Search Results - EGA European Genome-Phenome Archive

Ghana Prostate Study

Participants were recruited through the Ghana Prostate Study-a population-based component, and a clinical component. The population-based component was a probability sample designed using the 2000 Ghana Population and Housing Census data in an attempt to recruit approximately 1,000 men aged 50-74 years in the Greater Accra region (~3 million people), which successfully recruited 1,037 healthy men between 2004 and 2006 with a response percentage of 98.8 %. Consented individuals underwent an in-person interview, and within 7 days had a digital rectal examination (DRE) and provided an overnight fasting blood sample for prostate-specific antigen (PSA) testing, biomarker assays, and genetic analysis. Subjects who had a positive screen by PSA (>2.5 ng/ml) or DRE underwent a transrectal ultrasound-guided biopsy. A total of 73 histologically confirmed prostate cancer cases were identified through the population-based screening component of the Ghana Prostate Study and were included in the case population in the published GWAS (Cook et al., Human genetics, 2013). From the remaining 964 screen-negative individuals, 836 had at least 20 μg DNA extracted and available for analysis, and 500 of these were matched to cases for analysis by age (in 5-year categories). In the Ghana Prostate Study, we recruited 676 prostate cancer cases at Korle Bu Teaching Hospital in Accra, Ghana, between 2008 and 2012. All consented cases were interviewed and provided an overnight fasting blood sample. At the time of selection for this analysis we had recruited 582 prostate cancer cases, from which we selected 427 for analysis. Combined with the 73 cases diagnosed through the population-based component of the study, this yielded 500 available prostate cancer cases for analysis.

Study phs000838

METABRIC

Solid tumors are complex tissues composed of a mixture of cancer and normal cells, which complicates the interpretation of their molecular profiles. Normal cell contamination can dilute cancer cell information and tissue architecture is generally not reflected in molecular assays. To address these challenges, we developed a computational approach based on standard Haematoxylin and Eosin-stained sections and demonstrated its power in a discovery cohort of 323 breast tumors and an independent validation cohort of 241 tumors. First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.First, to deconvolute cellular heterogeneity and detect subtle genomic aberrations, we introduced an algorithm based on tumor cellularity to increase the comparability of copy-number profiles between samples. Second, we demonstrated that a predictor for survival integrating image-based and molecular features significantly outperforms classifiers based on single data types. Third, we described and validated a novel, independent prognostic factor based on quantitative analysis of spatial patterns between stromal cells, which are not detectable by molecular assays. Our quantitative methods refine and complement molecular assays of tumor samples and could benefit all large-scale cancer studies.

Study EGAS00000000098

Enhanced detection of circulating tumor DNA by fragment size analysis

Existing methods to improve detection of circulating tumor DNA (ctDNA) have focused on sensitivity for detecting genomic alterations but have rarely considered the biological properties of plasma cell-free DNA (cfDNA). We hypothesized that differences in fragment lengths of circulating DNA could be exploited to enhance sensitivity for detecting the presence of ctDNA and for non-invasive genomic analysis of cancer. We surveyed ctDNA fragment sizes in 344 plasma samples from 200 cancer patients using low-pass whole-genome sequencing (0.4×). To establish the size distribution of mutant ctDNA, tumor-guided personalized deep sequencing was performed in 19 patients. We detected enrichment of ctDNA in fragment sizes between 90–150 bp, and developed methods for in vitro and in silico size selection of these fragments. Selecting fragments between 90–150 bp improved detection of tumor DNA, with more than 2-fold median enrichment in &gt;95% of cases, and more than 4-fold enrichment in &gt; 10% of cases. Analysis of size-selected cfDNA identified clinically actionable mutations and copy number alterations that were otherwise not detected. Identification of plasma samples from patients with advanced cancer was improved by predictive models integrating fragment length and copy number analysis of cfDNA, with AUC&gt; 0.99 compared to AUC &lt; 0.80 without fragmentation features. Increased identification of cfDNA from patients with glioma, renal, and pancreatic cancer was achieved with AUC &gt; 0.91, compared to AUC &lt; 0.5 without fragmentation features. Fragment size analysis and selective sequencing of specific fragment sizes can boost ctDNA detection. This could reduce the required depth of cfDNA sequencing for clinical applications, earlier diagnosis and study of tumor biology.

Study EGAS00001003258

ctDNA monitoring using patient-specific sequencing and integration of variant reads - Lung cohort

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

Study EGAS00001004447

ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

Study EGAS00001004446

Germline variants in patients with rare cancers and their implications for precision cancer medicine: experiences from the Multicenter MASTER Trial by the German Cancer Consortium (HIPO_021)

The era of precision oncology entails an increasing amount of molecular data from tumor sequencing in research and diagnostics. In this setting, germline variant analysis may add clinical benefits for patients and family members. In this study, we evaluated germline variants from genome/exome matched tumor-blood sequencing in 1.485 advanced cancer patients within a prospective observational study carried out by the German Cancer Consortium. Included patients had cancers of rare entities (79.2%) or were under the age of 51 at first diagnosis (76.6%). Ten percent of the patients harbored pathogenic germline variants in 35 tumor predisposition genes with autosomal-dominant inheritance such as BRCA1, BRCA2, TP53, RB1, CHEK2, ATM, PALB2, SDHB etc., while 4.6% of the patients were carriers of pathogenic germline variants in 18 genes with autosomal-recessive inheritance of tumor predisposition. Based on pathogenic germline variants, 14% of the patients received genetic counselling recommendations in the molecular tumor board report. Forty five percent of pathogenic germline variants supported a molecular treatment recommendation, which was implemented for 28 patients. Furthermore, we compared our approach and results to previous studies, broadening the insight into pan cancer germline findings but also revealing differences between studies on various levels, such as cohort demographics, tumor entities, gene nominations, variant detection and variant interpretation. Our data support the importance of germline variant interpretation in precision oncology studies for patients and their families, if applicable. However, guidelines for evaluation and reporting of germline variants in the context of genetic tumor profiling need to be established and further research on the relevance of germline mutations as biomarkers for treatment recommendations is needed.

Study EGAS00001005537

Arcagen – thoracic 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 we are submitting the dataset that contain NGS files from rare thoracic malignancies (n=102)

Dataset EGAD50000000168

Oxel Pilot Study

This pilot study will provide preliminary data regarding the role of a peripheral immunoscore (PIS) in predicting the benefit of immune checkpoint inhibition with or without chemotherapy for high risk patients with triple-negative breast cancer (TNBC) and residual disease after effective neoadjuvant chemotherapy.

Study EGAS50000000222

Phase 2 Study of Pembrolizumab in Combination with Gemcitabine and Cisplatin as Neoadjuvant Therapy

The purpose of the clinical trial (NCT02690558) is to evaluate whether adding pembrolizumab (Keytruda) to the combination of gemcitabine and cisplatin will improve shrinkage of the tumor before having a cystectomy, for people with muscle-invasive bladder cancer (MIBC).

Study phs003452

A fast, affordable and minimally-invasive diagnostic test for Cancer of Unknown Primary (CUP) using DNA methylation profiling

CUP diagnosis on FFPE tissue and liquid biopsies (blood, pleural and peritoneal effusions) using cfRRBS (cell-free reduced representation bisulfite sequencing), a technique that allows for identification of the methylation profile starting from minimal amounts of highly fragmented DNA.

Study EGAS50000000257

Genomic profiling of Rare Tumors Release 2

Utilizing the rare and unique patient samples provided by Pattern Medicine, LLC, MD Anderson will molecularly characterize rare cancer samples, and potentially generate a collection of preclinical models to enable identification of novel therapeutic targets and concepts, as well as evaluation of innovative treatment strategies.

Study EGAS50000000615

Transplant Outcomes in Aplastic Anemia (TOAA): GWAS and Whole Exome Sequence Data

The TOAA study is a research collaboration between the National Cancer Institute and the Center for International Blood and Marrow Transplant Research. The study aims to identify molecular predictors of outcomes after hematopoietic cell transplant in patients with severe aplastic anemia.

Study phs001710

WGS and WES data of metastatic breast cancer tissues and organoids

Paired-end WGS (x25) and WES data (x2) from metastatic breast cancer organoids, tissues and germline controls. WGS was performed on Illumina NovSeq 6000 and HiSeq X, using Illumina TruSeq Nano DNA kit. WES was performed on Illumina NovSeq 6000 and HiSeq 2000, using Agilent SureSelect XT HS + Human All Exon V7 and SureSelect Human All Exon V6+UTR (hg19).

Dataset EGAD50000000817

WGS data for ctDNA monitoring for NSCLC in TRACERx

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

Study EGAS50000001187

WGS data for Pancreatic Cancer samples (resection cohort)

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

Dataset EGAD50000001834

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

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

Study EGAS50000001211

ICARUS-BREAST01-ExomeSeq

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

Study EGAS50000000542

PHRT longitudinal ovarian cancer dataset

High-grade serous ovarian cancer presents significant challenges due to its poor prognosis and high heterogeneity, both of which complicate treatment responses. This project aims to understand intra-patient tumor evolution by investigating different sampling sites (primary and metastatic) at the time of diagnosis and during disease recurrence. A total of 183 biopsies from 50 patients were collected for this purpose, and bulk mRNA sequencing was performed. The majority of samples originated from following tissue types: omentum, ovary, and ascites.

Dataset EGAD50000002064

Spatial Profiling Reveals Resistance in HER2+ Gastric Cancer

HER2-positive gastric cancer (HER2+ GC) exhibits significant intra-tumoral heterogeneity and frequent development of resistance to HER2-targeted therapies. This study aimed to characterize the spatial tumor microenvironment (TME) and identify mechanisms of resistance to HER2 blockade including trastuzumab and trastuzumab deruxtecan (T-DXd) in HER2+ GC, with the goal of informing novel therapeutic strategies. We performed spatial transcriptomics on pre- and post-treatment samples from patients with HER2+ metastatic GC who received trastuzumab-based therapy.

Dataset EGAD50000000898

SNU_PROSPECTIVE

This study includes 5 paired samples of Korean AML paitients. 5 AML tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WES study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

Study EGAS00001002154

Genetic landscape of pediatric Low Grade Gliomas & Glioneuronal tumors

We performed whole-genome sequencing of 42 paired tumor/normal LGG genomes and analyzed somatically acquired single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes

Study EGAS00001000255

SNU_WGS_AML

This study includes 10 paired samples of Korean AML paitients.10 AML tumor samples are paired with each normal(Saliva or BM derived) sequencing data.The results of this WGS study were analyzed by Mutect and GATK for ranking germline variants and cancer variants to make mutational profile matrix.

Study EGAS00001001906

Exome_sequencing_of_patients_with_Ewings_sarcoma_

Cancer is driven by mutations in the genome. We will uncover the mutations that give rise to Ewing’s sarcoma, a bone tumour that largely affects children. We will use second generation Illumina massively parallel sequencing, and bespoke software, to characterise the genomes and transcriptomes of Ewings’ sarcoma tumours.

Study EGAS00001000266

Genomic profiling of Rare Tumors