3292 results for "ovarian cancer"

in 5.56 milliseconds.

• Single-cell RNA sequencing of metastatic colorectal cancer organoids treated with cetuximab

  Single-cell RNA sequencing was performed on metastatic colorectal cancer (mCRC) organoids derived from a cetuximab-sensitive patient-derived xenograft (PDX) model. The objective of this analysis was to investigate, at single-cell resolution, the transcriptional changes previously identified in bulk RNA-seq analyses of PDX models exposed to anti-EGFR therapeutic pressure.

  Study EGAS50000001460

• Identification of genetic mutations characteristic for recurrence and metastasis of colon and rectal cancer.

  We collected the cancerous tissues of the primary and recurrence tumors from the same patient with recurrent / metastatic colorectal cancer, and the purpose of this study is to find the characteristics of recurrent / metastatic colorectal cancers by carrying out a "molecular profiling", mainly the exome sequence analysis of these tissues.

  Study JGAS000091

• Whole exome sequencing from early stage non-small cell lung cancer patients at MDACC

  The purpose of the study is to evaluate the mutational landscape and tumor mutational burden in tumor from patients with early stage non-small cell lung cancer. Mutational landscape was compared to the T cell repertoire to determine the relationship between somatic mutations and T cell response in early-stage NSCLC.

  Study EGAS00001004026

• PMF_Exome_Study

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 50 Primary Myelofibrosis Myeloproliferative Disease 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 EGAS00001000175

• Oesophageal_Adenocarcinoma_Organoid_Hi_C

  Hi-C Sequencing of 6 patient derived organoid cell models. Each model was derived from a piece of patient tumour taken following surgical rescetion of the tumour. All model derivations took place with the CGaP facility in Sanger. This Hi-C data will be combined with other sequencing data in order to generate accurate reference cancer genomes.

  Study EGAS00001003122

• Integrative_Oncogenomics_of_Multiple_Myeloma

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from Multiple Myeloma patient DNA and matched normal DNA from the same patients. Two lanes of Illumina GA sequencing will be performed on the resulting exome libraries and mapped to build 37 of the human reference genome to facilitate the identification of novel cancer genes.

  Study EGAS00001000036

• ADCC_Exome_Sequencing

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

  Study EGAS00001000193

• Osteosarcoma_Exome_Sequencing

  Agilent whole exome hybridisation capture will be performed on genomic DNA derived from 50 osteosarcoma cancers 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 EGAS00001000163

• Triple_Negative_Breast_Cancer_Whole_Genome_Validations

  We propose to definitively characterise the somatic genetics of Triple negative breast cancer through generation of comprehensive catalogues of somatic mutations in 500 cases by high coverage genome sequencing coupled with integrated transcriptomic and methylation analyses. This study will use a bespoke bait set to pulldown regions of interest found in whole genome sequencing to validate mutations found.

  Study EGAS00001000426

• The WID-BC-index identifies women with primary poor prognostic breast cancer based on DNA methylation in cervical samples

  A surrogate marker based on the epigenome that captures these components in easily accessible epithelial tissue could potentially identify women at risk. The WID-BC-index identifies women with breast cancer based on a DNA methylation signature derived from cervical smear samples.

  Study EGAS00001005055