Assessment of diagnostic utility of multivariate diagnostic models in differential diagnosis of ovarian tumors.

INTRODUCTION: Ovarian cancer (OC) diagnosis remains a clinical challenge due to lack of early symptoms and insufficient accuracy of the available diagnostic methods. The purpose of this study was to determine whether osteopontin could be useful in differential diagnosis of ovarian tumors. MATERIAL AND METHODS: Serum samples from 92 patients qualified for surgical treatment due to ovarian mass were divided into 2 groups according to the histopathological result: OC including borderline ovarian tumors (n = 39) and benign ovarian tumors (BOTs) (n = 53). CA125, HE4 and osteopontin concentrations were measured in all patients. Areas under the receiver operating characteristic curves (AUC of ROC) were used to compare the discriminative ability of the univariate and multivariate diagnostic models. RESULTS: The addition of osteopontin to ROMA significantly improved the diagnostic performance of the test in 3 of the 5 analyses: 1) in the OC vs BOT group (from AUC of 0.955 to 0.975), 2) in premenopausal women OC vs BOT (from AUC of 0.828 to 0.892) and 3) in the FIGO I-II stage OC vs BOT (from AUC of 0.865 to 0.895). It did not alter the diagnostic performance of multifactor tests in the group of postmenopausal women nor in OC FIGO III-IV stage group. Osteopontin was also the best single marker to differentiate between early stage OC and BOTs (AUC of 0.863). CONCLUSIONS: Osteopontin improves the diagnostic performance of a multimarker OC diagnostic test and could be useful in differential diagnosis of ovarian tumors, especially in pre-menopausal women and for early stage OC.

Mass spectrometry-based proteomics techniques and their application in ovarian cancer research.

Ovarian cancer has emerged as one of the leading cause of gynecological malignancies. So far, the measurement of CA125 and HE4 concentrations in blood and transvaginal ultrasound examination are essential ovarian cancer diagnostic methods. However, their sensitivity and specificity are still not sufficient to detect disease at the early stage. Moreover, applied treatment may appear to be ineffective due to drug-resistance. Because of a high mortality rate of ovarian cancer, there is a pressing need to develop innovative strategies leading to a full understanding of complicated molecular pathways related to cancerogenesis. Recent studies have shown the great potential of clinical proteomics in the characterization of many diseases, including ovarian cancer. Therefore, in this review, we summarized achievements of proteomics in ovarian cancer management. Since the development of mass spectrometry has caused a breakthrough in systems biology, we decided to focus on studies based on this technique. According to PubMed engine, in the years 2008-2010 the number of studies concerning OC proteomics was increasing, and since 2010 it has reached a plateau. Proteomics as a rapidly evolving branch of science may be essential in novel biomarkers discovery, therapy decisions, progression predication, monitoring of drug response or resistance. Despite the fact that proteomics has many to offer, we also discussed some limitations occur in ovarian cancer studies. Main difficulties concern both complexity and heterogeneity of ovarian cancer and drawbacks of the mass spectrometry strategies. This review summarizes challenges, capabilities, and promises of the mass spectrometry-based proteomics techniques in ovarian cancer management.

Serum angiogenesis profile in gestational trophoblastic neoplasm using multiplex immunoassay.

AIMS: Gestational trophoblastic neoplasms (GTN) exemplify a rare, mostly curable but highly aggressive disease. It is often associated with a rapid formation of distant metastases and most likely with an intense neoangiogenesis processes. The aim of the study was to analyze markers in serum of patients with GTN before chemotherapy compared to healthy pregnant women. MAIN METHODS: In this study sixteen protein angiogenesis markers were evaluated in serum of 21 patients with GTN before chemotherapy and compared with healthy pregnant women. Markers were measured using BioPlex Pro Human Cancer Biomarker Panel 1 immunoassay. t-Tests and receiver operating characteristic curves were used for statistical analysis. KEY FINDINGS: Receiver operator curve analysis identified six proteins (sTIE-2, osteopontin, sIL-6α, sVEGFR-2, sEGFR, PECAM-1) which had sufficient sensitivity and specificity (AUC > 0,70) to distinguish GTN patients before the treatment from pregnant controls. The levels of three proteins (sTIE-2, osteopontin and sIL-6α) were altered in GTN patients before the treatment as compared to healthy controls (p = 0,0112; p = 0,0442; p = 0,0488, respectively) and thereby may serve as potential disease markers. SIGNIFICANCE: Serum concentration of proteins related to angiogenesis changes in the course of GTN and may appear useful in the diagnostic process of this disease.

Understanding Ovarian Cancer: iTRAQ-Based Proteomics for Biomarker Discovery.

Despite many years of studies, ovarian cancer remains one of the top ten cancers worldwide. Its high mortality rate is mainly due to lack of sufficient diagnostic methods. For this reason, our research focused on the identification of blood markers whose appearance would precede the clinical manifestation of the disease. ITRAQ-tagging (isobaric Tags for Relative and Absolute Quantification) coupled with mass spectrometry technology was applied. Three groups of samples derived from patients with: ovarian cancer, benign ovarian tumor, and healthy controls, were examined. Mass spectrometry analysis allowed for highlighting the dysregulation of several proteins associated with ovarian cancer. Further validation of the obtained results indicated that five proteins (Serotransferrin, Amyloid A1, Hemopexin, C-reactive protein, Albumin) were differentially expressed in ovarian cancer group. Interestingly, the addition of Albumin, Serotransferrin, and Amyloid A1 to CA125 (cancer antigen 125) and HE4 (human epididymis protein4) improved the diagnostic performance of the model discriminating between benign and malignant tumors. Identified proteins shed light on the molecular signaling pathways that are associated with ovarian cancer development and should be further investigated in future studies. Our findings indicate five proteins with a strong potential to use in a multimarker test for screening and detection of ovarian cancer.

MALDI-TOF-MS analysis in discovery and identification of serum proteomic patterns of ovarian cancer.

BACKGROUND: Due to high mortality and lack of efficient screening, new tools for ovarian cancer (OC) diagnosis are urgently needed. To broaden the knowledge on the pathological processes that occur during ovarian cancer tumorigenesis, protein-peptide profiling was proposed. METHODS: Serum proteomic patterns in samples from OC patients were obtained using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF). Eighty nine serum samples (44 ovarian cancer and 45 healthy controls) were pretreated using solid-phase extraction method. Next, a classification model with the most discriminative factors was identified using chemometric algorithms. Finally, the results were verified by external validation on an independent test set of samples. RESULTS: Main outcome of this study was an identification of potential OC biomarkers by applying liquid chromatography coupled with tandem mass spectrometry. Application of this novel strategy enabled the identification of four potential OC serum biomarkers (complement C3, kininogen-1, inter-alpha-trypsin inhibitor heavy chain H4, and transthyretin). The role of these proteins was discussed in relation to OC pathomechanism. CONCLUSIONS: The study results may contribute to the development of clinically useful multi-component diagnostic tools in OC. In addition, identifying a novel panel of discriminative proteins could provide a new insight into complex signaling and functional networks associated with this multifactorial disease.

Diagnostic Value of Serum Angiogenesis Markers in Ovarian Cancer Using Multiplex Immunoassay.

As cancer development involves pathological vessel formation, 16 angiogenesis markers were evaluated as potential ovarian cancer (OC) biomarkers. Blood samples collected from 172 patients were divided based on histopathological result: OC (n = 38), borderline ovarian tumours (n = 6), non-malignant ovarian tumours (n = 62), healthy controls (n = 50) and 16 patients were excluded. Sixteen angiogenesis markers were measured using BioPlex Pro Human Cancer Biomarker Panel 1 immunoassay. Additionally, concentrations of cancer antigen 125 (CA125) and human epididymis protein 4 (HE4) were measured in patients with adnexal masses using electrochemiluminescence immunoassay. In the comparison between OC vs. non-OC, osteopontin achieved the highest area under the curve (AUC) of 0.79 (sensitivity 69%, specificity 78%). Multimarker models based on four to six markers (basic fibroblast growth factor-FGF-basic, follistatin, hepatocyte growth factor-HGF, osteopontin, platelet-derived growth factor AB/BB-PDGF-AB/BB, leptin) demonstrated higher discriminatory ability (AUC 0.80-0.81) than a single marker (AUC 0.79). When comparing OC with benign ovarian tumours, six markers had statistically different expression (osteopontin, leptin, follistatin, PDGF-AB/BB, HGF, FGF-basic). Osteopontin was the best single angiogenesis marker (AUC 0.825, sensitivity 72%, specificity 82%). A three-marker panel consisting of osteopontin, CA125 and HE4 better discriminated the groups (AUC 0.958) than HE4 or CA125 alone (AUC 0.941 and 0.932, respectively). Osteopontin should be further investigated as a potential biomarker in OC screening and differential diagnosis of ovarian tumours. Adding osteopontin to a panel of already used biomarkers (CA125 and HE4) significantly improves differential diagnosis between malignant and benign ovarian tumours.

PROTEOMIC ANALYSIS OF APIS MELLIFERA VENOM DETERMINED BY LIQUID CHROMATOGRAPHY (LC) COUPLED WITH NANO-LC-MALDI-TOF/TOF MS.

The integration of multidimensional liquid chromatography and mass spectrometry analytical plat- form was proposed for proteomic exploration of honeybee venom. The combination of HPLC with nanoLC-MALDI-TOF/TOF MS system was our method of choice for compressing the dynamic range of honeybee venom protein concentration. Honeybee venom samples were separated into 6 fractions using HPLC and further analyzed by nanoLC-MALDI-TOF/TOF. Applied approach allowed to identify in total 394 peptides giving the identification of 50 components including putative toxins and trace elements. Moreover, all 12 known honeybee venom allergens were acknowledged. Additionally, four novel hypothetical proteins have been observed which were not observed in other studies. The newly recognized proteins should be further investigated, in order to characterize their functions in the venom of Apis mellifera.

Identification of Serum Peptidome Signatures of Non-Small Cell Lung Cancer.

Due to high mortality rates of lung cancer, there is a need for identification of new, clinically useful markers, which improve detection of this tumor in early stage of disease. In the current study, serum peptide profiling was evaluated as a diagnostic tool for non-small cell lung cancer patients. The combination of the ZipTip technology with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for the analysis of peptide pattern of cancer patients (n = 153) and control subjects (n = 63) was presented for the first time. Based on the observed significant differences between cancer patients and control subjects, the classification model was created, which allowed for accurate group discrimination. The model turned out to be robust enough to discriminate a new validation set of samples with satisfactory sensitivity and specificity. Two peptides from the diagnostic pattern for non-small cell lung cancer (NSCLC) were identified as fragments of C3 and fibrinogen α chain. Since ELISA test did not confirm significant differences in the expression of complement component C3, further study will involve a quantitative approach to prove clinical utility of the other proteins from the proposed multi-peptide cancer signature.

Influence of honeybee sting on peptidome profile in human serum.

The aim of this study was to explore the serum peptide profiles from honeybee stung and non-stung individuals. Two groups of serum samples obtained from 27 beekeepers were included in our study. The first group of samples was collected within 3 h after a bee sting (stung beekeepers), and the samples were collected from the same person a second time after at least six weeks after the last bee sting (non-stung beekeepers). Peptide profile spectra were determined using MALDI-TOF mass spectrometry combined with Omix, ZipTips and magnetic beads based on weak-cation exchange (MB-WCX) enrichment strategies in the mass range of 1-10 kDa. The samples were classified, and discriminative models were established by using the quick classifier, genetic algorithm and supervised neural network algorithms. All of the statistical algorithms used in this study allow distinguishing analyzed groups with high statistical significance, which confirms the influence of honeybee sting on the serum peptidome profile. The results of this study may broaden the understanding of the human organism's response to honeybee venom. Due to the fact that our pilot study was carried out on relatively small datasets, it is necessary to conduct further proteomic research of the response to honeybee sting on a larger group of samples.