Silencing of CDCA5 inhibits cancer progression and serves as a prognostic biomarker for hepatocellular carcinoma

Key oncogenes and candidate drugs for hepatitis-B-driven hepatocellular carcinoma progression

BACKGROUND

This study aimed to uncover the key hepatitis-B (HB)-related liver cancer (LC) promoting genes, and clarity their interrelationships, enrichments, impacts on LC immune infiltration, and potential drugs targeting these genes.

METHODS

The LC-survival associated genes were acquired from the LIHC samples of the TCGA-database; and HB related genes from the DisGeNET database. The intersection was used to screen the key genes. Using the 8 HB-LC genes, we constructed prognostic models for survival prediction of HBV positive patients with LIHC and performed enrichment analysis, interaction analysis, immune infiltration analysis, and potential drug digging from the GTRP and GDSC databases.

RESULTS

In the core intersection of different sets. Based on these genes, prognostic cox regression models for OS and DFS were constructed. Overall, HB-LC genes were significantly negatively correlated with Th17, MAIT, monocytes, and CD4 Naive cells, while they were positively correlated with B cells, nTreg cells, and Tr1 cells. Among 8 genes, MKI67, EZH2, and CDCA5 were hub ones. Finally, 7 drugs target at least three HB-LC genes and can be used as novel drugs.

CONCLUSIONS

Together, eight key HB-LC genes play important cancer-promoting roles in LC, which may be the molecular mechanism by which HBV drives the development of LC.

Shared and specific competing endogenous RNAs network mining in four digestive system tumors

Background

Digestive system malignancies, including esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), liver hepatocellular carcinoma (LIHC), and colon adenocarcinoma (COAD), pose significant global health challenges. Identifying shared and distinct regulatory mechanisms across these cancers can lead to improved therapies. This study aims to construct and compare competing endogenous RNA (ceRNA) networks across ESCA, STAD, LIHC, and COAD to identify RNA biomarkers that could serve as precision therapeutic targets to enhance clinical outcomes and advance personalized cancer care.

Methods

Clinical and transcriptomic data from The Cancer Genome Atlas (TCGA) were analyzed to predict differentially expressed RNAs using the edgeR package. The ceRNA networks were constructed using the miRcode and ENCORI databases. Functional enrichment analysis and prognostic RNA screening were performed with ConsensusPathDB and univariate Cox regression analysis.

Results

we identified 6, 88, 55, and 41 RNA biomarkers in ESCA, STAD, LIHC, and COAD, respectively. Network analysis revealed shared and specific elements, with shared nodes enriched in cell cycle and mitotic processes. Several biomarkers, including HMGB3 and RGS16 (ESCA), COL4A1 and COL6A3 (STAD), CDCA5 and CDCA8 (LIHC), and LIMK1 and OSBPL3 (COAD), were consistent with prior studies, while novel biomarkers, such as C3P1 (ESCA), P2RY6 (STAD), and N4BP2L1 and PPP1R3B (LIHC), were discovered. Based on RNA correlation analysis, 1, 23, and 2 potential ceRNA regulatory axes were identified in STAD (PVT1/miR-490-3p/HMGA2), LIHC (DLX6-AS1/miR-139-5p/TOP2A, etc.), and COAD (STRCP1 & LINC00488/miR-142-3p/GAB1), respectively.

Conclusions

This study advances the understanding of ceRNA networks in digestive cancers, highlighting RNA biomarkers with potential as therapeutic targets for personalized treatment strategies.

Finding key genes (UBE2T, KIF4A, CDCA3, and CDCA5) co-expressed in hepatitis, cirrhosis and hepatocellular carcinoma based on multiple bioinformatics techniques

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Hepatitis B virus (HBV) is one of the major causes of liver cirrhosis (LC) and HCC. Therefore, the discovery of common markers for hepatitis B or LC and HCC is crucial for the prevention of HCC.

METHODS

Expressed genes for to chronic active hepaititis B (CAH-B), LC and HCC were obtained from the GEO and TCGA databases, and co-expressed genes were screened using Protein-protein interaction (PPI) networks, least absolute shrinkage and selection operator (LASSO), random forest (RF) and support vector machine - recursive feature elimination (SVM-RFE). The prognostic value of genes was assessed using Kaplan-Meier (KM) survival curves. Columnar line plots, calibration curves and receiver operating characteristic (ROC) curves of individual genes were used for evaluation. Validation was performed using GEO datasets. The association of these key genes with HCC clinical features was explored using the UALCAN database ( https://ualcan.path.uab.edu/index.html ).

RESULTS

Based on WGCNA analysis and TCGA database, the co-expressed genes (565) were screened. Moreover, the five algorithms of MCODE (ClusteringCoefficient, MCC, Degree, MNC, and DMNC) was used to select one of the most important and most closely linked clusters (the top 50 genes ranked). Using, LASSO regression model, RF model and SVM-RFE model, four key genes (UBE2T, KIF4A, CDCA3, and CDCA5) were identified for subsequent research analysis. These 4 genes were highly expressed and associated with poor prognosis and clinical features in HCC patients.

CONCLUSION

These four key genes (UBE2T, KIF4A, CDCA3, and CDCA5) may be common biomarkers for CAH-B and HCC or LC and HCC, promising to advance our understanding of the molecular basis of CAH-B/LC/HCC progression.

Mechanistic Insights into 1,2-bis(2,4,6-tribromophenoxy)ethane-Induced Male Reproductive Toxicity in Zebrafish

The novel brominated flame retardant, 1,2-bis(2,4,6-tribromophenoxy)ethane (BTBPE), has increasingly been detected in environmental and biota samples. However, limited information is available regarding its toxicity, especially at environmentally relevant concentrations. In the present study, adult male zebrafish were exposed to varying concentrations of BTBPE (0, 0.01, 0.1, 1, and 10 μg/L) for 28 days. The results demonstrated underperformance in mating behavior and reproductive success of male zebrafish when paired with unexposed females. Additionally, a decline in sperm quality was confirmed in BTBPE-exposed male zebrafish, characterized by decreased total motility, decreased progressive motility, and increased morphological malformations. To elucidate the underlying mechanism, an integrated proteomic and phosphoproteomic analysis was performed, revealing a predominant impact on mitochondrial functions at the protein level and a universal response across different cellular compartments at the phosphorylation level. Ultrastructural damage, increased expression of apoptosis-inducing factor, and disordered respiratory chain confirmed the involvement of mitochondrial impairment in zebrafish testes. These findings not only provide valuable insights for future evaluations of the potential risks posed by BTBPE and similar chemicals but also underscore the need for further research into the impact of mitochondrial dysfunction on reproductive health.

Functional Heterogeneity of Bone Marrow Mesenchymal Stem Cell Subpopulations in Physiology and Pathology

Bone marrow mesenchymal stem cells (BMSCs) are multi-potent cell populations and are capable of maintaining bone and body homeostasis. The stemness and potential therapeutic effect of BMSCs have been explored extensively in recent years. However, diverse cell surface antigens and complex gene expression of BMSCs have indicated that BMSCs represent heterogeneous populations, and the natural characteristics of BMSCs make it difficult to identify the specific subpopulations in pathological processes which are often obscured by bulk analysis of the total BMSCs. Meanwhile, the therapeutic effect of total BMSCs is often less effective partly due to their heterogeneity. Therefore, understanding the functional heterogeneity of the BMSC subpopulations under different physiological and pathological conditions could have major ramifications for global health. Here, we summarize the recent progress of functional heterogeneity of BMSC subpopulations in physiology and pathology. Targeting tissue-resident single BMSC subpopulation offers a potentially innovative therapeutic strategy and improves BMSC effectiveness in clinical application.

Single-Cell RNA Sequencing of Bone Marrow Mesenchymal Stem Cells from the Elderly People

Background and Objectives

Bone marrow mesenchymal stem cells (BMSCs) show considerable promise in regenerative medicine. Many studies demonstrated that BMSCs cultured in vitro were highly heterogeneous and composed of diverse cell subpopulations, which may be the basis of their multiple biological characteristics. However, the exact cell subpopulations that make up BMSCs are still unknown.

Methods and Results

In this study, we used single-cell RNA sequencing (scRNA-Seq) to divide 6,514 BMSCs into three clusters. The number and corresponding proportion of cells in clusters 1 to 3 were 3,766 (57.81%), 1,720 (26.40%), and 1,028 (15.78%). The gene expression profile and function of the cells in the same cluster were similar. The vast majority of cells expressed the markers defining BMSCs by flow cytometry and gene expression analysis. Each cluster had at least 20 differentially expressed genes (DEGs). We conducted Gene Ontology enrichment analysis on the top 20 DEGs of each cluster and found that the three clusters had different functions, which were related to self-renewal, multilineage differentiation and cytokine secretion, respectively. In addition, the function of the top 20 DEGs of each cluster was checked by the National Center for Biotechnology Information gene database to further verify our hypothesis.

Conclusions

This study indicated that scRNA-Seq can be used to divide BMSCs into different subpopulations, demonstrating the heterogeneity of BMSCs.

Gene Expression Characteristics of Liver Tissue Reveal the Underlying Pathogenesis of Hepatocellular Carcinoma

Background

Hepatocellular carcinoma (HCC) is high-mortality primary liver cancer and the most common malignant tumor in the world. This study is based on a hepatocellular carcinoma-related dysfunction module designed to explore the dysregulation of genes in liver cancer tissue.

Methods

By downloading the relevant data on the GEO database, we performed a differential analysis of healthy liver tissue and liver cancer tissues as well as healthy liver tissue and hepatocellular carcinoma tissue and then obtained two sets of differential genes and combined them. We performed a cointerpretation analysis of these differential genes and constructed related functional disorder modules. A hypergeometric test was performed to calculate the potential regulatory effects of multiple factors on the module, and a series of ncRNA and TF regulators were identified. We obtained a total of 4479 differentially expressed genes in hepatocellular carcinoma, and these genes were clustered into ten hepatocellular carcinoma-related functional interpretation disorder modules.

Results

Enrichment analysis revealed that these modular genes are mainly involved in signal transduction including cell cycle, TGF-beta signal transduction, and p53 signal transduction. Depending on the predictive analysis of multidimensional regulators, 323 ncRNAs and 52 TF-mediated hepatocellular carcinoma-related dysregulation modules were found to regulate disease progression.

Conclusions

Based on a series of investigations, it was found that miR-30b-5p may participate in the peroxisome signal transduction by downregulating ABCD3-mediated module 1, thereby promoting the development and progression of hepatocellular carcinoma. Our research results not only provide a theoretical basis for biologists to study hepatocellular carcinoma further but also offer new methods and new ideas for the personalized care and treatment of hepatocellular carcinoma.

AKT3-mediated IWS1 phosphorylation promotes the proliferation of EGFR-mutant lung adenocarcinomas through cell cycle-regulated U2AF2 RNA splicing

AKT-phosphorylated IWS1 regulates alternative RNA splicing via a pathway that is active in lung cancer. RNA-seq studies in lung adenocarcinoma cells lacking phosphorylated IWS1, identified a exon 2-deficient U2AF2 splice variant. Here, we show that exon 2 inclusion in the U2AF2 mRNA is a cell cycle-dependent process that is regulated by LEDGF/SRSF1 splicing complexes, whose assembly is controlled by the IWS1 phosphorylation-dependent deposition of histone H3K36me3 marks in the body of target genes. The exon 2-deficient U2AF2 mRNA encodes a Serine-Arginine-Rich (RS) domain-deficient U2AF65, which is defective in CDCA5 pre-mRNA processing. This results in downregulation of the CDCA5-encoded protein Sororin, a phosphorylation target and regulator of ERK, G2/M arrest and impaired cell proliferation and tumor growth. Analysis of human lung adenocarcinomas, confirmed activation of the pathway in EGFR-mutant tumors and showed that pathway activity correlates with tumor stage, histologic grade, metastasis, relapse after treatment, and poor prognosis.

Identification and analysis of genes associated with epithelial ovarian cancer by integrated bioinformatics methods

Background

Though considerable efforts have been made to improve the treatment of epithelial ovarian cancer (EOC), the prognosis of patients has remained poor. Identifying differentially expressed genes (DEGs) involved in EOC progression and exploiting them as novel biomarkers or therapeutic targets is of great value.

Methods

Overlapping DEGs were screened out from three independent gene expression omnibus (GEO) datasets and were subjected to Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analyses. The protein-protein interactions (PPI) network of DEGs was constructed based on the STRING database. The expression of hub genes was validated in GEPIA and GEO. The relationship of hub genes expression with tumor stage and overall survival and progression-free survival of EOC patients was investigated using the cancer genome atlas data.

Results

A total of 306 DEGs were identified, including 265 up-regulated and 41 down-regulated. Through PPI network analysis, the top 20 genes were screened out, among which 4 hub genes, which were not researched in depth so far, were selected after literature retrieval, including CDC45, CDCA5, KIF4A, ESPL1. The four genes were up-regulated in EOC tissues compared with normal tissues, but their expression decreased gradually with the continuous progression of EOC. Survival curves illustrated that patients with a lower level of CDCA5 and ESPL1 had better overall survival and progression-free survival statistically.

Conclusion

Two hub genes, CDCA5 and ESPL1, identified as probably playing tumor-promotive roles, have great potential to be utilized as novel therapeutic targets for EOC treatment.

New Perspectives in Different Gene Expression Profiles for Early and Locally Advanced Non-Small Cell Lung Cancer Stem Cells

INTRODUCTION

Lung cancer is one of the most common cancers in the world, causing over 1.7 million deaths in 2018. Thus far, no effective treatments against lung cancer for advanced stages have been found. For early stages, although surgery is considered the gold standard treatment, 30-55% of patients develop recurrence within the first 5 years of surgery. Our aim is to assess whether cancer stem cells (CSC) display overexpression of a pool of genes that were previously identified for adenocarcinoma recurrence in patients with early and locally advanced stages of non-small cell lung cancer (NSCLC).

METHODS

This cross-sectional study was carried out by harvesting surgical tumor specimens obtained from patients harboring early (I-II) and locally advanced (IIIA) stages of NSCLC. For each patient, cell sorting was performed to identify and isolate the ALDHhigh (CSC) and ALDHlow (cancer cells) populations. The mRNA expressions of 31 recurrence-related genes (target genes) in both ALDHhigh and ALDHlow populations were then assessed and compared.

RESULTS

Surgical specimens were obtained from 22 patients harboring NSCLC. Sixteen (51.6%) out of 31 recurrence-related genes were significantly overexpressed in ALDHhigh cells in the early stages and 9 (29.0%) were overexpressed in the locally advanced stages of NSCLC. Overall, the relative mRNA expressions for these recurrence-related genes were higher in early-stage patients. The average fold change, considering all 31 recurrence-related genes together, was 4.5 (95% CI = 3.1-6.3) in early-stage patients and 1.6 (95% CI = 1.2-2.2) in locally advanced-stage patients.

CONCLUSIONS

Our study represents the first attempt toward identifying genes associated with recurrence that are overexpressed in cancer stem cells in patients with early and locally advanced stages of NSCLC. This finding may contribute to the identification of new target therapies tailored for NSCLC stages.

Comprehensive Analysis of CDCAs Methylation and Immune Infiltrates in Hepatocellular Carcinoma

Background

As essential components of cycle growth, the cell division cycle-associated family genes (CDCAs) have crucial roles in tumor development and progression, especially in hepatocellular carcinoma (HCC). However, due to the tumor heterogeneity of HCC, little is known about the methylation variability of CDCAs in mediating phenotypic changes (e.g., immune infiltrates) in HCC. Presently, we aim to comprehensively explore the expression and prognosis of CDCAs methylation with regard to immune infiltrates of HCC.

Methods

We first identified the correlating differentially expressed genes (co-DEGs) among 19 different types of cancer cohorts (a total of 7,783 patients) and then constructed the weighted gene co-expressed and co-methylated networks. Applying the clustering analysis, significant modules of DEGs including CDCAs were selected and their functional bioinformatics analyses were performed. Besides, using DiseaseMeth and TIMER, the correlation between the methylation levels of CDCAs and tumor immune infiltrates was also analyzed. In final, to assess the influence of CDCAs methylation on clinical prognosis, Kaplan-Meier and Cox regression analysis were carried out.

Result

A total of 473 co-DEGs are successfully identified, while seven genes of CDCAs (CDCA1–3 and CDCA5–8) have significant over-expression in HCC. Co-expressed and co-methylated networks reveal the strong positive correlations in mRNA expression and methylation levels of CDCAs. Besides, the biological enrichment analysis of CDCAs demonstrates that they are significantly related to the immune function regulation of infiltrating immune cells in HCC. Also, the methylation analysis of CDCAs depicts the strong association with the tumor immunogenicity, i.e., low-methylation of CDCA1, CDCA2, and CDCA8 dramatically reduced the immune infiltrate levels of T cells and cytotoxic lymphocytes. Additionally, CDCA1–6 and CDCA8 with low-methylation levels significantly deteriorate the overall survival of patients in HCC.

Conclusions

The co-expressed and co-methylated gene networks of CDCAs show a powerful association with immune function regulation. And the methylation levels of CDCAs suggesting the prognostic value and infiltrating immune differences could be a novel and predictive biomarker for the response of immunotherapy.

Microarray Data Mining and Preliminary Bioinformatics Analysis of Hepatitis D Virus-Associated Hepatocellular Carcinoma

Several studies have demonstrated that chronic hepatitis delta virus (HDV) infection is associated with a worsening of hepatitis B virus (HBV) infection and increased risk of hepatocellular carcinoma (HCC). However, there is limited data on the role of HDV in the oncogenesis of HCC. This study is aimed at assessing the potential mechanisms of HDV-associated hepatocarcinogenesis, especially to screen and identify key genes and pathways possibly involved in the pathogenesis of HCC. We selected three microarray datasets: GSE55092 contains 39 cancer specimens and 81 paracancer specimens from 11 HBV-associated HCC patients, GSE98383 contains 11 cancer specimens and 24 paracancer specimens from 5 HDV-associated HCC patients, and 371 HCC patients with the RNA-sequencing data combined with their clinical data from the Cancer Genome Atlas (TCGA). Afterwards, 948 differentially expressed genes (DEGs) closely related to HDV-associated HCC were obtained using the R package and filtering with a Venn diagram. We then performed gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis to determine the biological processes (BP), cellular component (CC), molecular function (MF), and KEGG signaling pathways most enriched for DEGs. Additionally, we performed Weighted Gene Coexpression Network Analysis (WGCNA) and protein-to-protein interaction (PPI) network construction with 948 DEGs, from which one module was identified by WGCNA and three modules were identified by the PPI network. Subsequently, we validated the expression of 52 hub genes from the PPI network with an independent set of HCC dataset stored in the Gene Expression Profiling Interactive Analysis (GEPIA) database. Finally, seven potential key genes were identified by intersecting with key modules from WGCNA, including 3 reported genes, namely, CDCA5, CENPH, and MCM7, and 4 novel genes, namely, CDC6, CDC45, CDCA8, and MCM4, which are associated with nucleoplasm, cell cycle, DNA replication, and mitotic cell cycle. The CDCA8 and stage of HCC were the independent factors associated with overall survival of HDV-associated HCC. All the related findings of these genes can help gain a better understanding of the role of HDV in the underlying mechanism of HCC carcinogenesis.

CDCA5 promotes the progression of prostate cancer by affecting the ERK signalling pathway

Cell division cycle-associated 5 (CDCA5) can regulate cell cycle-related proteins to promote the proliferation of cancer cells. The purpose of the present study was to investigate the expression level of CDCA5 in prostate cancer (PCa) and its effect on PCa progression. The signalling pathway by which CDCA5 functions through was also attempted to elucidate. Clinical specimens of PCa patients were collected from the Second Hospital of Tianjin Medical University. The expression level of CDCA5 in cancer tissues and paracancerous tissues from PCa patients was detected by RT-qPCR analysis and IHC. The relationship between the expression level of CDCA5 and the survival rate of PCa patients was analysed using TCGA database. Two stable cell lines (C4-2 and PC-3) with CDCA5 knockdown were established, and the effects of CDCA5 on PCa cell proliferation were detected by MTT and colony formation assays. Flow cytometry was performed to detect the effect of CDCA5 on the PCa cell division cycle, and western blot analysis was used to determine changes in ERK phosphorylation levels after CDCA5 knockdown. The effect of CDCA5 expression on prostate tumour growth was assessed using a mouse xenograft model. The results revealed that the mRNA and protein expression levels of CDCA5 were significantly higher in PCa tissues than in paracancerous tissues. High CDCA5 expression was associated with the prognosis of patients with PCa. CDCA5 expression knockdown significantly reduced the number of PCa cells in mitoses and inhibited their proliferation in vitro and in vivo. When CDCA5 was knocked down, the phosphorylation level of ERK was also reduced. Collectively, CDCA5 was upregulated and affected the prognosis of patients with PCa. Decreased CDCA5 expression inhibited PCa cell proliferation by inhibiting the ERK signalling pathway. Thus, CDCA5 may be a potential therapeutic target for PCa.

Cyclin-Dependent Kinase 1 (CDK1) is Co-Expressed with CDCA5: Their Functions in Gastric Cancer Cell Line MGC-803

Background

Gastric cancer (GC) is a worldwide malignancy and the molecular mechanism of the GC carcinogenesis has not been fully elucidated. Our previous study suggested CDCA5 played a role in GC development via regulating cell proliferation, migration, and apoptosis in GC cells.

Material/Methods

Here, we first carried out bioinformatics analysis and found cyclin-dependent kinase 1 (CDK1) was possibly associated with CDCA5 using STRING. Then, the expression levels of CDK1 and CDCA5 in cancer tissues were estimated through Oncomine and The Cancer Genome Atlas (TCGA) database. After that, functional experiments were exerted to detect the association of CDK1 and CDCA5. Finally, cell proliferation assay, colon formation assay, cell scratch assay, transwell migration and invasion assays were applied to explore the roles of CDK1 and CDCA5 in GC cells MGC-803.

Results

CDK1 and CDCA5 were both upregulated and co-expressed in GC tissues. The expression of CDK1 and CDCA5 in MGC-803 was positively related. CDK1 or CDCA5 inhibition can suppress the proliferation, colon formation, migration, and invasion abilities of GC cells.

Conclusions

Co-expression of CDK1 and CDCA5 might confer cell proliferation, migration, and invasion abilities in GC cells, and this can provide some clues for further therapies of gastric tumors.

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

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

Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis

Lung adenocarcinoma is the most frequently diagnosed subtype of nonsmall cell lung cancer. The molecular mechanisms of the initiation and progression of lung adenocarcinoma remain to be further determined. This study aimed to screen genes related to the progression of lung adenocarcinoma. By weighted gene coexpression network analysis (WGCNA), we constructed a free-scale gene coexpression network to evaluate the correlations between multiple gene sets and patients' clinical traits, then further identify predictive biomarkers. GSE11969 was obtained from the Gene Expression Omnibus (GEO) database which contained the gene expression data of 90 lung adenocarcinoma patients. Data of the Cancer Genome Atlas (TCGA) were employed as the validation cohort. After the average linkage hierarchical clustering, a total of 9 modules were generated. In the clinical significant module (R = 0.44, P < 0.0001), we identified 29 network hub genes. Subsequent verification in the TCGA database showed that 11 hub genes (ANLN, CDCA5, FLJ21924, LMNB1, MAD2L1, RACGAP1, RFC4, SNRPD1, TOP2A, TTK, and ZWINT) were significantly associated with poor survival data of lung adenocarcinomas. Besides, the results of receiver operating characteristic curves indicated that the mRNA levels of this group of genes exhibited high specificity and sensitivity to distinguish malignant lesions from nonmalignant tissues. Apart from mRNA levels, we found that the protein abundances of these 11 genes were remarkably upregulated in lung adenocarcinomas compared with normal tissues. In conclusion, by the WGCNA method, a panel of 11 genes were identified as predictive biomarkers for tumorigenesis and poor prognosis of lung adenocarcinomas.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Co-expression network analysis identified candidate biomarkers in association with progression and prognosis of breast cancer

PURPOSE

Breast cancer is one of the most common malignancies among females, and its prognosis is affected by a complex network of gene interactions. Weighted gene co-expression network analysis was used to construct free-scale gene co-expression networks and to identify potential biomarkers for breast cancer progression.

METHODS

The gene expression profiles of GSE42568 were downloaded from the Gene Expression Omnibus database. RNA-sequencing data and clinical information of breast cancer from TCGA were used for validation.

RESULTS

A total of ten modules were established by the average linkage hierarchical clustering. We identified 58 network hub genes in the significant module (R2 = 0.44) and 6 hub genes (AGO2, CDC20, CDCA5, MCM10, MYBL2, and TTK), which were significantly correlated with prognosis. Receiver-operating characteristic curve validated that the mRNA levels of these six genes exhibited excellent diagnostic efficiency in the test data set of GSE42568. RNA-sequencing data from TCGA showed that the expression levels of these six genes were higher in triple-negative tumors. One-way ANOVA suggested that these six genes were upregulated at more advanced stages. The results of independent sample t test indicated that MCM10 and TTK were associated with tumor size, and that AGO2, CDC20, CDCA5, MCM10, and MYBL2 were overexpressed in lymph-node positive breast cancer.

CONCLUSIONS

AGO2, CDC20, CDCA5, MCM10, MYBL2, and TTK were identified as candidate biomarkers for further basic and clinical research on breast cancer based on co-expression analysis.

Identification of Biomarkers for Controlling Cancer Stem Cell Characteristics in Bladder Cancer by Network Analysis of Transcriptome Data Stemness Indices

Background: Stem cells characterized by self-renewal and therapeutic resistance play crucial roles in bladder cancer (BLCA). However, the genes modulating the maintenance and proliferation of BLCA stem cells are still unclear. In this study, we aimed to characterize the expression of stem cell-related genes in BLCA.

Methods: The mRNA expression-based stemness index (mRNAsi) of The Cancer Genome Atlas (TCGA) was evaluated and corrected by tumor purity. Corrected mRNAsi were further analyzed with regard to muscle-invasive bladder cancer molecular subtypes, survival analysis, pathological staging characteristics, and outcomes after primary treatment. Next, weighted gene co-expression network analysis was used to find modules of interest and key genes. Functional enrichment analysis was performed to functionally annotate the modules and key genes. The expression levels of key genes in all cancers were validated using Oncomine and Gene Expression Omnibus (GEO) database containing molecular subtypes in BLCA. Protein interaction networks were used to identify upstream genes, and the relationships between genes were analyzed at the protein and transcription levels.

Findings: mRNAsi was significantly upregulated in cancer tissues. Corrected mRNAsi in BLCA increased as tumor stage increased, with T3 having the highest stem cell characteristics. Lower corrected mRNAsi scores had better overall survival and treatment outcome. The modules of interest and key genes were determined based on topological overlap measurement clustering results and the inclusion criteria. For 13 key genes (AURKA, BUB1B, CDCA5, CDCA8, KIF11, KIF18B, KIF2C, KIFC1, KPNA2, NCAPG, NEK2, NUSAP1, and RACGAP1), enriched gene ontology terms related to cell proliferation (e.g., mitotic nuclear division, spindle, and microtubule binding) were determined. Their expression did not differ according to the pathological stages of BLCA, and these genes were clearly overexpressed in many types of cancers. In GEO database, the expression levels of 13 key genes were higher in basal subtype with the highest stem cell characteristics than in luminal and its subtypes. AURKB and PLK1 may be regulated upstream of other key genes, and the key genes were found to be strongly correlated with each other and with upstream genes.

Interpretation: The 13 key genes identified in this study were found to play important roles in the maintenance of BLCA stem cells. Controlling the upstream genes AURKB and PLK1 may have applications in the treatment of BLCA. These genes may act as therapeutic targets for inhibiting the stemness characteristics of BLCA.