Translational study for stereotactic body radiotherapy against non-small cell lung cancer, including oligometastases, considering cancer stem-like cells enable predicting clinical outcome from in vitro data

Background: Curative effects of stereotactic body radiotherapy (SBRT) for non-small cell lung cancer (NSCLC) have been evaluated using various biophysical models. Because such model parameters are empirically determined based on clinical experience, there is a large gap between in vitro and clinical studies. In this study, considering the heterogeneous cell population, we performed a translational study to realize the possible linkage based on a modeling approach.Methods: We modeled cell-killing and tumor control probability (TCP) considering two populations: progeny and cancer stem-like cells. The model parameters were determined from in vitro survival data of A549 and EBC-1 cells. Based on the cellular parameters, we predicted TCP and compared it with the corresponding clinical data from 553 patients collected at Hirosaki University Hospital.Results: Using an all-in-one developed model, the so-called integrated microdosimetric-kinetic (IMK) model, we successfully reproduced both in vitro survival after acute irradiation and the 3-year TCP with various fractionation schemes (6-10 Gy per fraction). From the conventional prediction without considering cancer stem cells (CSCs), this study revealed that radioresistant CSCs play a key role in the linkage between in vitro and clinical outcomes. Conclusions: This modeling study provides a possible generalized biophysical model that enables precise estimation of SBRT worldwide.(c) 2022 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 181 (2023) 109444

Automated summary

By modeling the cells and tumor, this study reveals the close relationship between the efficacy of radiotherapy for non-small cell lung cancer and cancer stem cells. Using the integrated microdosimetric-kinetic model, the survival rate in vitro and clinical outcomes were successfully predicted, providing a precise estimation model of radiotherapy worldwide.