11989 results for "cancer rna-seq"

in 44.20 milliseconds.

• Combined gene expression and digital pathology identifies molecular mediators of T cell exclusion and immune suppression in ovarian cancer

  Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what determines the spatial distribution of T cells in the tumour microenvironment is not well understood. Coupling digital pathology and transcriptome analysis on a large ovarian tumour cohort, we develop a machine learning approach to molecularly classify and characterize tumour-immune phenotypes. Our study identifies two important hallmarks characterizing T cell excluded tumours: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFb and activated stroma. Furthermore, we identify TGFb as a key mediator of T cell exclusion. TGFb reduces MHC-I expression in ovarian cancer cells in vitro; TGFb also activates fibroblasts and induced extracellular matrix (ECM) production as a potential physical barrier to hinder T cell infiltration. Our findings indicate that targeting TGFb may represent a promising strategy to overcome T cell exclusion and improve clinical benefits of cancer immunotherapy.

  Study EGAS00001003487

• Early on-treatment changes in circulating tumor DNA fraction and response to enzalutamide or abiraterone in metastatic castration-resistant prostate cancer

  On-treatment circulating tumor DNA (ctDNA) quantification is touted as a surrogate biomarker for understanding metastatic cancer response to systemic therapy, but there is relatively little supporting data from standardized patient cohorts. Here, in a prospective observational cohort, we demonstrate that 4-week on-treatment changes in plasma ctDNA levels can accurately identify metastatic castration-resistant prostate cancer that will progress within 6 months of initiating first-line abiraterone or enzalutamide treatment. On-treatment ctDNA measurements outperformed existing clinical variables for predicting disease response and were also closely associated with differential overall survival. Although optimal timing of blood collections and thresholds for ctDNA detection will require further testing, our data highlights the potential for sequential ctDNA measurements to provide an early and reliable read-out for therapy response. The high accuracy of this information suggests that ctDNA could be useful for guiding clinical trials of therapy changes in initially non-responsive metastatic cancers.

  Study EGAS00001006856

• Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA

  These data relate to Abbosh et al 2023 'Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA'. Some patients were included in this work that were excluded from the other TRACERx 421 papers (Frankell et al and Al-bakir et al) often due to exclusion criteria in the TRACERx clinical trial. Reasons include partial contamination with C>A artefact mutational signature (CRUK0480 ,0490) which were included for ctDNA detection analyses using high confidence clonal mutations but not clonality analyses, incomplete resection at primary surgery (CRUK0291, 0234, 0230, 0387, 0622) and a concurrent oesophageal second primary cancer (CRUK0498). The primary tissue exome sequencing for these patients that were used in this study are included in this repository. Deep targeted sequencing of (median 200) tumour specific mutations in plasma for 1069 samples from 198 TRACERx patients are also included. Additional details related to these patients and samples can be found in the supplementary or data repositories from Frankell et al and Abbosh et al.

  Study EGAS00001006923

• RNAseq of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007300

• WES of Colorectal cancer organoid-stroma biobank cohort

  In colorectal cancers (CRC) the tumor microenvironment plays a key role for prognosis and therapy efficacy. Patient-derived tumor organoids (PDTOs) show enormous potential for preclinical testing, however, in purely epithelial cultures features including the ‘consensus molecular subtypes’ (CMS) are largely eradicated. To better reflect cell heterogeneity, we established the CRC organoid-stroma biobank of matched PDTOs and cancer-associated fibroblasts (CAFs) from 30 patients. Context-specific phenotyping showed that xenotransplantation or co-culture with CAFs restores the individual transcriptomic status and instructs subtype-specific stromal gene expression. Furthermore, co-culture exposed CMS4-specific resistance to Gefitinib and SN-38 and revealed prognostic gene expression signatures. Chemogenomic library screening identified patient- and therapy-dependent mechanisms of stromal resistance including MET as common target. Our results demonstrate that CRC phenotypes are encrypted in the cancer epithelium in a plastic fashion that strongly depends on the context. Consequently, CAFs are essential for faithful representation of molecular subtypes and therapy responses ex vivo.

  Study EGAS00001007301

• Sensitive and Frequent Identification of High Avidity Neo-epitope Specific CD8 + T-cells in Immunotherapy-naïve Ovarian Cancer

  Immunotherapy directed against private tumor neo-antigens derived from non-synonymous somatic mutations is a promising strategy of personalized cancer immunotherapy. However, feasibility in low mutational load tumor types remains unknown. Comprehensive and deep analysis of circulating and tumor-infiltrating lymphocytes (TILs) for neo-epitope specific CD8 + T cells allowed prompt identification of oligoclonal and polyfunctional such cells from most immunotherapy-naïve patients with advanced epithelial ovarian cancer studied. Neo-epitope recognition was discordant between circulating T cells and TILs, and was more likely to be found among TILs, which displayed higher functionalavidity and unique TCRs with higher predicted affinity than their blood counterparts. Our results imply that identification of neo-epitope specific CD8 + T cells is achievable even in tumors with relatively low number of somatic mutations, and neo-epitope validation in TILs extends opportunities for mutanome-based personalized immunotherapies to such tumors.

  Study EGAS00001002803

• DAC - Comparison of sequencing assays for sensitive detection of circulating tumour DNA in stage IA-IV breast cancer

  Dac EGAC00001002549

• Data Access Committee for data from EGAS00001002864: Genome analysis of oesophageal cancer and Barretts oesophagus

  Dac EGAC00001000863

• Detection of ctDNA in Plasma of Patients with Clinically Localised Prostate Cancer is Associated with Rapid Disease Progression

  Dac EGAC00001001718

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

  Dac EGAC00001002007

• Whole-exome sequencing of 47 microsatellites stable Early-onset sporadic rectal cancer (EOSRC) tumors and corresponding normal samples.

  Dac EGAC00001002502

• DAC for Clonal somatic copy number altered driver events inform drug sensitivity in high-grade serous ovarian cancer

  Dac EGAC00001002644

• Tumor dataset - Case

  tumor-based gene expression from breast cancer cases

  Dataset EGAD00010001064

• Molecular Classification of Lymph Node Metastases Subtypes Predict for Survival in Head and Neck Cancer

  Study EGAS00001003233

• Polyomavirus-positive Merkel cell carcinoma derived from a trichoblastoma suggests an epithelial origin of Merkel cell carcinoma

  Study EGAS00001003784

• Molecular profiling reclassifies adult astroblastoma into known and clinically distinct tumor entities with frequent MAPK pathway alterations

  Study EGAS00001003798

• Genetic characterization of a Unique Neuroendocrine Transdifferentiation Prostate Circulating Tumor Cell - Derived eXplant (CDX) Model

  Study EGAS00001004272

• Molecular analysis of CRC in patients with Primary Sclerosing Cholangitis (PSC) and Inflammatory Bowel Disease (IBD)

  Study EGAS00001004497

• DNA methylation and Panel sequencing for pancreatic neuroendocrine carcinomas (PanNECs) and pancreatic neuroendocrine tumors (PanNETs)

  Study EGAS00001005731

• Overexpression of the miR-17-92 cluster in colorectal adenoma organoids induces a carcinoma-like genotype

  Study EGAS00001005949

• Mechanism of action and resistance to Trastuzumab Deruxtecan in patients with metastatic breast cancer: the DAISY trial

  Study EGAS00001006905

• Enhancer profiling to identify identifies epigenetic markers of endocrine resistance in metastatic castration resistant prostate cancer patients

  Study EGAS00001006161

• DAC for "Establishment and characterization of circulating tumor cells-derived organoids from metastatic breast cancer patients."

  Dac EGAC00001003514

• Methylation data for Genomic landscapes of endometrioid and mucinous ovarian cancers and morphologically similar tumor types

  Study EGAS00001008175

• The INFORM Precision Medicine Study for High-Risk Pediatric Malignancies

  Study EGAS00001005112