Serum protein fingerprinting coupled with a pattern-matching algorithm distinguishes prostate cancer from benign prostate hyperplasia and healthy men.

The prostate-specific antigen test has been a major factor in increasing awareness and better patient management of prostate cancer (PCA), but its lack of specificity limits its use in diagnosis and makes for poor early detection of PCA. The objective of our studies is to identify better biomarkers for early detection of PCA using protein profiling technologies that can simultaneously resolve and analyze multiple proteins. Evaluating multiple proteins will be essential to establishing signature proteomic patterns that distinguish cancer from noncancer as well as identify all genetic subtypes of the cancer and their biological activity. In this study, we used a protein biochip surface enhanced laser desorption/ionization mass spectrometry approach coupled with an artificial intelligence learning algorithm to differentiate PCA from noncancer cohorts. Surface enhanced laser desorption/ionization mass spectrometry protein profiles of serum from 167 PCA patients, 77 patients with benign prostate hyperplasia, and 82 age-matched unaffected healthy men were used to train and develop a decision tree classification algorithm that used a nine-protein mass pattern that correctly classified 96% of the samples. A blinded test set, separated from the training set by a stratified random sampling before the analysis, was used to determine the sensitivity and specificity of the classification system. A sensitivity of 83%, a specificity of 97%, and a positive predictive value of 96% for the study population and 91% for the general population were obtained when comparing the PCA versus noncancer (benign prostate hyperplasia/healthy men) groups. This high-throughput proteomic classification system will provide a highly accurate and innovative approach for the early detection/diagnosis of PCA.

Imaging mass spectrometry of a specific fragment of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase kinase 2 discriminates cancer from uninvolved prostate tissue.

PURPOSE: Histopathology is the standard approach for tissue diagnostics and centerpiece of pathology. Although the current system provides prognostic information, there is need for molecular markers that enhance diagnosis and better predict clinical prognosis. The ability to localize disease-specific molecular changes in biopsy tissue would help improve critical pathology decision making. Direct profiling of proteins from tissue using matrix-assisted laser desorption/ionization imaging mass spectrometry has the potential to supplement morphology with underlying molecular detail. EXPERIMENTAL DESIGN: A discovery set of 11 prostate cancer (PCa)-containing and 10 benign prostate tissue sections was evaluated for protein expression differences. A separate validation set of 54 tissue sections (23 PCa and 31 benign) was used to verify the results. Cryosectioning was done to yield tissue sections analyzed by a pathologist to determine tissue morphology and mirror sections for imaging mass spectrometry. Spectra were acquired and the intensity of signals was plotted as a function of the location within the tissue. RESULTS: An expression profile was found that discriminates between PCa and normal tissue. The overexpression of a single ion at m/z 4,355 was able to discriminate cancer from uninvolved tissue. Tandem mass spectrometry identified this marker as a fragment of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase kinase 2 (MEKK2). The ability of MEKK2 to discriminate tumor from normal cells was orthogonally confirmed. CONCLUSIONS: This study highlights the potential of this approach to uncover molecular detail that can be correlated with pathology decision making. In addition, the identification of MEKK2 shows the ability to discover proteins of relevance to PCa biology.

Glycomic characterization of prostate-specific antigen and prostatic acid phosphatase in prostate cancer and benign disease seminal plasma fluids.

Prostate-specific antigen (PSA) and prostatic acid phosphatase (PAP) are glycoproteins secreted by prostate epithelial cells, and have a long clinical history of use as serum biomarkers of prostate cancers. These two proteins are present at significantly higher concentrations in seminal plasma, making this proximal fluid of the prostate a good source for purifying enough protein for characterization of prostate disease associated changes in glycan structures. With the use of seminal fluid samples representative of normal control, benign prostatic disease and prostate cancers, PAP and PSA were enriched by thiophilic absorption chromatography. Released N-linked glycan constituents from both proteins were analyzed by a combination of normal phase HPLC and MALDI-TOF spectrometry. For PSA, 40 putative glycoforms were determined, and 21 glycoforms were determined for PAP. PAP glycans were further analyzed with a hybrid triple quadrupole/linear ion trap mass spectrometer to assign specific glycoform classes to each of the three N-linked sites. The glycans identified in these studies will allow for more defined targeting of prostate disease-specific changes for PAP, PSA and other secreted prostatic glycoproteins.

Clinical collection and protein properties of expressed prostatic secretions as a source for biomarkers of prostatic disease.

The prostate gland secretes many proteins in a prostatic fluid that combines with seminal vesicle derived fluids to promote sperm activation and function. Proximal fluids of the prostate that can be collected clinically are seminal plasma and expressed-prostatic secretion (EPS) fluids. EPS represents the fluid being secreted by the prostate following a digital rectal prostate massage, which in turn can be collected in voided urine post-exam. This collection is not disruptive to a standard urological exam, and it can be repeatedly collected from men across all prostatic disease states. A direct EPS fluid can also be collected under anesthesia prior to prostatectomy. While multiple genetic assays for prostate cancer detection are being developed for the shed epithelial cell fraction of EPS urines, the remaining fluid that contains many prostate-derived proteins has been minimally characterized. Approaches to optimization and standardization of EPS collection consistent with current urological exam and surgical practices are described, and initial proteomic and glycomic evaluations of the of EPS fluid are summarized for prostate specific antigen and prostatic acid phosphatase. Continued characterization of the prostate specific protein components of EPS urine combined with optimization of clinical collection procedures should facilitate discovery of new biomarkers for prostate cancer.