Oncology and mechanics: landmark studies and promising clinical applications

TL;DR

This paper reviews how mechanical phenomena influence cancer progression and treatment, highlighting recent advances in modeling, experimental methods, and personalized therapies that integrate biological and mechanical insights.

Contribution

It provides a comprehensive overview of mechanical findings in cancer and discusses successful workflows for patient-specific therapies based on mechanistic modeling.

Findings

Mechanical signaling impacts cancer progression and treatment.

Integration of mechanical and biological approaches advances modeling and therapy.

Imaging-informed models enable personalized cancer treatment strategies.

Abstract

Clinical management of cancer has continuously evolved for several decades. Biochemical, molecular and genomics approaches have brought and still bring numerous insights into cancerous diseases. It is now accepted that some phenomena, allowed by favorable biological conditions, emerge via mechanical signaling at the cellular scale and via mechanical forces at the macroscale. Mechanical phenomena in cancer have been studied in-depth over the last decades, and their clinical applications are starting to be understood. If numerous models and experimental setups have been proposed, only a few have led to clinical applications. The objective of this contribution is to propose to review a large scope of mechanical findings which have consequences on the clinical management of cancer. This review is mainly addressed to doctoral candidates in mechanics and applied mathematics who are faced with the challenge of the mechanics-based modeling of cancer with the aim of clinical applications. We show that the collaboration of the biological and mechanical approaches has led to promising advances in terms of modeling, experimental design and therapeutic targets. Additionally, a specific focus is brought on imaging-informed mechanics-based models, which we believe can further the development of new therapeutic targets and the advent of personalized medicine. We study in detail several successful workflows on patient-specific targeted therapies based on mechanistic modeling.