Abstract
Purpose: :
Breast cancer is the most common diagnosed cancer type in women. Despite of an increased survival, many patients die from metastatic relapse. The early detection of breast cancer is a key factor for a successful treatment. Many biomarkers for breast cancer have been investigated, but they still do not provide useful clinical specificity and sensitivity. The current routine diagnosis of breast cancer is mammography with following biopsy, which is an invasive and displeasing method. In this study we used tear fluid from 50 patients with breast cancer and 50 healthy controls to examine the protein profiles in both groups.
Methods: :
Protein profile patterns in tear fluid of breast cancer patients (CA) and healthy donors of the same age (CTRL) were investigated with Surface-Enhanced Laser Desorption-Ionisation Time-Of-Flight Mass Spectrometry (SELDI-TOF-MS) on cationic exchanger (CM-10) and reverse-phase surface (H50) protein chip surfaces. After the enrichment of samples, the identification of significant biomarkers was performed with Matrix Assisted Laser Desorption Ionisation (MALDI-TOF-TOF)-MS. The obtained data were analyzed by multivariate statistical techniques and artificial neural networks.
Results: :
A panel of 20 significant biomarkers has been detected in both groups with 6 elevated proteins in CA. The specificity and sensitivity of the discrimination between CA and CTRL of approximately 70% were achieved with the Area Under Curve (AUC) of 0.75. In preview studies, one of increased peaks in CA was identified as Proline-rich protein 4 (PRP4).
Conclusions: :
We could show that SELDI-TOF-MS can serve as a potential screening method for detection of breast cancer. The use of tear fluid is a non-invasive and simple method to obtain stable protein profiles. The form of identified PRP4 has been associated with nasopharyngeal carcinoma (NCAPP4). Its role remains unclear but it could have a protective function in the eye such as modulation of the microflora. Further subsequent de novo screening of the discovered biomarkers can help to understand cancer emergence and development and can possibly facilitate the early diagnosis of breast cancer.
Keywords: proteomics • oncology • discrimination