8432 results for "canc*"

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• A single-cell multi-omic atlas of nodal B-cell non-Hodgkin lymphomas

  Nodal B-cell non-Hodgkin lymphomas (B-NHL) are a clinically diverse set of cancers thought to originate from distinct stages of B-cell maturation. To characterize intratumor heterogeneity across B-NHL entities, we performed CITE-Seq (cellular indexing of transcriptomes and epitopes) on 51 lymph node samples including mantle cell lymphoma (MCL, n = 8), follicular lymphoma (FL, n = 12), germinal center (GCB, n = 5) or activated B-cell (non-GCB/ABC, n = 7) diffuse large B-cell lymphoma (DLBCL) and marginal zone lymphoma (MZL, n = 11) tumors, in addition to non-malignant reactive lymph nodes (rLN, n = 8). We also performed 5 prime scRNA-seq with immune receptor profiling for 11 of these samples (2 rLN, 2 MCL, 3 FL, 2 DLBCL, and 2 MZL).

  Study EGAS50000000342

• IBCT-1 (Improved Breast Cancer Therapy) - WXS

  Study Purpose and Design This RNA-seq dataset is derived from the same prospective, randomized neoadjuvant breast cancer trial (IBCT-1) and complements the WXS analysis. RNA sequencing was performed at basline to characterize transcriptomic biomarkers associated with carboplatin response prediction. The cohort includes 187 patients breast cancer tumors across multiple subtypes. Sample Composition - Total samples: 187 (tumor tissue only) Tumor samples: 187 - Sample type: RNA from primary tumor tissue biopsies Technical Specifications - Sequencing platform: Illumina HiSeq4000 - Read type: Paired-end - Read length: 2 × 76 bp - Library preparation: KAPA RNA HyperPrep kit with Twist Bioscience Human Comprehensive Exome Plus RefSeq v1 hybrid selection - RNA input: 100 ng per sample - Sequencing depth: Mean of 35 million read pairs per sample

  Dataset EGAD50000003092

• IBCT-1 (Improved Breast Cancer Therapy) - WES

  This dataset comprises DNA whole-exome sequencing from a prospective, randomized neoadjuvant trial designed to evaluate DNA-based biomarkers for predicting carboplatin response in patients with early, high-risk breast cancer. The study enrolled 196 patients with with high-risk features, including triple-negative breast cancer (TNBC) and hormone receptor-positive (HR+) breast cancer subtypes. The final analysis included 187 patients, for which WES data is being made available for controlled access. Sample Composition Total samples: 373 (186 blood/normal + 187 tumor) - Blood samples: 186 (germline/reference) - Tumor samples: 187 (tumor tissue biopsies) Technical Specifications - Sequencing platform: Illumina HiSeq4000 - Read type: Paired-end - Read length: 2 × 76 bp - Library preparation: Twist Bioscience Human Comprehensive Exome Plus RefSeq v1 hybrid selection - DNA input: 100 ng per sample - Mean sequencing coverage: 46× for normal samples; 106× for tumor samples

  Dataset EGAD50000003091

• 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. Primary tumour tissues and matched normal squamous oesophagus tissues were collected from each individual. Laboratory studies were performed at the Centre for Applied Medical Research (AMR) and sequencing was performed at the Kinghorn Cancer Centre. 64 of 65 cancer samples and 61 matched squamous oesophageal mucosa control tissues were successfully sequenced and passed minimal quality metrics.

  Study EGAS50000002190

• Window-of-opportunity trial of olaparib and durvalumab before standard neoadjuvant chemotherapy for stage II/III triple-negative or ER-low breast cancer (MEDIOLA WOO): whole-exome and transcriptome profiling of serial tumor biopsies

  The MEDIOLA window-of-opportunity (WOO) trial (ESR-16-11923; NCT03594396) was a single-arm, non-randomized, open-label study conducted at Seoul National University Hospital in 54 female patients with stage II/III triple-negative or estrogen receptor (ER)-low breast cancer. Patients received olaparib 300 mg twice daily for 4 weeks with a single 1500 mg dose of durvalumab on day 15, followed by standard neoadjuvant chemotherapy. The primary objective was to characterize changes in tumor biology through serial biopsies obtained at baseline, day 14 (on-treatment 1; OT1, after olaparib alone and before durvalumab), and day 29 (on-treatment 2; OT2, after olaparib plus durvalumab). This study comprises two sequencing datasets. Whole-exome sequencing was performed on baseline tumor biopsies with matched peripheral-blood germline DNA from all 54 patients (54 tumor-normal pairs). RNA sequencing was performed on fresh-frozen serial tumor biopsies, yielding 160 libraries (baseline n = 54, OT1 n = 54, OT2 n = 52; two patients did not undergo OT2 biopsy). All libraries were sequenced on an Illumina NovaSeq 6000 platform. Raw sequence data are provided here under controlled access; processed RNA-seq quantification files are available through the Gene Expression Omnibus.

  Study EGAS50000002019

• MEDIOLA WOO Data Access Committee

  The MEDIOLA WOO Data Access Committee oversees access to controlled-access human genomic data generated by the MEDIOLA window-of-opportunity trial of olaparib and durvalumab in triple-negative or ER-low breast cancer. The Committee reviews and approves data access requests in accordance with the conditions of the original participant consent and institutional ethical approvals. The Committee is administered by Seoul National University Hospital and comprises the corresponding author and the data custodian.

  Dac EGAC50000001066

• This is the dataset for the study "Liquid Biopsy-informed Precision Oncology Study to Evaluate the Clinical Utility of Non-invasive Genomic Profiling for Cancer Treatment Selection"

  This dataset pertains to the study of the first planned analysis of an observational trial assessing the clinical utility of serial LB, combined with precision oncology recommendations by a molecular tumor board (MTB). 50 patients were enrolled between March 2023 and July 2024. The dataset includes 129 BAM files from the targeted capture. 84 samples are from cfDNA, and 45 are from matched buffy coat.

  Dataset EGAD50000003077

• Whole genome sequencing of CheckPAC cfDNA replicates

  188 cfDNA samples from individuals with pancreatic cancer from the CheckPAC trial sequenced to ~2x coverage using 150 bp reads on the Illumina NovaSeq 6000 instrument.

  Dataset EGAD50000001905

• Whole genome sequencing of Endoscopy III Project cfDNA replicates

  181 cfDNA samples from individuals without cancer from the Endoscopy III Project sequenced to ~10x coverage using 100 bp reads on the Illumina NovaSeq 6000 instrument.

  Dataset EGAD50000001906

• 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