10117 results for "cancer rna-seq"

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• EGAD00010000474

  blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 2 (CC2)

  Dataset EGAD00010000474

• EGAD00010000476

  blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 1 (CC1)

  Dataset EGAD00010000476

• EGAD00010000478

  blood-based gene expression from breast cancer cases and age-matched controls in case-control serie 3 (CC3)

  Dataset EGAD00010000478

• EGAD00010000498

  Affymetrix SNP6.0 genotype data for prostate cancer patients

  Dataset EGAD00010000498

• Capture Hi-C

  Capture Hi-C identifies the chromatin interactome of colorectal cancer risk loci.

  Dataset EGAD00001001243

• Cell Line Dataset

  Frequent somatic transfer of mitochondrial DNA into the nuclear genome of human cancer cells

  Dataset EGAD00001001349

• OCAC OncoArray data

  Germline genotype data on 56,479 ovarian cancer cases and controls

  Dataset EGAD00010001192

• Exome reads

  Cancer exomes consisting of FASTQ paired-end reads from ovary samples

  Dataset EGAD00001003916

• Transcriptome sequencing of Gingivo-buccal Cancer : ICGC-India Project_Batch05

  Dataset EGAD00001004430

• Blood dataset - Case

  blood-based gene expression from breast cancer cases

  Dataset EGAD00010001063

• EPIC

  EPIC array data from 72 tumor samples with muscle invasive bladder cancer.

  Dataset EGAD00010001921

• SAFIR02_Agilent

  Genomics to select patients with metastatic breast cancer for targeted therapy (microarray_agilent)

  Dataset EGAD00010002243

• Genomic Analyses in Neoadjuvant Immunotherapy-Treated Head and Neck Cancers

  This is a phase 2 multicenter interventional trial involving the preoperative (neoadjuvant) administration of pembrolizumab, an anti-programmed cell death protein-1 (anti-PD-1) agent, to patients with pathologically confirmed, surgically resectable advanced head and neck squamous cell carcinoma (HNSCC). Participating centers were Dana-Farber/Harvard Cancer Center, Alvin J. Siteman Cancer Center, Washington University and Memorial Sloan Kettering Cancer Center. The trial (NCT02296684) consisted of two cohorts: Cohort 1 enrolled and treated patients received one dose of pembrolizumab prior to surgical resection with curative intent, and adjuvant pembrolizumab was planned for patients with high risk pathological features (positive margins and/or extranodal extension) in the surgical specimen. Cohort 2 enrolled and treated patients received 2 doses of pembrolizumab prior to surgical resection with curative intent. Adjuvant treatment was not dictated by the trial protocol for Cohort 2. The primary endpoint was rate of at least 50% pathological tumor response (pTR), defined as the presence of tumor necrosis/keratinous debris in the tumor bed following neoadjuvant pembrolizumab. pTR was graded as follows: pTR0 (<10%), pTR1 (10-49%) and pTR2 (≥50%). Baseline, pre-treatment tumor biopsy and post-neoadjuvant pembrolizumab surgically resected tumor specimens were dissociated, and CD3+CD45+ cells were analyzed for T cell receptor (TCR) expression and 5' gene expression analysis using single cell sequencing technologies for a subset of patients.

  Study phs002864

• 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

• 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

• 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

• A comprehensive DNA methylation landscape of human and mouse cell lines derived from hematological malignancies

  Human cancer cell lines constitute useful models to study the primary disease and many relevant findings in tumor biology have been originated from them since the first immortalized cell line (HeLa) was obtained. The easy experimental intervention, the purity of the transformed cells and their versatility to undergo high-throughput screenings represent advantageous features of the established cancer cell lines. In recent years, major efforts have characterized in detail the multiomics make-up of hundreds of cancer cell lines and studied their association with sensitivity to anticancer drugs. Most of these studies have been genetic-centric and have not characterized in detail the epigenetic profiles underlying the characteristics of these cells or their impact on the efficacy of antitumoral compounds. In this regard, a past version of a DNA methylation microarray or a less accessible and more time-consuming such as reduced representation bisulfite sequencing have been used in those attempts to interrogate the epigenetic setting. Herein, we have obtained the DNA methylation profiles of 210 cell lines derived from hematological malignancies utilizing comprehensive DNA methylation microarrays that interrogates more than 850,000 and 285,000 CpG sites from human and mouse genomes, respectively. Importantly, we also provide a pharmacoepigenetic example of the potential use of this resource by showing how DNA methylation can predict response to nucleoside analogues.

  Study EGAS50000000627

• New England-Based Case-Control Study of Ovarian Cancer

  The case-control data provided to dbGaP were collected under NCI grant number CA54419 which had 3 enrollment phases: I (1992-1997), II (1998-2002) and III (2003-2008). Altogether, CA54419 funded 15 years of data and specimen collection, resulting in one of the longest running population based case-control studies of ovarian cancer. The study goal was to examine reproductive factors, lifestyle exposures, and genetic background in relation to ovarian cancer risk. The project recruited cases from Eastern Massachusetts and New Hampshire, and became known as the New England-based Case-Control study (NECC) of ovarian cancer. 3957 ovarian cancer cases diagnosed at ages 18-80 and residing in Eastern Massachusetts and New Hampshire were identified through tumor boards and registries. Of these, 3083 (78%) were eligible and among those eligible, 2203 (71%) were enrolled. After excluding 127 non-epithelial and 35 mixed mesodermal tumors, 2041 cases with epithelial tumors of ovarian, primary peritoneal, and fallopian tube origin, including borderline malignancies were included. On average, cases were interviewed 10 months after their diagnosis. A pathologist reviewed pathology reports and recorded histologic subtype, grade, and stage. Mixed ovarian cancers described as predominantly one type were classified as that type. Undifferentiated, transitional cell tumors, or mixed serous/transitional cell tumors were counted as serous. Other mixed epithelial, malignant Brenner, and unspecified epithelial tumors were classified as other. 2100 controls were identified through random digit dialing (RDD), driver-license lists, and town-resident lists. During the first funding phase from 1992 to 1997, 420 (72%) controls identified through RDD and 102 (51%) through town-resident lists agreed to participate. From 1998 to 2008, only town-resident lists were used to identify potential controls. 4366 controls were identified, of whom 1426 (33%) were ineligible if they had died, moved, or were seriously ill or if they did not have a working telephone, speak English, or have at least one ovary. Of eligible controls, 1362 (46%) declined to participate by phone or via 'opt-out' postcard and 1578 (54%) were enrolled. Controls were frequency matched to cases by 5-year age groups and region of residence. In all phases, after written informed consent, demographic information, reproductive and medical history, and habits were assessed by in-person or telephone interview (in a few instances). All of the questions were framed with respect to a reference date defined as 1 year before the diagnosis date for women in the case group and the date of interview for those in the control group. This study was approved by institutional review boards at Dana Farber Harvard Cancer Center and Dartmouth Medical Center.

  Study phs001034

• RNA-Sequencing of B-Lymphoblastic Leukemia with Glucocorticoids and PI3K Delta Inhibition

  Mononuclear cells were isolated from bone marrow or peripheral blood of 7 pediatric subjects with B-lymphoblastic leukemia at the time of diagnosis. To determine the effect of PI3K delta inhibition on glucocorticoid-induced gene regulation, B-lymphoblastic leukemia cells were treated with glucocorticoids +/- the PI3K delta inhibitor, idelalisib, for 24 hours prior to RNA extraction and sequencing. Biological replicates were performed for 4 of the 7 subjects; 2 of these subjects had specimens demonstrating an additive response to the combination of glucocorticoids and idelalisib in viability testing in vitro, and 2 subjects' specimens demonstrated a synergistic response. All 7 subjects were analyzed together and the 4 specimens with biological replicates were also evaluated in an additional analysis. An average of 40 million reads per specimen and treatment condition were obtained. We compared gene expression in each treatment condition to vehicle-treated cells and expression in glucocorticoid or idelalisib only treated cells to combination treated cells. Using a high dose of dexamethasone (25 or 50 nM) and an equivalent dose of prednisolone, we found that the addition of idelalisib (500 nM) enhanced prednisolone-induced gene regulation but not dexamethasone-induced gene regulation. Surprisingly, the specimens with additive response to combination therapy demonstrated enhancement of prednisolone-induced gene regulation with the addition of idelalisib, while the specimens with synergistic responses did not. Raw sequencing data (FASTQ) and count tables will be available through dbGaP.

  Study phs003085

• Neurodegenerative_TGS

  An investigation of clonal haematopoiesis in patients with neurodegenerative disease.

  Study EGAS00001002431

• Exome_sequencing_of_EBV_driven_lymphoma

  Exome sequencing of a case of lethal EBV-driven LPD

  Study EGAS00001001021

• Preoperative ipilimumab plus nivolumab in locoregionally advanced urothelial cancer (NABUCCO Cohorts 1 and 2)

  Study EGAS00001004521

• Targeted analysis of cell-free circulating tumor DNA is suitable for early relapse and actionable target detection in patients with neuroblastoma

  Study EGAS00001006027

• Ludwig Center for Cancer Genetics and Therapeutics at Johns Hopkins

  Dac EGAC00001000507

• Data access committee for study - The subclonal architecture of metastatic breast cancer: Results from a prospective community-based rapid autopsy program "CASCADE".

  Dac EGAC00001000574