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Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models

Cancer heterogeneity represents the main issue for defining an effective treatment in clinical practice, and the scientific community is progressively moving towards the development of more personalized therapeutic regimens. Radiotherapy (RT) remains a fundamental therapeutic treatment used for many...

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Autores principales: Savoca, Gaetano, Calvaruso, Marco, Minafra, Luigi, Bravatà, Valentina, Cammarata, Francesco Paolo, Iacoviello, Giuseppina, Abbate, Boris, Evangelista, Giovanna, Spada, Massimiliano, Forte, Giusi Irma, Russo, Giorgio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712665/
https://www.ncbi.nlm.nih.gov/pubmed/33080870
http://dx.doi.org/10.3390/jpm10040177
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author Savoca, Gaetano
Calvaruso, Marco
Minafra, Luigi
Bravatà, Valentina
Cammarata, Francesco Paolo
Iacoviello, Giuseppina
Abbate, Boris
Evangelista, Giovanna
Spada, Massimiliano
Forte, Giusi Irma
Russo, Giorgio
author_facet Savoca, Gaetano
Calvaruso, Marco
Minafra, Luigi
Bravatà, Valentina
Cammarata, Francesco Paolo
Iacoviello, Giuseppina
Abbate, Boris
Evangelista, Giovanna
Spada, Massimiliano
Forte, Giusi Irma
Russo, Giorgio
author_sort Savoca, Gaetano
collection PubMed
description Cancer heterogeneity represents the main issue for defining an effective treatment in clinical practice, and the scientific community is progressively moving towards the development of more personalized therapeutic regimens. Radiotherapy (RT) remains a fundamental therapeutic treatment used for many neoplastic diseases, including breast cancer (BC), where high variability at the clinical and molecular level is known. The aim of this work is to apply the generalized linear quadratic (LQ) model to customize the radiant treatment plan for BC, by extracting some characteristic parameters of intrinsic radiosensitivity that are not generic, but may be exclusive for each cell type. We tested the validity of the generalized LQ model and analyzed the local disease-free survival rate (LSR) for breast RT treatment by using four BC cell cultures (both primary and immortalized), irradiated with clinical X-ray beams. BC cells were chosen on the basis of their receptor profiles, in order to simulate a differential response to RT between triple negative breast and luminal adenocarcinomas. The MCF10A breast epithelial cell line was utilized as a healthy control. We show that an RT plan setup based only on α and β values could be limiting and misleading. Indeed, two other parameters, the doubling time and the clonogens number, are important to finely predict the tumor response to treatment. Our findings could be tested at a preclinical level to confirm their application as a variant of the classical LQ model, to create a more personalized approach for RT planning.
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spelling pubmed-77126652020-12-04 Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models Savoca, Gaetano Calvaruso, Marco Minafra, Luigi Bravatà, Valentina Cammarata, Francesco Paolo Iacoviello, Giuseppina Abbate, Boris Evangelista, Giovanna Spada, Massimiliano Forte, Giusi Irma Russo, Giorgio J Pers Med Article Cancer heterogeneity represents the main issue for defining an effective treatment in clinical practice, and the scientific community is progressively moving towards the development of more personalized therapeutic regimens. Radiotherapy (RT) remains a fundamental therapeutic treatment used for many neoplastic diseases, including breast cancer (BC), where high variability at the clinical and molecular level is known. The aim of this work is to apply the generalized linear quadratic (LQ) model to customize the radiant treatment plan for BC, by extracting some characteristic parameters of intrinsic radiosensitivity that are not generic, but may be exclusive for each cell type. We tested the validity of the generalized LQ model and analyzed the local disease-free survival rate (LSR) for breast RT treatment by using four BC cell cultures (both primary and immortalized), irradiated with clinical X-ray beams. BC cells were chosen on the basis of their receptor profiles, in order to simulate a differential response to RT between triple negative breast and luminal adenocarcinomas. The MCF10A breast epithelial cell line was utilized as a healthy control. We show that an RT plan setup based only on α and β values could be limiting and misleading. Indeed, two other parameters, the doubling time and the clonogens number, are important to finely predict the tumor response to treatment. Our findings could be tested at a preclinical level to confirm their application as a variant of the classical LQ model, to create a more personalized approach for RT planning. MDPI 2020-10-17 /pmc/articles/PMC7712665/ /pubmed/33080870 http://dx.doi.org/10.3390/jpm10040177 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Savoca, Gaetano
Calvaruso, Marco
Minafra, Luigi
Bravatà, Valentina
Cammarata, Francesco Paolo
Iacoviello, Giuseppina
Abbate, Boris
Evangelista, Giovanna
Spada, Massimiliano
Forte, Giusi Irma
Russo, Giorgio
Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models
title Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models
title_full Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models
title_fullStr Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models
title_full_unstemmed Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models
title_short Local Disease-Free Survival Rate (LSR) Application to Personalize Radiation Therapy Treatments in Breast Cancer Models
title_sort local disease-free survival rate (lsr) application to personalize radiation therapy treatments in breast cancer models
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7712665/
https://www.ncbi.nlm.nih.gov/pubmed/33080870
http://dx.doi.org/10.3390/jpm10040177
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