datasets, do please just let us know.

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• Advancing fast in the analysis of circulating tumour DNA

  In cancer patients, solid tumours also release DNA fragments into the blood, and they are called Circulating Tumours DNA (ctDNA). Nowadays, the standard procedure for cancer monitoring is analysis of surgically obtained biopsies. They generate a big amount of material, but the operation is highly invasive and provide medical doctors with a single-time snapshot of the tumours, which are often highly changeable. Analysis of ctDNA, on the other hand, can provide continuous information regarding the tumour itself without the need of invasive procedures. This is why interest in this method is growing, and with it, the need for its technological optimization. Guanhua Zhu and colleagues, at the Genome Institute of Singapore, developed a methodology to quantify ctDNA burden, which means to estimate the amount of tumours derived circulating DNA among all cell-free DNA in the blood of individuals. Their work, published in Nature Communications in april 2021 and summarized in a sketch below, uses state-of-the art methods to analyse cfDNA degradation patterns at promoters and exon regions, to discern it from the DNA coming from the tumours. The bright point of their approach is that simultaneously enable for profiling of actionable cancer mutations and quantitative estimation of ctDNA burden. Their sequencing data of ctDNA has been deposited in the EGA under the accession number EGAS00001004657. This study sums up to a total of 37 of cfDNA and 36 about ctDNA present up to date in the EGA archive. The existence of cfDNA was firstly described back in 2002, while the use of ctDNA analysis in the oncological field exploded only after 2016. The approach is rapidly evolving, moving in parallel with the ever-improving sequencing technologies. Especially, the possibility to obtain high quality sequences from minimal amount of material is a crucial factor. Being able to alleviate cancer patients of disturbing and often slow-recovery procedures, while at the same time improving the quality of diagnosis and disease monitoring seems like a lot to ask. Thankfully, we are blessed with brilliant and dedicated scientists from all around the world who collaborate to make this a reality, sharing their results, knowledge and data.

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• Finding the way towards the eradication of therapy-related myeloid neoplasms

  Therapy-related neoplasms are directly caused by the drugs used to eradicate a previous cancer. It is well known that a subset of drugs designed to kill cancer cells through DNA-damage-induced apoptosis can intrinsically, as secondary effect, cause DNA-damage in other cells, thus inducing a neoplasm. Those neoplasms have especially bad prognosis. Why are these drugs still in use? Because for many diseases we do not have anything better, at the moment. Approximately 0.5-1% of the kids treated for various types of cancers develop a therapy-related myeloid neoplasm (tMN) as a result of the treatment. Despite having the same origin, their prognostic and molecular features are different from the adult ones, and a complete understanding of the pathogenesis of tMN in children is still missing. A total of 84 paediatrics neoplasms have been profiled by either Whole Genome or Whole Exome sequencing by Jason R. Schwartz and his colleagues, in a collaborative effort guided at the St. Jude Children's hospital, in Memphis. They identified a mean of 28 somatic mutations per patient, a number which is significantly bigger than the number of mutations found in paediatrics primary neoplasms, as depicted in the original paper's figure 1b, shown here. Their sequencing data identified that Ras/MAPK pathway mutations, alterations in RUNX1 or TP53, and KMT2A rearrangements as the most frequent drivers of the disease. Clonal evolution analysis (the comparative study of the behaviour of cells harbouring different mutations) highlighted that, unlike in adults’ tMN, there were not pre-existing leukemic clones, and virtually all mutated cells were found arising as a direct consequence of cytotoxic therapy. This represents yet another important difference between adult and paediatric tMN. This important study have been published in Nature communications in February 2021. The sequencing data have been deposited at EGA under the study number EGAS00001004850. Thanks to this, other researchers around the world could re-use it to uncover more information, integrate and validate their studies. Revealing the molecular features underlying the development of cancers is the only way towards the development of new generation targeted therapies, which will allow us to finally drop the cytotoxic drugs eliciting such unwanted and catastrophic secondary effects as tMN. It is not an overstatement to say that, while improving the treatment of primary tumours, we could entirely eradicate therapy-related neoplasms right from their origin. Looking forward.

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• Data upcycling, powered by EGA

  In 2012 a collaborative effort headed by the teams of Carlos Caldas in Cambridge, UK and Samuel Aparicio, Canada, produced a pivotal study aimed at defining the mutational landscape of breast cancer. They gathered a collection of over 2000 breast cancer samples (METABRIC) associated with long-term clinical follow-up. They delineated an array of inherited and somatically acquired genetic variants and associated them to gene expression. This led to the identification of putative cancer-driving events and improved stratification of breast cancer patients. The study elicited huge attention and was tackled as herculean effort by fellow researchers. Cristina Curtis and her colleagues deposited the data in the EGA archive (EGAS00000000083). What they probably could not foresee is that their data would be reused more than 100 times, becoming one of the most downloaded datasets at EGA. In 2015, Frederik S. Varn and colleagues accessed the above-mentioned data from the New Hampshire, USA, to correlate it to transcriptional programs of hematopoietic cells infiltrated in breast tumours and found that those can influence patients' prognosis. Their findings, published in Nature Communications, improved the understanding of the interplay between immune system and cancer. Again, in 2017 the dataset was downloaded by an Italian/Polish collaboration and used to corroborate their mechanistic study that demonstrate how a long non-coding RNA (lncRNA) is aberrantly localized into the chromatin, where it modulates oncogenic isoforms expression, thus contributing to breast cancer. To date, the METABRIC dataset has been reused to contribute to 147 publications. Its impact on breast cancer research is incalculable, and it even spread beyond that, with recent contributions to the understanding of pan-cancer mechanisms and features. Some of the publications are translating into improvements in diagnosis and treatment of different types of breast cancer. This is just an example of how data upcycling can amplify the potential of any dataset, well past the scope of its creation, the imagination of its owners and any geographical border. At EGA, we are proud to empower such fruitful worldwide cycles of knowledge, providing a platform that enables safe sharing of sensitive genetic data.

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• Gut microbiome dynamics unravelled with metagenomics sequencing

  It has been already several years since we discovered that microbial therapeutics like Faecal Microbiota Transplantation can be used to treat Clostridium difficile infection (CDI) and Inflammatory bowel disease (IBD) with great success. The concept has challenged us to test the limits of our knowledge with the perspective to improve health in the most diverse conditions like Parkinson disease, depression, autism and obesity, just to mention a few. Note: the figure belongs to the original paper and is owned by the authors. Allyson L.Bird and colleagues from Genentech Inc. (San Francisco) recently published an interesting study building up on the key concept that “As microbial therapeutics are increasingly being tested in diverse patient populations, it is essential to understand the host and environmental factors influencing the microbiome.” The authors of this work analysed 1359 gut microbiome samples using shotgun metagenomics sequencing.  The results of the comparison done between microbiota composition across the different groups showed that biological sex is the strongest driver of diversity, while aging (age range studied: 20–69) appears to be the second factor. As smartly outlined in the authors’ own graphical abstract (figure to the left), Bacteroidota species consistently increased with donors' age while Actinobacteriota species, including Bifidobacterium, decreased. This study also integrated data from oncological patients to draw cancer-related evidences. After correcting the biases for technical and geographic differences, they found that cancer patients show significantly altered gut bacterial communities compared with their healthy counterparts. Eg. E.coli was found to be increased in cancer patients together with Bacteroidota/Firmicutes ratios. By comparing sequential samples taken from the same donors (413) within short-distance time points, the authors found that in the short term, intra-individual differences were less than the inter-individual ones, indicating a certain community stability being the norm. One of the pivotal points from this interesting study is that the data proceeds from extremely well-defined and selected donors. Specifically, the data for 949 selected healthy donors came from the Milieu Intérieur (MI) Consortium and extensive metadata, including demographic variables, serological measures, dietary information, and systemic immune profiles, are available. This precise stratification allowed for the robust detection of smaller changes, compared to former works. All sequencing data has been deposited in the EGA archive under the accession number EGAS00001004437. Enjoy this amazing open access paper published in the Experimental Journal of Medicine on January 2021.

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• Discover Cancer Image Europe, the first release of the EUCAIM platform to fuel cancer research and data sharing

  The EUCAIM consortium and the European Commission have announced the release of Cancer Image Europe, a platform to fuel collaborative innovation and data sharing across Europe. This constitutes a major milestone in EUCAIM's development and an exciting step towards achieving the project's vision and goals. The platform aims to accelerate the pace of AI development and other data-intensive cancer research activities, constituting the basis for a fully-fledged infrastructure for sharing, reusing, and exploiting cancer imaging data, especially using AI techniques. A platform paving the way for the future of cancer diagnosis and treatment Cancer Image Europe brings benefits to researchers, clinicians, and AI innovators across Europe as it addresses the fragmentation of existing cancer image repositories. The platform gathers a public catalogue of cancer imaging datasets from the repositories of the EU-funded AI for Health Imaging projects. A distributed Atlas of Cancer Imaging with over 60 million anonymised cancer image data from over 100,000 patients will be established as part of future updates. The first version of Cancer Image Europe also includes a public catalogue of cancer imaging datasets, a federated searching tool to understand the information available in the federated providers, and full integration with Life Science Login. Moreover, it reuses and adds value to key components of EU-funded research projects and infrastructure in the field of cancer. The Public Catalogue When we talk about data re-use, data discovery is key. The EUCAIM public catalogue is the result of a systematic and collaborative process to which the EGA-CRG has actively contributed. This browsing interface gathers the metadata of the available cancer imaging datasets. This descriptive information will help researchers in their data retrieval. Our contribution to the Public Catalogue comes from our experience gained in the deployment of our federated network, the Federated EGA (FEGA), and as partners in projects such as EuCanImage (AI4HI initiative), in which we worked on the definition of common data models, ontologies and data standards. The EUCAIM Project EUCAIM is a cornerstone of the European Commission-initiated European Cancer Imaging Initiative, a flagship of the Europe's Beating Cancer Plan, which aims to foster innovation and deployment of digital technologies in cancer treatment and care, to achieve more precise and faster clinical decision-making, diagnostics, treatments, and predictive medicine for cancer patients. For more information about the first release of the Cancer Image Europe platform and the EUCAIM project, please visit cancerimage.eu.

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• First datasets available in the Federated EGA Network

  In February 2024, a great milestone was reached for the human omics data community: the first datasets are now available in the Federated European Genome-phenome Archive (FEGA). These datasets - hosted by national nodes in Poland, Norway, and Sweden - are discoverable in the EGA portal and accessible according to national laws. These datasets include: From FEGA Poland - The Genomic Map Of Poland From FEGA Norway - CRCbiome: Gut metagenome of Norwegian screening participants using FIT sampling Also from FEGA Norway - Single cell transcriptomics in expanded Tregs of APS-1 patients From FEGA Sweden - A Combined Omics and Tissue Biobank for Paediatric Cancers The establishment of these datasets represents a significant step towards achieving the broader objectives of the FEGA; to facilitate the sharing of high-quality human genomic and phenotypic data across borders. “The value for users is twofold: it becomes easier to make data available securely compared to storing data locally, and data becomes easier to find for other researchers. The possibility of reuse improves the chances of both verifying scientific discoveries and reaching groundbreaking conclusions, of benefit to the research community and later also patients,” said Anna Hagwall, project manager and head of human data at FEGA Sweden, NBIS. About Federated EGA FEGA was launched in 2022 as a network to store and lawfully share sensitive human omics data safely. It relies on the technology originally developed by the EGA and support from ongoing collaborations with ELIXIR - a European life sciences infrastructure. FEGA has contributed to and benefitted from the implementation of community standards for sensitive data management including those developed by the Global Alliance for Genomics and Health (GA4GH). “The FEGA concept and the development of the Nordic FEGA nodes have been made possible thanks to several projects coordinated by NeIC,” said Kjell Petersen, FEGA Norway technical lead. Managing human omics data is challenging due to its sheer size and privacy concerns, often resulting in restrictions on how and where sensitive data can be shared. The FEGA network follows a federated data access model whereby sensitive data is stored securely within a local or national jurisdiction, while discovery across the network for data of interest is enabled via a central portal. As of February 2024, the FEGA network comprises seven European national nodes with tens of additional national partners working towards establishing a FEGA node. As the FEGA network continues to onboard nodes from around the world, populated with more and more data, we move closer to a vision of a truly global resource for discovery of and access to sensitive human omics data to accelerate disease research and improve human health. "The Federated EGA network is entering a key phase where the first research datasets are now available across the network. In coming years, we look forward to expanding these datasets to cover key areas such as cancer and rare diseases for the benefit of patients" said Thomas Keane, Group Leader at EMBL-EBI.

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• How mitochondrial DNA research can benefit from data reuse through EGA?

  Mitochondria are the only cellular organelles harbouring their own DNA, which encodes for proteins essentials in its respiration process. Despite its discovery in 1960, Mitochondrial DNA is often overlooked compared to nuclear DNA. Indeed, not all sequencing technologies capture a good representation of mtDNA (mitochondrial DNA). Recently, Ed Reznik's team (The Ed Reznik Lab | Memorial Sloan Kettering Cancer Center) carried out a massive analysis and reanalysis of single cells WGS (whole genome sequencing) produced with an amplification-free protocol (Direct library prep, DLP). As they demonstrated in the paper Single-cell mtDNA dynamics in tumors is driven by coregulation of nuclear and mitochondrial genomes - PMC, DLP is more effective in catching mtDNA compared to classical single-cell sequencing. These data allowed the team to unravel mtDNA dynamics in tumoral and normal samples, highlighting how mtDNA and nuclear DNA are co-regulated and their ratio is critical for phenotype. Data reuse to achieve the greatest results For this project, Reznik's team re-used data from 3 studies stored at the European Genome-phenome Archive (EGAS00001006343, EGAS00001004448 and EGAS00001003190) that comprised a total of 602 datasets. All of them were initially produced by the teams of Sam Aparicio and Sohrab P. Shah at the Memorial Sloan Kettering Cancer Centre, where Ed Reznik is a promising group leader. This demonstrates, once again, that networking, collaboration and data sharing can achieve the greatest results when coupled with innovative and smart ideas. At the EGA we are proud to provide the scientific community with an infrastructure to enable all those very smart ideas out there to find the right data to be tested.

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• Drug development for pediatric cancers: the importance of patient' s genomic data re-use

  Cancer in children is uncommon and the overall prognosis for most pediatric cancers is good. However, while the combined survival rates have improved over the last decades, certain childhood malignancies, such as high-grade gliomas or metastatic sarcomas, still remain incurable in most patients. New strategies for targeting those devastating diseases are imperative, and patient genomic data can become a key asset in the process [1]. The Pediatric Cancer Genome Project’s datasets At EGA, we store over 500 datasets with sequencing data from pediatric cancer patients. A remarkable case is the datasets belonging to the Pediatric Cancer Genome Project (PCGP) from St. Jude Children’s Research Hospital–Washington University (Table 1 - EGAS list). PCGP is an ambitious effort to identify the mutations that drive childhood cancer and find new cures. Those datasets include 600 patients with complete tumor and normal genomes from 15 different tumor types. PCGP datasets have been an important resource for various studies that pooled genomic data from different public and in-house datasets to perform extensive genomic characterizations and publish comprehensive pan-cancer pediatric studies [2],[3]. Other interesting pediatric cancer datasets are from the Pediatric Brain Tumor Consortium, Sickkids or ICGC PedBrain project. How data reuse impacts drug development for pediatric cancers Recently, in October 2024, Nature Communications published a work led by the University of Michigan where authors used data from EGA (PCGP) check the table below as part of their strategy to pursue the identification of new tumor vulnerabilities susceptible to becoming novel therapeutic targets in diffuse midline glioma. Diffuse midline gliomas (DMG) are treatment-resistant and uniformly fatal pediatric brain tumors. The prognosis of this brainstem tumor is dismal with a median overall survival of 9–12 months from diagnosis. In this study, the authors first developed a lab model of the disease and reanalyzed data from the EGA to identify genes potentially linked to tumor severity. This approach revealed involvement of specific metabolic pathways, suggesting new possibilities for therapeutic intervention. In mice, the study shows that the use of statins can improve survival. For a brief overview of the underlying science, diffuse midline gliomas present intratumor heterogeneity with subpopulations of less-differentiated oligodendrocyte precursors and more differentiated astrocytes. Authors established in vitro models to recapitulate both phenotypes and identify metabolic programs in both subpopulations. To determine the clinical relevance, the authors re-used gene expression data from 76 DMG patients identifying a gene signature predicting decreased overall survival. After extensive metabolic characterization of subpopulations, authors defined strategies to target specific metabolic vulnerabilities. Pre-clinical experiments in mice using OXPHOS inhibitors and statins showed a reduction in tumor burden and increased overall survival [4]. In this scenario, the re-use of high-quality patient’s sequencing data appeared as an advantageous strategy to support the clinical relevance of in-vitro and pre-clinical findings. On the other hand, in rare conditions such as childhood cancer, the availability of public datasets and the possibility of pooling data from different sources can be the only way to obtain impactful results that lead to improvements for patients. References Davidoff, A. M. Pediatric Oncology. Seminars in pediatric surgery 19, 225–233 (2010). Gröbner, S. N. et al. The landscape of genomic alterations across childhood cancers. Nature 555, 321–327 (2018). Venu Thatikonda et al. Comprehensive analysis of mutational signatures reveals distinct patterns and molecular processes across 27 pediatric cancers. Nature Cancer 4, 276–289 (2023). Mbah, N. E. et al. Therapeutic targeting of differentiation-state dependent metabolic vulnerabilities in diffuse midline glioma. Nature Communications 15, (2024). Datasets and Studies ID Title Access Policy Year EGAD00001000134 Driver mutations in histone H3.3 and chromatin remodelling genes in paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAS0000100192 Somatic Histone H3 Mutations in Diffuse Intrinsic Pontine Gliomas and Non-Brainstem Paediatric Glioblastomas St. Jude Children's Research Hospital - Washington University Pediatric Cancer Genome Project 2017 EGAS00001000575 Whole genome sequencing and whole exome sequencing of DIPG tumors and matched normal tissue The hospital for sick children ("SickKids") 2016 EGAD00001000792 Exome sequencing reads of paediatric glioblastoma McGill-DKFZ Pediatric Brain Tumour Consortium 2016 EGAD00001002006 Whole genome sequencing of paediatric glioblastoma in the ICGC PedBrain project ICGC PedBrain project 2016

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• Enhancer profiling to identify identifies epigenetic markers of endocrine resistance in metastatic castration resistant prostate cancer patients

  Study EGAS00001006161

• Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer

  Emergence of resistance to immune checkpoint blockade (ICB) mandates the development of strategies for ICB sensitization. We aimed to understand the effects of epigenetic priming in re-shaping the tumor microenvironment, together with molecular drivers of therapeutic response of epigenetic therapy followed by ICB in non-small cell lung cancer (NSCLC; NCT01928576). This was done through a multi-omic approach encompassing both genomic and transcriptomic analyses. Findings suggest that epigenetic therapy may reshape the tumor microenvironment towards a more inflamed phenotype and prime responses to immunotherapy.

  Study EGAS50000000913

• Study of biomarkers implicated in radio-immunotherapy response in metastatic cancer

  Immuno-radiotherapy may improve outcomes for patients with advanced solid tumors, although optimized combination modalities remain unclear. Here, we report the analysis from the SABR-PDL1 (NCT02992912) trial that evaluated the PD-L1 inhibitor atezolizumab in combination with stereotactic body radiation therapy (SBRT) in patients with advanced cancer.

  Study EGAS50000001149

• Multi-omic dataset utilized in the analysis of a phase II study of epigenetic priming followed by nivolumab in lung cancer

  This dataset includes sequence files from whole exome sequencing and bulk RNA sequencing of tissue and blood biospecimens from a phase II clinical trial investigating epigenetic priming followed by immune checkpoint blockade in non-small cell lung cancer (NSCLC; NCT01928576). There are 78 whole exome sequencing files and 36 bulk RNA sequencing files included in this dataset.

  Dataset EGAD50000001336

• Study of biomarkers implicated in radio-immunotherapy response in metastatic cancer

  RNA sequencing data of tumors from 53 patients with advanced or metastatic cancer

  Dataset EGAD50000001644

• DAC for EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer

  This is the Data Access Committee for the EGA study: Multi-omic analyses from a randomized phase II study of epigenetic priming followed by nivolumab in previously treated metastatic non-small cell lung cancer (temp ID 800).

  Dac EGAC50000000563

• Identifying genetic variants that alter TCR usage in the peripheral repertoire

  The relationship between genetic variation and CD8+ T-cell receptor (TCR) repertoire usage in patients receiving Immune Checkpoint Blockade (ICB) therapy for cancer is unexplored. We have conducted a genome-wide and human leukocyte antigen (HLA)-focused analysis of CD8+ T-cell TCR repertoire to identify genetic determinants of variable gene (V-gene) and CDR3 K-mer usage from samples taken prior to and after ICB (n=250). We identify 11 cis and 10 trans V-gene associations, primarily to the MHC, that meet genome-wide significance. TCR clones containing HLA associated V-genes were less stable across treatment, whilst at the single-cell level, genetically associated clones demonstrate subset enrichment and increased tumor reactivity expression profiles. Notably, patients with HLA-matched TCR clones demonstrate improved overall survival. Our work indicates a complex relationship between genotype and TCR repertoire in the context of ICB treatment, with novel implications for understanding factors relating to therapeutic response and patient outcomes.

  Study EGAS00001008189

• The dataset for Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  The dataset for “Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types” includes 288 bam files from whole genome, whole exome and targeted next-generation sequencing on the Illumina HiSeq2500 and MiSeq. The samples analyzed include tumor and normal tissue samples from patients with cancer.

  Dataset EGAD50000000744

• Southern African Prostate Cancer Study (SAPCS) 70 whole bloods

  new 70 germline WGS data of prostate cancer patients

  Dataset EGAD50000001626

• DAC for Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  While endometrioid and mucinous ovarian cancers represent nearly a quarter of ovarian cancers, their molecular characteristics and pathologic origins are poorly understood. To characterize the genomic and epigenomic alterations of these ovarian cancer subtypes and evaluate links to morphologically similar tumors from other sites, we performed sequence, copy number, mutation signature, rearrangement, and methylation analyses from tumor samples and matched normal tissues of 133 patients. These analyses included patients with ovarian endometrioid (n=44), ovarian mucinous (n=43), uterine endometrial (n=15), and gastrointestinal mucinous cancers (n=31). In addition to identifying genes previously known to be involved in these tumors, we identified alterations in RAD51C, NOTCH4, SMARCA1/4 and JAK1 in ovarian endometrioid, ESR1 in uterine endometrioid, and SMARCA4 in ovarian mucinous cancers. Whole genome sequencing revealed rearrangements involving PTEN, NF1, and NF2 in ovarian endometrioid tumors, and NF1 and MED1 in ovarian mucinous cancers. The number of alterations and affected genes in ovarian and uterine endometrioid cancers were similar as were genome-wide methylation profiles, suggesting that these tumors may have a similar tissue of origin. By contrast, methylation patterns in ovarian mucinous cancers were more similar to other gastrointestinal mucinous cancers, including mucinous cancers of the stomach, colon, and pancreas. These analyses provide insights into the genomic landscapes and origins of mucinous and endometrioid ovarian carcinomas, providing new avenues for early clinical intervention and management of patients with these cancers.

  Dac EGAC50000000341

• LOGGIC Core BioClinical Data Bank: Added clinical value of RNA-Seq in an international molecular diagnostic registry for pediatric low-grade glioma patients

  Study EGAS00001007072

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

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

  Study EGAS00001003280

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

  Study EGAS00001004521

• Ultra-Low-Pass Whole Genome Sequencing of Cell-Free DNA for Large B-Cell Lymphoma

  While deep targeted DNA sequencing of liquid biopsies has shown prognostic utility in large B-cell lymphoma (LBCL), the routine clinical adoption of these assays remains limited due to their high costs. Here, leveraging a well-annotated cohort of encompassing both frontline and relapsed/refractory (R/R) LBCL, we profiled patient plasma samples with two complementary modalities – ultra-low-pass whole genome sequencing (ulpWGS) and deep targeted DNA sequencing, the former being a cost-effective method to profile large scale chromosomal abnormalities and estimate tumor burden. Our findings revealed a strong association of high cell-free tumor burden by both genomic profiling modalities with established measures of tumor burden and patient survival. Notably, the associations with survival remained statistically significant after accounting for international prognostic index scoring. Furthermore, we showed that del(17p) in circulating tumor DNA as detected by ulpWGS was strongly associated with TP53 mutation status and predicted for significantly inferior patient outcome in frontline but not R/R LBCL patients. Our study demonstrates that ulpWGS can provide robust prognostic biomarkers for both frontline and R/R LBCL, highlighting its broad applicability for risk stratification.

  Study EGAS50000001027

• Shifted assembly and function of mSWI/SNF family subcomplexes underlie targetable dependencies in endometriod carcinomas

  The mammalian SWI/SNF (mSWI/SNF) family of chromatin remodelers govern cell type-specific chromatin accessibility and gene expression and assemble as three distinct complexes: canonical BAF (cBAF), Polybromo-associated BAF (PBAF), and non-canonical BAF (ncBAF). ARID1A and ARID1B are paralog subunits that specifically nucleate the assembly of cBAF complexes and are frequently dual deleted in highly aggressive differentiated endometrial carcinomas (DECs). Here, in cellular models and primary human tumors, we find that ARID1A/B-mediated cBAF loss results in increased ncBAF and PBAF biochemical abundance and function genome-wide to maintain the DEC oncogenic signature. Further, treatment of ARID1A/1B-mutant cell lines and PDX models in vivo with a clinical-grade SMARCA4/2 ATPase inhibitor, FHD-286, markedly attenuates cell proliferation and tumor growth, and synergizes with carboplatin-based chemotherapy. Taken together, these findings reveal the oncogenic contributions of shifted of mSWI/SNF family complex abundance and chromatin-level gene regulatory functions and suggest therapeutic utility of mSWI/SNF complex small molecule inhibitors in dedifferentiated endometrial carcinoma and other cBAF-disrupted cancer types.

  Study EGAS50000001004

• Diversity of U1 small nuclear RNAs and Evaluation of Diagnostic Methods for their Mutations

  U1 small nuclear RNA (snRNA) mutations are recurrent non-coding alterations found in various malignancies, including medulloblastoma, yet their identification has proven challenging due to their repetitive nature. To establish a robust DNA-based, and RNA-based method for detecting U1 snRNA mutations, we performed targeted DNA sequencing using our original gene panel for medulloblastoma and RNA-sequencing. As an RNA-based method, we developed a random forest classifier employing splicing patterns which were massively altered as a result of U1 snRNA mutations. By using both methods, we successfully detected U1 snRNA mutation in five DNA samples and four RNA samples.

  Study EGAS50000000693

• SCANDARE HNSCC

  Prospective biobanking study in SCANDARE HNSCC (Head and Neck Squamous Cell Carcinoma) patients aiming at better understand the link between the molecular alterations of the tumor itself, its microenvironment and immune response.

  Study EGAS50000001158

• SCANDARE ovarian

  Prospective biobanking study in ovarian cancer patients aiming at better understand the link between the molecular alterations of the tumor itself, its microenvironment and immune response.

  Study EGAS50000001161

• SCANDARE ovarian WES data

  SCANDARE (NCT03017573) is a multicentric biobanking study, enrolling adult patients with newly diagnosed head and neck squamous cell carcinoma (HNSCC), triple negative breast cancer (TNBC), ovarian and cervical cancer. Tumor tissue and blood samples are collected at several time points during patient's journey, including at diagnosis, post-neoadjuvant chemotherapy in case of neoadjuvant treatment, at surgery, at recurrence and at disease progression following treatment initiated at recurrence. Since its launch in 2017 at Institut Curie, SCANDARE has enabled the longitudinal collection and preservation of samples for in-depth analyses. Here, we describe molecular alterations in 91 frozen samples (n = 53 at baseline, n = 31 Post-NAC, n= 7 Recurrence, and n = 62 germline DNA) from 64 ovarian cancer patients using WES technology, with FASTQ files deposited in the dataset.

  Dataset EGAD50000001658

• Predicting resistance to chemotherapy using chromosomal instability signatures

  The aim of this study is to assess whether three chromosomal instability signature biomarkers are capable of predicting resistance to standard chemotherapies, namely platins, taxanes and anthracyclines. As part of this study we compiled a proof of principle cohort of ovarian cancers treated with these therapies, profiled using the Illumina TSO500 panel. Analysis of these data demonstrated that accurate biomarker calling can be computed from these gene panel data.

  Study EGAS50000000992

• Final results and ctDNA analyses from the randomized phase 3 IMpassion031 trial evaluating peri-operative atezolizumab for early-stage triple-negative breast cancer

  In IMpassion031, adding atezolizumab to neoadjuvant chemotherapy significantly improved pathologic complete response (pCR) rate (primary endpoint) for stage II/III triple-negative breast cancer (TNBC). Patients with stage II/III TNBC were randomized 1:1 to neoadjuvant chemotherapy plus peri-operative atezolizumab or pre-operative placebo. Descriptive secondary endpoints included event-free, disease-free, and overall survival. Long-term outcomes favored the atezolizumab group (event-free survival HR 0.76, 95% CI: 0.47–1.21). Among patients without pCR, 14/70 (20%) atezolizumab-treated and 33/99 (33%) placebo-treated patients received additional adjuvant therapy, frequently capecitabine. In exploratory analyses, pCR was prognostic for long-term outcome. Patients with baseline ctDNA-negative status (6%) had excellent long-term outcomes. Most patients (87%) had cleared ctDNA at surgery. ctDNA-positive status at surgery identified a subset of non-pCR patients with poorest prognosis. Long-term safety was consistent with primary results. Adding atezolizumab to chemotherapy for stage II/III TNBC is associated with more favorable long-term outcomes. ctDNA dynamics provide prognostic value beyond pCR. ClinicalTrials.gov identifier: NCT03197935

  Study EGAS50000000974

• Sequenced IDH wildtype, untreated, human glioblastoma samples (GB-UK cohort)

  BAM files for 42 IDH wildtype, untreated, human glioblastoma samples from the GB-UK cohort, published in Noorani & Haughey et al. Cancer Discovery (2025).

  Dataset EGAD50000001649

• DynaTag for efficient profiling of transcription factors in small samples and single cells

  Systematic discovery of transcription factor (TF) landscapes in low-input samples and at single cell level is a major challenge in the fields of molecular biology, genetics, and epigenetics. To address this, we present here cleavage under Dynamic targets and Tagmentation (DynaTag), which allows robust mapping of specific TF-DNA interactions via the use of a physiological salt solution during sample preparation. Using this method, we revealed occupancy alterations for 15 different TFs in stem cell and cancer tissue models. Of note, we showcased for NANOG, MYC, and OCT4 differentially occupied genomic loci during stem cell differentiation, both in bulk and at single-cell resolution. DynaTag demonstrated superior signal-to-background ratio and occupancy resolution in comparison to CUT&RUN and ChIP-seq. In addition, a model for small cell lung cancer chemotherapy treatment in vivo showed increased chromatin occupancies of the gain-of-function mutant P53 p.R248Q, FOXA1, and MYC at altered gene pathways, such as epithelial-mesenchymal-transition. Altogether, these results highlight the technical advancement of DynaTag to uncover TF landscapes in cell models and in tissues of a complex disease model.

  Study EGAS50000001074

• Aberrant EZHIP Expression Drives Tumorigenesis in Osteosarcoma

  Study EGAS00001007531

• A Prospective Study of the Oral Microbiome and Pancreatic Cancer

  Two prospective cohort studies - the Black Women's Health Study and the Southern Community Cohort Study - were used to investigate the oral microbiome in relation to pancreatic cancer risk. Using a nested case-control study design, 148 cases and 510 matched controls were included (122 Black American pancreatic cancer cases and 409 matched controls). DNA was extracted from oral wash samples, using the PowerSoil Pro kit. Paired-end whole metagenomic shotgun sequencing was performed, using the Illumina HiSeq2000 platform with a read length of 100 bp (insert size 350 bp).

  Study phs002454

• Profiling Genome-Wide Circulating ncRNAs for the Early Detection of Lung Cancer

  Lung cancer remains the leading cause of cancer-related mortality worldwide, with non-small cell lung cancer (NSCLC) accounting for approximately 85% of all cases. Although imaging techniques such as low-dose computed tomography (LDCT), combined with tissue biopsies, have improved early detection rates, current diagnostic approaches are often limited by high false-positive rates, invasiveness, and radiation exposure, which lead to misdiagnosis and increased patient burden. Therefore, there is an urgent need for minimally invasive, accurate, and safe diagnostic biomarkers, particularly those derived from liquid biopsies such as blood-based exosomal RNA.This dataset specifically focuses on plasma-derived exosomal small non-coding RNAs (sncRNAs).A total of 233 de-identified plasma samples were obtained from Rush University Medical Center, including 116 NSCLC patients and 117 non-cancer controls. Exosomes were isolated from plasma, RNA was extracted, and small RNA sequencing was performed using the Illumina NextSeq 500 platform. Data available through dbGaP include individual-level raw sequencing files (FASTQ) and basic phenotype annotations of the plasma cohort.A diagnostic model was initially developed using small RNA-seq data from 1,446 tissue samples obtained from TCGA and GEO, identifying a robust sncRNA signature that distinguished NSCLC from non-cancer samples with an AUC of 0.90 in hold-out tissue validation. This signature was subsequently validated in the plasma exosome cohort, achieving an AUC of 0.84 in independent validation. The model demonstrated consistent diagnostic performance across subgroups stratified by age, sex, smoking history, cancer stage, and NSCLC subtype. Survival and functional analyses further supported the clinical and biological relevance of the identified sncRNAs. It is hoped that this resource will contribute to a better understanding of the sncRNA expression landscape in NSCLC and promote the development of non-invasive biomarkers for early cancer detection. These data may be applied to the investigation of transcriptomic and other risk factors, provide insight into cancer screening, tumor progression mechanisms, and prognosis prediction, and ultimately support precision medicine for NSCLC.

  Study phs004166