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Discovery of Driver Genes in Colorectal HT29-derived Cancer Stem-Like Tumorspheres
Published on: July 22, 2020
Molecular Taxonomy and Tumourigenesis of Colorectal Cancer
S Biswas1, D Holyoake2, T S Maughan2
1Welcome Trust Centre for Human Genetics, Oxford, UK.
Abstract:
Over the last 5 years there has been a surge in interest in the molecular classification of colorectal cancer. The effect of molecular subtyping on current treatment decisions is limited to avoidance of adjuvant 5-fluorouracil chemotherapy in stage II microsatellite unstable-high disease and avoidance of epidermal growth factor receptor-targeted antibodies in extended RAS mutant tumours. The emergence of specific novel combination therapy for the BRAF-mutant cohort and of the microsatellite unstable-high cohort as a responsive group to immune checkpoint inhibition shows the growing importance of a clinically relevant molecular taxonomy. Clinical trials such as the Medical Research Council FOCUS4 trial using biomarkers to select patients for specific therapies are currently open and testing such approaches. The integration of mutation, gene expression and pathological analyses is refining our understanding of the biological subtypes within colorectal cancer. Sharing of data sets of parallel sequencing and gene expression of thousands of cancers among independent groups has allowed the description of disease subsets and the need for a validated consensus classification has become apparent. This biological understanding of the disease is a key step forward in developing a stratified approach to patient management. The discovery of stratifiers that predict a response to existing and emerging therapies will enable better use of these treatments. Improved scientific understanding of the biological characteristics of poorly responsive subgroups will facilitate the design of novel biologically rational combinations. Novel treatment regimens, including the combination of new drugs with radiation, and the discovery and validation of their associated predictive biomarkers will gradually lead to improved outcomes from therapy.
Insights
Molecular classification of colorectal cancer is advancing treatment. Identifying specific molecular subtypes, like microsatellite unstable-high and BRAF-mutant, guides targeted therapies and improves patient outcomes.
Area of Science:
- Oncology
- Molecular Biology
- Genomics
Background:
- Colorectal cancer (CRC) research shows a growing interest in molecular classification.
- Current treatment decisions are minimally impacted by molecular subtypes, except for specific cases like stage II microsatellite unstable-high (MSI-H) and extended RAS mutant tumors.
- Emerging therapies show promise for specific molecular cohorts, highlighting the need for a robust molecular taxonomy.
Purpose of the Study:
- To explore the impact of molecular subtyping on colorectal cancer treatment.
- To emphasize the importance of a clinically relevant molecular classification for personalized medicine.
- To discuss the integration of multi-omics data for refining CRC subtypes and guiding therapeutic strategies.
Main Methods:
- Analysis of mutation, gene expression, and pathological data.
- Leveraging large-scale, shared datasets from parallel sequencing and gene expression studies.
- Review of ongoing clinical trials (e.g., FOCUS4) that utilize biomarkers for patient selection.
Main Results:
- Molecular subtyping currently influences treatment by guiding avoidance of certain chemotherapies and targeted agents.
- Specific molecular subtypes, such as BRAF-mutant and MSI-H CRC, are emerging as responsive to novel combination therapies and immune checkpoint inhibition.
- Integration of multi-omics data is refining the understanding of CRC biological subtypes, necessitating a consensus classification.
Conclusions:
- A deeper biological understanding of colorectal cancer subtypes is crucial for developing stratified patient management approaches.
- Discovery of predictive biomarkers for existing and novel therapies will optimize treatment efficacy.
- Improved understanding of poorly responsive subgroups will facilitate the design of novel, biologically rational combination therapies and improve patient outcomes.
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