10158 results for "cancer rna-seq"

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• SGCC GASCAD-II dataset

  The GASCAD-II dataset from the Singapore Gastric Cancer Consortium includes paired tumor-blood whole exome sequencing data for 209 gastric cancer (GC) patients, along with whole transcriptome sequencing data for 125 GC samples. Whole exome sequencing was conducted using Agilent SureSelect Human All Exon V6 kits. For RNA sequencing, total RNA was isolated using the RNeasy Mini Kit, and libraries were prepared with the TruSeq Stranded Total RNA with Ribo-Zero Gold protocol (Illumina). Aligned BAM files for both exome and RNAseq data are included in this dataset

  Dataset EGAD00001015433

• RNA sequencing of Korean ER positive breast cancer females aged under 35 years old.

  Corresponding data set is composed of RNA sequencing of Korean ER positive breast cancer under 35 years old. This set provides 50 alignment files of 50 tumor samples. This is a part of total project data set.

  Dataset EGAD00001003243

• small RNA next generation sequencing in head and neck cancer

  small RNA next generation sequencing in head and neck cancer

  Dataset EGAD00001008402

• Molecular Signatures of DCIS to Invasive Progression for Basal-Like Breast Cancers: An Integrated Mouse Model and Human Tumor Study

  We studied the genomic signatures of progression in breast ductal carcinoma in situ (DCIS) as it progresses towards triple negative invasive breast cancer (TNBC). Single cell RNA sequencing (scRNAseq) was performed on the C3Tag genetically engineered mouse model that forms human breast-like DCIS and TNBC. Bulk RNA sequencing was performed on RNA harvested from archival formalin-fixed, paraffin embedded (FFPE) pairs comprising of estrogen receptor (ER) positive (ER+) and negative (ER-) subsets of DCIS. 

  Study phs002443

• Transfer Learning Associates CAFs with EMT and Inflammation in Tumor Cells in Human Tumors and Organoid Co-Culture in Pancreatic Ductal Adenocarcinoma

  This study examined the transcriptional changes induced by cancer associated fibroblasts (CAFs) in pancreatic ductal adenocarcinoma patient-derived tumor organoids. We hypothesized that cancer associated fibroblasts impacted tumor cell transcription to promote tumorigenic behavior. Using patient-matched cells from 3 patients, we compared the transcriptional profiles of patient-derived organoids in monoculture to patient-derived organoids co-cultured with CAFs. Similarly, we looked at the transcriptional changes in matched patient-derived cancer associated fibroblasts grown in monoculture or co-cultured with patient-derived organoids. With a focus on intercellular crosstalk, we identified crosstalk between cancer associated fibroblasts and patient-derived organoids through VEGFA and NRP1. This was identified by bulk RNA sequencing and examined dynamically in organoid-CAF co-culture. This dbGaP deposit is the bulk RNA sequencing data for these 3 patients.

  Study phs003563

• scRNA-seq and snRNA-seq of trophoblast stem cells (TSCs) differentiation into extravillous trophoblast organoids (EVTs)

  This dataset is part of a study that aims to compare in vivo human trophoblast differentiation into EVTs to different in vitro trophoblast organoids using single-cell and single-nuclei RNA sequencing. This specific dataset includes scRNA-seq and snRNA-seq data from trophoblast stem cells (TSCs). Trophoblast stem cell (TSC) lines BTS5 and BTS11 derived by Okae and colleagues were grown as described previously (Okae et al. 2018) together with EVT differentiation media. This study shows that the main regulatory programs mediating EVT invasion in vivo are preserved in in vitro models of EVT differentiation from primary trophoblast organoids and trophoblast stem cells. Data for primary trophoblast organoids is available under E-MTAB-12650.

  Dataset EGAD00001010017

• Characterization of High-Grade Serous Ovarian Cancer Subtypes via Single-Cell Profiling

  We measured gene expression in single-cell RNA sequencing samples from patients with high-grade serous ovarian cancer (HGSOC), for a study on improving HGSOC subtype definition by taking into account varying cell type proportions within tumors. The initial dataset (added October, 2020) contains 3 samples (3 individuals). The next dataset (added November, 2022) contains 34 samples from 8 individuals. The samples in the second dataset were sequenced in five different ways: 1) rRNA depletion and bulk RNA sequencing of tumor chunks, 2) rRNA depletion and bulk RNA sequencing of dissociated cells, 3) poly-A capture and bulk RNA sequencing of dissociated cells, 4) poly-A capture and scRNA sequencing of dissociated cells, 5) barcoding and pooling cells and scRNA sequencing (2 pools of 4 samples each).

  Study phs002262

• RNA sequencing in primary inflammatory (TPP) macrophages following deletion of a disease-associated gene desert at chr21q22, disruption of ETS2, or treatment of ETS2-edited macrophages with a HIF1α stabiliser.

  This dataset comprises raw RNA sequencing data (FASTQs) from primary inflammatory (TPP) macrophages that were unedited (non-targeting control, NTC), edited to delete the disease-associated chr21q22 enhancer region (n=5), or edited to disrupt ETS2 with 1 of 2 independent gRNAs (n=9). We also performed RNA-sequencing in NTC or ETS2-edited TPP macrophages that were treated for 12 hours with vehicle (DMSO) or roxadustat (30 uM, n=3). Macrophages were detached using Accutase and lysed. RNA was extracted from cell lysates using an AllPrep DNA/RNA Mini Kit (Qiagen). Sequencing libraries were prepared from 10ng RNA using the SMARTer Stranded Total RNA-Seq Kit v2 - Pico Input Mammalian (Takara) following the manufacturer’s instructions. The quality and molarity of all libraries was assessed using a BioAnalyzer 2100 and the libraries were sequenced on a NextSeq500. Raw data are provided as 50 bp paired-end Illumina reads.

  Dataset EGAD00001011338

• Comparison of 3 protocols for deriving pancreatic progenitors from hPSC with RNA-seq and ATAC-seq

  Several distinct differentiation protocols for deriving pancreatic progenitors (PP) from human pluripotent stem cells have been described but it remains to be shown how similar the PP are across protocols, and how well they resemble their in vivo counterparts. Here we evaluated three differentiation protocols; performed RNA and ATAC-seq on isolated PP derived with these, and compared them to fetal human pancreas populations. This enabled us to define a shared transcriptional and epigenomic signature of the PP, including several genes not previously implicated in pancreas development. Furthermore, we identified a significant and previously unappreciated cross-protocol variation of the PP through multi-omics analysis and demonstrate how such information can be applied to refine differentiation protocols for derivation of insulin-producing beta-like cells. Together, our study highlights the importance of a detailed characterization of defined cell populations derived from distinct differentiation protocols, and provides a valuable resource for exploring human pancreatic development.

  Study EGAS00001003513

• Identification of the Global miR-130a Targetome Reveals a Novel Role for TBL1XR1 in Hematopoietic Stem Cell Self-Renewal and t(8;21) AML

  In this study, we identified miR-130a as a regulator of HSC self-renewal and differentiation. To characterize gene expression changes following enforced expression of miR-130a OE, we performed RNA-seq in CD34+ cord blood (CB) cells transduced with control and miR-130a OE lentiviruses. To capture miRNA targets in an unbiased, transcriptome-wide manner, we perfomed enhanced CLIPseq procol in 2 replicates of CD34+ CB cells and Kasumi-1 cell line, which represent a model system for t(8;21) AML. We chose this cell line, as we found miR-130a to be highly expressed in this AML subtype where it is critical for maintaining the oncogenic molecular program mediated by AML1-ETO. Chimeric Ago2 eCLIPseq in CD34+ CB cells combined with Mass Spectrometry data analysis identified TBL1XR1 as a principal target of miR-130a. To elucidate gene expression changes associated with TBL1XR1 loss of function, we performed RNA-seq in CD34+CD38- CB cells transduced with control and shRNA targeted against TBL1XR1. To determine the functional significance of high miR-130a expression levels in Kasumi-1 cells on the molecular network controlled by AML1-ETO, we performed CUT&RUN assay and RNA-seq in Kasumi-1 cells following miR-130a knock-down (KD). Collectively, our findings reveal a unique role of miR-130a in regulating normal hematopoietic stem cell self-renewal and how elevated levels of miR-130a in t(8;21) AML contribute to the leukemogenesis of this AML subtype.

  Dataset EGAD00001008412

• Personalized Breast Cancer Vaccines Based on Genome Sequencing

  This study is from a phase I clinical trial of neoantigen DNA vaccines in triple negative breast cancer patients with persistent disease following neoadjuvant chemotherapy. The exome and RNA sequences used to identify somatic mutations, predict neoantigens, and design vaccines is within.

  Study phs002787

• ICGC PCAWG Dataset: PACA-AU_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: PACA-AU.

  Dataset EGAD00001003410

• ICGC PCAWG Dataset: PACA-AU_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: PACA-AU.

  Dataset EGAD00001003411

• ICGC PCAWG Dataset: OV-AU_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: OV-AU.

  Dataset EGAD00001003415

• ICGC PCAWG Dataset: OV-AU_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: OV-AU.

  Dataset EGAD00001003416

• ICGC PCAWG Dataset: LIRI-JP_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: LIRI-JP.

  Dataset EGAD00001003546

• ICGC PCAWG Dataset: LIRI-JP_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: LIRI-JP.

  Dataset EGAD00001003547

• ICGC PCAWG Dataset: CLLE-ES_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: CLLE-ES.

  Dataset EGAD00001003548

• ICGC PCAWG Dataset: CLLE-ES_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: CLLE-ES.

  Dataset EGAD00001003549

• ICGC PCAWG Dataset: RECA-EU_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: RECA-EU.

  Dataset EGAD00001003558

• ICGC PCAWG Dataset: RECA-EU_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: RECA-EU.

  Dataset EGAD00001003559

• ICGC PCAWG Dataset: MALY-DE_PCAWG_RNA-Seq_Star

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using Star. Project: MALY-DE.

  Dataset EGAD00001003560

• ICGC PCAWG Dataset: MALY-DE_PCAWG_RNA-Seq_TopHat2

  ICGC PCAWG Dataset for RNA-Seq BAM aligned using TopHat2. Project: MALY-DE.

  Dataset EGAD00001003561

• Log2 normalized TPM matrix for POPLAR (GO28753)

  This dataset contains log2(TPM + 1) for 192 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from POPLAR (GO28753).

  Dataset EGAD00001008390

• Log2 normalized TPM matrix for OAK (GO28915)

  This dataset contains log2(TPM + 1) for 699 tumor samples profiled by RNA-seq for the entire transcriptome for samples originating from OAK (GO28915).

  Dataset EGAD00001008391