A prognostic prediction system for hepatocellular carcinoma based on gene co-expression network

Predictive Roles of ADAM17 in Patient Survival and Immune Cell Infiltration in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is the deadliest malignant tumour worldwide. The metalloproteinase ADAM17 is associated with tumour formation and development; however, its significance in HCC is unclear. This study aimed to investigate the role of ADAM17 in HCC and the correlation between its expression and immune cell infiltration. ADAM17 expression was analysed in pan-cancer and HCC tissues using The Cancer Genome Atlas and Genotype-Tissue Expression datasets. Kaplan-Meier survival analysis displayed a negative association between ADAM17 expression and the overall survival of patients with HCC. High ADAM17 expression was linked to poor tumour/node (T/N) stage and alpha fetoprotein (AFP) levels. Gene Set Enrichment Analysis, Gene Ontology, and Kyoto Encyclopaedia of Genes and Genomes analyses revealed the enrichment of several pathways, including epithelial-mesenchymal transition, inflammatory response, Hedgehog, and KRAS signalling, in patients with upregulated ADAM17. ADAM17 was shown to be positively correlated with immune cell infiltration and immune checkpoint expression via the Tumour Immune Estimation Resource (TIMER) database and immunohistochemistry analyses. Protein-protein interaction (PPI) network analysis revealed that ADAM17 plays a core role in cancer development and immune evasion. In vitro and in vivo experiments demonstrated that ADAM17 influences HCC growth and metastasis. In conclusion, ADAM17 is upregulated in most cancers, particularly HCC, and is critical in the development and immune evasion of HCC.

Deep View of HCC Gene Expression Signatures and Their Comparison with Other Cancers

BACKGROUND

Gene expression signatures correlate genetic alterations with specific clinical features, providing the potential for clinical usage. A plethora of HCC-dependent gene signatures have been developed in the last two decades. However, none of them has made its way into clinical practice. Thus, we investigated the specificity of public gene signatures to HCC by establishing a comparative transcriptomic analysis, as this may be essential for clinical applications.

METHODS

We collected 10 public HCC gene signatures and evaluated them by utilizing four different (commercial and non-commercial) gene expression profile comparison tools: Oncomine Premium, SigCom LINCS, ProfileChaser (modified version), and GENEVA, which can assign similar pre-analyzed profiles of patients with tumors or cancer cell lines to our gene signatures of interests. Among the query results of each tool, different cancer entities were screened. In addition, seven breast and colorectal cancer gene signatures were included in order to further challenge tumor specificity of gene expression signatures.

RESULTS

Although the specificity of the evaluated HCC gene signatures varied considerably, none of the gene signatures showed strict specificity to HCC. All gene signatures exhibited potential significant specificity to other cancers, particularly for colorectal and breast cancer. Since signature specificity proved challenging, we furthermore investigated common core genes and overlapping enriched pathways among all gene signatures, which, however, showed no or only very little overlap, respectively.

CONCLUSION

Our study demonstrates that specificity, independent validation, and clinical use of HCC genetic signatures solely relying on gene expression remains challenging. Furthermore, our work made clear that standards in signature generation and statistical methods but potentially also in tissue preparation are urgently needed.

A Seven-Gene Signature to Predict Prognosis of Patients With Hepatocellular Carcinoma

Purpose: Hepatocellular carcinoma (HCC) is one of the most prevalent malignant diseases worldwide and has a poor prognosis. Gene-based prognostic models have been reported to predict the overall survival of patients with HCC. Unfortunately, most of the genes used in earlier prognostic models lack prospective validation and, thus, cannot be used in clinical practice.

Methods: Candidate genes were selected from GEPIA (Gene Expression Profiling Interactive Analysis), and their associations with patients’ survival were confirmed by RT-PCR using cDNA tissue microarrays established from patients with HCC after radical resection. A multivariate Cox proportion model was used to calculate the coefficient of corresponding gene. The expression of seven genes of interest (MKI67, AR, PLG, DNASE1L3, PTTG1, PPP1R1A, and TTR) with two reference genes was defined to calculate a risk score which determined groups of different risks.

Results: Our risk scoring efficiently classified patients (n = 129) with HCC into a low-, intermediate-, and high-risk group. The three groups showed meaningful distinction of 3-year overall survival rate, i.e., 88.9, 74.5, and 20.6% for the low-, intermediate-, and high-risk group, respectively. The prognostic prediction model of risk scores was subsequently verified using an independent prospective cohort (n = 77) and showed high accuracy.

Conclusion: Our seven-gene signature model performed excellent long-term prediction power and provided crucially guiding therapy for patients who are not a candidate for surgery.

High Expression of SLC41A3 Correlates with Poor Prognosis in Hepatocellular Carcinoma

Purpose

SLC41A3 is a member of the solute carrier family 41 (SLC41) and is involved in many cellular processes as a magnesium ion transporter. Although it plays an important role in cancer formation and development, the correlation between the expression of SLC41A3 and the occurrence and prognosis of hepatocellular carcinoma (HCC) remains unclear. Therefore, this study was focused on the evaluation of the relationship between SLC41A3 and the development and prognosis of HCC.

Patients and Methods

Firstly, we collected the mRNA expression of SLC41A3 in HCC through the platform of Oncomine. Then, the subgroups of HCC were performed by the UALCAN website and the prognosis of HCC was analyzed by Kaplan-Meier Plotter database. Subsequently, immunohistochemistry (IHC) method was used to detect SLC41A3 expression in 323 clinically confirmed HCC samples and 184 non-cancerous liver tissues. Finally, function enrichment analysis was done using the LinkInterpreter module in LinkedOmics, and gene set enrichment analysis (GSEA) was performed using TCGA data set.

Results

The Oncomine database and immunohistochemical (IHC) showed higher SLC41A3 expression in HCC tissue compared to normal tissue. The expression of SLC41A3 was significantly correlated with tumor metastasis, Edmondson grade, microvascular invasion, and AFP level. Kaplan-Meier and Cox regression analyses verified that high SLC41A3 expression is a significant prognostic factor for reduced overall survival in HCC patients.

Conclusion

Our results demonstrated that high expression of SLC41A3 was the predictor of poor prognosis in HCC patients, suggesting that this protein may be a potential target for HCC therapy.

Expression of cell divisioncycle-associated genes and their prognostic significance in hepatocellular carcinoma

The cell division cycle-associated (CDCA) protein family plays an essential role in tumor progression by cell division. However, the function of each CDCA family member in hepatocellular carcinoma (HCC) is not well known. This study is to find the roles of CDCAs in the prognosis of HCC patients by using ONCOMINE, UALCAN, Human Protein Atlas, Kaplan-Meier Plotter, and cBioPortal databases. Overexpression of CDCA mRNA and protein were found to be significantly associated with individual cancer stages and tumor grades in HCC patients. Higher mRNA expressions of 6 CDCA family members were found to be significantly associated with shorter overall survival (OS) in HCC patients. Multivariate analysis showed that overexpressions of CDCA mRNA were independent prognostic factors for shorter OS in HCC patients. Moreover, a high mutation rate of CDCAs (27%) was also detected in HCC patients, and genetic alteration in CDCAs was associated with shorter overall survival (OS) and disease-free survival (DFS) in HCC patients. Finally, a functional analysis showed that CDCAs were mainly enriched in the cell cycle (hsa04110) and oocyte meiosis. Overall, these results indicated that CDCA2/3/4/5/8 could be prognostic biomarkers of survival in HCC patients.

Integrative Analysis of Metallothioneins Identifies MT1H as Candidate Prognostic Biomarker in Hepatocellular Carcinoma

Background: Metallothioneins (MTs) play crucial roles in the modulation of zinc/copper homeostasis, regulation of neoplastic growth and proliferation, and protection against apoptosis. The present study attempted to visualize the prognostic landscape of MT functional isoforms and identify potential prognostic biomarkers in hepatocellular carcinoma (HCC). Methods: The transcriptional expression, comprehensive prognostic performances, and gene-gene interaction network of MT isoforms in HCC were evaluated via Oncomine, GEPIA, Kaplan-Meier plotter, and GeneMANIA databases. Characterized by good prognostic value in three external cohorts, MT1H was specifically selected as a potential prognostic biomarker in HCC with various clinicopathological features. Functional and pathway enrichment analyses of MT1H status were performed using cBioPortal, the Database for Annotation, Visualization, and Integrated Discovery (DAVID), and ssGSVA method. Results: MT1E/1F/1G/1H/1M/1X/2A was greatly downregulated in HCC. Prognostic analyses elucidated the essential correlations between MT1A/1B/1H/1X/2A/4 attenuation and poor overall survival, between MT1B/1H/4 downregulation and worse relapse-free survival, and between MT1A/1B/1E/1H/1M/2A/4 downregulation and diminished progression-free survival in HCC. Taken together, these results indicated the powerful prognostic value of MT1H among MTs in HCC. In-depth analyses suggested that MT1H may be more applicable to alcohol-derived HCC and involved in the downregulation of the inflammatory pathway, Jak-STAT pathway, TNF pathway, and Wnt signaling pathway. Conclusion: MT-specific isoforms displayed aberrant expression and varying prognostic value in HCC. MT1H repression in HCC was multi-dimensionally detrimental to patient outcomes. Therefore, MT1H was possibly associated with carcinogenesis and exploited as a novel prognostic biomarker and candidate therapeutic target for HCC.

The diagnostic and prognostic value of cell division cycle associated gene family in Hepatocellular Carcinoma

Cell division cycle associated (CDCA) gene family plays an important role in cells. However, some researchers revealed that overexpression of CDCAs might contribute to the tumor progression in several cancers. Here, we analyzed the role of this gene family in hepatocellular carcinoma (HCC). We used several web tools and found that most of CDCAs were highly expressed in tumor tissues compared to the paracancer tissues in HCC. We then used RT-qPCR to confirm our results. The results showed that CDCA2, CDCA3, CDCA5 and CDCA8 were up-regulated in HCC. We also found that these genes were associated with poor overall survival and relapse free survival except CDCA7. The functional analysis showed that this gene family might take part in many processes, including cell division, apoptosis, DNA damage and DNA repair, which might contribute to the tumor progression. The KEGG pathway analysis showed that these genes participated in several important pathways such as PI3K-Akt signaling pathway and hippo signaling pathway. In conclusion, our findings suggested that CDCA2, CDCA3, CDCA4, CDCA5, and CDCA8 might have potential diagnostic and prognostic values for hepatocellular carcinoma.

Histone-fold centromere protein W (CENP-W) is associated with the biological behavior of hepatocellular carcinoma cells

Centromere protein W (CENP-W), identified as a centromeric component, plays an important role in the cell life cycle. However, how CENPW expression affects biological processes in liver cancer cells remains unknown. In this article, we found that CENPW was overexpressed in liver cancer tissues. Low CENPW expression was correlated with a better prognosis in hepatocellular carcinoma (HCC) patients, compared to high CENPW expression. The results of qRT-PCR and western blot assay showed that CENPW was effectively knocked down in HCC cells using siRNA transfection. Cell proliferation, migration, and invasion were inhibited. Cell apoptosis rates were increased. The cells were arrested in the G2/M phase of the cell cycle. Subsequently, 127 differentially expressed genes (DEGs) were identified based on RNA-seq data. GO and KEGG enrichment and PPI network analysis were performed. The novel DEGs were found and mainly enriched in nucleosome assembly and the complement system. In summary, our study indicated that overexpression of CENPW implied unfavorable prognosis and CENPW might be the potential predictive biomarker in liver cancer. Downregulation of CENPW might inhibit the HCC developmentby regulating the expression of the molecules in nucleosomes and the complement system.

Analysis of the Expression of Cell Division Cycle-Associated Genes and Its Prognostic Significance in Human Lung Carcinoma: A Review of the Literature Databases

Background

Lung cancer (LC) has become the top cause responsible for cancer-related deaths. Cell division cycle-associated (CDCA) genes exert an important role in the life process. Dysregulation in the process of cell division may lead to malignancy.

Methods

Transcriptional data on CDCA gene family and patient survival data were examined for lung cancer (LC) patients from the GEPIA, Oncomine, cBioPortal, and Kaplan-Meier Plotter databases.

Results

CDCA1/2/3/4/5/7/8 expression levels were higher in lung adenocarcinoma tissues, and the CDCA1/2/3/4/5/6/7/8 expression levels were increased in squamous cell LC tissues compared with those in noncarcinoma lung tissues. The expression levels of CDCA1/2/3/4/5/8 showed correlation with tumor classification. The Kaplan-Meier Plotter database was employed to carry out survival analysis, indicating that increased CDCA1/2/3/4/5/6/7/8 expression levels were increased in squamous cell LC tissues compared with those in noncarcinoma lung tissues. The expression levels of P < 0.05). Only LC patients with increased CDCA3/4/5/8 expression were significantly related to lower post-progression survival (PPS) (P < 0.05). Only LC patients with increased CDCA gene family and patient survival data were examined for lung cancer (LC) patients from the GEPIA, Oncomine, cBioPortal, and Kaplan-Meier Plotter databases. CDCA8, INCENP, AURKB, and BIRC5); CORUM: 127: NDC80 kinetochore complex; M129: the PID PLK1 pathway; and GO: 0007080: mitotic metaphase plate congression, all of which were remarkably modulated since the alterations affected CDCA gene family and patient survival data were examined for lung cancer (LC) patients from the GEPIA, Oncomine, cBioPortal, and Kaplan-Meier Plotter databases.

Conclusions

Upregulated CDCA genes' expression levels in LC tissues probably play a crucial part in LC oncogenesis. The upregulated CDCA genes' expression levels are used as the potential prognostic markers to improve patient survival and the LC prognostic accuracy. CDCA genes probably exert their functions in tumorigenesis through the PLK1 pathway.CDCA gene family and patient survival data were examined for lung cancer (LC) patients from the GEPIA, Oncomine, cBioPortal, and Kaplan-Meier Plotter databases. CDCA gene family and patient survival data were examined for lung cancer (LC) patients from the GEPIA, Oncomine, cBioPortal, and Kaplan-Meier Plotter databases. CDCA gene family and patient survival data were examined for lung cancer (LC) patients from the GEPIA, Oncomine, cBioPortal, and Kaplan-Meier Plotter databases.

Graph Theoretic and Pearson Correlation-Based Discovery of Network Biomarkers for Cancer

Two graph theoretic concepts—clique and bipartite graphs—are explored to identify the network biomarkers for cancer at the gene network level. The rationale is that a group of genes work together by forming a cluster or a clique-like structures to initiate a cancer. After initiation, the disease signal goes to the next group of genes related to the second stage of a cancer, which can be represented as a bipartite graph. In other words, bipartite graphs represent the cross-talk among the genes between two disease stages. To prove this hypothesis, gene expression values for three cancers— breast invasive carcinoma (BRCA), colorectal adenocarcinoma (COAD) and glioblastoma multiforme (GBM)—are used for analysis. First, a co-expression gene network is generated with highly correlated gene pairs with a Pearson correlation coefficient ≥ 0.9. Second, clique structures of all sizes are isolated from the co-expression network. Then combining these cliques, three different biomarker modules are developed—maximal clique-like modules, 2-clique-1-bipartite modules, and 3-clique-2-bipartite modules. The list of biomarker genes discovered from these network modules are validated as the essential genes for causing a cancer in terms of network properties and survival analysis. This list of biomarker genes will help biologists to design wet lab experiments for further elucidating the complex mechanism of cancer.