Inchingolo Angelo Michele, Malcangi Giuseppina, Piras Fabio, Palmieri Giulia, Settanni Vito, Riccaldo Lilla, Morolla Roberta, Buongiorno Silvio, de Ruvo Elisabetta, Inchingolo Alessio Danilo, Mancini Antonio, Inchingolo Francesco, Dipalma Gianna, Benagiano Stefania, Tartaglia Gianluca Martino, Patano Assunta
Department of Interdisciplinary Medicine, University of Bari "Aldo Moro", 70121 Bari, Italy.
Department of Biomedical, Surgical and Dental Sciences, School of Dentistry, University of Milan, 20122 Milan, Italy.
J Pers Med. 2023 May 31;13(6):933. doi: 10.3390/jpm13060933.
Precision medicine using highly precise technologies and big data has produced personalised medicine with rapid and reliable diagnoses and targeted therapies. The most recent studies have directed precision medicine into the study of tumours. The application of precision medicine in the oral microbiota can be used both in the field of prevention and treatment in the strictly dental field. This article aims to evaluate the interaction between microbiota and oral cancer and the presence of biomarkers as risk predictors.
A literature search of PubMed, Scopus, and Web of Science was performed analysing the various interactions between microorganisms, biomarkers, and oral cancer.
After screening processes, 21 articles were selected for qualitative analysis.
The correlation between oral diseases/cancers and changes in the microbiota explains the increasing utility of precision medicine in enhancing diagnosis and adapting treatment on the individual components of the microbiota. Diagnosing and treating oral diseases and cancers through precision medicine gives, as well as economic advantages to the health care system, predictable and rapid management of the patient.
使用高精度技术和大数据的精准医学已经产生了具有快速可靠诊断和靶向治疗的个性化医学。最近的研究已将精准医学引入肿瘤研究领域。精准医学在口腔微生物群中的应用可用于严格意义上的牙科预防和治疗领域。本文旨在评估微生物群与口腔癌之间的相互作用以及作为风险预测指标的生物标志物的存在情况。
对PubMed、Scopus和科学网进行文献检索,分析微生物、生物标志物与口腔癌之间的各种相互作用。
经过筛选过程,选择了21篇文章进行定性分析。
口腔疾病/癌症与微生物群变化之间的相关性解释了精准医学在加强诊断和根据微生物群的个体组成调整治疗方面日益增加的效用。通过精准医学诊断和治疗口腔疾病和癌症,除了给医疗保健系统带来经济优势外,还能对患者进行可预测且快速的管理。