Targeted Proteins Reveal Cathepsin D as a Novel Biomarker in Differentiating Hepatocellular Carcinoma from Cirrhosis and Other Liver Cancers

Objective: Hepatocellular carcinoma (HCC) represents a global health concern, particularly in Southeast Asia where hepatitis B virus (HBV) infection is common. In this study, we applied tissue-based proteomics to identify novel serological proteins for HCC and validated their performance in serum specimens. Methods: In a discovery set, liver tissue specimens of HBV-related HCC, intrahepatic cholangiocarcinoma (iCCA) and colorectal cancer with liver metastasis (CRLM) were analyzed using mass spectrometry (LTQ-Orbitrap-XL). A subset of proteins that showed highly expressed in HCC were then confirmed by Western blotting. Additionally, clinical significance of selected candidate proteins was tested in serum samples of 80 patients with HBV-related HCC, 50 patients with HBV-related liver cirrhosis and 30 healthy controls. Results: Based on LTQ-Orbitrap-XL mass spectrometer, various differentially expressed proteins (DEPs) between tumor and adjacent non-tumor tissues were identified. These included 77 DEPs for HCC, 77 DEPs for iCCA and 55 DEPs for CRLM. Among selected candidate proteins, annexin A2 and cathepsin D were confirmed to be overexpressed in HCC tissue by Western blot analysis. In a validate cohort, serum cathepsin D level, but not annexin A2, was significantly higher in HCC compared with the non-HCC groups. Serum cathepsin D level was also positively correlated with tumor size and tumor stage. Additionally, the combined assay of serum cathepsin D and alpha-fetoprotein had a high sensitivity in detecting early HCC (83%) and intermediate/advanced HCC (96%). Moreover, patients with low serum cathepsin D (<305 ng/mL) displayed significantly better overall survival than those whose serum levels were high (≥305 ng/mL). Conclusions: Proteomics and subsequent validation revealed cathepsin D as a novel biomarker for HCC. Apart from its diagnostic role, serum cathepsin D might also serve as a prognostic biomarker of HCC. Additional large-scale studies are needed to verify our finding

Proteomic insight towards key modulating proteins regulated by the aryl hydrocarbon receptor involved in ovarian carcinogenesis and chemoresistance

Gynecological malignancies pose a severe threat to female lives. Ovarian cancer (OC), the most lethal gynecological malignancy, is clinically presented with chemoresistance and a higher relapse rate. Several studies have highly correlated the incidence of OC to exposure to environmental pollutants, such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), a process mainly mediated through activating the aryl hydrocarbon receptor (AhR). We have previously reported that exposure of OC cells to TCDD, an AhR activator, significantly modulated the expression of several genes that play roles in stemness and chemoresistance. However, the effect of AhR activation on the whole OC cell proteome aiming at identifying novel druggable targets for both prevention and treatment intervention purposes remains unrevealed. For this purpose, we conducted a comparative proteomic analysis of OC cells A2780 untreated/treated with TCDD for 24 h using a mass spectrometry-based label-free shotgun proteomics approach. The most significantly dysregulated proteins were validated by Western blot analysis. Our results showed that upon AhR activation by TCDD, out of 2598 proteins identified, 795 proteins were upregulated, and 611 were downregulated. STRING interaction analysis and KEGG-Reactome pathway analysis approaches identified several significantly dysregulated proteins that were categorized to be involved in chemoresistance, cancer progression, invasion and metastasis, apoptosis, survival, and prognosis in OC. Importantly, selected dysregulated genes identified by the proteomic study were validated at the protein expression levels by Western blot analysis. In conclusion, this study provides a better understanding of the the cross-talk between AhR and several other molecular signaling pathways and the role and involvement of AhR in ovarian carcinogenesis and chemoresistance. Moreover, the study suggests that AhR is a potential therapeutic target for OC prevention and maintenance. Significance: To our knowledge, this is the first study that investigates the role and involvement of AhR and its regulated genes in OC by performing a comparative proteomic analysis to identify the critical proteins with a modulated expression upon AhR activation. We found AhR activation to play a tumor-promoting and chemoresistance-inducing role in the pathogenesis of OC. The results of our study help to devise novel therapeutics for better management and prevention and open the doors to finding novel biomarkers for the early detection and prognosis of OC.This study was supported by Qatar University International Research Collaboration Cofund Grant No. IRCC-2022-484, Qatar University Collaborative Grant no. QUCG-CPH-23/24-154, Hamad Medical Corporation, Medical Research Center Grant no. MRC-01-21-820, Doha, Qatar and MU's Strategic Research Fund, Mahidol University, Bangkok, Thailand. Open Access funding is provided by the Qatar National Library.Scopu

A database of naturally occurring human urinary peptides and proteins for use in clinical applications

Owing to its availability, ease of collection and correlation with (patho-) physiology, urine is an attractive source for clinical proteomics. However, the lack of comparable datasets from large cohorts has greatly hindered development in this field. Here we report the establishment of a high resolution proteome database of naturally occurring human urinary peptides and proteins - ranging from 800-17,000 Da - from over 3,600 individual samples using capillary electrophoresis coupled to mass spectrometry, yielding an average of 1,500 peptides per sample. All processed data were deposited in an SQL database, currently containing 5,010 relevant unique urinary peptides that serve as classifiers for diagnosis and monitoring of diseases, including kidney and vascular diseases. Of these, 352 have been sequenced to date. To demonstrate the applicability of this database, two examples of disease diagnosis were provided: For renal damage diagnosis, patients with a specific renal disease were identified with high specificity and sensitivity in a blinded cohort of 131 individuals. We further show definition of biomarkers specific for immunosuppression and complications after transplantation (Kaposi's sarcoma). Due to its high information content, this database will be a powerful tool for the validation of biomarkers for both renal and non-renal diseases

Proteomics in Dengue Virus Infection: Host Response in Human Endothelial Cells

This mini-review highlights important findings obtained from a series of our recent proteomic studies of human endothelial cells in response to dengue virus infection, which remains common in tropical/subtropical countries. These findings shed light onto mechanisms of vascular leakage, which is a fatal complication of this disease

Defining and Systematic Analyses of Aggregation Indices to Evaluate Degree of Calcium Oxalate Crystal Aggregation

Crystal aggregation is one of the most crucial steps in kidney stone pathogenesis. However, previous studies of crystal aggregation were rarely done and quantitative analysis of aggregation degree was handicapped by a lack of the standard measurement. We thus performed an in vitro assay to generate aggregation of calcium oxalate monohydrate (COM) crystals with various concentrations (25–800 μg/ml) in saturated aggregation buffer. The crystal aggregates were analyzed by microscopic examination, UV-visible spectrophotometry, and GraphPad Prism6 software to define a total of 12 aggregation indices (including number of aggregates, aggregated mass index, optical density, aggregation coefficient, span, number of aggregates at plateau time-point, aggregated area index, aggregated diameter index, aggregated symmetry index, time constant, half-life, and rate constant). The data showed linear correlation between crystal concentration and almost all of these indices, except only for rate constant. Among these, number of aggregates provided the greatest regression coefficient (r = 0.997; p &lt; 0.001), whereas the equally second rank included aggregated mass index and optical density (r = 0.993; p &lt; 0.001 and r = −0.993; p &lt; 0.001, respectively) and the equally forth were aggregation coefficient and span (r = 0.991; p &lt; 0.001 for both). These five indices are thus recommended as the most appropriate indices for quantitative analysis of COM crystal aggregation in vitro