11925 results for "cancer rna-seq"

in 14.43 milliseconds.

• RNA_expression_profiling_of_melanoma_patient_derived_xenograft

  Patient-derived xenografts (n=96) were derived from metastatic melanoma patients. RNA expression profiling will be preformed to study 1. HLA-typing and 2. the effect of the tumour microenvironment on tumour growthThis data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Study EGAS00001001537

• Gene expression by RNAseq in bronchial biopsies of asthmatics, asthma in remission and healthy subjects

  The study focus was differential expression in bronchial biopsies between persistent asthma, asthma in remission and healthy controls using RNAseq. There were 184 samples that passed QC. RNA samples were processed using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina, San Diego, CA), using an automated procedure in a Caliper Sciclone NGS Workstation (PerkinElmer, Waltham, MA). In this procedure, all cytoplasmic and mitochondria rRNA was removed (RiboZero Gold kit). The obtained cDNA fragment libraries were loaded in pools of multiple samples unto an Illumina HiSeq2500 sequencer using default parameters for paired-end sequencing (2 × 100 bp). Data are available as 221 pairs of FASTQ-files. Note that several samples are associated with multiple sequence runs.

  Dataset EGAD00001005112

• HG Transcriptome sequencing in the INTERVAL cohort

  We performed bulk RNA-sequencing on peripheral blood collected from 4,732 blood donors recruited as part of the INTERVAL study. Using these data, we mapped gene expression and splicing quantitative trait loci (QTLs). Then, we integrated these data with protein, metabolite and lipid QTLs in the same individuals. The study aimed to identify the shared genetic etiology across transcriptional phenotypes, molecular traits and health outcomes in humans.

  Study EGAS00001003346

• RNAseq Iron-Treated iPSC-derived Microglia

  Iron accumulation in microglia has been observed in Alzheimer’s disease and other neurodegenerative disorders and is thought to contribute to disease progression through various mechanisms including neuroinflammation. To study the interaction between iron accumulation and inflammation, we treated human induced pluripotent stem cell-derived microglia (iPSC-MG) with an increasing concentration of iron, in combination with inflammatory stimuli such as interferon gamma and amyloid β, and performed RNA sequencing.

  Study EGAS00001006112

• Multiomics Characterization of Low-grade Serous Ovarian Carcinoma

  Low-grade serous ovarian carcinoma (LGSOC) is a rare tumor subtype with high case fatality rates. There is a pressing need to develop effective treatments using newly available preclinical models for therapeutic discovery and drug evaluation. In this study, we use multiomics integration of whole exome sequencing, RNA sequencing, and mass spectrometry-based proteomics on fourteen LGSOC patient derived cell lines to elucidate novel biomarkers and therapeutic vulnerabilities.

  Study EGAS00001004724

• Somatic L1 retrotranspositions in normal human cells

  Genomic mutations accumulate in normal cells during lifetime; however, somatic mosaicism generated by mobilization of transposable elements is not well understood. Here, we explored whole-genome sequences of single-cell expanded clones to illustrate the mutational landscape produced by L1. In addition, we analyzed promoter DNA methylation status of retrotransposition-competent L1 and read-through RNA expression profiles to investigate the epigenetic regulation of L1 activity.

  Study EGAS00001006213

• SPECIAL: Dissecting the melanoma ecosystem one cell at the time during immunotherapy

  The aim of this study was to identify potential biomarkers of response to immunotherapy (anti-PD1-based) as well as gain understanding of the biological mechanism of therapy resistance (either intrinsic or acquired) in melanoma patients. Single cell RNA sequencing was performed from pre- and on-treatment (2-3 weeks after immunotherapy) metastatic biopsies from stage III and IV melanoma patients.

  Study EGAS00001006488

• Division of Cancer Genomics, National Cancer Center Research Institute Data Access Committee

  Dac EGAC00001000957

• Transcriptome profiling by array

  Expression profiling by Nanostring cancer immune

  Dataset EGAD00010001274

• Bone metastatic biopsies of breast cancer patients progressing on endocrine therapies.

  Study EGAS00001004268

• Detailed molecular and immune marker profiling of archival prostate cancer samples

  Study EGAS00001004396

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (tumour data)

  Study EGAS00001006096

• Tumour evolvability metrics predict recurrence in advanced localised prostate cancer (normal data)

  Study EGAS00001006098

• HPV-associated Cancer Consortium Data Access Committee

  HPV-associated Cancer Consortium Data Access Committee

  Dac EGAC50000000088

• Integrative pan-cancer genomic and transcriptomic analyses of refractory metastatic cancer

  Study EGAS00001006648

• Stabilising selection causes grossly altered but stable karyotypes in metastatic colorectal cancer

  Study EGAS00001004219

• Cancer Alliance Exome

  Exome sequencing for individualized cancer interpretation

  Dataset EGAD00001006236

• WTCCC case-control study for Breast cancer

  WTCCC genome-wide case-control association study for Breast cancer (BC) using the 1958 British Birth Cohort collection as controls.

  Study EGAS00000000024

• Framome cancer samples

  Cancer samples for neo-open reading frame peptides that comprise the tumor framome are a rich source of neoantigens for cancer immunotherapy.

  Dataset EGAD50000000420

• Transcriptomic characterization of the histopathological growth patterns in breast cancer liver metastases

  Characterizing transcriptommic profiles of the two main histopathological growth patterns in liver metastases in patients with breast cancer.

  Study EGAS50000000225

• Whole exome sequence in EGFR-TKI resistant non-small cell lung cancer

  Whole exome analysis to clear molecular basis and mutation spectrum in EGFR-TKI resistant non-small cell lung cancer

  Study JGAS000102

• Cancer_Cell_Line_Exome_Sequencing_

  Genomic characterisation of a large series of cancer cell lines.

  Study EGAS00001000978

• OCCAMS_Oesophageal Cancer Organoids_1

  ***THIS DATA CAN ONLY BE USED FOR NON-COMMERCIAL CANCER RESEARCH*** Sequencing of organoid cell lines derived from oesophageal tumour sections taken from patients diagnosed with primary oesophageal cancer who underwent tumour resection surgery.

  Dataset EGAD00001001889

• Somatic_mutations_in_twin_breast_cancers

  The aim of this study is to investigate the somatic mutations in twins with BRCA1/2 negative breast cancer with no strong family history.

  Study EGAS00001002379

• The patterns and dynamics of genomic instability in metastatic pancreatic cancer

  Pancreatic cancer is an aggressive malignancy with a five-year mortality of 97–98%, usually due to widespread metastatic disease. Previous studies indicate that this disease has a complex genomic landscape, with frequent copy number changes and point mutations, but genomic rearrangements have not been characterized in detail. Despite the clinical importance of metastasis, there remain fundamental questions about the clonal structures of metastatic tumours, including phylogenetic relationships among metastases, the scale of ongoing parallel evolution in metastatic and primary sites, and how the tumour disseminates. Here we harness advances in DNA sequencing to annotate genomic rearrangements in 13 patients with pancreatic cancer and explore clonal relationships among metastases. We find that pancreatic cancer acquires rearrangements indicative of telomere dysfunction and abnormal cell-cycle control, namely dysregulated G1-to-S-phase transition with intact G2–M checkpoint. These initiate amplification of cancer genes and occur predominantly in early cancer development rather than the later stages of the disease. Genomic instability frequently persists after cancer dissemination, resulting in ongoing, parallel and even convergent evolution among different metastases. We find evidence that there is genetic heterogeneity among metastasis-initiating cells, that seeding metastasis may require driver mutations beyond those required for primary tumours, and that phylogenetic trees across metastases show organ-specific branches. These data attest to the richness of genetic variation in cancer, brought about by the tandem forces of genomic instability and evolutionary selection.

  Study EGAS00000000064