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Review
. 2022 Apr 22;14(9):2097.
doi: 10.3390/cancers14092097.

Improving Patients' Life Quality after Radiotherapy Treatment by Predicting Late Toxicities

Ariane Lapierre  1   2 , Laura Bourillon  1 , Marion Larroque  1 , Tiphany Gouveia  1 , Céline Bourgier  1 , Mahmut Ozsahin  3 , André Pèlegrin  1 , David Azria  1 , Muriel Brengues  1
Affiliations
Review

Improving Patients' Life Quality after Radiotherapy Treatment by Predicting Late Toxicities

Ariane Lapierre et al. Cancers (Basel). .

Abstract

Personalized treatment and precision medicine have become the new standard of care in oncology and radiotherapy. Because treatment outcomes have considerably improved over the last few years, permanent side-effects are becoming an increasingly significant issue for cancer survivors. Five to ten percent of patients will develop severe late toxicity after radiotherapy. Identifying these patients before treatment start would allow for treatment adaptation to minimize definitive side effects that could impair their long-term quality of life. Over the last decades, several tests and biomarkers have been developed to identify these patients. However, out of these, only the Radiation-Induced Lymphocyte Apoptosis (RILA) assay has been prospectively validated in multi-center cohorts. This test, based on a simple blood draught, has been shown to be correlated with late radiation-induced toxicity in breast, prostate, cervical and head and neck cancer. It could therefore greatly improve decision making in precision radiation oncology. This literature review summarizes the development and bases of this assay, as well as its clinical results and compares its results to the other available assays.

Keywords: biomarkers; late toxicities prediction; personalized treatment; radiotherapy.

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Conflict of interest statement

D. Azria declares NovaGray, stock options. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Figures

Figure 1
Figure 1
RILA assay procedure (adapted from Brengues et al. [36]).
Figure 2
Figure 2
Main hypotheses for RILA molecular rationale.
See this image and copyright information in PMC

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