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• Highlights from 2025: Our top 10 requested studies

  In 2025, as in previous years, EGA has facilitated the reuse of numerous datasets spanning a broad range of research and healthcare topics. To reflect on this activity, we would like to highlight the top 10 studies behind the most requested datasets of last year. Notably, the vast majority of these highly requested datasets are cancer-focused, particularly involving the study of immune checkpoint inhibitor therapies. Immune checkpoint inhibitors (ICIs) have become one of the most transformative advances in modern cancer therapy. These monoclonal antibodies enhance antitumor immune responses by targeting inhibitory immune checkpoint molecules. While ICIs have led to remarkably favorable and durable responses in some patients, treatment outcomes vary widely. This variability has fueled intense research efforts aimed at understanding resistance mechanisms, exploring combination therapies, and discovering predictive biomarkers to better stratify patients and guide treatment decisions. Study Title Disease 1 EGAS00001005503 Integrated genomic analyses reveal molecular correlates of clinical response and resistance to atezolizumab in combination with bevacizumab in advanced hepatocellular carcinoma Liver Cancer 2 EGAS00001005013 Intratumoral plasma cells predict outcomes to PD-L1 blockade in non-small cell lung cancer Lung Cancer 3 EGAS00001004809 BIOKEY: A single-cell catalogue of the dynamic changes underlying Checkpoint Immunotherapy response in Early Breast Cancer Breast Cancer 4 EGAS50000000138 BIOKEY: Immune heterogeneity in small cell lung cancer and vulnerability to immune checkpoint blockade Lung Cancer 5 EGAS50000000497 Bladder cancer subtyping study across 4 atezo clinical trials Bladder Cancer 6 EGAS50000000689 MOSAIC - Multi-Omics Spatial Atlas In Cancer Cancer Atlas 7 EGAS00000000083 METABRIC (Breast cancer - genome and transcriptome) Breast Cancer 8 EGAS00001005702 Human genomic and phenotypic synthetic data for the study of rare diseases Synthetic data 9 EGAS00001002556 TGF-β attenuates tumour response to PD-L1 blockade by contributing to exclusion of T cells Bladder Cancer 10 EGAS00001004353 Molecular subsets in renal cancer determine outcome to checkpoint and angiogenesis blockade Renal Cancer The most requested dataset of the year was EGAD00001008128. It belongs to a study that analyzed 358 liver cancer patients enrolled in clinical trials and treated with the combination of atezolizumab (anti–PD-L1) and bevacizumab (anti-VEGF), atezolizumab alone, or sorafenib. The study highlights how bevacizumab enhances anti-PD-L1 effect and identifies candidate biomarkers to predict treatment response. Hepatocellular carcinoma (HCC) is the most common type of primary liver cancer and the third leading cause of cancer-related death worldwide [1]. Because symptoms often appear late, many patients are diagnosed at advanced stages, when curative options are no longer viable. For many years, sorafenib—a multikinase inhibitor approved in 2007—was the only systemic treatment available. Although numerous clinical trials followed, it was not until a decade later that additional therapies showed meaningful clinical benefit. Among these advances, immunotherapy emerged as a promising first-line option [2]. In particular, the combination of atezolizumab and bevacizumab demonstrated improved survival in patients with advanced HCC, reshaping the treatment landscape. However, treatment efficacy remains limited by the complex and diverse hepatic microenvironments that influence immune responses, as well as by high intratumoral heterogeneity. Identifying robust predictors of treatment response is critical to enable effective patient stratification and maximize the benefits of these therapies [2]. The continued demand for these datasets highlights the interest and critical role of data reuse in deepening our understanding of cancer, accelerating the development of more effective therapies, and improving patient outcomes. By providing secure access to high-quality genomic and clinical data, EGA acts as a catalyst for biomedical progress. References Sung, Hyuna, et al. "Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries."CA: a cancer journal for clinicians 71.3 (2021): 209-249. Ladd, Alexandra D, et al.“Mechanisms of drug resistance in HCC.” Hepatology 79(4) (2024): 926-940

  Blog top-10-studies-2025

• cBioportal lands at EGA: What this means for researchers

  cBioPortal is a widely used platform designed to simplify the exploration of complex cancer genomic data. It brings together large-scale datasets—covering mutations, copy number alterations, gene expression, and clinical annotations—and presents them through an intuitive, interactive interface. Since its launch, it has become a cornerstone of cancer research, helping translate raw genomic data into meaningful biological insights. cBioPortal Is Now Available at EGA At the European Genome-phenome Archive (EGA), we host controlled-access genomic and phenoclinical datasets. By integrating cBioPortal within EGA, researchers could explore cancer datasets (once access has been granted by data owners) through the powerful and user-friendly cBioportal interface. We believe this marks an important step forward for the cancer research community, with several key benefits: Faster Insights Researchers can quickly visualize and explore datasets through the cBioPortal interface before downloading and analyzing complex raw data. This provides an immediate overview, saving time and enabling more informed decisions about which datasets to pursue. Broader Accessibility Working with complex genomic data often requires advanced computational and bioinformatic expertise. This integration lowers the technical barrier, allowing a wider range of scientists to engage with high-value datasets and, for example, accelerate hypothesis generation. Enhanced Data Integration cBioPortal enables the seamless combination of genomic and clinical data, as well as the comparison and exploration of multiple datasets within a single platform. This promotes more comprehensive analyses and supports deeper biological insights. The arrival of cBioPortal at EGA brings together powerful visualization and controlled data access, making it easier than ever for researchers to transform complex cancer genomics data into actionable knowledge. Data submitters: Would you like to make your cBioPortal data available? See our documentation page.

  Blog cbioportal

• Arcagen - Gynecologic cancer domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from patients with rare ovarian cancer and primary peritoneal cancer and/or fallopian-tube cancer, including low grade serous carcinoma, mucinous adenocarcinoma, clear cell adenocarcinoma; and other rare cancers such as sex cord tumors, germ cell tumor, yolk sac tumor, and malignant/immature teratoma (n=94).

  Study EGAS50000000900

• Arcagen - CNS domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset from patients with rare tumor from the central nervous system (n=61).

  Study EGAS50000001002

• SPECTA RP-1759-AYA CNS cohort

  EORTC-SPECTA RP1759 study focuses on cancers in adolescent and young adult (AYA), age 12 to 29 years. This study explicitly recruited AYA patients and therefore collected empirical data to bridge the molecular gap between pediatric and adult oncology. The initial pilot study, activated in February 2019 across Europe, aimed to recruit 50 AYA patients (aged 12-29 years) with newly diagnosed or relapsed high-grade gliomas, and for which matching tumor and blood samples were collected.

  Study EGAS50000000985

• Arcagen - Gynecologic cancer (ovarian, peritoneal and/or fallopian-tube)

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files in .BAM format from 94 patients with rare ovarian cancer and primary peritoneal cancer and/or fallopian-tube cancer, including low grade serous carcinoma, mucinous adenocarcinoma, clear cell adenocarcinoma; and other rare cancers such as sex cord tumors, germ cell tumor, yolk sac tumor, and malignant/immature teratoma.

  Dataset EGAD50000001315

• MethylScan data from tissue samples

  Raw data (fastq files) for tumor/normal paired samples (378 samples in total; 78, 58, 29, 24 pairs from liver, lung, ovary, and stomach cancer patients, respectively) profiled with the MethylScan assay, a low cost assay for profiling methylation. The MethylScan assay is designed for cfDNA methylome sequencing that enriches for the disease-associated DNA by depleting background signal. For solid tissues, the assay was performed without the MSRE digestion step.

  Dataset EGAD00001015685

• MethylScan data from plasma

  Raw data (fastq files) from 1061 plasma samples profiled with the MethylScan assay, a highly cost-effective approach for cfDNA methylome sequencing. MethylScan is a cost-efficient cfDNA methylome sequencing method that enriches methylation-informative fragments while actively depleting abundant background DNA derived from blood cells. By reducing this background noise, it improves the detection sensitivity for disease-associated cfDNA, such as tumor-derived DNA.The plasma samples (n = 1,061) were from 460 cancer patients (covering 4 major cancers: liver, lung, ovarian, and stomach cancer) and 601 noncancer individuals. The noncancer individuals (n = 601) can be further categorized into three groups: noncancer patients at high-risk of liver cancer who have chronic liver diseases (n = 157), noncancer patients at high-risk of lung cancer who have benign lung nodules (n = 43), and general noncancer hospital visitors (n = 401).

  Dataset EGAD00001015686

• Arcagen - Relapsing germ cell tumors of any origin

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files in .BAM format from 23 patients with Relapsing germ cell tumors, of any origin and of any histological type.

  Dataset EGAD50000000914

• Arcagen – Cancer of unknown Primary domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files patients diagnosed with a locally advanced or metastatic Cancer of Unknown Primary (n=96).

  Study EGAS50000000177

• Arcagen - Skin cancer domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files patients diagnosed with adnexal carcinoma of the skin, Merkel cells cancer, and malignant melanoma of the uvea (n=49).

  Study EGAS50000000491

• Arcagen - Head and Neck domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files from patients with salivary gland tumors of major salivary gland; salivary gland type tumors of head and neck with a strong focus on acinic cell carcinoma, NUT carcinoma and sinus carcinoma (n=102).

  Study EGAS50000000625

• Arcagen – Adrenal and Thyroid cancers domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files from patients with adrenocortical carcinoma, pheochromocytoma, anaplastic thyroid cancer, medullary thyroid cancer and radioiodine refractory thyroid cancer (n=103).

  Study EGAS50000000626

• Arcagen - Sarcoma domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from patients with undifferentiated sarcoma of the bone; aggressive angiomyxoma; alveolar soft part sarcoma; small round cell sarcoma without EWSR1 and CIC translocations; undifferentiated pleomorphic sarcoma; undifferentiated sarcoma; myxofibrosarcoma; or sarcoma with an incidence of less than 1 per 10 million (n=62).

  Study EGAS50000000639

• Arcagen - Relapsing germ cell tumors domain

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from patients with Relapsing germ cell tumors, of any origin and of any histological type (n=23).

  Study EGAS50000000645

• Arcagen – Cancer of unknown Primary

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files from 96 patients in .BAM format diagnosed with a locally advanced or metastatic Cancer of Unknown Primary.

  Dataset EGAD50000000256

• Arcagen - Skin cancer

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files in .BAM format from 49 patients diagnosed with adnexal carcinoma of the skin, Merkel cells cancer or malignant melanoma of the uvea.

  Dataset EGAD50000000705

• Arcagen - Head and Neck malignancies

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files in .BAM from 102 patients diagnosed with salivary gland tumors of major salivary gland; salivary gland type tumors of head and neck with a strong focus on acinic cell carcinoma (diagnostic based on morphology, but IHC can be performed for DOG1 and SOX10), NUT carcinoma (presence of NUT, cytokeratin and p40 by IHC) and sinus carcinoma.

  Dataset EGAD50000000885

• Arcagen – Adrenal and Thyroid cancers

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here were are submitting the dataset that contains NGS files in .BAM format from 103 patients with adrenocortical carcinoma, pheochromocytoma, anaplastic thyroid cancer, medullary thyroid cancer and radioiodine refractory thyroid cancer.

  Dataset EGAD50000000886

• Arcagen - Sarcoma

  Arcagen is an EORTC/SPECTA pan-European project that aims to recruit 1000 rare cancer patients from different tumour domains of EURACAN. This study collected samples from advanced or metastatic rare cancer from patients older than 12, and analysed them using Foundation Medicine next-generation sequencing (NGS) panels (FoundationOne CDx for FFPE samples or FoundationOne Liquid CDx for blood samples). Here we are submitting the dataset that contain NGS files in .BAM format from 62 patients with undifferentiated sarcoma of the bone; aggressive angiomyxoma; alveolar soft part sarcoma; small round cell sarcoma without EWSR1 and CIC translocations; undifferentiated pleomorphic sarcoma; undifferentiated sarcoma; myxofibrosarcoma; or sarcoma with an incidence of less than 1 per 10 million.

  Dataset EGAD50000000902

• Zanidatamab in Patients with Early Stage HER2-positive Breast Cancer: The NeoZanHER Phase 2 Single-Arm Open-Label Trial

  Strategies are needed to avoid chemotherapy in early stage HER2-positive (HER2+) breast cancer (BC). We conducted a neoadjuvant therapy trial with zanidatamab, a dual HER2-directed bispecific antibody, in patients with 1-3 cm, node-negative HER2+ BC. Primary endpoint was pathologic complete response (pCR). Secondary endpoints were radiographic response by ultrasound and magnetic resonance imaging. US and MRI, pathologic response by residual cancer burden (RCB), rate of adverse events, feasibility of accrual and biomarkers of response. Fifteen patients with HER2 IHC 3+, and 5 with HER2 IHC 2+/ISH+ BC were enrolled. Patients received zanidatamab 20 mg/kg every 2 weeks for 6 (n=11) or 10 doses (n=9). Fourteen patients also received endocrine therapy. At 6 weeks, there was a significant decrease in tumor size and volume. At surgery, six patients (30%) had pCR, meeting the prespecified pCR target, and four had limited RCB (RCB-1; 20%). Treatment was well tolerated. All patients with pCR had HER2 IHC 3+ tumors, ERBB2 amplification on WES, PAM50 HER2-high subtype, and a trend towards higher HER2 mRNA expression (p=0.06). In conclusion, de-escalation to HER2-targeted therapy alone may be feasible. Further research is needed to refine patient selection.

  Study EGAS50000001930

• Whole-exome sequencing data for breast cancer patients

  This datasets contains the FASTQ files sequenced by Illumina NovaSeqX Plus, and the variants called from the sequencing data.

  Dataset EGAD50000002800

• DAC for study of Zanidatamab in breast cancer patients

  This is the DAC for manuscript "Zanidatamab in Patients with Early Stage HER2-positive Breast Cancer: The NeoZanHER Phase 2 Single-Arm Open-Label Trial"

  Dac EGAC50000001059

• Single-molecule nanopore sequencing of plasma and cerebrospinal fluid cell-free DNA from paediatric patients with brain and extracranial solid tumours.

  Cell-free DNA (cfDNA) profiling enables minimally invasive cancer detection and monitoring. Here, we report single-molecule nanopore sequencing data generated using the SIMMA assay for 792 plasma and cerebrospinal fluid cfDNA samples from 277 paediatric patients with diverse brain and extracranial tumours. SIMMA is a low-input single-molecule sequencing approach that enables multimodal whole-genome and high-depth targeted sequencing of the same cfDNA sample for both tumour-agnostic and tumour-informed liquid biopsy analysis (Sauer et al. 2026).

  Study EGAS50000001839

• High-grade serous ovarian cancer is associated with increased TP53 mutation burden in uterine lavage

  High grade serous ovarian cancer (HGSC) has low survival partly due to the lack of methods for detection, diagnosis, and risk prediction. TP53 mutations, which drive HGSC, are found in gynecological tissues as the result of somatic evolution, but it is unknown whether an excess of mutations is linked to ovarian cancer. Here we investigate if TP53 mutation burden measured in uterine lavage, a minimally invasive gynecological liquid biopsy, can discriminate between patients with and without HGSC. We used ultradeep TP53 duplex sequencing (>15,000x duplex depth) to detect TP53 mutations in uterine lavage collected pre-operatively in 278 patients undergoing gynecological surgery for pelvic masses (average risk) or cancer risk-reduction (high risk). All lavages contained multiple TP53 mutant clones, which were used to quantify TP53 mutation burden frequency (MBF). Average risk patients with HGSC had significantly higher TP53 MBF independently of age and other risk factors (77% sensitivity, 89% specificity, AUC =0.88). Excluding tumor TP53 clonal mutations from the lavage MBF calculation maintains this association, suggesting that it is the overall TP53 somatic mutation burden (rather than the discovery of the specific tumor driver mutation) that identifies HGSC. These results demonstrate that TP53 somatic mutations are common in uterine lavage but more abundant in patients with HGSC, highlighting a connection between TP53 somatic evolution and ovarian cancer. Uterine lavage offers a minimally invasive approach that could be valuable to identify patients with HGSC.

  Study EGAS50000001910

• Detection of high-grade serous ovarian cancer using TP53 mutation burden in uterine lavage

  In total, 436 DNA samples from the 278 patients were processed for TP53 ultradeep duplex sequencing: 278 lavages, 86 tissue samples (some patients had multiple tissue samples), and 72 blood samples. Duplex sequencing was performed on an Illumina NovaSeq 6000 by TwinStrand Biosciences using a capture panel targeting the coding regions of the TP53 gene. Data were processed by TwinStrand Biosciences and .bam files were created for each sample.

  Dataset EGAD50000002776

• Carcinoma of Unknown Primary (CUP): A comparison across tissue and liquid biomarkers (CUP-COMP) study

  The Carcinoma of Unknown Primary (CUP): A comparison across tissue and liquid biomarkers (CUP-COMP) study (NCT: NCT04750109) was sponsored by The Christie NHS Foundation Trust and funded by Innovate UK.

  Study EGAS50000001821

• Single-cell RNA sequencing of liver metastasis-derived colorectal cancer organoids profiling cellular heterogeneity and lineage dynamics across time

  The objective of this analysis was to identify, at single-cell resolution, trasncriptionally distinct subpopulations in untreated metastatic colorectal cancer organoids with diverse genetic backgrounds and to investigate their temporal dynamics.

  Study EGAS50000001927

• Transcriptome profiling of liver metastasis-derived colorectal cancer organoids to dissect pro-differentiative effects of TGFB1 and IL-6

  Bulk RNA sequencing was performed on patient-derived xenograft (PDX)-derived organoid models of metastatic colorectal cancer (mCRC). The aim of this study was to test the effect of IL-6 and TGFbeta1 on mCRC organoid cell differentiation. Transcriptomic profiling was conducted following cytokine treatments to investigate molecular changes associated with treatments. Three biological replicates were included for each experimental condition (control, IL-6, and TGF-beta1 treatments).

  Study EGAS50000001914

• Bulk RNA sequencing of metastatic colorectal cancer PDX-derived organoids - untreated and treated with IL-6 or TGF-beta1

  Bulk RNA sequencing was performed on patient-derived xenograft (PDX)-derived organoid models of metastatic colorectal cancer (mCRC). The aim of this study was to test the effect of IL-6 and TGF-beta1 on mCRC organoid cell differentiation. Transcriptomic profiling was conducted following cytokine treatments to investigate molecular changes associated with treatments.

  Dataset EGAD50000002782

• Single-cell transcriptomic profiling of metastatic colorectal cancer organoids maintained in growth medium.

  Single-cell RNA sequencing was performed on metastatic colorectal cancer (mCRC) organoids derived from patient-derived xenograft (PDX) models. Organoids were seeded in 12-well plates, embedded in 200 µL of Matrigel or BME diluted 1:1 with culture medium, and maintained with EGF-supplemented growth medium. After 7 days (or 11 days) of growth, organoids were harvested, dissociated, and live single cells were sorted for single-cell RNA sequencing using the 10x Genomics platform.

  Dataset EGAD50000002797

• IRCCS Candiolo - Quantitative Cancer Cell Biology (QCCB)

  DAC for Quantitative Cancer Cell Biology (QCCB) datasets

  Dac EGAC50000001019

• Personalized ctDNA detection and genomic profiling in the NeoRHEA Study

  In the management of early hormone receptor (HR)+, HER2-negative breast cancer, circulating tumor DNA (ctDNA) detection is an evolving yet promising diagnostic approach. We evaluated ctDNA detection using the personalized RaDaR assay in plasma samples from patients enrolled in the NeoRHEA clinical trial (NCT03065621), a single-arm, phase II study of neoadjuvant palbociclib and endocrine therapy administered over 4 months (four 28‑day cycles). Plasma samples were collected pre-treatment, after the first treatment cycle, prior to surgery, and one month post-surgery. At baseline, ctDNA positivity was detected in 55% of patients; however, this dropped to 5% during treatment and ctDNA became undetectable in all patients by one month post-surgery. CtDNA detection at baseline was higher in histological grade 3 tumors, lower in multifocal/multicentric tumors and higher in residual cancer burden (RCB) 3 tumors. Genomic analysis revealed MYC gene gains or amplifications were more frequent in ultrasound (US) responders, while PIK3CA gains were more common in US non-responders. Additionally, FAT1 losses were more frequently observed in patients with RCB 3. Our findings suggest that baseline ctDNA presence predicts poor response to neoadjuvant palbociclib and endocrine therapy, underscoring its potential as a biomarker to guide tailored therapeutic approaches in HR+/HER2-negative breast cancer.

  Study EGAS50000001702

• Personalized ctDNA Monitoring and Matched Tumor–Normal Whole-Exome Sequencing in Early HR+/HER2− Breast Cancer

  The dataset comprises whole-exome sequencing (WES) data generated from 160 samples, corresponding to matched tumor–normal pairs from breast cancer patients. For each subject, one tumor biopsy sample and one matched white blood cell (WBC) sample (germline control) are included. Sequencing data are provided as aligned BAM files with corresponding BAI index files. The data were generated using Illumina paired-end sequencing technology following hybrid-capture exome enrichment. The matched tumor–normal design enables accurate identification of somatic variants by filtering germline alterations, supporting downstream analyses such as mutation profiling, biomarker discovery, and personalized circulating tumor DNA (ctDNA) assay development.

  Dataset EGAD50000002446

• Whole exome sequencing of small cell neuroendocrine cancer of the cervix

  In order to improve treatment selection for high grade neuroendocrine carcinomas of the cervix (NECC), we performed a comparative genomic analysis between this rare tumor type and other cervical cancer types, as well as extra-cervical neuroendocrine small cell carcinomas of the lung and bladder. We performed whole exome sequencing on fresh-frozen tissue from 15 NECCs and matched normal tissue. We then identified mutations and copy number variants using standard analysis pipelines. Published mutation tables from cervical cancers and extra-cervical small cell carcinomas were used for comparative analysis. Descriptive statistical methods were used and a two-sided threshold of P < .05 was used for significance. In the NECC cohort, we detected a median of 1.7 somatic mutations per megabase (range 1.0-20.9). PIK3CA p.E545K mutations were the most frequency observed oncogenic mutation (4/15 tumors, 27%). Activating MAPK pathway mutations in KRAS (p.G12D) and GNAS (p.R201C) co-occurred in two tumors (13%). In total we identified PI3-kinase or MAPK pathway activating mutations in 67% of NECC. When compared to NECC, lung and bladder small cell carcinomas exhibited a statistically significant higher rate of coding mutations (P < .001 for lung; P = .001 for bladder). Mutation of TP53 was uncommon in NECC (13%) and was more frequent in both lung (103 of 110 tumors [94%], P < .001) and bladder (18 of 19 tumors [95%], P < .001) small cell carcinoma. These comparative genomics data suggest that NECC may be genetically more similar to common cervical cancer subtypes than to extra-cervical small cell neuroendocrine carcinomas of the lung and bladder. These results may have implications for the selection of cytotoxic and targeted therapy regimens for this rare disease.

  Study EGAS00001003142

• Persistent Mutation Burden Drives Sustained Anti-Tumor Immune Responses

  Tumor mutation burden is an imperfect proxy of tumor foreignness and has therefore failed to consistently demonstrate clinical utility in predicting responses in the context of immunotherapy. We evaluated mutations in regions of the genome that are unlikely to undergo loss and discovered that clonal mutations in single-copy regions and those present in multiple copies per cell constitute a persistent tumor mutation burden (pTMB) that is linked with therapeutic response to immune checkpoint blockade. Persistent mutations were retained in the context of tumor evolution under selective pressure of immunotherapy and tumors with a high pTMB content were characterized by a more inflamed tumor microenvironment. pTMB imposes an evolutionary bottleneck that cancer cells cannot overcome and may thus drive sustained immunologic tumor control in the context of immunotherapy.

  Study EGAS00001006660

• molecular profiles of serum-derived extracellular vesicles in high-grade serous ovarian cancer

  Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (R0) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have response enabling interval cytoreductive surgery. Clinically useful predictive biomarkers for such distinctions are still lacking. Extracellular vesicles (EVs) have been recognized as liquid biopsy-based biomarkers for early cancer detection and disease surveillance in other disease settings. In this study, we performed extensive molecular characterization of serum-derived EVs and correlated them with therapeutic outcomes in patients with HGSC.

  Study EGAS00001006350

• Combined targeting of BRD4-associated Promoter Activation and NFKB Immunomodulation in ARID1A-mutated Gastric Adenocarcinoma

  Gastric cancer (GC) a leading causes of cancer-related deaths worldwide, with ARID1A identified as the second most frequently mutated driver gene in GC. This study involves comprehensive genomic profiling of a Singaporean cohort of over 200 GC patients to characterize the mutational signatures associated with ARID1A inactivation across various molecular subtypes of GC. The findings highlight a potential therapeutic approach for ARID1A-mutated GCs, targeting both tumor-intrinsic mechanisms (BRD4-associated promoter activation) and extrinsic immunomodulatory pathways (NFKB signaling).

  Study EGAS00001006397

• RNA sequencing data of 142 samples from 142 patients with HER2+ breast cancer treated with letrozole or tamoxifen (SOLTI PAMELA trial)

  PAMELA (NCT01973660) is a non-randomized, open-label, multicentric, prospective translational research study in stage I-IIIA HER2+ breast cancer designed to evaluate the ability of the PAM50 intrinsic subtypes to predict pCR in the breast (pCRB) following 18 weeks of neoadjuvant lapatinib and trastuzumab (+/- hormonal therapy if hormone receptor [HR] positive). Patients with HR+ disease received letrozole (if postmenopausal) or tamoxifen (if pre-menopausal). The primary objective was to compare the pCRB rates of the HER2-E versus the non-HER2-E subtypes in the intent-to-treat population.

  Study EGAS00001006410

• Whole-Exome Sequencing analyses in tamoxifen-associated endometrial cancer

  An increased incidence of endometrial cancer has been described for patients that have received tamoxifen to treat breast cancer. Using samples from endometrial tumors, isolated from surgivcal specimens of patients who previously received tamoxifen treatment for breast cancer, we aimed to identify whether there are specific somatic mutations enriched in this population, relative to endometrial tumors from the general population. For this, WES was performed on matched endometrial tumors and healthy tissue (n=21).

  Study EGAS00001006453

• Multimodal Epigenetic Sequencing Analysis (MESA) of Cell-free DNA for Non-invasive Cancer Detection

  Multimodal characterization of cell-free DNA (cfDNA) in the blood can enable the sensitive and non-invasive detection of human cancers but remains technically challenging and costly. Here, we developed Multimodal Epigenetic Sequencing Analysis (MESA), a flexible and sensitive method of capturing and integrating multimodal epigenetic information of cfDNA using a single experimental assay, i.e., non-disruptive bisulfite-free methylation sequencing, such as Enzymatic Methyl-seq (EM-seq) and TET-assisted pyridine borane sequencing (TAPS). MESA can simultaneously infer cfDNA methylation, nucleosome occupancy, nucleosome fuzziness, and fragmentation profile for regions surrounding the promoters and polyadenylation sites (PASs). MESA’s integrated analysis of multimodal epigenetic features significantly improved the performance of cancer detection models compared to the usage of any single modality alone. MESA captures additional and highly complementary epigenetic information from cfDNA without additional experimental assays, highlighting the importance and clinical prospect of using multimodal epigenetic features for non-invasive cancer detection

  Study EGAS00001006462

• Robust methylation-based classification of brain tumours using nanopore sequencing

  Background: DNA methylation-based classification of cancer provides a comprehensive molecular approach to diagnose tumours. In fact, DNA methylation profiling of human brain tumours already profoundly impacts clinical neuro-oncology. However, current implementations using hybridization microarrays are time-consuming and costly. We recently reported on shallow nanopore whole-genome sequencing for rapid and cost-effective generation of genome-wide 5-methylcytosine profiles as input to supervised classification. Here, we demonstrate that this approach allows to discriminate a wide spectrum of primary brain tumours. Results: Using public reference data of 82 distinct tumour entities, we performed nanopore genome sequencing on N=382 tissue samples covering 46 brain tumour (sub)types. Using bootstrap sampling in a cohort of N = 56 cases, we find that a minimum set of 1,000 random CpG features is sufficient for high-confidence classification by ad hoc random forests. We implemented score recalibration as confidence measure for interpretation in a clinical context and empirically determined a platform-specific threshold in a randomly sampled discovery cohort (N = 185). Applying this cut-off to an independent validation series (N = 184) yielded 148 classifiable cases (sensitivity 80.4%) and demonstrated 100 % specificity. Cross-lab validation demonstrated robustness with concordant results across four laboratories in 10/11 (90.9%) cases. In a prospective benchmarking (N = 15), median time to results was 21.1 hours. Conclusions: In conclusion, nanopore sequencing allows robust and rapid methylation-based classification across the full spectrum of brain tumours. Platform-specific confidence scores facilitate clinical implementation for which prospective evaluation is warranted and ongoing.

  Study EGAS00001006540

• Neurodegenerative_TGS

  An investigation of clonal haematopoiesis in patients with neurodegenerative disease.

  Study EGAS00001002431

• ER___HER2___PR__breast_Cancer_genome_sequencing

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

  Study EGAS00001000197

• Longitudinal monitoring of cell-free DNA methylation in ALK-positive non-small cell lung cancer patients

  Here, we performed genome-wide 5-mC profiling in plasma of metastatic ALK-rearranged non-small cell lung cancer (NSCLC) patients receiving tyrosine kinase inhibitor therapy. We established a strategy to identify ALK-specific 5-mC changes from cfDNA and demonstrated the suitability of the identified markers for cancer detection, prognosis and therapy monitoring. Longitudinal plasma samples (n = 79) of 21 ALK-positive NSCLC patients and 13 healthy donors were collected alongside 15 ALK-positive tumor tissue and 10 healthy lung tissue specimens. All plasma and tissue samples were analyzed by cell-free DNA methylation immunoprecipitation sequencing to generate genome-wide 5-mC profiles. Information on genomic alterations (i.e., somatic mutations/fusions and copy number alterations) determined in matched plasma samples were available from previous studies.

  Study EGAS00001006573

• FFPE_whole_genome_pilot

  To assess feasibility of whole genome sequencing

  Study EGAS00001001967

• Whole-genome sequencing in gastric cancer (part2)

  we analysis structural variations (SVs) and mutational signatures via whole-genome sequencing of 168 GCs. Our data demonstrates diverse models of complex SVs operative in GC, which lead to high-level amplification of oncogenes. We find varying proportion of tandem-duplications (TDs) among individuals and identify 24 TD hotspots involving well-established cancer genes such as CCND1, ERBB2 and MYC.

  Study EGAS00001006575

• Whole_Genome_sequencing_of_rhabdomyosarcoma_tumour_tissue

  The aim of this study is to investigate the genomic landscape of human cancer.

  Study EGAS00001008280

• Long-read sequencing of diagnosis and post-therapy medulloblastoma reveals complex rearrangement patterns and epigenetic signatures

  Cancer genomes harbor a broad spectrum of structural variants (SV) driving tumorigenesis, a relevant subset of which are likely to escape discovery in short reads. We employed Oxford Nanopore Technologies (ONT) sequencing in a paired diagnostic and post-therapy medulloblastoma to unravel the haplotype-resolved somatic genetic and epigenetic landscape. We assemble complex rearrangements and such associated with telomeric sequences, including a 1.55 Megabasepair chromothripsis event. We uncover a complex SV pattern termed "templated insertion thread", characterized by short (mostly less than 1kb) insertions showing prevalent self-concatenation into highly amplified structures of up to 50kbp in size. Templated insertion threads occur in 3% of cancers, with a prevalence ranging to 74% in liposarcoma, and frequent colocalization with chromothripsis. We also perform long-read based methylome profiling and discover allele-specific methylation (ASM) effects, complex rearrangements exhibiting differential methylation, and differential promoter methylation in seven cancer-driver genes. Our study shows the potential of long-read sequencing in cancer.

  Study EGAS00001006576

• Nuclear_single_seq_pilot

  The aim of this study is to analyse the genomes of tumours

  Study EGAS00001003386