Transcriptional profiling and co-expression network analysis identifies potential biomarkers to differentiate chronic hepatitis B and the caused cirrhosis

C-Biomarker.net: A Cytoscape app for the identification of cancer biomarker genes from cores of large biomolecular networks

Although there have been many studies revealing that biomarker genes for early cancer detection can be found in biomolecular networks, no proper tool exists to discover the cancer biomarker genes from various biomolecular networks. Accordingly, we developed a novel Cytoscape app called C-Biomarker.net, which can identify cancer biomarker genes from cores of various biomolecular networks. Derived from recent research, we designed and implemented the software based on parallel algorithms proposed in this study for working on high-performance computing devices. We tested our software on various network sizes and found the suitable size for each running mode on CPU or GPU. Interestingly, using the software for 17 cancer signaling pathways, we found that on average 70.59% of the top three nodes residing at the innermost core of each pathway are biomarker genes of the cancer respectively to the pathway. Similarly, by the software, we also found 100% of the top ten nodes at both cores of Human Gene Regulatory (HGR) network and Human Protein-Protein Interaction (HPPI) network are multi-cancer biomarkers. These case studies are reliable evidence for performance of cancer biomarker prediction function in the software. Through the case studies, we also suggest that true cores of directed complex networks should be identified by the algorithm of R-core rather than K-core as usual. Finally, we compared the prediction result of our software with those of other researchers and confirmed that our prediction method outperforms the other methods. Taken together, C-Biomarker.net is a reliable tool that efficiently detects biomarker nodes from cores of various large biomolecular networks. The software is available at https://github.com/trantd/C-Biomarker.net.

Whole-transcriptome sequencing revealed differentially expressed mRNAs and non-coding RNAs played crucial roles in NiONPs-induced liver fibrosis

Nickel oxide nanoparticles (NiONPs) induced liver fibrosis, while its mechanisms associated with transcriptome remained unclear. This study aimed to investigate the roles of differentially expressed (DE) messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs) in NiONPs-induced liver fibrosis, and further confirm whether JNK/c-Jun pathway enriched by the DE RNAs was involved in the regulation of the disease. A liver fibrosis rat model was established by intratracheal perfusion of NiONPs twice a week for 9 weeks. Whole-transcriptome sequencing was applied to obtain expression profiles of mRNAs, long non-coding RNAs (lncRNAs), microRNAs (miRNAs), and circular RNAs (circRNAs) in the model rat and control liver tissues. Comparing the RNA expression profiles of the model and control liver tissues, we identified 324 DE mRNAs, 129 DE lncRNAs, 24 DE miRNAs and 33 DE circRNAs, and the potential interactions among them were revealed by constructing two co-expression networks, including lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA networks. Using RT-qPCR, we verified the sequencing results of some RNAs in the networks and obtained similar expression profiles, indicating our sequencing results were reliable and referable. Through Gene Ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, we predicted the biological functions and signaling pathways potentially related to NiONPs-induced liver fibrosis, such as "positive regulation of JNK cascade", "inflammatory response", "transcription factor binding", and MAPK, Wnt, PI3K-Akt signaling pathways. JNK/c-Jun pathway, a subclass of MAPK signal, was selected for further investigation because it was significantly enriched by fibrosis-related DE genes and activated in animal models. In vitro, we detected the cytotoxicity of NiONPs on LX-2 cells and treated the cells with 5 μg/ml NiONPs for 12 h. The results showed NiONPs induced the up-regulated protein expression of fibrotic factors collagen-1a1 (Col-1a1) and matrix metalloproteinas2 (MMP2) and JNK/c-Jun pathway activation. While these effects were reversed after JNK/c-Jun pathway was blocked by SP600125 (JNK pathway inhibitor), indicating the pathway was involved in NiONPs-induced excessive collagen formation. In conclusion, our results revealed the DE mRNAs and ncRNAs played crucial roles in NiONPs-induced liver fibrosis, and JNK/c-Jun pathway mediated the development of the disease.

Association of Genetic Polymorphisms With Hepatitis C Virus-related Liver Cirrhosis in Japan

BACKGROUND/AIM

Hepatitis C virus (HCV) infection is an important health problem in the direct-acting antivirals-era. HCV causes life-threatening diseases, such as cirrhosis and hepatocellular carcinoma. Our aim was to examine whether certain single-nucleotide polymorphisms (SNPs) are associated with the prevalence of HCV infections progressing to cirrhosis in the Japanese population by a genome-wide association study-based approach.

MATERIALS AND METHODS

We used DNA extracted from blood specimens of Japanese subjects with the establishment of the BioBank Japan project.

RESULTS

We observed statistically significant differences in the frequency of 4 SNPs (rs1989972, rs2293766, rs1877033 and rs4805439) between anti-HCV-positive cirrhotic patients and controls.

CONCLUSION

Four SNPs are associated with susceptibility to cirrhosis among HCV-infected Japanese subjects, while further studies with cohorts other than those sourced from BioBank Japan, must be conducted.

Prediction of hepatocellular carcinoma risk in patients with chronic liver disease from dynamic modular networks

Background

Discovering potential predictive risks in the super precarcinomatous phase of hepatocellular carcinoma (HCC) without any clinical manifestations is impossible under normal paradigm but critical to control this complex disease.

Methods

In this study, we utilized a proposed sequential allosteric modules (AMs)-based approach and quantitatively calculated the topological structural variations of these AMs.

Results

We found the total of 13 oncogenic allosteric modules (OAMs) among chronic hepatitis B (CHB), cirrhosis and HCC network used SimiNEF. We obtained the 11 highly correlated gene pairs involving 15 genes (r > 0.8, P < 0.001) from the 12 OAMs (the out-of-bag (OOB) classification error rate < 0.5) partial consistent with those in independent clinical microarray data, then a three-gene set (cyp1a2-cyp2c19-il6) was optimized to distinguish HCC from non-tumor liver tissues using random forests with an average area under the curve (AUC) of 0.973. Furthermore, we found significant inhibitory effect on the tumor growth of Bel-7402, Hep 3B and Huh7 cell lines in zebrafish treated with the compounds affected those three genes.

Conclusions

These findings indicated that the sequential AMs-based approach could detect HCC risk in the patients with chronic liver disease and might be applied to any time-dependent risk of cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-02791-9.

Postoperative recurrent factors and therapeutic and preventive strategies for hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors in China. The recurrence rate is about 50% at 3 years and over 70% at 5 years after hepatectomy for HCC. The high recurrence rate seriously affects the curative effect and long-term survival of patients with HCC, and is the primary cause of death after operation. Postoperative recurrence of HCC is a complex multi-step, multi-factorial process involving three factors: the body, microenvironment, and tumor tissue, which include body immunity, local pH value, interstitial pressure, vascular osmotic pressure, inflammatory reaction, tumor cell adhesion, extracellular matrix degradation, cell migration, cell proliferation, and tumor angiogenesis. HCC recurrence is closely related to abnormal gene expression and related molecular function changes, but the molecular mechanism has not been fully elucidated. How to treat the recurrence of HCC after operation directly affects the prognosis of patients with HCC, and treatments include reoperation, liver transplantation, local minimally invasive treatment, radiotherapy, molecular targeted drugs, immunotherapy, and traditional Chinese medicine treatment. It is difficult to cure or control tumor progression by a single therapy. Two or more therapeutic methods need to be combined organically to achieve a synergistic therapeutic effect. According to the specific situation of patients with HCC, it is key to analyze the individual characteristics of patients, to combine the clinical experience of clinicians and the best evidence, to adopt the individualized treatment plan, and to choose the appropriate treatment methods. For HCC patients with high-risk factors for recurrence, selecting the appropriate treatment is important to reduce the recurrence of HCC after operation and prolong the survival of patients.

High miR-139-3p expression predicts a better prognosis for hepatocellular carcinoma: a pooled analysis

Objective

To observe the expression and clinical significance of micro RNA (miR)-139-3p in liver cancer tissues, and to explore its relationship with miR-139-3p target genes related to the prognosis of hepatocellular carcinoma (HCC).

Methods

A total of 362 patients with HCC were included in the study. Liver hepatocellular carcinoma data were obtained directly from The Cancer Genome Atlas data portal .The bioinformatics analysis tool TargetScan was applied to predict miR-139-3p target genes.

Results

Survival time was significantly higher in patients with high miR-139-3p expression, compared with the low miR-139-3p expression group. Bioinformatics analysis showed that miR-139-3p target genes ISG20L2, RAD54B, KIAA0101, and PIGS were significantly negatively correlated with miR-139-3p expression.

Conclusions

High miR-139-3p expression in HCC tissues was indicative of good patient prognosis. miR-139-3p target genes ISG20L2, RAD54B, KIAA0101, and PIGS were related to HCC prognosis.

Hierarchical closeness-based properties reveal cancer survivability and biomarker genes in molecular signaling networks

Specific molecular signaling networks underlie different cancer types and quantitative analyses on those cancer networks can provide useful information about cancer treatments. Their structural metrics can reveal survivability of cancer patients and be used to identify biomarker genes for early cancer detection. In this study, we devised a novel structural metric called hierarchical closeness (HC) entropy and found that it was negatively correlated with 5-year survival rates. We also made an interesting observation that a network of higher HC entropy was likely to be more robust against mutations. This finding suggested that cancers of high HC entropy tend to be incurable because their signaling networks are robust to perturbations caused by treatment. We also proposed a novel core identification method based on the reachability factor in the HC measure. The cores were permitted to decompose such that the negative relationship between HC entropy and cancer survival rate was consistently conserved in every core level. Interestingly, we observed that many promising biomarker genes for early cancer detection reside in the innermost core of a signaling network. Taken together, the proposed analyses of the hierarchical structure of cancer signaling networks may be useful in developing future novel cancer treatments.

iTRAQ-Based Proteomics Identification of Serum Biomarkers of Two Chronic Hepatitis B Subtypes Diagnosed by Traditional Chinese Medicine

Background. Chronic infection with hepatitis B virus (HBV) is a leading cause of cirrhosis and hepatocellular carcinoma. By traditional Chinese medicine (TCM) pattern classification, damp heat stasis in the middle-jiao (DHSM) and liver Qi stagnation and spleen deficiency (LSSD) are two most common subtypes of CHB. Results. In this study, we employed iTRAQ proteomics technology to identify potential serum protein biomarkers in 30 LSSD-CHB and 30 DHSM-CHB patients. Of the total 842 detected proteins, 273 and 345 were differentially expressed in LSSD-CHB and DHSM-CHB patients compared to healthy controls, respectively. LSSD-CHB and DHSM-CHB shared 142 upregulated and 84 downregulated proteins, of which several proteins have been reported to be candidate biomarkers, including immunoglobulin (Ig) related proteins, complement components, apolipoproteins, heat shock proteins, insulin-like growth factor binding protein, and alpha-2-macroglobulin. In addition, we identified that proteins might be potential biomarkers to distinguish LSSD-CHB from DHSM-CHB, such as A0A0A0MS51_HUMAN (gelsolin), PON3_HUMAN, Q96K68_HUMAN, and TRPM8_HUMAN that were differentially expressed exclusively in LSSD-CHB patients and A0A087WT59_HUMAN (transthyretin), ITIH1_HUMAN, TSP1_HUMAN, CO5_HUMAN, and ALBU_HUMAN that were differentially expressed specifically in DHSM-CHB patients. Conclusion. This is the first time to report serum proteins in CHB subtype patients. Our findings provide potential biomarkers can be used for LSSD-CHB and DHSM-CHB.

Microarray and Co-expression Network Analysis of Genes Associated with Acute Doxorubicin Cardiomyopathy in Mice

Clinical use of doxorubicin (DOX) in cancer therapy is limited by its dose-dependent cardiotoxicity. But molecular mechanisms underlying this phenomenon have not been well defined. This study was to investigate the effect of DOX on the changes of global genomics in hearts. Acute cardiotoxicity was induced by giving C57BL/6J mice a single intraperitoneal injection of DOX (15 mg/kg). Cardiac function and apoptosis were monitored using echocardiography and TUNEL assay at days 1, 3 and 5. Myocardial glucose and ATP levels were measured. Microarray assays were used to screen gene expression profiles in the hearts at day 5, and the results were confirmed with qPCR analysis. DOX administration caused decreased cardiac function, increased cardiomyocyte apoptosis and decreased glucose and ATP levels. Microarrays showed 747 up-regulated genes and 438 down-regulated genes involved in seven main functional categories. Among them, metabolic pathway was the most affected by DOX. Several key genes, including 2,3-bisphosphoglycerate mutase (Bpgm), hexokinase 2, pyruvate dehydrogenase kinase, isoenzyme 4 and fructose-2,6-bisphosphate 2-phosphatase, are closely related to glucose metabolism. Gene co-expression networks suggested the core role of Bpgm in DOX cardiomyopathy. These results obtained in mice were further confirmed in cultured cardiomyocytes. In conclusion, genes involved in glucose metabolism, especially Bpgm, may play a central role in the pathogenesis of DOX-induced cardiotoxicity.

Actions of Huangqi decoction against rat liver fibrosis: a gene expression profiling analysis

Background

Huangqi decoction (HQD) is used for liver fibrosis and cirrhosis treatment in Chinese medicine. This study aims to investigate the pharmacological actions of HQD against liver fibrosis in rats by high-throughput gene expression profiling, network analysis and real-time qRT-PCR.

Methods

We analyzed the profiles of differentially expressed genes (DEGs) in dimethylnitrosamine (DMN)-induced liver fibrosis in rat. The liver tissue samples of control group (n = 3), model group (n = 3) and HQD group (n = 3) were examined by microarrays. Pathways were analyzed by KEGG. Pathway-gene and protein–protein interaction (PPI) networks were constructed with Cytoscape software. The expression of candidate genes was verified by qRT-PCR. P values less than 0.05 indicated statistical significance.

Results

Collagen deposition and hydroxyproline (Hyp) content were decreased in the HQD group compared with the model group (P < 0.001), while that of Hyp in the model group were increased compared with the control group (P < 0.001). In comparison with the model group, 1085 DEGs (all P < 0.05, |fold change| >1.5) and 52 pathways in the HQD group were identified. TGF-beta, ECM-receptor interaction, and the cell adhesion molecules pathways were significantly recovered by HQD (P < 0.001). A pathway-gene network was constructed, including 303 DEGs and 52 pathways, and 514 nodes and 2602 edges, among 142 genes with node degrees greater than 10. The expressions of PDGFra, PDGFrb, PDGFb, PDGFd, COL1A1, COL1A2, COL5A2, and THBS1 were significantly down-regulated by HQD (P < 0.001).

Conclusion

HQD down-regulated the expressions of PDGFra, PDGFrb, PDGFb, PDGFd, COL1A1, COL1A2, COL5A2 and THBS1, and TGF-β and PDGF signaling pathways in the DMN-induced liver fibrosis in rats.

Electronic supplementary material

The online version of this article (doi:10.1186/s13020-015-0066-5) contains supplementary material, which is available to authorized users.