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

Caveolae-mediated endocytosis of extracellular QSOX1b modulates the migration of fibroblasts

Quiescin/sulfhydryl oxidase (QSOX1) is a secreted flavoprotein that modulates cellular proliferation, migration and adhesion, roles attributed to its ability to organize the extracellular matrix. We previously showed that exogenously added QSOX1b induces smooth muscle cells migration in a process that depends on its enzymatic activity and that is mediated by hydrogen peroxide derived from Nox1, a catalytic subunit of NAD(P)H oxidases. Here, we report that exogenous QSOX1b also stimulates the migration of L929 fibroblasts and that this effect is regulated by its endocytosis. The use of endocytosis inhibitors and caveolin 1-knockdown demonstrated that this endocytic pathway is caveola-mediated. QSOX1b colocalized with Nox1 in intracellular vesicles, as detected by confocal fluorescence, suggesting that extracellular QSOX1b is endocytosed with the transmembrane Nox1. These results reveal that endosomal QSOX1b is a novel intracellular redox regulator of cell migration.

Polymeric immunoglobulin receptor and galectin-3-binding protein are raised in biliary atresia: Reveals a proteomic-based study

To identify and evaluate differentially expressed plasma proteins in biliary atresia (BA), we performed plasma proteome profiling using liquid chromatography with tandem mass spectrometry (LC-MS/MS) in 20 patients with BA and 10 control children. Serological assays validated the most significant and highly upregulated proteins in a cohort of 45 patients and 15 controls. Bioinformatics tools were used for functional classification and protein-protein interactions of differentially expressed proteins (DEPs). Of 405 proteins detected in patients and 360 in controls, 242 proteins, each with ≥2 unique peptides (total of 3230 peptides), were common in both groups. Compared to controls, 90 proteins in patients were differentially expressed and were dysregulated. Twenty-five were significantly upregulated with polymeric immunoglobulin receptor (PIgR), galectin-3-binding protein (Gal-3BP), complement C2, the most prominent, and 15 had low expression. The bioinformatic analysis revealed functional interaction between DEPs and their role in an inflammatory immune response. Enzyme immunoassay for PIgR and Gal-3BP in patients' plasma showed their levels raised significantly (p = 0.0021 and p = 0.0369, respectively). The PIgR and Gal-3BP are novel proteins upregulated in BA and may be tested further for their utility as potential circulating disease biomarker(s). SIGNIFICANCE: The study shows that plasma PIgR and GAL-3BP levels are significantly raised in infants with BA within the first 3 months of life. If tested in a larger cohort, these proteins may be found to have their diagnostic potential and utility as disease biomarkers. The study also provides valuable information on the involvement of several DEPs in innate immune response, chronic inflammation, and fibrosis. This strengthens the hypothesis that the immune-mediated inflammatory processes are responsible for the progressive nature of BA.

Role of CD14 in human disease

The cell surface antigen CD14 is primarily understood to act as a co-receptor for toll-like receptors (TLRs) to activate innate immunity responses to pathogens and tissue injury in macrophages and monocytes. However, roles for CD14 are increasingly being uncovered in disease responses in epithelial and endothelial cells. Consistent with these broader functions, CD14 expression is altered in a variety of non-immune cell types in response to a several of disease states. Moreover, soluble CD14 activated by factors from both pathogens and tissue damage may initiate signalling in a variety of non-immune cells. This review examined the current understanding CD14 in innate immunity as well as its potential functions in nonimmune cells and associated human diseases.

Biomarkers of gut barrier dysfunction and risk of hepatocellular carcinoma in the REVEAL-HBV and REVEAL-HCV cohort studies

Gut barrier dysfunction can result in the liver being exposed to an elevated level of gut-derived bacterial products via portal circulation. Growing evidence suggests that systemic exposure to these bacterial products promotes liver diseases including hepatitis, cirrhosis, and hepatocellular carcinoma (HCC). However, prospective studies have not examined the association between biomarkers of gut barrier dysfunction and HCC risk in a population of hepatitis B or C viral (HBV/HCV) carriers. We investigated whether prediagnostic, circulating biomarkers of gut barrier dysfunction were associated with HCC risk, using the Risk Evaluation of Viral Load Elevation and Associated Liver Disease/Cancer (REVEAL)-HBV and REVEAL-HCV cohorts from Taiwan. REVEAL-HBV included 185 cases and 161 matched controls, and REVEAL-HCV 96 cases and 96 matched controls. The biomarkers quantitated were immunoglobulin A (IgA), IgG, and IgM against lipopolysaccharide (LPS) and flagellin, soluble CD14 (an LPS coreceptor), and LPS-binding protein (LBP). Odds ratios (ORs) and 95% confidence intervals (CIs) for associations between biomarker levels and HCC were calculated using multivariable-adjusted logistic regression. A doubling of the circulating levels of antiflagellin IgA or LBP was associated with a 76% to 93% increased risk of HBV-related HCC (OR per one unit change in log2 antiflagellin IgA = 1.76, 95% CI: 1.06-2.93; OR for LBP = 1.93, 95% CI: 1.10-3.38). None of the other markers were associated with an increased risk of HBV-related or HCV-related HCC. Results were similar when cases diagnosed in the first 5 years of follow-up were excluded. Our findings contribute to understanding the interplay of gut barrier dysfunction and primary liver cancer etiology.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

Quantitative Proteomics in Translational Absorption, Distribution, Metabolism, and Excretion and Precision Medicine

A reliable translation of in vitro and preclinical data on drug absorption, distribution, metabolism, and excretion (ADME) to humans is important for safe and effective drug development. Precision medicine that is expected to provide the right clinical dose for the right patient at the right time requires a comprehensive understanding of population factors affecting drug disposition and response. Characterization of drug-metabolizing enzymes and transporters for the protein abundance and their interindividual as well as differential tissue and cross-species variabilities is important for translational ADME and precision medicine. This review first provides a brief overview of quantitative proteomics principles including liquid chromatography-tandem mass spectrometry tools, data acquisition approaches, proteomics sample preparation techniques, and quality controls for ensuring rigor and reproducibility in protein quantification data. Then, potential applications of quantitative proteomics in the translation of in vitro and preclinical data as well as prediction of interindividual variability are discussed in detail with tabulated examples. The applications of quantitative proteomics data in physiologically based pharmacokinetic modeling for ADME prediction are discussed with representative case examples. Finally, various considerations for reliable quantitative proteomics analysis for translational ADME and precision medicine and the future directions are discussed. SIGNIFICANCE STATEMENT: Quantitative proteomics analysis of drug-metabolizing enzymes and transporters in humans and preclinical species provides key physiological information that assists in the translation of in vitro and preclinical data to humans. This review provides the principles and applications of quantitative proteomics in characterizing in vitro, ex vivo, and preclinical models for translational research and interindividual variability prediction. Integration of these data into physiologically based pharmacokinetic modeling is proving to be critical for safe, effective, timely, and cost-effective drug development.

Advances in High Throughput Proteomics Profiling in Establishing Potential Biomarkers for Gastrointestinal Cancer

Gastrointestinal cancers (GICs) remain the most diagnosed cancers and accounted for the highest cancer-related death globally. The prognosis and treatment outcomes of many GICs are poor because most of the cases are diagnosed in advanced metastatic stages. This is primarily attributed to the deficiency of effective and reliable early diagnostic biomarkers. The existing biomarkers for GICs diagnosis exhibited inadequate specificity and sensitivity. To improve the early diagnosis of GICs, biomarkers with higher specificity and sensitivity are warranted. Proteomics study and its functional analysis focus on elucidating physiological and biological functions of unknown or annotated proteins and deciphering cellular mechanisms at molecular levels. In addition, quantitative analysis of translational proteomics is a promising approach in enhancing the early identification and proper management of GICs. In this review, we focus on the advances in mass spectrometry along with the quantitative and functional analysis of proteomics data that contributes to the establishment of biomarkers for GICs including, colorectal, gastric, hepatocellular, pancreatic, and esophageal cancer. We also discuss the future challenges in the validation of proteomics-based biomarkers for their translation into clinics.

Identifying Potential New Gene Expression-Based Biomarkers in the Peripheral Blood Mononuclear Cells of Hepatitis B-Related Hepatocellular Carcinoma

OBJECTIVE

The analysis of the gene expression of peripheral blood mononuclear cells (PBMCs) is important to clarify the pathogenesis of hepatocellular carcinoma (HCC) and the detection of suitable biomarkers. The purpose of this investigation was to use RNA-sequencing to screen the appropriate differentially expressed genes (DEGs) in the PBMCs for the HCC.

METHODS

The comprehensive transcriptome of extracted RNA of PBMC (n = 20) from patients with chronic hepatitis B (CHB), liver cirrhosis, and early stage of HCC (5 samples per group) was carried out using RNA-sequencing. All raw RNA-sequencing data analyses were performed using conventional RNA-sequencing analysis tools. Next, gene ontology (GO) analyses were carried out to elucidate the biological processes of DEGs. Finally, relative transcript abundance of selected DEGs was verified using qRT-PCR on additional validation groups.

RESULTS

Specifically, 13, 1262, and 1450 DEGs were identified for CHB, liver cirrhosis, and HCC, when compared with the healthy controls. GO enrichment analysis indicated that HCC is closely related to the immune response. Seven DEGs (TYMP, TYROBP, CD14, TGFBI, LILRA2, GNLY, and GZMB) were common to HCC, cirrhosis, and CHB when compared to healthy controls. The data revealed that the expressions of these 7 DEGs were consistent with those from the RNA-sequencing results. Also, the expressions of 7 representative genes that had higher sensitivity were obtained by receiver operating characteristic analysis, which indicated their important diagnostic accuracy for HBV-HCC.

CONCLUSION

This study provides us with new horizons into the biological process and potential prospective clinical diagnosis and prognosis of HCC in the near future.

Evaluation of dithiothreitol-oxidizing capacity (DOC) as a serum biomarker for chronic hepatitis B in patients exhibiting normal alanine aminotransferase levels: a pilot study towards better monitoring of disease

BACKGROUND

Alanine aminotransferase (ALT) is the most commonly used serum biomarker for chronic liver diseases (CLDs) but may not accurately reflect hepatic disorders and easily underestimates hepatic fibrosis. The previously revised upper limit of normal (ULN) of ALT (19 U/L for women and 30 U/L for men) increases its sensitivity but yields higher numbers of false-positives. Moreover, CLDs patients with ALT lower than the revised ULN may nonetheless have progression of disease. Therefore there is a need of novel biomarkers to complement the use of ALT. Here we have evaluated measurements of serum dithiothreitol-oxidizing capacity (DOC) in cohorts of chronic hepatitis B patients with different stages of disease as an exploratory pilot study for this purpose.

METHODS

Serum samples obtained from healthy persons and from chronic hepatitis B patients with normal ALT values were used for sensitivity evaluation. The hepatitis B patients encompassed end-stage liver diseases (ELD), chronic hepatitis B (CHB), CHB with persistently normal ALT (CHB-P) and inactive carriers (ICs). Sensitivity was also evaluated with samples from patients with other diseases. The study period was March 2018 to December 2020.

FINDINGS

DOC was found to be a robust biomarker that may become complementary to ALT measurements, especially in patients displaying low ALT levels. ROC analyses indicated that the AUC values of DOC reached 0.983 and 0.956 in ELD and CHB patients exhibiting normal ALT levels, respectively. Importantly, the AUC values of DOC reached 0.852 and 0.844 in CHB-P patients and ICs, respectively. Such AUC values permit screening and continued monitoring, corresponding to over 30% and 50% sensitivity with 99% and 95% specificity for CHB-P and ICs, respectively. DOC was also significantly correlated with indicators for fibrosis, assessing both APRI (Pearson r = 0.4905, P < 0.0001) and FIB-4 (Pearson r = 0.4421, P < 0.0001). Surprisingly, the AUC values of DOC in the hepatitis B patients with ALT levels lower than the revised ULN were not compromised. In examined non-liver diseases, DOC was low and normal, including in patients with acute myocardial infection displaying increased ALT levels.

INTERPRETATIONS

The results suggest that DOC can be promising as a complementary biomarker used in addition to ALT for monitoring of disease in chronic hepatitis B patients, especially when ALT levels are normal. DOC should be further evaluated for possible clinical use as biomarker also in other CLDs.

FUNDING

This study was funded by the National Natural Science Foundation of China (Grant numbers: 31771971 and 32001013).

Soluble cluster of differentiation 14 levels elevated in bile from gallbladder cancer cases from Shanghai, China

Elevated systemic levels of soluble cluster of differentiation 14 (sCD14) have been associated with gallbladder cancer (GBC), but the association with sCD14 levels within the gallbladder has not been investigated. Here, we evaluated sCD14 in the bile of 41 GBC cases and 117 gallstone controls with data on 65 bile inflammation markers. We examined the relationship between bile sCD14 levels and GBC using logistic regression and stratified the analysis by stage. We included GBC-associated inflammatory biomarkers in the model to evaluate the influence of local inflammation. Bile sCD14 levels (third versus first tertile) were associated with GBC (adjusted odds ratio [OR]: 3.0, 95% confidence interval [CI]: 1.2–8.0). The association was equally strong for stage I/II (OR: 3.3, 95% CI: 0.9–15.6) and stage III/IV (OR: 3.2, 95% CI: 1.0–12.4) cancers. Including the GBC-associated inflammatory markers in the model removed the association between bile sCD14 and GBC (OR: 1.0, 95% CI: 0.3–3.5). The findings suggest that immune activation within the gallbladder may be related to GBC development, and the effect of sCD14 is influenced by inflammation. Similar associations across tumor stages suggest that elevated bile sCD14 levels may reflect changes early in GBC pathogenesis. Associations between GBC and sCD14 levels in both bile and plasma suggest sCD14 could be a potential biomarker for GBC.

Quantitative proteomics characterization of cancer biomarkers and treatment

Cancer accounted for 16% of all death worldwide in 2018. Significant progress has been made in understanding tumor occurrence, progression, diagnosis, treatment, and prognosis at the molecular level. However, genomics changes cannot truly reflect the state of protein activity in the body due to the poor correlation between genes and proteins. Quantitative proteomics, capable of quantifying the relatively different protein abundance in cancer patients, has been increasingly adopted in cancer research. Quantitative proteomics has great application potentials, including cancer diagnosis, personalized therapeutic drug selection, real-time therapeutic effects and toxicity evaluation, prognosis and drug resistance evaluation, and new therapeutic target discovery. In this review, the development, testing samples, and detection methods of quantitative proteomics are introduced. The biomarkers identified by quantitative proteomics for clinical diagnosis, prognosis, and drug resistance are reviewed. The challenges and prospects of quantitative proteomics for personalized medicine are also discussed.

The use of minimally invasive biomarkers for the diagnosis and prognosis of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a common cause of cancer-related deaths worldwide. Despite advances in systemic therapies, patient survival remains low due to late diagnosis and frequent underlying liver diseases. HCC diagnosis generally relies on imaging and liver tissue biopsy. Liver biopsy presents limitations because it is invasive, potentially risky for patients and it frequently misrepresents tumour heterogeneity. Recently, liquid biopsy has emerged as a way to monitor cancer progression in a non-invasive manner. Tumours shed content into the bloodstream, such as circulating tumour cells (CTCs), circulating nucleic acids, extracellular vesicles and proteins, that can be isolated from biological fluids of patients with HCC. These biomarkers provide knowledge regarding the genetic landscape of tumours and might be used for diagnostic or prognostic purposes. In this review, we summarize recent literature on circulating biomarkers for HCC, namely CTCs, circulating tumour DNA (ctDNA), RNA, extracellular vesicles and proteins, and their clinical relevance in HCC.

Computational advances of tumor marker selection and sample classification in cancer proteomics

Cancer proteomics has become a powerful technique for characterizing the protein markers driving transformation of malignancy, tracing proteome variation triggered by therapeutics, and discovering the novel targets and drugs for the treatment of oncologic diseases. To facilitate cancer diagnosis/prognosis and accelerate drug target discovery, a variety of methods for tumor marker identification and sample classification have been developed and successfully applied to cancer proteomic studies. This review article describes the most recent advances in those various approaches together with their current applications in cancer-related studies. Firstly, a number of popular feature selection methods are overviewed with objective evaluation on their advantages and disadvantages. Secondly, these methods are grouped into three major classes based on their underlying algorithms. Finally, a variety of sample separation algorithms are discussed. This review provides a comprehensive overview of the advances on tumor maker identification and patients/samples/tissues separations, which could be guidance to the researches in cancer proteomics.

iTRAQ and PRM-based quantitative proteomics in early recurrent spontaneous abortion: biomarkers discovery

Background

Early recurrent spontaneous abortion (ERSA) is a common condition in pregnant women. To prevent ERSA is necessary to look for abortion indicators, such as hormones and proteins, in an early stage.

Methods

Thirty patients with ERSA were enrolled in the case group. In the control group, we recruited 30 healthy women without a history of miscarriage undergoing voluntary pregnancy termination. The differentially expressed proteins in the serum were identified between the two groups using PRM and iTRAQ.

Results

Seventy-eight differentially expressed proteins were identified. Using GO functional annotation and KEGG pathway analysis, we detected that the most significant changes occurred in the pathway of Fc gamma R-mediated phagocytosis. Meanwhile, using PRM, we identified three proteins that were closely related to abortion, B4DTF1 (highly similar to PSG1), P11464 (PSG1), and B4DF70 (highly similar to Prdx-2). The levels of B4DTF1 and P11464 were down-regulated, while the level of B4DF70 was up-regulated.

Conclusions

CD45, PSG1, and Prdx-2, were significantly dysregulated in the samples of ERSA and could become important biomarkers for the prediction and diagnosis of ERSA. Larger‑scale studies are required to confirm the diagnostic value of these biomarkers.

Molecular Inhibitor of QSOX1 Suppresses Tumor Growth In Vivo

Quiescin sulfhydryl oxidase 1 (QSOX1) is an enzyme overexpressed by many different tumor types. QSOX1 catalyzes the formation of disulfide bonds in proteins. Because short hairpin knockdowns (KD) of QSOX1 have been shown to suppress tumor growth and invasion in vitro and in vivo, we hypothesized that chemical compounds inhibiting QSOX1 enzymatic activity would also suppress tumor growth, invasion, and metastasis. High throughput screening using a QSOX1-based enzymatic assay revealed multiple potential QSOX1 inhibitors. One of the inhibitors, known as "SBI-183," suppresses tumor cell growth in a Matrigel-based spheroid assay and inhibits invasion in a modified Boyden chamber, but does not affect viability of nonmalignant cells. Oral administration of SBI-183 inhibits tumor growth in 2 independent human xenograft mouse models of renal cell carcinoma. We conclude that SBI-183 warrants further exploration as a useful tool for understanding QSOX1 biology and as a potential novel anticancer agent in tumors that overexpress QSOX1.

Biomarkers vs imaging in the early detection of hepatocellular carcinoma and prognosis

Hepatocellular carcinoma (HCC) is the 5^th most frequently diagnosed cancer in the world, according to the World Health Organization. The incidence of HCC is between 3/100000 and 78.1/100000, with a high incidence reported in areas with viral hepatitis B and hepatitis C, thus affecting Asia and Africa predominantly. Several international clinical guidelines address HCC diagnosis and are structured according to the geographical area involved. All of these clinical guidelines, however, share a foundation of diagnosis by ultrasound surveillance and contrast imaging techniques, particularly computed tomography, magnetic resonance imaging, and sometimes contrast-enhanced ultrasound. The primary objective of this review was to systematically summarize the recent published studies on the clinical utility of serum biomarkers in the early diagnosis of HCC and for the prognosis of this disease.

Current Challenges and Opportunities in Treating Glioblastoma

Glioblastoma multiforme (GBM), the most common and aggressive primary brain tumor, has a high mortality rate despite extensive efforts to develop new treatments. GBM exhibits both intra- and intertumor heterogeneity, lending to resistance and eventual tumor recurrence. Large-scale genomic and proteomic analysis of GBM tumors has uncovered potential drug targets. Effective and “druggable” targets must be validated to embark on a robust medicinal chemistry campaign culminating in the discovery of clinical candidates. Here, we review recent developments in GBM drug discovery and delivery. To identify GBM drug targets, we performed extensive bioinformatics analysis using data from The Cancer Genome Atlas project. We discovered 20 genes, BOC, CLEC4GP1, ELOVL6, EREG, ESR2, FDCSP, FURIN, FUT8-AS1, GZMB, IRX3, LITAF, NDEL1, NKX3-1, PODNL1, PTPRN, QSOX1, SEMA4F, TH, VEGFC, and C20orf166AS1 that are overexpressed in a subpopulation of GBM patients and correlate with poor survival outcomes. Importantly, nine of these genes exhibit higher expression in GBM versus low-grade glioma and may be involved in disease progression. In this review, we discuss these proteins in the context of GBM disease progression. We also conducted computational multi-parameter optimization to assess the blood-brain barrier (BBB) permeability of small molecules in clinical trials for GBM treatment. Drug delivery in the context of GBM is particularly challenging because the BBB hinders small molecule transport. Therefore, we discuss novel drug delivery methods, including nanoparticles and prodrugs. Given the aggressive nature of GBM and the complexity of targeting the central nervous system, effective treatment options are a major unmet medical need. Identification and validation of biomarkers and drug targets associated with GBM disease progression present an exciting opportunity to improve treatment of this devastating disease.

Liver cancer-associated changes to the proteome: what deserves clinical focus?

INTRODUCTION

Hepatocellular carcinoma (HCC) is recognized as the fifth most common neoplasm and currently represents the second leading form of cancer-related death worldwide. Despite great progress has been done in the understanding of its pathogenesis, HCC represents a heavy societal and economic burden as most patients are still diagnosed at advanced stages and the 5-year survival rate remain below 20%. Early detection and revolutionary therapies that rely on the discovery of new molecular biomarkers and therapeutic targets are therefore urgently needed to develop precision medicine strategies for a more efficient management of patients. Areas covered: This review intends to comprehensively analyse the proteomics-based research conducted in the last few years to address some of the principal still open riddles in HCC biology, based on the identification of molecular drivers of tumor progression and metastasis. Expert commentary: The technical advances in mass spectrometry experienced in the last decade have significantly improved the analytical capacity of proteome wide studies. Large-scale protein and protein variant (post-translational modifications) identification and quantification have allowed detailed dissections of molecular mechanisms underlying HCC progression and are already paving the way for the identification of clinically relevant proteins and the development of their use on patient care.

iTRAQ analysis of urinary proteins: Potential use of gelsolin and osteopontin to distinguish benign thyroid goiter from papillary thyroid carcinoma

BACKGROUND

Benign thyroid goiter (BTG) and papillary thyroid carcinoma (PTC) are often interchangeably misdiagnosed.

METHODS

Pooled urine samples of patients with BTG (n=10), patients with PTC (n=9) and healthy controls (n=10) were subjected to iTRAQ analysis and immunoblotting.

RESULTS

The ITRAQ analysis of the urine samples detected 646 proteins, 18 of which showed significant altered levels (p<0.01; fold-change>1.5) between patients and controls. Whilst four urinary proteins were commonly altered in both BTG and PTC patients, 14 were unique to either BTG or PTC. Amongst these, four proteins were further chosen for validation using immunoblotting, and the enhanced levels of osteopontin in BTG patients and increased levels of a truncated gelsolin fragment in PTC patients, relative to controls, appeared to corroborate the findings of the iTRAQ analysis.

CONCLUSION

The data of the present study is suggestive of the potential application of urinary osteopontin and gelsolin to discriminate patients with BTG from those with PTC non-invasively. However, this needs to be further validated in studies of individual urine samples.