Search Results - EGA European Genome-Phenome Archive

DETECT-A NGS Data Batch 4

This batch is a subset of the full DETECT-A dataset, containing 25210 fastq files generated from 3040 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

Dataset EGAD00001015360

DETECT-A NGS Data Batch 6

This batch is a subset of the full DETECT-A dataset, containing 9 fastq files generated from 8 subjects. All sequencing was conducted using Illumina HiSeq 4000 and Illumina MiSeq platforms. Note that the division into batches follows no specific criteria and that the sequencing data for each subject has multiple files which may span multiple datasets. Thus, for a comprehensive analysis, it is recommended to request access to all datasets that comprise this study.

Dataset EGAD00001015458

SNP data

SNP data from 49 paired samples (tumor/germline) with muscle invasive bladder cancer.

Dataset EGAD00010001943

TOTHER3

Patritumab deruxtecan in HER2-negative breast cancer: part B results of the window-of-opportunity SOLTI TOT-HER3 trial and biological determinants of early-response

Dac EGAC50000000255

Finding structural variation and functional consequences from primary acute myeloid leukemia cells with complex karyotype (CK-AML) at the single-cell level

Study EGAS00001007436

EuCanImage_DEMO_UC1

This dataset contains the standardized clinical information related to the Use case 1 - Liver Cancer (HCC) from EuCanImage. The Data is Synthetic.

Dataset EGAD50000002083

Osteosarcoma_X10

This is a continuation of the osteosarcoma work we have undertaken.

Study EGAS00001002167

Somatic_mutation_in_edited_cholangiocyte_organoids_NanoSeq

Characterisation of mutation rates and patterns in edited human cholangiocyte organoids (NanoSeq)

Study EGAS00001006405

Raw count table

Raw count matrix of the 124 bulk tumor RNAseq samples from patients with hormone sensitive or castration resistant prostate cancer.

Dataset EGAD00001008762

Heterogeneous Genomic Evolution and Immune Microenvironments in Metastatic Lung Cancer

WES data of paired primary and metastatic tumors

Dataset EGAD00001006213

Genomic Landscape of Human Skin at a Single-Cell Resolution

Every cell in the human body has a unique set of somatic mutations, yet it remains difficult to comprehensively genotype an individual cell. Here, we developed solutions to overcome this obstacle in the context of normal human skin, thus offering the first glimpse into the genomic landscapes of melanocytes at single-cell resolution. We comprehensively genotyped 133 melanocytes from 19 sites across 6 donors. As expected, sun-shielded melanocytes had fewer mutations than sun-exposed melanocytes. However, within sun-exposed sites, melanocytes on chronically sun-exposed skin (e.g. the face) displayed a lower mutation burden than melanocytes on intermittently sun-exposed skin (e.g. the back). Melanocytes from donors with a history of skin cancer had higher mutation burdens than melanocytes from donors without skin cancer, implying that the mutation burden of normal skin can be harnessed to measure cumulative sun damage and skin cancer risk. Moreover, melanocytes from healthy skin commonly harbor pathogenic mutations, likely explaining the origins of the melanomas that arise in the absence of a pre-existing nevus. Phylogenetic analyses identified groups of related melanocytes, suggesting that melanocytes spread throughout skin as fields of clonally related cells, invisible to the naked eye. Overall, our study offers an unprecedented view into the genomic landscapes of individual melanocytes, revealing key insights into the causes and origins of melanoma.

Study phs001979

Somatic rearrangements causing oncogenic ectodomain deletions of FGFR1 in squamous cell lung cancer

The discovery of frequent 8p11-p12 amplifications in squamous cell lung cancer (SQLC) has fueled hopes that FGFR1, located inside this amplicon, might be a therapeutic target. In a clinical trial, only 11% of patients with 8p11 amplification (detected by FISH) responded to FGFR kinase inhibitor treatment. To understand the mechanism of FGFR1 dependency, we performed deep genomic characterization of 52 SQLCs with 8p11-p12 amplification, including 10 tumors obtained from patients who had been treated with FGFR inhibitors. We discovered somatically altered variants of FGFR1 with deletion of exons 1-8 that resulted from intragenic tail-to-tail rearrangements. These ectodomain-deficient FGFR1 variants (ΔEC-FGFR1) were expressed in the affected tumors and were tumorigenic in both in vitro and in vivo models of lung cancer. Mechanistically, breakage-fusion-bridges were the source of 8p11-p12 amplification, resulting from frequent head-to-head and tail-to-tail rearrangements. Generally, tail-to-tail rearrangements within or in close proximity upstream of FGFR1 were associated with FGFR1 dependency. Thus, the genomic events shaping the architecture of the 8p11-p12 amplicon provide a mechanistic explanation for the emergence of FGFR1-driven SQLC. Specifically, we believe that FGFR1 ectodomain-deficient and FGFR1-centered amplifications caused by tail-to-tail rearrangements are a novel somatic genomic event that might be predictive of therapeutically relevant FGFR1 dependency.

Study EGAS50000001368

Neoadjuvant immune checkpoint blockade in mismatch-repair proficient colon cancers

Immune checkpoint blockade has led to paradigm shifts in the treatment of various tumour types, yet limited efficacy has been observed in patients with metastatic mismatch-repair proficient (pMMR) colorectal cancer. Here we report an in-depth analysis of patients with early-stage pMMR colon cancer from the phase II NICHE study (ClinicalTrials.gov: NCT03026140). A total of 31 patients received neoadjuvant treatment of nivolumab plus ipilimumab followed by surgery. The response rate was 26% and included six patients with a major pathological response (≤10% residual viable tumour). One patient with an ongoing clinical complete response did not undergo surgery. Responses were observed despite a low tumour mutational burden in all tumours, while chromosomal genomic instability scores were significantly higher in responders compared to non-responders. Responding tumours were more likely to be TP53 mutant, KRASG12 wildtype and had significantly higher baseline expression of proliferation signatures and TCF1. Imaging mass cytometry also revealed a higher percentage of Ki-67+ cancer and Ki-67+ CD8+ T cells in responders compared to non-responders. Meanwhile, in non-responders, we observed an enrichment for an inflamed-fibrotic microenvironment associated with TGF-β expression, hinting towards possible resistance mechanisms. These results provide a comprehensive analysis of response to neoadjuvant ICB in early-stage pMMR colon cancers and identify potential biomarkers for patient selection.

Study EGAS50000000856

Machine Learning Signal Enrichment for Ultrasensitive Plasma Tumor Burden Monitoring

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

Study EGAS00001007451

Machine learning guided signal enrichment for ultrasensitive plasma tumor burden monitoring

In solid tumor oncology, circulating tumor DNA (ctDNA) is poised to transform care through accurate assessment of minimal residual disease (MRD) and therapeutic response monitoring. To overcome the sparsity of ctDNA fragments in low tumor fraction (TF) settings and increase MRD sensitivity, we previously leveraged genome-wide mutational integration through plasma whole genome sequencing (WGS). We now introduce MRD-EDGE, a composite machine learning-guided WGS ctDNA single nucleotide variant (SNV) and copy number variant (CNV) detection platform designed to increase signal enrichment. MRD-EDGESNV uses deep learning and a ctDNA-specific feature space to increase SNV signal-to-noise enrichment in WGS by 300X compared to previous WGS error suppression. MRD-EDGECNV also reduces the degree of aneuploidy needed for ultrasensitive CNV detection through WGS from 1 Gb to 200 Mb, thereby expanding its applicability to a wider range of solid tumors. We harness the improved performance to identify MRD following surgery in multiple cancer types, track changes in tumor burden in response to neoadjuvant immunotherapy in non-small cell lung cancer (NSCLC) and demonstrate ctDNA shedding in precancerous colorectal adenomas. Finally, the radical signal-to-noise enrichment in MRD-EDGESNV enables de novo mutation calling in melanoma and small cell lung cancer (SCLC) without matched tumor, yielding clinically informative TF monitoring for patients on immune checkpoint inhibition (ICI).

Study EGAS00001007545

Genome-Wide Association Study of aspirin-induced PUD in a UK cohort

Aspirin is a widely prescribed non-steroidal anti-inflammatory drug used as an effective analgesic and at low doses as anti-platelet drug for the prevention of cardiovascular diseases. However, aspirin is associated with a significant incidence of upper gastrointestinal (GI) complications, notably peptic ulceration. This study aims to identify genetic risk factors associated with the pathogenesis of aspirin-induced upper GI ulceration.A cohort of 248 patients with aspirin-induced, endoscopiclly confirmed GI ulceration and 491 controls (ulcer, without aspirin or aspirin without ulcer) were genotyped for 1.524,956 SNPs using the Illumina Omni 2.5 SNP array. A replication cohort (206 NSAID-induced ulcer cases [of which 87 were aspirin] and 309 controls) was subsequently genotyped for identified SNP association signals using Sequenom iPLEX Massarry. Logistic regression analysis of identified two SNP signal with suggestive association with aspirin-induced GI ulceration. A SNP within the EYA1 locus (rs12678747) was found to be associated with aspirin GI ulceration in both the discovery cohort (p=3.79x10-7, OR=2.06 ([1.55-2.73]) and, to a lesser extent, in the replication cohort (p=.0005, OR=1.71[1.17-2.50]. Combined analysis of both cohorts yielded a genome wide significant association (p=1.46x10-8). The rs12678747 genotype was found to be associated with significantly higher EYA1 transcript in ulcer biopsy tissue (p<0.05).Data suggest that EYA1 may represent a risk locus for aspirin-induced GI ulceration. Though it is thought that EYA1 may play a key role in mediating cell death/ survival

Study EGAS00001002052

Confirmation of a founder effect in a Northern European population (FRL) of a new beta-globin variant: HBB:c.23_26dup (codons 8/9 (+AGAA))

Beta-thalassemia is a genetic disease caused by a defect in the production of the beta-like globin chain. More than 200 known different variants can lead to the disease and are mainly found in populations that have been exposed to malaria parasites. We recently described a duplication of 4 nucleotides in the first exon of beta-globin gene in several families of patients living in Nord-Pas-de-Calais (France). Using the genotypes at 12 microsatellite markers surrounding the beta-globin gene of four unrelated variant carriers plus an additional one recently discovered, we found that they shared a common haplotype indicating a founder effect that was estimated to have taken place 225 years ago (9 generations). In order to determine whether this variant arose in this region of Northern-Europe or was introduced by migrants from regions of the world where thalassemia is endemic, we genotyped the first 4 unrelated variant carriers and 32 controls from Nord-Pas-de-Calais for 97 European ancestry informative markers (EAIMs). Using these EAIMs and comparing with population reference panels, we demonstrated that the variant carriers were very similar to the controls and were closer to North European populations than to South European or Middle-East populations. Rare beta-thalassemia variants have already been described in patients sampled in non-endemic regions but it is the first proof of a founder effect in Northern Europe. The new genetic panel FRL is under registration in EGA.

Study EGAS00001000980

shallow WGS and deep targeted panel on ctDNA in rhabdomyosarcomas

The genomic spectrum of rhabdomyosarcoma (RMS) progression from primary to relapse is not fully understood. In this study we investigate 35 patients with relapsed RMS from two contributing institutions, 18 fusion-positive (FP-RMS) and 17 fusion-negative RMS (FN-RMS). Targeted DNA or whole exome sequencing (WES) was used to detect alterations in paired primary/relapsed samples. In 10 cases, circulating tumor DNA (ctDNA) from multiple timepoints through clinical care and progression was analyzed for feasibility of liquid biopsy in monitoring treatment response/relapse. ctDNA alterations were evaluated using a targeted custom RMS panel (36 genes) at high coverage for single nucleotide variation and fusion detection, and a shallow whole genome sequencing for copy number variation. FP-RMS had a stable genome with relapse, with the most common secondary alterations : CDKN2A/B, MYCN and CDK4 alterations, being already present at diagnosis and impacting overall survival. FP-RMS lacking major secondary events at baseline acquired recurrent MYCN and AKT1 alterations. FN-RMS acquired a higher number of new alterations, most commonly SMARCA2 missense mutations. ctDNA analyses detected pathognomonic variants in all RMS patients at diagnosis, regardless of FP/FN or type of alterations, while at relapse selected alterations were confirmed in 86% of FP-RMS and 100% FN-RMS. Moreover, a higher number of fusion reads was detected with increased disease burden and at relapse in patients following a fatal outcome. These results underscore patterns of tumor progression within a relatively stable genomic landscape and provide rationale for using liquid biopsy to monitor treatment response.

Study EGAS00001007399

Peripheral blood DNA methylome in adalimumab-treated patients with rheumatoid arthritis

Background and aims Rheumatoid arthritis (RA) patients are currently treated with biological agents mostly aimed at cytokine blockade such as anti-TNFα therapy. Currently, there are no biomarkers to predict therapy response to these agents. Here, we aimed to predict response to adalimumab (ADA) treatment in RA patients using DNA methylation in peripheral blood Methods DNA methylation profiling on whole peripheral blood from 92 RA patients before the start of adalimumab (ADA) was determined using Illumina HumanMethylationEPIC BeadChip Array. After 6 months, treatment response was assessed according to the Alliance of Associations for Rheumatology (EULAR) criteria for disease response. Patients were classified as responders (DAS28<3.2 or decrease of 1.2 points) or as non-responders (DAS28>5.1 or decrease of less than 0.6 points). Machine learning models were built with gradient boosting and stability selection models to predict response prior to ADA treatment with predictor DNA methylation markers. Results We demonstrated a 27-feature panel of DNA methylation markers or CpG classifiers that predict response in RA patients treated with ADA. Forty-nine patients were assigned as responder and 43 patients assigned as non-responders. We differentiate responders from non-responders with a high sensitivity (AUC 0.76). The predictor CpGs annotated to genes involved in immunological- and pathophysiological pathways related to RA such as T-cell signaling, B-cell pathology and angiogenesis. Conclusion Our findings indicate that DNA methylation signatures discriminate responders and non-responders to ADA treatment and can serve as a tool for therapy prediction.

Study EGAS00001007578

OMKar

The whole genome karyotype refers to the sequence of large chromosomal segments that make up an individuals genotype. karyotype analysis, which includes descriptions of aneuploidies and other rearrangements is crucial for understanding genetic risk factors, for diagnosis, treatment decisions, and genetic counseling linked to constitutional disorders. The current karyotyping standard is based on microscopic examination of chromosomes, a complex process that requires high expertise and offers Mb scale resolution. Optical Genome Mapping (OGM) technology can identify large DNA lesions in a cost-effective manner. In this paper, we developed OMKar, a method that uses OGM data to create a virtual karyotype. OMKar processes Structural (SV) and Copy Number (CN) Variants as inputs and encodes them into a compact breakpoint graph. It recomputes copy numbers using Integer Linear Programming to maintain CN balance and then identifies constrained Eulerian paths representing entire donor chromosomes. In tests using 38 whole genome simulations of constitutional disorders, OMKar reconstructed the karyotype with 88% precision and 95% recall on SV concordance and 95% Jaccard score on CN concordance. We applied OMKar to 50 prenatal, 41 postnatal, and 63 parental samples from ten different sites. OMKar reconstructed the correct karyotype in 144 out of 154 samples, covering 25 of 25 aneuploidies, 32 of 32 balanced translocations, and 72 of 82 unbalanced variations. Detected constitutional disorders included Cri-du-chat, Wolf-Hirschhorn, Prader-Willi deletions, Down, and Turner syndromes. Importantly, it identified a plausible genetic mechanism for five cases of constitutional disorder that were not detected by other technologies. Together, these results demonstrate the robustness of OMKar for OGM-based karyotyping.

Study EGAS00001008245

DAC for Combined MEK and BCL-2/XL inhibition is effective in high-grade serous ovarian cancer patient-derived xenograft models and BIM levels are predictive of responsiveness

Dac EGAC00001001250

Noninvasive detection of cancer-associated genome-wide hypomethylation and copy number aberrations by plasma DNA bisulfite sequencing

Dataset EGAD00001000856

15174 results for "cancer studies using rna-seq"

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