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The trajectory of vesicular proteomic signatures from HBV-HCC by chitosan-magnetic bead-based separation and DIA-proteomic analysis

ABSTRACT: Hepatocellular carcinoma (HCC) is a prevalent primary liver cancer often associated with chronic hepatitis B virus infection (CHB) and liver cirrhosis (LC), underscoring the critical need for biomarker discovery to improve patient outcomes. Emerging as a promising avenue for biomarker development, proteomic technology leveraging liquid biopsy from small extracellular vesicles (sEV) offers new insights. Here, we evaluated various methods for sEV isolation and identified polysaccharide chitosan (CS) as an optimal approach. Subsequently, we employed optimized CS-based magnetic beads (Mag-CS) for sEV separation from serum samples of healthy controls, CHB, LC, and HBV-HCC patients. Leveraging data-independent acquisition mass spectrometry coupled with machine learning, we uncovered potential vesicular protein biomarker signatures (PSAP, MMRN2, CAPNS1, CDH1, TIPRL, NME2) capable of distinguishing HBV-HCC from CHB, LC, and non-HCC conditions. Collectively, our findings highlight the utility of Mag-CS-based sEV isolation for identifying early detection biomarkers in HBV-HCC.

ORGANISM(S): Homo Sapiens (human)

SUBMITTER: Zengqi Tan

PROVIDER: PXD050099 | JPOST Repository | Tue Feb 25 00:00:00 GMT 2025

REPOSITORIES: jPOST

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Project description:Gene-expression profiles of hepatitis C-related, early-stage liver cirrhosis Background & Aims: Liver cirrhosis affects 1%M-bM-^HM-^R2% of population and is the major risk factor of hepatocellular carcinoma (HCC). Hepatitis C cirrhosis-related HCC is the most rapidly increasing cause of cancer death in the US. Non-invasive methods have been developed to identify patients with asymptomatic, early-stage cirrhosis, increasing the burden of HCC surveillance, but biomarkers are needed to identify patients with cirrhosis who are most in need of surveillance. We investigated whether a liver-derived 186-gene signature previously associated with outcomes of patients with HCC is prognostic for patients newly diagnosed with cirrhosis but without HCC. Methods: We performed gene expression profile analysis of formalin-fixed needle biopsies from the livers of 216 patients with hepatitis C-related early-stage (Child-Pugh class A) cirrhosis who were prospectively followed for a median of 10 years at an Italian center. We evaluated whether the 186-gene signature was associated with death, progression of cirrhosis, and development of HCC. Results: Fifty-five (25%), 101 (47%), and 60 (28%) patients were classified as having poor-, intermediate-, and good-prognosis signatures, respectively. In multivariable Cox regression modeling, the poor-prognosis signature was significantly associated with death (P=.004), progression to advanced cirrhosis (P<.001), and development of HCC (P=.009). The 10-year rates of survival were 63%, 74%, and 85% and the annual incidences of HCC were 5.8%, 2.2%, and 1.5% for patients with poor-, intermediate-, and good-prognosis signatures, respectively. Conclusions: A 186-gene signature used to predict outcomes of patients with HCC is also associated with outcomes of patients with hepatitis C-related early-stage cirrhosis. This signature might be used to identify patients with cirrhosis in most need of surveillance and strategies to prevent their development of HCC. 216 liver biopsy specimens

Project description:In cancer management, early and accurate diagnosis of hepatocellular carcinoma (HCC) is important for enhancing survival rate of patients. Currently, serum alpha-fetoprotein (AFP) is the only one biomarker for detection of HCC. However, serum AFP is not satisfactory for diagnosis of HCC due to its low accuracy (about 60-70%). In this study, we collected 109 serum samples (discovery set) from healthy control (HC) and patients with chronic hepatitis B (CHB), liver cirrhosis (LC) and HCC, and analyzed them with custom lncRNA microarray. Profiling analysis shows 181 differentially expressed lncRNAs between HCs and patients with CHB, LC and HCC. Then a 48-lncRNA diagnostic signature was identified with 100% predictive accuracy for all subjects in the discovery set. This diagnostic signature was verified with a cross-validation analysis in the discovery set. To further corroborate the signature, we gathered another 66 serum samples (validation set) and also analyzed them with microarray. The result indicates that the same signature has similar diagnostic accuracy for HC (100%), CHB (73%), LC (88%) and HCC (95%), implying a reproducible diagnostic biomarker for HCC. Receiver operating characteristic (ROC) analysis exhibits that this signature has significantly higher diagnostic accuracy for HCC and non-cancerous subjects (area under curve [AUC]: 0.994) than AFP (AUC: 0.773) in the discovery set and this was also verified in the validation set (0.964 vs 0.792). More importantly, the signature detected small HCC (<3cm) with 100% (13/13) accuracy while AFP with only 61.5% (8/13). Altogether, this study demonstrates that the serum 48-lncRNA signature is not only a powerful and sensitive biomarker for diagnosis of HCC but also a potential biomarker for LC. ***************************************************************** Submitter declares these data are subject to patent number ZL 2016 1 0397094. *****************************************************************

Project description:Background: Of Hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC), 85%-90% of cases develop from liver cirrhosis, and circular RNAs (circRNAs) have important roles in this process; however, differences in serum circRNA expression profiles between patients with HBV-related cirrhosis and those with HCC have not been studied. Methods: Serum RNA was extracted from patients with HCC and cirrhosis (n = 5 per group) and used for microarray analysis of circRNA expression profiles. Bioinformatics analyses, including clustering, differential expression, and construction of a ceRNA network, were performed. Quantitative real-time reverse transcription PCR validation analysis was conducted using samples from patients with HBV-related cirrhosis (n = 88) and HCC (n = 73). Further, statistical analyses were used to analyze the potential function and value of selected circRNAs with expression differing between the HBV-related cirrhosis and HCC groups. Results: Cluster analysis revealed 8 up-regulated and 80 down-regulated circRNAs. Further, qRT-PCR analysis showed that circRNA_0000367 expression was consistent with that detected by microarray experiments, with significantly lower levels in patients with HBV-related HCC than those with HBV-related cirrhosis. CircRNA_0000367 expression levels were also significantly lower in patients with drug-resistant HBV and those with HBV-related cirrhosis with Model for End-Stage Liver Disease score < 10. Further, circRNA_00000367 expression levels were lower in patients with HBV-related cirrhosis who progressed to HCC. Analysis of the lncRNA-miRNA-mRNA ceRNA network identified 39 miRNAs and 24 mRNAs involved in circRNA_00000367 networks; these target genes were involved in various biological processes and signaling pathways. Conclusion: Serum cicrRNA_0000367 is a potential HCC biomarker in patients with HBV-related cirrhosis, where down-regulation of cicrRNA_0000367 in HBV-related cirrhosis may be associated with progression to HCC.

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The trajectory of vesicular proteomic signatures from HBV-HCC by chitosan-magnetic bead-based separation and DIA-proteomic analysis

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