15028 results for "cancer studies using rna-seq"

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• Single cell BCR sequencing

  Paired-end fastq files of 22 AML and 2 normal bone marrow samples were generated using 10x Genomics single cell BCR sequencing following manufacturer's protocol (CG000086 User Guide RevG) for chemistry version 1.0 and targeting 10000 cells per sample. Libraries were sequenced using Illumina NovaSeq 6000 using recommended cycling parameters.

  Dataset EGAD00001007673

• Single cell TCR sequencing

  Paired-end fastq files of 22 AML and 2 normal bone marrow samples were generated using 10x Genomics single cell TCR sequencing following manufacturer's protocol (CG000086 User Guide RevG) for chemistry version 1.0 and targeting 10000 cells per sample. Libraries were sequenced using Illumina NovaSeq 6000 using recommended cycling parameters.

  Dataset EGAD00001007674

• Mutation analysis of core biopsies from localized breast cancer patients

  Targeted next-generation sequencing (NGS) of 93 frequently mutated genes in breast cancer using the QIAseq Human Breast Cancer Targeted Panel (QIAGEN), which uses digital sequencing by incorporating unique molecular barcodes (UMI).

  Dataset EGAD00001008396

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Lung cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Study EGAS00001004447

• ctDNA monitoring using patient-specific sequencing and integration of variant reads - Breast cohort

  Circulating tumor-derived DNA (ctDNA) can be used to monitor cancer dynamics noninvasively. Detection of ctDNA can be challenging in patients with low-volume or residual disease, where plasma contains very few tumor-derived DNA fragments. We show that sensitivity for ctDNA detection in plasma can be improved by analyzing hundreds to thousands of mutations that are first identified by tumor genotyping. We describe the INtegration of VAriant Reads (INVAR) pipeline, which combines custom error-suppression methods and signal-enrichment approaches based on biological features of ctDNA. With this approach, the detection limit in each sample can be estimated independently based on the number of informative reads sequenced across multiple patient-specific loci. We applied INVAR to custom hybrid-capture sequencing data from 176 plasma samples from 105 patients with melanoma, lung, renal, glioma, and breast cancer across both early and advanced disease. By integrating signal across a median of >105 informative reads, ctDNA was routinely quantified to 1 mutant molecule per 100,000, and in some cases with high tumor mutation burden and/or plasma input material, to individual parts per million. This resulted in median Area Under the Curve (AUC) values of 0.98 in advanced cancers, and 0.80 in early stage and challenging settings for ctDNA detection. We generalized this method to whole-exome and whole-genome sequencing, showing that the INVAR may be applied without requiring personalized sequencing panels, so long as a tumor mutation list is available. As tumor sequencing becomes increasingly performed, such methods for personalized cancer monitoring may enhance the sensitivity of cancer liquid biopsies.

  Study EGAS00001004446

• RNA bulk sequencing on organoids from different organs with or without TS2/16 antibody

  RNA bulk sequencing on organoids from colon, ileum, jejunum, duodenum and pancreas duct with or without TS2/16 antibody. Also there is difference in extracellular matrix used, BME vs Colagen.

  Dataset EGAD50000001606

• RNA sequencing of control OM cells exposed to traffic-related air pollutants

  Total RNA sequencing of olfactory mucosa (OM) cells derived from cognitively healthy individuals exposed to traffic-related ultrafine particles (UFPs) for 24h and 72h in submerged cultures. The UFPs used for exposures were: A0, A20 and Euro6. Exposures were compared to the corresponding blank samples.

  Dataset EGAD00001011317

• Longitudinal evaluation of serum microRNAs as biomarkers for neuroblastoma burden and therapeutic p53 reactivation

  Small RNA sequencing data (TruSeq small RNA library preparation kit v2) from serum samples and tumor tissue of orthotopically injected mice (SH-SY5Y cell line) and unengrafted mice, treated with idasanutlin, temsirolimus and vehicle control.

  Dataset EGAD00001009625

• A molecular atlas of the human postmenopausal fallopian tube and ovary from single-cell RNA

  This datasets contains raw sequencing fastq data of 17 samples from 7 donors of single cell RNA using10x genome technology of human postmenopausal fallopian tube and ovary tissues.

  Dataset EGAD00001010076

• RNA sequencing of Human Organoid Lines

  The study will use RNA sequencing to aid in benchmarking different culture conditions in a set of genetically annotated human organoid lines. The data will be used to assess whether there are any clonal differences introduced when culturing these lines in different conditions.

  Dataset EGAD00001007971

• RNA sequencing of T-LGLL patients

  RNA sequencing was performed on 15 T-LGLL patients and five control samples. The raw data is provided as fastq files.

  Dataset EGAD00001008408

• Seminal Plasma RNA DAC

  Dac EGAC00001002111

• BLUEPRINT Bisulfite-seq (CNAG)

  Bisulfite-Seq

  Study EGAS00001000418

• H3K27ac ChIP-seq in primary inflammatory (TPP) macrophages

  We investigated an intergenic haplotype on chr21q22, linked to five different inflammatory diseases, and identified the molecular mechanism by which the risk haplotype increases expression of the causal gene, ETS2. This mechanism was predicted to alter enhancer activity at the disease-associated locus. We therefore performed H3K27ac ChIP-seq in inflammatory macrophages from minor and major allele homozygotes at the causal allele and investigated the effect on enhancer activity. In doing so, we mechanistically delineated how the risk haplotype increases expression of ETS2.

  Study EGAS00001007562