12136 results for "cancer rna-seq"

in 14.37 milliseconds.

• Copy number profiling of tissue and plasma samples from high grade serous epithelial ovarian cancer patients

  This dataset includes 289 samples from 46 high grade serous epithelial ovarian cancer patients. Data are from both tissue samples (either primary tumor, or synchronous metastases) and circulating cell-free DNA (cfDNA) of plasma samples taken during therapy and follow-up.

  Dataset EGAD00001006422

• Single-Cell Data from "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer"

  This dataset contains the FASTQ files from the Single-Cell GEx+TCR 10X Genomics data from the study "Spatiotemporal T-cell tracking for personalized T-cell receptor T-cell therapy designs in childhood cancer" (EGAS00001008174)

  Dataset EGAD00001015632

• Raw bulk TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008118

• Single cell TCRseq data fromTIL and non-TIL expanded TRACERx samples in the manuscript Bulk TCRseq from TRACERx samples from 'Subclonal immune evasion in non-small cell lung cancer'

  Immune checkpoint blockade in non-small cell lung cancer (NSCLC) rarely leads to complete tumour remission, suggesting that tumours harbour subpopulations of cancer cells that can escape immune predation. However, while tumours consist of multiple genetically distinct clones, the extent to which separate tumour subclones differ intrinsically in their functional capacity for immune evasion remains largely unexplored. This has been challenging to address due to an inability to isolate and propagate individual tumour subclones from human cancers. Here, we leverage the multi-region TRACERx lung cancer evolution study to generate a patient-derived platform that allows the functional analysis of immune escape at single clone resolution. We generated libraries of >20 separate NSCLC organoid lines per patient by isolating individual (clonal) organoids established from multiple spatially separated tumour regions. Each organoid subline was co-cultured with autologous tumour infiltrating lymphocytes (TIL) to evaluate their capacity to elicit a T cell response. Organoid lines derived from separate tumour regions, or from single clones within individual regions, differ vastly in their capacity to elicit a T cell response, showing the coexistence of intrinsically immune evading (‘cold) and non-evading (‘hot) clones in the same primary tumour. Organoid lines escaping T cell recognition represent genetically and transcriptionally unique subclones with a distinct evolutionary history, showing that evolutionary sculpting of subclonal diversity can have functional consequences for anti-tumour immunity. Notably, the identification of immune-evasive subclones would not have been possible using computational approaches alone, highlighting the unique value of functional co-culture platforms. This patient-derived functional co-culture platform reveals that tumour evolution can give rise to distinct cancer clones with intrinsic differences in immune evasion capacity and provides an approach to prospectively identify, isolate and characterise immune evading subclones from patients with cancer.

  Study EGAS00001008161

• Complex Landscapes of Somatic Rearrangements in Human Breast Cancer Genomes

  We have used massively parallel paired end sequencing strategies to reconstruct the genomic landscape of 24 breast cancer genomes, through the identification and characterization of 2166 somatically acquired genomic rearrangements. These studies have revealed considerable complexity in the patterns of structural variation, identified novel fusion genes and unveiled new insights into the complex structure of amplicons.

  Study EGAS00000000062

• TMD_AMLK_Exome_Study

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 20 Primary Acute Megakaryocytic Leukemia samples and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting 100 exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes

  Study EGAS00001000027

• The Genomic Complexity of Primary Human Prostate Cancer

  Seven primary prostate cancers and their paired normal counterparts were DNA-sequenced on a massively parallel sequencing platform. This approach was taken to investigate the genomes for mutations and genomic alterations that would be undetectable by lower-resolution methods. As result, tumors containing chains of balanced rearrangements that occurred within or adjacent to known cancer genes were discovered.

  Study phs000330

• Variant analysis on FFPE specimen from NSCLC patients (OCAPlus)

  This study assessed the presence of somatic variants via the Oncomine Comprehensive Panel Plus panel (ThermoFisher) for commonly mutated cancer genes and measure tumor mutational burden using next-generation sequencing. It was performed on genomic DNA from FFPE tissue of tumor resections. Mutations were used to draw OncoPrints and to assess TMB in relation with response metrics.

  Study EGAS50000001136

• ER___HER2___PR__breast_Cancer_genome_sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from X triple negative breast cancers and matched normal DNA from the same patients. Three lanes of Illumina GA sequencing will be performed on the resulting X exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000197

• Whole-genome sequencing in gastric cancer (part2)

  we analysis structural variations (SVs) and mutational signatures via whole-genome sequencing of 168 GCs. Our data demonstrates diverse models of complex SVs operative in GC, which lead to high-level amplification of oncogenes. We find varying proportion of tandem-duplications (TDs) among individuals and identify 24 TD hotspots involving well-established cancer genes such as CCND1, ERBB2 and MYC.

  Study EGAS00001006575