Background

The rapid progress of proteomics over the past years has allowed the discovery of a large number of
potential biomarker candidates to improve early tumor diagnosis and therapeutic response, thus being further
integrated into clinical environment. High grade gliomas represent one of the most aggressive and treatment-resistant
types of human brain cancer, with approximately 9–12 months median survival rate for patients with grade IV glioma
(glioblastoma). Using state-of-the-art proteomics technologies, we have investigated the proteome profile for glioblastoma
patients in order to identify a novel protein biomarker panel that could discriminate glioblastoma patients from controls
and increase diagnostic accuracy.

Results

 In this study, SELDI-ToF MS technology was used to screen potential protein patterns in glioblastoma patients
serum; furthermore, LC-MS/MS technology was applied to identify the candidate biomarkers peaks. Through these
proteomic approaches, three proteins S100A8, S100A9 and CXCL4 were selected as putative biomarkers and confirmed
by ELISA. Next step was to validate the above mentioned molecules as biomarkers through identification of protein
expression by Western blot in tumoral versus peritumoral tissue.

Conclusions

Proteomic technologies have been used to investigate the protein profile of glioblastoma patients and
established several potential diagnostic biomarkers. While it is unlikely for a single biomarker to be highly effective for
glioblastoma diagnostic, our data proposed an alternative and efficient approach by using a novel combination of
multiple biomarkers.