Deciphering Aging, Genetic, and Epigenetic Heterogeneity in Cancer Evolution: Toward Personalized Precision Preventative Medicine

Abstract

Background

Cancer's inherent ability to evolve presents significant challenges for its categorization and treatment. Cancer evolution is driven by genetic, epigenetic, and phenotypic diversity influenced by microenvironment changes. Aging plays a crucial role by altering the microenvironment and inducing substantial genetic and epigenetic heterogeneity within an individual's somatic cells even before cancer initiation.

Objectives

This review highlights the clinical significance of epigenetic mechanisms in cancer evolution, focusing on hematopoietic and solid tumors. The review aims to explore opportunities for integrating evolutionary principles and data science into cancer research.

Methods

The review synthesizes recent advancements in omics technologies, single-cell sequencing, and genetic barcoding to elucidate epigenetic mechanisms and aging's role in cancer evolution.

Results

Epigenetic mechanisms' high plasticity generates heritable phenotypic diversity, driving malignant evolution toward poor prognosis. Advances in single-cell sequencing and genetic barcoding enable the precise detection and tracking of biomarkers, allowing early, personalized interventions. Incorporating data science into cancer research has the potential to map, predict, and prevent cancer evolution effectively.

Conclusion

Understanding cancer evolution through novel technologies and data analysis offers a proactive approach to cancer prevention and treatment. By predicting key evolutionary events and leveraging personalized strategies, patient outcomes can be improved, and healthcare burdens reduced, marking a transformative shift in oncology.