Three new potential ovarian cancer biomarkers detected in human urine with equalizer bead technology.

OBJECTIVE: To examine whether urine can be used to measure specific ovarian cancer proteomic profiles and whether one peak alone or in combination with other peaks or CA125 has the sensitivity and specificity to discriminate between ovarian cancer pelvic mass and benign pelvic mass. METHODS: A total of 209 women were admitted for surgery for pelvic mass at the Gynaecological Department at Rigshospitalet, Copenhagen. Of the women, 156 had benign gynaecological tumors, 13 had borderline tumors and 40 had malignant epithelial ovarian cancer. The prospectively and preoperatively collected urine samples were aliquotted and frozen at -80 degrees until the time of analysis. The urine was fractionated using equalizer bead technology and then analyzed with surface-enhanced laser desorption/ionization time-of-flight mass spectrometry. Biomarkers were purified and identified using combinations of chromatographic techniques and tandem mass spectrometry. RESULTS: Benign and malignant ovarian cancer cases were compared; 21 significantly different peaks (p<0.001) were visualized using Mann-Whitney analysis, ranging in m/z values from 1,500 to 185,000. The three most significant peaks were purified and identified as fibrinogen alpha fragment (m/z=2570.21), collagen alpha 1 (III) fragment (m/z=2707.32) and fibrinogen beta NT fragment (m/z=4425.09). The area under the receiver operator characteristic curve (ROC AUC) value for these three peaks in combination was 0.88, and their ROC AUC value in combination with CA125 was 0.96. CONCLUSION: This result supports the feasibility of using urine as a clinical diagnostic medium, and the ROC AUC value for the three most significant peaks in combination with or without CA125 demonstrates the enhanced prediction performance of combined marker analysis.

Platelets actively sequester angiogenesis regulators.

Clinical trials with antiangiogenic agents have not been able to validate plasma or serum levels of angiogenesis regulators as reliable markers of cancer presence or therapeutic response. We recently reported that platelets contain numerous proteins that regulate angiogenesis. We now show that accumulation of angiogenesis regulators in platelets of animals bearing malignant tumors exceeds significantly their concentration in plasma or serum, as well as their levels in platelets from non-tumor-bearing animals. This process is selective, as platelets do not take up a proportional amount of other plasma proteins (eg, albumin), even though these may be present at higher concentrations. We also find that VEGF-enriched Matrigel pellets implanted subcutaneously into mice or the minute quantities of VEGF secreted by microscopic subcutaneous tumors (0.5-1 mm(3)) result in an elevation of VEGF levels in platelets, without any changes in its plasma levels. The profile of other angiogenesis regulatory proteins (eg, platelet-derived growth factor, basic fibroblast growth factor) sequestered by platelets also reflects the presence of tumors in vivo before they can be macroscopically evident. The ability of platelets to selectively take up angiogenesis regulators in cancer-bearing hosts may have implications for the diagnosis and management of many angiogenesis-related diseases and provide a guide for antiangiogenic therapies.

The distinctive gastric fluid proteome in gastric cancer reveals a multi-biomarker diagnostic profile.

BACKGROUND: Overall gastric cancer survival remains poor mainly because there are no reliable methods for identifying highly curable early stage disease. Multi-protein profiling of gastric fluids, obtained from the anatomic site of pathology, could reveal diagnostic proteomic fingerprints. METHODS: Protein profiles were generated from gastric fluid samples of 19 gastric cancer and 36 benign gastritides patients undergoing elective, clinically-indicated gastroscopy using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry on multiple ProteinChip arrays. Proteomic features were compared by significance analysis of microarray algorithm and two-way hierarchical clustering. A second blinded sample set (24 gastric cancers and 29 clinically benign gastritides) was used for validation. RESULTS: By significance analysyis of microarray, 60 proteomic features were up-regulated and 46 were down-regulated in gastric cancer samples (p < 0.01). Multimarker clustering showed two distinctive proteomic profiles independent of age and ethnicity. Eighteen of 19 cancer samples clustered together (sensitivity 95%) while 27/36 of non-cancer samples clustered in a second group. Nine non-cancer samples that clustered with cancer samples included 5 pre-malignant lesions (1 adenomatous polyp and 4 intestinal metaplasia). Validation using a second sample set showed the sensitivity and specificity to be 88% and 93%, respectively. Positive predictive value of the combined data was 0.80. Selected peptide sequencing identified pepsinogen C and pepsin A activation peptide as significantly down-regulated and alpha-defensin as significantly up-regulated. CONCLUSION: This simple and reproducible multimarker proteomic assay could supplement clinical gastroscopic evaluation of symptomatic patients to enhance diagnostic accuracy for gastric cancer and pre-malignant lesions.

[Proteinchip profiling of tumor markers in lung adenocarcinoma tissue from non-smoking oriental female patients].

BACKGROUND & OBJECTIVE: Although lung cancer is largely attributable to tobacco smoking, more than half of the female patients with adenocarcinoma are non-smokers in Hong Kong. This study dedicated to discover biomarkers for lung adenocarcinoma in non-smoking female patients with high-throughput proteinchip technology. METHODS: Protein profiles were generated from 29 specimens of primary lung cancers with matched adjacent non-cancer tissues using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). RESULTS: Comparing the lung cancer and matched normal lung tissues from the non-smoking female patients, 52 proteins with differential expression were discovered, with a percentage of difference ranging from 60% to 213% for the top ten biomarkers. Comparing the lung cancer tissues from the patients without smoking history and those with smoking history, 84 proteins with differential expression were found. The area under receiver operating characteristic curve (AUC) for the top ten biomarkers ranged from 0.82 to 0.89. Comparing lung cancer tissues from female and male patients, 69 proteins with differential expression were found. The AUC for the top ten biomarkers was ranged from 0.81 to 0.86. CONCLUSION: Using SELDI-TOF-MS, the biomarker candidates that are highly associated with non-smoking female patients with lung adenocarcinoma were filtered.

Proteomic approach to biomarker discovery in cancer tissue from lung adenocarcinoma among nonsmoking Chinese women in Hong Kong.

Half of the female patients with adenocarcinoma in East Asia are never-smokers. Proteomic analysis of tumor tissue may throw important light on the pathogenesis of this interesting subgroup of lung cancer. The cancer and adjacent normal lung tissue were taken from 21 never-smoked adenocarcinoma and profiled using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Fifty-two proteins were significantly discriminatory between tumor and normal lung tissues. Ninety-three proteins were found to have high accuracy in discriminating between adenocarcinoma with or without smoking history. These proteins may yield new insights about the altered pathogenetic pathways of never-smoked lung cancers.

Platelet-associated PF-4 as a biomarker of early tumor growth.

Early tumor detection and intervention are important determinants of survival in patients with cancer. We have recently reported that the "platelet angiogenesis proteome" may be used to detect microscopic tumors in mice. We now present evidence that changes in platelet-associated platelet factor-4 (PF-4) detect malignant growth across a spectrum of human cancers in mice. A deregulated expression of an 8206-Da protein was observed by surfaceenhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-ToF MS) proteomic comparison of platelets from normal and tumor-bearing mice. The differentially expressed protein was identified as PF-4 by tandem mass spectrometry and ProteinChip immunoassay using anti-PF-4 antibody. The platelet-associated PF-4 appeared to be up-regulated in early growth of human liposarcoma, mammary adenocarcinoma, and osteosarcoma. A 120-day follow-up study of liposarcoma revealed a sustained 2-fold or higher increase of platelet-associated PF-4 at 19, 30, and 120 days. In contrast, only an insignificant change of PF-4 was observed in the plasma of mice bearing the different human tumor xenografts, and throughout the 120 days of the liposarcoma study. We conclude that platelet-associated PF-4, but not its plasma counterpart, may represent a potential biomarker of early tumor presence.

Deep proteome profiling of sera from never-smoked lung cancer patients.

Previous studies on the serum proteome are hampered by the huge dynamic range of concentration of different protein species. The use of Equalizer Beads coupled with a combinatorial library of ligands has been shown to allow access to many low-abundance proteins or polypeptides undetectable by classical analytical methods. This study focused on never-smoked lung cancer, which is considered to be more homogeneous and distinct from smoking-related cases both clinically and biologically. Serum samples obtained from 42 never-smoked lung cancer patients (28 patients with active untreated disease and 14 patients with tumor resected) were compared with those from 30 normal control subjects using the pioneering Equalizer Beads technology followed by subsequent analysis by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS). Eighty-five biomarkers were significantly different between lung cancer and normal control. The application of classification algorithms based on significant biomarkers achieved good accuracy of 91.7%, 80% and 87.5% in class-prediction with respect to presence or absence of disease, subsequent development of metastasis and length of survival (longer or shorter than median) respectively. Support vector machine (SVM) performed best overall. We have proved the feasibility and convenience of using the Equalizer Beads technology to study the deep proteome of the sera of lung cancer patients in a rapid and high-throughput fashion, and which enables detection of low abundance polypeptides/proteins biomarkers. Coupling with classification algorithms, the technologies will be clinically useful for diagnosis and prediction of prognosis in lung cancer.

ProteinChip array profiling for identification of disease- and chemotherapy-associated biomarkers of nasopharyngeal carcinoma.

BACKGROUND: We previously used ProteinChip array profiling analysis to discover a serum biomarker associated with nasopharyngeal carcinoma (NPC). In this study, we used the same method to examine other biomarkers associated with NPC and response to chemotherapy (CT) in NPC patients. METHODS: We performed ProteinChip array analysis in 209 serum samples from 66 relapsed patients before and after salvage CT with gemcitabine and cisplatin or etoposide and cisplatin combinations, 11 patients in remission, and 35 healthy individuals. Intensities of the biomarker peaks were correlated with CT response of the patients and other clinical parameters. RESULTS: We discovered 13 candidate biomarkers associated with different clinical parameters. Two biomarkers (2803 and 3953 Da) were significantly increased in patients compared with controls at all stages of disease. Analysis of pre- and post-CT paired serum samples revealed 7 biomarkers correlated with impact of CT. Of these 7 biomarkers, 2 (2509 and 2756 Da) were significantly increased and 5 (7588, 7659, 7765, 7843, and 8372 Da) were significantly decreased post-CT in either 1 or both CT cohorts. Four biomarkers from pre-CT sera were correlated with CT response, with 3 (2950, 13 510, and 14 855 Da) being significantly decreased and 1 (6701 Da) significantly increased in patients who did not respond to CT. Tandem mass spectrometric sequencing and/or immunoaffinity capture assay identified the 3953 Da biomarker as a fragment of interalpha-trypsin inhibitor precursor and 7765 Da biomarker as platelet factor-4. CONCLUSIONS: Treatment-associated serum biomarkers found might serve to triage NPC patients for appropriate CT treatment.

Potential biomarkers found by protein profiling may provide insight for the macrovascular pathogenesis of diabetes mellitus.

Diabetes mellitus (DM) is an alarming threat to health of mankind, yet its pathogenesis is unclear. The purpose of this study was to find potential biomarkers to serve as indicators for the pathogenesis of DM in a time course manner. Based on our previous findings that oxidative stress occurred at week 8, aorta lysate and sera of 102 streptozotocin (STZ)-induced diabetic and 85 control male Sprague-Dawley rats were obtained at the 4th, 8th and 12th week after STZ injection. The protein profiles were studied employing surface-enhanced laser desorption/ionization time-of-flight mass spectrometry technology in attomole sensitivity range. In the aorta, a multiple biomarker panel was discovered at the 4th week. At the 8th week, 4 biomarkers were found, while at the 12th week, 3 biomarkers were identified. In the sera, a triplet of 3 peaks and 2 biomarkers were all discovered to have 100% classification accuracy rate to differentiate the DM and control groups at all time intervals. Besides, 2 biomarkers were also found to have high classification value at week 12. Comparing the aorta and sera from DM and non-DM rats, a bundle of potential biomarkers with significant changes in peak intensities and high classification values were found. Two of the serum biomarkers matched with islet amyloid polypeptide and resistin in the SWISS-PROT knowledgebase. Validation has been conducted using immunoassay kits. These potential biomarkers may provide valuable insight on the pathogenesis of DM and macrovascular complications.

Classification of cancer types by measuring variants of host response proteins using SELDI serum assays.

Protein expression profiling has been increasingly used to discover and characterize biomarkers that can be used for diagnostic, prognostic or therapeutic purposes. Most proteomic studies published to date have identified relatively abundant host response proteins as candidate biomarkers, which are often dismissed because of an apparent lack of specificity. We demonstrate that 2 host response proteins previously identified as candidate markers for early stage ovarian cancer, transthyretin and inter-alpha trypsin inhibitor heavy chain 4 (ITIH4), are posttranslationally modified. These modifications include proteolytic truncation, cysteinylation and glutathionylation. Assays using Surface Enhanced Laser Desorption/Ionization Time of Flight Mass Spectrometry (SELDI-TOF-MS) may provide a means to confer specificity to these proteins because of their ability to detect and quantitate multiple posttranslationally modified forms of these proteins in a single assay. Quantitative measurements of these modifications using chromatographic and antibody-based ProteinChip array assays reveal that these posttranslational modifications occur to different extents in different cancers and that multivariate analysis permits the derivation of algorithms to improve the classification of these cancers. We have termed this process host response protein amplification cascade (HRPAC), since the process of synthesis, posttranslational modification and metabolism of host response proteins amplifies the signal of potentially low-abundant biologically active disease markers such as enzymes.

Simultaneous monitoring of multiple kinase activities by SELDI-TOF mass spectrometry.

Cellular response to the external environment is often controlled by one or more protein kinases. We report a methodology for simultaneously monitoring multiple kinase activities across multiple signal-transduction pathways using ProteinChip Array technology. Based on the addition of specific peptide reporters, kinase activity is detected by the presence of a mass shift of 80 Da (or multiple thereof) corresponding to the addition of one or more phosphate groups. These phosphorylated peptide substrates are then enriched using an immobilized metal affinity capture (IMAC)-Ga array and detected directly by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). SELDI-TOF MS is sensitive, tagless (nonradioactive, nonfluorescent), can be easily multiplexed for the analysis of several different kinases in a single reaction mixture (limited only by the specificity of the kinase for its substrate peptides), and is directly scalable through the use of robotic sample processing. By multiplexing kinase assays, one can dramatically increase the amount of information obtained from rare or volume-limited samples. More important, results reflect closely the complex interrelationships between kinases and show high correlation with in vivo assays.

Identification of serum amyloid a protein as a potentially useful biomarker to monitor relapse of nasopharyngeal cancer by serum proteomic profiling.

PURPOSE: Nasopharyngeal cancer (NPC) is a common cancer in Hong Kong, and relapse can occur frequently. Using protein chip profiling analysis, we aimed to identify serum biomarkers that were useful in the diagnosis of relapse in NPC. EXPERIMENTAL DESIGN: Profiling analysis was performed on 704 sera collected from 42 NPC patients, 39 lung cancer patients, 30 patients with the benign metabolic disorder thyrotoxicosis (TX), and 35 normal individuals (NM). Protein profile in each NPC patient during clinical follow up was correlated with the relapse status. RESULTS: Profiling analysis identified two biomarkers with molecular masses of 11.6 and 11.8 kDa, which were significantly elevated in 22 of 31 (71%) and 21 of 31 (68%) NPC patients, respectively, at the time of relapse (RP) as compared with 11 patients in complete remission (CR; RP versus CR, P = 0.009), 30 TX (RP versus TX, P < 0.001), or 35 NM (RP versus NM, P < 0.001). The markers were also elevated in 16 of 39 (41%) lung cancer patients at initial diagnosis. By tryptic digestion, followed by tandem mass spectrometry fragmentation, the markers were identified as two isoforms of serum amyloid A (SAA) protein. Monitoring the patients longitudinally for SAA level both by protein chip and immunoassay showed a dramatic SAA increase, which correlated with relapse and a drastic fall correlated with response to salvage chemotherapy. Serum SAA findings were compared with those of serum Epstein-Barr virus DNA in three relapsed patients showing a similar correlation with relapse and chemo-response. CONCLUSIONS: SAA could be a useful biomarker to monitor relapse of NPC.

Comprehensive proteomic profiling identifies serum proteomic signatures for detection of hepatocellular carcinoma and its subtypes.

BACKGROUND: Detection of hepatocellular carcinoma (HCC) in patients with chronic liver disease (CLD) is difficult. We investigated the use of comprehensive proteomic profiling of sera to differentiate HCC from CLD. METHODS: Proteomes in sera from 20 CLD patients with alpha-fetoprotein (AFP) <500 microg/L (control group) and 38 HCC patients (disease group) were profiled by anion-exchange fractionation (first dimension), two types (IMAC3 copper and WCX2) of ProteinChip Arrays (second dimension), and time-of-flight mass spectrometry (third dimension). Bioinformatic tests were used to identify tumor-specific proteomic features and to estimate the values of the tumor-specific proteomic features in the diagnosis of HCC. Cross-validation was performed, and we also validated the models with pooled sera from the control and disease groups, serum from a CLD patient with AFP >500 microg/L, and postoperative sera from two HCC patients. RESULTS: Among 2384 common serum proteomic features, 250 were significantly different between the HCC and CLD cases. Two-way hierarchical clustering differentiated HCC and CLD cases. Most HCC cases with advanced disease were clustered together and formed two subgroups that contained significantly more cases with lymph node invasion or distant metastasis. For differentiation of HCC and CLD by an artificial network (ANN), the area under the ROC curve was 0.91 (95% confidence interval, 0.82-1.01; P <0.0005) for all cases and 0.954 (95% confidence interval, 0.881-1.027; P <0.0005) for cases with nondiagnostic serum AFP (<500 microg/L). At a specificity of 90%, the sensitivity was 92%. Both cluster analysis and ANN correctly classified the pooled serum samples, the CLD serum sample with increased AFP, and the HCC patient in complete remission. CONCLUSION: Tumor-specific proteomic signatures may be useful for detection and classification of hepatocellular cancers.

SELDI ProteinChip array in oncoproteomic research.

Research into the causes, early detection and treatment of cancers is a primary focus of the health care industry and proteomic-based methodologies are providing an increasingly important role in addressing these issues. The ProteinChip Array technology forms the basis of a clinical proteomics platform designed to expedite the discovery, validation, and characterization of cancer biomarkers at all stages of cancer progression. Being able to detect cancer progression early in turn allows for the possibility of more effective treatment. This short review serves to introduce the technology by highlighting specific examples related to cancer biomarker discoveries.