Identification of 13 Key Genes Correlated With Progression and Prognosis in Hepatocellular Carcinoma by Weighted Gene Co-expression Network Analysis

Identification of Hub Genes in Liver Hepatocellular Carcinoma Based on Weighted Gene Co-expression Network Analysis

Liver hepatocellular carcinoma (LIHC) is a malignant cancer with high incidence and poor prognosis. To investigate the correlation between hub genes and progression of LIHC and to provided potential prognostic markers and therapy targets for LIHC. Our study mainly used The Cancer Genome Atlas (TCGA) LIHC database and the gene expression profiles of GSE54236 from the Gene Expression Omnibus (GEO) to explore the differential co-expression genes between LIHC and normal tissues. The differential co-expression genes were extracted by Weighted Gene Co-expression Network Analysis (WGCNA) and differential gene expression analysis methods. The Genetic Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were carried out to annotate the function of differential genes. Then the hub genes were validated using protein-protein interaction (PPI) network. And the expression level and prognostic analysis were performed. The probable associations between the expression of hub genes and both tumor purity and infiltration of immune cells were explored by TIMER. A total of 68 differential co-expression genes were extracted. These genes were mainly enriched in complement activation (biological process), collagen trimer (cellular component), carbohydrate binding and receptor ligand activity (molecular function) and cytokine - cytokine receptor interaction. Then we demonstrated that the 10 hub genes (CFP, CLEC1B, CLEC4G, CLEC4M, FCN2, FCN3, PAMR1 and TIMD4) were weakly expressed in LIHC tissues, the qRT-PCR results of clinical samples showed that six genes were significantly downregulated in LIHC patients compared with adjacent tissues. Worse overall survival (OS) and disease-free survival (DFS) in LIHC patients were associated with the lower expression of CFP, CLEC1B, FCN3 and TIMD4. Ten hub genes had positive association with tumor purity. CFP, CLEC1B, FCN3 and TIMD4 could serve as novel potential molecular targets for prognosis prediction in LIHC.

SKA3 targeted therapies in cancer precision surgery: bridging bench discoveries to clinical applications - review article

Spindle and kinetochore-associated complex subunit 3 (SKA3) is a microtubule-binding subcomplex of the outer kinetochore, which plays a vital role in proper chromosomal segregation and cell division. Recently, SKA3 have been demonstrated its oncogenic role of tumorigenesis and development in cancers. In this review, the authors comprehensively deciphered SKA3 in human cancer from various aspects, including bibliometrics, pan-cancer analysis, and narrative summary. The authors also provided the top 10 predicted drugs targeting SKA3. The authors proposed that SKA3 was a potential target and brought new therapeutic opportunities for cancer patients.

Delineating the twin role of autophagy in lung cancer

Autophagy represents an intracellular defense mechanism equipped within each eukaryotic cells to enable them to cope with variety of physical, chemical, and biological stresses. This mechanism helps to restore the homeostasis and preserve the cellular integrity and function of the cells. In these conditions, such as hypoxia, nutrient deprivation, inhibition of protein synthesis or microbial attack, the process of autophagy is upregulated to maintain cellular homeostasis. The role of autophagy in cancer is an intriguing topic which needs further exploration. This process of autophagy has been many times referred as a double-edged sword in the process of tumorigenesis. In the initial stages, it may act as a tumor suppressor and enable to quench the damaged organelles and harmful molecules generated. In more advanced stages, autophagy has been shown to act as a tumor-promoting system as it may help the cancer cells to cope better with stressful microenvironments. Besides this, autophagy has been associated with development of resistance to anticancer drugs as well as promoting the immune evasion in cancer cells, representing a serious obstacle in cancer treatment and its outcome. Also, autophagy is associated with hallmarks of cancer that may lead to activation of invasion and metastasis. The information on this twin role needs further exploration and deeper understanding of the pathways involved. In this review, we discuss the various aspects of autophagy during tumor development, from early to late stages of tumor growth. Both the protective role of autophagy in preventing tumor growth and the underlying mechanisms adopted with evidence from past studies have been detailed. Further, the role of autophagy in conferring resistance to distinct lung cancer treatment and immune shielding properties has also been discussed. This is essential for further improving on treatment outcome and success rates.

PRR11 in Malignancies: Biological Activities and Targeted Therapies

Proline rich 11 (PRR11), initially renowned for its relevance with cell-cycle progression, is a proline-rich protein coding gene in chromosome 17q22-23. Currently, accumulating studies have demonstrated that PRR11 plays a critical role in cellular proliferation, colony formation, migration, invasion, cell-cycle progression, apoptosis, autophagy and chemotherapy resistance via multiple signaling pathways and biological molecules in several solid tumors. In particular, PRR11 also serves as a promising prognostic indicator in a limited number of human cancers, gradually manifesting its potential application for targeted therapies. In this review, we summarize functional activities, related signaling pathways and biological molecules of PRR11 in various malignancies and generalize potential application of PRR11 for targeted therapies, thereby contributing to further exploration of PRR11 in cancer treatment.

Identification of BRIP1, NSMCE2, ANAPC7, RAD18 and TTL from chromosome segregation gene set associated with hepatocellular carcinoma

INTRODUCTION

Hepatocellular carcinoma is one of the most frequent cancers with high mortality rate worldwide.

METHODS

TCGA LIHC HTseq counts were analyzed. GSEA was performed with GO BP gene sets. GO analysis was performed with differentially expressed genes. The subset of genes contributing most of the enrichment result of GO_BP_CHROMOSOME_SEGREGATION of GSEA were identified. Five genes have been selected in this subset of genes for further analysis. A microarray data set, GSE112790, was analyzed as a validation data set. Survival analysis was performed.

RESULTS

According to GSEA and GO analysis several gene sets and processes related to chromosome segregation were enriched in LIHC. GO_BP_CHROMOSOME_SEGREGATION gene set from GSEA had the highest size of the genes contributing most of the enrichment. Five genes in this gene set; BRIP1, NSMCE2, ANAPC7, RAD18 and TTL, whose expressions and prognostic values have not been studied in hepatocellular carcinoma in detail, have been selected for further analyses. Expression of these five genes were identified as significantly upregulated in LIHC RNA-seq and HCC microarray data set. Survival analysis showed that high expression of the five genes was associated with poor overall survival in HCC patients.

CONCLUSION

Selected genes were upregulated and had prognostic value in HCC.

SNRPD2 Is a Novel Substrate for the Ubiquitin Ligase Activity of the Salmonella Type III Secretion Effector SlrP

Simple Summary

Salmonella is a genus of bacterial pathogens that can cause several diseases in humans and other animals. These bacteria can inject proteins known as effectors into animal cells through a secretion system. One of these effectors, SlrP, promotes the covalent addition of ubiquitin, a small eukaryotic protein, to specific host proteins, leading to an alteration of their stability or function. Here, we have performed a genetic screen to find new human targets of SlrP. In this way, we have identified SNRPD2, a core component of the spliceosome, the ribonucleoprotein complex that removes introns from eukaryotic pre-mRNA. SNRPD2 physically interacts with SlrP and is also a substrate of its ubiquitination activity. Lysines at positions 85 and 92 in SNRPD2 are among the residues that were ubiquitinated in the presence of SlrP. The identification of new host targets of Salmonella effectors contributes to a better understanding of the biological processes that are highjacked by these pathogens during infection, and can help in the design of future therapeutic strategies.

Abstract

SlrP is a protein with E3 ubiquitin ligase activity that is translocated by Salmonella enterica serovar Typhimurium into eukaryotic host cells through a type III secretion system. A yeast two-hybrid screen was performed to find new human partners for this protein. Among the interacting proteins identified by this screen was SNRPD2, a core component of the spliceosome. In vitro ubiquitination assays demonstrated that SNRPD2 is a substrate for the catalytic activity of SlrP, but not for other members of the NEL family of E3 ubiquitin ligases, SspH1 and SspH2. The lysine residues modified by this activity were identified by mass spectrometry. The identification of a new ubiquitination target for SlrP is a relevant contribution to the understanding of the role of this Salmonella effector.

Construction of a co-expression network and prediction of metastasis markers in colorectal cancer patients with liver metastasis

BACKGROUND

Colorectal cancer (CRC) is a common global malignancy associated with high invasiveness, high metastasis, and poor prognosis. CRC commonly metastasizes to the liver, where the treatment of metastasis is both difficult and an important topic in current CRC management.

METHODS

Microarrays data of human CRC with liver metastasis (CRCLM) were downloaded from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database to identify potential key genes. Differentially expressed (DE) genes (DEGs) and DEmiRNAs of primary CRC tumor tissues and metastatic liver tissues were identified. Microenvironment Cell Populations (MCP)-counter was used to estimate the abundance of immune cells in the tumor micro-environment (TME), and weighted gene correlation network analysis (WGCNA) was used to construct the co-expression network analysis. Gene Ontology and Kyoto Encyclopaedia of Gene and Genome (KEGG) pathway enrichment analyses were conducted, and the protein-protein interaction (PPI) network for the DEGs were constructed and gene modules were screened.

RESULTS

Thirty-five pairs of matched colorectal primary cancer and liver metastatic gene expression profiles were screened, and 610 DEGs (265 up-regulated and 345 down-regulated) and 284 DEmiRNAs were identified. The DEGs were mainly enriched in the complement and coagulation cascade pathways and renin secretion. Immune infiltrating cells including neutrophils, monocytic lineage, and cancer-associated fibroblasts (CAFs) differed significantly between primary tumor tissues and metastatic liver tissues. WGCN analysis obtained 12 modules and identified 62 genes with significant interactions which were mainly related to complement and coagulation cascade and the focal adhesion pathway. The best subset regression analysis and backward stepwise regression analysis were performed, and eight genes were determined, including F10, FGG, KNG1, MBL2, PROC, SERPINA1, CAV1, and SPP1. Further analysis showed four genes, including FGG, KNG1, CAV1, and SPP1 were significantly associated with CRCLM.

CONCLUSIONS

Our study implies complement and coagulation cascade and the focal adhesion pathway play a significant role in the development and progression of CRCLM, and FGG, KNG1, CAV1, and SPP1 may be metastatic markers for its early diagnosis.

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.

High Expression of DEPDC1B Predicts Poor Prognosis in Lung Adenocarcinoma

Introduction

Lung adenocarcinoma (LUAD) is the most common type of lung cancer. DEP domain-containing 1 B (DEPDC1B) is involved in the development of several cancers; however, its role in LUAD is unknown. Therefore, we aimed to determine the biological function and prognostic value of DEPDC1B in LUAD.

Material and Methods

We analyzed the correlation between DEPDC1B expression and the clinical features of LUAD and lung squamous cell carcinoma (LUSC). Survival was evaluated by generating Kaplan-Meier curves, which were used to analyze the relationship between DEPDC1B expression and prognosis in LUAD and LUSC. DEPDC1B expression in tumor and normal tissues from patients with LUAD and LUSC was determined using immunohistochemistry, and its clinical significance was analyzed. Finally, the correlation between the expression and biological function of DEPDC1B in LUAD was examined.

Results

Our findings revealed that DEPDC1B expression was higher in tumor tissues than that in normal tissues from patients with LUAD and LUSC (P < 0.001). These results were confirmed in clinical samples from patients using immunohistochemistry. Analysis of a dataset from The Cancer Genome Atlas (TCGA) showed that high DEPDC1B expression was associated with poor prognosis only in patients with LUAD (P < 0.001). Similarly, high DEPDC1B expression was related to shorter overall survival (OS) and progression-free interval (PFI) in patients with LUAD. These associations were not observed in LUSC. Functional enrichment analysis suggested that DEPDC1B promoted tumor development in LUAD by regulating the cell cycle.

Conclusion

High DEPDC1B expression predicts poor prognosis in patients with LUAD. Thus, DEPDC1B has potential as a therapeutic target for LUAD.

The Expression and Role Analysis of Methylation-Regulated Differentially Expressed Gene UBE2C in Pan-Cancer, Especially for HGSOC

Simple Summary

DNA methylation has attracted a great deal of scientific interest as an early biomarker and potential therapeutic target. HGSOC result in high mortality due to the absence of reliable biomarkers for early diagnosis and prognosis. In this study, we performed an integrated bioinformatic analysis and found that UBE2C was hypomethylation and overexpression in ovarian cancer, which was associated with advanced cancer stages and poor prognoses. Meantime, this finding was also confirmed in pan-cancer analysis. Furthermore, the experimental validation of the expression and role of UBE2C was performed on HGSOC tissues and cancer cell lines. Importantly, demethylation could upregulate the expression of UBE2C. Taken together, methylation-regulated UBE2C may be a novel biomarker for diagnosis and prognosis, not only for ovarian cancer but a variety of cancers.

Abstract

High-grade serous ovarian cancer (HGSOC) is the most fatal gynecological malignant tumor. DNA methylation is associated with the occurrence and development of a variety of tumor types, including HGSOC. However, the signatures regarding DNA methylation changes for HGSOC diagnosis and prognosis are less explored. Here, we screened differentially methylated genes and differentially expressed genes in HGSOC through the GEO database. We identified that UBE2C was hypomethylation and overexpression in ovarian cancer, which was associated with more advanced cancer stages and poor prognoses. Additionally, the pan-cancer analysis showed that UBE2C was overexpressed and hypomethylation in almost all cancer types and was related to poor prognoses for various cancers. Next, we established a risk or prognosis model related to UBE2C methylation sites and screened out the three sites (cg03969725, cg02838589, and cg00242976). Furthermore, we experimentally validated the overexpression of UBE2C in HGSOC clinical samples and ovarian cell lines using quantitative real-time PCR, Western blot, and immunohistochemistry. Importantly, we discovered that ovarian cancer cell lines had lower DNA methylation levels of UBE2C than IOSE-80 cells (normal ovarian epithelial cell line) by bisulfite sequencing PCR. Consistently, treatment with 5-Azacytidine (a methylation inhibitor) was able to restore the expression of UBE2C. Taken together, our study may help us to understand the underlying molecular mechanism of UBE2C in pan-cancer tumorigenesis; it may be a useful biomarker for diagnosis, treatment, and monitoring, not only of ovarian cancer but a variety of cancers.

The feasibility of proteomics sequencing based immune-related prognostic signature for predicting clinical outcomes of bladder cancer patients

Background

Bladder cancer (BCa) shows its potential immunogenity in current immune-checkpoint inhibitor related immunotherapies. However, its therapeutic effects are improvable and could be affected by tumor immune microenvironment. Hence it is interesting to find some more prognostic indicators for BCa patients concerning immunotherapies.

Methods

In the present study, we retrospect 129 muscle-invasive BCa (MIBC) patients with radical cystectomy in Shanghai General Hospital during 2007 to 2018. Based on the results of proteomics sequencing from 9 pairs of MIBC tissue from Shanghai General Hospital, we focused on 13 immune-related differential expression proteins and their related genes. An immune-related prognostic signature (IRPS) was constructed according to Cancer Genome Atlas (TCGA) dataset. The IRPS was verified in ArrayExpress (E-MTAB-4321) cohort and Shanghai General Hospital (General) cohort, separately. A total of 1010 BCa patients were involved in the study, including 405 BCa patients in TCGA cohort, 476 BCa patients in E-MTAB-4321 cohort and 129 MIBC patients in General cohort.

Result

It can be indicated that high IRPS score was related to poor 5-year overall survival and disease-free survival. The IRPS score was also evaluated its immune infiltration. We found that the IRPS score was adversely associated with GZMB, IFN-γ, PD-1, PD-L1. Additionally, higher IRPS score was significantly associated with more M2 macrophage and resting mast cell infiltration.

Conclusion

The study revealed a novel BCa prognostic signature based on IRPS score, which may be useful for BCa immunotherapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-022-09783-y.

Overexpressed SNRPB/D1/D3/E/F/G correlate with poor survival and immune infiltration in hepatocellular carcinoma

BACKGROUND

Prior reports have indicated that the abnormal expression of small nuclear ribonucleoproteins (snRNPs) genes is related to malignant tumors. However, in hepatocellular carcinoma (HCC), the precise role of snRNPs is not well understood. Therefore, the purpose of this study was to evaluate the prognostic roles of SNRPB/D1/D2/D3/E/F/G and their correlation to immune infiltration in HCC.

METHODS

The study was carried out via the following databases, software, and experimental validation: ONCOMINE, GEPIA2, UALCAN, The Cancer Genome Atlas, Gene Expression Omnibus, ArrayExpress, Kaplan-Meier plotter, cBioPortal, STRING, DAVID 6.8, TIMER, Cytoscape software, and immunohistochemistry experiments.

RESULTS

Overexpressed SNRPB/D1/D2/D3/E/F/G proteins were found in HCC tissues. The transcription levels of 7 snRNPs genes were related to the TP53 mutation and tumor grades. SNRPB/D1/D2/D3/F/G expression was significantly correlated with cancer staging, whereas SNRPE was not. Moreover, Kaplan-Meier survival analysis showed that upregulation of SNRPB/D1/D2/E/G was relevant to worse OS in HCC patients, especially in patients with alcohol consumption and those without viral hepatitis. Multivariate Cox regression analysis indicated that expression of SNRPB/D1/D3/E/F/G were independent prognostic factors for unfavorable OS in HCC. In addition, a high mutation rate of snRNPs genes (44%) was also found in HCC. The mRNA expression levels of snRNPs were meaningfully and positively related to six types of infiltrating immune cells (B cells, CD4⁺ T cells, CD8⁺ T cells, neutrophil, macrophage, and dendritic cells). Also, SNRPB/D1/G genes were significantly associated with molecular markers of various immune cells in HCC.

CONCLUSIONS

SNRPB/D1/D3/E/F/G are potential prognostic biomarkers for a short OS in HCC, and SNRPB/D1/G were novel immune therapy targets in HCC patients.

A pan-cancer analysis of GINS complex subunit 4 to identify its potential role as a biomarker in multiple human cancers

This study was initiated to explore the expression variation, clinical significance, and biological importance of the GINS complex subunit 4 (GINS4) in different human cancers as a shared biomarker via pan-cancer analysis through different platforms including UALCAN, Kaplan Meier (KM) plotter, TNMplot, GENT2, GEPIA, DriverDBv3, Human Protein Atlas (HPA), MEXPRESS, cBioportal, STRING, DAVID, MuTarge, Enrichr, TIMER, and CTD. Our findings have verified the up-regulation of GINS4 in 24 major subtypes of human cancers, and its overexpression was found to be substantially associated with poor overall survival (OS), relapse-free survival (RFs), and metastasis in ESCA, KIRC, LIHC, LUAD, and UCEC. This suggested that GINS4 plays a significant role in the development and progression of these five cancers. Furthermore, we noticed that GINS4 is also overexpressed in ESCA, KIRC, LIHC, LUAD, and UCEC patients with different clinicopathological characteristics. Enrichment analysis revealed the involvement of GINS4 associated genes in a variety of diverse GO and KEGG terms. We also explored few significant correlations between GINS4 expression and promoter methylation, genetic alterations, CNVs, other mutant genes, tumor purity, and immune cells infiltration. In conclusion, our results elucidated that GINS4 can serve as a shared diagnostic, prognostic biomarker, and a potential therapeutic target in ESCA, KIRC, LIHC, LUAD, and UCEC patients with different clinicopathological characteristics.

Computational identification of host genomic biomarkers highlighting their functions, pathways and regulators that influence SARS-CoV-2 infections and drug repurposing

The pandemic threat of COVID-19 has severely destroyed human life as well as the economy around the world. Although, the vaccination has reduced the outspread, but people are still suffering due to the unstable RNA sequence patterns of SARS-CoV-2 which demands supplementary drugs. To explore novel drug target proteins, in this study, a transcriptomics RNA-Seq data generated from SARS-CoV-2 infection and control samples were analyzed. We identified 109 differentially expressed genes (DEGs) that were utilized to identify 10 hub-genes/proteins (TLR2, USP53, GUCY1A2, SNRPD2, NEDD9, IGF2, CXCL2, KLF6, PAG1 and ZFP36) by the protein–protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of hub-DEGs revealed some important functions and signaling pathways that are significantly associated with SARS-CoV-2 infections. The interaction network analysis identified 5 TFs proteins and 6 miRNAs as the key regulators of hub-DEGs. Considering 10 hub-proteins and 5 key TFs-proteins as drug target receptors, we performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 FDA approved drugs. We found Torin-2, Rapamycin, Radotinib, Ivermectin, Thiostrepton, Tacrolimus and Daclatasvir as the top ranked seven candidate drugs. We investigated their resistance performance against the already published COVID-19 causing top-ranked 11 independent and 8 protonated receptor proteins by molecular docking analysis and found their strong binding affinities, which indicates that the proposed drugs are effective against the state-of-the-arts alternatives independent receptor proteins also. Finally, we investigated the stability of top three drugs (Torin-2, Rapamycin and Radotinib) by using 100 ns MD-based MM-PBSA simulations with the two top-ranked proposed receptors (TLR2, USP53) and independent receptors (IRF7, STAT1), and observed their stable performance. Therefore, the proposed drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections.

DEP domain containing 1B (DEPDC1B) exerts the tumor promoter in hepatocellular carcinoma through activating p53 signaling pathway via kinesin family member 23 (KIF23)

Hepatocellular carcinoma (HCC) is closely associated with chronic liver disease and possesses a high incidence. DEP domain containing 1B (DEPDC1B) expression has been found to be upregulated in HCC according to bioinformatics analysis. This paper sought to study the specific role of DEPDC1B in HCC. The data of DEPDC1B expression and individual overall survival in HCC and normal liver tissues were acquired from UALCAN database. The association between DEPDC1B and the downstream signal, kinesin family member 23 (KIF23), was determined using LinkedOmics and STRING database, and subsequently confirmed by co-immunoprecipitation assay. The expression levels of DEPDC1B and KIF23 in normal hepatic epithelial cells and HCC cell lines were assessed by RT-qPCR and Western blotting, respectively. Following transfection with small interference RNA-DEPDC1B, the influences of DEPDC1B knockdown on cell proliferation, colony formation, cell cycle, cell invasion, migration, and KIF23 expression were evaluated. In addition, the effects of KIF23 overexpression on the above aspects of HCC cells were also determined, as well as the expression level of p53 signaling-related proteins. The results indicated that DEPDC1B was highly expressed in HCC cells. DEPDC1B knockdown inhibited the proliferation, migration, invasion, cycle, and KIF23 expression in HCC cells. Moreover, KIF23 overexpression reversed the inhibitory effect of DEPDC1B knockdown in HCC cells and the activation of the p53 signaling. In conclusion, DEPDC1B knockdown exerts anti-cancer role in HCC by activating the p53 signaling through KIF23.

A pan-cancer analysis based on weighted gene co-expression network analysis identifies the biomarker utility of lamin B1 in human tumors

Emerging evidence has revealed a relationship between lamin B1 (LMNB1) and several cancers such as cervical cancer, liver cancer, and prostate cancer. But no systematic pan-cancer analysis is available. Little is known about the clinical significance and biomarker utility of LMNB1. In this study, we first revealed the key role of LMNB1 in esophageal carcinoma (ESCA) through weighted gene co-expression network analysis (WGCNA) and disease-free survival (DFS) analysis. Based on this result and the datasets of the cancer genome atlas (TCGA), we explored the biomarker utility of LMNB1 across thirty-three tumors. We found that LMNB1 was highly expressed in most of the cancers and significant associations existed between LMNB1 expression and prognosis of cases of nearly half of the cancers. We also found that LMNB1 expression was associated with the infiltration level of Macrophages M1 and T cells CD4 memory activated in some cancers. Moreover, LMNB1 was mainly involved in the functional mechanisms of MRNA binding, olfactory transduction, and gene silencing. Our study first provides a pan-cancer study of LMNB1, thereby offering a relatively comprehensive understanding of the biomarker utility of LMNB1 across thirty-three tumors.

Novel oncogenes and tumor suppressor genes in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) is a very deadly disease. HCC initiation and progression involve multiple genetic events, including the activation of proto-oncogenes and disruption of the function of specific tumor suppressor genes. Activation of oncogenes stimulates cell growth and survival, while loss-of-function mutations of tumor suppressor genes result in unrestrained cell growth. In this review, we summarize the new findings that identified novel proto-oncogenes and tumor suppressors in HCC over the past five years. These findings may inspire the development of novel therapeutic strategies to improve the outcome of HCC patients.

A Reliable Prognostic Model for HCC Using Histological Grades and the Expression Levels of Related Genes

Hepatocellular carcinoma (HCC) is the most common primary liver malignancy and is a leading cause of cancer-related death worldwide. This study aimed to establish a reliable prognostic model for HCC using histological grades and the expression levels of related genes. The histological grade of a tumor provides prognostic information. The expression data of HCC samples were downloaded from The Cancer Genome Atlas (TCGA) database. We employed the univariate and multivariate Cox regression analyses, as well as the least absolute shrinkage and selection operator (LASSO) regression to establish the prognostic model. After verification of the proposed model using data downloaded from the International Cancer Genome Consortium (ICGC) database, we found that the model was highly reliable, and it was revealed that the prognosis in the high-risk group was significantly worse than that in the low-risk group. Next, we explored the correlation of RiskScore with patients' clinicopathological characteristics, and we found that the RiskScore could be used as an independent prognostic factor, which further confirmed the reliability of our model. In summary, the proposed model could accurately predict the prognosis of HCC patients, assisting clinicians to study the roles of different histological grades of HCC.

A Five-Gene-Based Prognostic Signature for Hepatocellular Carcinoma

Objective: This study intends to identify potential prognostic marker genes associated with the prognosis of patients suffering from hepatocellular carcinoma (HCC) based on TCGA and GEO analysis.

Methods: TCGA-LIHC cohort was downloaded and the data related to HCC were extracted from The Cancer Genome Atlas (TCGA) database and subjected to differential analysis. HCC-related gene expression datasets were retrieved from the GEO database, followed by differential analysis. After intersection of the results of TCGA and GEO databases, gene interaction analysis was performed to obtain the core genes. To identify the genes related to the prognosis of HCC patients, we conducted univariate and multivariate Cox analyses.

Results: Based on differential analysis of TCGA database, 854 genes were differentially expressed in HCC, any of which might link to the occurrence and progression of HCC. Meanwhile, joint analysis of HCC-related gene expression datasets in the GEO database screened 214 genes. Five core genes CDC20, TOP2A, RRM2, UBE2C and AOX1 were significantly associated with the prognosis of HCC patients and the risk model based on these five genes effectively predicted the prognosis of HCC patients.

Conclusion: Collectively, our data suggest that CDC20, TOP2A, RRM2, UBE2C and AOX1 may be the key genes affecting the prognosis of patients with HCC. The five-gene signature could accurately predict the prognosis of HCC patients.

Integrative Transcriptome Profiling Reveals SKA3 as a Novel Prognostic Marker in Non-Muscle Invasive Bladder Cancer

Approximately 80% of all new bladder cancer patients are diagnosed with non-muscle invasive bladder cancer (NMIBC). However, approximately 15% of them progress to muscle-invasive bladder cancer (MIBC), for which prognosis is poor. The current study aimed to improve diagnostic accuracy associated with clinical outcomes in NMIBC patients. Nevertheless, it has been challenging to identify molecular biomarkers that accurately predict MIBC progression because this disease is complex and heterogeneous. Through integrative transcriptome profiling, we showed that high SKA3 expression is associated with poor clinical outcomes and MIBC progression. We performed RNA sequencing on human tumor tissues to identify candidate biomarkers in NMIBC. We then selected genes with prognostic significance by analyzing public datasets from multiple cohorts of bladder cancer patients. We found that SKA3 was associated with NMIBC pathophysiology and poor survival. We analyzed public single-cell RNA-sequencing (scRNA-seq) data for bladder cancer to dissect transcriptional tumor heterogeneity. SKA3 was expressed in an epithelial cell subpopulation expressing genes regulating the cell cycle. Knockdown experiments confirmed that SKA3 promotes bladder cancer cell proliferation by accelerating G2/M transition. Hence, SKA3 is a new prognostic marker for predicting NMIBC progression. Its inhibition could form part of a novel treatment lowering the probability of bladder cancer progression.

Identification of the Real Hub Gene and Construction of a Novel Prognostic Signature for Pancreatic Adenocarcinoma Based on the Weighted Gene Co-expression Network Analysis and Least Absolute Shrinkage and Selection Operator Algorithms

Background: Pancreatic adenocarcinoma (PAAD) has a considerably bad prognosis, and its pathophysiologic mechanism remains unclear. Thus, we aimed to identify real hub genes to better explore the pathophysiology of PAAD and construct a prognostic panel to better predict the prognosis of PAAD using the weighted gene co-expression network analysis (WGCNA) and the least absolute shrinkage and selection operator (LASSO) algorithms. Methods: WGCNA identified the modules most closely related to the PAAD stage and grade based on the Gene Expression Omnibus. The module genes significantly associated with PAAD progression and prognosis were considered as the real hub genes. Eligible genes in the most significant module were selected for construction and validation of a multigene prognostic signature based on the LASSO-Cox regression analysis in The Cancer Genome Atlas and the International Cancer Genome Consortium databases, respectively. Results: The brown module identified by WGCNA was most closely associated with the clinical characteristics of PAAD. Scaffold attachment factor B (SAFB) was significantly associated with PAAD progression and prognosis, and was identified as the real hub gene of PAAD. Moreover, both transcriptional and translational levels of SAFB were significantly lower in PAAD tissues compared with normal pancreatic tissues. In addition, a novel multigene-independent prognostic signature consisting of SAFB, SP1, and SERTAD3 was identified and verified. The predictive accuracy of our signature was superior to that of previous studies, especially for predicting 3- and 5-year survival probabilities. Furthermore, a prognostic nomogram based on independent prognostic variables was developed and validated using calibration curves. The predictive ability of this nomogram was also superior to the well-established AJCC stage and histological grade. The potential mechanisms of different prognoses between the high- and low-risk subgroups were also investigated using functional enrichment analysis, GSEA, ssGSEA, immune checkpoint analysis, and mutation profile analysis. Conclusion: SAFB was identified as the real hub gene of PAAD. A novel multigene-independent prognostic signature was successfully identified and validated to better predict PAAD prognosis. An accurate nomogram was also developed and verified to aid in the accurate treatment of tumors, as well as in early intervention.

G2 and S phase-expressed-1 acts as a putative tumor promoter in cervical cancer by enhancing Wnt/β-catenin signaling via modulation of GSK-3β

G2 and S phase-expressed-1 (GTSE1) is currently identified as a key regulator of carcinogenesis. However, the involvement of GTSE1 in cervical cancer is unclear. The aims of this work were to explore the relationship between GTSE1 and cervical cancer. Our data elucidated high GTSE1 expression in cervical cancer tissue, which predicted a poor prognosis in cervical cancer patients. GTSE1 knockdown had tumor-suppressive effects in cervical cancer cells by inhibiting cell proliferative and invasive abilities. GTSE1 knockdown decreased the level of phosphorylated glycogen synthase kinase-3β (GSK-3β) and active β-catenin, resulted in inactivation of Wnt/β-catenin signaling. Suppression of GSK-3β remarkably abolished the GTSE1-knockdown-induced inhibitory effects on Wnt/β-catenin signaling. Suppression of Wnt/β-catenin signaling abolished the GTSE1-overexpression-induced oncogenic effects. Notably, GTSE1 knockdown impeded the in vivo tumorigenicity of cervical cancer cells. In short, this work demonstrates that GTSE1 is overexpressed in cervical cancer and GTSE1 suppression exerts a tumor-inhibiting role in cervical cancer by down-regulating Wnt/β-catenin signaling. Our work underlines a crucial relevance between GTSE1 and cervical cancer progression and suggests GTSE1 as a promising therapeutic target for cervical cancer.

RPL19 Is a Prognostic Biomarker and Promotes Tumor Progression in Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most common malignancies, and the therapeutic outcome remains undesirable due to its recurrence and metastasis. Gene dysregulation plays a pivotal role in the occurrence and progression of cancer, and the molecular mechanisms are largely unknown.

Methods

The differentially expressed genes of HCC screened from the GSE39791 dataset were used to conduct weighted gene co-expression network analysis. The selected hub genes were validated in The Cancer Genome Atlas (TCGA) database and 11 HCC datasets from the Gene Expression Omnibus (GEO) database. Then, a tissue microarray comprising 90 HCC specimens and 90 adjacent normal specimens was used to validate the hub genes. Moreover, the Hallmark, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were used to identify enriched pathways. Then, we conducted the immune infiltration analysis.

Results

A total of 17 co-expression modules were obtained by weighted gene co-expression network analysis. The green, blue, and purple modules were the most relevant to HCC samples. Four hub genes, RPL19, RPL35A, RPL27A, and RPS12, were identified. Interestingly, we found that all four genes were highly expressed in HCC and that their high expression was related to a poor prognosis by analyzing the TCGA and GEO databases. Furthermore, we investigated RPL19 in HCC tissue microarrays and demonstrated that RPL19 was overexpressed in tumor tissues compared with non-tumor tissues (p = 0.016). Moreover, overexpression of RPL19 predicted a poor prognosis in hepatocellular carcinoma (p < 0.0007). Then, enrichment analysis revealed that cell cycle pathways were significantly enriched, and bile acid metabolism-related pathways were significantly down-regulated when RPL19 was highly expressed. Furthermore, immune infiltration analysis showed that immune response was suppressed.

Conclusion

Our study demonstrates that RPL19 may play an important role in promoting tumor progression and is correlated with a poor prognosis in HCC. RPL19 may serve as a promising biomarker and therapeutic target for the precise diagnosis and treatment of HCC in the future.

Expression of DEP Domain-Containing 1B in Canine Lymphoma and Other Types of Canine Tumours

Canine lymphoma is the most common haematological malignancy in dogs and is typically treated with multidrug chemotherapy. Most cases are at risk of relapse after several courses of chemotherapy and the oncogenic mechanism remains unknown. This study was aimed at identifying genes expressed in canine lymphoma by cDNA microarray. We found elevated expression of Dishevelled, EGL-10 and pleckstrin (DEP) domain-containing 1B (DEPDC1B) in canine lymphoma cells compared with cells and tissues from healthy dogs. Canine DEPDC1B protein was detected in 13 of 41 lymphoma specimens by immunohistochemistry, but was not detected in lymph nodes from normal dogs. Immunoreactive DEPDC1B protein was also detected in several other types of canine tumour. This is the first report documenting the association of DEPDC1B with canine cancer and the results suggest that DEPDC1B might serve as a potential marker or therapeutic target for canine malignancies.

Integrative analysis identifies key mRNA biomarkers for diagnosis, prognosis, and therapeutic targets of HCV-associated hepatocellular carcinoma

Hepatitis C virus-associated HCC (HCV-HCC) is a prevalent malignancy worldwide and the molecular mechanisms are still elusive. Here, we screened 240 differentially expressed genes (DEGs) of HCV-HCC from Gene expression omnibus (GEO) and the Cancer Genome Atlas (TCGA), followed by weighted gene coexpression network analysis (WGCNA) to identify the most significant module correlated with the overall survival. 10 hub genes (CCNB1, AURKA, TOP2A, NEK2, CENPF, NUF2, CDKN3, PRC1, ASPM, RACGAP1) were identified by four approaches (Protein-protein interaction networks of the DEGs and of the significant module by WGCNA, and diagnostic and prognostic values), and their abnormal expressions, diagnostic values, and prognostic values were successfully verified. A four hub gene-based prognostic signature was built using the least absolute shrinkage and selection operator (LASSO) algorithm and a multivariate Cox regression model with the ICGC-LIRI-JP cohort (N =112). Kaplan-Meier survival plots (P = 0.0003) and Receiver Operating Characteristic curves (ROC = 0.778) demonstrated the excellent predictive potential for the prognosis of HCV-HCC. Additionally, upstream regulators including transcription factors and miRNAs of hub genes were predicted, and candidate drugs or herbs were identified. These findings provide a firm basis for the exploration of the molecular mechanism and further clinical biomarkers development of HCV-HCC.

Overexpression of CRABP2 inhibits dexamethasone-induced apoptosis in human osteoblast cells

Background

The purpose of the current study was to explore the role and underlying mechanism of cellular retinoic acid binding protein 2 (CRABP2) in dexamethasone (DEX)-induced apoptosis in human osteoblast cells.

Methods

GSE10311 was downloaded from the Gene Expression Omnibus (GEO) database to identify the differentially expressed genes (DEGs) by the limma/R package. Primary human osteoblast was isolated and treated with different concentration of DEX (0, 10^-8, 10^-7, 10^-6, 10^-5, and 10^-4 mol/L), and cell viability and flow cytometry were used to detect cell proliferation and apoptosis. A CRABP2 overexpression plasmid (oe-CRABP2) was used to overexpress CRABP2, and western blotting was conducted to detect protein expression.

Results

We found that CRABP2 was downregulated in the DEX-treated group. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that DEGs were associated with PI3K/Akt signaling pathway. DEX downregulated CRABP2 gene and protein expression, inhibited viability, and induced human osteoblast apoptosis. Overexpression of CRABP2 reversed DEX-induced apoptosis in human osteoblast. Moreover, overexpression of CRABP2 delayed the progression of DEX-induced osteonecrosis of the femoral head (ONFH) animal model.

Conclusion

In conclusion, CRABP2 is effective at inhibiting DEX-induced human osteoblast apoptosis and delayed ONFH progression.

Exploration and validation of a novel prognostic signature based on comprehensive bioinformatics analysis in hepatocellular carcinoma

The present study aimed to construct a novel signature for indicating the prognostic outcomes of hepatocellular carcinoma (HCC). Gene expression profiles were downloaded from Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. The prognosis-related genes with differential expression were identified with weighted gene co-expression network analysis (WGCNA), univariate analysis, the least absolute shrinkage and selection operator (LASSO). With the stepwise regression analysis, a risk score was constructed based on the expression levels of five genes: Risk score = (−0.7736* CCNB2) + (1.0083* DYNC1LI1) + (−0.6755* KIF11) + (0.9588* SPC25) + (1.5237* KIF18A), which can be applied as a signature for predicting the prognosis of HCC patients. The prediction capacity of the risk score for overall survival was validated with both TCGA and ICGC cohorts. The 1-, 3- and 5-year ROC curves were plotted, in which the AUC was 0.842, 0.726 and 0.699 in TCGA cohort and 0.734, 0.691 and 0.700 in ICGC cohort, respectively. Moreover, the expression levels of the five genes were determined in clinical tumor and normal specimens with immunohistochemistry. The novel signature has exhibited good prediction efficacy for the overall survival of HCC patients.

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.

CDCA4 suppresses epithelial-mesenchymal transtion (EMT) and metastasis in Non-small cell lung cancer through modulating autophagy

BACKGROUND

Cell division cycle associated 4 (CDCA4) has been reported to be engaged into the progression of several cancers. The function of CDCA4 in Non-small cell lung cancer (NSCLC) was unknown. We aimed to explore the critical role of CDCA4 in NSCLC.

METHODS

CDCA4 stably knocking down and overexpression cell lines were established and Western blotting assay was applied to measure relevant protein expression of Epithelial-Mesenchymal Transtion (EMT) and cell autophagy. Staining of acidic vacuoles, transmission electron microscopy and immunofluorescence staining were employed to detect autophagy. The ability of cells to migrate and invade were detected by Transwell migration and invasion assays. The interaction of CDCA4 with CARM1 was identified by immunoprecipitation and Western blotting analysis.

RESULTS

In the present study, it was found that inhibition of CDCA4 induced EMT, migration and invasion of NSCLC cells while inhibiting autophagy of NSCLC cells. Meanwhile, overexpression of CDCA4 in NSCLC cells showed the opposite function. More importantly, the inhibition of autophagy could promote the EMT, migration and invasion of NSCLC cells, which should be impaired via the activation of autophagy. In addition, CDCA4-inhibited EMT, migration and invasion could be partially aggravated by autophagy activator, rapamycin, and reversed by autophagy inhibitor, 3-MA. Correspondingly, the application of rapamycin or 3-MA to CDCA4 knockdown cells showed the opposite effects. Further investigation suggested that CDCA4 could interact with coactivator associated arginine methyltransferase 1 (CARM1). Autophagy was induced while cell migration and invasion were inhibited in CARM1 knockdown cells. CDCA4 could suppress the protein expression CARM1 and knocking down of CARM1 could alter cell autophagy, migratory and invasive abilities regulated by CDCA4.

CONCLUSION

All data indicated that CDCA4 inhibited the EMT, migration and invasion of NSCLC via interacting with CARM1 to modulate autophagy.

Identification and Analysis of Potential Key Genes Associated With Hepatocellular Carcinoma Based on Integrated Bioinformatics Methods

BACKGROUND

Hepatocellular carcinoma (HCC) is a type of primary liver tumor with poor prognosis and high mortality, and its molecular mechanism remains incompletely understood. This study aimed to use bioinformatics technology to identify differentially expressed genes (DEGs) in HCC pathogenesis, hoping to identify novel biomarkers or potential therapeutic targets for HCC research.

METHODS

The bioinformatics analysis of our research mostly involved the following two datasets: Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). First, we screened DEGs based on the R packages (limma and edgeR). Using the DAVID database, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were carried out. Next, the protein-protein interaction (PPI) network of the DEGs was built in the STRING database. Then, hub genes were screened through the cytoHubba plug-in, followed by verification using the GEPIA and Oncomine databases. We demonstrated differences in levels of the protein in hub genes using the Human Protein Atlas (HPA) database. Finally, the hub genes prognostic values were analyzed by the GEPIA database. Additionally, using the Comparative Toxicogenomics Database (CTD), we constructed the drug-gene interaction network.

RESULTS

We ended up with 763 DEGs, including 247 upregulated and 516 downregulated DEGs, that were mainly enriched in the epoxygenase P450 pathway, oxidation-reduction process, and metabolism-related pathways. Through the constructed PPI network, it can be concluded that the P53 signaling pathway and the cell cycle are the most obvious in module analysis. From the PPI, we filtered out eight hub genes, and these genes were significantly upregulated in HCC samples, findings consistent with the expression validation results. Additionally, survival analysis showed that high level gene expression of CDC20, CDK1, MAD2L1, BUB1, BUB1B, CCNB1, and CCNA2 were connected with the poor overall survival of HCC patients. Toxicogenomics analysis showed that only topotecan, oxaliplatin, and azathioprine could reduce the gene expression levels of all seven hub genes.

CONCLUSION

The present study screened out the key genes and pathways that were related to HCC pathogenesis, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of HCC.

SPC25 overexpression promotes tumor proliferation and is prognostic of poor survival in hepatocellular carcinoma

Background: The nuclear division cycle 80 (NDC80) complex assures proper chromosome segregation during the cell cycle progression. SPC25 is a crucial component of NDC80, and its role in hepatocellular carcinoma (HCC) has been explored recently. This study characterized the differential expression of SPC25 in HCC patients of different races and HBV infection status.

Methods: Expression patterns of SPC25 were evaluated in TCGA and Chinese HCC patients. Kaplan-Meier analysis was applied to examine the predictive value of SPC25. In vitro and in vivo functional assays were conducted to explore the role of SPC25 in HCC. Bioinformatics methods were applied to investigate the regulatory mechanisms of SPC25.

Findings: The mRNA levels of SPC25 were up-regulated in HCC. SPC25 has a significantly higher transcriptional level in Asian patients than Caucasian patients. SPC25 promoted HCC cell proliferation in vitro and tumor growth in vivo by accelerating the cell cycle. We identified transcription factors, miRNAs, and immune cells that may interact with SPC25.

Interpretation: The findings suggest that increased expression of SPC25 is associated with poor prognosis of HCC and enhances the proliferative capacity of HCC cells. SPC25 could serve as a valuable prognostic marker and a novel treatment target for HCC.