A blood-based three-gene signature for the non-invasive detection of early human hepatocellular carcinoma

A trace amine associated receptor mediates antimicrobial immune response in the oyster Crassostrea gigas

Trace amine-associated receptors (TAARs) are a class of G protein-coupled receptors, playing an immunomodulatory function in the neuroinflammatory responses. In the present study, a TAAR homologue with a 7tm_classA_rhodopsin-like domain (designated as CgTAAR1L) was identified in oyster Crassostrea gigas. The abundant CgTAAR1L transcripts were detected in visceral ganglia and haemocytes compared to other tissues, which were 55.35-fold and 32.95-fold (p < 0.01) of those in adductor muscle, respectively. The mRNA expression level of CgTAAR1L in haemocytes significantly increased and reached the peak level at 3 h after LPS or Poly (I:C) stimulation, which was 4.55-fold and 12.35-fold of that in control group, respectively (p < 0.01). After the expression of CgTAAR1L was inhibited by the injection of its targeted siRNA, the mRNA expression levels of interleukin17s (CgIL17-1, CgIL17-5 and CgIL17-6), and defensin (Cgdefh1) significantly decreased at 3 h after LPS stimulation, which was 0.51-fold (p < 0.001), 0.39-fold (p < 0.01), 0.48-fold (p < 0.05) and 0.41-fold (p < 0.05) of that in the control group, respectively. The nuclear translocation of Cgp65 protein was suppressed in the CgTAAR1L-RNAi oysters. Furthermore, the number of Vibrio splendidus in the haemolymph of CgTAAR1L-RNAi oysters significantly increased (4.11-fold, p < 0.001) compared with that in the control group. In contrast, there was no significant difference in phagocytic rate of haemocytes to V. splendidus in the CgTAAR1L-RNAi oysters. These results indicated that CgTAAR1L played an important role in the immune defense against bacterial infection by inducing the expressions of interleukin and defensin.

Programmed Death 1 and Cytotoxic T-Lymphocyte-Associated Protein 4 Gene Expression in Peripheral Blood Mononuclear Cells Can Serve as Prognostic Biomarkers for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a highly aggressive form of liver cancer with poor prognosis. The lack of reliable biomarkers for early detection and accurate diagnosis and prognosis poses a significant challenge to its effective clinical management. In this study, we investigated the diagnostic and prognostic potential of programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) expression in peripheral blood mononuclear cells (PBMCs) in HCC. PD-1 and CTLA-4 gene expression was analyzed comparatively using PBMCs collected from HCC patients and healthy individuals. The results revealed higher PD-1 gene expression levels in patients with multifocal tumors, lymphatic invasion, or distant metastasis than those in their control counterparts. However, conventional serum biomarkers of liver function do not exhibit similar correlations. In conclusion, PD-1 gene expression is associated with OS and PFS and CTLA-4 gene expression is associated with OS, whereas the serum biomarkers analyzed in this study show no significant correlation with survival in HCC. Hence, PD-1 and CTLA-4 expressed in PBMCs are considered potential prognostic biomarkers for patients with HCC that can facilitate prediction of malignancy, response to currently available HCC treatments, and overall survival.

Emerging biomolecules for practical theranostics of liver hepatocellular carcinoma

Most cases of hepatocellular carcinoma (HCC) are able to be diagnosed through regular surveillance in an identifiable patient population with chronic hepatitis B or cirrhosis. Nevertheless, 50% of global cases might present incidentally owing to symptomatic advanced-stage HCC after worsening of liver dysfunction. A systematic search based on PUBMED was performed to identify relevant outcomes, covering newer surveillance modalities including secretory proteins, DNA methylation, miRNAs, and genome sequencing analysis which proposed molecular expression signatures as ideal tools in the early-stage HCC detection. In the face of low accuracy without harmonization on the analytical approaches and data interpretation for liquid biopsy, a more accurate incidence of HCC will be unveiled by using deep machine learning system and multiplex immunohistochemistry analysis. A combination of molecular-secretory biomarkers, high-definition imaging and bedside clinical indexes in a surveillance setting offers a comprehensive range of HCC potential indicators. In addition, the sequential use of numerous lines of systemic anti-HCC therapies will simultaneously benefit more patients in survival. This review provides an overview on the most recent developments in HCC theranostic platform.

Molecular and Metabolic Phenotyping of Hepatocellular Carcinoma for Biomarker Discovery: A Meta-Analysis

Identifying and translating hepatocellular carcinoma (HCC) biomarkers from bench to bedside using mass spectrometry-based metabolomics and lipidomics is hampered by inconsistent findings. Here, we investigated HCC at systemic and metabolism-centric multiomics levels by conducting a meta-analysis of quantitative evidence from 68 cohorts. Blood transcript biomarkers linked to the HCC metabolic phenotype were externally validated and prioritized. In the studies under investigation, about 600 metabolites were reported as putative HCC-associated biomarkers; 39, 20, and 10 metabolites and 52, 12, and 12 lipids were reported in three or more studies in HCC vs. Control, HCC vs. liver cirrhosis (LC), and LC vs. Control groups, respectively. Amino acids, fatty acids (increased 18:1), bile acids, and lysophosphatidylcholine were the most frequently reported biomarkers in HCC. BAX and RAC1 showed a good correlation and were associated with poor prognosis. Our study proposes robust HCC biomarkers across diverse cohorts using a data-driven knowledge-based approach that is versatile and affordable for studying other diseases.

MYC-driven synthesis of Siglec ligands is a glycoimmune checkpoint

The Siglecs (sialic acid-binding immunoglobulin-like lectins) are glycoimmune checkpoint receptors that suppress immune cell activation upon engagement of cognate sialoglycan ligands. The cellular drivers underlying Siglec ligand production on cancer cells are poorly understood. We find the MYC oncogene causally regulates Siglec ligand production to enable tumor immune evasion. A combination of glycomics and RNA-sequencing of mouse tumors revealed the MYC oncogene controls expression of the sialyltransferase St6galnac4 and induces a glycan known as disialyl-T. Using in vivo models and primary human leukemias, we find that disialyl-T functions as a "don't eat me" signal by engaging macrophage Siglec-E in mice or the human ortholog Siglec-7, thereby preventing cancer cell clearance. Combined high expression of MYC and ST6GALNAC4 identifies patients with high-risk cancers and reduced tumor myeloid infiltration. MYC therefore regulates glycosylation to enable tumor immune evasion. We conclude that disialyl-T is a glycoimmune checkpoint ligand. Thus, disialyl-T is a candidate for antibody-based checkpoint blockade, and the disialyl-T synthase ST6GALNAC4 is a potential enzyme target for small molecule-mediated immune therapy.

FASN multi-omic characterization reveals metabolic heterogeneity in pancreatic and prostate adenocarcinoma

BACKGROUND

Pancreatic ductal adenocarcinoma (PDAC) and prostate cancer (PCa) are among the most prevalent malignant tumors worldwide. There is now a comprehensive understanding of metabolic reprogramming as a hallmark of cancer. Fatty acid synthase (FASN) is a key regulator of the lipid metabolic network, providing energy to favor tumor proliferation and development. Whereas the biological role of FASN is known, its response and sensitivity to inhibition have not yet been fully established in these two cancer settings.

METHODS

To evaluate the association between FASN expression, methylation, prognosis, and mutational profile in PDAC and PCa, we interrogated public databases and surveyed online platforms using TCGA data. The STRING database was used to investigate FASN interactors, and the Gene Set Enrichment Analysis platform Reactome database was used to perform an enrichment analysis using data from RNA sequencing public databases of PDAC and PCa. In vitro models using PDAC and PCa cell lines were used to corroborate the expression of FASN, as shown by Western blot, and the effects of FASN inhibition on cell proliferation/cell cycle progression and mitochondrial respiration were investigated with MTT, colony formation assay, cell cycle analysis and MitoStress Test.

RESULTS

The expression of FASN was not modulated in PDAC compared to normal pancreatic tissues, while it was overexpressed in PCa, which also displayed a different level of promoter methylation. Based on tumor grade, FASN expression decreased in advanced stages of PDAC, but increased in PCa. A low incidence of FASN mutations was found for both tumors. FASN was overexpressed in PCa, despite not reaching statistical significance, and was associated with a worse prognosis than in PDAC. The biological role of FASN interactors correlated with lipid metabolism, and GSEA indicated that lipid-mediated mitochondrial respiration was enriched in PCa. Following validation of FASN overexpression in PCa compared to PDAC in vitro, we tested TVB-2640 as a FASN inhibitor. PCa proliferation arrest was modulated by FASN inhibition in a dose- and time-dependent manner, whereas PDAC proliferation was not altered. In line with this finding, mitochondrial respiration was found to be more affected in PCa than in PDAC. FASN inhibition interfered with metabolic signaling causing lipid accumulation and affecting cell viability with an impact on the replicative processes.

CONCLUSIONS

FASN exhibited differential expression patterns in PDAC and PCa, suggesting a different evolution during cancer progression. This was corroborated by the fact that both tumors responded differently to FASN inhibition in terms of proliferative potential and mitochondrial respiration, indicating that its use should reflect context specificity.

Comparative Transcriptional Signature Analysis of Peripheral Blood Mononuclear Cells in Early Stage of Hepatitis B-related Hepatocellular Carcinoma

Background: Hepatocellular carcinoma (HCC) is a prevalent and life-threatening tumor with high morbidity and mortality. Proper prediction and prognosis are incredibly stressed to diagnose HCC and increase patient survival. Objectives: This research aims to evaluate gene expression levels of pre-differentiated transcripts for those suffering from chronic hepatitis B (CHB) and HCC. Methods: To examine the previously analyzed peripheral blood mononuclear cells (PBMCs) transcriptomic array data, we selected seven differentially expressed genes (DEGs) in normal versus CHB and CHB versus HCC (CD44, SP3, USP8, E2F2, UFM1, IFN regulative factor binding protein 2 (IRF2BP2), and T-cell intracellular antigen 1 (TIA1)). The study included individuals with treatment-naïve CHB (n = 30) and primary HCC (n = 25) and healthy controls (n = 15). Subsequently, the expression of genes was assayed using qRT-PCR. A phylogenetic evaluation was performed using direct sequencing of HBsAg. Results: In HCC patients, 60% (n = 15) were HBeAg-positive. HBeAg was negative in all CHB patients, but all were anti-HBe-positive. The hepatitis B virus (HBV) load of HCC patients was more than that of CHB subjects. All patients were of the Iranian race and HBV D genotype. The expression of five transcriptional markers (CD44, SP3, USP8, E2F2, and UFM1) was higher in HCC patients than in CHB and healthy subjects, which was similar to the initial microarray data analysis. Conclusions: Transcriptional signatures may be related to the pathogenesis of HCC and used as diagnostic biological markers for the initial monitoring and prediction of HCC.

Intravenous Immunoglobulins Promote an Expansion of Monocytic Myeloid-Derived Suppressor Cells (MDSC) in CVID Patients

Common variable immunodeficiency disorders (CVID), the most common primary immune deficiency, includes heterogeneous syndromes characterized by hypogammaglobulinemia and impaired antibody responses. CVID patients frequently suffer from recurrent infections and inflammatory conditions. Currently, immunoglobulin replacement therapy (IgRT) is the first-line treatment to prevent infections and aminorate immune alterations in CVID patients. Intravenous Immunoglobulin (IVIg), a preparation of highly purified poly-specific IgG, is used for treatment of immunodeficiencies as well as for autoimmune and inflammatory disorders, as IVIg exerts immunoregulatory and anti-inflammatory actions on innate and adaptive immune cells. To determine the mechanism of action of IVIg in CVID in vivo, we determined the effect of IVIg infusion on the transcriptome of peripheral blood mononuclear cells from CVID patients, and found that peripheral blood monocytes are primary targets of IVIg in vivo, and that IVIg triggers the acquisition of an anti-inflammatory gene profile in human monocytes. Moreover, IVIg altered the relative proportions of peripheral blood monocyte subsets and enhanced the proportion of CD14⁺ cells with a transcriptional, phenotypic, and functional profile that resembles that of monocytic myeloid-derived suppressor cells (MDSC). Therefore, our results indicate that CD14 + MDSC-like cells might contribute to the immunoregulatory effects of IVIg in CVID and other inflammatory disorders.

CRISPRs in the human genome are differentially expressed between malignant and normal adjacent to tumor tissue

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) have been identified in bacteria, archaea and mitochondria of plants, but not in eukaryotes. Here, we report the discovery of 12,572 putative CRISPRs randomly distributed across the human chromosomes, which we termed hCRISPRs. By using available transcriptome datasets, we demonstrate that hCRISPRs are distinctively expressed as small non-coding RNAs (sncRNAs) in cell lines and human tissues. Moreover, expression patterns thereof enabled us to distinguish normal from malignant tissues. In prostate cancer, we confirmed the differential hCRISPR expression between normal adjacent and malignant primary prostate tissue by RT-qPCR and demonstrate that the SHERLOCK and DETECTR dipstick tools are suitable to detect these sncRNAs. We anticipate that the discovery of CRISPRs in the human genome can be further exploited for diagnostic purposes in cancer and other medical conditions, which certainly will lead to the development of point-of-care tests based on the differential expression of the hCRISPRs.

Integrated Analysis of miRNA and mRNA Expression Profiles Reveals the Molecular Mechanism of Posttraumatic Stress Disorder and Therapeutic Drugs

Purpose

Post-traumatic stress disorder (PTSD) is a result of trauma exposure and is related to psychological suffering as a long-lasting health issue. Further analysis of the networks and genes involved in PTSD are critical to the molecular mechanisms of PTSD.

Methods

In this study, we aimed to identify key genes and molecular interaction networks involved in the pathogenesis of PTSD by integrating mRNA and miRNA data.

Results

By integrating three high-throughput datasets, 5606 differentially expressed genes (DEGs) were detected, including five differentially expressed miRNAs (DEmiRNAs) and 5525 differentially expressed mRNAs (DEmRNAs). Nineteen upregulated and 46 downregulated DEmRNAs were identified in both GSE64813 and GSE89866 datasets, while five upregulated DEmiRNAs were found in the GSE87768 dataset. Functional annotations of these DEmRNAs indicated that they were mainly enriched in blood coagulation, cell adhesion, platelet activation, and extracellular matrix (ECM)-receptor interaction. Integrated protein-protein and miRNA-protein interaction networks among the DEGs were established with the help of 65 nodes and 121 interactions. Finally, 286 small molecules were obtained based on the Drug-Gene Interaction database (DGIdb). Three genes, prostaglandin-endoperoxide synthase 1 (PTGS1), beta-tubulin gene (TUBB1), and cyclin-dependent kinase inhibitor 1A (CDKN1A), were the most promising targets for PTSD therapy. Additionally, the present study also provided a higher performance diagnostic model for PTSD based on 17 DEmRNAs, which was validated in two independent datasets, GSE109409 and GSE63878.

Conclusion

Our data provides a new molecular aspect that ECM-receptor interaction and the platelet activation process could be the potential molecular mechanism of PTSD, and the genes involved in this process may be promising therapeutic targets. A higher-performance diagnostic model for PTSD has also been identified.

Identifying Potential New Gene Expression-Based Biomarkers in the Peripheral Blood Mononuclear Cells of Hepatitis B-Related Hepatocellular Carcinoma

OBJECTIVE

The analysis of the gene expression of peripheral blood mononuclear cells (PBMCs) is important to clarify the pathogenesis of hepatocellular carcinoma (HCC) and the detection of suitable biomarkers. The purpose of this investigation was to use RNA-sequencing to screen the appropriate differentially expressed genes (DEGs) in the PBMCs for the HCC.

METHODS

The comprehensive transcriptome of extracted RNA of PBMC (n = 20) from patients with chronic hepatitis B (CHB), liver cirrhosis, and early stage of HCC (5 samples per group) was carried out using RNA-sequencing. All raw RNA-sequencing data analyses were performed using conventional RNA-sequencing analysis tools. Next, gene ontology (GO) analyses were carried out to elucidate the biological processes of DEGs. Finally, relative transcript abundance of selected DEGs was verified using qRT-PCR on additional validation groups.

RESULTS

Specifically, 13, 1262, and 1450 DEGs were identified for CHB, liver cirrhosis, and HCC, when compared with the healthy controls. GO enrichment analysis indicated that HCC is closely related to the immune response. Seven DEGs (TYMP, TYROBP, CD14, TGFBI, LILRA2, GNLY, and GZMB) were common to HCC, cirrhosis, and CHB when compared to healthy controls. The data revealed that the expressions of these 7 DEGs were consistent with those from the RNA-sequencing results. Also, the expressions of 7 representative genes that had higher sensitivity were obtained by receiver operating characteristic analysis, which indicated their important diagnostic accuracy for HBV-HCC.

CONCLUSION

This study provides us with new horizons into the biological process and potential prospective clinical diagnosis and prognosis of HCC in the near future.

SPARC Overexpression Promotes Liver Cancer Cell Proliferation and Tumor Growth

Background: Secreted protein acidic and rich in cysteine (SPARC) plays an important role in cancer development. The roles of SPARC in the liver hepatocellular carcinoma (LIHC) are unclear. Methods: GEPIA2 and UALCAN were used to analyze the SPARC mRNA expression levels in LIHC based on the TCGA database. The GEO database was used to verify the analysis results. Immunohistochemical (IHC) analysis was used to investigate the SPARC protein levels in LIHC tissues. The Kaplan-Meier (KM) plotter was used to analyze the correlation between SPARC and prognosis. The serum SPARC levels were measured by ELISA. CCK8 and murine xenograft models were used to investigate the effect of SPARC on the liver cancer growth in vitro and in vivo. SPARC-correlated genes were screened by LinkedOmics. Results: Based on the TCGA and GEO databases, the analysis showed that the SPARC mRNA expression levels were increased in tumor tissues and peripheral blood mononuclear cell (PBMC) from LIHC compared to normal controls. The IHC analysis showed an increased level of SPARC in LIHC tissues compared to adjacent non-tumor tissues. However, we found that the serum SPARC levels were lower in LIHC than those in healthy controls. The KM plotter showed that there was no significant correlation between the SPARC mRNA levels and overall survival. However, in sorafenib-treated LIHC patients, the high SPARC expression predicts favorable prognosis. Furthermore, the endogenous SPARC overexpression promotes liver cancer cell proliferation in vitro and tumor growth in vivo, while there was no significant effect of exogenous SPARC treatment on liver cancer cell proliferation. Function enrichment analysis of SPARC-correlated genes indicated a critical role of interaction with an extracellular matrix in SPARC-promoting cancer cell proliferation. Conclusion: SPARC mRNAs were increased in LIHC tumor tissues, and SPARC overexpression may promote the liver cancer growth. Further studies are needed to clarify the potential prognostic value of SPARC, both in tissues and in circulation.

Identification of Gene Signature as Diagnostic and Prognostic Blood Biomarker for Early Hepatocellular Carcinoma Using Integrated Cross-Species Transcriptomic and Network Analyses

Background: Hepatocellular carcinoma (HCC) is considered the most common type of liver cancer and the fourth leading cause of cancer-related deaths in the world. Since the disease is usually diagnosed at advanced stages, it has poor prognosis. Therefore, reliable biomarkers are urgently needed for early diagnosis and prognostic assessment. Methods: We used genome-wide gene expression profiling datasets from human and rat early HCC (eHCC) samples to perform integrated genomic and network-based analyses, and discovered gene markers that are expressed in blood and conserved in both species. We then used independent gene expression profiling datasets for peripheral blood mononuclear cells (PBMCs) for eHCC patients and from The Cancer Genome Atlas (TCGA) database to estimate the diagnostic and prognostic performance of the identified gene signature. Furthermore, we performed functional enrichment, interaction networks and pathway analyses. Results: We identified 41 significant genes that are expressed in blood and conserved across species in eHCC. We used comprehensive clinical data from over 600 patients with HCC to verify the diagnostic and prognostic value of 41-gene-signature. We developed a prognostic model and a risk score using the 41-geneset that showed that a high prognostic index is linked to a worse disease outcome. Furthermore, our 41-gene signature predicted disease outcome independently of other clinical factors in multivariate regression analysis. Our data reveals a number of cancer-related pathways and hub genes, including EIF4E, H2AFX, CREB1, GSK3B, TGFBR1, and CCNA2, that may be essential for eHCC progression and confirm our gene signature's ability to detect the disease in its early stages in patients' biological fluids instead of invasive procedures and its prognostic potential. Conclusion: Our findings indicate that integrated cross-species genomic and network analysis may provide reliable markers that are associated with eHCC that may lead to better diagnosis, prognosis, and treatment options.

RUNX2 and LAMC2: promising pancreatic cancer biomarkers identified by an integrative data mining of pancreatic adenocarcinoma tissues

Pancreatic carcinoma (PC) is a severe disease associated with high mortality. Although strategies for cancer therapy have made great progress, outcomes of pancreatic carcinoma patients remain extremely poor. Therefore, it is urgent to find novel biomarkers and therapeutic targets. To identify biomarkers for early diagnosis and therapy, three mRNA microarray datasets and two miRNA datasets were selected, and combinative analysis was performed by GEO2R. Functional and pathway enrichment analysis were performed using DAVID database. MiRTarBase, miRWalk and Diana Tools were used to get key genes. TCGA, HPA and western blotting were used to verify diagnostic and prognostic value of key genes. By integrating mRNA and miRNA expression profiles, we identified 114 differentially expressed genes and 114 differentially expressed miRNAs, respectively. Then, three overlapping key genes, RUNX2, LAMC2 and FBXO32, were found. Their protein levels in pancreatic tissue from PC patients and normal people were analyzed by immunohistochemical staining and western blotting. RUNX2 showed a potential property to identify PC. Aberrant over-expression of LAMC2 was associated with poor prognosis of PC patients, tumor status and subtypes. In summary, our current study identified that RUNX2 and LAMC2 may be promising targets for early diagnosis and therapy of PC patients.

Identifying the biomarkers and pathways associated with hepatocellular carcinoma based on an integrated analysis approach

BACKGROUND AND AIMS

Hepatocellular carcinoma (HCC) is one of the most common causes of cancer-related death worldwide. The molecular mechanism underlying HCC is still unclear. In this study, we conducted a comprehensive analysis to explore the genes, pathways and their interactions involved in HCC.

METHODS

We analysed the gene expression datasets corresponding to 488 samples from 10 studies on HCC and identified the genes differentially expressed in HCC samples. Then, the genes were compared against Phenolyzer and GeneCards to screen those potentially associated with HCC. The features of the selected genes were explored by mapping them onto the human protein-protein interaction network, and a subnetwork related to HCC was constructed. Hub genes in this HCC specific subnetwork were identified, and their relevance with HCC was investigated by survival analysis.

RESULTS

We identified 444 differentially expressed genes (177 upregulated and 267 downregulated) related to HCC. Functional enrichment analysis revealed that pathways like p53 signalling and chemical carcinogenesis were eriched in HCC genes. In the subnetwork related to HCC, five disease modules were detected. Further analysis identified six hub genes from the HCC specific subnetwork. Survival analysis showed that the expression levels of these genes were negatively correlated with survival rate of HCC patients.

CONCLUSIONS

Based on a systems biology framework, we identified the genes, pathways, as well as the disease specific network related to HCC. We also found novel biomarkers whose expression patterns were correlated with progression of HCC, and they could be candidates for further investigation.

The expression of FLNA and CLU in PBMCs as a novel screening marker for hepatocellular carcinoma

Early detection improves survival and increases curative probability in hepatocellular carcinoma (HCC). Peripheral blood mononuclear cells (PBMCs) can provide an inexpensive, less-invasive and highly accurate method. The objective of this study is to find the potential marker for HCC screening, utilizing gene expression of the PBMCs. Data from the NCBI GEO database of gene expression in HCC patients and healthy donor's PBMCs was collected. As a result, GSE 49515 and GSE 58208 were found. Using both, a statistical significance test was conducted in each gene expression of each data set which resulted in 187 genes. We randomized three selected genes (FLNA, CAP1, and CLU) from the significant p-value group (p-values < 0.001). Then, a total of 76 healthy donors, 153 HCC, 20 hepatic fibrosis, 20 non-alcoholic fatty liver were collected. Quantitative RT-PCR (qRT-PCR) was performed in cDNA from all blood samples from the qRT-PCR, The Cycle threshold (Ct) value of FLNA, CLU, CAP1 of HCC group (28.47 ± 4.43, 28.01 ± 3.75, 29.64 ± 3.90) were lower than healthy group (34.23 ± 3.54, 32.90 ± 4.15, 32.18 ± 5.02) (p-values < 0.0001). The accuracy, sensitivity and specificity of these genes as a screening tool were: FLNA (80.8%, 88.0%, 65.8%), CLU (63.4%, 93.3%, 31.3%), CAP1 (67.2%, 83.3%, 39.1%). The tests were performed in two and three gene combinations. Results demonstrated high accuracy of 86.2%, sensitivity of 85% and specificity of 88.4% in the FLNA and CLU combination. Furthermore, after analyzed using hepatic fibrosis and non-alcoholic fatty liver as a control, the FLNA and CLU combination is shown to have accuracy of 76.9%, sensitivity of 77.6% and specificity of 75%. Also, we founded that our gene combination performs better than the current gold standard for HCC screening. We concluded that FLNA and CLU combination have high potential for being HCC novel markers. Combined with current tumor markers, further research of the gene’s expression might help identify more potential markers and improve diagnosis methods.

Identification of BHLHE40 expression in peripheral blood mononuclear cells as a novel biomarker for diagnosis and prognosis of hepatocellular carcinoma

Novel and sensitive biomarkers is highly required for early detection and predicting prognosis of hepatocellular carcinoma (HCC). Here, we investigated transcription profiles from peripheral blood mononuclear cells (PBMCs) of 8 patients with HCC and PBMCs from co-culture model with HCC using RNA-Sequencing. These transcription profiles were cross compared with published microarray datasets of PBMCs in HCC to identify differentially expressed genes (DEGs). A total of commonly identified of 24 DEGs among these data were proposed as cancer-induced genes in PBMCs, including 18 upregulated and 6 downregulated DEGs. The KEGG pathway showed that these enriched genes were mainly associated with immune responses. Five up-regulated candidate genes including BHLHE40, AREG, SOCS1, CCL5, and DDIT4 were selected and further validated in PBMCs of 100 patients with HBV-related HCC, 100 patients with chronic HBV infection and 100 healthy controls. Based on ROC analysis, BHLHE40 and DDIT4 displayed better diagnostic performance than alpha-fetoprotein (AFP) in discriminating HCC from controls. Additionally, BHLHE40 and DDIT4 had high sensitivity for detecting AFP-negative and early-stage HCC. BHLHE40 was also emerged as an independent prognostic factor of overall survival of HCC. Together, our study indicated that BHLHE40 in PBMCs could be a promising diagnostic and prognostic biomarker for HBV-related HCC.

Identification of potential biomarkers of peripheral blood mononuclear cell in hepatocellular carcinoma using bioinformatic analysis: A protocol for systematic review and meta-analysis

BACKGROUND

Hepatocellular carcinoma (HCC) is the cause of an overwhelming number of cancer-related deaths across the world. Developing precise and noninvasive biomarkers is critical for diagnosing HCC. Our research was designed to explore potentially useful biomarkers of host peripheral blood mononuclear cell (PBMC) in HCC by integrating comprehensive bioinformatic analysis.

METHODS

Gene expression data of PBMC in both healthy individuals and patients with HCC were extracted from the Gene Expression Omnibus (GEO) to identify differentially expressed genes (DEGs). The gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were applied to annotate the function of DEGs. Protein-protein interaction analysis was performed to screen the hub genes from DEGs. cBioportal database analysis was performed to assess the prognostic significance of hub genes. The Cancer Cell Line Encyclopedia (CCLE) and The Human Protein Atlas (HPA) database analyses were performed to confirm the expression levels of the hub genes in HCC cells and tissue.

RESULTS

A total of 95 DEGs were screened. Results of the GO analysis revealed that DEGs were primarily involved in platelet degranulation, cytoplasm, and protein binding. Results of the KEGG analysis indicated that DEGs were primarily enriched in focal adhesion. Five genes, namely, myosin light chain kinase (MYLK), interleukin 1 beta (IL1B), phospholipase D1 (PLD1), cortactin (CTTN), and moesin (MSN), were identified as hub genes. A search in the CCLE and HPA database showed that the expression levels of these hub genes were remarkably increased in the HCC samples. Survival analysis revealed that the overexpression of MYLK, IL1B, and PLD1 may have a significant effect on HCC survival. The aberrant high expression levels of MYLK, IL1B, and PLD1 strongly indicated worse prognosis in patients with HCC.

CONCLUSIONS

The identified hub genes may be closely linked with HCC tumorigenicity and may act as potentially useful biomarkers for the prognostic prediction of HCC in PBMC samples.

Polymeric immunoglobulin receptor (PIGR) exerts oncogenic functions via activating ribosome pathway in hepatocellular carcinoma

Objective: This report aimed to investigate the potential mechanism of polymeric immunoglobulin receptor (PIGR) in promoting cancer development in hepatocellular carcinoma (HCC). Methods: PIGR expression was investigated in Gene Expression Omnibus (GEO), Oncomine, The Cancer Genome Atlas (TCGA) and The Human Protein Atlas (HPA) databases. Relationships between PIGR and HCC survival and clinico-pathological features were conducted in TCGA. RNAseq of PIGR overexpression and knockdown samples in Bel-7404 cells were performed for identifying potential mechanisms. Results: PIGR was significantly overexpressed in tumors compared to nontumors and in HCC serum peripheral blood mononuclear cells (PBMC) than in healthy individuals (all p < 0.05). In TCGA, PIGR was highly altered in 14% HCC patients. PIGR upregulation was significantly associated with poor disease-free survival (p < 0.05). More patients recurred/progressed in PIGR altered group compared to unaltered group (p < 0.01). PIGR was significantly higher in HCC patients with incomplete cirrhosis (p < 0.001) and established cirrhosis (p < 0.05). Fewer patients had N₀ lymph node stage in PIGR altered group than those in the unaltered group (p < 0.05). PIGR RNAseq revealed that ribosome signaling was the common pathway in PIGR overexpression and PIGR knockdown samples. RNAseq analysis indicated that RPL10, RPL10A, RPL12, RPL19, RPL36, RPL38, RPL41, RPL6, RPL8, RPS12, RPS14, RPS15A, RPS2, RPS27A and RPSA were significantly upregulated in PIGR overexpression group and downregulated in PIGR underexpression group (all p < 0.05). Conclusions: Aberrant PIGR was associated with HCC recurrence, and PIGR stimulated ribosome pathway might be a potential mechanism.

Recent advances targeting C-C chemokine receptor type 2 for liver diseases in monocyte/macrophage

Liver plays a critical role in metabolism, nutrient storage and detoxification. Emergency signals or appropriate immune response leads to pathological inflammation and breaks the steady state when liver dysfunction appears, which makes body more susceptible to chronic liver infection, autoimmune diseases and tumour. Compelling proof has illustrated the non-redundant importance of C-C chemokine receptor type 2 (CCR2), one of G-protein-coupled receptors, in different diseases. Selectively expressed on the surface of cells, CCR2 is involved in various signalling pathways and regulates the migration of cells. Especially, a peculiar role of CCR2 has been identified within decades in the onset and progression of hepatic diseases, which led to particular focusing on CCR2 as a new therapeutic and diagnostic target for non-alcoholic fatty liver disease and hepatocellular carcinoma. In this review, we discuss the effect of CCR2 in monocytes/macrophages on liver diseases. The application and translation of the decades of discoveries into therapies promise novel approaches in the treatment of liver disease.

DYNLL1 is hypomethylated and upregulated in a tumor stage- and grade-dependent manner and associated with increased mortality in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is the fifth most common cancer worldwide and cellular mechanisms regulating HCC pathogenesis and progression are not completely understood. DYNLL1 is essential for the development and expansion of MYC-driven B cell lymphoma, and also regulates genomic stability and responses to DNA-damaging chemotherapy in BRCA1-deficient tumors. However, the role and regulation of DYNLL1 has not been previously studied in the context of HCC. Here we report that DYNLL1 gene is hypomethylated and its expression is upregulated in HCC patients compared to healthy controls. The expression of DYNLL1 changes in a tumor grade- and stage-dependent manner in HCC. In this study, we further show that high DYNLL1 expression results in shorter overall and progression-free survival in hepatocellular carcinoma patients. Similar to DYNLL1, one of its protein interactors, RACK1, also shows decreased CpG-aggregated methylation and increased expression in HCC. RACK1 expression increases from early to late stage and from low to high grade in HCC. We found that high RACK1 expression is significantly associated with increased mortality of HCC patients. The present study shows that the epigenetic regulation of DYNLL1 and its consequent upregulation might be contributing to cancer development and progression in HCC. Its higher expression in late stage or high grade HCC may favor more aggressive disease as pointed by the increased mortality in high expression cohort. A better mechanistic understanding of the role of DYNLL1 in HCC will be needed to develop targeted treatment strategies in the future.

Identification of Gene Signatures for Diagnosis and Prognosis of Hepatocellular Carcinomas Patients at Early Stage

The onset of liver cancer is insidious. Currently, there is no effective method for the early detection of hepatocellular carcinoma (HCC). Transcriptomic profiles of 826 tissue samples from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), Genotype tissue expression (GTEx), and International Cancer Genome Consortium (ICGC) databases were utilized to establish models for early detection and surveillance of HCC. The overlapping differentially expressed genes (DEGs) were screened by elastic net and robust rank aggregation (RRA) analyses to construct the diagnostic prediction model for early HCC (DP.eHCC). Prognostic prediction genes were screened by univariate cox regression and lasso cox regression analyses to construct the survival risk prediction model for early HCC (SP.eHCC). The relationship between the variation of transcriptome profile and the oncogenic risk-score of early HCC was analyzed by combining Weighted Correlation Network Analysis (WGCNA), Gene Set Enrichment Analysis (GSEA), and genome networks (GeNets). The results showed that the AUC of DP.eHCC model for the diagnosis of early HCC was 0.956 (95% CI: 0.941–0.972; p < 0.001) with a sensitivity of 90.91%, a specificity of 92.97%. The SP.eHCC model performed well for predicting the overall survival risk of HCC patients (HR = 10.79; 95% CI: 6.16–18.89; p < 0.001). The oncogenesis of early HCC was revealed mainly involving in pathways associated with cell proliferation and tumor microenvironment. And the transcription factors including EZH2, EGR1, and SOX17 were screened in the genome networks as the promising targets used for precise treatment in patients with HCC. Our findings provide robust models for the early diagnosis and prognosis of HCC, and are crucial for the development of novel targets applied in the precision therapy of HCC.

Dynamic edge-based biomarker non-invasively predicts hepatocellular carcinoma with hepatitis B virus infection for individual patients based on blood testing

Hepatitis B virus (HBV)-induced hepatocellular carcinoma (HCC) is a major cause of cancer-related deaths in Asia and Africa. Developing effective and non-invasive biomarkers of HCC for individual patients remains an urgent task for early diagnosis and convenient monitoring. Analyzing the transcriptomic profiles of peripheral blood mononuclear cells from both healthy donors and patients with chronic HBV infection in different states (i.e. HBV carrier, chronic hepatitis B, cirrhosis, and HCC), we identified a set of 19 candidate genes according to our algorithm of dynamic network biomarkers. These genes can both characterize different stages during HCC progression and identify cirrhosis as the critical transition stage before carcinogenesis. The interaction effects (i.e. co-expressions) of candidate genes were used to build an accurate prediction model: the so-called edge-based biomarker. Considering the convenience and robustness of biomarkers in clinical applications, we performed functional analysis, validated candidate genes in other independent samples of our collected cohort, and finally selected COL5A1, HLA-DQB1, MMP2, and CDK4 to build edge panel as prediction models. We demonstrated that the edge panel had great performance in both diagnosis and prognosis in terms of precision and specificity for HCC, especially for patients with alpha-fetoprotein-negative HCC. Our study not only provides a novel edge-based biomarker for non-invasive and effective diagnosis of HBV-associated HCC to each individual patient but also introduces a new way to integrate the interaction terms of individual molecules for clinical diagnosis and prognosis from the network and dynamics perspectives.

microRNA-519d Induces Autophagy and Apoptosis of Human Hepatocellular Carcinoma Cells Through Activation of the AMPK Signaling Pathway via Rab10

Background and Aim

Hepatocellular carcinoma (HCC) is a type of cancer with high mortality rates. The overexpression of microRNA-519d (miR-519d) has been explored in different types of cancers, which could significantly help suppress cancer development. This study aimed to investigate the interaction of miR-519d with its target gene, Rab10, as well as its effects on cell proliferation and autophagy in HCC cells through modulation of the AMPK signaling pathway.

Methods

Microarray analysis was used to analyze the differentially expressed genes in HCC, and the target genes of the screened-out miRNA were predicted and verified. The expression of miR-519d and Rab10, AMPK signaling pathway-related proteins, apoptosis- and autophagy-related proteins was determined by RT-qPCR and Western blot analysis in HCC tissues and cell lines. Lastly, the effects of miR-519d and Rab10 in HCC cell proliferation, apoptosis, and mouse tumour xenograft in vivo were examined through gain- and loss-of-function experiments.

Results

MiR-519d was down-regulated and Rab10 was upregulated in HCC tissues and cell lines. Overexpression of miR-519d decreased the expression of Rab10, mTOR, and Bcl-2, but increased the expression of Bax, Beclin1, Atg5, and p53. Upregulated miR-519d and downregulated Rab10 expression suppressed cell proliferation and induced cell apoptosis and autophagy in HCC cells. Finally, upregulation of miR-519d inhibited tumour growth in vivo.

Conclusion

The result obtained in this study indicates that up-regulation of miR-519d inhibits proliferation and promotes apoptosis and autophagy of HCC cells through activation of the AMPK signaling pathway via downregulating Rab10, which provides a potential target for the treatment of HCC.

Discovery of candidate gene expression signatures in peripheral blood for the screening of cervical cancer

Aim: To investigate whether cervical cancer (CC) and cervical intraepithelial neoplasia (CIN) can be screened by analyzing gene expression profiling of peripheral blood. Methods: RNA-sequencing analysis of blood was performed on 11 CC patients, 21 CIN patients and 19 healthy controls (H). Fifty-nine genes were validated by quantitative real-time PCR using blood samples from 46 H, 83 CC and 32 CIN patients. Results: There were significant differences in the expression levels of six genes between CC and H, five genes between CIN and H and four genes between CC and CIN (p < 0.05). Four genes discriminated cervical lesions from H with a sensitivity of 82.61%, a specificity of 87.83% and an area under the curve of 0.8981. Three genes discriminated CC from CIN with a sensitivity of 53.13%, a specificity of 96.39% and an area under the curve of 0.7786. Conclusion: Our findings provided a promising noninvasive quantitative real-time PCR diagnostic assay of CC and CIN.

Oncogenic Roles of RAD51AP1 in Tumor Tissues Related to Overall Survival and Disease-Free Survival in Hepatocellular Carcinoma

OBJECTIVE

This study aimed to investigate the associations between RAD51AP1 and the outcomes of hepatocellular carcinoma (HCC).

METHODS

RAD51AP1 expression levels were compared in Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) datasets. The Liver Hepatocellular Carcinoma (TCGA, Provisional) and GSE36376 datasets were used for survival analysis. RAD51AP1 associations with clinicopathological features were determined with the GSE36376 dataset.

RESULTS

RAD51AP1 mRNA expression was significantly upregulated in advanced liver fibrosis samples (S3-4 vs. S0-2 and G3-4 vs. G0-2) from hepatitis B virus (HBV)-related liver fibrosis patients and in tumor tissues and peripheral blood mononuclear cells (PBMCs) from HCC patients (all P < 0.05). HCC patients with high RAD51AP1 expression had significantly worse overall survival (OS) and disease-free survival (DFS) than those with low RAD51AP1 expression (P = 0.0034 and P = 0.0012, respectively) in the TCGA dataset, and these findings were validated with the GSE36376 dataset (P = 0.0074 and P = 0.0003, respectively). A Cox regression model indicated that RAD51AP1 was a risk factor for OS and DFS in HCC patients in GSE36376 (HR = 1.54, 95% CI = 1.02-2.32, P = 0.04 and HR = 1.71, 95% CI = 1.22-2.39, P = 0.002, respectively). Moreover, RAD51AP1 mRNA expression increased gradually with increasing tumor stage, including stratification by American Joint Committee on Cancer (AJCC) stages, Barcelona Clinic Liver Cancer (BCLC) stages and Edmondson grades. In addition, RAD51AP1 was overexpressed in HCC patients with intrahepatic metastasis, major portal vein invasion, vascular invasion and/or an alpha-fetoprotein (AFP) level > 300 ng/ml.

CONCLUSIONS

Contributing to an advanced tumor stage, intrahepatic metastasis, vascular invasion and AFP level elevation, RAD51AP1 upregulation was significantly associated with OS and DFS in HCC patients.

A twenty gene-based gene set variation score reflects the pathological progression from cirrhosis to hepatocellular carcinoma

The molecular mechanism of the pathological progression from cirrhosis to hepatocellular carcinoma (HCC) remains elusive. In the present study, tissue samples from normal liver, cirrhosis and HCC were subjected to differentially gene expression analysis, weighted gene correlation network analysis to identify the twenty hub genes (TOP2A, CDC20, PTTG1, CDCA5, CCNB2, PRC1, KIF20A, SF3B4, HSP90AB1, FOXD2, PLOD3, CCT3, SETDB1, VPS45, SPDL1, RACGAP1, MED24, KIAA0101, ZNF282, and USP21) in the pathological progression from cirrhosis to HCC. Each sample was calculated a hub gene set variation analysis (HGSVA) score using Gene Set Variation Analysis, The HGSVA score significantly increased with progression from cirrhosis to HCC, and this result was validated in two independent data sets. Moreover, this score may be used as a blood-based marker for HCC and is an independent prognostic factor of recurrence-free survival (RFS) and overall survival (OS). High expression of the hub genes may be driven by hypomethylation. The twenty gene-based gene set variation score may reflect the pathological progression from cirrhosis to HCC and is an independent prognostic factor for both OS and RFS.

In silico identification of EP400 and TIA1 as critical transcription factors involved in human hepatocellular carcinoma relapse

Hepatocellular carcinoma (HCC) is the second leading cause of cancer-associated mortality worldwide. Transcription factors (TFs) are crucial proteins that regulate gene expression during cancer progression; however, the roles of TFs in HCC relapse remain unclear. To identify the TFs that drive HCC relapse, the present study constructed co-expression network and identified the Tan module the most relevant to HCC relapse. Numerous hub TFs (highly connected) were subsequently obtained from the Tan module according to the intra-module connectivity and the protein-protein interaction network connectivity. Next, E1A-binding protein p400 (EP400) and TIA1 cytotoxic granule associated RNA binding protein (TIA1) were identified as hub TFs differentially connected between the relapsed and non-relapsed subnetworks. In addition, zinc finger protein 143 (ZNF143) and Yin Yang 1 (YY1) were also identified by using the plugin iRegulon in Cytoscape as master upstream regulatory elements, which could potentially regulate expression of the genes and TFs of the Tan module, respectively. The Kaplan-Meier (KM) curves obtained from KMplot and Gene Expression Profiling Interactive Analysis tools confirmed that the high expression of EP400 and TIA1 were significantly associated with shorter relapse-free survival and disease-free survival of patients with HCC. Furthermore, the KM curves from the UALCAN database demonstrated that high EP400 expression significantly reduced the overall survival of patients with HCC. EP400 and TIA1 may therefore serve as potential prognostic and therapeutic biomarkers.

Loss of alanine-glyoxylate and serine-pyruvate aminotransferase expression accelerated the progression of hepatocellular carcinoma and predicted poor prognosis

BACKGROUND

Accumulated studies reported abnormal gene expression profiles of hepatocellular carcinoma (HCC) by cDNA microarray. We tried to merge cDNA microarray data from different studies to search for stably changed genes, and to find out better diagnostic and prognostic markers for HCC.

METHODS

A systematic review was performed by searching publications indexed in Pubmed from March 1, 2001 to July 1, 2016. Studies that reporting cDNA microarray profiles in HCC, containing both tumor and nontumor data and published in English-language were retrieved. The differentially expressed genes from eligible studies were summarized and ranked according to the frequency. High frequency genes were subjected to survival analyses. The expression and prognostic value of alanine-glyoxylate and serine-pyruvate aminotransferase (AGXT) was further evaluated in HCC datasets in Oncomine and an independent HCC tissue array cohort. The role of AGXT in HCC progression was evaluated by proliferation and migration assays in a human HCC cell line.

RESULTS

A total of 43 eligible studies that containing 1917 HCC patients were included, a list of 2022 non redundant abnormally expressed genes in HCC were extracted. The frequencies of reported genes were ranked. We finally obtained a list of only five genes (AGXT; ALDOB; CYP2E1; IGFBP3; TOP2A) that were differentially expressed in tumor and nontumor tissues across studies and were significantly correlated to HCC prognosis. Only AGXT had not been reported in HCC. Reduced expression of AGXT reflected poor differentiation of HCC and predicts poor survival. Knocking down of AGXT enhanced cell proliferation and migration of HCC cell line.

CONCLUSIONS

The present study supported the feasibility and necessity of systematic review on discovering new and reliable biomarkers for HCC. We also identified a list of high frequency prognostic genes and emphasized a critical role of AGXT deletion during HCC progression.

Identification of novel blood-based HCC-specific diagnostic biomarkers for human hepatocellular carcinoma

INTRODUCTION

Hepatocellular carcinoma (HCC) ranks fourth in global cancer mortality, accounting for 8.2% of all cancer deaths. Early detection of HCC has a significant impact on clinical outcomes. The aim of this study was to identify blood-based biomarkers which are HCC-specific.

METHODS

Comprehensive gene expression raw data of purified RNA of peripheral blood mononuclear cells (PBMC) was downloaded from GEO and was then analyzed. Differentially expressed genes (DEGs) in HCC were screened and the method of weighted gene co-expression network analysis was applied to identify candidate blood-based biomarkers associated with HCC.

RESULTS

Three modules closely related to HCC were screened using WGCNA. Nuclear localization signal (NLS)-bearing protein import into nucleus biological process was the most significant enriched physiological process identified by MCODE, and 3 genes (DICER1, GMPS and NCOR1) were selected as biomarkers.

CONCLUSION

In our study, three novel blood-based HCC-specific diagnostic biomarkers for human hepatocellular carcinoma were identified. These findings may contribute to the non-invasive detection of early HCC patients.

Genome-wide CRISPR knockout screens identify NCAPG as an essential oncogene for hepatocellular carcinoma tumor growth

Hepatocellular carcinoma (HCC) is a common and deadly cancer with limited treatment options. Through genome-wide growth depletion screens using clustered regularly interspaced short palindromic repeats and expression profiling of primary HCC tumors, we identified 13 clinically relevant target genes with therapeutic potential. Subsequent functional annotation analysis revealed significant enrichment of these 13 genes in the cell cycle, cell death, and survival pathways. Non-structural maintenance of chromosomes condensin I complex subunit G (NCAPG) was ranked the highest among the depletion screens and multiple HCC expression datasets. Transient inhibition of NCAPG using specific small interfering RNAs resulted in a significant reduction in cell growth, migration, and the down-regulation of mitochondrial gene expression in vitro. Small homologous RNA-mediated knockdown of NCAPG significantly impaired cell viability, caused aberrant mitotic division, fragmented the mitochondrial network, and increased cell death in vitro. HCC cells with a reduced expression of NCAPG formed significantly smaller xenograft tumors in vivo. Importantly, high NCAPG expression was significantly associated with poorer overall and disease-free survival in HCC patients. High NCAPG expression is a novel prognostic biomarker to predict HCC early recurrence after surgical resection. In conclusion, NCAPG is an essential gene for HCC tumor cell survival. It represents a promising novel target for treating HCC and a prognostic biomarker for clinical management of HCC.-Wang, Y., Gao, B., Tan, P. Y., Handoko, Y. A., Sekar, K., Deivasigamani, A., Seshachalam, V. P., OuYang, H.-Y., Shi, M., Xie, C., Goh, B. K. P., Ooi, L. L., Hui, K. M. Genome-wide CRISPR knockout screens identify NCAPG as an essential oncogene for hepatocellular carcinoma tumor growth.

Novel significant stage-specific differentially expressed genes in hepatocellular carcinoma

BACKGROUND

Liver cancer is among top deadly cancers worldwide with a very poor prognosis, and the liver is a vulnerable site for metastases of other cancers. Early diagnosis is crucial for treatment of the predominant liver cancers, namely hepatocellular carcinoma (HCC). Here we developed a novel computational framework for the stage-specific analysis of HCC.

METHODS

Using publicly available clinical and RNA-Seq data of cancer samples and controls and the AJCC staging system, we performed a linear modelling analysis of gene expression across all stages and found significant genome-wide changes in the log fold-change of gene expression in cancer samples relative to control. To identify genes that were stage-specific controlling for confounding differential expression in other stages, we developed a set of six pairwise contrasts between the stages and enforced a p-value threshold (< 0.05) for each such contrast. Genes were specific for a stage if they passed all the significance filters for that stage. The monotonicity of gene expression with cancer progression was analyzed with a linear model using the cancer stage as a numeric variable.

RESULTS

Our analysis yielded two stage-I specific genes (CA9, WNT7B), two stage-II specific genes (APOBEC3B, FAM186A), ten stage-III specific genes including DLG5, PARI, NCAPG2, GNMT and XRCC2, and 35 stage-IV specific genes including GABRD, PGAM2, PECAM1 and CXCR2P1. Overexpression of DLG5 was found to be tumor-promoting contrary to the cancer literature on this gene. Further, GABRD was found to be signifincantly monotonically upregulated across stages. Our work has revealed 1977 genes with significant monotonic patterns of expression across cancer stages. NDUFA4L2, CRHBP and PIGU were top genes with monotonic changes of expression across cancer stages that could represent promising targets for therapy. Comparison with gene signatures from the BCLC staging system identified two genes, HSP90AB1 and ARHGAP42. Gene set enrichment analysis indicated overrepresented pathways specific to each stage, notably viral infection pathways in HCC initiation.

CONCLUSIONS

Our study identified novel significant stage-specific differentially expressed genes which could enhance our understanding of the molecular determinants of hepatocellular carcinoma progression. Our findings could serve as biomarkers that potentially underpin diagnosis as well as pinpoint therapeutic targets.

[Identification of differentially expressed genes in peripheral blood mononuclear cells of patients with hepatocellular carcinoma and its regulatory network analysis]

OBJECTIVE

To identify the differentially expressed genes (DEGs) in peripheral blood mononuclear cells (PBMC) of patients with hepatocellular carcinoma (HCC) and to analyze their regulatory network.

METHODS

The DEGs in PBMCs of HCC patients were screened based on GEO database. The functional enrichment analysis and interaction analysis were carried out for DEGs. MCODE algorithm was used to screen core genes of DEGs, and the mirDIP and starBase online tools were used to predict upstream miRNAs and lncRNAs of the core genes.

RESULTS

A total of 265 DEGs with a high credibility were identified, which were mainly enriched in the biological activity, such as regulation of cell proliferation, metabolic regulation, cell communication and signaling, and inflammatory diseases according to Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway, and the two analyses were correlated. Four diagnostic candidate genes were identified, including FUS RNA binding protein, C-X-C motif chemokine ligand 8, cullin 1 and RNA polymerase Ⅱ subunit H. Subsequently, 10 miRNAs, 1 lncRNAs and 38 circRNAs were predicted, and finally a lncRNA/circRNA-miRNA-mRNA-pathway regulatory networks was constructed.

CONCLUSIONS

The diagnostic candidate genes and its regulatory network in HCC PBMC have been identified based on data mining, which could provide potential tumor biomarkers for early diagnosis and treatment of HCC.

NUF2 is a valuable prognostic biomarker to predict early recurrence of hepatocellular carcinoma after surgical resection

Early tumor recurrence after curative surgical resection poses a great challenge to the clinical management of hepatocellular carcinoma (HCC). We conducted whole genome expression microarrays on 64 primary HCC tumors with clinically defined recurrence status and cross-referenced with RNA-seq data from 18 HCC tumors in the Cancer Genome Atlas project. We identified a 77-gene signature, which is significantly associated with early recurrent (ER) HCC tumors. This ER-associated signature shows significant enrichment in genes involved in cell cycle pathway. We performed receiver operating characteristic (ROC) analysis to evaluate the prognostic biomarker potential of these 77 genes and Pearson correlation analysis to identify 11 close clusters. The one gene with the best area under the ROC curve in each of the 11 clusters was selected for validation using reverse-transcription quantitative PCR in an independent cohort of 24 HCC tumors. NUF2 was identified to be the minimal biomarker sufficient to discriminate ER tumors from LR tumors. NUF2 in combination with liver cirrhosis could significantly improve the detection of ER tumors with an AUROC of 0.82 and 0.85 in the test and validation cohort, respectively. In conclusion, NUF2 in combination with liver cirrhosis is a promising prognostic biomarker for early HCC recurrence.

Assessing The Predictive Value Of Regulatory Molecules For Patient Outcome In Pancreatic Cancer: A Computational Approach

Pancreatic Cancer (PC) can be characterized as one of the most lethal cancers considering its poor diagnosis and symptoms in early stages. To assess the predictive value of regulatory molecules in terms of differentially expressed genes, we first performed a thorough search of gene expression profiling studies in pancreatic cohorts. We obtained the genes that have been identified and validated experimentally to be associated with patient outcome and also differentially expressed in tumors compared with adjacent non-tumor tissues. A two-step upstream analysis on the derived set of the genes under study was performed. The subsequent promoter and pathway analysis unveiled candidate transcription factors and regulatory molecules that potentially have regulated the detected differentially expressed genes. Predictive analysis was applied in the identified regulators and classification algorithms were implemented to model accurately patient outcome. In view of our findings, Gaussian Naïve Bayes model exhibited the highest classification accuracy and f-score concerning the predictive value of regulatory molecules in PC (accuracy =0.85, f-score =0.84).

Loci-specific differences in blood DNA methylation in HBV-negative populations at risk for hepatocellular carcinoma development

Late onset of clinical symptoms in hepatocellular carcinoma (HCC) results in late diagnosis and poor disease outcome. Approximately 85% of individuals with HCC have underlying liver cirrhosis. However, not all cirrhotic patients develop cancer. Reliable tools that would distinguish cirrhotic patients who will develop cancer from those who will not are urgently needed. We used the Illumina HumanMethylation450 BeadChip microarray to test whether white blood cell DNA, an easily accessible source of DNA, exhibits site-specific changes in DNA methylation in blood of diagnosed HCC patients (post-diagnostic, 24 cases, 24 controls) and in prospectively collected blood specimens of HCC patients who were cancer-free at blood collection (pre-diagnostic, 21 cases, 21 controls). Out of 22 differentially methylated loci selected for validation by pyrosequencing, 19 loci with neighbouring CpG sites (probes) were confirmed in the pre-diagnostic study group and subjected to verification in a prospective cirrhotic cohort (13 cases, 23 controls). We established for the first time 9 probes that could distinguish HBV-negative cirrhotic patients who subsequently developed HCC from those who stayed cancer-free. These probes were identified within regulatory regions of BARD1, MAGEB3, BRUNOL5, FXYD6, TET1, TSPAN5, DPPA5, KIAA1210, and LSP1. Methylation levels within DPPA5, KIAA1210, and LSP1 were higher in prospective samples from HCC cases vs. cirrhotic controls. The remaining probes were hypomethylated in cases compared with controls. Using blood as a minimally invasive material and pyrosequencing as a straightforward quantitative method, the established probes have potential to be developed into a routine clinical test after validation in larger cohorts.

Review and Meta-Analyses of TAAR1 Expression in the Immune System and Cancers

Since its discovery in 2001, the major focus of TAAR1 research has been on its role in monoaminergic regulation, drug-induced reward and psychiatric conditions. More recently, TAAR1 expression and functionality in immune system regulation and immune cell activation has become a topic of emerging interest. Here, we review the immunologically-relevant TAAR1 literature and incorporate open-source expression and cancer survival data meta-analyses. We provide strong evidence for TAAR1 expression in the immune system and cancers revealed through NCBI GEO datamining and discuss its regulation in a spectrum of immune cell types as well as in numerous cancers. We discuss connections and logical directions for further study of TAAR1 in immunological function, and its potential role as a mediator or modulator of immune dysregulation, immunological effects of psychostimulant drugs of abuse, and cancer progression.

Analysis of expression profile data identifies key genes and pathways in hepatocellular carcinoma

The aims of the present study were to identify key genes and pathways associated with hepatocellular carcinoma (HCC) progression and predict compounds potentially associated with this type of carcinogenesis. The gene expression profile data of the GSE49515 dataset was obtained from the Gene Expression Omnibus database. The limma software package was used to identify the differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed using the Biological Networks Gene Ontology tool and the Database for Annotation, Visualization and Integrated Discovery, respectively. The Michigan Molecular Interactions database plugin within the Cytoscape software platform was used to perform protein-protein interaction (PPI) network analysis. Chemical-gene interaction data for HCC were obtained from the Comparative Toxicogenomics Database to evaluate the associations between drugs and specific genes. A total of 302 DEGs, including 231 downregulated and 71 upregulated, were identified. Cytokine-cytokine receptor interaction and chemokine signaling were the significantly enriched pathways. Additionally, PPI network analysis indicated a total of 13 highest degree hub nodes, including FBJ murine osteosarcoma viral oncogene homolog (FOS) and DNA damage-inducible transcript 3 protein (DDIT3). Chemical-gene interaction analysis revealed that FUN and FOS were targeted by >500 compounds, while >200 genes were targeted by 2,3,7,8-tetrachlorodibenzodioxin and benzo(α)pyrene. In conclusion, the present study demonstrated that FOS, DDIT3, the cytokine-cytokine receptor interaction pathway and the chemokine signaling pathway may be key genes and pathways associated with the development of HCC. Furthermore, exposure to 2,3,7,8-tetrachlorodibenzodioxin or benzo(α)pyrene may lead to hepatocarcinogenesis.

Transcriptome analysis of peripheral blood mononuclear cells from chronic hepatitis B and hepatocellular carcinoma patients: a network-based attitude

Aim: The aim of the study was constructing a protein–protein interaction network for chronic hepatitis B (CHB) and hepatocellular carcinoma (HCC) patients. Materials & methods: Comprehensive gene expression profile of peripheral blood mononuclear cells of CHB and HCC were obtained from Gene Expression Omnibus/NCBI database. Differentially expressed genes (DEGs) of samples were analyzed using GEO2R web application. Results: The majority of DEGs in both CHB and HCC has been enriched in immune system responses. However, there was a significant disparity between the enrichment of these genes (especially genes associated with Toll-like receptor-and-TNF) in CHB-HCC compared with normal-CHB. Conclusion: The transcriptome properties of peripheral blood mononuclear cells are changed in patients with HBV-HCC. The immune response genes are the most deregulated genes in HCC patients.

[Formula: see text]

Gene Expression Profiling of Peripheral Blood From Kidney Transplant Recipients for the Early Detection of Digestive System Cancer

BACKGROUND

Kidney transplant recipients are at increased risk of developing cancer in comparison with the general population. To effectively manage post-transplantation malignancies, it is essential to proactively monitor patients. A long-term intensive screening program was associated with a reduced incidence of cancer after transplantation. This study evaluated the usefulness of the gene expression profiling of peripheral blood samples obtained from kidney transplant patients and adopted a screening test for detecting cancer of the digestive system (gastric, colon, pancreas, and biliary tract).

STUDY DESIGN AND METHOD

Nineteen patients were included in this study and a total of 53 gene expression screening tests were performed. The gene expression profiles of blood-delivered total RNA and whole genome human gene expression profiles were obtained. We investigated the expression levels of 2665 genes associated with digestive cancers and counted the number of genes in which expression was altered. A hierarchical clustering analysis was also performed. The final prediction of the cancer possibility was determined according to an algorithm.

RESULTS

The number of genes in which expression was altered was significantly increased in the kidney transplant recipients in comparison with the general population (1091 ± 63 vs 823 ± 94; P = .0024). The number of genes with altered expression decreased after the induction of mechanistic target of rapamycin (mTOR) inhibitor (1484 ± 227 vs 883 ± 154; P = .0439). No cases of possible digestive cancer were detected in this study period.

CONCLUSION

The gene expression profiling of peripheral blood samples may be a useful and noninvasive diagnostic tool that allows for the early detection of cancer of the digestive system.

Biomarkers in hepatocellular carcinoma: an overview

Current methods for HCC diagnosis have not an optimal diagnostic accuracy. The detection of more than one biomarker seems to improve their individual performance and provide an accurate HCC diagnosis approach. Individual gene expression seems to influence whether or not the treatment is successful, since several molecules have interfere with cancer associated pathways and have been related to poor prognosis which condition the lack of effective treatment options. Areas covered: Novel biomarkers have been proposed as a useful tool in each patient prognosis. This article aims to review the recent evidence based on HCC biomarkers which seems to have a regulative role according to tumor cell development leading to a specific biological response. Epigenetic regulation, miRNAs, and genome sequencing analysis propose molecular expression signatures as novel biomarkers which allowed achieve the major goal for the use of biomarkers in clinical practice. Moreover, a deeper analysis for determine the diagnostic accuracy of biomarkers has been made. Expert commentary: To improve of methodological designs and sample sizes are needed in order to support the role of biomarkers in HCC. Furthermore, is necessary to consider HCC etiologies and all clinic disease context to carried out clinical phase studies to thrust biomarkers application.

Biomarkers for Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the third leading cause of cancer deaths worldwide. The HCC diagnosis is usually achieved by biomarkers, which can also help in prognosis prediction. Furthermore, it might represent certain therapeutic interventions through some combinations of biomarkers. Here, we review on our current understanding of HCC biomarkers.

Time for paradigm change in management of hepatocellular carcinoma: is a personalized approach on the horizon?

Hepatocellular carcinoma (HCC) is the fifth most frequent cancer form but the second leading cause of all cancer-related deaths. There are several reasons for high mortality in the HCC cohort: lack of effective screening programs and consequently late diagnosis, multifactorial origin with cumulative risk factors, complex carcinogenesis, tumor heterogeneity, unpredictable impacts of individual microenvironment on tumor development and progression, and, as the consequence, frequently untargeted therapy and cancer resistance toward currently applied treatment approaches. The currently applied 'treat and wait' approach is inappropriate in the overall HCC management. Urgent need in paradigm change toward predictive, preventive and personalized medicine is discussed in this review article. Innovative strategies for an advanced predictive, preventive and personalized medicine approach in the overall HCC management benefiting the patient are presented.

Biomarkers of Resilience in Stress Reduction for Caregivers of Alzheimer's Patients

Caregiving for a dementia patient is associated with increased risk of psychological and physical health problems. We investigated whether a mindfulness-based stress reduction (MBSR) training course for caregivers that closely models the MBSR curriculum originally established by the Center of Mindfulness at the University of Massachusetts may improve the psychological resilience of non-professional caregivers of Alzheimer's disease patients. Twenty adult non-professional caregivers of dementia patients participated in an 8-week MBSR training course. Caregiver stress, depression, burden, grief, and gene expression profiles of blood mononuclear cells were assessed at baseline and following MBSR. MBSR training significantly improved the psychological resilience of some of the caregivers. We identified predictive biomarkers whose expression is associated with the likelihood of caregivers to benefit from MBSR, and biomarkers whose expression is associated with MBSR psychological benefits. Our biomarker studies provide insight into the mechanisms of health benefits of MBSR and a basis for developing a personalized medicine approach for applying MBSR for promoting psychological and cognitive resilience in caregivers of dementia patients.

Diagnostic and therapeutic management of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is an increasing health problem, representing the second cause of cancer-related mortality worldwide. The major risk factor for HCC is cirrhosis. In developing countries, viral hepatitis represent the major risk factor, whereas in developed countries, the epidemic of obesity, diabetes and nonalcoholic steatohepatitis contribute to the observed increase in HCC incidence. Cirrhotic patients are recommended to undergo HCC surveillance by abdominal ultrasounds at 6-mo intervals. The current diagnostic algorithms for HCC rely on typical radiological hallmarks in dynamic contrast-enhanced imaging, while the use of α-fetoprotein as an independent tool for HCC surveillance is not recommended by current guidelines due to its low sensitivity and specificity. Early diagnosis is crucial for curative treatments. Surgical resection, radiofrequency ablation and liver transplantation are considered the cornerstones of curative therapy, while for patients with more advanced HCC recommended options include sorafenib and trans-arterial chemo-embolization. A multidisciplinary team, consisting of hepatologists, surgeons, radiologists, oncologists and pathologists, is fundamental for a correct management. In this paper, we review the diagnostic and therapeutic management of HCC, with a focus on the most recent evidences and recommendations from guidelines.

T Cell Transcriptomes Describe Patient Subtypes in Systemic Lupus Erythematosus

Background

T cells regulate the adaptive immune response and have altered function in autoimmunity. Systemic Lupus Erythematosus (SLE) has great diversity of presentation and treatment response. Peripheral blood component gene expression affords an efficient platform to investigate SLE immune dysfunction and help guide diagnostic biomarker development for patient stratification.

Methods

Gene expression in peripheral blood T cell samples for 14 SLE patients and 4 controls was analyzed by high depth sequencing. Unbiased clustering of genes and samples revealed novel patterns related to disease etiology. Functional annotation of these genes highlights pathways and protein domains involved in SLE manifestation.

Results

We found transcripts for hundreds of genes consistently altered in SLE T cell samples, for which DAVID analysis highlights induction of pathways related to mitochondria, nucleotide metabolism and DNA replication. Fewer genes had reduced mRNA expression, and these were linked to signaling, splicing and transcriptional activity. Gene signatures associated with the presence of dsDNA antibodies, low complement levels and nephritis were detected. T cell gene expression also indicates the presence of several patient subtypes, such as having only a minimal expression phenotype, male type, or severe with or without induction of genes related to membrane protein production.

Conclusions

Unbiased transcriptome analysis of a peripheral blood component provides insight on autoimmune pathophysiology and patient variability. We present an open source workflow and richly annotated dataset to support investigation of T cell biology, develop biomarkers for patient stratification and perhaps help indicate a source of SLE immune dysfunction.