9338 results for "cancer rna-seq"

in 35.52 milliseconds.

• 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

• 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

• Human primary and metastatic colorectal cancer (CRC) samples

  Dac EGAC00001002954

• CRMY-Translational Cancer Biology Research Unit DAC

  Dac EGAC00001003199

• Breast Cancer Cell Line Data Access Committee

  Dac EGAC00000000015

• Breast Cancer Cell Line Data Access Committee

  Dac EGAC00001000134

• Cancer Genome Database Data Access Committee (CGDB_DAC)

  Dac EGAC00001000033

• DAC for Single Cell Transcriptomics of Colorectal Cancer

  Dac EGAC00001000550

• Spatial Maps of Prostate Cancer Transcriptomes Data Access

  Dac EGAC00001000913

• Colorectal Cancer Organoids Data Access Committee

  Dac EGAC00001000998

• Data Access Commitee for gastric cancer ascites

  Dac EGAC00001001026

• DAC for MCO colorectal cancer genomics at UNSW

  Dac EGAC00001001122

• Korean Advanced Thyroid Cancer Data Access Commitee

  Dac EGAC00001001151

• DAC for GAMuT Project - Peter MacCallum Cancer Centre

  Dac EGAC00001001154

• 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

• Hyperpolarized 13C MRI in breast cancer DAC

  Dac EGAC00001001438

• Prostate Cancer Biobank Insbruck DAC

  Dac EGAC00001001463

• Metastases of a cancer of unknown primary (CUP)

  Dac EGAC00001001484

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001001500

• Children's Cancer Therapy Development Institute DAC

  Dac EGAC00001001581

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001001906

• 4C Ovarian Cancer Data Access Committee

  Dac EGAC00001001953

• Peter MacCallum Cancer Centre Research Data Access Committee

  Dac EGAC00001001988