Additive effect of the AZGP1, PIP, S100A8 and UBE2C molecular biomarkers improves outcome prediction in breast carcinoma

Ubiquitin-conjugating enzyme UBE2C is highly expressed in breast microcalcification lesions

Ubiquitin-conjugating enzyme 2C (UBE2C) contributes to ubiquitin-mediated proteasome degradation of cell cycle progression in breast cancer. Microcalcification (MC) is the most common mammographic feature of early breast cancer. In this study, we evaluated whether UBE2C could be a tumor marker of early breast cancer with MC found on screening mammography. UBE2C protein and mRNA expression were measured in breast core biopsy pairs of MC and adjacent non-MC breast tissue from each subject. Immunohistochemistry revealed UBE2C positivity in 69.4% of MC samples and 77.6% negativity in non-MC samples (p<0.0001). On RT-qPCR, 56.1% of malignant MC lesion samples showed high mRNA level of UBE2C and 80% of benign MC lesion samples showed a low level of UBE2C (p = 0.1766). We investigated the carcinogenic role of UBE2C in MCF-7 breast cancer cells with UBE2C knockdown; UBE2C knockdown downregulated cell proliferation and activated the cellular apoptosis pathway to inhibit cell colony formation. Furthermore, UBE2C expression was associated with that of carcinogenic genes human epidermal growth factor receptor type 2 (HER2), cellular c-Ki-ras2 proto-oncogene (KRAS), vascular endothelial growth factor (VEGF), CXC chemokine receptor 4 (CXCR4), C-C motif chemokine 5 (CCL5), neural precursor cell expressed, developmentally downregulated 9 (NEDD9) and Ras homolog family member C (RhoC). UBE2C may be a marker for diagnosis of nonpalpable breast lesions but not benign or malignant tumors in mammography core biopsies. Suppression of UBE2C may be a potential therapy target in breast cancer.

Potential serum biomarkers for glioblastoma diagnostic assessed by proteomic approaches

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.