15169 results for "cancer studies using rna-seq"

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• Targeted Sequencing Data for RESOLVE Clinical Trial

  This is a Phase II clinical trial. This research study is studying a combination of targeted therapies as a possible treatment for estrogen-receptor positive (ER+) endometrial cancer and low-grade serous ovarian cancer. The drugs involved in this study are: - Abemaciclib (also known as Verzenio™) - Letrozole (also known as Femara®) - Metformin (also known as Glucophage®) - Zotatifin (also known as eFT226) - Gedatolisib (also known as PF-05212384)

  Dataset EGAD50000001711

• Whole-genome sequencing study of uveal melanoma

  Uveal melanoma is the most common primary intraocular cancer, characterized by metastasis-related mortality. Here, we explored whole-genome sequences from 40 primary uveal melanomas to illustrate the landscape of genomic mutations and investigate their association with prognosis.

  Study EGAS50000001603

• Genetic landscape of pediatric ependymoma

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

  Study EGAS00001000254

• Genetic landscape of pediatric Rhabdomyosarcoma

  We performed whole-genome sequencing of 13 paired tumor/normal Rhabdomyosarcoma genomes and analyzed somatically acquired single nucleotide variations SNVs, insertion/deletions, structural variations and copy number variations in the cancer genomes

  Study EGAS00001000256

• Genetic landscape of pediatric Osteosarcoma

  We performed whole-genome sequencing of 37 paired tumor/normal OS genomes and analyzed somatically acquired single nucleotide variations (SNVs), insertion/deletions, structural variations and copy number variations in the cancer genomes

  Study EGAS00001000263

• Whole Genome sequencing of colorectal cancer patients (SG-BULK-4)

  Whole Genome sequencing of colorectal cancer patients (SG-BULK-4)

  Dataset EGAD00001008625

• Early breast cancer (WGS)

  Low-coverage whole genome sequencing of 29 early breast cancer samples.

  Dataset EGAD00001007056

• Dataset-linking-WGS-samples-in-ega-box-81-via-README-for-study-EGAS00001002923

  This dataset contains 318 Tumor and Control WGS files submitted in another EGA box for samples for Gerhauser et al.,Cancer Cell, 2018, 34:996-1011. WGS and sequencing protocol was earlier described in Weischenfeldt et al, Cancer Cell, 2013.

  Dataset EGAD00001007861

• February 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  February 2021 data update (fastq) for reference epigenomes generated at Centre for Epigenome Mapping Technologies (Canadian Epigenetics, Environment and Health Research Consortium), Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001007919

• The somatic mutation landscape of normal gastric epithelium - TGS

  The landscapes of somatic mutation in normal cells inform on the processes of mutation and selection operative throughout life, permitting insight into embryogenesis, normal ageing and the earliest stages of cancer development. Here, by whole-genome sequencing and targeted panel sequencing of microdissections from 30 individuals, including 18 with gastric cancer, we elucidate the developmental trajectories of normal and malignant gastric epithelium.

  Dataset EGAD00001015352

• The somatic mutation landscape of normal gastric epithelium - WGS

  The landscapes of somatic mutation in normal cells inform on the processes of mutation and selection operative throughout life, permitting insight into embryogenesis, normal ageing and the earliest stages of cancer development. Here, by whole-genome sequencing and targeted panel sequencing of microdissections from 30 individuals, including 18 with gastric cancer, we elucidate the developmental trajectories of normal and malignant gastric epithelium.

  Dataset EGAD00001015351

• Dataset for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancew

  The dataset for white blood cell and cell-free DNA analyses for detection of residual disease in gastric cancer includes 169 bam files from targeted deep sequencing on the Illumina HiSeq2500. The samples analyzed include genomic DNA from white blood cells and cell-free DNA from longitudinal blood collections of patients with gastric cancer.

  Dataset EGAD00001005750

• Dynamics of multiple resistance mechanisms in plasma DNA during EGFR‐targeted therapies in non‐small cell lung cancer - sWGS

  Shallow whole‐genome sequencing dataset on samples from three patients who underwent histological transformation to small‐cell lung cancer. Samples included in this dataset include normal buffy coat samples, plasma samples collected at diagnosis of NSCLC as well as prior to small‐cell transformation and after SCLC transformation and progression on cisplatin and irinotecan.

  Dataset EGAD00001004379

• Aligned whole genome bisulfite sequencing data for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Aligned whole genome bisulfite sequencing data for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001435

• PCR-free shallow whole genome sequencing for chromosomal copy number detection from plasma of cancer patients is an efficient alternative to the conventional PCR-based approach

  Somatic copy number alterations (SCNAs) can be detected in tumor cell-free DNA (cfDNA) by shallow whole genome sequencing (sWGS). Polymerase chain reaction (PCR) is typically included in library preparations, but a PCR-free method could be an effective alternative for research and diagnostics. Peripheral blood samples (n=22) were collected in EDTA-containing tubes from non-small cell lung cancer patients (n=10) and healthy donors (n=12). PCR and PCR-free library preparations underwent sWGS and the following metrics were compared: mapping quality, proportion of duplicate reads, genome coverage, sequencing read length and copy number profiles. The PCR-free method was further evaluated on archived plasma samples (n=33) of varying pre-analytical quality collected in EDTA or lithium heparin tubes. Archived samples were from acute myeloid leukaemia (n=15) and B-cell lymphoma (n=18) patients. The percentage of unique reads was significantly higher for the 22 samples analysed by PCR-free (95.7%) compared to PCR (84%). PCR-free libraries from 33 archived samples produced data of a comparable quality, with 95.4% unique reads. All other evaluated metrics were highly comparable for PCR and PCR-free library preparations. We conclude that SCNA detection can be performed by PCR-free sWGS on cfDNA from cancer patients and is feasible for diagnostic and archival plasma collected in EDTA- or lithium heparin-containing tubes. Our results pave the way for an automated cfDNA workflow for cancer plasma samples.

  Study EGAS00001004692

• Whole Exome Sequencing data of six chRCC tumors corresponding to three patients

  Mammalian target of rapamycin (mTOR) is a central regulator of mammalian metabolism and physiology. Aberrant hyperactivation of the mTOR pathway promotes tumor growth and metastasis, and can also promote tumor resistance to chemotherapy and cancer drugs; this makes mTOR an attractive cancer therapeutic target. mTOR inhibitors have been approved to treat cancer; however, the mechanisms underlying drug sensitivity remain poorly understood. Here, whole exome sequencing of three chromophobe renal cell carcinoma (chRCC) patients with exceptional mTOR inhibitor sensitivity revealed that all three patients shared somatic mutations in the deubiquitinase USP9X. The clonal characteristics of the mutations, which were amassed by studying multiple patients’ primary and metastatic samples from various years, together with the low USP9X mutation rate in unselected chRCC series, reinforced a causal link between USP9X and mTOR inhibitor sensitivity. Rapamycin treatment of USP9X-depleted HeLa and renal cancer 786-O cells, along with the pharmacological inhibition of USP9X, confirmed that this protein plays a role in patients’ sensitivity to mTOR inhibition. USP9X was not found to exert a direct effect on mTORC1, but subsequent ubiquitylome analyses identified p62 as a direct USP9X target. Increased p62 ubiquitination and the augmented rapamycin effect upon bortezomib treatment, together with the results of p62 and LC3 immunofluorescence assays, suggested that dysregulated autophagy in USP9X-depleted cells can have a synergistic effect with mTOR inhibitors. In summary, we show that USP9X constitutes a potential novel marker of sensitivity to mTOR inhibitors in chRCC patients, and represents a clinical strategy for increasing the sensitivity to these drugs.

  Study EGAS00001007104

• The University of Hong Kong Intestinal Metaplasia Organoids Study

  Background: Gastric intestinal metaplasia (IM) is a pre-cancerous stage spanning a morphological spectrum that is poorly represented by human cell line models. Objective: We aim to establish and characterize human IM cell models to better understand IM progression along the cancer spectrum. Design: A large human gastric IM organoid (IMO) cohort (n=28), their clonal derivatives and normal gastric organoids (n=42) for comparison were established. Comprehensive multi-omics profiling and functional characterization were performed. Results: Single-cell transcriptomes revealed IMO cells spanning a spectrum from hybrid gastric/intestinal to advanced intestinal differentiation. Their lineage trajectories connected different cycling and quiescent stem and progenitors, highlighting differences in gastric to IM transition and the potential origin of IM from STMN1 cycling isthmus stem cells. Hybrid IMOs showed impaired differentiation potential, high lineage plasticity beyond gastric or intestinal fates, and reactivation of a fetal gene program. Cell populations in gastric IM and cancer tissues were highly similar to those derived from IMOs and exhibited a fetal signature. Genomically, IMOs showed elevated mutation burden, frequent chromosome 20 gain, and epigenetic de-regulation of many intestinal and gastric genes. Functionally, IMOs were FGF10 independent and showed downregulated FGFR2. Several IMOs exhibited a cell-matrix adhesion independent (CMi) subpopulation that displayed chromosome 20 gain but lacked key cancer driver mutations, potentially representing the earliest neoplastic precursor of IM-induced gastric cancer. Conclusions: Overall, our IM organoid biobank captured the heterogeneous nature of IM, revealing mechanistic insights on IM pathogenesis and progression, offering an ideal platform for studying early gastric neoplastic transformation and chemoprevention.

  Study EGAS00001007899

• CRU-Ukrainian National Research Center for Radiation Medicine Trio Study

  Data on transgenerational effects following nuclear accidents are important for understanding fully the consequences of parental exposure to ionizing radiation. Few studies to date have had adequate statistical power to detect effects of the magnitude expected based on animal data, and most have not been of low-dose, protracted exposures associated with nuclear accidents and their aftermath. Although, to date, scant use has been made of the new genomic technologies, in Chernobyl-exposed areas of Ukraine and Belarus, excess minisatellite mutations have been seen in children born after the accident. We propose a study of parent-child trios in which at least one parent was exposed to Chernobyl radiation as a clean-up worker (mean dose>=100 mGy) and/or evacuee from a contaminated area (mean >=50 mGy). The specific aims are to investigate the transgenerational and de novo mutation rates of the spectrum of genetic variants in trios, in particular looking at effects in children and mapping them to possible parental origin of the chromsoome. Together with long-term collaborators at the Research Center for Radiation Medicine (RCRM) in Kiev, epidemiologic data will be collected for up to 450 trios of parents with preconceptional doses and their unexposed offspring. We will use state-of-the-art genomic technologies to characterize the landscape of the genomes of the trios to determine whether parental radiation exposure is associated with genetic mutations transmitted to the offspring, by examining de novo mutation rates, minisatellite mutations, copy number alterations, and variations in telomere length. The analysis will be conducted in peripheral blood and/or buccal samples (when blood is not available) from complete father-mother-child trios. Doses to the gonads from the time of the accident to the time of conception will be reconstructed for all parents using existing records supplemented by interview data. Trio subjects will be selected from representative populations exposed to radiation from Chernobyl who are under active follow-up in the Clinico-Epidemiologic Registry at RCRM. To help identify specific effects of paternal and maternal radiation exposure, we will initially select sets of trio subjects in five categories: (1) exposed father, unexposed mother; (2) unexposed father, exposed mother; (3) both parents exposed; (4) both parents unexposed; and (5) a group of high dose "emergency workers" with acute radiation syndrome. All trio members will be invited to the RCRM outpatient clinic for collection of a 20 ml blood sample (or buccal cells for those who refuse phlebotomy). Both parents will be asked to complete a general questionnaire to obtain demographic and lifestyle data. Then one or both will complete detailed dosimetry questionnaires, based on forms used in previous collaborations with RCRM and administered by specially trained interviewers. Once 50 trios have been recruited (10 from each of the 5 exposure categories), we will conduct an interim evaluation of participation rates, sample collection and quality, and dose reconstruction in order to modify the protocol as needed. The analytical approach will be to correlate the extent, especially for de novo events of genetic alterations in the offspring with parental pre-conceptional radiation dose overall and by parental origin. The statistical power in relation to de novo mutations is very high, in excess of 90%, but somewhat lower for trends in minisatellite mutations. Study findings will contribute importantly to knowledge of the heritable effects of moderate- and low-dose radiation exposure in humans and to radiation risk projection. Eventually data from the Trio Study may be shared with the international community through dbGap.

  Study phs001163

• NHLBI TOPMed - NHGRI CCDG: The BioMe Biobank at Mount Sinai

  The IPM BioMe Biobank, founded in September 2007, is an ongoing, broadly-consented electronic health record (EHR)-linked clinical care biobank that enrolls participants non-selectively from the Mount Sinai Medical Center patient population. BioMe currently comprises >42,000 participants from diverse ancestries, characterized by a broad spectrum of longitudinal biomedical traits. Participants are enrolled through an opt-in process and consent to be followed throughout their clinical care (past, present, and future) in real-time, allowing us to integrate their genomic information with their EHRs for discovery research and clinical care implementation. BioMe participants consent for recall, based on their genotype and/or phenotype, permitting in-depth follow-up and functional studies for selected participants at any time. Phenotypic and genomic data are stored in a secure database and made available to investigators, contingent on approval by the BioMe Governing Board. BioMe uses a "data-broker" system to protect confidentiality. Ancestral diversity - BioMe participants represent a broad racial, ethnic and socioeconomic diversity with a distinct and population-specific disease burden. Specifically, BioMe participants are of African (AA), Hispanic/Latino (HL), European (EA) and other/mixed ancestry. BioMe participants are predominantly of African (AA, 24%), Hispanic/Latino (HL, 35%), European (EA, 32%), and other ancestry (OA, 10%). Participants who self-identify as Hispanic/Latino further report to be of Puerto Rican (39%), Dominican (23%), Central/South American (17%), Mexican (5%) or other Hispanic (16%) ancestry. More than 40% of European ancestry participants are genetically determined to be of Ashkenazi Jewish ancestry. With this broad ancestral diversity, BioMe is uniquely positioned to examine the impact of demographic and evolutionary forces that have shaped common disease risk. Phenotypes available in BioMe - BioMe has a high-quality and validated set of fully implemented clinical phenotype data that has been culled by a multi-disciplinary team of experienced investigators, clinicians, information technologists, data-managers, and programmers who apply advanced medical informatics and data mining tools to extract and harmonize EHRs. BioMe, as a cohort, offers a great versatility for designing nested case-control sample-sets, particularly for studying longitudinal traits and co-morbidity in disease burden. Biomedical and clinical outcomes: The BioMe Biobank is linked to Mount Sinai's system-wide Epic EHR, which captures a full spectrum of biomedical phenotypes, including clinical outcomes, covariate and exposure data from past, present and future health care encounters. As such, the BioMe Biobank has a longitudinal design as participants consent to make all of their EHR data from past (dating back as far as 2003), present and future inpatient or outpatient encounters available for research, without restriction. The median number of outpatient encounters is 21 per participant, reflecting predominant enrollment of participants with common chronic conditions from primary care facilities. Environmental data: The clinical and EHR information is complemented by detailed demographic and lifestyle information, including ancestry, residence history, country of origin, personal and familial medical history, education, socio-economic status, physical activity, smoking, dietary habits, alcohol intake, and body weight history, which is collected in a systematic manner by interview-based questionnaire at time of enrollment. The IPM BioMe Biobank contributed ~10,600 DNA samples for whole genome sequencing to the TOPMed program. Samples were selected for the Coronary Artery Disease (CAD) and the Chronic Obstructive Pulmonary Disease (COPD) working groups. Using a Case-Definition-Algorithm (CDA), we identified ~4,100 individuals with CAD (~50% women) and ~3,000 individuals as controls (65% women). In addition, we identified ~800 individuals with COPD (62% women) and 1800 individuals as controls (72% women). Another 600 BioMe participants with Atrial Fibrillation, all of African ancestry, were included.

  Study phs001644

• DNA methylation-based classification of sinonasal tumors [Proteomics data]

  This dataset includes raw label-free mass spectrometry proteomics data of different sinonasal tumor entities as well as normal sinonasal tissue. 72 samples were processed on a Q Exactive HF-X instrument coupled to an easy nanoLC 1200 system using one microgram of peptides and an 110 minutes gradient.

  Dataset EGAD00010002381

• Korean WGS

  We sequenced the genomes of 141 Korean never-smoker lung adenocarcinoma patients, excluding EGFR and ALK alterations. We utilized the TruSeq DNA Library Prep Kit and performed by the Illumina NovaSeq 6000 instrument, yielding sequencing paired reads of approximately 150 bp in size. Afterward, we processed the FASTQ files using the GATK Best Practice pipeline.

  Dataset EGAD50000000346

• Exome sequencing data, phenotypic information, and somatic mutation analysis results for 44 diagnosis-relapse DLBCL pairs

  This dataset contains exome sequencing data, phenotypic information, and somatic mutation analysis results for 44 diagnosis-relapse DLBCL pairs. Exon sequencing data were captured using the Agilent HaloPlex exon kit. bam files were obtained from illumina sequencing followed by BWA alignment.

  Dataset EGAD50000000049

• Moroccan Genome Project: Sequencing Data from 109 Whole Genomes of Moroccan Individuals

  This study is the first phase of the Moroccan Genome Project, which included the complete sequencing of 109 genomes from the Kingdom of Morocco. The sequencing was performing using the Illumina NovaSeq6000 platform, with a mean coverage of 30X.

  Dataset EGAD50000000750

• Cas9-targeted-based long-read sequencing for genetic screening of RPE65 locus

  The dataset includes sequencing data from five inherited retinal dystrophies (IRD) patients using three diferent platforms: Clinical Exome (CES), Long-read sequencing of RPE65 locus, and 3) whole genome sequencing.

  Dataset EGAD50000000847

• APS-1 TCR Sequencing

  Single cell TCR sequencing of expanded regulatory T cells (Tregs) in 9 APS-1 patients and 9 ange and gender matched controls. T-cell receptor (TCR) libraries were generated using the Single Cell Human TCR Amplification Kit and the Library Construction Kit from 10x genomics.

  Dataset EGAD50000000261