Objective: This study aims to evaluate changes in proteomic salivary profile of patients with oral mucositis after adjuvant cancer treatments. Materials and Methods: Samples were collected from patients after adjuvant cancer therapies, and were analyzed by means of SELDI/TOF. Patients were separated in two groups: patients affected by mucositis (MUCOSITIS) and patient without mucositis (NO MUCOSITIS). All patients were divided in function of the anticancer treatment: patients who had radiotherapy (MUCOSITIS RADIO), had not radiotherapy (MUCOSITIS NO RADIO), had chemotherapy (MUCOSITIS CHEMO), and those who had not chemotherapy (MUCOSITIS NO CHEMO). Statistical evaluation PCA (Principal Component Analysis) was conducted with the software BIO-RAD Data Manager™ (Version 3.5). Results: We found the increased peaks of 3443, 3487, and 4135 m/z in MUCOSITIS group, while 6237 m/z was reduced. These same peaks would the same modifications in MUCOSITIS RADIO, while in MUCOSITIS CHEMIO are increased 3443 and 6237 m/z but 3487, 4135 m/z are reduced. These data were confirmed by the PCA. Conclusion: Anticancer therapy influenced the level expression of many salivary biomarkers in mucositis with a good significance. Therefore, 3443, 3487, 4135, and 6237 m/z are good biomarker candidates of oral mucositis.

Objective: This study aims to evaluate changes in proteomic salivary profile of patients with oral mucositis after adjuvant cancer treatments. Materials and Methods: Samples were collected from patients after adjuvant cancer therapies, and were analyzed by means of SELDI/TOF. Patients were separated in two groups: patients affected by mucositis (MUCOSITIS) and patient without mucositis (NO MUCOSITIS). All patients were divided in function of the anticancer treatment: patients who had radiotherapy (MUCOSITIS RADIO), had not radiotherapy (MUCOSITIS NO RADIO), had chemotherapy (MUCOSITIS CHEMO), and those who had not chemotherapy (MUCOSITIS NO CHEMO). Statistical evaluation PCA (Principal Component Analysis) was conducted with the software BIO-RAD Data Manager™ (Version 3.5). Results: We found the increased peaks of 3443, 3487, and 4135 m/z in MUCOSITIS group, while 6237 m/z was reduced. These same peaks would the same modifications in MUCOSITIS RADIO, while in MUCOSITIS CHEMIO are increased 3443 and 6237 m/z but 3487, 4135 m/z are reduced. These data were confirmed by the PCA. Conclusion: Anticancer therapy influenced the level expression of many salivary biomarkers in mucositis with a good significance. Therefore, 3443, 3487, 4135, and 6237 m/z are good biomarker candidates of oral mucositis.

Expression of salivary biomarkers in patients with oral mucositis: Evaluation by SELDI-TOF/MS

COLELLA, Giuseppe;
2016

Abstract

Objective: This study aims to evaluate changes in proteomic salivary profile of patients with oral mucositis after adjuvant cancer treatments. Materials and Methods: Samples were collected from patients after adjuvant cancer therapies, and were analyzed by means of SELDI/TOF. Patients were separated in two groups: patients affected by mucositis (MUCOSITIS) and patient without mucositis (NO MUCOSITIS). All patients were divided in function of the anticancer treatment: patients who had radiotherapy (MUCOSITIS RADIO), had not radiotherapy (MUCOSITIS NO RADIO), had chemotherapy (MUCOSITIS CHEMO), and those who had not chemotherapy (MUCOSITIS NO CHEMO). Statistical evaluation PCA (Principal Component Analysis) was conducted with the software BIO-RAD Data Manager™ (Version 3.5). Results: We found the increased peaks of 3443, 3487, and 4135 m/z in MUCOSITIS group, while 6237 m/z was reduced. These same peaks would the same modifications in MUCOSITIS RADIO, while in MUCOSITIS CHEMIO are increased 3443 and 6237 m/z but 3487, 4135 m/z are reduced. These data were confirmed by the PCA. Conclusion: Anticancer therapy influenced the level expression of many salivary biomarkers in mucositis with a good significance. Therefore, 3443, 3487, 4135, and 6237 m/z are good biomarker candidates of oral mucositis.
2016
Objective: This study aims to evaluate changes in proteomic salivary profile of patients with oral mucositis after adjuvant cancer treatments. Materials and Methods: Samples were collected from patients after adjuvant cancer therapies, and were analyzed by means of SELDI/TOF. Patients were separated in two groups: patients affected by mucositis (MUCOSITIS) and patient without mucositis (NO MUCOSITIS). All patients were divided in function of the anticancer treatment: patients who had radiotherapy (MUCOSITIS RADIO), had not radiotherapy (MUCOSITIS NO RADIO), had chemotherapy (MUCOSITIS CHEMO), and those who had not chemotherapy (MUCOSITIS NO CHEMO). Statistical evaluation PCA (Principal Component Analysis) was conducted with the software BIO-RAD Data Manager™ (Version 3.5). Results: We found the increased peaks of 3443, 3487, and 4135 m/z in MUCOSITIS group, while 6237 m/z was reduced. These same peaks would the same modifications in MUCOSITIS RADIO, while in MUCOSITIS CHEMIO are increased 3443 and 6237 m/z but 3487, 4135 m/z are reduced. These data were confirmed by the PCA. Conclusion: Anticancer therapy influenced the level expression of many salivary biomarkers in mucositis with a good significance. Therefore, 3443, 3487, 4135, and 6237 m/z are good biomarker candidates of oral mucositis.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11591/366437
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