11932 results for "cancer rna-seq"

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• RNA-seq from PDAC samples

  Bam and fastq files from RNA-seq of PDAC samples used in the PCSI mismatch repair study

  Dataset EGAD00001006261

• snRNA-seq of subcortical MS

  Single-nuclei RNA-sequencing (snRNA-seq) from subcortical white matter controls and MS lesions, specifically chronic active (CA) and chronic inactive (CI), that paired with the spatial transcriptomics from the same samples, was used to identify spatial niches and key cell interactions driving inflammation and disease progression.

  Study EGAS50000000354

• Single-cell RNA-seq data of bronchoalveolar lavage fluid and extramedullary relapse of a multiple myeloma patient with sarcoidosis-like reactions after anti-BCMA CAR T-cell therapy

  We performed single-cell RNA-sequencing (scRNA-seq) of cells in the bronchoalveolar lavage (BAL) fluid at 3-month follow-up of a multiple myeloma patient experiencing sarcoidosis-like pulmonary reactions after anti-BCMA CAR T-cell therapy (Sample alias: A8_3, A9_3; technical replicates). In addition we performed scRNA-seq of a extramedullary relapse lesion at 6-month follow-up (Sample alias: B10_3).

  Dataset EGAD00001008649

• Transcriptional Profiling of Macrophages In Situ in Metastatic Melanoma Reveals Localization-Dependent Phenotypes and Function

  Therapeutic interventions modulating immune function at the tumor site could improve outcomes in cancer. Here we analyzed metastatic melanoma, a tumor type highly responsive to T-cell based therapies, and found that the tumor-infiltrating T cells are localized closely to CD14+ monocytes/macrophages rather than to melanoma cells. Using novel immunofluorescence-guided laser capture micro-dissection, we analyzed transcriptomes of CD3+ T cells, CD14+ monocytes/macrophages and melanoma cells in non-dissociated tissue. CD14+ cells localized in tumors beds displayed specific transcriptional signatures distinct from CD14+ cells that were localized in tumor stroma.The 8 distinct metastatic melanoma samples are from the Cooperative Human Tissue Network (CHTN). 64 RNA-seq files are available from 16 intraCD14+, 16 stromaCD14+, 16 cancer cells, 8 intraCD3+ and 8 stromaCD3+ cells. 2 LCM harvests were completed for the CD14+ and cancer cells on two sections of the samples. One harvest was done for the CD3+ samples.The processed data (TPM/raw counts tables) are available on GEO under GSE180124. 

  Study phs002564

• Development of the prevention and therapy of CRC using patient derived culture tissues.

  Tumor tissues consist of functionally heterogeneous cells including those with high clonogenic potential called cancer stem cells (CSCs) which produce differentiated non-tumorigenic progenies. Transplantation assays have been performed to identify cell surface markers in solid tumors including colorectal cancers, which identified several CSC markers such as CD133 and CD44. In addition to the transplantation, the lineage tracing of genetically labelling cells in animal models of cancer qhas been employed to explore the cellular heterogeneity of tumors by identifying the CSCs and its progenies. This approach is particularly useful to investigate solid tumors, where cellular proliferation and differentiation are controlled by niche factors and cell-cell contact with adjacent cells. Lineage tracing of mouse model of cancer unravel the mode of growth of autochthonous tumor in their native environment. In this study, we used patient derived organoids (PDO) established from surgically resected CRC patients to identify the CSC. Single cell RNA-seq analysis identified potential CRC markers, which may exhibit self-renewal activity and produce progenitors

  Study JGAS000139

• Dissecting intratumor heterogeneity of nodal B cell lymphoma on the transcriptional, genetic, and drug response level

  Tumor heterogeneity encompasses both the malignant cells and their microenvironment. While heterogeneity between individual patients is well-known to affect the efficacy of anti-cancer, most personalized treatment approaches do not account for intratumor heterogeneity. We addressed this issue by studying the heterogeneity of lymph node-derived B cell non-Hodgkin lymphoma (B-NHL) by single cell RNA-sequencing (scRNA-seq) and transcriptome-informed flow cytometry. We identified transcriptionally distinct malignant subclones and compared their drug response and genomic profiles. Malignant subclones of the same patient responded strikingly different to anti-cancer drugs ex vivo, which recapitulated subclone-specific drug sensitivity during in vivo treatment. Tumor infiltrating T cells represented the majority of non-malignant cells, whose gene expression signatures were similar across all donors, whereas the frequencies of T cell subsets varied significantly between the donors. Our data provide new insights into the heterogeneity of B-NHL and highlight the relevance of intratumor heterogeneity for personalized cancer therapies.

  Study EGAS00001004335

• Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation

  We tested the efficiency and reproducibility of 10 RNA isolation methods on 5 different biofluids. Pooled human plasma and serum, bile and urine were used along with cell culture supernatants from human embryonic stem cells (hESC), primary neonatal rat ventricular myocytes (NRVM) and human cholangiocarcinoma cells (KMBC). 4 RNA isolation methods designed to isolate total RNA from bio fluids without enrichment of exRNA carriers were used. 6 methods that preferentially enriched for exRNA carriers were also compared. Small RNA libraries were constructed using the NEBNext small-RNA library prep. The efficiency and reproducibility of the different RNA isolation methods was compared using small-RNA seq.

  Study phs002143

• Leiden University Medical Center Adipose tissue RNA-seq

  Dac EGAC00001000503

• Board considering access to BELOB RNA-seq data

  Dac EGAC00001001686

• RNA-seq data from 27 glioblastoma samples

  Study EGAS00001005807

• Blood Gene Signatures Associated with Stiffness After TKA

  In this study, we used PAXgene Blood RNA tubes collected from patients undergoing total knee arthroplasty (TKA) for osteoarthritis. Samples were collected with IRB approval and patient consent. We identified 8 patients with knee stiffness after TKA (cases) and 10 patients without post-TKA stiffness (controls). We isolated RNA from cases and controls for RNA-seq analyses, comparing samples collected the day of surgery and samples collected at 24 hours after surgery.

  Study phs002927

• RNA-sequencing of Non-muscle Invasive Bladder cancer (NMIBC)

  This RNA-sequencing cohort includes 78 Non-muscle Invasive Bladder cancer (NMIBC) samples and 7 Muscle Invasive Bladder cancer (MIBC) samples.

  Study EGAS00001004358

• Human and rat skeletal muscle multi-omic profiling

  Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples.

  Study EGAS00001005730

• fibroblast RNAseq from a GINS3 patient and two parents

  RNA-seq was performed from 3 separate GINS3 patient fibroblast cultures and 1 replicate of fibroblasts derived from each of the two parents. RNA-seq libraries were generated with NEBNext Ultra II Directional RNA library prep for Illumina with NEBNext Poly(A) mRNA Magnetic Isolation Module (New England Biolabs) and sequenced on Illumina NextSeq500 with paired-end 150 bp read length. SIRV Set 3 (Lexogen) spike-ins were added. Two fastq files are provided for each RNAseq sample.

  Dataset EGAD00001008571

• Dysregulation of Alternative Splicing Is a Transcriptomic Feature of Patient Derived Fibroblasts From CAG Repeat Expansion Spinocerebellar Ataxias

  The aim of this study was to characterize transcriptomic changes in patient-derived cell lines of CAG repeat expansion spinocerebellar ataxias (SCAs), using RNA-sequencing (RNA-Seq), to help us better understand disease pathogenesis. The data consists of two SCA1, two SCA3, and one SCA7 cell lines with 5 unaffected controls. Widespread alternative splicing dysregulation was identified across all SCA cell lines. Alternative splicing analysis also revealed that the dysregulation affected disease-relevant pathways with novel skipped-exon splicing events from the RNA-Seq data validated with RT-PCR. These findings are consistent with a previous study that identified robust transcriptomic dysregulation, specifically at the splicing level, in SCA1, -3, and -7 mouse models even at presymptomatic ages. Therefore, alternative splicing has the potential to be used as a biomarker not only in mouse models, but also patient models of repeat expansion SCAs.

  Study phs003759