Variabilities of serum proteomic spectra in patients with nasopharyngeal carcinoma before and after radiotherapy
10.3760/cma.j.issn.0254-5098.2010.04.004
- VernacularTitle:鼻咽癌放疗前后血清蛋白质谱的变异性研究
- Author:
Xiaodong ZHU
;
Fang SU
;
Song QU
;
Qi WANG
;
Li LI
;
Wei ZHANG
- Publication Type:Journal Article
- Keywords:
Nasopharyngeal carcinoma;
Surface-enhanced laser desorption ionization time-of flight-mass spectrometry;
Protein biomarker
- From:
Chinese Journal of Radiological Medicine and Protection
2010;30(4):391-394
- CountryChina
- Language:Chinese
-
Abstract:
Objective To study the changes of serum proteomic spectra in patients with nasopharyngeal carcinoma(NPC) before and after treatment in order to detect the protein biomarkers.Methods Proteomic spectra from serum of 50 NPC patients before radiotherapy,25 NPC patients who achieved complete remission(CR) after radiotherapy, and 40 persons from normal control subjects were analyzed by CM-10 protein chip and surface-enhanced laser desorption ionization time of flight mass spectrometry. Results Expressed proteins in serum were screened by analysis of the proteomic spectra of pre-radiotherapy patients and normal individuals. 4 kinds of proteins with the relative molecular masses of 2931,4098,5343,13 766 made up markers pattern which was able to classify the patients and normal individuals. The sensitivity and specificity results were 90.0% and 90. 0% , respectively. The twenty differential expression protein peaks of patients before and after radiotherapy were obviously different. The relative molecular masses of 2931 , 4182, 4688 and 13 766 were up-regulated in untreated NPC, while were close to the normal levels in CR group. Two other protein peaks of 4098 and 5343 were down-regulated in untreated NPC group, which were close to normal levels in CR group. Conclusions The expressions of protein levels are different before and after radiotherapy in NPC patients. Protein signatures of NPC may be screened using SELDI-TOF-MS. Those signatures may be helpful in assessing the minimal residual disease and predicting the treatment efficacy.
