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Genome-Wide Analysis of DNA Methylation in Gastrointestinal Cancer
Published on: September 18, 2020
Genomics, microRNA, epigenetics, and proteomics for future diagnosis, treatment and monitoring response in upper GI
Björn L D M Brücher1,2,3,4,5,6, Yan Li7, Philipp Schnabel8
1Theodor-Billroth-Academy®, Munich, Germany. b-bruecher@gmx.de.
Abstract:
One major objective for our evolving understanding in the treatment of cancers will be to address how a combination of diagnosis and treatment strategies can be used to integrate patient and tumor variables with an outcome-oriented approach. Such an approach, in a multimodal therapy setting, could identify those patients (1) who should undergo a defined treatment (personalized therapy) (2) in whom modifications of the multimodal therapy due to observed responses might lead to an improvement of the response and/or prognosis (individualized therapy), (3) who might not benefit from a particular toxic treatment regimen, and (4) who could be identified early on and thereby be spared the morbidity associated with such treatments. These strategies could lead in the direction of precision medicine and there is hope of integrating translational molecular data to improve cancer classifications. In order to achieve these goals, it is necessary to understand the key issues in different aspects of biotechnology to anticipate future directions of personalized and individualized diagnosis and multimodal treatment strategies. Providing an overview of translational data in cancers proved to be a challenge as different methods and techniques used to obtain molecular data are used and studies are based on different tumor entities with different tumor biology and prognoses as well as vastly different therapeutic approaches. The pros and cons of the available methodologies and the potential response data in genomics, microRNA, epigenetics and proteomics with a focus on upper gastrointestinal cancers are considered herein to allow for an understanding of where these technologies stand with respect to cancer diagnosis, prognosis and treatment.
Insights
Integrating patient and tumor data guides personalized cancer therapy. This approach aims to tailor treatments for better outcomes and spare patients unnecessary morbidity.
Area of Science:
- Oncology and Biotechnology
- Translational Cancer Research
Background:
- Cancer treatment is evolving towards integrating patient and tumor variables for outcome-oriented strategies.
- Multimodal therapy settings can enable personalized and individualized treatment approaches.
- Precision medicine aims to improve cancer classification by integrating translational molecular data.
Purpose of the Study:
- To explore key biotechnology issues for personalized and individualized cancer diagnosis and multimodal treatment.
- To provide an overview of translational data in cancer, focusing on upper gastrointestinal cancers.
- To assess the pros and cons of methodologies in genomics, microRNA, epigenetics, and proteomics for cancer care.
Main Methods:
- Review of current biotechnologies and translational data in cancer research.
- Analysis of methodologies for molecular data acquisition (genomics, microRNA, epigenetics, proteomics).
- Focus on upper gastrointestinal cancers to illustrate diagnostic and therapeutic challenges.
Main Results:
- Challenges exist in integrating diverse molecular data due to varied methods and tumor types.
- Genomics, microRNA, epigenetics, and proteomics offer potential for improved cancer diagnosis and prognosis.
- Understanding technological limitations is crucial for advancing personalized cancer treatment.
Conclusions:
- Personalized and individualized cancer therapies require integrating patient and tumor data.
- Biotechnology advancements are key to refining cancer classification and treatment strategies.
- Further research is needed to overcome challenges in translational data integration for precision oncology.
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