15028 results for "cancer studies using rna-seq"

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• Infiltrative and drug-resistant slow-cycling cells support metabolic heterogeneity in glioblastoma

  Glioblastoma patient derived Fast/Slow cycling cancer stem cell RNA sequencing. Consists of 3 patient cell lines and 6 files

  Dataset EGAD00001004380

• Human Brain Small Extracellular Vesicles Contain Selectively-Packaged, Full-Length mRNA

  Brain cells release and take up small extracellular vesicles (sEVs) containing bioactive nucleic acids. sEV exchange is hypothesized to contribute to stereotyped spread of neuropathological changes in the diseased brain. We assessed mRNA from sEVs of non-diseased (ND) and Alzheimer’s disease (AD) human postmortem brain, using short- and long-read sequencing. sEV transcriptomes were distinct from bulk tissue, showing enrichment for multiple genes including mRNAs encoding ribosomal proteins and L1Hs transposable elements. AD versus ND sEVs showed enrichment of inflammation-related and depletion of synaptic signaling mRNAs. sEV mRNA from cultured murine primary neurons, astrocytes, or microglia showed similarities with human brain sEVs and revealed cell-type specific packaging. Nearly 80% of human brain sEV transcripts sequenced using long-read sequencing were full-length. Motif analyses of sEV-enriched full-length isoforms revealed RNA-binding proteins that may be associated with sEV loading. Collectively, we show that mRNA in brain sEVs is selectively-packaged and altered by disease state.

  Study EGAS50000000029

• NIDCD Otitis Media Genetic Susceptibility and Middle Ear Microbial Shifts

  The study funded by R01 DC015004 aims to: (1) Identify rare OM susceptibility variants within families and in probands; and (2) Identify differences in the middle ear microbiome due to OM susceptibility variants. This study will also elucidate mechanisms responsible for the formation and growth of cholesteatoma, and bony erosion and complications due to cholesteatoma e.g. intracranial, hearing/vestibular loss, facial nerve palsy. A better understanding of cholesteatoma pathogenesis will potentially reveal novel drug targets, which can lead to new non-surgical therapies for cholesteatomatous OM. Our specific aims for this administrative supplement are: Aim 1 -- Perform RNA-sequencing using cholesteatoma samples collected from Filipino and Colorado patients who will be screened for FUT2, SPINK5 and A2ML1 variants; and Aim 2 -- Using network analysis, identify bone-expressed proteins potentially interacting with FUT2, SPINK5 or A2ML1, then test protein expression in archival human temporal bone in direct contact with cholesteatoma.

  Study phs001941

• Bulk-tissue RNA-sequencing of anterior cingulate cortex samples derived from Lewy body disease patients

  Parkinson’s disease (PD), Parkinson’s disease with dementia (PDD) and dementia with Lewy bodies (DLB) are three clinically, genetically and neuropathologically overlapping neurodegenerative diseases collectively known as the Lewy body diseases (LBDs). A variety of molecular mechanisms have been implicated in PD pathogenesis, but the mechanisms underlying PDD and DLB remain largely unknown, a knowledge gap that presents an impediment to the discovery of disease-modifying therapies. Transcriptomic profiling can contribute to addressing this gap, but remains limited in the LBDs. Here, we applied paired bulk-tissue and single-nucleus RNA-sequencing to anterior cingulate cortex samples derived from 28 individuals, including healthy controls, PD, PDD and DLB cases (n = 7 per group), to transcriptomically profile the LBDs. Using this approach, we (i) found transcriptional alterations in multiple cell types across the LBDs; (ii) discovered evidence for widespread dysregulation of RNA splicing, particularly in PDD and DLB; (iii) identified potential splicing factors, with links to other dementia-related neurodegenerative diseases, coordinating this dysregulation; and (iv) identified transcriptomic commonalities and distinctions between the LBDs that inform understanding of the relationships between these three clinical disorders. Together, these findings have important implications for the design of RNA-targeted therapies for these diseases and highlight a potential molecular “window” of therapeutic opportunity between the initial onset of PD and subsequent development of Lewy body dementia.

  Study EGAS00001005305

• RNA Sequencing of Colorectal Liver Metastases

  A subset of patients with metastatic colorectal cancer achieves prolonged survival after hepatic resection of limited liver metastases. Here, we examined the molecular features of colorectal liver metastases as they relate to clinical outcomes.

  Study EGAS00001002945

• Genome-wide DNA methylation profiles of NSCLC xenograft and primary lung tissues for the identification of epigenetic predictive biomarkers.

  Non-small cell lung cancers (NSCLC) are the most common cause of cancer-related deaths worldwide and primarily treated with platinum-based drugs like cisplatin and carboplatin, radiation and surgery. The major challenge in the management of NSCLC are intrinsic or acquired resistance mechanisms with only few published molecular markers which can predict the outcome of the patients. On the other side, changes in DNA methylation are observed in nearly all cancer types making them suitable as biomarker. Here genome-wide methylation profiles from MeDIP-Seq and gene expression profiling data of 22 primary NSCLC, adjacent normal tissue and PDX samples are provided. For each PDX tumor growth rates were measured in absence or presence of chemotherapy.

  Study EGAS00001002479

• Detection of mutational patterns in cell free DNA (cfDNA) of colorectal cancer by custom amplicon sequencing

  Monitoring the mutational patterns of solid tumors during cancer therapy is a major challenge in oncology. Analysis of mutations in cell free (cf) DNA offers a non-invasive approach to detect mutations that may be prognostic for disease survival or predictive for primary or secondary drug resistance. A main challenge for the application of cfDNA as a diagnostic tool is the diverse mutational landscape of cancer. Here, we developed a flexible end-to-end experimental and bioinformatics workflow to analyze mutations in cfDNA using custom amplicon sequencing. Our approach relies on open software tools to select primers suitable for multiplex PCR using minimal cfDNA as input. In addition, we developed a robust linear model to identify specific genetic alterations from sequencing data of cfDNA. We used our method to design a custom amplicon panel suitable for detection of hotspot mutations relevant for colorectal cancer and analyzed mutations in serial cfDNA samples from 34 patients with advanced colorectal cancer. Our data demonstrates that recurrent and patient-specific mutational patterns can be reliably detected for the majority of patients. Furthermore, we show that the allele frequency of mutations in cfDNA correlates well with disease progression. Finally, we demonstrate that monitoring of cfDNA can outperform the predictive power of currently used tumor markers and reveal mechanisms of resistance to anti-EGFR antibody treatment.

  Study EGAS00001003382

• Bulk RNA sequencing data of high-grade serous ovarian cancer samples (set 7-17)

  The dataset contains RNA sequencing data of 272 high-grade serous carcinoma (HGSC) patients sequenced with Novoseq 6000, MGISEQ or Hiseq X Ten. The 814 samples are fresh frozen tissue samples that have been collected from different tissues and time points before and during treatment. The files provided are paired fastq files.

  Dataset EGAD50000001370

• Single-cell RNA sequencing of metastatic colorectal cancer patient-derived xenografts treated with cetuximab

  Tumor implantation and expansion were performed in two 6-week-old NOD/SCID mice. Once tumors reached an average volume of approximately 700 mm³, mice were randomly assigned to one of two treatment arms: vehicle (physiological saline, intraperitoneally, twice weekly) or cetuximab (20 mg/kg, intraperitoneally, twice weekly). After 1 week of treatment, mice were sacrificed, and tumors were harvested and preserved in sCelLiVE® Buffer for downstream single-cell RNA sequencing analysis.

  Dataset EGAD50000002103

• HiC files for Zhang GenomePaint paper

  HiC files for GenomePaint paper titled "Exploration of coding and non-coding variants in cancer using GenomePaint."

  Dataset EGAD00001006678