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The receptor tyrosine kinase HER2 is an oncogene amplified in invasive breast cancer and its overexpression in mammary epithelial cell lines is a strong determinant of a tumorigenic phenotype. Accordingly, HER2-overexpressing mammary tumors are commonly indicative of a poor prognosis in patients. Several quantitative proteomic studies have employed two-dimensional gel electrophoresis in combination with tandem mass spectrometry, which provides only limited information about the molecular mechanisms underlying HER2/neu signaling. In the present study, we used a SILAC-based approach to compare the proteomic profile of normal breast epithelial cells with that of Her2/neu-overexpressing mammary epithelial cells, isolated from primary mammary tumors arising in MMTV-Her2/neu transgenic mice. We identified 23 proteins with relevant annotated functions in breast cancer, showing a substantial differential expression. This included overexpression of creatine kinase, retinol-binding protein 1, thymosin beta 4 and tumor protein D52, which correlated with the tumorigenic phenotype of Her2-overexpressing cells. The differential expression pattern of two genes, gelsolin and retinol binding protein 1, was further validated in normal and tumor tissues. Finally, an in silico analysis of published cancer microarray datasets revealed a 23-gene signature which can be used to predict the probability of metastasis-free survival in breast cancer patients.

Purpose The pathological state of the prostate may be reflected by serum proteome in a man. We hypothesized that biomarkers are present in preoperative serum, which may be used to predict the probability of biochemical recurrence following radical prostatectomy. Materials and Methods Mass spectrometry analysis was used to compare 52 men who experienced biochemical recurrence with 52 who remained biochemical recurrence-free for approximately 5 years after radical retropubic prostatectomy. A total of 30 matched pairs of recurrent and nonrecurrent serum samples were randomly selected as a training set for biomarker discovery and model development. Selected mass spectrometry peaks were combined with pre-radical retropubic prostatectomy prostate specific antigen in a multivariate algorithm to predict recurrence. The algorithm was evaluated using the remaining 22 recurrent and 22 nonrecurrent subjects as test samples. Protein identities of the selected mass spectrometry peaks were investigated. Results Two serum biomarkers for recurrence, P1 and P2, were combined with preoperative prostate specific antigen to predict biochemical recurrence. The ROC AUC for prostate specific antigen and the predicted outcome was 0.606 and 0.691 in the testing data, respectively. Using a single cutoff the samples were divided into 2 groups that were predictive of biochemical recurrence (p = 0.026). In contrast, preoperative prostate specific antigen did not differ between recurrent and nonrecurrent cases (Wilcoxon matched pairs test p = 0.07). The protein identity of P1 was determined to be a truncated form of C4a (C4a des-Arg). Preliminary data indicated that P2 was an N-terminal fragment of protein C inhibitor. Conclusions In the current study population, which was matched on Gleason score and TNM staging, pre-radical retropubic prostatectomy prostate specific antigen retained no independent power to predict recurrence. However, by adding 2 proteomic biomarkers to preoperative prostate specific antigen the combined model demonstrated statistically significant value for predicting prostate cancer recurrence in men who underwent radical retropubic prostatectomy.