4955 results for "*oma"

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• Integrated genomic analysis for HCC

  Liver cancer is a common malignancy and is the third cause of cancer-related death in the world and hepatocellular carcinoma (HCC) is the major type of liver cancer, accounting for ~90% of cases. Only 20 ~ 30% of patients can benefit from combined immunotherapy and targeted therapy due to the high inter-tumor heterogeneity of HCC. This work aims to identify homogeneous and robust molecular subtypes in HCC based on a large, homogenous and well-annotated cohort. We performed whole genome/exome sequencing (WGS/WES) and/or RNA sequencing (RNA-seq) on 529 HCC from 461 patients collected mainly in France. Based on the great consistence between genomic and transcriptomic data, we identified 9 robust HCC subtypes mainly based on driver mutations. And we further characterized HCC subtypes using genomic, transcriptomic and clinicopathological features. Among 9 subtypes, 5 subtypes belonged to chromosome instable tumors, while 3 subtypes belonged to chromosome stable tumors. In addition, our subtypes were associated with prognosis and we also found different distributions of subtypes across various features, such as etiology and gender. Our study provided a robust molecular classification based on a large HCC dataset from Western country, it improves our understanding of the mechanisms of carcinogenesis and will facilitate development of genome-based precision medicine in HCC.

  Study EGAS00001007957

• Three-dimensional patient-derived models of glioblastoma retain intra-tumoral heterogeneity

  The intra- and inter- tumoral heterogeneity of glioblastoma represents a significant therapeutic challenge, as well as difficulty in generating reliable models for in vitro studies. Here, we quantify the tumor cell composition from matched patient-derived neurospheres (PDN) and organoids (PDO) established from the same primary tumor using a series of multi-omic interrogations, relative to primary tissue

  Study EGAS00001008023

• Patient-derived tumoroids from CIC::DUX4 rearranged sarcoma identify MCL1 as a therapeutic target

  High-risk sarcomas, such as metastasized and relapsed Ewing and CIC-rearranged sarcomas, currently lack effective curative systemic treatment options. Precision medicine approaches offer hope and among them ex vivo drug response profiling of patient-derived tumor cells emerges as a promising novel tool to identify effective drugs for individual patients. Here, we established ex vivo culture conditions to propagate Ewing and CIC::DUX4-sarcomas as tumoroids in a co-clinical manner. These models retained their original molecular and functional characteristics, including recurrent ARID1A mutations, and serve as tumor avatars suitable for large-scale drug testing. Indeed, screening a large drug library on a small living biobank of such tumors not only revealed distinct response differences between the two entities, but also identified an exceptional dependency of CIC::DUX4-sarcoma cells on MCL1. Mechanistically. MCL1 was identified as a direct target gene of the CIC::DUX4 fusion protein. Genetic and pharmacological inhibition of MCL1 induced rapid apoptosis in CIC::DUX4-sarcoma cells and inhibited tumor growth in a xenograft model. Thus, MCL1 represents a potential novel therapeutic target for CIC::DUX4-sarcoma. Overall, our study highlights the feasibility of co-clinical drug response profiling for individual sarcoma cases and suggests that prospective tests, to evaluate its clinical benefit are highly warranted.

  Study EGAS00001008039

• Beyond BRCA deficiency: Clinical and molecular predictors of survival in patients with BRCA-deficient tubo-ovarian high-grade serous carcinoma

  Homologous recombination DNA repair deficient (HRD) tumors account for about 50% of tubo-ovarian high-grade serous carcinomas (HGSC) and are associated with a high response to platinum-based chemotherapy. However, a subset of patients with HRD tumors have unexpected resistance to chemotherapy and experience short survival. Our study compared BRCA-deficient and proficient HGSC among patients with short (<3 years, the lowest quartile of overall survival (OS)) versus longer-term (>3 year OS) to identify prognostic markers and potential therapeutic opportunities. Primary tumors from a cohort of patients with advanced-stage HGSC (n=154) enriched for those with HRD tumors and short survival (n=42) were analyzed using whole-genome sequencing, bulk RNA-sequencing, and DNA methylation profiling. A subset of HRD tumors (n=143) were characterized for immune cell densities by multiplex immunofluorescence. Clinicopathological features were assessed in 1,389 patients with HGSC, including 282 with pathogenic germline BRCA variants (gBRCApv). Findings were validated in two international HGSC cohorts: the Ovarian Tumor Tissue Analysis consortium (n=5,875) and Multisciplinary Ovarian Cancer Outcome Group (n=895). In gBRCApv-carriers, residual disease following surgical cytoreduction was not associated with shorter OS unlike in non-carriers where it was strongly associated. While most patients with gBRCApv had a more favorable OS compared to non-carriers, a survival advantage was not apparent in those with variants located outside of BRCA1 exon 10/23 and BRCA2 exon 11/27. Patient survival correlated with HRD score, such that those with a score ≥63 had significantly longer OS compared to those with HRD scores of 42-63 and <42. While higher HRD scores were associated with better survival outcomes, most gBRCApv carriers with a short survival had tumor HRD scores that exceeded the threshold typically considered predictive of a good response to carboplatin or PARP inhibitors. BRCA2-deficient HGSC with loss of the tumor suppressor NF1 was associated with exceptionally favorable outcome (median OS 17 years), whereas amplification of both PIK3CA and RAD21, was associated with poor outcome in BRCA2-deficient HGSC (median OS 2.9 years). The density of tumor-infiltrating CD8+ PD-1+ T cells was prognostic for OS in gBRCApv-carriers. In summary, rather than simply the presence or absence of a germline BRCA pathological variant influencing patient survival, the co-occurrence of specific somatic gene alterations, the extent of immune cell infiltration, the level of homologous recombination deficiency, and BRCA-variant location may modify clinical outcomes in patients with BRCA-deficient HGSC. Analysis of exceptional outcome patients, in this case gBRCApv-carriers with an atypically short survival, may identify determinants of outcome applicable to the wider HGSC patient population.

  Study EGAS00001008059

• Single-cell RNA-sequencing of a multi-region pleural mesothelioma case

  Single-cell RNA-sequencing from three distant regions of an epithelioid pleural mesothelioma case.

  Study EGAS00001008062

• Selective targeting of TBXT with DARPins identifies regulatory networks and therapeutic vulnerabilities in chordoma

  The embryonic transcription factor TBXT (brachyury) drives chordoma, a spinal neoplasm without effective drug therapies. TBXT’s regulatory network is poorly understood, and strategies to disrupt its activity for therapeutic purposes are lacking. We developed designed ankyrin repeat proteins that block TBXT-DNA binding (T-DARPins). In chordoma cells, T-DARPins reduced cell cycle progression, spheroid formation, and tumor growth in mice and induced signs of senescence and differentiation. Transcriptomic and proteomic analyses identified gene networks involved in cell cycle regulation, embryonic cell identity, and interferon response and revealed features of regulome components, such as druggability for future translational studies and the fine-tuning of TBXT downstream effectors through IGFBP3. Finally, we found high interferon signaling in chordoma cell lines and patient tumors, which was promoted by TBXT and associated with sensitivity to JAK2 inhibitors. These findings demonstrate the potential of DARPins for probing nuclear proteins to understand the regulatory networks of transcription factor-driven cancers, including entry points for therapies that warrant testing in patients.

  Study EGAS00001008140

• Cross-species Comparison Reveals Therapeutic Vulnerabilities Halting Glioblastoma Progression

  The growth of a tumor is tightly linked to the distribution of its cells along a continuum of activation states. Here, we systematically decode the activation state architecture (ASA) in a glioblastoma (GBM) patient cohort through comparison to adult murine neural stem cells. Modelling of these data forecast how tumor cells organize to sustain growth and identifies rate of activation as the main predictor of growth. Accordingly, patients with a higher quiescence fraction exhibit improved outcomes. Further, DNA methylation arrays enable ASA- related patient stratification. Comparison of healthy and malignant gene expression dynamics reveals dysregulation of the Wnt- antagonist SFRP1 at the quiescence to activation transition. SFRP1 overexpression renders GBM quiescent and increases overall survival of tumor-bearing mice. Surprisingly, it does so through reprogramming the tumor’s stem-like methylome into an astrocyte- like one. Our findings offer a framework for patient stratification with prognostic value, biomarker identification, and therapeutic avenues to halt GBM progression.

  Study EGAS00001008155

• Analysis of enhancer-promoter connectivity alterations

  The study uncovers epigenomic changes associated with dexamethasone response heterogeneity in myeloma cells, revealing rewired promoter-enhancer interactions and DNA loop stabilization

  Study EGAS00001007411

• Integrative Multi-Omics and Drug Sensitivity Profiling Reveals Potential Predictive Biomarkers in Pediatric Solid Tumors from the INFORM Registry

  Cure rates for childhood malignancies using established therapy protocols have increased to an average of 80% but have reached a plateau. Moreover, survival rates are particularly low for some pediatric tumors (such as high-risk Group3 medulloblastomas, osteosarcomas, Ewing sarcomas, high-risk neuroblastomas and high-grade gliomas) and dismal for patients with relapsed malignancies. A functional drug response profiling platform for pediatric solid and brain tumors has been established within the INFORM program to identify patient-specific vulnerabilities, biomarkers and unravel molecular mechanisms associated with drug response profiles for clinical translation. Here, we perform a multi-omics analysis using drug sensitivity profiles, genomic, and transcriptomic data of 81 pediatric solid tumor samples. The integrative analysis revealed two multi-omics signatures with high drug sensitivity predictivity. One signature highlighted neuroblastoma samples with sensitivity to navitoclax (a BCL-2 family inhibitor). A second signature was significantly specific to a subset of Wilms tumors harboring the SIX1 (Q177R) hotspot mutation, which had high expression of MGAM, PTPN14, STAT4 and KDM2B and high sensitivity to MEK inhibitors. A patient-specific causal interaction network analysis elucidated the potential biological mechanism of action between MEK inhibitors and the SIX1 mutation in n = 6 Wilms tumor samples.

  Study EGAS00001008249

• Immune activation in the tumor microenvironment of renal cell carcinoma

  Study describes immunological responses to immunotherapy (anti-PD-1, pembrolizumab) and targeted therapy (VEGFR inhibition, axitinib) as well as anti-CD3/CD28/CD2 (Immunocult) in a patient-derived ex vivo tumor model of renal cell carcinoma. Patient-derived ex vivo tumor models were established and their treatment response studied using material from eight renal cell carcinoma patients. Samples were collected under informed consent in HUS Helsinki University Hospital, Finland. The study aims to understand immunological treatment responses in the patient tumor microenvironment.

  Study EGAS50000001349

• Longitudinal snRNAseq and DNAseq of IDHmutant glioma

  We collected longitudinal glioma samples from 35 patients with an IDH-mutant oligodendroglioma (n = 13) or IDH-mutant astrocytoma (n = 22) diagnosis based on 2021 WHO glioma classification at two or three time points (n = 75 samples). For each patient, we designated the two earliest samples as the initial and recurrence for longitudinal analyses. In 17 of 35 longitudinal pairs, the initial sample was obtained at primary diagnosis, whereas the remaining 18 cases the initial samples were collected at a subsequent surgery. Between the initial and recurrence samples, 26 of 35 patients received radiotherapy and/or alkylating chemotherapy, whereas no adjuvant treatment was reported for the remaining patients. To comprehensively investigate IDH-mutant glioma evolution, we used snRNAseq and bulk DNA/RNA sequencing from the same resected glioma samples. A subset of these samples was profiled with simultaneous snRNA-ATAC sequencing (48 out of 75), including 21 matched longitudinal pairs,

  Dac EGAC50000000973

• Epigenetic characterization of glioblastoma stem cells

  Chromatin accessibility discriminates stem from mature cell populations, enabling the identification of primitive stem-like cells in primary tumors, such as glioblastoma (GBM) where self-renewing cells driving cancer progression and recurrence are prime targets for therapeutic intervention. We show, using single-cell chromatin accessibility, that primary human GBMs harbor a heterogeneous self-renewing population whose diversity is captured in patient-derived glioblastoma stem cells (GSCs). In-depth characterization of chromatin accessibility in GSCs identifies three GSC states: Reactive, Constructive, and Invasive, each governed by uniquely essential transcription factors and present within GBMs in varying proportions. Orthotopic xenografts reveal that GSC states associate with survival, and identify an invasive GSC signature predictive of low patient survival, in line with the higher invasive properties of Invasive state GSCs compared to Reactive and Constructive GSCs as shown by in vitro and in vivo assays. Our chromatin-driven characterization of GSC states improves prognostic precision and identifies dependencies to guide combination therapies.

  Study EGAS50000001804

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• Cellular Analysis of Resistance and Evolution in IDH-mutant glioma

  We profiled a total of 75 IDH-mutant gliomas to study tumor evolution in this tumor type, among which 51 samples are presented here. These data reflect a combination of whole genome sequencing, whole exome sequencing, 10x single nucleus RNA sequencing, and 10x simultaneous single nucleus RNA and ATAC sequencing.

  Dataset EGAD50000002485

• WES of Adenoid Cystic Carcinoma Treated with Axitinib and Avelumab

  To determine potential mutational biomarkers of response to combination axitinib and avelumab, whole exome sequencing was performed on 24 adenoid cystic carcinomas treated with combination axitinib and avelumab with paired normal samples.

  Dataset EGAD50000002467

• ASPSCR1-TFE3 gene fusion panel deep amplicon sequencing data

  Dataset contains compressed, paired-end Fastq files of deep amplicon sequencing data from a custom ASPSCR1-TFE3 gene fusion panel for three alveolar soft part sarcoma cases described in "Development and first-in-human CAR T therapy targeting the pathognomonic MiT-fusion driven protein GPNMB".

  Dataset EGAD50000002438

• WGS data from both single-cell and bulk samples

  This dataset contains the raw BAM/CRAM files used in the manuscript "Single-cell whole-genome sequencing reveals convergent evolution in Burkitt lymphoma" Steemers et al. (2026). This includes: - 332 PTA-based single-cell WGS samples (~15X depth) - 7 bulk tumour samples (~30X depth) with matched germline samples (~30X depth) - 14 bulk tumour samples seqeunced by the Princess Maxima Centre diagnostics department (~105X depth) with matched germline samples (~35X depth)

  Dataset EGAD50000002411

• Whole genome sequencing data of high-grade serous ovarian cancer samples (set 17)

  The dataset contains whole genome sequencing data of 26 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000. The 86 samples are either fresh frozen tumour samples or blood samples. The files provided are paired fastq files.

  Dataset EGAD50000002409

• Case Report: Pre-Clinical Combination Targeting VEGF and PI3K in a Rare, Aggressive Mixed Endometrial Carcinoma

  We report a rare case of a young patient (VENUS 167) initially diagnosed with grade 1 endometrioid endometrial cancer, which, following endocrine treatment, presented with mixed aggressive carcinoma with three distinct histologic patterns: grade 1 endometrioid, large cell neuroendocrine, and undifferentiated carcinoma. The NGS fastq data are WES, RNAseq and ATAC

  Dataset EGAD50000002397

• Single-nucleus RNA sequencing (snRNA-seq) of seven human diffuse midline glioma (DMG) patient tumour samples.

  This dataset comprises 7 paired (14 total) FASTQ files of single-nucleus RNA sequencing (snRNA-seq) data generated from seven human diffuse midline glioma (DMG) patient tumour samples. snRNA-seq libraries were generated using the 10X Chromium Controller and Chromium Next GEM Single Cell 3’ kit version 3.1 in line with the manufacturer’s instructions. Generated libraries were sequenced on an Illumina NextSeq 2000 (P3 XLEAP-SBS chemistry) at targeted 20,000 reads per nucleus.

  Dataset EGAD50000002514

• WES and RNA sequencing of mesothelioma patients from CONFIRM clinical trial

  CONFIRM is a placebo controlled, double-blind randomised phase III clinical trial designed to investigate the efficacy of the anti-PD1 inhibitor nivolumab in patients with relapsed mesothelioma. This study applied the whole exome sequencing and transcriptomic sequencing to uncover determinants of efficacy in patients exhibiting the most extreme response outcomes.

  Study EGAS50000001814

• Multi-omics datasets (WES, RNA-seq) of mesothelioma MIST4 study, a phase II PD-L1/VEGF blockage clinical trial

  This study comprises 26 mesothelioma patients with whole exome and RNA sequencing, designed to examine the efficacy and correlates of response to dual inhibition of programmed death-ligand 1 and vascular endothelial growth factor inhibition.

  Study EGAS50000001818

• Error-corrected targeted sequencing of rectal mucus from patients suspected to have colorectal cancer

  This dataset contains error-corrected next-generation sequencing (ecNGS) data generated from 161 rectal mucus samples. These samples belong to colorectal cancer, adenoma, and control participants. Genomic DNA was extracted and processed using a hybrid-capture panel targeting 50 colorectal cancer–associated genes, incorporating unique molecular identifiers (UMIs) for duplex consensus error correction. Libraries were sequenced on an Illumina NovaSeq 6000 (paired-end 150 bp) producing paired-end FASTQ files. These data support analyses of DNA mutations in CRC detection and progression.

  Dataset EGAD50000002032

• Plasma cfDNA dataset from healthy donors and cancer patients

  The dataset contains 424 paired-end raw fastq files of 224 plasma cfDNA samples from healthy donors and cancer (Ewing Sarcoma, CIC) patients. WGS and methylation binding domain sequencing was performed at 2 × 150 bp on an NovaSeq6000 or NextSeq 500. 200 samples underwent both WGS and methylation binding domain sequencing. 24 samples underwent only WGS.

  Dataset EGAD50000002051

• Whole-genome sequencing data of metastatic salivary gland cancer

  This dataset contains whole-genome sequencing data of three patients with metastatic salivary gland cancer who underwent autopsy to harvest tumor biopsies from spatially separated metastatic sites and biopsies from healthy skin as a control. Two patients had the subtype adenoid cystic carcinoma (patients 1 and 4) and one patient had the subtype myoepithelial carcinoma.

  Dataset EGAD50000002056