5628 results for "*oma"

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• Nanopore Amplicon Sequencing of 34 uveal melanoma samples (33 patient tumors + 1 primary cell line) in 4 mutational hotspot regions for genotyping

  Sequencing of one mutational hotspot region in each of the genes GNA11, GNAQ, SF3B1 and SRSF2. 33 patient tumor samples and a primary cell line were analyzed, all uveal melanoma. Amplicons were generated in a PCR step followed by AMPure XP clean up. Amplicons were pooled equally per sample and sequenced for genotyping.

  Dataset EGAD50000003067

• WES dataset of mesothelioma CONFIRM study

  This dataset comprises 33 whole-exome sequencing (WES) samples from mesothelioma patients, including 18 tumor, 13 matched normal, and 2 relapsed samples.

  Dataset EGAD50000002621

• RNA sequencing dataset of mesothelioma CONFIRM study

  This dataset includes 27 RNA sequencing tumors from mesothelioma, of which two are derived from relapsed patients.

  Dataset EGAD50000002622

• 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 AND operator when a space is inserted between two words. Include OR (capitalised) between the keywords in your search in order to show pages containing either term or 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

• Cell-free DNA Whole Genome Sequencing for Non-Invasive Minimal Residual Disease Detection in Multiple Myeloma

  Minimal residual disease (MRD) monitoring in multiple myeloma (MM) relies on invasive bone marrow (BM) biopsies, which often yield insufficient tumor material. We performed whole genome sequencing of cell-free DNA from 163 plasma samples from 51 patients to develop a non-invasive MRD classifier. BM WGS identified a median of 2,502 clonal mutations, enabling cfDNA tracking at levels comparable to BM-based MRD testing. The cfDNA classifier achieved a mean AUC of 0.86 against multiparameter flow cytometry and targeted immunoglobulin sequencing (clonoSEQ), and MRD negativity after one year of maintenance was strongly associated with two-year relapse-free survival probability (Hazard Ratio = 24), with cfDNA changes preceding clinical progression by a median of 12.6 months. To establish a BM-agnostic mode, a plasma-only classifier trained on baseline cfDNA established a mean AUC of 0.79 compared to BM clinical testing and stratified relapse risk (HR = 4.18), enabling MRD detection in patients with suboptimal BM samples. Longitudinal cfDNA profiles detected subclonal evolution in half of profiled patients. Cell-free DNA whole genome sequencing provides a sensitive, scalable, and clinically informative platform for non-invasive MRD monitoring in MM.

  Study EGAS50000002055

• Visium Spatial transcriptomic profiling of IOKIN samples

  This study aimed to define the spatial tumor microenvironment features associated with response to immune checkpoint blockade in recurrent/metastatic head and neck squamous cell carcinoma (RM-HNSCC). Spatial transcriptomic profiling was performed on tumor biopsies from ICB-naive patients to characterize malignant, stromal, and immune cell states and their spatial interactions. The study investigated how intratumoral heterogeneity, cancer-associated fibroblast programs, immune contexture, and tumor-microenvironment signaling relate to subsequent clinical response and progression-free survival following immunotherapy.

  Study EGAS50000002196

• Whole-Exome Sequencing of Tumor Biopsies from a Colorectal Cancer Patient with Two Distinct Primary Tumors and Matched Metastases

  Colorectal cancer (CRC) is a heterogeneous disease in which rare genetic alterations, such as neurotrophic receptor tyrosine kinase (NTRK) fusions, have emerged as clinically relevant therapeutic targets. Here, we report the case of a 69-year-old man with an advanced colorectal carcinoma comprising two intermixed but histologically distinct components: a predominant (>90%) poorly differentiated solid carcinoma and a conventional adenocarcinoma with mucinous features. Whole-exome sequencing (WES) of microdissected tumor regions (two primary tumors and two matched metastases) along with germline DNA analysis revealed profound genetic divergence between the two tumor components. This case illustrates the coexistence of two genetically independent yet spatially inseparable CRCs following distinct evolutionary trajectories—one driven by an NTRK1 fusion and microsatellite instability (MSI), and the other by canonical KRAS and SMAD4 alterations.

  Study EGAS50000001385

• Single-cell study of 14 childhood medulloblastoma patients

  Study EGAS00001006392

• Genomic correlates with survival after treatment of oesophageal adenocarcinoma by surgery alone

  A 451 cancer-associated gene panel, described in McCabe et al. 2019, was used to assess genomic alterations associated with survival in a Swedish cohort of 65 oesophageal adenocarcinoma (OAC) patients who underwent surgical resection without perioperative treatment. This DAC controls access to sequencing data.

  Dac EGAC50000001177

• Multi-omics analysis revealed clonal evolution of the sarcoma patient-derived xenograft

  We performed whole-exome sequencing and RNA-seq of sarcoma PDXs, along with their matched original tumors when available.

  Study EGAS50000001860