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Updated: Jan 27, 2026

Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
Cancer Treatment in the Genomic Era
Gary J Doherty1, Michele Petruzzelli1,2, Emma Beddowes1,3
1Department of Oncology, Addenbrooke's Hospital, Cambridge University Hospitals National Health Service (NHS) Foundation Trust, Cambridge CB2 0QQ, United Kingdom; email: gd231@cam.ac.uk , Richard.Gilbertson@cruk.cam.ac.uk.
Abstract:
The complexity of human cancer underlies its devastating clinical consequences. Drugs designed to target the genetic alterations that drive cancer have improved the outcome for many patients, but not the majority of them. Here, we review the genomic landscape of cancer, how genomic data can provide much more than a sum of its parts, and the approaches developed to identify and validate genomic alterations with potential therapeutic value. We highlight notable successes and pitfalls in predicting the value of potential therapeutic targets and discuss the use of multi-omic data to better understand cancer dependencies and drug sensitivity. We discuss how integrated approaches to collecting, curating, and sharing these large data sets might improve the identification and prioritization of cancer vulnerabilities as well as patient stratification within clinical trials. Finally, we outline how future approaches might improve the efficiency and speed of translating genomic data into clinically effective therapies and how the use of unbiased genome-wide information can identify novel predictive biomarkers that can be either simple or complex.
Insights
Genomic data offers insights beyond individual alterations, improving cancer therapy. Integrated approaches and multi-omic data are key to identifying new drug targets and biomarkers for better patient outcomes.
Area of Science:
- Genomic Medicine
- Cancer Genomics
- Translational Oncology
Background:
- Human cancer's complexity leads to poor clinical outcomes.
- Targeted cancer drugs improve outcomes for some but not most patients.
- Genomic alterations drive cancer, but current therapies have limitations.
Purpose of the Study:
- Review the genomic landscape of cancer.
- Explore how genomic data can be leveraged for therapeutic insights.
- Discuss approaches to identify and validate therapeutic genomic targets.
Main Methods:
- Analysis of genomic and multi-omic cancer data.
- Review of successes and pitfalls in target validation.
- Discussion of integrated data approaches for biomarker discovery.
Main Results:
- Genomic data provides comprehensive insights beyond individual alterations.
- Multi-omic data enhances understanding of cancer dependencies and drug sensitivity.
- Integrated data approaches can prioritize cancer vulnerabilities and stratify patients.
Conclusions:
- Translating genomic data into effective therapies requires integrated approaches.
- Unbiased genome-wide information can identify novel predictive biomarkers.
- Future strategies aim to accelerate the clinical application of genomic insights for cancer treatment.
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