Ilda Patrícia Ribeiro1,2, Luísa Esteves1, Sandra Isabel Anjo3, Francisco Marques2,4,5, Leonor Barroso6, Bruno Manadas3, Isabel Marques Carreira1,2,7, Joana Barbosa Melo8,2,7. 1. Cytogenetics and Genomics Laboratory, Faculty of Medicine, University of Coimbra, Coimbra, Portugal. 2. iCBR-CIMAGO - Center of Investigation on Environment, Genetics and Oncobiology - Faculty of Medicine, University of Coimbra, Coimbra, Portugal. 3. CNC - Center for Neuroscience and Cell Biology, University of Coimbra, Coimbra, Portugal. 4. Stomatology Unit, Coimbra Hospital and University Centre, CHUC, EPE, Coimbra, Portugal. 5. Department of Dentistry, Faculty of Medicine, University of Coimbra, Coimbra, Portugal. 6. Maxillofacial Surgery Department, Coimbra Hospital and University Centre, CHUC, EPE, Coimbra, Portugal. 7. CNC.IBILI, Group of Aging and Brain Diseases: Advanced Diagnosis and Biomarkers, Coimbra, Portugal. 8. Cytogenetics and Genomics Laboratory, Faculty of Medicine, University of Coimbra, Coimbra, Portugal citogenetica@fmed.uc.pt mmelo@fmed.uc.pt.
Abstract
BACKGROUND/AIM: Head and neck squamous cell carcinoma (HNSCC) presents high morbidity, an overall poor prognosis and survival, and a compromised quality of life of the survivors. Early tumor detection, prediction of its behavior and prognosis as well as the development of novel therapeutic strategies are urgently needed for a more successful HNSCC management. MATERIALS AND METHODS: In this study, a proteomics analysis of HNSCC tumor and non-tumor samples was performed and a model to predict the risk of recurrence and metastasis development was built. RESULTS: This predictive model presented good accuracy (>80%) and comprises as variables the tumor staging along with DHB12, HMGB3 and COBA1 proteins. Differences at the intensity levels of these proteins were correlated with the development of metastasis and recurrence as well as with patient's survival. CONCLUSION: The translation of proteomic predictive models to routine clinical practice may contribute to a more precise and individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The capability of generalization of this proteomic model to predict the recurrence and metastases development should be evaluated and validated in other HNSCC populations. Copyright
BACKGROUND/AIM: Head and neck squamous cell carcinoma (HNSCC) presents high morbidity, an overall poor prognosis and survival, and a compromised quality of life of the survivors. Early tumor detection, prediction of its behavior and prognosis as well as the development of novel therapeutic strategies are urgently needed for a more successful HNSCC management. MATERIALS AND METHODS: In this study, a proteomics analysis of HNSCC tumor and non-tumor samples was performed and a model to predict the risk of recurrence and metastasis development was built. RESULTS: This predictive model presented good accuracy (>80%) and comprises as variables the tumor staging along with DHB12, HMGB3 and COBA1 proteins. Differences at the intensity levels of these proteins were correlated with the development of metastasis and recurrence as well as with patient's survival. CONCLUSION: The translation of proteomic predictive models to routine clinical practice may contribute to a more precise and individualized clinical management of the HNSCC patients, reducing recurrences and improving patients' quality of life. The capability of generalization of this proteomic model to predict the recurrence and metastases development should be evaluated and validated in other HNSCC populations. Copyright
Authors: D Song; G Liu; V Luu-The; D Zhao; L Wang; H Zhang; G Xueling; S Li; L Désy; F Labrie; G Pelletier Journal: J Steroid Biochem Mol Biol Date: 2006-08-22 Impact factor: 4.292
Authors: Anca Maria Cimpean; Raluca Amalia Balica; Ioan Caius Doros; Nicolae Constantin Balica; Pusa Nela Gaje; Ramona Amina Popovici; Marius Raica Journal: Cancer Genomics Proteomics Date: 2016 Jan-Feb Impact factor: 4.069