From 2D cultures to 3D systems: evolving cancer models at the interface of functional precision medicine and theranostics

Abstract

Advances in patient-derived cancer models are pushing precision oncology by linking functional testing directly to therapeutic decision-making. Traditional two-dimensional (2D) cancer cell culture systems have long served as accessible tools for studying cancer biology and drug responses, but their inability to replicate the complexity of the tumor microenvironment limits their translational value. In recent years, advances in culture and imaging technologies have enabled the development of three-dimensional (3D) cancer models, such as spheroids, organoids, and patient-derived explants, that more accurately represent tumor architecture and behavior in vivo. These models better capture cell–cell and cell–ECM interactions and allow to study immune-tumor dynamics, providing critical insights into therapeutic efficacy and drug resistance of chemotherapies, targeted therapies, and immunotherapies. Notably, the integration of 3D modeling with functional precision medicine approaches, such as ex vivo drug screening using patient-derived samples, has opened new avenues for individualized cancer treatment. Coupling these advanced models with advanced imaging readouts for spatially resolved and functional analysis further transforms them into quantitative theranostic platforms that link biological mechanisms to clinical decision-making. In this review, we explore the evolution from 2D to 3D cancer models, examine their respective advantages and limitations, and highlight their role in advancing functional precision oncology and immuno-theranostics.