11925 results for "cancer rna-seq"

in 9.79 milliseconds.

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  This study includes treatment-naïve fresh tissue sample from 4 HGSOC patients.

  Dataset EGAD00001006984

• Drug-induced epigenomic plasticity reprograms circadian rhythm regulation to drive prostate cancer towards androgen-independence

  ChIP-seq for AR, FOXA1 and H3K27ac in primary prostate tumors before and after 3 months of neoadjuvant enzalutamide treatment. RNA-seq expression data of primary prostate tumors before and after 3 months of neoadjuvant enzalutamide treatment.

  Dataset EGAD00001008562

• Comprehensive RNA repository of tissue and plasma from patients with esophageal cancer or precursor lesions

  A comprehensive RNA repository (both coding and non-coding) from 17 patients diagnosed with esophageal adenocarcinoma, high-grade dysplastic or non-dysplastic Barrett’s esophagus. Per patient, a blood plasma sample, and a healthy esophageal and disease tissue sample were collected. This dataset includes both mRNA and small RNA sequencing data (fastq.gz files) of all tissue and plasma samples. In total,102 RNA-seq libraries from 51 samples (17 plasma and 34 tissue samples) were sequenced (plasma mRNA libraries were sequenced twice).

  Dataset EGAD00001006857

• RNA-seq of PDAC patient-derived xenograft tumors

  This dataset contains single cell RNA-seq data of stromal cells derived from two PDX models (N = 2 in total) and bulk RNA-seq data of two PDX models treated with gemcitabine and our novel antibody-drug conjugate, C6-EBET (N = 59 in total). Bulk RNA-seq experiments were performed with Agilent SureSelect Strand Specific RNA Library Prep Kit (Agilent). Single cell RNA-seq experiments were performed with Chromium Single Cell 3' Reagent Kits v2 Chemistry (10x Genomics).

  Dataset EGAD00001010130

• bulk RNA-seq of the 5 HCC patients which also have the single cell T cell RNA-seq data

  bulk RNA-seq data of the 5 HCC patinets. Single cell RNA seq data of these patients was under the accession number EGAD00001003337

  Dataset EGAD00001004148

• Comparison of capture-based method for transcriptome profiling of formalin-fixed paraffin embedded tumor samples

  Background: The need for fresh frozen (FF) tissue limits implementing RNA sequencing (RNA-seq) in the clinic. The majority of clinical samples are stored as formalin-fixed, paraffin-embedded (FFPE) tissues. Exome capture platforms have been developed for RNA-seq from FFPE samples. However, these methods have not been systematically compared. Methods: Transcriptomic analysis of 32 FFPE tumor samples from 11 patients was performed using three exome capture-based methods: Agilent SureSelect V6, TWIST NGS Exome, and IDT XGen Exome Research Panel. We compared these methods to TruSeq RNA-seq of fresh frozen (FF-TruSeq) tumor samples from the same patients. We assessed the recovery of clinically relevant biological features. Results: The Spearman's correlation coefficients between the global expression profiles of the three capture-based methods from FFPE and matched FF-TruSeq were high (rho = 0.72-0.9, p < 0.05). A significant correlation between the expression of key immune genes between individual capture-based methods and FF-TruSeq (rho = 0.76-0.88, p < 0.05) was observed. All exome capture-based methods reliably detected outlier expression of actionable genes, including ERBB2, MET, NTRK1, and PPARG. In urothelial cancer samples, the Agilent assay was associated with the highest molecular subtype concordance with FF-TruSeq (Cohen's k = 0.7, p < 0.01). Both Agilent and IDT detected all the clinically relevant fusions that were initially identified in FF-TruSeq. Conclusion: All exome capture-based methods had comparable performance and concordance with FF-TruSeq. By enabling the interrogation of FFPE tumor samples, our findings will enable the implementation of RNA-seq in the clinic to guide precision oncology approaches.

  Study EGAS00001005255

• Response and Resistance to ER-Directed Therapy in Metastatic Breast Cancer

  Despite the reduction in cancer recurrence and mortality provided by hormonal therapy, estrogen receptor positive (ER+) metastatic breast cancer (MBC) remains the most common cause of breast cancer death, resulting in more than 20,000 deaths in the U.S each year. Although several therapeutic options exist to target the estrogen receptor, resistance to these therapies invariably occurs. Genetic mechanisms of acquired resistance to targeted therapies in ER+ MBC are not well understood. To address this, we developed a prospective biopsy protocol where multiple research biopsies are collected from metastatic samples and used for pathology, ER/PR/HER2, OncoPanel (a CLIA 300 gene sequencing panel), whole exome sequencing (WES), transcriptome sequencing (RNA-Seq), and single-cell RNA-seq (scRNA-seq). In some cases, tissue is used for cell line and xenograft generation. Archival primary biopsies are also obtained when possible for parallel genomic studies. Patients are followed and serial metastatic biopsies are obtained. This data will be used to determine the landscape of genomic alterations in treatment-resistant ER+ MBC, and compared to data generated by TCGA for treatment-naive ER+ primary breast cancer. Comparison of genomic studies from resistant, metastatic specimens with corresponding pre-treatment primary samples will allow us to identify genomic association with resistance to specific therapies. Analysis of the serial metastatic biopsies collected over the course of multiple treatments will also shed light on tumor evolution under selective therapeutic pressure.NoteA subset of the MBC blood biopsies that are included in our study can be accessed and downloaded from the phs001977 accession.Another subset of patients in this study participated in a clinical trial (NCT02871791) and have their data deposited in the current study as well.

  Study phs001285

• CASCADE tumour transcriptome data

  RNA-Seq data from 20 fresh-frozen postmortem samples from three patients who participated in the CASCADE rapid autopsy program and died of metastatic castration resistant prostate cancer.

  Dataset EGAD00001009492

• Expressed Pseudogenes in the Transcriptional Landscape of Human Cancers

  In this study, we describe a systematic analysis of pseudogene 'transcription' from an RNA-Seq resource of 293 samples, from 13 cancer and normal tissue types. We observed a highly prevalent, genome-wide expression of pseudogenes that could be categorized as universally expressed or lineage- and/or cancer-specific. We also explored disease subtype specificity and functions of selected expressed pseudogenes. We provide evidence that transcribed pseudogenes are a significant contributor to the transcriptional landscape of cells and are positioned to play significant roles in cellular differentiation and cancer progression. Our work provides a transcriptome resource that enables high-throughput analyses of pseudogene expression.

  Study phs000525

• BLUEPRINT EpiVar RNA-seq for Naive naive CD4+ T-cells

  BLUEPRINT EpiVar RNA-seq for Naive naive CD4+ T-cells

  Study EGAS00001000752