9338 results for "cancer rna-seq"

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• Genomic Analysis of Metastatic Brain Cancer

  This study contains targeted exome and transcriptome sequencing of metastatic brain tumors from 68 patients. Sequencing data includes i) targeted Tempus xT exome sequencing from matched tumor/normal from 68 patients, and ii) whole-transcriptome RNA sequencing from a subset of 65 patients.

  Study phs002639

• Genome-Wide Characterization of Pancreatic Adenocarcinoma Patients Using Next Generation Sequencing

  In this study, we whole genome sequenced tumor/normal pairs from three pancreatic adenocarcinoma patients to separately characterize each patient with respect to somatic alterations. For 2 patients for whom tumor RNA was available, we also performed RNA sequencing to evaluate gene expression changes. While additional sequencing is needed to improve our understanding of the disease, the information acquired from this study contributes to our knowledge base on pancreatic cancer and helps to establish a foundation for identifying and developing more efficacious treatments for patients.

  Study phs000550

• Differential Presence of Exons in Cell-Free DNA Reveals Different Patterns in Colorectal Cancer Between Metastatic and Non-Metastatic Patients

  Tumor genotyping during disease follow-up is gaining an increasing interest for monitoring and clinical management in colorectal cancer (CRC). Growing evidences suggest that single biopsies are inefficient for molecular profiling, due to clonal evolution and intratumoral heterogeneity of primary tumors and/or metastasis. Circulating free DNA (cfDNA) has emerged as an alternative source of genetic material that seems to be representative of the continuously changing tumor molecular features. Thus, the so-called 'liquid biopsy' also offers the additional advantages of accessibility and non-invasiveness for the patient. Novel strategies based on next-generation sequencing (NGS) of cfDNA are being currently developed, with most studies focusing on targeted deep sequencing panels of potential clinically actionable genes. Here we describe an alternative approach, consisting of exome-sequencing in cfDNA at a relatively shallower depth to provide a more general overview of the circulating genome. In this study, two groups of colorectal cancer patients, with either disseminated (M) or localized disease (N), were compared using whole-exome sequencing and a RNA-seq bioinformatics analysis pipeline. Thus, a set of 379 exons present at different levels in cfDNA from both groups were identified, giving rise to a completely new concept in this field, termed as 'Differential Presence of Exons'. Differentially present exons (DPEs) were subsequently used for M and N patients clustering and classification, allowing for the design of a predictive algorithm with encouraging preliminary results in a small subset of patients that could not be initially classified attending to the selection criteria (U group, unassignable).

  Study EGAS00001002687

• Temporal Evolution Reveals Bifurcated Lineages in Aggressive Neuroendocrine Small Cell Prostate Cancer Trans-Differentiation

  Trans-differentiation from adenocarcinoma to small cell neuroendocrine (SCN) cancer is an adverse consequence of treatment escape in various cancers, including prostate, lung, and bladder cancers (Balanis and Sheu et al., 2019 Cancer Cell). Expression of dominant negative p53 (TP53DN), myrAkt1, RB1-shRNA, c-Myc, and Bcl2(PARCB forward transformation) using human naïve prostate basal epithelial cells recapitulated both transcriptional and histological characteristics of small cell neuroendocrine prostate cancer (NEPC) (Park et al., 2018 Science). To study the temporal transcriptional landscape during this trans-differentiation process, we conducted a time course study using a PARCB model by integrating multi-omics sequencing, including bulk RNA-sequencing and ATAC-sequencing on samples taken at different time point, as well as single cell RNA sequencing on serial xenograft tumors. We found a common SCN pathway that resulted in two distinct end states defined by mutually exclusive expression of ASCL1 and ASCL2. Further investigation using CUT&RUN sequencing identified TFAP4 as a potential epigenetic regulator of both proteins. Our study reveals temporal and transcriptional changes from prostate adenocarcinoma to NEPC trans-differentiation.

  Study phs003230

• Single-cell RNA sequencing of 6 follicular lymphoma tumors

  Follicular lymphoma (FL) is an indolent cancer of mature B-cells but carries increased risk of transformation to a more aggressive histology over time. We present here comprehensive profiling both tumor and immune compartments in 6 diagnostic FL biopsies by single-cell RNA sequencing. This confirmed results from 155 FL tumors characterized by mass cytometry (CyTOF) which revealed two distinct evolutionary trajectories with disparate risk of transformation and alternate biologies.

  Study EGAS00001005257

• Differential expression profile of gluten-specific T cells identified by single-cell RNA-seq

  Gluten-specific CD4+ T cells drive the pathogenesis of celiac disease and circulating gluten-specific T cells can be identified by staining with HLA-DQ:gluten tetramers. In this first single-cell RNA-seq study of tetramer-sorted T cells from untreated celiac disease patients blood, we found that gluten-specific T cells showed distinct transcriptomic profiles consistent with activated effector memory T cells that shared features with Th1 and follicular helper T cells. Compared to non-specific cells, gluten-specific T cells showed differential expression of several genes involved in T-cell receptor signaling, translational processes, apoptosis, fatty acid transport, and redox potentials. Many of the gluten-specific T cells studied shared T-cell receptor with each other, indicating that circulating gluten-specific T cells belong to a limited number of clones. Moreover, the transcriptional profiles of cells that shared the same clonal origin were transcriptionally more similar compared with between clonally unrelated gluten-specific cells.

  Study EGAS00001005517

• Pancreatic islets PISA RNA-seq samples

  GWAS have identified more than 700 genetic signals associated with type 2 diabetes (T2D). To gain insight into the underlying molecular mechanisms, we created the Translational human pancreatic Islet Genotype tissue-Expression Resource (TIGER), aggregating >500 human islet RNA-seq and genotyping datasets. We imputed genotypes using 4 reference panels and meta-analyzed cohorts to improve coverage of expression quantitative trait loci (eQTL) and developed a method to combine allele-specific expression across samples (cASE). We identified >1 million islet eQTLs (56% novel), of which 53 colocalize with T2D signals (60% novel). Among them, a low-frequency allele that reduces T2D risk by half increases CCND2 expression. We identified 8 novel cASE colocalizations, among which an SLC30A8 T2D associated variant. We make all the data available through the open-access TIGER portal (http://tiger.bsc.es), which represents a comprehensive human islet genomic data resource to elucidate how genetic variation affects islet function and translate this into therapeutic insight and precision medicine for T2D.

  Study EGAS00001005535

• RNA sequencing data of 66 matched primary and recurrent high grade serous ovarian cancer

  Gene expression profiles of matched primary and recurrent fresh frozen tumor tissues from 66 HGSOC patients were obtained by RNA sequencing. RNA libraries were created using the Illumina TruSeq RNA sample preparation kit V2 according to the manufacturer’s instructions and sequenced on a HiSeq2000 (Illumina, California, USA) using a V3 flowcell generating 1 x 50 bp reads. Raw sequencing reads were mapped to the transcriptome and the human reference genome (NCBI37/hg19) using TopHat 2.0 and Bowtie 2.0.

  Study EGAS00001002660

• Multimodal Epigenetic Sequencing Analysis (MESA) of Cell-free DNA for Non-invasive Cancer Detection

  Multimodal characterization of cell-free DNA (cfDNA) in the blood can enable the sensitive and non-invasive detection of human cancers but remains technically challenging and costly. Here, we developed Multimodal Epigenetic Sequencing Analysis (MESA), a flexible and sensitive method of capturing and integrating multimodal epigenetic information of cfDNA using a single experimental assay, i.e., non-disruptive bisulfite-free methylation sequencing, such as Enzymatic Methyl-seq (EM-seq) and TET-assisted pyridine borane sequencing (TAPS). MESA can simultaneously infer cfDNA methylation, nucleosome occupancy, nucleosome fuzziness, and fragmentation profile for regions surrounding the promoters and polyadenylation sites (PASs). MESA’s integrated analysis of multimodal epigenetic features significantly improved the performance of cancer detection models compared to the usage of any single modality alone. MESA captures additional and highly complementary epigenetic information from cfDNA without additional experimental assays, highlighting the importance and clinical prospect of using multimodal epigenetic features for non-invasive cancer detection

  Study EGAS00001006462

• Development of Computational Approaches for Cell Hashing in scRNA-Seq

  As a test of cell overloading after cell hashing, a sample of peripheral blood mononuclear cells (PBMC) from a single subject was separated into naive T cells, memory T cells, and non-T cell PBMC populations using fluorescence activated cell sorting (FACS). Each population was separated into two technical replicates, then stained with BioLegend TotalSeq-A antibodies. All 6 samples were pooled, then loaded into 6 wells of a 10X Genomics Chromium 3' RNA-seq v3 chip at increasing cell counts: 16,000 (k), 24k, 32k, 48k, 64, and 80k cells per well. We also included a single sample that was not hashed or pooled, as well as a single sample that was stained with hashing antibodies, but not pooled in two separate wells.

  Study phs002695