Cancer-associated fibroblasts in radiotherapy: challenges and new opportunities

Abstract

Background

Radiotherapy is one of the most important therapeutic strategies for treating cancer. For decades, studies concerning the outcomes of radiotherapy mainly focused on the biological effects of radiation on tumor cells. Recently, we have increasingly recognized that the complex cellular interactions within the tumor microenvironment (TME) are closely related to treatment outcomes.

Main content

As a critical component of the TME, fibroblasts participate in all stages of cancer progression. Fibroblasts are able to tolerate harsh extracellular environments, which are usually fatal to all other cells. They play pivotal roles in determining the treatment response to chemoradiotherapy. Radiotherapy activates the TME networks by inducing cycling hypoxia, modulating immune reaction, and promoting vascular regeneration, inflammation and fibrosis. While a number of studies claim that radiotherapy affects fibroblasts negatively through growth arrest and cell senescence, others argue that exposure to radiation can induce an activated phenotype in fibroblasts. These cells take an active part in constructing the tumor microenvironment by secreting cytokines and degradative enzymes. Current strategies that aim to inhibit activated fibroblasts mainly focus on four aspects: elimination, normalization, paracrine signaling blockade and extracellular matrix inhibition. This review will describe the direct cellular effects of radiotherapy on fibroblasts and the underlying genetic changes. We will also discuss the impact of fibroblasts on cancer cells during radiotherapy and the potential value of targeting fibroblasts to enhance the clinical outcome of radiotherapy.

Conclusion

This review provides good preliminary data to elucidate the biological roles of CAFs in radiotherapy and the clinical value of targeting CAFs as a supplementary treatment to conventional radiotherapy. Further studies to validate this strategy in more physiological models may be required before clinical trial.