Lisa van Den Dreist- FRAME AWARD: Development of a gene expression bioinformatics pipeline to identify driver mutations of colorectal cancer

Project: Research

Project Details

Description

Competitively awarded FRAME summer studentship with stipend (£2,500)

Layman's description

Colon cancer is one of the leading cancer types worldwide, with only 53% of diagnosed patients surviving a colon cancer diagnosis past the 10 year survival rate and 16,571 patients succumbing to this disease in the UK alone (source: Cancer Research UK). In recent years with significant advancements in gene sequencing technologies and the increasing numbers of biobanks from patient tumour biopsies, there has been a significant rise in the amount of clinical information available within the public domain. These datasets provide a significant wealth of information for researchers to examine patterns of gene expression and their role in disease. A key advantage of using these datasets is replacing the need for animal testing and refining their use in studying patterns of disease. If we can use information contained in patient samples, this will reduce the need for exploratory studies in animals which may ultimately prove to not translate to humans. In this project we aim to understand significant mutations occurring in colorectal cancer and how they contribute to disease severity and patient outcomes. The data generated from this internship project will be used to plan future experimental studies in cancer cells exploring the evidence for the role of these mutations. This project will ultimately pave the path for the development of new diagnostics and treatments for patients with colon cancer. Any pipelines developed through this internship will be shared with the wider cancer research community to increase the use of patient datasets and reduce the use of animals during early discovery studies in cancer research.
StatusFinished
Effective start/end date22/06/2129/08/21

Keywords

  • Cancer
  • Colon
  • Drug discovery

Fingerprint

Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.