Diagnosis accuracy of serum glypican-3 level in patients with hepatocellular carcinoma: a systematic review with meta-analysis

Hepatocellular Carcinoma Genetic Classification

ABSTRACT

Hepatocellular carcinoma (HCC) represents a significant global burden, with management complicated by its heterogeneity, varying presentation, and relative resistance to therapy. Recent advances in the understanding of the genetic, molecular, and immunological underpinnings of HCC have allowed a detailed classification of these tumors, with resultant implications for diagnosis, prognostication, and selection of appropriate treatments. Through the correlation of genomic features with histopathology and clinical outcomes, we are moving toward a comprehensive and unifying framework to guide our diagnostic and therapeutic approach to HCC.

Precision diagnosis of hepatocellular carcinoma

ABSTRACT

Hepatocellular carcinoma (HCC) is the most common type of primary hepatocellular carcinoma (PHC). Early diagnosis of HCC remains the key to improve the prognosis. In recent years, with the promotion of the concept of precision medicine and more in-depth analysis of the biological mechanism underlying HCC, new diagnostic methods, including emerging serum markers, liquid biopsies, molecular diagnosis, and advances in imaging (novel contrast agents and radiomics), have emerged one after another. Herein, we reviewed and analyzed scientific advances in the early diagnosis of HCC and discussed their application and shortcomings. This review aimed to provide a reference for scientific research and clinical practice of HCC.

Proteoglycans in breast cancer, identification and characterization by LC-MS/MS assisted proteomics approach: A review

PURPOSE

Proteoglycans (PGs) are negatively charged macromolecules containing a core protein and single or several glycosaminoglycan chains attached by covalent bond. They are distributed in all tissues, including extracellular matrix (ECM), cell surface, and basement membrane. They are involved in major pathways and cell signalling cascades which modulate several vital physiological functions of the body. They have also emerged as a target molecule for cancer treatment and as possible biomarkers for early cancer detection. Among cancers, breast cancer is a highly invasive and heterogenous type and has become the major cause of mortality especially among women. So, this review revisits the studies on PGs characterization in breast cancer using LC-MS/MS-based proteomics approach, which will be further helpful for identification of potential PGs-based biomarkers or therapeutic targets.

EXPERIMENTAL DESIGN

There is a lack of comprehensive knowledge on the use of LC-MS/MS-based proteomics approaches to identify and characterize PGs in breast cancer.

RESULTS

LC-MS/MS assisted PGs characterization in breast cancer revealed the vital PGs in breast cancer invasion and progression. In addition, comprehensive profiling and characterization of PGs in breast cancer are efficiently carried out by this approach.

CONCLUSIONS

Proteomics techniques including LC-MS/MS-based identification of proteoglycans is effectively carried out in breast cancer research. Identification of expression at different stages of breast cancer is a major challenge, and LC-MS/MS-based profiling of PGs can boost novel strategies to treat breast cancer, which involve targeting PGs, and also aid early diagnosis using PGs as biomarkers.

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

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignant tumor with high morbidity and mortality globally. Compared with traditional diagnostic methods, microRNAs (miRNAs) were novel biomarkers with higher accuracy.

OBJECTIVE

We aimed to identify combinatorial biomarkers of miRNAs to construct a classification model for the diagnosis of HCC.

METHOD

The mature miRNAs 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 fold-change method were utilized to identify HCC-specific differentially expressed miRNAs (DEMs). Using all combinations of obtained HCC- specific DEMs as input features, we construct 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.

RESULTS

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.

CONCLUSION

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.

Cobalt Chloride Induced Apoptosis by Inhibiting GPC3 Expression via the HIF-1α/c-Myc Axis in HepG2 Cells

Purpose

To investigate the role of glypican-3 (GPC3) in cobalt chloride (CoCl₂)-induced cell apoptosis in hepatocellular carcinoma.

Methods

HepG2 cells were treated with CoCl₂ in the absence or presence of GPC3 plasmid transfection. Cell viability and apoptosis were assessed by MTT assay and flow cytometry, respectively. The expression of GPC3, hypoxia-inducible factor 1α (HIF-1α), c-myc, sp1, poly-ADP-ribose polymerase (PARP) and caspase-3 was determined by real-time PCR, Western blotting, and immunofluorescence after the cells were treated with different concentrations of CoCl₂ or siRNA targeting HIF-1α.

Results

CoCl₂ significantly inhibited the proliferation of HepG2 cells and induced apoptosis. Additionally, the expression of GPC3 mRNA and protein was decreased, and overexpression of GPC3 attenuated the tumour inhibiting effects. Further studies showed that CoCl₂ increased the expression of HIF-1α while reducing the expression of sp1 and c-myc; knockdown of HIF-1α elevated the expression of GPC3, sp1, and c-myc.

Conclusion

CoCl₂ inhibited the growth of HepG2 cells through downregulation of GPC3 expression via the HIF-1α/c-myc axis.

Glypican 3-Targeted Therapy in Hepatocellular Carcinoma

Glypican-3 (GPC3) is an oncofetal glycoprotein attached to the cell membrane by a glycophosphatidylinositol anchor. GPC3 is overexpressed in some kinds of tumors, particularly hepatocellular carcinoma (HCC). The prognostic significance of serum GPC3 levels and GPC3 immunoreactivity in tumor cells has been defined in patients with HCC. In addition to its usefulness as a biomarker, GPC3 has attracted attention as a novel therapeutic target molecule, and clinical trials targeting GPC3 are in progress. The major mechanism of anti-GPC3 antibody (GPC3Ab) against cancer cells is antibody-dependent cellular cytotoxicity and/or complement-dependent cytotoxicity. Since GPC3Ab is associated with immune responses, a combination of protocols with immune checkpoint inhibitors has also been investigated. Moreover, some innovative approaches for GPC3-targeting therapy have emerged in recent years. This review introduces the results of recent clinical trials targeting GPC3 in HCC and summarizes the latest knowledge regarding the role of GPC3 in HCC progression and clinical application targeting GPC3.

Multiple “Omics” data-based biomarker screening for hepatocellular carcinoma diagnosis

The huge prognostic difference between early and late stage hepatocellular carcinoma (HCC) is a challenging diagnostic problem. Alpha-fetoprotein is the mostly widely used biomarker for HCC used in the clinic, however it’s sensitivity and specificity of is not optimal. The development and application of multiple biotechnologies, including next generation sequencing, multiple “omics” data, that include genomics, epigenomics, transcriptomics, proteomics, metabolomics, metagenomics has been used for HCC diagnostic biomarker screening. Effective biomarkers/panels/models have been identified and validated at different clinical levels. A large proportion of these have a good diagnostic performance for HCC, especially for early HCC. In this article, we reviewed the various HCC biomarkers derived from “omics” data and discussed the advantages and disadvantages for diagnosis HCC.

Diagnostic accuracy of serum dickkopf-1 protein in diagnosis hepatocellular carcinoma: An updated meta-analysis

BACKGROUND

To verify the accuracy of serum dickkopf-1 protein (DKK-1) in the diagnosis of hepatocellular carcinoma (HCC) by an updated meta-analysis.

METHODS

We searched potential eligible studies in PubMed and Embase before July 8, 2018. Sensitivity (SN), specificity (SP), positive likelihood ratio (PLR), negative likelihood ratio (NLR), summary receiver operating characteristics curve (sROC), and diagnostic odds ratio (DOR) were pooled with their 95% confidence intervals CIs) using a bivariate random-effects model.

RESULTS

A total of 8 articles contained 10 studies on diagnosis of HCC with DKK-1 alone,7 articles contained 9 studies on diagnosis of HCC with a-fetoprotein (AFP) alone and 5 articles contained 7 studies on diagnosis of HCC with DKK-1 + AFP were identified. The pooled SN, SP, PLR, NLR, and DOR of DKK-1 alone, AFP alone and DKK-1 + AFP were 0.72 (95% CI: 0.70-0.75), 0.62 (95% CI:0.59-0.64) and 0.80 (95% CI:0.78-0.83), 0.86 (95% CI: 0.84-0.87), 0.82 (95% CI:0.80-0.84) and 0.87 (95% CI: 0.85-0.88), 4.91 (95% CI: 2.73-8.83), 3.60 (95% CI:2.01-6.44) and 6.18 (95% CI: 4.68-8.16), 0.32 (95% CI: 0.22-0.47), 0.49 (95% CI:0.40-0.60) and 0.20 (95% CI: 0.15-0.26), and 17.21 (95% CI: 9.10-32.57), 7.45 (95% CI:3.69-15.01) and 31.39 (95% CI: 23.59-43.20), respectively. The area under the sROC was 0.88, 0.70, and 0.92 for the 3 diagnostic methods.

CONCLUSIONS

Serum DKK-1 + AFP showed a high accuracy for diagnosis of HCC, and serum DKK-1 alone had moderate accuracy as compared to a previous meta-analysis, while AFP alone owned an unsatisfied diagnostic behavior for HCC. Due to the limitations of the current analysis, further well-designed studies are needed to confirm the diagnostic value of DKK-1 and DKK-1 + AFP in HCC diagnosis.