9337 results for "cancer rna-seq"

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• Genomic Analysis of Fibrolamellar Hepatocellular Carcinoma

  Fibrolamellar hepatocellular carcinoma (FL-HCC) is a very rare and distinct subtype of hepatocellular carcinoma that occurs in the previously healthy livers of adolescents and young adults. The low incidence rate has kept FL-HCC an understudied cancer, thus the list of FL-HCC markers is limited and the genetic alterations driving its growth have remained unknown. In order to gain a better understanding of the molecular mechanisms underlying FL-HCC initiation and progression, we performed an in-depth genomic analyses of one tumor followed by immunohistochemistry validation on seven other tumors. We showed the expression of neuroendocrine markers in FL-HCC. In addition, DNA/RNA sequencing revealed that common cancer pathways are not visibly altered in FL-HCC but identified two novel structural variants, both resulting in fusion transcripts. Through in vitro studies, we demonstrated the oncogenic properties of these fusion transcripts. These experiments further highlight the tumorigenic role of gene fusions in the etiology of pediatric solid tumors and identify both candidate biomarkers and possible therapeutic targets for this lethal pediatric disease.

  Study phs000828

• Evolution of Chromatin Architecture and Transcriptional Regulation in Mammals

  Changes in gene expression are a critical force driving the evolution of form and function. As a result, the mechanisms by which gene expression evolves have become a subject of intense interest. A number of investigators have measured evolutionary changes in gene expression at the chromatin, mRNA, and protein levels, leading to new insights about how species evolve. However, studies of different stages in gene expression have not always been in agreement. For example, the extremely rapid rates of evolutionary changes that have been widely observed at enhancers appear to conflict with the slower rates observed in mRNA abundance. We recently completed a major comparative study in primates showing that this disparity between enhancer and mRNA evolution, in part, reflects extensive compensation at enhancers that jointly determine transcription at target genes. Likewise, related findings have demonstrated that post-transcriptional changes buffer protein abundance to relatively more common differences in mRNA expression. Together, these recent findings demonstrate that evolutionary changes affecting multiple stages of transcriptional regulation often have interdependent effects on gene expression. Here we propose to determine how stages early during transcriptional regulation work in concert, either to conserve gene expression through compensatory changes across stages, or, in rare cases, to change mRNA in ways that alter organism phenotypes. Our central hypothesis is that interactions between stages are common, especially at long evolutionary time-scales. To test this hypothesis we propose an ambitious plan to collect rich genomic data profiling distinct stages of gene expression in two cell types and three tissues from nine mammalian species. We have focused our study on several early rate-limiting steps in mRNA production, using molecular assays selected to provide orthogonal sources of information about chromatin architecture (Hi-C/Hi-ChIP), accessibility (ATAC-seq), transcription (PRO-seq), and mRNA levels (RNA-seq). This project will produce the largest resource of genomic data uniformly collected across mammals to date. We will integrate genomic data using a suite of new computational tools, which together will provide a new understanding of how distinct regulatory stages work in concert during regulatory evolution.

  Study phs002146

• Genomics of Pediatric Renal Medullary Carcinomas

  Version 1We derived faithful cancer cell lines from patients with a diagnosis of renal medullary carcinomas (RMC). These models have been sequenced with whole genome, exome and transcriptome technologies along with the patient's primary germline and tumor samples. We took these faithful models and performed loss-of-function genetic perturbation screens (e.g. RNAi and CRISPR-Cas9) along with an orthogonal small molecule screen. We identified the ubiquitin-proteasome system as an important target in RMC as well as other SMARCB1 deficient cancers.Version 2We have collaborated with the Children's Oncology Group and the study AREN03B2 to study the cohort of patients with a central diagnosis of RMC. Here, we used 10x linked read sequencing along with RNA-sequencing to profile these matched tumor-normal pairs.

  Study phs001800

• Therapeutic Targeting of ATR Yields Durable Regressions in High Replication Stress Tumors

  Patients with relapsed or recurrent small cell lung cancer or extra-pulmonary small cell cancers were enrolled on an investigator-initiated, single-arm, phase 2 trial (NCT02487095) combining an ATR inhibitor M6620 (VX-970, berzosertib) administered at 210 mg/m2 intravenously over 60 minutes on day 2 and day 5, and topotecan 1.25 mg/m2 intravenously over 30 minutes every 23 hours on days 1 through 5, with a support of pegfilgrastim 6mg subcutaneously on day 6 in 21-day cycles. Tumor samples were collected either just before starting the treatment or before starting treatment prior to be enrolled in the trial. Whole exome and RNA were sequenced to evaluate genomic and transcriptomic characteristics associated with the response to the combination treatment.

  Study phs002327

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): A Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI). Due to additional sharing restrictions, data from one site can be found in phs003094.

  Study phs003066

• Urothelial Cancer - Genomic Analysis to Improve Patient Outcomes and Research (UC-GENOME): a Bladder Cancer Advocacy Network (BCAN)-Led Collaborative Research Pilot Study - for Samples Collected at Johns Hopkins

  UC-GENOME is a real-world cohort of patients with metastatic urothelial carcinoma (UC). The study consisted of two co-equal aims: 1) to provide targeted DNA sequencing for clinical decision making at no cost to patients; and 2) to create a resource for collaborative translational science including a clinically annotated biobank. The submitted data represents the foundational analysis of 218 patients accrued at 7 academic medical centers. The analysis includes 176 patients with both targeted DNA sequencing and RNA sequencing. The genomic data was combined with clinical variables to model response to chemotherapy and immune checkpoint inhibitors (ICI).The larger dataset for this study can be found in dbGaP study phs003066.

  Study phs003094

• Repli-seq data for 'Replication timing alterations are associated with mutation acquisition during tumour evolution in breast and lung cancer'

  The essential process of DNA replication timing during each cell cycle is highly regulated ensuring the correct duplication of the genome. The extent and importance of alterations in this process during malignant transformation has not been extensively explored. Here, we evaluate the impact of altered replication timing (ART) on cancer evolution by analysing replication-timing sequencing of cancer and normal cell lines and 952 whole-genome sequenced lung and breast tumours. We find 6%-18% of the cancer genome displays ART. Genomic regions with a change from early to late replication exhibit an increased mutation rate and distinct mutational signatures, while regions changing from late to early contain genes with increased expression and present a preponderance of APOBEC3-mediated mutation clusters and associated driver mutations. We demonstrate that ART is a relatively early event during cancer evolution and that ART may have a stronger correlation with mutation acquisition than alterations in chromatin structure.

  Study EGAS00001007773

• Targeted Linked-Read DNA-seq Analysis of Castration-Resistant Prostate Cancers

  Androgen receptor (AR) inhibition is standard of care for advanced prostate cancer (PC). However, its efficacy is limited by progression to castration-resistant PC (CRPC), usually due to AR re-activation via mechanisms that include AR amplification and structural rearrangement. These two classes of AR alterations often co-occur in CRPC tumors, but it is unclear whether this reflects intercellular or intracellular heterogeneity of AR. It is important to resolve the mechanisms of AR genomic rearrangements to develop new therapies and predictive biomarkers for PC. We developed a targeted linked-read DNA sequencing assay to interrogate alterations in AR and a panel of genes known to be amplified or mutated in CRPC. Linked-read DNA-sequencing libraries were generated using the 10X Genomics Chromium platform and subjected to hybridization enrichment using a custom-designed Agilent SureSelect bait panel. Post-capture DNA-seq libraries were pooled and sequenced on an Illumina HiSeq 2500 using 2x150 bp settings. This targeted linked-read DNA-seq assay was used to interrogate a set of 6 benchmarking samples harboring known AR gene rearrangements and other alterations in AR, as well a panel of 6 patient-derived xenograft CRPC tumors and 23 clinical CRPC tumors. In this cohort, we identified a subset of samples that developed complex, multiply-rearranged AR gene structures in conjunction with very high AR copy number. The data that will be made available through dbGaP are raw FASTQ files.

  Study phs003343

• RNA Splicing Dysregulation in the Pathogenesis of Chronic Lymphocytic Leukemia

  RNA splicing dysregulation is a hallmark of cancers, promoting the onset and progression of disease. In chronic lymphocytic leukemia (CLL), spliceosome mutations leading to aberrant splicing occurs in approximately 20% of patients. However, the underlying mechanism for splicing defects in spliceosome unmutated CLL cases remains elusive. To discover posttranscriptional regulation of RNA splicing, we performed RNA sequencing using RNA derived from B cells from 6 healthy donors and 36 CLL patients, along with MAZTER sequencing from 9 CLL patients (8 matched with RNA sequencing cohort) and B cells from 5 healthy donors. We found that CLL cells have dysregulated m6A modification sites on transcripts from splicing factors, suggesting a critical role of m6A modification in RNA splicing dysregulation.

  Study phs003191

• ChIP-seq and 4C-seq datasets in megakaryocytes and granulocytes from individuals with QPD and unaffected controls

  ChIP-seq was performed for the following histone modifications in both megakaryocytes and granulocytes: H3K27ac, H3K4me2, and H3K36me3. ChIP-seq was performed for H3K27me3 and CTCF in megakaryocytes only. All ChIP experiments consist of n=3 replicates for each of QPD and Control, with the exception of control granulocyte H3K4me2 for which only n=2 replicates were performed. 4C-seq datasets consist of 2 viewpoints (PLAU promoter and an intergenic enhancer), profiled in megakaryocytes from n=2 controls and n=4 QPD.

  Dataset EGAD00001006048

• Stem-like peripheral helper T cells seed their effector counterpart in rheumatoid arthritis

  The dynamics of helper T cells in the synovium of rheumatoid arthritis was investigated using scRNA-seq, scTCR-seq, and spatial transcriptome.

  Study JGAS000774

• Reference epigenome Islet-derived_iPSC04 h3k9me3 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007893

• Reference epigenome Islet-derived_iPSC04 h3k27ac ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007888

• Reference epigenome Islet-derived_iPSC04 h3k27me3 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007889

• Reference epigenome Islet-derived_iPSC04 h3k36me3 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007890

• Reference epigenome Islet-derived_iPSC04 h3k4me1 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007891

• Reference epigenome Islet-derived_iPSC04 h3k4me3 ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007892

• Reference epigenome Islet-derived_iPSC04 input ChIP-Seq data generated from KEP study

  Islet-derived_iPSC04 input ChIP-Seq paired end data

  Dataset EGAD00001007894

• Reference epigenome Islet-derived_MSC06 h3k27ac ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k27ac ChIP-Seq paired end data

  Dataset EGAD00001007895

• Reference epigenome Islet-derived_MSC06 h3k27me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k27me3 ChIP-Seq paired end data

  Dataset EGAD00001007896

• Reference epigenome Islet-derived_MSC06 h3k36me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k36me3 ChIP-Seq paired end data

  Dataset EGAD00001007897

• Reference epigenome Islet-derived_MSC06 h3k4me1 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007898

• Reference epigenome Islet-derived_MSC06 h3k4me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k4me3 ChIP-Seq paired end data

  Dataset EGAD00001007899

• Reference epigenome Islet-derived_MSC06 h3k9me3 ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 h3k9me3 ChIP-Seq paired end data

  Dataset EGAD00001007900

• Reference epigenome Islet-derived_MSC06 input ChIP-Seq data generated from KEP study

  Islet-derived_MSC06 input ChIP-Seq paired end data

  Dataset EGAD00001007901