11769 results for "cancer rna-seq"

in 15.55 milliseconds.

• Gene expression profiles of disseminated breast cancer cells

  Study EGAS00001004597

• Novel de novo pathogenic variant in the GNAI1 as a cause of severe disorders of intellectual development with autistic features

  Study EGAS00001005355

• Single-cell multi-omics of human clonal hematopoiesis reveals that DNMT3A R882 mutations perturb early progenitor states through selective hypomethylation.

  Study EGAS00001006364

• Genomic and immune signatures predict clinical outcome in newly diagnosed multiple myeloma treated with immunotherapy regimens

  Study EGAS00001007404

• Targeted gene panel sequencing of leiomyosarcoma

  We conducted MSK-IMPACT sequencing of leiomyosarcoma.

  Study EGAS50000000595

• Pancreatic Cancer OICR

  ICGC DCC Release 24, PACA-CA Exome sequence

  Dataset EGAD00001003264

• Capture Hi-C

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

  Dataset EGAD00001001243

• Exome reads

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

  Dataset EGAD00001003916

• Cell Line Dataset

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

  Dataset EGAD00001001349

• Influence of Genomic Landscape on Cancer Immunotherapy for Newly Diagnosed Ovarian Cancer: Biomarker Analyses from the IMagyn050 Randomized Clinical Trial

  The IMagyn050 trial (NCT03038100), which evaluated the efficacy of Atezo vs placebo (Pla) with carboplatin, paclitaxel and bevacizumab (CPB) in front line ovarian cancer patient (pts), did not meet its co-primary endpoints of PFS in ITT or PD-L1+ (Moore et al. JCO 2021). The aim of this exploratory study was to evaluate whether patients with BRCA1/2-mutated or homologous recombination-deficient (HRD) ovarian cancers benefitted from atezolizumab in the phase III IMagyn050 (NCT03038100) trial. Methods: Patients with newly diagnosed ovarian cancer were randomized to either atezolizumab or placebo with standard chemotherapy and bevacizumab. PD-L1 status of tumor-infiltrating immune cells was determined centrally (VENTANA SP142 assay). Genomic alterations, including deleterious BRCA1/2 alterations, genomic loss of heterozygosity (gLOH), tumor mutation burden (TMB), and microsatellite instability (MSI), were evaluated using the FoundationOne assay. HRD was defined as gLOH ≥16%, regardless of BRCA1/2 mutation status. Potential associations between progression-free survival (PFS) and genomic biomarkers were evaluated using standard correlation analyses and log-rank of Kaplan-Meier estimates. Results Among biomarker-evaluable samples, 22% (234/1050) harbored BRCA1/2 mutations and 46% (446/980) were HRD. Median TMB was low irrespective of BRCA1/2 or HRD. Only 3% (29/1024) had TMB ≥10 mut/Mb and 0.3% (3/1022) were MSI-high. PFS was better in BRCA2-mutated versus BRCA2-non-mutated tumors and in HRD versus proficient tumors. PD-L1 positivity (≥1% expression on immune cells) was associated with HRD but not BRCA1/2 mutations. PFS was not improved by adding atezolizumab in BRCA2-mutated or HRD tumors; there was a trend toward enhanced PFS with atezolizumab in BRCA1-mutated tumors. Conclusion Most ovarian tumors have low TMB despite BRCA1/2 mutations or HRD. Neither BRCA1/2 mutation nor HRD predicted enhanced benefit from atezolizumab. This is the first randomized double-blind trial in ovarian cancer demonstrating that genomic instability triggered by BRCA1/2 mutation or HRD is not associated with improved sensitivity to immune checkpoint inhibitors.

  Study EGAS00001006838

• Evolution and clinical impact of genetic epistasis within EGFR-mutant lung cancers

  The current understanding of tumorigenesis is largely centered on a monogenic driver oncogene model. This paradigm is incompatible with the prevailing clinical experience in most solid malignancies: monotherapy with a drug directed against an individual oncogenic driver typically results in incomplete clinical responses and eventual tumor progression1-7. By profiling the somatic genetic alterations present in over 2,000 cases of lung cancer, the leading cause of cancer mortality worldwide, we show that combinations of functional genetic alterations, i.e. genetic collectives dominate the landscape of advanced-stage disease. We highlight this polygenic landscape and evolution of advanced-stage non-small cell lung cancer (NSCLC) through the spatial-temporal genomic profiling of 7 distinct tumor biopsy specimens and 6 plasma specimens obtained from an EGFR-mutant NSCLC patient at (1) initial diagnosis of early-stage disease, (2) metastatic progression, (3) sequential treatment and resistance to 2 EGFR inhibitors, (4) death. The comprehensive genomic analysis of this case, coupled with circulating free (cf) tumor DNA profiling of additional advanced-stage EGFR-mutant NSCLC clinical cohorts with associated treatment responses uncovered features of evolutionary selection for multiple concurrent gene alterations: including the presence of EGFR inhibitor-sensitive (EGFRL858R;EGFRexon19del) or inhibitor-resistant (EGFRT790M;EGFRC797S) forms of oncogenic EGFR along with cell cycle gene alterations (e.g. in CDK4/6, CCNE1, RB1) and activating alterations in WNT/β-catenin and PI3K pathway genes, which our data suggest can cooperatively impart non-redundant functions to limit EGFR targeted therapy response and/or promote tumor progression. Moreover, evidence of an unanticipated parallel evolution of both EGFR T790M and two distinct forms of oncogenic PIK3CA was observed. Our study provides a large-scale clinical and genetic dataset of advanced-stage EGFR-mutant NSCLC, a rationale for specific polytherapy strategies such as EGFR and CDK4/6 inhibitor co-treatment to potentially enhance clinical outcomes, and prompts a re-evaluation of the prevailing paradigm of monogenic-based molecular stratification for targeted therapy. Instead, our findings highlight an alternative model of genetic collectives that operate through epistasis to drive lung cancer progression and therapy resistance.

  Study EGAS00001002604

• Chromatin profiles classify castration-resistant prostate cancers suggesting therapeutic targets

  Untreated prostate cancers rely on androgen receptor (AR) signaling for growth and survival, forming the basis for the initial efficacy of androgen deprivation therapy (ADT). Yet, the disease can relapse and progress to a lethal stage termed castration-resistant prostate cancer (CRPC). Reactivation of AR signaling represents the most common driver of CRPC growth and next generation AR signaling inhibitors (ARSIs) are now used in combination with ADT as a first line therapy. However, ARSIs can result in selective pressure generating AR-independent tumors. The transition from AR-dependence frequently accompanies a change in phenotype resembling developmental trans-differentiation or ‘lineage plasticity’. Neuroendocrine prostate cancer, which lacks a defined pathologic classification, is the most studied type of lineage plasticity. However, most AR-null tumors do not exhibit neuroendocrine features and are classified as ‘double-negative prostate cancer’, the drivers of which are poorly defined. Lineage plasticity studies in CRPC are limited by the lack of genetically defined patient-derived models that recapitulate the disease spectrum. To address this, we developed a biobank of organoids generated from patient biopsies to study the landscape of metastatic CRPC and allow for functional validation assays. Proteins called transcription factors (TFs) are drivers of tumor lineage plasticity. To identify the key TFs that drive the growth of AR-independent tumors, we integrated epigenetic and transcriptomic data generated from CRPC models. By presenting a map of the chromatin accessibility and transcriptomic landscape of CRPC using a diverse biobank of organoids, PDXs and cell lines that recapitulate the heterogeneity of metastatic prostate cancer, we validate CRPC-AR and CRPC-NE subtypes and reveal two subtypes of AR-negative/low samples as well as their respective masterTFs. Additional analysis revealed a model in which YAP, TAZ, TEAD and AP-1 function together and drive oncogenic growth in CRPC-SCL samples. Overall, we show here how an approach to stratify CRPC patients into four subtypes using their transcriptomic signatures can potentially inform upon appropriate clinical decisions.

  Study EGAS00001006059

• 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

• EXOME_ARRAY_ANALYSIS

  EXOME ARRAY ANALYSIS OF ADVERSE REACTIONS TO FLUOROPYRIMIDINE-BASED THERAPY FOR GASTROINTESTINAL CANCER

  Dataset EGAD00010001499

• Whole Genome Sequencing of Gingivo-buccal Cancer: ICGC-India Project_YR03

  Dataset EGAD00001004478

• methylation_tnbc

  Raw methylation data from triple negative breast cancer.

  Dataset EGAD00010002077

• OICR-DAC, Ontario Institute for Cancer Research

  Dac EGAC00001000591

• OICR-DAC, Ontario Institute for Cancer Research

  Dac EGAC00001000710

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

  Study EGAS00001006027

• 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

• BC WGS Dataset 3

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

  Dataset EGAD00001001351

• BC WGS Dataset 4

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

  Dataset EGAD00001001353

• Sharc-prostate

  Low coverage nanopore sequencing of prostate cancer tumors

  Dataset EGAD00001005473