Up-regulation of CTD-2547G23.4 in hepatocellular carcinoma tissues and its prospective molecular regulatory mechanism: a novel qRT-PCR and bioinformatics analysis study

Targeting Adenylate Cyclase Family: New Concept of Targeted Cancer Therapy

The adenylate cyclase (ADCY) superfamily is a group of glycoproteins regulating intracellular signaling. ADCYs act as key regulators in the cyclic adenosine monophosphate (cAMP) signaling pathway and are related to cell sensitivity to chemotherapy and ionizing radiation. Many members of the superfamily are detectable in most chemoresistance cases despite the complexity and unknownness of the specific mechanism underlying the role of ADCYs in the proliferation and invasion of cancer cells. The overactivation of ADCY, as well as its upstream and downstream regulators, is implicated as a major potential target of novel anticancer therapies and markers of exceptional responders to chemotherapy. The present review focuses on the oncogenic functions of the ADCY family and emphasizes the possibility of the mediating roles of deleterious nonsynonymous single nucleotide polymorphisms (nsSNPs) in ADCY as a prognostic therapeutic target in modulating resistance to chemotherapy and immunotherapy. It assesses the mediating roles of ADCY and its counterparts as stress regulators in reprogramming cancer cell metabolism and the tumor microenvironment. Additionally, the well-evaluated inhibitors of ADCY-related signaling, which are under clinical investigation, are highlighted. A better understanding of ADCY-induced signaling and deleterious nsSNPs (p.E1003K and p.R1116C) in ADCY6 provides new opportunities for developing novel therapeutic strategies in personalized oncology and new approaches to enhance chemoimmunotherapy efficacy in treating various cancers.

N6-Methyladenosine-Related lncRNA Signature Predicts the Overall Survival of Colorectal Cancer Patients

BACKGROUND

The N6-methyladenosine (m6A) RNA modification can modify long non-coding RNAs (lncRNAs), thereby affecting the tumorigenesis and progression of tumors. However, the underlying role of m6A-modified lncRNAs in colorectal cancer (CRC) remains largely unknown. Therefore, our aim was to assess the prognostic value of m6A-modified lncRNAs in CRC patients.

METHODS

The gene expression and clinicopathological data of CRC were extracted from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was used to investigate the m6A-modified lncRNAs. Consensus clustering was conducted to identify molecular subtypes of CRC, and the clinical significance of molecular subtypes was identified. The least absolute shrinkage and selection operator analysis (LASSO) was applied to establish a risk signature. Finally, a prognostic nomogram with risk score and clinicopathological variables was established.

RESULTS

In total, 29 m6A-modified lncRNAs were identified as prognostic lncRNAs. Two molecular clusters were identified and significant differences were found with respect to clinicopathological features and prognosis. Cluster1 is associated with poor overall survival (OS), down-regulation of Programmed cell death ligand-1 (PD-L1) expression, lower immune score, and less immune cell infiltration. Then, an m6A-modified lncRNA signature for predicting OS was constructed in the TCGA training cohort. The signature demonstrated favorable prediction performance in both training and validation sets. Compared with low-risk patients, patients with high risk showed worse clinical outcomes, lower immune scores, and downregulated PD-L1 expression. Further analysis indicated that the signature was an independent prognostic indicator, and then a prognostic nomogram based on risk score, tumor location, and tumor stage was established.

CONCLUSIONS

Our study identified a seven m6A-modified lncRNA signature and established a prognostic nomogram that reliably predicts OS in CRC. These findings may improve the understanding of m6A modifications in CRC and provide insights into the prognosis and treatment strategy of CRC.

Identification of a Novel Metastasis-Related miRNAs-Based Signature for Predicting the Prognosis of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common internal malignancies worldwide and is associated with a poor prognosis. Abnormal expression of miRNAs is believed to play a role in the recurrent metastasis of HCC. However, limited studies on the role of miRNAs in HCC metastasis have been carried out. Therefore, this study is aimed at exploring the potential value of metastasis-related miRNAs (MRMs) in HCC. We retrieved MRMs were from the Human Cancer Metastasis Database. Differential miRNAs were identified for tumor samples of HCC patients and normal samples based on the TCGA database. Further, univariate and multivariate Cox regression analyses were used to screen MRMs known to be independent prognostic factors in HCC. These MRMs were then used to build a prognostic signature. All patients were classified into high-risk and low-risk groups based on the median of the signature scores. Moreover, GO and KEGG pathway enrichment analyses were performed to predict the function of these MRMs. Finally, a nomogram was constructed to predict the OS of patients at 1, 2, and 3 years. In our study, a total of seven prognostic MRMs (miR-140-3p, miR-9-5p, miR-942-5p, miR-324-3p, miR-29c-5p, miR-551a, and miR-149-5p) were identified and used for constructing the prognostic signature based on the training cohort. Patients in the low-risk HCC group showed better overall survival (OS) than those in the high-risk group. The results were validated using the validation cohort. In summary, the findings of this study provide evidence that MRMs-based prognostic signature is an independent biomarker in the prognosis of HCC patients.

Clinical significance of miR-1180-3p in hepatocellular carcinoma: a study based on bioinformatics analysis and RT-qPCR validation

miRNAs play an indispensable role in human carcinogenesis. Dysregulated miR-1180-3p has been observed in several types of cancer, including hepatocellular carcinoma (HCC). This study intends to correlate the expression level of miR-1180-3p with clinical features and overall survival in HCC patients. The expression and clinical significance of miR-1180-3p, selected from GEO and TCGA databases, were verified using an RT-qPCR method. The target genes of miR-1180-3p were obtained using 3 miRNA target gene prediction databases, and their functions were analyzed using the online tool WebGestalt. miR-1180-3p expression was significantly upregulated in 88 HCC tissues compared with non-tumor liver tissues (0.004 ± 0.009 vs. 0.002 ± 0.002, t = − 2.099, P = 0.038). Additionally, we found that the expression levels of miR-1180-3p were significantly correlated with tumor number (χ² = 9.157, P = 0.006) and MVI (χ² = 11.354, P = 0.003). Based on Kaplan–Meier analysis, patients with high miR-1180 expression had a shorter overall survival than those with low miR-1180-3p expression (P = 0.002). Furthermore, multivariate Cox analyses indicated that miR-1180-3p expression was an independent prognostic factor for overall survival (HR = 13.36, 95% CI 1.16, 153.69, P = 0.038). In addition, a total of 733 target genes of miR-1180-3p were found from three prediction databases. The GO analyses demonstrated that the target genes were closely related to the proliferation and malignancy of tumors. The KEGG analysis showed that target genes were enriched in several key cancer-related signaling pathways, including the Pathways in cancer, the Ras signaling pathway, and the MAPK signaling pathway. In conclusion, we demonstrate that miR-1180-3p is upregulated in HCC and is associated with a poor prognosis. Thus, miR-1180-3p might be useful as a prognostic marker for HCC.

Overexpression of MiR-452-5p in hepatocellular carcinoma tissues and its prospective signaling pathways

BACKGROUND

The implication of miR-452-5p and its prospective machinery in hepatocellular carcinoma (HCC) remains largely unknown. For this reason, this study aimed to inspect the clinical implication of miR-452-5p expression in HCC tissues with multiple detection approaches, to analyze its potential function via in silico methods, and to validate this using a dual-luciferase reporter assay.

METHODS

The assessment of the expression level of miR-452-5p in HCC was conducted via four methods: 1) in-house real-time quantitative PCR (RT-qPCR), 2) miRNA-sequencing (miRNA-seq) from The Cancer Genome Atlas (TCGA), 3) miRNA microarrays from the Gene Expression Omnibus (GEO), and 4) comprehensive meta-analyses calculating the standard mean difference (SMD) and summary of receiver operator characteristic (sROC). Following the target prediction, one of the potential targets of miR-452-5p was validated through a dual-luciferase reporter assay.

RESULTS

MiR-452-5p was consistently elevated in HCC tissues via various detection methods, including in-house RT-qPCR, miRNA-seq, and miRNA microarrays. The final SMD was 0.842 for 820 cases of HCC samples. Simultaneously, the area under curve (AUC) of the sROC was 0.80 (0.76-0.83). The 1,135 predicted targets of miR-452-5p were enriched in the pathways of cytokine-cytokine receptor interaction, carbon metabolism, and complement and coagulation cascades. Among these predicted targets, CDKN1B was verified to be a real target of miR-452-5p.

CONCLUSION

The overexpression of miR-452-5p may play a pivotal role in the carcinogenesis of HCC via targeting multiple signaling pathways and genes. The function and molecular machinery of miR-452-5p in HCC requires further in-depth exploration.

Epigenetic identification of ADCY4 as a biomarker for breast cancer: an integrated analysis of adenylate cyclases

Aim: To explore the role of adenylyl cyclase isoforms and its epigenetics in cancer. Materials & methods: Adenylyl cyclase expression profiles, epigenetic alterations, prognostic value and molecular networks were assessed by use of public omics datasets. Results: ADCY4 was significantly downregulated in breast cancer. This downregulation was associated with promoter hypermethylation. High ADCY4 expression was correlated with better survival of patients with breast cancer and its different intrinsic subtypes and tumor stages. ADCY4 was shown to be strongly associated with G protein coupled receptors and the downstream cAMP signaling pathway, which was also significantly enriched in newly identified lysophosphatidic acid receptor 4 and glucagon-like peptide-1. Conclusion: ADCY4 may be used as an epigenetic biomarker for breast cancer, as well as a possible target for therapy.

SUCO as a Promising Diagnostic Biomarker of Hepatocellular Carcinoma: Integrated Analysis and Experimental Validation

Background

Hepatocellular carcinoma (HCC) is not frequently diagnosed until the late stage due to its concealed symptoms. Therefore, the identification of biomarkers that have effective diagnostic performance and act as potential key therapeutic targets for HCC becomes urgent.

Material/Methods

Comprehensive analysis of accumulated data downloaded from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) databases was used to obtain more reliable potential diagnostic biomarkers of HCC and to explore related molecular mechanisms. Meta-analysis and summary receiver operating characteristic (SROC) curve analysis were performed to evaluate the differential expression of SUCO gene in HCC and identify the capability of SUCO in distinguishing HCC-tissues from normal liver-tissues.

Results

SUCO was found to be upregulated in HCC-tissues and exhibited a favorable value in diagnosing HCC. Bioinformatics analysis showed that SUCO might play important roles in HCC progression, and was significantly related to cell cycle, cell metabolism, and proliferation.

Conclusions

This study was the first to demonstrate that SUCO was overexpressed in HCC-tissues, and that high expression of SUCO was significantly related to poor overall survival in HCC patients. SUCO might be a potential diagnostic biomarker for HCC patients, which promotes the tumorigenesis and progression of HCC.

Pseudogene DUXAP10 acts as a diagnostic and prognostic marker and promotes cell proliferation by activating PI3K/AKT pathway in hepatocellular carcinoma

Background: Recently, the pseudogene DUXAP10 was shown to be overexpressed in various human cancers and emerged as a key cancer regulator. However, the roles of DUXAP10 in hepatocellular carcinoma (HCC) tumorigenesis and progression remain uncharacterized. Methods: Comprehensive analyses were performed to investigate DUXAP10 expression patterns, potential biologic functions, and clinical significance in HCC based on the data downloaded from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. DUXAP10 expression levels in HCC tissue sections and cells were verified using quantitative real-time PCR analysis. DUXAP10-siRNA was used to silence DUXAP10 in the Hep3B cell line to determine the roles of DUXAP10 in HCC cell proliferation. Results: DUXAP10 was significantly overexpressed in HCC, and DUXAP10 upregulation was closely associated with poor prognoses in HCC patients. DUXAP10 knockdown decreased cell proliferation and arrested HCC cells in the G1 phase of the cell cycle. Western blot analysis showed that DUXAP10 knockdown decreased p-AKT expression in HCC cells. Conclusion: Our study demonstrates that pseudogene DUXAP10 promotes HCC cell proliferation by activating PI3K/AKT pathway and could act as a potential diagnostic and prognostic biomarker for HCC patients.

Comprehensive analysis of potential prognostic genes for the construction of a competing endogenous RNA regulatory network in hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is an extremely common malignant tumor with worldwide prevalence. The aim of this study was to identify potential prognostic genes and construct a competing endogenous RNA (ceRNA) regulatory network to explore the mechanisms underlying the development of HCC.

METHODS

Integrated analysis was used to identify potential prognostic genes in HCC with R software based on the GSE14520, GSE17548, GSE19665, GSE29721, GSE60502, and the Cancer Genome Atlas databases. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway-enrichment analyses were performed to explore the molecular mechanisms of potential prognostic genes. Differentially expressed miRNAs (DEMs) and lncRNAs (DELs) were screened based on the Cancer Genome Atlas database. An lncRNA-miRNA-mRNA ceRNA regulatory network was constructed based on information about interactions derived from the miRcode, TargetScan, miRTarBase, and miRDB databases.

RESULTS

A total of 152 potential prognostic genes were screened that were differentially expressed in HCC tissue and significantly associated with overall survival of HCC patients. There were 13 key potential prognostic genes in the ceRNA regulatory network: eleven upregulated genes (CCNB1, CEP55, CHEK1, EZH2, KPNA2, LRRC1, PBK, RRM2, SLC7A11, SUCO, and ZWINT) and two downregulated genes (ACSL1 and CDC37L1) whose expression might be regulated by eight DEMs and 61 DELs. Kaplan-Meier curve analysis showed that nine DELs (AL163952.1, AL359878.1, AP002478.1, C2orf48, C10orf91, CLLU1, CLRN1-AS1, ERVMER61-1, and WARS2-IT1) in the ceRNA regulatory network were significantly associated with HCC-patient prognoses.

CONCLUSION

This study identified potential prognostic genes and constructed an lncRNA- miRNA-mRNA ceRNA regulatory network of HCC, which not only has important clinical significance for early diagnoses but also provides effective targets for HCC treatments and could provide new insights for HCC-interventional strategies.

Microarray-based measurement of microRNA-449c-5p levels in hepatocellular carcinoma and bioinformatic analysis of potential signaling pathways

The clinical role and potential molecular mechanisms of microRNA-449c-5p (miR-449c-5p) in hepatocellular carcinoma (HCC) tissues remains unclear. Combining multiple bioinformatic tools, we studied the miR-449c-5p expression levels in HCC tissues and explored possible target genes and related signaling pathways. First, miR-449c-5p expression data from microarrays provided by publicly available sources were mined and analyzed using various meta-analysis methods. Next, genes that were downregulated after miR-449c-5p mimic transfection into HCC cells were identified, and in silico methods were used to predict potential target genes. Several bioinformatic assessments were also performed to evaluate the possible signaling pathways of miR-449c-5p in HCC. Five microarrays were included in the current study, including GSE98269, GSE64632, GSE74618, GSE40744 and GSE57555. The standard mean difference was 0.44 (0.07-0.80), and the area under the curve was 0.68 (0.63-0.72), as assessed by meta-analyses, which consistently indicated the upregulation of miR-449c-5p in HCC tissues. A total of 2244 genes were downregulated after miR-449c-5p mimic transfection into an HCC cell line, while 5217 target genes were predicted by in silico methods. The overlap of these two gene pools led to a final group of 428 potential target genes of miR-449c-5p. These 428 potential target genes were primarily enriched in the homologous recombination pathway, which includes DNA Polymerase Delta 3 (POLD3). Data mining with Oncomine and the Human Protein Atlas showed a decreasing trend in POLD3 mRNA and protein levels in HCC tissue samples. This evidence suggests that miR-449c-5p could play an essential role in HCC through various pathways and that POLD3 could be a potential miR-449c-5p target. However, these in silico findings should be validated with further experiments.