Biomarker For Diagnosis Of Hepatocellular Carcinoma Research Articles

Five miRNAs identified in fucosylated extracellular vesicles as non-invasive diagnostic signatures for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a prevalent and aggressive cancer that presents significant challenges for early detection. This study introduces the GlyExo-Capture method for isolating fucosylated extracellular vesicles (Fu-EVs) from serum. We analyze microRNA (miRNA) profiles from Fu-EVs in 88 HCC patients and 179 non-HCC controls using next-generation sequencing (NGS) and identify five miRNAs (hsa-let-7a, hsa-miR-21, hsa-miR-125a, hsa-miR-200a, and hsa-miR-150) as biomarkers for HCC diagnosis. The five-miRNA panel demonstrates exceptional HCC diagnostic performance, with a sensitivity of 0.90 and specificity of 0.92 in a combined cohort of 194 HCC and 412 non-HCC controls, significantly surpassing the performance of alpha-fetoprotein (AFP) and des-gamma-carboxy prothrombin (DCP). Notably, the miRNA model achieves recall rates of 85.7% and 90.8% for stage 0 and stage A early-stage HCC, respectively, identifies 88.1% of AFP-negative HCC cases, and effectively differentiates HCC from other cancers. This study provides a high-throughput, rapid, and non-invasive approach for early HCC detection.

Early-stage biomarkers identification by integrated genomic analysis in hepatocellular carcinoma

Hepatocellular carcinoma (HCC), a type of liver cancer, ranks as the third-leading cause of death due to the lack of definite biomarkers for early-stage detection. HCC progression occurs by the dysregulation of several genes. Though several studies focus on biomarkers for HCC diagnosis, stage-specific marker identification remains elusive. Hence, the present study aims to identify early-stage biomarkers for the detection of HCC through integrated in silico analysis. The differential gene expression was performed using GEO2R for the datasets (GSE14520, GSE63898, GSE121248, GSE124535, GSE94660, and GSE6764) retrieved from Gene Expression Omnibus (GEO) of patients with cirrhotic liver or HCC. The common differentially expressed gene enrichment analysis was performed using Funrich for Gene ontology (GO) and Kyoto Encyclopedia of Gene and Genomics (KEGG) gene mapping. The Protein-Protein Interaction (PPI) network was performed using the Search Tool for the Retrieval of Interacting Genes (STRING). The hub genes were identified using the CytoHubba plug-in of Cytoscape software. The identified genes were verified for their prognostic value using the Kaplan-Meier plotter and Immunohistochemistry micrographs obtained from the Human Protein Atlas database. An overall of 243 common differentially expressed genes (DEGs) were identified containing 171 upregulated and 72 downregulated genes. With the help of PPI network construction, ten hub genes were identified as CDK1, AURKA, CCNB1, CCNB2, CENPF, CDC20, TOP2A, BUB1, RRM2, and HMMR, which are dysregulated owing to HCC proliferation, tumorigenesis and poor prognosis in patients. These hub genes are suitable waypoints for the diagnosis and targeted therapy against early-stage HCC.

Multiomics profiling of buffy coat and plasma unveils etiology-specific signatures in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a leading cause of cancer mortality worldwide. Despite identification of several biomarkers for HCC diagnosis, challenges such as low sensitivity and intratumoral heterogeneity have impeded early detection, highlighting the need for etiology-specific blood biomarkers. We generated whole-transcriptome sequencing (WTS) and targeted proteome data from buffy coat and plasma samples from HCC patients. By integrating etiological information on viral infection, we investigated the etiology-specific gene expression landscape at the blood level. Validation of differentially expressed genes (DEGs) was performed using publicly available RNA-seq datasets and qRT‒PCR with AUC analyses. Differential expression analyses with multiomics data revealed distinct gene expression profiles between HBV-associated HCC and nonviral HCC, indicating the presence of etiology-specific blood biomarkers. The identified DEGs were validated across multiple independent datasets, underscoring their utility as biomarkers. Additionally, single-cell RNA-seq analysis of HCC confirmed differences in DEG expression across distinct immune cell types. Our buffy coat WTS data and plasma proteome data may serve as reliable sources for identifying etiology-specific blood biomarkers of HCC and might contribute to discovery of therapeutic targets for HCC across different etiologies.

Midkine (MDK) in Hepatocellular Carcinoma: More than a Biomarker.

Midkine (MDK) is a multifunctional secreted protein that can act as a cytokine or growth factor regulating multiple signaling pathways and being implicated in fundamental cellular processes, such as survival, proliferation, and migration. Although its expression in normal adult tissues is barely detectable, MDK serum levels are found to be elevated in several types of cancer, including hepatocellular carcinoma (HCC). In this review, we summarize the findings of recent studies on the role of MDK in HCC diagnosis and progression. Overall, studies show that MDK is a powerful biomarker for HCC early diagnosis, as it can differentiate not only between HCC patients and normal individuals but also between HCC patients and patients with other liver pathologies. It is correlated with high recurrence rates and was shown to be valuable for the diagnosis of early-stage HCC, even in patients negative for α-fetoprotein (AFP), the most commonly used biomarker for HCC diagnosis. A comparison with AFP reveals that MDK is inferior to AFP with regard to specificity but significantly superior with regard to sensitivity, which further indicates the need for using both biomarkers for more effective HCC diagnosis.

Discovery of a haptoglobin glycopeptides biomarker panel for early diagnosis of hepatocellular carcinoma.

There is a need for new serum biomarkers for early detection of hepatocellular carcinoma (HCC). Haptoglobin (Hp) N-glycosylation is altered in HCC, but the diagnostic value of site-specific Hp glycobiomarkers is rarely reported. We aimed to determine the site-specific glycosylation profile of Hp for early-stage HCC diagnosis. Hp glycosylation was analyzed in the plasma of patients with liver diseases (n=57; controls), early-stage HCC (n=50) and late-stage HCC (n=32). Hp phenotype was determined by immunoblotting. Hp was immunoisolated and digested into peptides. N-glycopeptides were identified and quantified using liquid chromatography-mass spectrometry. Cohort samples were compared using Wilcoxon rank-sum (Mann-Whitney U) tests. Diagnostic performance was assessed using receiver operating characteristic (ROC) curves and area under curve (AUC). Significantly higher fucosylation, branching and sialylation of Hp glycans, and expression of high-mannose glycans, was observed as disease progressed from cirrhosis to early- and late-stage HCC. Several glycopeptides demonstrated high values for early diagnosis of HCC, with an AUC of 93% (n=1), >80% (n=3), >75% (n=13) and >70% (n=11), compared with alpha-fetoprotein (AFP; AUC of 79%). The diagnostic performance of the identified biomarkers was only slightly affected by Hp phenotype. We identified a panel of Hp glycopeptides that are significantly differentially regulated in early- and late-stage HCC. Some glycobiomarkers exceeded the diagnostic value of AFP (the most commonly used biomarker for HCC diagnosis). Our findings provide evidence that glycobiomarkers can be effective in the diagnosis of early HCC - individually, as a panel of glycopeptides or combined with conventional serological biomarkers.

Bilirubin is a superior biomarker for hepatocellular carcinoma diagnosis and for differential diagnosis of benign liver disease

Abstract Objectives To develop a novel diagnostic model combining bilirubin, protein induced by vitamin K absence or antagonist-II (PIVKA-II), and alpha-fetoprotein (AFP) to improve hepatocellular carcinoma (HCC) diagnosis. Methods The serum levels of PIVKA-Ⅱ, AFP, and bilirubin in 718 HCC patients and 2,763 benign liver disease (BLD) patients were measured. A mathematical model was used as the combined diagnostic model (PIVKA-Ⅱ, AFP, and bilirubin: PAB combination) for improving HCC diagnosis. Receiver operating characteristic (ROC) curves were used to analyse the diagnostic value of the individual markers, the PIVKA-II and AFP (PA) combination, and the PAB combination for HCC diagnosis. Results With the increase in bilirubin, the positive predictive value (PPV) of bilirubin in HCC diagnosis decreased (p<0.001) while the negative predictive value (NPV) increased (p<0.001). The areas under the ROC curves (AUCs) of the PAB combination were 0.935 and 0.862 for the diagnosis of HCC and HCC<3.0 cm, respectively, which were significantly higher than those of PIVKA-Ⅱ, AFP, and the PA combination (p<0.001). The AUC values for PIVKA-Ⅱ, AFP, and the PA combination were significantly decreased for the diagnosis of HCC and HCC<3.0 cm when serum levels of PIVKA-Ⅱ≥40 mAU/mL and/or AFP≥20 ng/mL were used for diagnosis, while the AUC value of the PAB combination increased. Conclusions Bilirubin is a superior biomarker for diagnosing HCC and distinguishing HCC from BLD. The combination of bilirubin with PIVKA-Ⅱ and AFP has superior diagnostic value for HCC and early-stage HCC.

The ALKBH5/SOX4 axis promotes liver cancer stem cell properties via activating the SHH signaling pathway.

Hepatocellular carcinoma (HCC), featured with high prevalence and poor prognosis, is the major cause of cancer-related deaths worldwide. As a subgroup of liver cancer cells capable of differentiation, tumorigenesis and self-renewal, liver cancer stem cells (LCSCs) serve as one of the reasons leading to HCC progression and therapeutic resistance. Therefore, in-depth exploration of novel molecular biomarkers related to LSCSs is of great necessity. In our study, we found that human AlkB homolog H5 (ALKBH5) expression was enriched in LCSCs, which could foster proliferation, invasion and migration of the HCC cells. Mechanically, ALKBH5 positively mediated the expression of SOX4 via demethylation, and SOX4 promoted SHH expression at the transcriptional level to activate sonic hedgehog (SHH) signaling pathway. Furthermore, exosomes derived from CD133+ HCC cells could transmit ALKBH5 into THP-1 cells, which might be associated with M2 polarization of macrophages. In summary, the ALKBH5/SOX4 axis plays a significant role in exacerbating LCSC properties via activating SHH signaling pathway, and ALKBH5 could be a critical effector related to macrophage M2 polarization. These findings might provide a promising new biomarker for HCC diagnosis and treatment.

Glypican-3: A Promising Biomarker for Hepatocellular Carcinoma Diagnosis

Background Molecular targets are urgently required for the early detection of HCC and the development of novel therapeutic approaches. in HCC patients, GPC3 is overexpressed at both the gene and protein levels, and its expression predicts a poor prognosis. Moreover, GPC3 has been used as a target for molecular imaging and therapeutic intervention in HCC. Aim and objectives to study the role of Glypican 3 levels in the diagnosis of hepatocellular carcinoma in Egyptian patients and its prognostic role after successful treatment. Subjects and Methods This is a Case control study, was conducted in Internal Medicine department - Ain Shams University Hospitals on 60 patients divided into 2 groups: (Group 1): included 30 patients with liver cirrhosis and HCC on top, (Group 2): included 30 patients with liver cirrhosis and no evidence of HCC. Result There were high significant difference between both groups as regard GPC3. Conclusion Glypican-3 can be a valuable diagnostic marker for HCC diagnosis and prognosis after various treatment modalities and may be complementary to alpha fetoprotein increasing overall sensitivity of HCC detection.

Novel Long Noncoding RNAs, LINC01093 and MYLK-AS1, Serve as Potential Diagnostic and Prognostic Biomarkers or Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most fatal human malignancies worldwide. In this research, we aimed to identify long noncoding RNAs (lncRNAs) as biomarkers for HCC diagnosis and prognosis. lncRNA expression profiles were obtained from Gene Expression Omnibus and The Cancer Genome Atlas databases. The differentially expressed lncRNAs between HCC and adjacent tissues were analyzed with bioinformatic tools. Four lncRNAs with area under the curve of the receiver operating characteristic curve >0.9 were selected from both datasets. Univariate and Kaplan-Meier analyses were performed to obtain LINC01093, MYLK-AS1, and MCM3AP-AS1 as the optimal diagnostic and prognostic biomarkers. Finally, qPCR confirmed that LINC01093 and MYLK-AS1 were significantly differentially expressed in HCC and adjacent normal tissues. In general, we demonstrated that novel lncRNAs, LINC01093 and MYLK-AS1, could be used as potential diagnostic and prognostic biomarkers for HCC.

SSNA1 Promotes Hepatocellular Carcinoma Metastasis Via STAT3/EMT Induction.

Hepatocellular carcinoma (HCC) currently represents the third most prevalent cause of cancer-related deaths globally. HCC is typically diagnosed at advanced stages with metastasis, and has a poor outcome. In order to identify useful biomarkers for early diagnosis and develop novel therapeutic targets, it is necessary to better understand the cellular mechanisms driving HCC progression. Public datasets were used to detect Sjögren's syndrome nuclear autoantigen-1 (SSNA1) expression in HCC. Scratch assay and transwell invasion assays were used to evaluate the migration and invasion ability of HCC cells. We explored the molecular mechanism by western blotting, viability and transfection assays. SSNA1 was found up-regulated in human HCC tissues. SSNA1 expression increased along with HCC progression. In addition, elevated SSNA1 expression in HCC patients was closely correlated to a poor prognosis. The proliferation and apoptosis of HCC cells were unaffected by reducing SSNA1 expression. Meanwhile, STAT3/EMT axis inhibition mediated by SSNA1 depletion prevented HCC cells from migrating and invading in vitro. SSNA1 could be used as a biomarker for HCC diagnosis and prognosis, and point the direction for the future investigation of innovative approaches to target and treat HCC.

Detection of sFas, sCD137, and IL-27 Cytokines as Potential Biomarkers for Hepatocellular Carcinoma Diagnosis.

Hepatocellular carcinoma (HCC), a prevalent type of liver cancer, is mainly diagnosed in the advanced stage, leading to a high mortality rate. Recent advances have identified peripheral cytokines as a potential tool to predict disease outcomes and inform therapeutic decisions. Hence, in this study, we aim to build a predictive model for HCC based on serum levels of different cytokines. We used immunoassay to quantify the concentrations of IL-27, MIP-1β, Perforin, sCD137, sFas, and TNF-α in the serum of 38 HCC patients and 15 healthy controls. Logistic regression was then used to construct classification models detecting HCC based on these cytokines. A nomogram of the best-performing model was generated to visualize HCC prediction. sFas and MIP-1β were found to be significantly higher in HCC patients compared to controls. Predictive models based on cytokine levels combining sFas, sCD137, and IL-27 performed the best in distinguishing HCC patients from healthy controls. This model has a bias-corrected area under the receiver operating characteristic (ROC) curve (AUC) of 0.948, a sensitivity of 92.11%, a specificity of 93.33%, and an accuracy of 0.925. Our findings suggest that serum cytokines have the potential to be utilized in HCC screening to improve detection rates.

Circ_0124208 Promotes the Progression of Hepatocellular Carcinoma by Regulating the miR-338-3p/LAMC1 Axis.

Hundreds of circular RNAs (circRNAs) have been identified as key regulators in biological processes; however, only few of these circRNAs have been functionally described to participate in the development of hepatocellular carcinoma (HCC). The present study aimed to reveal the function and molecular mechanisms of circ_0124208 in HCC. Real-time quantitative PCR revealed the upregulation of circ_0124208 in HCC tissues and cells. Based on cell functional experiments, silencing circ_0124208 attenuated proliferation and migration, but boosted the apoptosis of Hep 3B and Huh7 cells in vitro. The in vivo experiment further validated the repression of tumor growth via circ_0124208 knockdown. RNA immunoprecipitation and dual-luciferase reporter assays showed that circ_0124208 sponged miR-338-3p and reduced its expression. miR-338-3p inhibition was found to partially reverse the tumor-suppressive effects caused by circ_0124208 in Hep 3B and Huh7 cells. Furthermore, miR-338-3p directly targeted laminin subunit gamma 1 (LAMC1). The malignancy of Hep 3B and Huh7 cell was decreased by LAMC1 knockdown, and this effect was mitigated by miR-338-3p suppression. Overall, circ_0124208 was demonstrated for the first time to play a crucial role as an oncogene in HCC, implying that it could be a useful biomarker for HCC diagnosis. Furthermore, the circ_0124208/miR-338-3p/LAMC1 axis can be used as a potential therapeutic target for HCC treatment.

Glypican-3, Vascular Endothelial Growth Factor and Golgi Protein-73 for Differentiation between Liver Cirrhosis and Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) accounts for more than 80% of primary liver cancers. Moreover, in the next 10 years, more than one million patients are expected to die from liver cancer as estimated by the World Health Organization. The aim of the present study is to evaluate the clinical utility of using Glypican (GPC3), Vascular endothelial growth factor (VEGF) and Golgi protein 73 (GP73) in serum by Enzyme-Linked Immunosorbent Assay (ELISA) and by Real-Time Polymerase Chain Reaction (RT-PCR), as diagnostic markers to differentiate HCC from cirrhotic liver disease. A total of 50 patients with histologically-proven HCC, 50 liver cirrhosis patients and 20 healthy volunteers as controls were enrolled in this study, blood samples were obtained from each patient. Expression of the studied biomarkers was evaluated by ELISA and Real-Time PCR. Statistical analysis of RT-PCR results showed that the expression of GPC3, VEGF and GP73 in serum of patients with HCC was significant (P value < 0.001, 0.01, and < 0.001) respectively and increased when compared to the cirrhotic group. Furthermore, the serum protein levels of GPC3 and VEGF in HCC and cirrhotic patients were significant when compared to the control group. While no significance was found between HCC and cirrhotic group. The serum protein level of GP73 was significantly increased in HCC and cirrhosis groups compared to the control group (P value < 0.001). Moreover, a significant increase was evident in HCC group compared to cirrhotic group (P value < 0.001). The results of the present study showed that the combination of VEGF and GP73 could discriminate HCC from cirrhosis. GPC3, VEGF and GP73 are reliable biomarkers for diagnosis of HCC. The serum level of GP73 is a potential screening marker for discriminating HCC from liver cirrhosis.

Construction of HBV gene-related prognostic and diagnostic models for hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) is a main cause of malignancy-related death all over the world with a poor prognosis. The current research is focused on developing novel prognostic and diagnostic models of Hepatocellular carcinoma from the perspective of hepatitis B virus (HBV)-related genes, and predicting its prognostic characteristics and potential reliable biomarkers for Hepatocellular carcinoma diagnosis. Methods: As per the information related to Hepatocellular carcinoma expression profile and the clinical data in multiple public databases, we utilized limma for assessing the differentially expressed genes (DEGs) in HBV vs non- hepatitis B virus groups, and the gene set was enriched, analyzed and annotated by WebGestaltR package. Then, STRING was employed to investigate the protein interactions. A risk model for evaluating Hepatocellular carcinoma prognosis was built with Lasso Cox regression analysis. The effect patients receiving immunotherapy was predicted using Tumor Immune Dysfunction and Exclusion (TIDE). Additionally, pRRophetic was used to investigate the drug sensitivity. Lastly, the Support Vector Machine (SVM) approach was utilized for building the diagnostic model. Results: The Hepatocellular Carcinoma Molecular Atlas 18 (HCCDB18) data set was utilized for the identification of 1344 HBV-related differentially expressed genes, mainly associated with cell division activities. Five functional modules were established and then we built a prognostic model in accordance with the protein-protein interaction (PPI) network. Five HBV-related genes affecting prognosis were identified for constructing a prognostic model. Then, the samples were assigned into RS-high and -low groups as per their relevant prognostic risk score (RS). High-risk group showed worse prognosis, higher mutation rate of TP53, lower sensitivity to immunotherapy but higher response to chemotherapeutic drugs than low-risk group. Finally, the hepatitis B virus diagnostic model of Hepatocellular carcinoma was established. Conclusion: In conclusion, the prognostic and diagnostic models of hepatitis B virus gene-related Hepatocellular carcinoma were constructed. ABCB6, IPO7, TIMM9, FZD7, and ACAT1, the five HBV-related genes that affect the prognosis, can work as reliable biomarkers for the diagnosis of Hepatocellular carcinoma, giving a new insight for improving the prognosis, diagnosis, and treatment outcomes of HBV-type Hepatocellular carcinoma.

The Importance of Microrna21 as Biomarker in Hepatocellular Carcinoma

Objective: Hepatocellular carcinoma (HCC) is the fifth most common cancer and the second leading cause of cancer- related deaths worldwide.The diagnosis of HCC patients remains difficult, especially early in the development of the disease, and yet early and accurate diagnosis of HCC patients is vital in order to improve prognosis. Promising biomarkers for diagnosis of HCC have been successfully identifiedin several studies. MicroRNA-21 is one of the oncogenic miRNAs which may be a potential diagnostic biomarker for HCC.Our aim in the study was to investigate microRNAs as a biomarker in HCC and to compare the most unique MiR-21 in the literature as a biomarker and prognostic factor. Materials and Methods: Ten patients diagnosed with HCC and ten healthy individuals of the same age and gender were selected as the control group. Six miRNAs (Let-7c, miR-1, miR-21, miR-29, miR-34, miR-335) selected and MiR 181 and miR 192 used as the endogenous control group. Results: MiR21 was upregulated and statistically important compared with the endogenous control miR181(p=0.041). In the ROC analysis curve, AUC was significantly high for Delta181CT miR-21 (0.778). The sensitivity and specificity values of Delta181CT miR-21 with an optimal cut-off value of -3.508564949 were 77.8% and 90.0%. respectively. None of six miRNA statistically important compared with the endogenous control miR192. Conclusion: MiR21 is important for determining as biomarkers at diagnosis of HCC.

The Identification and Analysis of MicroRNAs Combined Biomarkers for Hepatocellular Carcinoma Diagnosis.

Hepatocellular carcinoma (HCC) is a common malignant tumor with high morbidity and mortality globally. Compared with traditional diagnostic methods, microRNAs (miRNAs) are novel biomarkers with higher accuracy. We aimed to identify combinatorial biomarkers of miRNAs to construct a classification model for the diagnosis of HCC. The mature miRNA expression profile data of six cancers (liver, lung, gastric, breast, prostate, and colon) were retrieved from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database with accession number GSE36915, GSE29250, GSE99417, GSE41970, GSE64333 and GSE35982. The messenger RNA (mRNA) expression profile data of these six cancers were obtained from TCGA. Three R software packages, student's t-test, and a normalized foldchange method were utilized to identify HCC-specific differentially expressed miRNAs (DEMs). Using all combinations of obtained HCC-specific DEMs as input features, we constructed a classification model by support vector machine searching for the optimal combination. Furthermore, target genes prediction was conducted on the miRWalk 2.0 website to obtain differentially expressed mRNAs (DEmRNAs), and KEGG pathway enrichment was analyzed on the DAVID website. The optimal combination consisted of four miRNAs (hsa-miR-130a-3p, hsa-miR-450b-5p, hsa-miR-136-5p, and hsa-miR-24-1-5p), of which the last one has not been currently reported to be relevant to HCC. The target genes of hsa-miR-24-1-5p (CDC7, ACACA, CTNNA1, and NF2) were involved in the cell cycle, AMPK signaling pathway, Hippo signaling pathway, and insulin signaling pathway, which affect the proliferation, metastasis, and apoptosis of cancer cells. Moreover, the area under the receiver operating characteristic curves of the four miRNAs were all higher than 0.85. These results suggest that the miRNAs combined biomarkers were reliable for the diagnosis of HCC. Hsa-miR-24-1-5p was a novel biomarker for HCC diagnosis identified in this study.

Thymosin β4, a potential marker of malignancy and prognosis in hepatocellular carcinoma

Background The lack of effective early diagnostic markers is an obstacle in clinical diagnosis and treatment of hepatocellular carcinoma (HCC). Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is an increasing popular approach for identification of clinically relevant parameters including biomarkers. Patients and methods 540 subjects, including 274 HCC, 119 liver cirrhosis, 89 hepatitis, and 58 healthy volunteers were enrolled. MALDI-TOF MS was used to select potential novel biomarkers from serum of HCC patients. Its clinical application was evaluated by experiments and clinical data analysis. Results We identified Thymosin β4 (Tβ4) in serum by MALDI-TOF MS. The expression of Tβ4 was detected up-regulating in HCC cells and tissues which enhanced motility of HCC cells. More important, the level of serum Tβ4 was significantly elevated in HCC patients. The AUROC showed the optimum diagnostic cut-off was 1063.6 ng/mL, ROC and 95% CI of Tβ4 (0.908; 0.880–0.935) were larger than that of serum AFP (0.712; 0.662–0.762; p < 0.001). The sensitivity (91.3% vs 83.1%) and specificity (81.2% vs 20.3%) of serum Tβ4 were higher than alpha-fetoprotein (AFP). In AFP-negative HCC, the sensitivity could reach to 80.5%. ROC analysis showed serum Tβ4 had a better performance compared with AFP in distinguishing early-stage and small HCC. Tβ4 is correlated with TNM stage (p = 0.016) and vascular invasion (p = 0.005). Survival analysis indicated the survival time of Tβ4 positive patients was shorter (p < 0.001). Cox analysis suggested Tβ4 could be an independent factor for HCC prognosis. Conclusion Tβ4 may serve as a novel biomarker for HCC diagnosis and prognosis.

Quantification of cell-free circulating mitochondrial DNA copy number variation in hepatocellular carcinoma.

SUMMARYOBJECTIVE:Hepatocellular carcinoma is the most common primary malignant liver tumor. Mitochondrial DNA copy number has been shown to be associated with various malignancies. However, there has not been any study on the absolute quantification of mtDNA copy number in hepatocellular carcinoma. The aim of this study was to develop a new method for absolute quantification of mtDNA copy number and to relatively quantify the variations in the mtDNA copy number in hepatocellular carcinoma patients in comparison with healthy individuals.METHODS:Venous blood samples were collected from both hepatocellular carcinoma patients (34) and healthy individuals (34). Circulating cell-free DNAs were isolated and the relative quantification of mtDNA copy number variation was determined using quantitative polymerase chain reaction and digital polymerase chain reaction.RESULTS:It was found that the relative mtDNA copy number was significantly decreased in hepatocellular carcinoma patients in comparison with the control group (p<0.05). The median (range) and average of relative mtDNA/β-actin gene of the patients were determined as 42.8 cp/μL (11.1–88.5) and 45.1 cp/μL, respectively, while the median (range) and average relative mtDNA/β-actin gene of the control group were determined as 102.8 cp/μL (55.1–291.8) and 138.7 cp/μL, respectively (p<0.05). When quantitative polymerase chain reaction and digital polymerase chain reaction were compared, mtDNA/β-actin gene copy number ratio of digital polymerase chain reaction results was found to be 1.76-fold more than that of quantitative polymerase chain reaction results.CONCLUSION:Circulating mtDNA copy number was decreased in hepatocellular carcinoma patients in comparison with healthy individuals, and we suggest that it can be used as a noninvasive biomarker for hepatocellular carcinoma diagnosis in the future.

Hypomethylation status of miR-657 promoter region as biomarker for diagnosis of hepatocellular carcinoma: a retrospective study.

BackgroundThe purpose of our study was to evaluate whether the methylation status of the miR-657 promoter region could be used as a biomarker for diagnosis of hepatocellular carcinoma (HCC), so as to find alternative biomarkers of early HCC detection.MethodsCancerous and paired adjacent noncancerous tissues were collected from 160 patients who had been diagnosed with HCC by histopathology and received surgery. The methylation status of the miR-657 promoter region was measured using a MassARRAY Analyzer 4. Receiver operator characteristic (ROC) curve analysis was used to assess the effectiveness of miR-657 promoter region methylation status as a biomarker for diagnosis of HCC.ResultsThe mean methylation level of the miR-657 promoter region was significantly lower in cancerous tissues than in normal tissues of HCC patients (48.91%:67.04%, P<0.0001). ROC curve analysis revealed that the mean methylation level of the miR-657 promoter region could distinguish cancerous tissues from paired normal tissues of HCC patients (area under the curve: 0.847, P<0.001). Using 59.50% as the optimal cut-off, the sensitivity was 95.50% and the specificity was 70.01%.ConclusionsMethylation levels of the miR-657 promoter region were decreased in HCC patients and could be used as alternative and supplementary biomarkers for diagnosis of HCC.

Abnormal ECA-Binding Membrane Glycans and Galactosylated CAT and P4HB in Lesion Tissues as Potential Biomarkers for Hepatocellular Carcinoma Diagnosis

Hepatocellular carcinoma (HCC) is one of the most common types of cancer. Despite decades of research efforts, the search for novel biomarkers is still urgently needed for the diagnosis of HCC and the improvement of clinical outcomes. Previous studies of HCC clinical biomarkers have usually focused on serum and urine samples (e.g., serum Alpha-fetoprotein (AFP). However, cellular membrane proteins in lesion tissues are less used in HCC diagnosis. The abnormal expression of membrane glycoproteins in tumor lesions are considered as potential targets for tumor diagnosis and tumor therapies. Here, a lectin array has been employed to screen and identify abnormal glycopatterns and cellular membrane glycans in HCC lesion tissues compared with adjacent non-tumor tissues. We found that there was significantly less expression of Erythrina cristagalli (ECA) lectin binding (Galβ1-3/β1-4) glycans on the cellular membrane of HCC lesion tissues compared with those of adjacent non-tumor tissues. Immunohistochemistry analysis further showed that ECA-binding ability on the membrane proteins of HCC tissues progressively decreased in different tumor-node-metastasis (TNM) stages (stage I to stage III) as the malignancy of liver cancer increased. Receiver operating curve (ROC) analysis showed ECA-binding ability yielding a sensitivity of 85% and specificity of 75%, and a combination of ECA and AFP has better clinical diagnostic efficiency, yielding a sensitivity of 90% and specificity of 85%, than ECA or AFP assay alone. ECA pull-down followed by mass spectrometry further showed that there was significantly less expression of ECA binding membrane catalase (CAT) and prolyl 4-hydroxylase beta polypeptide (P4HB) in HCC tissues compared with the adjacent non-tumor tissues. The abnormally increased expression of total CAT and P4HB and decreased expression of galactosylated membrane CAT and P4HB in HCC cell lines were correlated with an HCC metastasis status. Our findings suggest that abnormal declined ECA-binding galatosylated membrane glycans and two galactosylated-CAT and P4HB glycoproteins in lesion tissues are potential biomarkers in the diagnosis and/or metastasis prediction for HCC.