title: [Identification of predictive biomarkers to radiotherapy outcome through proteomics approaches].
abstract: The success of radiotherapy mainly depends on the total administered dose. This dose must be homogenously delivered onto the tumor and must preserve the surrounding healthy tissue. However, several patients are hypersensitive to ionizing radiations and may develop important radiation-induced early and late side effects. The prediction of these side effects remains currently impossible, involving to limit the given dose with the risk to decrease the therapeutic benefit for patients. Therefore, one of the major challenges in radiobiology is to accurately predict tumour radioresistance and to determine normal tissue radiosensitivity to tailor treatment. Several studies have been carried out and different predictive assays have been described in this field. However, none of them showed significant results for clinical use. For several years, many technological advances in proteomic fields have been performed in order to identify new biomarkers. After a brief description of the main characteristics of tumor radioresistance and normal tissue radiosensitivity, we will develop in this review the different approaches proposed so far to identify predictive tools of radiotherapy outcome. We will then analyze in detail how proteomic studies can improve the understanding of mechanisms associated with radiosensitivity of healthy tissue and radioresistance of tumor cells and how they could highlight new predictive biomarkers in radiobiology.
authors.affiliation: Université Montpellier I, 5, boulevard Henri-IV, CS 19044, 34967 Montpellier cedex 2, France.
authors.forename: J
authors.initials: J
authors.lastname: Lacombe
authors.forename: A
authors.initials: A
authors.lastname: Mange
authors.forename: D
authors.initials: D
authors.lastname: Azria
authors.forename: J
authors.initials: J
authors.lastname: Solassol
mesh_terms: D017209:Apoptosis; D015415:Biomarkers; D001943:Breast Neoplasms / Q000737:chemistry / Q000235:genetics / Q000532:radiotherapy; D045744:Cell Line, Tumor / Q000528:radiation effects; D015179:Colorectal Neoplasms / Q000737:chemistry / Q000235:genetics / Q000628:therapy; D004249:DNA Damage; D004260:DNA Repair; D004273:DNA, Neoplasm / Q000378:metabolism / Q000528:radiation effects; D005260:Female; D006019:Glycolysis; D006258:Head and Neck Neoplasms / Q000737:chemistry / Q000235:genetics / Q000532:radiotherapy; D006801:Humans; D008297:Male; D008954:Models, Biological; D009363:Neoplasm Proteins / Q000032:analysis* / Q000235:genetics; D009369:Neoplasms / Q000235:genetics / Q000378:metabolism / Q000532:radiotherapy*; D018384:Oxidative Stress; D011237:Predictive Value of Tests; D011379:Prognosis; D011471:Prostatic Neoplasms / Q000737:chemistry / Q000235:genetics / Q000532:radiotherapy; D040901:Proteomics; D011836:Radiation Tolerance / Q000235:genetics; D016896:Treatment Outcome
chemical_list: D015415:Biomarkers; D004273:DNA, Neoplasm; D009363:Neoplasm Proteins