Perico Davide, Mauri Pierluigi
Institute of Biomedical Technologies-National Research Council ITB-CNR, Via Fratelli Cervi 93, 20054 Milan, Italy.
Institute of Endotypes in Oncology, Metabolism and Immunology "G.Salvatore"-National Research Council IEOMI-CNR, Via Sergio Pansini 5, 80131 Napoli, Italy.
Proteomes. 2025 Jun 16;13(2):25. doi: 10.3390/proteomes13020025.
Radiotherapy resistance represents a critical aspect of cancer treatment, and molecular characterization is needed to explore the pathways and mechanisms involved. DNA repair, hypoxia, metabolic reprogramming, apoptosis, tumor microenvironment modulation, and activation of cancer stem cells are the primary mechanisms that regulate radioresistance, and understanding their complex interactions is essential for planning the correct therapeutic strategy. Proteomics has emerged as a key approach in precision medicine to study tumor heterogeneity and treatment response in cancer patients. The integration of mass spectrometry-based techniques with bioinformatics has enabled high-throughput, quantitative analyses to identify biomarkers, pathways, and new potential therapeutic targets. This review highlights recent advances in proteomic technologies and their application in identifying biomarkers predictive of radiosensitivity and radioresistance in different tumors, including head and neck, breast, lung, and prostate cancers. Sample variability, data interpretation, and the translation of findings into clinical practice remain challenging elements of proteomics. However, technological advancements support its application in a wide range of topics, allowing a comprehensive approach to radiobiology, which helps overcome radiation resistance. Ultimately, incorporating proteomics into the radiotherapy workflow offers significant potential for enhancing treatment efficacy, minimizing toxicity, and guiding precision oncology strategies.
放射抗性是癌症治疗的一个关键方面,需要进行分子表征以探索其中涉及的途径和机制。DNA修复、缺氧、代谢重编程、凋亡、肿瘤微环境调节以及癌症干细胞的激活是调节放射抗性的主要机制,了解它们之间的复杂相互作用对于规划正确的治疗策略至关重要。蛋白质组学已成为精准医学中研究癌症患者肿瘤异质性和治疗反应的关键方法。基于质谱的技术与生物信息学的整合使得高通量、定量分析能够识别生物标志物、途径和新的潜在治疗靶点。本综述重点介绍了蛋白质组学技术的最新进展及其在识别不同肿瘤(包括头颈癌、乳腺癌、肺癌和前列腺癌)放射敏感性和放射抗性预测生物标志物方面的应用。样本变异性、数据解释以及将研究结果转化为临床实践仍然是蛋白质组学面临的挑战。然而,技术进步支持其在广泛主题中的应用,从而实现对放射生物学的全面研究,有助于克服放射抗性。最终,将蛋白质组学纳入放射治疗工作流程在提高治疗效果、最小化毒性以及指导精准肿瘤学策略方面具有巨大潜力。