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Clinical multi-omics strategies for the effective cancer management
Byong Chul Yoo1, Kyung-Hee Kim2, Sang Myung Woo3
1Biomarker Branch, Research Institute, National Cancer Center, Goyang-si, Gyeonggi-do, Republic of Korea.
Abstract:
Cancer is a global health issue as a multi-factorial complex disease, and early detection and novel therapeutic strategies are required for more effective cancer management. With the development of systemic analytical -omics strategies, the therapeutic approach and study of the molecular mechanisms of carcinogenesis and cancer progression have moved from hypothesis-driven targeted investigations to data-driven untargeted investigations focusing on the integrated diagnosis, treatment, and prevention of cancer in individual patients. Predictive, preventive, and personalized medicine (PPPM) is a promising new approach to reduce the burden of cancer and facilitate more accurate prognosis, diagnosis, as well as effective treatment. Here we review the fundamentals of, and new developments in, -omics technologies, together with the key role of a variety of practical -omics strategies in PPPM for cancer treatment and diagnosis.
Biological Significance:
In this review, a comprehensive and critical overview of the systematic strategy for predictive, preventive, and personalized medicine (PPPM) for cancer disease was described in a view of cancer prognostic prediction, diagnostics, and prevention as well as cancer therapy and drug responses. We have discussed multi-dimensional data obtained from various resources and integration of multisciplinary -omics strategies with computational method which could contribute the more effective PPPM for cancer. This review has provided the novel insights of the current applications of each and combined -omics technologies, which showed their powerful potential for the establishment of PPPM for cancer.
Insights
Predictive, preventive, and personalized medicine (PPPM) leverages -omics technologies for integrated cancer diagnosis and treatment. This approach enhances cancer management through data-driven insights and personalized therapeutic strategies.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Cancer is a complex, multifactorial global health challenge requiring advanced management strategies.
- Traditional hypothesis-driven research is evolving towards data-driven, untargeted investigations in cancer.
- Predictive, Preventive, and Personalized Medicine (PPPM) offers a new paradigm for cancer care.
Purpose of the Study:
- To review the fundamentals and advancements in -omics technologies for cancer.
- To explore the role of -omics strategies in PPPM for cancer diagnosis and treatment.
- To provide insights into the application of integrated -omics data for personalized cancer management.
Main Methods:
- Systematic review of -omics technologies and their applications in PPPM.
- Discussion of multi-dimensional data integration from various sources.
- Integration of multidisciplinary -omics strategies with computational methods.
Main Results:
- -Omics technologies are crucial for data-driven cancer research and personalized medicine.
- Integration of various -omics data provides novel insights for cancer prognosis and treatment.
- Combined -omics strategies show significant potential for establishing effective PPPM in oncology.
Conclusions:
- -Omics technologies are transforming cancer diagnosis, prevention, and treatment.
- PPPM, powered by -omics, enables more accurate prognosis and tailored therapies.
- The integration of computational methods with -omics data is key to advancing PPPM for cancer.
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