14983 results for "cancer studies using rna-seq"

in 12.56 milliseconds.

• RNA-seq data from Follicular Lymphoma samples

  Dataset included RNA-seq data (Two Fastq files per sample as paired end sequencing was performed) from ribosomal-depleted total RNA in 28 Follicular Lymphoma (FL) criopreserved samples to analyze long non-coding RNA and coding transcript expression profiles. Sample metadata is referred to histological groups of FL tumors (FL1-3A versus FL3B/DLBCL) either in tumor purified cell samples (N=12) as in unpurified tumor samples including normal cells of the lymph node microenvironment (N=16).

  Dataset EGAD00001004109

• Human melanoma samples with and without resistance to BRAF inhibitor therapy

  Human melanoma samples were collected pre, on, and progression on BRAF inhibitor therapy. RNA was extracted and run on RNA-seq. This has provided insights into different categories of BRAF inhibitor resistance mechanisms.

  Study EGAS00001000992

• Diversity of the immune microenvironment and response to checkpoint inhibitor immunotherapy in mucosal melanoma

  Mucosal melanoma (MucM) is a rare cancer with a poor prognosis and low response rate to immune checkpoint inhibition (ICI) compared to cutaneous melanoma (CM). To explore the immune microenvironment and potential drivers of MucM’s relative resistance to ICI drugs, we characterized 101 MucM tumors (43 head and neck, 31 female urogenital, 13 male urogenital, 11 anorectal, and 3 other gastro-intestinal) using bulk RNA-sequencing (RNAseq). The original publication is written by JL Vos, JJH Traets, et al. and published in JCI Insight in 2024.

  Study EGAS50000000631

• ctDNA mutation analysis using the SiMSen-seq approach

  Mutation analysis in plasma samples with low ctDNA levels using a molecular barcoding technology, i.e. the single target approach SiMSen-seq (Simple, multiplexed, PCR-based barcoding of DNA for sensitive mutation detection using sequencing).

  Dataset EGAD00001006104

• Regulation of T Cell CXCL13 Production

  This study evaluated the signals that regulate production of the B cell chemoattractant CXCL13 by human CD4 T cells. Single-cell and bulk RNA-seq datasets evaluated the gene expression changes induced by TGF-beta and the aryl hydrocarbon receptor (AHR), two signals that regulate CXCL13 production. Bulk ATAC-seq data evaluated the epigenetic changes in T cell stimulated with an AHR agonist or antagonist. Ex vivo bulk RNA-seq data of sorted T cell subsets from blood of patients with lupus and control donors interrogated the gene expression differences in sorted T cell subsets. Ex vivo ATAC-seq data allowed comparison of epigenetic profiles of PD-1hi Tph cells from rheumatoid arthritis synovial fluid and PD-1hi T follicular helper (Tfh) cells from tonsil to PD-1low CD4 T cells from the same samples. Single-cell RNA-seq data of T cells from lupus patients before and after treatment with anifrolumab (anti-IFNAR) allowed interrogation of T cell populations that change with anifrolumab treatment. These datasets allowed for genomic interrogation of changes induced by AHR, TGF-beta, and interferon and their relationship to CXCL13 production.

  Study phs003582

• PCF SELECT data on liquid biopsy samples from 3 clinical studies on prostate cancer patients

  Dac EGAC50000000758

• Gene expression of human Th17 cells before and after activation

  Although gene expression of human Th17 clones has been studies, to date, molecular mechanisms for human Th17 development remain unclear. We have analyzed gene expression of human Th17 cells before and after activation. Th17-cell clones from peripheral blood CD4 T cells cultured with LPS-stimulated dendritic cells derived from monocytes stimulated by TNF were established by a limited dilution method. One of the Th17 clones was proliferated significantly, and high percentages (>70%) of Th17 cells in the cultured cells were maintained by addition of monocytes, IL-1b, and IL-15. CD161+CXCR3- cells (CD161+Th17) in the cultures were sorted and purified up to approximately 97% of IL-17-producing cells after treatment with PMA/ionomycin. Furthermore, these cells were treated with TCR-stimuli, IL-1b, and IL-23 for 2 days, and IL-17-producing Th17 cells (active-Th17) detected by IL-17-catch-up antibodies were sorted. Total RNA sampled from 1x 106 CD161+Th17, active-Th17, na?ve CD4 T cells, or CXCR3+ Th1 cells from combined CD4 T and dendritic cell cultures was used for SAGE. SAGE was performed by using SOLID TM SAGETM kit with barcoding adaptor molecules (Applied Biosystems). DNA sequence was analyzed by using AB5500 Genetic Analyzer (Applied Biosystems), and gene expression was analyzed by using SOLID? SAGETM software (Applied Biosystems). Our data shows high levels of IL-17A-mRNA expression by active-Th17; however, but only slight expression by CD161+Th17. Therefore, the data could provide alteration of gene expression by Th17 cells before and after stimulation.

  Study JGAS000005

• University of Hull

  Tumour Regulatory Molecules in Early Pancreatic Cancer Detection (TEM-PAC) and EARLY DIAgnosis of PAncreatic Cancer by combined proteomics and genomics testing of pancreatic cyst fluid (DIA-PAC) studies.

  Dac EGAC50000000402

• HipSci HumanExome BeadChip analysis - Kabuki syndrome

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Genotyping analysis using the Infinium HumanExome BeadChip on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Kabuki syndrome.

  Study EGAS00001002007

• HipSci HumanHT 12 Expression BeadChip analysis - Kabuki syndrome

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Expression analysis using the Illumina HumanHT -12 Expression BeadChip on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Kabuki syndrome.

  Study EGAS00001002022

• HipSci HumanExome BeadChip analysis - monogenic diabetes

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we performed Genotyping analysis using the Infinium HumanExome BeadChip on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with monogenic diabetes.

  Study EGAS00001001273

• HipSci___Whole_Exome_sequencing___Alport

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Alport syndrome

  Study EGAS00001001974

• HipSci___Whole_Exome_sequencing___Cardiomyopathy

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with hypertrophic cardiomyopathy

  Study EGAS00001001980

• HipSci___Whole_Exome_sequencing___Kabuki

  The HipSci project brings together diverse constituents in genomics, proteomics, cell biology and clinical genetics to create a UK national iPS cell resource and use it to carry out cellular genetic studies. In this sub-study we perform whole exome sequencing using Agilent whole exome pulldown method on iPS cells generated from skin biopsies or blood samples from rare disease patients diagnosed with Kabuki syndrome

  Study EGAS00001001981