Identification of 40S ribosomal protein S8 as a novel biomarker for alcohol‑associated hepatocellular carcinoma using weighted gene co‑expression network analysis

DNA methylation-mediated epigenetic regulation of oncogenic RPS2 as a novel therapeutic target and biomarker in hepatocellular carcinoma

Ribosomal Protein S2 (RPS2) has emerged as a potential prognostic biomarker due to its involvement in key cellular processes and its altered expression pattern in certain types of cancer. However, its role in hepatocellular carcinoma (HCC) has yet to be investigated. Herein, we analyzed RPS2 mRNA expression and promoter methylation in HCC patient samples and HepG2 cells. Subsequently, loss-of-function experiments were conducted to determine the function of RPS2 in HCC cells in vitro. Our results revealed that RPS2 mRNA expression is significantly elevated, and its promoter is hypomethylated in HCC patient samples compared to controls. In addition, 5-Azacytidine treatment in HepG2 cells decreased RPS2 promoter methylation level and increased its mRNA expression. RPS2 knockdown in HepG2 cells suppressed cell proliferation and promoted apoptosis. Functional pathway analysis of genes positively and negatively associated with RPS2 expression in HCC showed enrichment in ribosomal biogenesis, translation machinery, cell cycle regulation, and DNA processing. Furthermore, utilizing drug-protein 3D docking, we found that doxorubicin, sorafenib, and 5-Fluorouracil, showed high affinity to the active sites of RPS2, and in vitro treatment with these drugs reduced RPS2 expression. For the first time, we report on DNA methylation-mediated epigenetic regulation of RPS2 and its oncogenic role in HCC. Our findings suggest that RPS2 plays a significant role in the development and progression of HCC, hence its potential prognostic and therapeutic utility. Moreover, as epigenetic changes happen early in cancer development, RPS2 may serve as a potential biomarker for tumor progression.

An immune signature to predict the prognosis of ATRX-wildtype glioma patients and guide immune checkpoint blockade therapy

Immune and stromal cells contribute to glioma progression by infiltrating the tumor microenvironment. We used clinical characteristics, RNA sequencing data and the ESTIMATE algorithm to obtain stromal and immune scores for alpha thalassemia retardation syndrome X-linked (ATRX)-mutation-type (ATRX-mt) and ATRX-wildtype (ATRX-wt) glioma tissues from The Cancer Genome Atlas. To identify specific immune biomarkers of glioma, we compared the gene expression profiles of ATRX-wt glioma tissues with high vs. low immune/stromal scores, and discovered 162 differentially expressed genes. The protein-protein interaction network based on these results contained 80 interacting genes, of which seven (HOXA5, PTPN2, WT1, HOXD10, POSTN, ADAMDEC1 and MYBPH) were identified as key prognostic genes via LASSO and Cox regression analyses. A risk model constructed using the expression of these seven genes could predict survival for ATRX-wt glioma patients, but was ineffective for ATRX-mt patients. T cells and macrophages were more prevalent in low-risk than in high-risk glioma tissues. Immune checkpoint blockade treatment was highly beneficial for patients with low risk scores. High-risk gliomas were predicted to be more sensitive to rapamycin, dasatinib, 5-fluorouracil and gemcitabine. Thus, our model can be used for the diagnosis, prognostic prediction and treatment planning of ATRX-wt glioma patients.

High expression of RPL27A predicts poor prognosis in patients with hepatocellular carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common cancers in the digestive system with rapid progression and poor prognosis. Recent studies have shown that RPL27A could be used as a biomarker for a variety of cancers, but its role in HCC is not clear.

METHOD

We analyzed the expression of RPL27A in the pan-cancer analysis and analyzed the relationship between the expression of RPL27A and the clinical features and prognosis of patients with HCC. We evaluated the expression difference of RPL27A in HCC tissues and paired normal adjacent tissues using immunohistochemistry. Furthermore, we analyzed the co-expression genes of RPL27A and used them to explore the possible mechanism of RPL27A and screen hub genes effecting HCC. In addition, we studied the role of RPL27A in immune infiltration and mutation.

RESULTS

We found that the expression level of RPL27A increased in a variety of cancers, including HCC. In HCC patients, the high expression of RPL27A was related to progression and poor prognosis as an independent predictor. We also constructed a protein interaction network through co-expression gene analysis of RPL27A and screened 9 hub genes. Enrichment analysis showed that co-expression genes were associated with ribosome pathway, viral replication, nuclear-transcribed mRNA catabolic process, and nonsense-mediated decay. We found that the expression level of RPL27A was closely related to TP53 mutation and immune infiltration in HCC.

CONCLUSION

RPL27A might become a biomarker in the diagnosis, treatment, and follow-up of patients with HCC.

Integrated analysis of single-cell and bulk RNA-sequencing reveals tumor heterogeneity and a signature based on NK cell marker genes for predicting prognosis in hepatocellular carcinoma

Background: Natural killer (NK) cells are a type of innate immune cell that recognize and eliminate tumor cells and infected cells, without prior sensitization or activation. Herein, we aimed to construct a predictive model based on NK cell-related genes for hepatocellular carcinoma (HCC) patients and assess the feasibility of utilizing this model for prognosis prediction. Methods: Single-cell RNA-seq data were obtained from the Gene Expression Omnibus (GEO) database to identify marker genes of NK cells. Univariate Cox and lasso regression were performed to further establish a signature in the TCGA dataset. Subsequently, qPCR and immunohistochemistry (IHC) staining were employed to validate the expression levels of prognosis signature genes in HCC. The effectiveness of the model was further validated using two external cohorts from the GEO and ICGC datasets. Clinical characteristics, prognosis, tumor mutation burden, immune microenvironments, and biological function were compared for different genetic subtypes and risk groups. Finally, molecular docking was performed to evaluate the binding affinity between the hub gene and chemotherapeutic drugs. Results: A total of 161 HCC-related NK cell marker genes (NKMGs) were identified, 28 of which were significantly associated with overall survival in HCC patients. Based on differences in gene expression characteristics, HCC patients were classified into three subtypes. Ten prognosis genes (KLRB1, CD7, LDB2, FCER1G, PFN1, FYN, ACTG1, PABPC1, CALM1, and RPS8) were screened to develop a prognosis model. The model not only demonstrated excellent predictive performance on the training dataset, but also were successfully validated on two independent external datasets. The risk scores derived from the model were shown to be an independent prognosis factor for HCC and were correlated with pathological severity. Moreover, qPCR and IHC staining confirmed that the expression of the prognosis genes was generally consistent with the results of the bioinformatic analysis. Finally, molecular docking revealed favorable binding energies between the hub gene ACTG1 and chemotherapeutic drugs. Conclusion: In this study, we developed a model for predicting the prognosis of HCC based on NK cells. The utilization of NKMGs as innovative biomarkers showed promise in the prognosis assessment of HCC.

Identification of ribosomal protein family as immune-cell-related biomarkers of NAFLD by bioinformatics and experimental analyses

Background

Immune cells play an integral role in the development and progression of non-alcoholic fatty liver disease (NAFLD). This study was to identify immune-cell-related biomarkers for the diagnosis and treatment of NAFLD.

Methods and findings

First, we introduced human liver transcriptome data from the GEO database (GSE48452 and GSE126848) and performed a weighted gene co-expression network analysis (WGCNA) to screen out the modules related to immune cell infiltration and to identify immune-cell-related differentially expressed genes (ICR-DEGs) associated with NAFLD progression. Further, the protein-protein interaction (PPI) network of ICR-DEGs was established to obtain hub genes and subsequently, the expression trend analysis was conducted to identify immune-cell-related biomarkers of NAFLD. Finally, the mRNA expression of biomarkers was validated in a NAFLD mouse model induced by high-fat diet (HFD) feeding. In total, we identified 66 ICR-DEGs and 13 hub genes associated with NAFLD. Among them, 9 hub genes (CD247, CD74, FCGR2B, IL2RB, INPP5D, MRPL16, RPL35, RPS3A, RPS8) were correlated with the infiltrating immune cells by the Pearson correlation analysis. Subsequently, 4 immune-cell-related biomarkers (RPL35, RPS3A, RPS8, and MRPL16) with the same expression trends in GSE48452 and GSE126848 datasets were identified. These biomarkers were enriched in immune-related pathways and had a good ability to distinguish between NASH and healthy samples. Moreover, we constructed a competing endogenous RNA (ceRNA) network of biomarkers and predicted twenty potential therapeutic drugs targeting RPS3A such as taxifolin and sitagliptin. Finally, experimental validation indicated that the hepatic mRNA expression of Rpl35, Rps3A, and Rps8 was significantly decreased in NAFLD mice.

Conclusions

This study identified four ribosomal protein genes (RPL35, RPS3A, RPS8, and MRPL16) as immune-cell-related biomarkers of NAFLD, which may actively participate in the immune processes during NAFLD progression and could serve as potential targets for the diagnosis and treatment of NAFLD.

RPS14 promotes the development and progression of glioma via p53 signaling pathway

Glioma is a common primary intracranial brain disease that exhibits an increasing incidence and mortality rate. Accumulating evidences have suggested that Ribosomal protein S14 (RPS14) was involved in cell proliferation and tumor progression. Nevertheless, the biological function and underlying mechanism of RPS14 in glioma are still largely unclear. Herein, we found that RPS14 was overexpressed in glioma. In the loss-of-function experiments, RPS14 depletion markedly suppressed glioma cell proliferation, migration and prompted cell apoptosis in vitro. Further study suggested that RPS14 depletion inhibited tumor growth of glioma in vivo. Additionally, human phospho-kinase array profiling and Western blot analysis revealed that the effects of RPS14 knockdown on glioma may be closely associated with p53 signaling pathway. Further study indicated that addition of p53 inhibitor pifithrin-α (PFT-α) could attenuate the influences of RPS14 knockdown on cell proliferation and apoptosis. Taken together, our findings suggested that RPS14 exhibits a pro-oncogenic role in glioma progression and may be act as a novel potential therapeutic target for gliomas.

Network analysis of hepatocellular carcinoma liquid biopsies augmented by single-cell sequencing data

Liquid biopsy, the analysis of body fluids, represents a promising approach for disease diagnosis and prognosis with minimal intervention. Sequencing cell-free RNA derived from liquid biopsies has been very promising for the diagnosis of several diseases. Cancer research, in particular, has emerged as a prominent candidate since early diagnosis has been shown to be a critical determinant of disease prognosis. Although high-throughput analysis of liquid biopsies has uncovered many differentially expressed genes in the context of cancer, the functional connection between these genes is not investigated in depth. An important approach to remedy this issue is the construction of gene networks which describes the correlation patterns between different genes, thereby allowing to infer their functional organization. In this study, we aimed at characterizing extracellular transcriptome gene networks of hepatocellular carcinoma patients compared to healthy controls. Our analysis revealed a number of genes previously associated with hepatocellular carcinoma and uncovered their association network in the blood. Our study thus demonstrates the feasibility of performing gene co-expression network analysis from cell-free RNA data and its utility in studying hepatocellular carcinoma. Furthermore, we augmented cell-free RNA network analysis with single-cell RNA sequencing data which enables the contextualization of the identified network modules with cell-type specific transcriptomes from the liver.

Aberrant Expression of BUB1B Contributes to the Progression of Thyroid Carcinoma and Predicts Poor Outcomes for Patients

Objective: This study aimed to clarify the function and potential mechanism of BUB1B in THCA.

Methods: Expression of BUB1B in THCA was firstly determined, and its important prognostic value was then demonstrated. The potential mechanism was initially predicted by KEGG analysis. To explore the specific function of BUB1B in THCA, we used lentivirus infection to knock down the BUB1B, and then performed flow cytometry, colony formation, transwell, and wound-healing assays. Related protein expression was detected through western blotting. Additionally, we predicted the BUB1B-regulated pathways involved in THCA by GSEA analysis.

Results: BUB1B expression was highly increased in THCA tissues relative to normal controls. We further found that BUB1B was essential for tumor cell proliferation, and BUB1B high expression predicted a shorter PFS time of THCA patients. More importantly, Cox regression determined the BUB1B as an independent prognostic factor for PFS in THCA. BUB1B was initially found to participate in the cell cycle pathway from KEGG analysis. Unexpectedly, we did not detect the disturbing effect on the cell cycle distribution of THCA cells with BUB1B knockdown. But, BUB1B knockdown inhibited the proliferation, invasion, and migration of THCA cells, as well as increased apoptotic cells, and the results were further confirmed by western blotting. Through GSEA analysis, we predicted a positive correlation between BUB1B and metastasis-related pathways such as mTOR and NF-kappa B signaling pathways.

Conclusions: Present study identified BUB1B as a promising clinical prognostic factor in THCA, as well as a potential novel therapeutic target for cancer treatment.

Downregulation of Methionine Cycle Genes MAT1A and GNMT Enriches Protein-Associated Translation Process and Worsens Hepatocellular Carcinoma Prognosis

The major biological methyl donor, S-adenosylmethionine (adoMet) synthesis occurs mainly in the liver. Methionine adenosyltransferase 1A (MAT1A) and glycine N-methyltransferase (GNMT) are two key enzymes involved in the functional implications of that variation. We collected 42 RNA-seq data from paired hepatocellular carcinoma (HCC) and its adjacent normal liver tissue from the Cancer Genome Atlas (TCGA). There was no mutation found in MAT1A or GNMT RNA in the 42 HCC patients. The 11,799 genes were annotated in the RNA-Seq data, and their expression levels were used to investigate the phenotypes of low MAT1A and low GNMT by Gene Set Enrichment Analysis (GSEA). The REACTOME_TRANSLATION gene set was enriched and visualized in a heatmap along with corresponding differences in gene expression between low MAT1A versus high MAT1A and low GNMT versus high GNMT. We identified 43 genes of the REACTOME_TRANSLATION gene set that are powerful prognosis factors in HCC. The significantly predicted genes were referred into eukaryotic translation initiation (EIF3B, EIF3K), eukaryotic translation elongation (EEF1D), and ribosomal proteins (RPs). Cell models expressing various MAT1A and GNMT proved that simultaneous restoring the expression of MAT1A and GNMT decreased cell proliferation, invasion, as well as the REACTOME_TRANSLATION gene EEF1D, consistent with a better prognosis in human HCC. We demonstrated new findings that downregulation or defect in MAT1A and GNMT genes can enrich the protein-associated translation process that may account for poor HCC prognosis. This is the first study demonstrated that MAT1A and GNMT, the 2 key enzymes involved in methionine cycle, could attenuate the function of ribosome translation. We propose a potential novel mechanism by which the diminished GNMT and MAT1A expression may confer poor prognosis for HCC.

Deregulation of ribosomal proteins in human cancers

The ribosome, the site for protein synthesis, is composed of ribosomal RNAs (rRNAs) and ribosomal proteins (RPs). The latter have been shown to have many ribosomal and extraribosomal functions. RPs are implicated in a variety of pathological processes, especially tumorigenesis and cell transformation. In this review, we will focus on the recent advances that shed light on the effects of RPs deregulation in different types of cancer and their roles in regulating the tumor cell fate.

Expression and Prognostic Role of E2F2 in Hepatocellular Carcinoma

Introduction

Hepatocellular carcinoma (HCC) is a common clinical malignancy. Recent studies reported that E2F transcription factor 2 (E2F2) plays a significant role in tumor progression. However, its expression and biological function in HCC are still unclear. Therefore, we explored the relationship between E2F2 expression and tumor progression in HCC.

Methods

In this study, we utilized some online tools to explore the E2F2 expression in pan-carcinoma and HCC. The association of E2F2 expression with the clinical characteristics and prognosis of HCC was further studied. In addition, we explored the co-expressed genes of E2F2 and mined the positively/negatively corrected significant genes and excavated the possible functions. Meanwhile, the hub gene set was constructed based on protein-protein interaction (PPI) network, and the relationship between E2F2 and immunity was discovered.

Results

We observed that the expression level of E2F2 was generally upregulated in HCC. However, E2F2 expression was not significantly different between HCC and normal tissues in regard to the disease stage 4. Furthermore, we also observed the poor prognosis in patients with high E2F2 expression. The co-expressed genes of E2F2 were identified and further detected. Thereafter, we identified the positively/negatively corrected significant genes and constructed the hub gene network of E2F2 based on PPI network. We also found that E2F2 expression was positively correlated with the infiltration levels of CD4+ T, CD8+ T cells, macrophages, neutrophils, and dendritic cells.

Conclusion

Our findings suggested that E2F2 could be a potential prognostic factor for HCC, which could provide a therapeutic target for the molecular treatment of HCC.

AURKB, CHEK1 and NEK2 as the Potential Target Proteins of Scutellaria barbata on Hepatocellular Carcinoma: An Integrated Bioinformatics Analysis

Objective

We aim to explore the potential anti-HCC mechanism of Scutellaria barbata through integrated bioinformatics analysis.

Methods

We searched active ingredients and related targets of Scutellaria barbata via TCMSP database, PubChem and SwissTargetPrediction database. Then, we identified HCC disease targets from GEO dataset by WGCNA. Next, the intersected targets of disease targets and drug targets were input into STRING database to construct PPI networking in order to obtain potential therapeutic targets of Scutellaria barbata. Cytoscape software was used to carry out network topology analysis of potential targets. We used the R package for GO analysis and KEGG analysis. Finally, we used AutoDock vina and PyMOL software for molecular docking.

Results

Sixteen active components from Scutellaria barbata were lastly selected for further investigation. A total of 442 component targets were identified from 16 active ingredients of Scutellaria barbata after the removal of duplicate targets. GSE45436 was selected for construction of WGCNA and screening of differentially expressed genes. A total of 354 genes were up-regulated in HCC samples and 100 were down-regulated in HCC patients. Twenty-one common genes were obtained by intersection and 10 critical targets were filtered for further investigation. The enrichment analysis showed that cell cycle, DNA replication, p53 signaling pathway were mainly involved. The molecular docking results showed that 4 potential combinations were with the best binding energy and molecular interactions.

Conclusion

AURKB, CHEK1 and NEK2 could be the potential target proteins of Scutellaria barbata in treating HCC. Cell cycle, DNA replication, p53 signaling pathway consist of the fundamental regulation cores in this mechanism.

Identification of metabolism genes related to hepatocarcinogenesis and progression in type 2 diabetes mellitus via co-expression networks analysis

Background

Type 2 Diabetes Mellitus (T2DM) is an independent risk factor of hepatocellular carcinoma (HCC). However, the related genes and modules to hepatocarcinogenesis and progression in T2DM remain unclear.

Methods

The microarray data from Gene Expression Omnibus (GEO) were analyzed to screen differentially expressed genes (DEGs) of T2DM and HCC dataset. Then, weighted gene co-expression network analysis (WGCNA) was performed on these DEGs to detect the modules and genes, respectively. Common genes in modules with clinical interests of T2DM and HCC were obtained and annotated via GOSemSim package and Metascape. Genes related to late-stage HCC and high glycated haemoglobin (HbA1c) were also identified. These genes were validated by UALCAN analysis and univariate cox regression based on The Cancer Genome Atlas (TCGA). Finally, another two independent datasets were applied to confirm the results of our study.

Results

A total of 1288 and 1559 DEGs of T2DM and HCC were screened, respectively. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment revealed several shared pathways in two diseases, such as pathways in cancer and metabolism. A total of 37 common genes correlated with T2DM and HCC were then identified with WGCNA. Furthermore, 12 genes from modules associated with late-stage HCC and high HbA1c were regarded as hub genes. Among these genes, 8 genes associated with tumor invasion and metastasis were validated by UALCAN analysis. Moreover, downregulations of ACAT1, SLC2A2, PCK1 and ABAT were significantly associated with poorer prognosis in HCC patients with elevated HbA1c. Additionally, the expressions of PCK1 and ABAT were raised in HepG2 cells pre-treated with metformin and phenformin.

Conclusions

The present study confirmed several metabolic genes related to hyperglycemia and malignant tumor, which may provide not only new insights into the pathogenesis of hepatocarcinogenesis and progression in T2DM, but also novel therapeutic targets for T2DM patients with HCC in the future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s41065-021-00177-x.

PSMC2, ORC5 and KRTDAP are specific biomarkers for HPV-negative head and neck squamous cell carcinoma

The prognosis of patients with human papillomavirus (HPV)-negative head and neck squamous cell carcinoma (HNSCC) is poorer than those with HPV-positive HNSCC. The present study aimed to identify novel and specific biomarkers of HPV-negative HNSCC using bioinformatics analysis and associated experiments. The gene expression profiles of HPV-negative HNSCC tissues and corresponding clinical data were downloaded from The Cancer Genome Atlas database and used in a weighted gene co-expression network analysis. Genes in clinically significant co-expression modules were used to construct a protein-protein interaction (PPI) network. The genes demonstrating a high degree score in the PPI network and a high correlation with tumor grade were considered hub genes. The diagnostic value of the hub genes associated with HPV-negative and HPV-positive HNSCC was analyzed using differential expression gene (DEG) analysis, immunohistochemical (IHC) staining and a receiver operating characteristic (ROC) curve analysis. Seven genes [Serrate RNA effector molecule (SRRT), checkpoint kinase 2 (CHEK2), small nuclear ribonucleoprotein polypeptide E (SNRPE), proteasome 26S subunit ATPase 2 (PSMC2), origin recognition complex subunit 5 (ORC5), S100 calcium binding protein A7 and keratinocyte differentiation associated protein (KRTDAP)] were demonstrated to be hub genes in clinically significant co-expression modules. DEG, IHC and ROC curve analyses revealed that SRRT, CHEK2 and SNRPE were significantly upregulated in HPV-negative and HPV-positive HNSCC tissues compared with in adjacent tissues, and these genes demonstrated a high diagnostic value for distinguishing HNSCC tissues. However, PSMC2, ORC5 and KRTDAP were the only differentially expressed genes identified in HPV-negative HNSCC tissues, and these genes demonstrated a high diagnostic value for HPV-negative HNSCC. PSMC2, ORC5 and KRTDAP may therefore serve as novel and specific biomarkers for HPV-negative HNSCC, potentially improving the diagnosis and treatment of patients with HPV-negative HNSCC.