Quantitative proteomic analysis by iTRAQ(R) for the identification of candidate biomarkers in ovarian cancer serum

Comprehensive serum proteomics profiles and potential protein biomarkers for the early detection of advanced adenoma and colorectal cancer

BACKGROUND

The majority of colorectal cancer (CRC) cases develop from precursor advanced adenoma (AA). With the development of proteomics technologies, blood protein biomarkers have potential applications in the early screening of AA and CRC in the general population.

AIM

To identify serum protein biomarkers for the early screening of AA and CRC.

METHODS

We collected 43 serum samples from 8 normal controls (NCs), 19 AA patients and 16 CRC patients at China-Japan Friendship Hospital. Quantitative proteomic analysis was performed using liquid chromatography-mass spectrometry/mass spectrometry and data independent acquisition, and differentially expressed proteins (DEPs) with P-values < 0.05 and absolute fold changes > 1.5 were screened out, followed by bioinformatics analysis. Prognosis was further analyzed based on public databases, and proteins expression in tissues were validated by immunohistochemistry.

RESULTS

A total of 2132 proteins and 17365 peptides were identified in the serum samples. There were 459 upregulated proteins and 118 downregulated proteins in the NC vs AA group, 289 and 180 in the NC vs CRC group, and 52 and 248 in the AA vs CRC group, respectively. Bioinformatic analysis revealed that these DEPs had different functions and participated in extensive signaling pathways. We also identified DIAPH1, VASP, RAB11B, LBP, SAR1A, TUBGCP5, and DOK3 as important proteins for the progression of AA and CRC. Furthermore, VASP (P < 0.01), LBP (P = 0.01), TUBGCP5 (P < 0.01), and DOK3 (P < 0.01) were associated with a poor prognosis. In addition, we propose that LBP and VASP may be more promising protein biomarkers for the early screening of colorectal tumors.

CONCLUSION

Our study elucidated the serum proteomic profiles of AA and CRC patients, and the identified proteins, such as LBP and VASP, may contribute to the early detection of AA and CRC.

An overview of glioblastoma multiforme and temozolomide resistance: can LC-MS-based proteomics reveal the fundamental mechanism of temozolomide resistance?

Glioblastoma multiforme (GBM) is a primary type of lethal brain tumor. Over the last two decades, temozolomide (TMZ) has remained the primary chemotherapy for GBM. However, TMZ resistance in GBM constitutes an underlying factor contributing to high rates of mortality. Despite intense efforts to understand the mechanisms of therapeutic resistance, there is currently a poor understanding of the molecular processes of drug resistance. For TMZ, several mechanisms linked to therapeutic resistance have been proposed. In the past decade, significant progress in the field of mass spectrometry-based proteomics has been made. This review article discusses the molecular drivers of GBM, within the context of TMZ resistance with a particular emphasis on the potential benefits and insights of using global proteomic techniques.

Lipopolysaccharide-binding protein as a biomarker in oral and maxillofacial tumors

Oral and maxillofacial tumors (OMTs), such as oral squamous cell carcinoma (SCC), pleomorphic adenoma, and ameloblastoma, are common head and neck tumors. Lipopolysaccharide-binding protein (LBP) is a type I acute reactive protein, which participates in body inflammatory response modulation through lipopolysaccharide (LPS)-induced signaling pathway by targeting macrophages (expressing cluster of differentiation 204 [CD204]). Although it is well established that LBP is associated with the development of multiple types of cancer, little is known about the role of LBP in OMTs. This study aims to explore the expression of LBP in OMTs. Here, immunohistochemical (IHC) double staining of LBP and CD204 and enzyme-linked immunosorbent assay (ELISA) were conducted to explore the LBP expression in OMTs. The findings demonstrated that the LBP expression in OMTs was significantly elevated (p < 0.001). In addition, the LBP expression was associated with the clinical stage (p < 0.001), T classification (p < 0.001), and lymph node metastasis (p < 0.001, except ELISA) but independent of histological grade of SCC, gender, and age in patients with SCC. The optional cutoff of the LBP serum level is 0.721 μg/ml. To conclude, LBP contributes to the development of OMTs and could be a biomarker in the screening and predicting metastasis in patients with OMTs.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Novel Diagnostic Biomarkers for High-Grade Serous Ovarian Cancer Uncovered by Data-Independent Acquisition Mass Spectrometry

High-grade serous ovarian cancer (HGSOC) represents the major histological type of ovarian cancer, and the lack of effective screening tools and early detection methods significantly contributes to the poor prognosis of HGSOC. Currently, there are no reliable diagnostic biomarkers for HGSOC. In this study, we performed liquid chromatography data-independent acquisition tandem mass spectrometry (MS) on depleted serum samples from 26 HGSOC cases and 24 healthy controls (HCs) to discover potential HGSOC diagnostic biomarkers. A total of 1,847 proteins were identified across all samples, among which 116 proteins showed differential expressions between HGSOC patients and HCs. Network modeling showed activations of coagulation and complement cascades, platelet activation and aggregation, neutrophil extracellular trap formation, toll-like receptor 4, insulin-like growth factor, and transforming growth factor β signaling, as well as suppression of lipoprotein assembly and Fc gamma receptor activation in HGSOC. Based on the network model, we prioritized 28 biomarker candidates and validated 18 of them using targeted MS assays in an independent cohort. Predictive modeling showed a sensitivity of 1 and a specificity of 0.91 in the validation cohort. Finally, in vitro functional assays on four potential biomarkers (FGA, VWF, ARHGDIB, and SERPINF2) suggested that they may play an important role in cancer cell proliferation and migration in HGSOC. All raw data were deposited in PRIDE (PXD033169).

Analysis of the Value of Serum Biomarker LBP in the Diagnosis of Spinal Tuberculosis

Objective

To investigate the correlation between the expression of lipopolysaccharide-binding protein (LBP) in peripheral blood of spinal tuberculosis and clinical diagnosis and to evaluate its value as a diagnostic marker of spinal tuberculosis.

Methods

In the experimental group, clinical history data and peripheral blood were collected from 100 patients with spinal tuberculosis who were admitted to the Department of Spine Surgery, General Hospital of Ningxia Medical University from May 2017 to May 2020, and peripheral blood was collected from 30 healthy volunteers in the control group. Screening of differential LBP expression by proteomics and ELISA to verify its expression in peripheral blood of spinal tuberculosis patients. t-test, Spearman analysis, linear regression and ROC curve were used to evaluate the diagnostic value of LBP in peripheral blood for spinal tuberculosis.

Results

The expression of LBP protein in peripheral blood is significantly higher in patients with spinal tuberculosis than in the normal population; LBP assay values were significantly and positively correlated with CRP and ESR values (P < 0.01); the AUC of LBP in the diagnosis of spinal tuberculosis for pathological examination, bacteriological culture, T-cell spot test for tuberculosis infection (T-SPOT), imaging diagnosis, and acid fast bacillus were, respectively, 0.677 (P < 0.01), 0.707 (P < 0.01), 0.751 (P < 0.01), 0.714 (P < 0.01), and 0.656 (P < 0.05), and there was a correlation between LBP and the diagnostic evaluation of spinal tuberculosis.

Conclusion

LBP could be a new candidate biomarker for the diagnosis of spinal tuberculosis.

Comprehensive Identification of Potential Crucial Genes and miRNA-mRNA Regulatory Networks in Papillary Thyroid Cancer

Background

Thyroid cancer is the most common endocrine malignancy, with a recent global increase of 20% in age-related incidence. Ultrasonography and ultrasonography-guided fine-needle aspiration biopsy (FNAB) are the most widely used diagnostic tests for thyroid nodules; however, it is estimated that up to 25% of thyroid biopsies are cytologically inconclusive. Molecular markers can help guide patient-oriented and targeted treatment of thyroid nodules and thyroid cancer.

Methods

Datasets related to papillary thyroid cancer (PTC) or thyroid carcinoma (GSE129562, GSE3678, GSE54958, GSE138042, and GSE124653) were downloaded from the GEO database and analysed using the Limma package of R software. For functional enrichment analysis, the Kyoto Encyclopedia of Genes and Genomes pathway analysis and Gene Ontology were applied to differentially expressed genes (DEGs) using the Metascape website. A protein-protein interaction (PPI) network was built from the STRING database. Gene expression, protein expression, immunohistochemistry, and potential functional gene survival were analysed using the GEPIA website, the Human Protein Atlas website, and the UALCAN website. Potential target miRNAs were predicted using the miRDB and Starbase datasets.

Results

We found 219 upregulated and 310 downregulated DEGs, with a cut-off of p < 0.01 and ∣log FC | >1.5. The DEGs in papillary thyroid cancer were mainly enriched in extracellular structural organisation. At the intersection of the PPI network and Metascape MCODEs, the hub genes in common were identified as FN1, APOE, CLU, and SDC2. In the targeted regulation network of miRNA-mRNA, the hsa-miR-424-5p was found to synchronously modulate two hub genes. Survival analysis showed that patients with high expression of CLU and APOE had better prognosis.

Conclusions

CLU and APOE are involved in the molecular mechanism of papillary thyroid cancer. The hsa-miR-424-5p might have the potential to reverse the processes of papillary thyroid cancer by modulating the hub genes. These are potential targets for the treatment of patients with papillary thyroid cancer.

Association of decreased levels of lipopolysaccharide-binding protein with OKN-007-induced regression of tumor growth in an F98 rat glioma model

OBJECTIVE

High-grade gliomas, such as glioblastoma (GBM), are devastating tumors with a very poor prognosis. Previously the authors have found that the nitrone compound OKN-007 (OKlahoma Nitrone 007; or disodium 4-[(tert-butyl-imino) methyl] benzene-1,3-disulfonate N-oxide) is effective against high-grade gliomas in various GBM rodent and human xenograft models. The purpose of the present study was to assess the levels of the lipopolysaccharide-binding protein (LBP) in rodent gliomas treated with OKN-007 as well as determine the expression of LBP in human gliomas.

METHODS

Microarray analysis was done to assess altered gene expression following OKN-007 administration in an F98 glioma model. An enzyme-linked immunosorbent assay was incorporated to assess LBP levels in glioma tissues, as well as blood serum, comparing results in OKN-007-treated and untreated tumor-bearing animals. Immunohistochemistry was used to assess LBP levels in varying grades of human glioma tissue sections.

RESULTS

Upon further assessment of gene expression fold changes in F98 gliomas in rats that received or did not receive OKN-007, it was found that the gene for LBP was significantly downregulated by OKN-007. Further investigation was done to see whether levels of LBP were affected by OKN-007 treatment in F98 gliomas. It was found that LBP could be detected not only in glioma tissue but also in blood serum of F98 glioma-bearing rats and that OKN-007 decreased the levels of LBP. It was also found that LBP levels are highly expressed in human high-grade glioma tissues.

CONCLUSIONS

LBP could potentially be used as a serum diagnostic marker of treatment response in high-grade gliomas.

Plasma levels of apolipoprotein E, APOE genotype, and all-cause and cause-specific mortality in 105 949 individuals from a white general population cohort

Aims

To determine whether plasma apoE levels and APOE genotype are associated with all-cause and cause-specific mortality.

Methods and results

Using a prospective cohort design with 105 949 white individuals from the general population, we tested the association between plasma apoE at study enrolment and death during follow-up, and whether this was independent of APOE genotype. We confirmed the well-known association between APOE genotypes and mortality. For all-cause, cardiovascular, and cancer mortality, high levels of apoE were associated with increased risk, while for dementia-associated mortality low levels were associated with increased risk. For the highest vs. the fifth septile of plasma apoE, hazard ratios (HRs) were 1.20 (95% confidence interval 1.12–1.28) for all-cause mortality, 1.28 (1.13–1.44) for cardiovascular mortality, and 1.18 (1.05–1.32) for cancer mortality. Conversely, for the lowest vs. the fifth septile the HR was 1.44 (1.01–2.05) for dementia-associated mortality. Results were similar in analyses restricted to APOE ɛ33 carriers. Examining genetically determined plasma apoE, a 1 mg/dL increase conferred risk ratios of 0.97 (0.92–1.03) for cardiovascular mortality and 1.01 (0.95–1.06) for cancer mortality, while a 1 mg/dL decrease conferred a risk ratio of 1.70 (1.36–2.12) for dementia-associated mortality.

Conclusion

High plasma levels of apoE were associated with increased all-cause, cardiovascular, and cancer mortality, however of a non-causal nature, while low levels were causally associated with increased dementia-associated mortality.

The clinical significance of lipopolysaccharide binding protein in hepatocellular carcinoma

Lipopolysaccharide binding protein (LBP) has been reported to be associated with prognosis in colorectal carcinoma and renal cell carcinoma; however, the clinical significance of LBP in human primary hepatocellular carcinoma (HCC) is inconclusive. We aimed to investigate the clinical significance and prognostic value of LBP in human primary HCC. In the present study, 346 patients with HCC who underwent curative resection were retrospectively analyzed. LBP protein expression was evaluated using western blot analysis and immunohistochemistry. LBP scores collected from immunohistochemical analysis were obtained by multiplying staining intensity and the percentage of positive cells. An outcome-based best cutoff-point was calculated by X-tile software. Moreover, Kaplan-Meier curves and Cox regressions were used for prognosis evaluation. LBP was frequently overexpressed in HCC compared with that in peritumor tissues (five pairs by western blot analysis, P=0.0533; 77 pairs by immunohistochemistry, P=0.0171), and LBP expression was positively associated with tumor-node-metastasis stage and tumor differentiation. Patients who had high LBP expression had decreased overall survival and time to recurrence compared with patients with low LBP expression. Furthermore, patients who were both serum α-fetoprotein positive and had high LBP expression had poor prognoses. Univariate and multivariate Cox analyses indicated that this combination was an independent prognostic factor [overall survival: Hazard ratio (HR), 1.458; 95% confidence interval (CI), 1.158–1.837; P=0.001; time to recurrence: HR,1.382; 95% Cl, 1.124–1.700; P=0.002]. In conclusion, LBP is highly expressed in HCC, and high LBP expression combined with serum α-fetoprotein may predict poor outcomes in patients with HCC following curative resection.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

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.

Integrated bioinformatics analysis reveals that the expression of cathepsin S is associated with lymph node metastasis and poor prognosis in papillary thyroid cancer

The prognosis of the majority of patients with papillary thyroid cancer (PTC) is excellent, although there are patients who experience disease recurrence and progression. The aim of the present study was to identify potential prognostic risk markers in PTC. Differentially expressed genes (DEGs), identified from four Genome Expression Omnibus cohorts were subjected to functional enrichment analyses with Gene Ontology terms and the Kyoto Encyclopedia of Genes and Genome pathways. Hub genes, filtered from cytoHubba, were validated using the The Cancer Genome Atlas (TCGA) cohort, and their associations with clinicopathological features and prognosis were analyzed. A total of 277 DEGs were identified following data preprocessing. DEGs were primarily enriched in 'small cell lung cancer', 'ECM-receptor interaction', 'pathways in cancer'and 'tyrosine metabolism'. Hub genes [APOE, cathepsin S (CTSS), insulin receptor substrate 1 (IRS1), KIT, LGALS3, RUNX2 and TGFBR1] were extracted from cytoHubba. Their expression in the TCGA cohort was consistent with that in the GEO cohorts. CTSS (P=0.006) and IRS1 (P=0.005) were associated with disease‑free survival, as determined using the Kaplan-Meier analysis. CTSS was an independent risk factor for poor disease‑free survival (HR, 2.649; 95% CI, 1.095-6.409; P=0.031). Patients with high expression of CTSS exhibited different histological types (increased tall-cell subtype and reduced follicular subtype; P<0.001), more frequent lymph node metastasis (P<0.001) and advanced tumor-node-metastasis stages (P=0.049) compared with the low-expression group. High expression of CTSS was independently associated with lymph node metastasis (OR, 2.015; 95% CI, 1.225-3.315; P=0.006). Therefore, CTSS may serve as a predictive risk marker for the progression and prognosis of PTC.

A multiplex platform for the identification of ovarian cancer biomarkers

Background

Currently, there are no FDA approved screening tools for detecting early stage ovarian cancer in the general population. Development of a biomarker-based assay for early detection would significantly improve the survival of ovarian cancer patients.

Methods

We used a multiplex approach to identify protein biomarkers for detecting early stage ovarian cancer. This new technology (Proseek^® Multiplex Oncology Plates) can simultaneously measure the expression of 92 proteins in serum based on a proximity extension assay. We analyzed serum samples from 81 women representing healthy, benign pathology, early, and advanced stage serous ovarian cancer patients.

Results

Principle component analysis and unsupervised hierarchical clustering separated patients into cancer versus non-cancer subgroups. Data from the Proseek^® plate for CA125 levels exhibited a strong correlation with current clinical assays for CA125 (correlation coefficient of 0.89, 95% CI 0.83, 0.93). CA125 and HE4 were present at very low levels in healthy controls and benign cases, while higher levels were found in early stage cases, with highest levels found in the advanced stage cases. Overall, significant trends were observed for 38 of the 92 proteins (p < 0.001), many of which are novel candidate serum biomarkers for ovarian cancer. The area under the ROC curve (AUC) for CA125 was 0.98 and the AUC for HE4 was 0.85 when comparing early stage ovarian cancer versus healthy controls. In total, 23 proteins had an estimated AUC of 0.7 or greater. Using a naïve Bayes classifier that combined 12 proteins, we improved the sensitivity corresponding to 95% specificity from 93 to 95% when compared to CA125 alone. Although small, a 2% increase would have a significant effect on the number of women correctly identified when screening a large population.

Conclusions

These data demonstrate that the Proseek^® technology can replicate the results established by conventional clinical assays for known biomarkers, identify new candidate biomarkers, and improve the sensitivity and specificity of CA125 alone. Additional studies using a larger cohort of patients will allow for validation of these biomarkers and lead to the development of a screening tool for detecting early stage ovarian cancer in the general population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12014-017-9169-6) contains supplementary material, which is available to authorized users.

Recent advances in quantitative and chemical proteomics for autophagy studies

Macroautophagy/autophagy is an evolutionarily well-conserved cellular degradative process with important biological functions that is closely implicated in health and disease. In recent years, quantitative mass spectrometry-based proteomics and chemical proteomics have emerged as important tools for the study of autophagy, through large-scale unbiased analysis of the proteome or through highly specific and accurate analysis of individual proteins of interest. At present, a variety of approaches have been successfully applied, including (i) expression and interaction proteomics for the study of protein post-translational modifications, (ii) investigating spatio-temporal dynamics of protein synthesis and degradation, and (iii) direct determination of protein activity and profiling molecular targets in the autophagic process. In this review, we attempted to provide an overview of principles and techniques relevant to the application of quantitative and chemical proteomics methods to autophagy, and outline the current landscape as well as future outlook of these methods in autophagy research.

Identification of CD14 as a potential biomarker of hepatocellular carcinoma using iTRAQ quantitative proteomics

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors without effective diagnostic biomarkers. This study intended to dynamically analyze serum proteomics in different pathological stages of liver diseases, and discover potential diagnostic biomarkers for early HCC. Patients with hepatitis B virus (HBV) infection, liver cirrhosis (LC), or HCC together with healthy controls (HC) were enrolled. Proteins differentially expressed between groups were screened using isobaric tagging for relative and absolute quantitation (iTRAQ), and promising HCC biomarker candidates were subjected to bioinformatics analysis, including K-means clustering, gene ontology (GO) and string network analysis. Potential biomarkers were validated by Western blotting and enzyme-linked immunosorbent assay (ELISA), and their diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis. Finally, 93 differentially expressed proteins were identified, of which 43 differed between HBV and HC, 70 between LC and HC, and 51 between HCC and HC. Expression levels of gelsolin (GELS) and sulfhydryl oxidase 1 (QSOX1) varied with disease state as follows: HC < HBV < LC < HCC. The reverse trend was observed with CD14. These iTRAQ results were confirmed by Western blotting and ELISA. Logistic regression and ROC curve analysis identified the optimal cut-off for alpha-fetoprotein (AFP), CD14 and AFP/CD14 was 191.4 ng/mL (AUC 0.646, 95%CI 0.467-0.825, sensitivity 31.6%, specificity 94.4%), 3.16 ng/mL (AUC 0.760, 95%CI 0.604-0.917, sensitivity 94.7%, specificity 50%) and 0.197 ng/mL (AUC 0.889, 95%CI 0.785-0.993, sensitivity 84.2%, specificity 83.3%) respectively. In conclusion, Assaying CD14 levels may complement AFP measurement for early detection of HCC.

Detection of candidate biomarkers of prostate cancer progression in serum: a depletion-free 3D LC/MS quantitative proteomics pilot study

BACKGROUND

Prostate cancer (PCa) is the most common male cancer in the United Kingdom and we aimed to identify clinically relevant biomarkers corresponding to stage progression of the disease.

METHODS

We used enhanced proteomic profiling of PCa progression using iTRAQ 3D LC mass spectrometry on high-quality serum samples to identify biomarkers of PCa.

RESULTS

We identified >1000 proteins. Following specific inclusion/exclusion criteria we targeted seven proteins of which two were validated by ELISA and six potentially interacted forming an 'interactome' with only a single protein linking each marker. This network also includes accepted cancer markers, such as TNF, STAT3, NF-κB and IL6.

CONCLUSIONS

Our linked and interrelated biomarker network highlights the potential utility of six of our seven markers as a panel for diagnosing PCa and, critically, in determining the stage of the disease. Our validation analysis of the MS-identified proteins found that SAA alongside KLK3 may improve categorisation of PCa than by KLK3 alone, and that TSR1, although not significant in this model, might also be a clinically relevant biomarker.

Serum levels of apolipoprotein E correlates with disease progression and poor prognosis in breast cancer

ApoE has been reported to be associated with tumorigenesis and tumor progression. In this study, we explored the potential diagnostic and prognostic role of serum ApoE in breast cancer patients. Subject cohorts consisted of 152 normal healthy controls female and 257 breast cancer cases. Serum levels of ApoE were determined with turbidimetric immunoassay. The serum levels of ApoE were significantly elevated in breast cancer patients compared with normal healthy controls (45.82 ± 13.96 mg/L vs. 33.61 ± 6.44 mg/L, respectively, P < 0.0001) and also significantly associated with TNM stage and lymph nodes status (all P < 0.05). Area under receiver operating characteristic curve for serum ApoE discriminate breast cancer patients from controls was 0.786 with specificity of 0.974 and sensitivity of 0.541, the cut-off value of ApoE was 43.15 mg/L. Kaplan-Meier log rank analysis showed that the high serum ApoE group (serum ApoE ≥ 43.15 mg/L) had a poorer progression-free survival and overall survival compared with low serum ApoE group (serum ApoE < 43.15 mg/L) (all P < 0.05). In addition, univariate and multivariate Cox regression analysis displayed serum ApoE as an independent risk factor of breast cancer patients prognosis (all P < 0.05). Serum ApoE played a role as serological biomarkers that indicated diagnostic and prognostic evaluation in breast cancer patients.

Composition of Rosenthal Fibers, the Protein Aggregate Hallmark of Alexander Disease

Alexander disease (AxD) is a neurodegenerative disorder characterized by astrocytic protein aggregates called Rosenthal fibers (RFs). We used mouse models of AxD to determine the protein composition of RFs to obtain information about disease mechanisms including the hypothesis that sequestration of proteins in RFs contributes to disease. A method was developed for RF enrichment, and analysis of the resulting fraction using isobaric tags for relative and absolute quantitation mass spectrometry identified 77 proteins not previously associated with RFs. Three of five proteins selected for follow-up were confirmed enriched in the RF fraction by immunobloting of both the AxD mouse models and human patients: receptor for activated protein C kinase 1 (RACK1), G1/S-specific cyclin D2, and ATP-dependent RNA helicase DDX3X. Immunohistochemistry validated cyclin D2 as a new RF component, but results for RACK1 and DDX3X were equivocal. None of these was decreased in the non-RF fractions compared to controls. A similar result was obtained for the previously known RF component, alphaB-crystallin, which had been a candidate for sequestration. Thus, no support was obtained for the sequestration hypothesis for AxD. Providing possible insight into disease progression, the association of several of the RF proteins with stress granules suggests a role for stress granules in the origin of RFs.

iTRAQ-based quantitative proteomic analysis reveals potential early diagnostic markers of clear-cell Renal cell carcinoma

Early detection is the key to improve the prognosis of kidney cancer. This study profiled and identified differentially expressed serum proteins in stage T1a renal cell carcinoma (RCC) using isobaric tags for relative and absolute quantification (iTRAQ)-based mass spectrometry. A total amount of 99 serum samples including 29 patients with ccRCC, 24 patients with a benign kidney mass, 28 patients with another type of urological tumor (20 cases of transitional cell carcinoma and 8 cases of prostate cancer or a male genital tumor), and 18 healthy controls were subjected to iTRAQ-based mass spectrometry. ProteinPilot software was used to identify the differentially expressed serum proteins in RCC compared to the other three populations. Hierarchical clustering analysis according to The Cancer Genome Atlas (TCGA) RCC database was then performed as the cross-platform validation. Immunohistochemistry was performed to verify the expression of selected proteins in tissue samples from these subjects. iTRAQ identified 27 differentially expressed serum proteins in the RCC patients, and 11 of these proteins were cross validated in RCC tissues from the TCGA database. The expression of C1QC, C1QB, S100A8, S100A9, ceruplasmin, and lumican was verified and associated with the tumor stage and/or grade. There were 27 differentially expressed proteins in early-stage RCC identified by iTRAQ; among them, the expression of C1QC, C1QB, S100A8, S100A9, ceruplasmin, and lumican were associated with the tumor stage and/or grade. Further studies are needed to confirm these data for their use as biomarkers for the early detection of RCC.

Acute Aortic Dissection Biomarkers Identified Using Isobaric Tags for Relative and Absolute Quantitation

The purpose of this study was to evaluate the utility of potential serum biomarkers for acute aortic dissection (AAD) that were identified by isobaric Tags for Relative and Absolute Quantitation (iTRAQ) approaches. Serum samples from 20 AAD patients and 20 healthy volunteers were analyzed using iTRAQ technology. Protein validation was performed using samples from 120 patients with chest pain. A total of 355 proteins were identified with the iTRAQ approach; 164 proteins reached the strict quantitative standard, and 125 proteins were increased or decreased more than 1.2-fold (64 and 61 proteins were up- and downregulated, resp.). Lumican, C-reactive protein (CRP), thrombospondin-1 (TSP-1), and D-dimer were selected as candidate biomarkers for the validation tests. Receiver operating characteristic (ROC) curves show that Lumican and D-dimer have diagnostic value (area under the curves [AUCs] 0.895 and 0.891, P < 0.05). For Lumican, the diagnostic sensitivity and specificity were 73.33% and 98.33%, while the corresponding values for D-dimer were 93.33% and 68.33%. For Lumican and D-dimer AAD combined diagnosis, the sensitivity and specificity were 88.33% and 95%, respectively. In conclusion, Lumican has good specificity and D-dimer has good sensitivity for the diagnosis of AAD, while the combined detection of D-dimer and Lumican has better diagnostic value.

Elevated serum apolipoprotein E is associated with metastasis and poor prognosis of non-small cell lung cancer

Apolipoprotein E (ApoE) is a factor involved in Alzheimer's disease, which recently attracted great attention as an important protein related to tumorigenesis and metastasis. However, serum ApoE levels and its diagnosis and prognosis value in non-small cell lung cancer (NSCLC) patients are still unknown. In 196 NSCLC patients and 203 healthy controls, serum ApoE was measured by turbidimetric immunoassay. The associations of serum ApoE levels with the clinicopathological characteristics and clinical outcomes of NSCLC patients were analyzed. Serum ApoE levels were obviously elevated in NSCLC patients compared with healthy controls (41.6 ± 11.63 vs. 33.8 ± 6.24 mg/L) and were associated with TNM stage, lymph node metastasis status, and distant metastasis status (all P < 0.0001). For NSCLC diagnosis, the area under the receiver operating characteristic (ROC) curve was 0.71 at a specificity of 0.90 and sensitivity of 0.47. For lymph node metastasis predicting, the area under the ROC curve was 0.68 at a specificity of 0.56 and sensitivity of 0.73. From ROC/area under curve (AUC) analysis, we used 41.25 mg/L as the serum ApoE cut-off value, to divide NSCLC patients into two groups, the median survival was 11.0 weeks (95 % CI = 8.7 to 13.3) for patients in high serum ApoE group and 20.0 weeks (95 % CI = 15.0 to 25.0) in low serum ApoE group. Serum ApoE levels elevated in NSCLC patients, which also associated with TNM stages, lymph node metastasis, distant metastasis, and poor prognosis, suggest that serum ApoE may act as a useful clinical serological biomarkers for evaluating the progress of NSCLC.

The clinical impact of recent advances in LC-MS for cancer biomarker discovery and verification

Mass spectrometry (MS) -based proteomics has become an indispensable tool with broad applications in systems biology and biomedical research. With recent advances in liquid chromatography (LC) and MS instrumentation, LC-MS is making increasingly significant contributions to clinical applications, especially in the area of cancer biomarker discovery and verification. To overcome challenges associated with analyses of clinical samples (for example, a wide dynamic range of protein concentrations in bodily fluids and the need to perform high throughput and accurate quantification of candidate biomarker proteins), significant efforts have been devoted to improve the overall performance of LC-MS-based clinical proteomics platforms. Reviewed here are the recent advances in LC-MS and its applications in cancer biomarker discovery and quantification, along with the potentials, limitations and future perspectives.

A quantitative proteomics-based signature of platinum sensitivity in ovarian cancer cell lines

Although DNA encodes the molecular instructions that underlie the control of cell function, it is the proteins that are primarily responsible for implementing those instructions. Therefore quantitative analyses of the proteome would be expected to yield insights into important candidates for the detection and treatment of disease. We present an iTRAQ (isobaric tag for relative and absolute quantification)-based proteomic analysis of ten ovarian cancer cell lines and two normal ovarian surface epithelial cell lines. We profiled the abundance of 2659 cellular proteins of which 1273 were common to all 12 cell lines. Of the 1273, 75 proteins exhibited elevated expression and 164 proteins had diminished expression in the cancerous cells compared with the normal cell lines. The iTRAQ expression profiles allowed us to segregate cell lines based upon sensitivity and resistance to carboplatin. Importantly, we observed no substantial correlation between protein abundance and RNA expression or epigenetic DNA methylation data. Furthermore, we could not discriminate between sensitivity and resistance to carboplatin on the basis of RNA expression and DNA methylation data alone. The present study illustrates the importance of proteomics-based discovery for defining the basis for the carboplatin response in ovarian cancer and highlights candidate proteins, particularly involved in cellular redox regulation, homologous recombination and DNA damage repair, which otherwise could not have been predicted from whole genome and expression data sources alone.

Secretomes are a potential source of molecular targets for cancer therapies and indicate that APOE is a candidate biomarker for lung adenocarcinoma metastasis

Identifying patients at high risk of metastasis is a major challenge in lung adenocarcinoma (ADC) therapy, therefore discovery of noninvasive biomarkers and therapeutic targets is urgent. We found significant differences between the secretomes of differentially expressed proteins in lung ADC cell lines, clinical tissue samples and serum plasma samples with high and low metastatic potential. In particular, Apolipoprotein E (APOE) levels were three-times greater in cells with lymph node metastases (LNM) than those without. Our study indicates that APOE is a potential indicator of metastatic lung ADC and that secretomes may offer a valuable resource for biomarkers of lung ADC with LNM.

Mitochondrial protein targets of radiosensitisation by 1,8-dihydroxy-3-acetyl-6-methyl-9,10 anthraquinone on nasopharyngeal carcinoma cells

In our preliminary study, 1,8-dihydroxy-3-acetyl-6-methyl-9,10 anthraquinone (GXHSWAQ-1), synthesised according to the basic structure of emodin, exhibited a 1.58-fold radiosensitisation on nasopharyngeal carcinoma CNE-1 cells. This study demonstrated that its radiosensitisation activity was achieved by altering the mitochondrial structure: swollen volume, fragmented crista, and decreasing transmembrane potential (P<0.01). Using isobaric tag for relative and absolute quantitation (iTRAQ) technology, 1396 proteins were identified, and the differentially expressed proteins were involved in metabolism, cell proliferation, angiogenesis, DNA repair process according to the biological process clustering results. Bioinformatic analysis showed that CDH1, RAC1, CDC42 proteins might be mostly mitochondrial targets in the radiosensitisation process. Western blotting analyses verified the differential expression of these proteins.

Tear fluid protein biomarkers

The tear film covers and protects the ocular surface. It contains various molecules including a large variety of proteins. The protein composition of the tear fluid can change with respect to various local and systemic diseases. Prior to the advent of the proteomic era, tear protein analysis was limited to a few analytical techniques, the most common of which was immunoelectrophoresis, an approach dependent on antibody availability. Using proteomics, hundreds of tear proteins could potentially be identified and subsequently studied. Although detection of low-abundance proteins in the complex tear proteome remains a challenge, advances in sample fractionation and mass spectrometry have greatly enhanced our ability to detect these proteins. With increasing proteomic applications, tears show great potential as biomarkers in the development of clinical assays for various human diseases. In this chapter, we discuss the structure and functions of the tear film and methods for its collection. We also summarize potential tear protein biomarkers identified using proteomic techniques for both ocular and systemic diseases. Finally, modern proteomic techniques for tear biomarker research and future challenges are explored.

Identification of adipophilin as a potential diagnostic tumor marker for lung adenocarcinoma

In our previous study, the upregulation of adipophilin in lung adenocarcinoma were identified compared with normal lung tissues by quantitative proteomics. In this study, our aim was to verify the result from quantitative proteomics, further investigate the relationship between adipophilin expression and clinicopathologic factors of lung cancer patients. The expression levels of adipophilin were examined in 10 pairs of lung adenocarcinoma and normal lung tissues using western blotting and the expression and cellular distribution of adipophilin were determined by IHC in 62 formalin-fixed and paraffin embedded primary lung cancer specimens. Adipophilin expression was significantly higher in lung adenocarcinoma specimens than in normal tissues and lung squamous cell carcinomas (P<0.05). There were no significant difference of adipophilin expression between lung squamous cell carcinomas and normal lung tissues. The expression of adipophilin in lung cancer did not correlate with any clinicopathologic factors such as lymph node metastasis, patients' age, gender, tumor size, grade, and TNM stage. In Conclusion, Adipophilin was upregulated in lung adenocarcinoma, suggesting that adipophilin play an important role in tumorigenesis of lung adenocarcinoma and may serve as a potential marker for lung adenocarcinoma.

Identification of O-glycosylated proteins that are aberrantly excreted in the urine of patients with early stage ovarian cancer

Cancer is known to induce or alter the O-glycosylation of selective proteins that may eventually be excreted in the patients' urine. The present study was performed to identify O-glycosylated proteins that are aberrantly excreted in the urine of patients with early stage ovarian cancer (OCa). These urinary glycoproteins are potential biomarkers for early detection of OCa. In this study, urinary proteins of patients with early stage OCa and age-matched OCa negative women were subjected to two-dimensional gel electrophoresis and detection using a lectin that binds to the O-glycosylated proteins. Our analysis demonstrated significant enhanced expression of clusterin and leucine-rich alpha-2-glycoprotein, but lower levels of kininogen in the urine of the OCa patients compared to the controls. The different altered levels of these urinary glycoproteins were further confirmed using competitive ELISA. Our data are suggestive of the potential use of the aberrantly excreted urinary O-glycosylated proteins as biomarkers for the early detection of OCa, although this requires further validation in a large clinically representative population.

Potential tumor biomarkers identified in ovarian cyst fluid by quantitative proteomic analysis, iTRAQ

BACKGROUND

Epithelial-derived ovarian adenocarcinoma (EOC) is the most deadly gynecologic tumor, and the principle cause of the poor survival rate is diagnosis at a late stage. Screening and diagnostic biomarkers with acceptable specificity and sensitivity are lacking. Ovarian cyst fluid should harbor early ovarian cancer biomarkers because of its closeness to the tumor. We investigated ovarian cyst fluid as a source for discovering biomarkers for use in the diagnosis of EOC.

RESULTS

Using quantitative mass spectrometry, iTRAQ MS, we identified 837 proteins in cyst fluid from benign, EOC stage I, and EOC stage III. Only patients of serous histology were included in the study. Comparing the benign (n = 5) with the malignant (n = 10) group, 87 of the proteins were significantly (p < 0.05) differentially expressed. Two proteins, serum amyloid A-4 (SAA4) and astacin-like metalloendopeptidase (ASTL), were selected for verification of the iTRAQ method and external validation with immunoblot in a larger cohort with mixed histology, in plasma (n = 68), and cyst fluid (n = 68). The protein selections were based on either high significance and high fold change or abundant appearance and several peptide recognitions in the sample sets (p = 0.04, FC = 1.95) and (p < 0.001, FC = 8.48) for SAA4 and ASTL respectively. Both were found to be significantly expressed (p < 0.05), but the methods did not correlate concerning ASTL.

CONCLUSIONS

Fluid from ovarian cysts connected directly to the primary tumor harbor many possible new tumor-specific biomarkers. We have identified 87 differentially expressed proteins and validated two candidates to verify the iTRAQ method. However several of the proteins are of interest for validation in a larger setting.

Detection of differential levels of proteins in the urine of patients with endometrial cancer: analysis using two-dimensional gel electrophoresis and o-glycan binding lectin

Cancers can cause some proteins to be aberrantly excreted or released in the urine, which can be used as biomarkers. To screen for potential biomarkers for endometrial cancer (ECa), the urinary proteins from patients who were newly diagnosed with early stage ECa and untreated controls were separated using two-dimensional gel electrophoresis (2-DE) and followed by image analysis. The altered levels of zinc alpha-2 glycoprotein, alpha 1-acid glycoprotein, and CD59 were detected in the patients compared to the controls. In addition, the urine of the ECa patients was also found to contain relatively lower levels of a fragment of nebulin when the 2-DE separated urinary proteins were probed using champedak galactose binding (CGB) lectin. The different levels of the nebulin fragment were further validated by subjecting the urinary protein samples to CGB lectin affinity chromatography and analysis of the bound fractions by LC-MS/MS. Our data is suggestive of the potential use of the differentially expressed urinary proteins as biomarkers for ECa although this requires further extensive validation on clinically representative populations.

Reproducible quantification of cancer-associated proteins in body fluids using targeted proteomics

The rigorous testing of hypotheses on suitable sample cohorts is a major limitation in translational research. This is particularly the case for the validation of protein biomarkers; the lack of accurate, reproducible, and sensitive assays for most proteins has precluded the systematic assessment of hundreds of potential marker proteins described in the literature. Here, we describe a high-throughput method for the development and refinement of selected reaction monitoring (SRM) assays for human proteins. The method was applied to generate such assays for more than 1000 cancer-associated proteins, which are functionally related to candidate cancer driver mutations. We used the assays to determine the detectability of the target proteins in two clinically relevant samples: plasma and urine. One hundred eighty-two proteins were detected in depleted plasma, spanning five orders of magnitude in abundance and reaching below a concentration of 10 ng/ml. The narrower concentration range of proteins in urine allowed the detection of 408 proteins. Moreover, we demonstrate that these SRM assays allow reproducible quantification by monitoring 34 biomarker candidates across 83 patient plasma samples. Through public access to the entire assay library, researchers will be able to target their cancer-associated proteins of interest in any sample type using the detectability information in plasma and urine as a guide. The generated expandable reference map of SRM assays for cancer-associated proteins will be a valuable resource for accelerating and planning biomarker verification studies.

iTRAQ identification of candidate serum biomarkers associated with metastatic progression of human prostate cancer

A major challenge in the management of patients with prostate cancer is identifying those individuals at risk of developing metastatic disease, as in most cases the disease will remain indolent. We analyzed pooled serum samples from 4 groups of patients (n = 5 samples/group), collected prospectively and actively monitored for a minimum of 5 yrs. Patients groups were (i) histological diagnosis of benign prostatic hyperplasia with no evidence of cancer 'BPH', (ii) localised cancer with no evidence of progression, 'non-progressing' (iii) localised cancer with evidence of biochemical progression, 'progressing', and (iv) bone metastasis at presentation 'metastatic'. Pooled samples were immuno-depleted of the 14 most highly abundant proteins and analysed using a 4-plex iTRAQ approach. Overall 122 proteins were identified and relatively quantified. Comparisons of progressing versus non-progressing groups identified the significant differential expression of 25 proteins (p<0.001). Comparisons of metastatic versus progressing groups identified the significant differential expression of 23 proteins. Mapping the differentially expressed proteins onto the prostate cancer progression pathway revealed the dysregulated expression of individual proteins, pairs of proteins and 'panels' of proteins to be associated with particular stages of disease development and progression. The median immunostaining intensity of eukaryotic translation elongation factor 1 alpha 1 (eEF1A1), one of the candidates identified, was significantly higher in osteoblasts in close proximity to metastatic tumour cells compared with osteoblasts in control bone (p = 0.0353, Mann Whitney U). Our proteomic approach has identified leads for potentially useful serum biomarkers associated with the metastatic progression of prostate cancer. The panels identified, including eEF1A1 warrant further investigation and validation.

Protein quantitation using iTRAQ: Review on the sources of variations and analysis of nonrandom missingness

As a technique that allows simultaneous quantitation of proteins in multiple samples, iTRAQ (isobaric Tags for Relative and Absolute Quantitation) has gained increased interest and applications in proteomics research. Despite its success, iTRAQ data present a number of statistical challenges even after the proteins and peptides are identified and the peak areas of the reported ions are estimated for peptide intensities. In this article, we review recent studies on the analysis of iTRAQ data, the computation problems involved and the nonrandom missingness in the iTRAQ data.

Quantitative proteomics analysis by isobaric tags for relative and absolute quantitation identified Lumican as a potential marker for acute aortic dissection

Acute aortic dissection (AAD) is a serious vascular disease. Currently the diagnosis relies on clinical and radiological means whereas serum biomarkers are lacking. The purpose of this study was to identify potential serum biomarkers for AAD using isobaric tags for relative and absolute quantitation (iTRAQ) approach. A total of 120 serum samples were collected from three groups: AAD patients (n = 60), patients with acute myocardial infarction (AMI, n = 30), and healthy volunteers (n = 30), whereas the first 10 samples from each group were used for iTRAQ analysis. Using iTRAQ approach, a total of 174 proteins were identified as significantly different between AAD patients and healthy subjects. Among them, forty-six proteins increased more than twofold, full-scale analysis using serum sample for the entire 120 subjects demonstrated that Lumican level was significantly increased relative to control and AMI samples. Further, Lumican level correlated with time from onset to admission in AAD but not AMI samples. Using iTRAQ approach, our study showed that Lumican may be a potential AAD-related serum marker that may assist the diagnosis of AAD.

A systematic analysis of the effects of increasing degrees of serum immunodepletion in terms of depth of coverage and other key aspects in top-down and bottom-up proteomic analyses

Immunodepletion of clinical fluids to overcome the dominance by a few very abundant proteins has been explored but studies are few, commonly examining only limited aspects with one analytical platform. We have systematically compared immunodepletion of 6, 14, or 20 proteins using serum from renal transplant patients, analysing reproducibility, depth of coverage, efficiency, and specificity using 2-D DIGE (‘top-down’) and LC-MS/MS (‘bottom-up’). A progressive increase in protein number (≥2 unique peptides) was found from 159 in unfractionated serum to 301 following 20 protein depletion using a relatively high-throughput 1-D-LC-MS/MS approach, including known biomarkers and moderate–lower abundance proteins such as NGAL and cytokine/growth factor receptors. On the contrary, readout by 2-D DIGE demonstrated good reproducibility of immunodepletion, but additional proteins seen tended to be isoforms of existing proteins. Depletion of 14 or 20 proteins followed by LC-MS/MS showed excellent reproducibility of proteins detected and a significant overlap between columns. Using label-free analysis, greater run-to-run variability was seen with the Prot20 column compared with the MARS14 column (median %CVs of 30.9 versus 18.2%, respectively) and a corresponding wider precision profile for the Prot20. These results illustrate the potential of immunodepletion followed by 1-D nano-LC-LTQ Orbitrap Velos analysis in a moderate through-put biomarker discovery process.

Quantitative profiling of serum samples using TMT protein labelling, fractionation and LC-MS/MS

Blood-borne biomarkers are urgently required for the early detection, accurate diagnosis and prognosis of disease. Additionally, improved methods of profiling serum and plasma proteins for biomarker discovery efforts are needed. Herein, we report a quantitative method based on amino-group labelling of serum proteins (rather than peptides) with isobaric tandem mass tags (TMT) and incorporating immune-based depletion, gel-based and strong anion exchange separation of proteins prior to differential endoproteinase treatment and liquid chromatography tandem mass spectrometry. We report a generally higher level of quantitative coverage of the serum proteome compared to other peptide-based isobaric tagging approaches and show the potential of the method by applying it to a set of unique samples that pre-date the diagnosis of pancreatic cancer.

Leucine-rich alpha-2-glycoprotein-1 is upregulated in sera and tumors of ovarian cancer patients

BACKGROUND

New biomarkers that replace or are used in conjunction with the current ovarian cancer diagnostic antigen, CA125, are needed for detection of ovarian cancer in the presurgical setting, as well as for detection of disease recurrence. We previously demonstrated the upregulation of leucine-rich alpha-2-glycoprotein-1 (LRG1) in the sera of ovarian cancer patients compared to healthy women using quantitative mass spectrometry.

METHODS

LRG1 was quantified by ELISA in serum from two relatively large cohorts of women with ovarian cancer and benign gynecological disease. The expression of LRG1 in ovarian cancer tissues and cell lines was examined by gene microarray, reverse-transcriptase polymerase chain reaction (RT-PCR), Western blot, immunocytochemistry and mass spectrometry.

RESULTS

Mean serum LRG1 was higher in 58 ovarian cancer patients than in 56 healthy women (89.33 ± 77.90 vs. 42.99 ± 9.88 ug/ml; p = 0.0008) and was highest among stage III/IV patients. In a separate set of 193 pre-surgical samples, LRG1 was higher in patients with serous or clear cell ovarian cancer (145.82 ± 65.99 ug/ml) compared to patients with benign gynecological diseases (82.53 ± 76.67 ug/ml, p < 0.0001). CA125 and LRG1 levels were moderately correlated (r = 0.47, p < 0.0001). LRG1 mRNA levels were higher in ovarian cancer tissues and cell lines compared to their normal counterparts when analyzed by gene microarray and RT-PCR. LRG1 protein was detected in ovarian cancer tissue samples and cell lines by immunocytochemistry and Western blotting. Multiple iosforms of LRG1 were observed by Western blot and were shown to represent different glycosylation states by digestion with glycosidase. LRG1 protein was also detected in the conditioned media of ovarian cancer cell culture by ELISA, Western blotting, and mass spectrometry.

CONCLUSIONS

Serum LRG1 was significantly elevated in women with ovarian cancer compared to healthy women and women with benign gynecological disease, and was only moderately correlated with CA125. Ovarian cancer cells secrete LRG1 and may contribute directly to the elevated levels of LRG1 observed in the serum of ovarian cancer patients. Future studies will determine whether LRG1 may serve as a biomarker for presurgical diagnosis, disease recurrence, and/or as a target for therapy.