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Extracellular vesicles as potential biomarkers for diagnosis and recurrence detection of hepatocellular carcinoma.

ABSTRACT: Hepatocellular carcinoma (HCC) is the most common primary malignant liver tumor and a leading cause of cancer-related deaths worldwide. However, current diagnostic tools are often invasive and technically limited. In the last decade, non-invasive liquid biopsies have transformed the field of clinical oncology, showcasing the potential of various liquid-biopsy derived analytes, including extracellular vesicles (EVs), to diagnose and monitor HCC progression and metastatic spreading, serving as promising novel biomarkers. A prospective single-center cohort study including 37 HCC patients and 20 patients with non-malignant liver disease (NMLD), as a control group, was conducted. Serum EVs of both groups were analyzed before and after liver surgery. The study utilized microbead-based magnetic particle sorting and flow cytometry to detect 37 characteristic surface proteins of EVs. Furthermore, HCC patients who experienced tumor recurrence (R-HCC) within 12 months after surgery were compared to HCC patients without recurrence (NR-HCC). EVs of R-HCC patients (n = 12/20) showed significantly lower levels of CD31 compared to EVs of NR-HCC patients (p = 0.0033). EVs of NMLD-group showed significantly higher expressions of CD41b than EVs of HCC group (p = 0.0286). The study determined significant short-term changes in CD19 dynamics in EVs of the NMLD-group, with preoperative values being significantly higher than postoperative values (p = 0.0065). This finding of our pilot study suggests EVs could play a role as potential targets for the development of diagnostic and therapeutic approaches for the early and non-invasive detection of HCC recurrence. Further, more in-depth analysis of the specific EV markers are needed to corroborate their potential role as diagnostic and therapeutic targets for HCC.

SUBMITTER: Juratli MA

PROVIDER: S-EPMC10912302 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Extracellular vesicles as potential biomarkers for diagnosis and recurrence detection of hepatocellular carcinoma.

Juratli Mazen A MA Pollmann Nicola S NS Oppermann Elsie E Mohr Annika A Roy Dhruvajyoti D Schnitzbauer Andreas A Michalik Sabine S Vogl Thomas T Stoecklein Nikolas H NH Houben Philipp P Katou Shadi S Becker Felix F Hoelzen Jens Peter JP Andreou Andreas A Pascher Andreas A Bechstein Wolf O WO Struecker Benjamin B

Scientific reports 20240304 1

Hepatocellular carcinoma (HCC) is the most common primary malignant liver tumor and a leading cause of cancer-related deaths worldwide. However, current diagnostic tools are often invasive and technically limited. In the last decade, non-invasive liquid biopsies have transformed the field of clinical oncology, showcasing the potential of various liquid-biopsy derived analytes, including extracellular vesicles (EVs), to diagnose and monitor HCC progression and metastatic spreading, serving as pro ...[more]

PMID: 38438456

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Project description:Hepatocellular carcinoma (HCC) has a high mortality rate owing to its complexity. Identification of abnormally expressed genes in HCC tissues compared to those in normal liver tissues is a viable strategy for investigating the mechanisms of HCC tumorigenesis and progression as a means of developing novel treatments. A significant advantage of the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) is that the data therein were collected from different independent researchers and may be integrated, allowing for a more robust data analysis. Accordingly, in the present study, the gene expression profiles for HCC and control samples were downloaded from the GEO and TCGA. Functional enrichment analysis was performed using a Metascape dataset, and a protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/proteins (STRING) online database. The prognostic value of mRNA for HCC was assessed using the Kaplan-Meier Plotter, a public online tool. A gene mRNA heatmap and DNA amplification numbers were obtained from cBioPortal. A total of 2,553 upregulated genes were identified. Functional enrichment analysis revealed that these differentially expressed genes (DEGs) were mainly accumulated in metabolism of RNA and the cell cycle. Considering the complexity and heterogeneity of the molecular alterations in HCC, multiple genes for the prognostication of patients with HCC are more reliable than a single gene. Thus, the PPI network and univariate Cox regression analysis were applied to screen candidate genes (small nuclear ribonucleoprotein polypeptide B and B1, nucleoporin 37, Rac GTPase activating protein 1, kinesin family member 20A, minichromosome maintenance 10 replication initiation factor, ubiquitin conjugating enzyme E2 C and hyaluronan mediated motility receptor) that are associated with the overall survival and progression-free survival of patients with HCC. In conclusion, the present study identified a set of genes that are associated with overall survival and progression-free survival of patients with HCC, providing valuable information for the prognosis of HCC.

Project description:BackgroundHepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers.MethodsWe first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively.ResultsWith the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The 'upregulated' ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the 'downregulated' network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients.ConclusionsIn conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

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Extracellular vesicles as potential biomarkers for diagnosis and recurrence detection of hepatocellular carcinoma.

Publications

Extracellular vesicles as potential biomarkers for diagnosis and recurrence detection of hepatocellular carcinoma.

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