15167 results for "cancer studies using rna-seq"

in 18.80 milliseconds.

• Somatic mutations in facial skin from countries of contrasting skin cancer risk

  The incidence of non-melanoma skin cancer is 17-fold lower in Singapore compared to the UK1, despite Singapore receiving 2-3 times more year-round ultraviolet radiation (UV)2,3. The ageing epidermis of the skin comprises competing somatic mutant clones4,5, from which such cancers develop. We question if differences in keratinocyte skin cancer incidence are reflected in the mutational landscape by comparing ageing facial epidermis from donors of Singapore and the UK. We find UK skin to be a highly competitive, densely mutated landscape with 4-fold greater mutation burden compared to Singaporean skin and differences in clonal selection by country. We disproportionately observe multiple features common to keratinocyte skin cancers6,7,8 in UK skin, such as UV mutagenesis, copy number aberration and hotspot mutations (in particular TP53 R248W). We conclude that keratinocyte skin cancer incidence is reflected in the somatic clones of non-cancerous epidermis. Finally, we re-analyse squamous cell carcinoma exomes from Korea9 to show, even in low incidence populations, carcinogenesis is driven by UV damage.

  Dataset EGAD00001009666

• Somatic mutation and clonal evolution normal breast tissue WGS

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development. . This dataset contains all the data available for this study on 2023-03-09.

  Dataset EGAD00001010123

• Somatic mutation and clonal evolution normal breast tissue TGS (2020-01-15)

  Cancer is a genetic disease caused by an accumulation of mutations, however many of these mutations have been identified in pathologically normal tissue. We aim to use laser-capture microscopy (LCM) to sample individual clones from breast tissue to identify whether cancer-associated mutations appear in this normal tissue, assess the mutational burden present, and identify the mutational processes causing these mutations. We will sample from a wide age range of individuals (<20 to >70 years old) to determine whether these processes differ in pre- and post-menopausal women. We will also be comparing the tissue from healthy individuals (samples from breast reduction surgery) to those at elevated risk of breast cancer (mastectomy from BRCA1/2 patients) and those who have breast cancer (adjacent normal, distal normal, and tumour tissue from mastectomy). This will allow us to determine how these processes are different between these groups of individuals, and gain insight into the earliest stages of tumour development. . This dataset contains all the data available for this study on 2020-01-15.

  Dataset EGAD00001005787

• A prospective multicenter study of plasma ctDNA versus archival tumor tissue to guide FGFR-targeted therapy in metastatic urothelial cancer - Targeted

  Targeted sequencing data related to the publication titled "A prospective multicenter study of plasma ctDNA versus archival tumor tissue to guide FGFR-targeted therapy in metastatic urothelial cancer." FGFR alterations, seen in up to 25% of metastatic urothelial carcinoma, can be exploited with targeted therapy. Here, we perform targeted sequencing of cell-free DNA, archival FFPE, and white blood cell DNA to compare ctDNA versus tissue for FGFR biomarker status and monitor temporal changes to FGFR over the disease course, specifically after progressing on targeted therapy.

  Study EGAS50000001450

• The Institute of Cancer Research - Endocrinology Team

  Dac EGAC00001000532

• CRMY-Translational Cancer Biology Research Unit DAC

  Dac EGAC00001003199

• MD Anderson Cancer Center Data Access Committee

  Dac EGAC00001002802

• Radboud Pediatric Cancer Data Access Committee

  Dac EGAC00001000369

• Genetic predisposition to cancer, University of Tampere

  Dac EGAC00001000488

• Cancer Pharmacogenetics Group at King's College London

  Dac EGAC00001000795

• Colorectal Cancer Organoids Data Access Committee

  Dac EGAC00001000998

• SNP array datas of "Matched" cancer/PNE

  Dac EGAC00001001069

• Korean Advanced Thyroid Cancer Data Access Commitee

  Dac EGAC00001001151

• Gastric Cancer Pan-genome Data Access Commitee

  Dac EGAC00001001211

• DAC for HSTCL study. National Cancer Centre Singapore.

  Dac EGAC00001001302

• DAC for MEITL study. National Cancer Centre Singapore.

  Dac EGAC00001001323

• Prostate Cancer Biobank Insbruck DAC

  Dac EGAC00001001463

• DAC for Phylogenetic reconstruction of breast cancer

  Dac EGAC00001001572

• Children's Cancer Therapy Development Institute DAC

  Dac EGAC00001001581

• DAC for Stuttgart Breast Cancer Cohort

  Dac EGAC00001001693

• Data access committee for lung cancer

  Dac EGAC00001001942

• 4C Ovarian Cancer Data Access Committee

  Dac EGAC00001001953

• Breast Cancer Single-Cell Data Access Committee

  Dac EGAC00001002160

• AA/UTUC Cancer Data Access Commitee

  Dac EGAC00001002162

• Breast Cancer Single-Cell Data Access Committee

  Dac EGAC00001002291