MicroRNA expression in cervical cancer: Novel diagnostic and prognostic biomarkers

Elastic Net-Based Identification of a Multigene Combination Predicting the Survival of Patients with Cervical Cancer

Background

The objective of the present study was to identify prognostication biomarkers in patients with cervical cancer.

Material/Methods

Survival related genes were identified in The Cancer Genome Atlas (TCGA) cervical cancer study, and they were included into an elastic net regularized Cox proportional hazards regression model (CoxPH). The genes that their coefficients that were not zero were combined to build a prognostication combination. The prognostication performance of the multigene combination was evaluated and validated using Kaplan-Meier curve and univariate and multivariable CoxPH model. Meanwhile, a nomogram was built to translate the multigene combination into clinical application.

Results

There were 37 survival related genes identified, 9 of which were integrated to build a multigene combination. The area under the curve (AUC) of receiver operating characteristic (ROC) curve at 1-year, 3-year, 5-year, and 7-year in the training set were 0.757, 0.744, 0.799, and 0.854, respectively, and the multigene combination could stratify patients into significantly different prognostic groups (hazard ratio [HR]=0.2223, log-rank P<0.0001). Meanwhile, the corresponding AUCs in the test set was 0.767, 0.721, 0.735, and 0.703, respectively, and the multigene combination could classify patients into different risk groups (HR=0.3793, log-rank P=0.0021). The multigene combination could stratify patients with early stage and advanced stage into significantly different survival groups in the training set and test set. The prognostication performance of the multigene combination was better compared with 3 existing prognostic signatures. Finally, a multigene containing nomogram was developed.

Conclusions

We developed a multigene combination which could be treated as an independent prognostic factor in cervical cancer and be translated into clinical application.

Faraday-Cage-Type Electrochemiluminescence Immunoassay: A Rise of Advanced Biosensing Strategy

Electrochemiluminescence immunoassays are usually carried out through "on-electrode" strategy, i.e., sandwich-type immunoassay format, the sensitivity of which is restricted by two key bottlenecks: (1) the number of signal labels is limited and (2) only a part of signal labels could participate in the electrode reaction. In this Perspective, we discuss the development of an "in-electrode" Faraday-cage-type concept-based immunocomplex immobilization strategy. The biggest difference from the traditional sandwich-type one is that the designed "in-electrode" Faraday-cage-type immunoassay uses a conductive two-dimensional (2-D) nanomaterial simultaneously coated with signal labels and a recognition component as the detection unit, which could directly overlap on the electrode surface. In such a case, electrons could flow freely from the electrode to the detection unit, the outer Helmholtz plane (OHP) of the electrode is extended, and thousands of signal labels coated on the 2-D nanomaterial are all electrochemically "effective." Thus, then, the above-mentioned bottlenecks obstructing the improvement of the sensitivity in sandwich-type immunoassay are eliminated, and as a result a much higher sensitivity of the Faraday-cage-type immunoassay can be obtained. And, the applications of the proposed versatile "in-electrode" Faraday-cage-type immunoassay have been explored in the detection of target polypeptide, protein, pathogen, and microRNA, with the detection sensitivity improved tens to hundreds of times. Finally, the outlook and challenges in the field are summarized. The rise of Faraday-cage-type electrochemiluminescence immunoassay (FCT-ECLIA)-based biosensing strategies opens new horizons for a wide range of early clinical identification and diagnostic applications.

Prediction of a miRNA-mRNA functional synergistic network for cervical squamous cell carcinoma

Cervical squamous cell carcinoma (CSCC) accounts for a significant proportion of cervical cancer; thus, there is a need for novel and noninvasive diagnostic biomarkers for this malignancy. In this study, we performed integrated analysis of a dataset from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) and differentially expressed miRNAs (DEmiRNAs) between CSCC, cervical intraepithelial neoplasia (CIN) and healthy control subjects. We further established protein-protein interaction and DEmiRNA-target gene interaction networks, and performed functional annotation of the target genes of DEmiRNAs. In total, we identified 1375 DEGs and 19 DEmiRNAs in CIN versus normal control, and 2235 DEGs and 33 DEmiRNAs in CSCC versus CIN by integrated analysis. Our protein-protein interaction network indicates that the common DEGs, Cyclin B/cyclin-dependent kinase 1 (CDK1), CCND1, ESR1 and Aurora kinase A (AURKA), are the top four hub genes. P53 and prostate cancer were identified as significantly enriched signaling pathways of common DEGs and DEmiRNA targets, respectively. We validated that expression levels of three DEGs (TYMS, SASH1 and CDK1) and one DEmiRNA of hsa-miR-99a were altered in blood samples of patients with CSCC. In conclusion, a total of four DEGs (TYMS, SASH1, CDK1 and AURKA) and two DEmiRNAs (hsa-miR-21 and hsa-miR-99a) may be involved in the pathogenesis of CIN and the progression of CIN into CSCC. Of these, TYMS is predicted to be regulated by hsa-miR-99a and SASH1 to be regulated by hsa-miR-21.

miR‑218 functions as a tumor suppressor gene in cervical cancer

Previous microRNA (miR) microarray analysis revealed that miR‑218 is downregulated in cervical cancer tissues. The present study aimed to further evaluate the expression of miR‑218 in cervical cancer specimens, determine the association between its expression with disease progression, and investigate the roles of miR‑218 in cervical cancer cells. Tissue specimens were obtained from 80 patients with cervical squamous cell carcinoma, 30 patients with high‑grade cervical intraepithelial neoplasia [(CIN) II/III] and 15 patients with low‑grade CIN (CINI); in addition, 60 plasma samples were obtained from patients with cervical cancer, and 15 normal cervical tissue specimens and 30 plasma samples were obtained from healthy women. These samples were used for analysis of miR‑218 expression via reverse transcription‑-quantitative PCR. In addition, tumor cells were transfected with miR‑218 mimics, human papillomavirus (HPV)16 E6/E7 small interfering RNA, or their respective negative controls to determine the viability, colony formation, migration and invasion of cells using MTT, colony formation, wound healing and Transwell assays, respectively. Target genes of miR‑218 were bioinformatically predicted and analyzed using Gene Ontology (GO) terms. The results revealed that miR‑218 was downregulated in the tumor tissues and plasma of patients with cervical cancer, with expression associated with the advanced clinicopathological characteristics of patients, including HPV positivity, tumor size, blood vessel invasion and lymph node metastasis. Furthermore, miR‑218 overexpression reduced tumor cell viability and xenograft growth, and suppressed tumor cell migration and invasion. HPV was detected in 75% of the 80 patients with cervical cancer, and HPV positivity was inversely associated with miR‑218 expression. In addition, bioinformatics analysis predicted that roundabout guidance receptor 1 (ROBO1) was a target gene of miR‑218; miR‑218 overexpression significantly reduced ROBO1 levels. Furthermore, GO analysis revealed that ROBO1 was involved in regulating cell proliferation, adhesion and migration, and the cell cycle. In conclusion, the findings of the present study suggested that miR‑218 may possess antitumor activities in cervical cancer.

One DNA circle capture probe with multiple target recognition domains for simultaneous electrochemical detection of miRNA-21 and miRNA-155

In this work, a novel DNA circle capture probe with multiple target recognition domains was designed to develop an electrochemical biosensor for ultrasensitive detection of microRNA-21 (miRNA-21) and miRNA-155 simultaneously. The DNA circle capture probe was anchored at the top of the tetrahedron DNA nanostructure (TDN) to simultaneously recognize miRNA-21 and miRNA-155 through multiple target recognition domains under the assistance of Helper strands, which could trigger mimetic proximity ligation assay (mPLA) for capturing the beacons ferrocene (Fc)-A1 and methylene blue (MB)-A2 to achieve multiple miRNAs detection. In this way, the local reaction concentration could be enhanced and avoid the interference of various capture probes compared with the traditional multiplexed electrochemical biosensor with the use of different capture probes, resulting in the significantly improvement of detection sensitivity. As a result, this proposed biosensor showed wide linearity ranging from 0.1 fM to 10 nM with detection limits of miRNA-21 and miRNA-155 as 18.9 aM and 39.6 aM respectively, which also could be applied in the simultaneously detection of miRNA-21 and miRNA-155 from cancer cell lysates. The present strategy paved a new path in the design of capture probes for achieving more efficient and sensitive multiple biomarkers detections and possessed the potential applications in clinical diagnostic of diseases.

Integrative transcriptome data mining for identification of core lncRNAs in breast cancer

Background

Cumulative evidence suggests that long non-coding RNAs (lncRNAs) play an important role in tumorigenesis. This study aims to identify lncRNAs that can serve as new biomarkers for breast cancer diagnosis or screening.

Methods

First, the linear fitting method was used to identify differentially expressed genes from the breast cancer RNA expression profiles in The Cancer Genome Atlas (TCGA). Next, the diagnostic value of all differentially expressed lncRNAs was evaluated using a receiver operating characteristic (ROC) curve. Then, the top ten lncRNAs with the highest diagnostic value were selected as core genes for clinical characteristics and prognosis analysis. Furthermore, core lncRNA-mRNA co-expression networks based on weighted gene co-expression network analysis (WGCNA) were constructed, and functional enrichment analysis was performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). The differential expression level and diagnostic value of core lncRNAs were further evaluated by using independent data set from Gene Expression Omnibus (GEO). Finally, the expression status and prognostic value of core lncRNAs in various tumors were analyzed based on Gene Expression Profiling Interactive Analysis (GEPIA).

Results

Seven core lncRNAs (LINC00478, PGM5-AS1, AL035610.1, MIR143HG, RP11-175K6.1, AC005550.4, and MIR497HG) have good single-factor diagnostic value for breast cancer. AC093850.2 has a prognostic value for breast cancer. AC005550.4 and MIR497HG can better distinguish breast cancer patients in early-stage from the advanced-stage. Low expression of MAGI2-AS3, LINC00478, AL035610.1, MIR143HG, and MIR145 may be associated with lymph node metastasis in breast cancer.

Conclusion

Our study provides candidate biomarkers for the diagnosis and prognosis of breast cancer, as well as a bioinformatics basis for the further elucidation of the molecular pathological mechanism of breast cancer.

GABRQ expression is a potential prognostic marker for patients with clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer. Novel biomarkers of ccRCC may provide crucial information on tumor features and prognosis. The present study aimed to determine whether the expression of γ-aminobutyric acid (GABA) A receptor subunit θ (GABRQ) could serve as a novel prognostic marker of ccRCC. GABA is the main inhibitory neurotransmitter in the brain that activates the receptor GABA_A, which is comprised of three subunit isoforms: GABRA3, GABRB3 and GABRQ. A recent study reported that GABRQ is involved in the initiation and progression of hepatocellular carcinoma; however, the role of GABRQ in ccRCC remains unknown. In the present study, clinical and transcriptomic data were obtained from cohorts of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). Differential GABRQ expression levels among early (TI and II), late (TIII and IV), nonmetastatic (M0) and metastatic (M1, primary tumor) stages of ccRCC samples were then identified. Furthermore, the use of GABRQ as a prognostic gene was analyzed using Uno's C-index based on the time-dependent area under the curve (AUC), the AUC of the receiver operating characteristic curve at 5 years, the Kaplan-Meier survival curve and multivariate analysis. The survival curve analysis revealed that low GABRQ mRNA expression was significantly associated with a poor prognosis of ccRCC (P<0.001 and P=0.0012 for TCGA and ICGC data, respectively). In addition, analyses of the C-index and AUC values further supported this discriminatory power. Furthermore, the prognostic value of GABRQ mRNA expression was confirmed by multivariate Cox regression analysis. Taken together, these results suggested that GABRQ mRNA expression may be considered as a novel prognostic biomarker of ccRCC.

An integrated approach for mining precise RNA-based cervical cancer staging biomarkers

Since international federation of gynecology and obstetrics (FIGO) staging is mainly based on clinical assessment, an integrated approach for mining RNA based biomarkers for understanding the molecular deregulation of signaling pathways and RNAs in cervical cancer was proposed in this study. Publicly available data were mined for identifying significant RNAs after patient staging. Significant miRNA families were identified from mRNA-miRNA and lncRNA-miRNA interaction network analyses followed by stage specific mRNA-miRNA-lncRNA association network generation. Integrated bioinformatic analyses of selected mRNAs and lncRNAs were performed. Results suggest that HBA1, HBA2, HBB, SLC2A1, CXCL10 (stage I), PKIA (stage III) and S100A7 (stage IV) were important. miRNA family enrichment of interacting miRNA partners of selected RNAs indicated the enrichment of let-7 family. Assembly of collagen fibrils and other multimeric structures_Homosapiens_R-HSA-2022090 in pathway analysis and progesterone_CTD_00006624 in DSigDB analysis were the most significant and SLC2A1, hsa-miR-188-3p, hsa-miR-378a-3p and hsa-miR-150-5p were selected as survival markers.

MiR-144-3p: a novel tumor suppressor targeting MAPK6 in cervical cancer

Cervical cancer is the third most common gynecologic cancer in the world. Exploration of the molecular mechanism underlying cervical cancer pathogenesis will provide new insights into the development of novel therapies. In this study, we were aimed to characterize a novel miRNA in cervical cancer tumorigenesis. First, we measured the expressional change of miR-144-3p in clinical tissues and cancer cells. Second, we employed cell proliferation, cell migration, and invasion assays to understand its functional role in cervical cancer. Then, we confirmed in vitro findings in xenograft cancer model. Last, we mapped out a downstream target of miR-144-3p and validated its functional role in cancer cells. In the results, miR-144-3p was found significantly downregulated in cervical cancer cells and tissues. Over-expressing miR-144-3p suppressed cancer cells growth and metastasis. Consistent with in vitro results, over-expressing miR-144-3p led to tumor growth inhibition in vivo. Further on, MAPK6 was identified as an endogenous target of miR-144-3p in cervical cancer. Knocking down MAPK6 inhibited cervical cancer cells proliferation, migration, and invasion potential. Our investigation was the first time to report miR-144-3p as a tumor suppressive miRNA in cervical cancer. It inhibited tumor growth by targeting MAKP6. The newly identified signalling axis may serve as novel therapeutic targets to manage cervical cancer.

Prognostic Role of TMED3 in Clear Cell Renal Cell Carcinoma: A Retrospective Multi-Cohort Analysis

Transmembrane p24 trafficking protein 3 (TMED3) is a metastatic suppressor in colon cancer and hepatocellular carcinoma. However, its function in the progression of clear cell renal cell carcinoma (ccRCC) is unknown. Here, we report that TMED3 could be a new prognostic marker for ccRCC. Patient data were extracted from cohorts in the Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC). Differential expression of TMED3 was observed between the low stage (Stage I and II) and high stage (Stage III and IV) patients in the TCGA and ICGC cohorts and between the low grade (Grade I and II) and high grade (Grade III and IV) patients in the TCGA cohort. Further, we evaluated TMED3 expression as a prognostic gene using Kaplan-Meier survival analysis, multivariate analysis, the time-dependent area under the curve (AUC) of Uno’s C-index, and the AUC of the receiver operating characteristics at 5 years. The Kaplan-Meier analysis revealed that TMED3 overexpression was associated with poor prognosis for ccRCC patients. Analysis of the C-indices and area under the receiver operating characteristic curve further supported this. Multivariate analysis confirmed the prognostic significance of TMED3 expression levels (P = 0.005 and 0.006 for TCGA and ICGC, respectively). Taken together, these findings demonstrate that TMED3 is a potential prognostic factor for ccRCC.

Establishing the prognostic value of platelet-to-lymphocyte ratio in cervical cancer: a systematic review and meta-analysis

Objective

The aim of this study was to conduct a meta-analysis to establish the prognostic value of platelet-to-lymphocyte ratio in cervical cancer.

Methods

We conducted a search in Medline and Embase datasets for articles published until May 1, 2018 to perform a meta-analysis to establish the prognostic value of platelet-to-lymphocyte ratio in cervical cancer. The primary survival outcomes were overall survival and progression-free survival. The pooled hazard ratios (HRs) and 95% confidence intervals (95% CIs) were combined to calculate overall effects. Cochran’s Q test and Higgins’ I2statistics were employed to estimate the heterogeneity. In addition, the subgroup analysis, sensitivity analysis, and meta-regression were performed to identify the source of heterogeneity. Egger’s linear regression test and Begg’s funnel plot and the trim and fill methods were employed to evaluate the publication bias.

Results

A total of 2616 patients from eight studies were enrolled in the meta-analysis. Significant association was observed between elevated platelet-to-lymphocyte ratio and a worse overall survival, with a combined HR of 1.49 (95% CI 1.24 to 1.79, I2=32.8%). Elevated platelet-to-lymphocyte ratio was significantly associated with a worse progression-free survival, with a combined HR of 1.65 (95% CI 1.17 to 2.33, I2= 49.4%). Subsequently, sensitivity analysis, subgroup analysis, and meta-regression model containing six predominant factors were applied to trace the origin of heterogeneity. However, no significant factors or studies were explored as the potential source of heterogeneity.

Conclusion

Elevated pre-treatment platelet-to-lymphocyte ratio may be an adverse prognostic factor for overall survival and progression-free survival in patients with cervical cancer. Further investigations are warranted to determine the exact mechanism by which platelet-to-lymphocyte ratio impacts survival outcomes in cervical cancer.

Recent Advances on the Molecular Mechanism of Cervical Carcinogenesis Based on Systems Biology Technologies

Cervical cancer is one of the common malignancies in women worldwide. Exploration of pathogenesis and molecular mechanism of cervical cancer is pivotal for development of effective treatment for this disease. Recently, systems biology approaches based on high-throughput technologies have been carried out to investigate the expression of some genes and proteins in genomics, transcriptomics, proteomics, and metabonomics of cervical cancer. Compared with traditional methods，systems biology technology has been shown to provide large of information regarding prognostic biomarkers and therapeutic targets for cervical cancer. These molecular signatures from system biology technology could be useful to understand the molecular mechanisms of cervical cancer development and progression, and help physicians to design targeted therapeutic strategies for patients with cervical cancer.

Identification of a 26-lncRNAs Risk Model for Predicting Overall Survival of Cervical Squamous Cell Carcinoma Based on Integrated Bioinformatics Analysis

As a common malignancy in women, cervical squamous cell carcinoma is a major cause of cancer-related mortality globally. Recent studies have demonstrated that long non-coding RNA (lncRNA) can function as potential biomarkers in cancer prognosis; however, little is known about its role in cervical cancer. In this study, we downloaded the gene expression profiles along with the clinical data of patients with cervical squamous cell carcinoma from The Cancer Genome Atlas. By applying bioinformatics analysis including random forest selection and Least Absolute Shrinkage and Selection Operator (LASSO) cox regression model along with 10-fold cross-validation, we constructed a 26-lncRNAs risk model that can be used to predict the overall survival of cervical squamous cell carcinoma. After that, Kaplan-Meier analysis combined with log-rank p test was applied to assess the predictive accuracy of the 26-lncRNAs risk model. Further analysis showed that the prognostic value of 26-lncRNAs risk model was independent of other clinicopathological factors. At last, lncRNAs in the model were put into gene ontology biological process enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways analysis, which suggested that these lncRNAs might contribute to cancer-associated processes such as cell cycle and apoptosis. This study indicated that lncRNAs signature could be a useful marker to predict the prognosis of cervical squamous cell carcinoma.

E2F7, EREG, miR-451a and miR-106b-5p are associated with the cervical cancer development

PURPOSE

We aimed to seek the crucial genes or microRNAs (miRNA) correlated with the cervical cancer development.

METHODS

The miRNA profiling GSE30656 and gene expression profiling GSE63514 were obtained from Gene Expression Omnibus database. Differentially expressed microRNAs (DEMiRs) and differentially expressed genes (DEGs) were screened. Then target genes of DEMiRs were obtained and matched with DEGs to obtain interaction pairs between DEMiRs and DEGs. Gene Ontology-biological process and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted for DEGs and DEMiRs in the DEMiRs-DEGs pairs. The DEMiRs-DEGs regulatory network, protein-protein interaction network and transcription factor (TF)-target regulatory network were constructed. Ultimately, long non-coding RNAs (lncRNAs) associated with DEMiRs were obtained, and then lncRNA-miRNA-target ceRNA network was established.

RESULTS

Total 18 DEMiRs and 620 DEGs were identified. DEMiRs were enriched in 35 KEGG pathways, such as PI3K-Akt signaling pathway (involving miR-451a). DEGs were enriched in various functions, such as DNA replication (involving E2F7) and angiogenesis (involving EREG). There were 120 nodes and 216 interaction pairs in the DEMIR-DEG regulatory network, and miR-106b-5p has the greatest degree. EREG and E2F7 were regulated by miR-451a and miR-148a-3p, respectively. Besides, E2F7 was identified in the TF-target regulatory network, regulating CDC6. There were 15 lncRNAs, 11 miRNAs and 90 DEGs in the ceRNA network. Specially, miR-148a-3p was interacted with lncRNA HOTAIR in the ceRNA network.

CONCLUSION

E2F7, EREG, miR-451a and miR-106b-5p were likely to be related to the cervical cancer development.

MicroRNA-218-5p inhibits cell growth and metastasis in cervical cancer via LYN/NF-κB signaling pathway

Background

We are committed to investigate miR-218-5 effects on the progression of cervical cancer (CC) cell and find out the molecular mechanism.

Methods

GSE9750 was obtained from GEO database and R Limma package was applied to filter out dysregulated genes. The pathways were enriched by GSEA software, ClusterProfiler and enrichplot packages to predict the function of DEGs. The binding sites of LYN were detected by miRanda and TargetScan. The miR2Disease database was used to find miRNAs related with CC. The expression of miR-218-5p and LYN were quantified by qRT-PCR and that of LYN protein was measured by western blot. The targeted relationships between miR-218-5p and LYN were verified by dual-luciferase reporter assay. Colony formation assays, wound healing, transwell invasion assay and flow cytometer analysis were performed to investigate the roles that miR-218-5p and LYN played in migration, invasion and death of cervical carcinoma. Xenografts established in nude mice were used to assess tumor growth in vivo.

Results

The highly expressed mRNA LYN was selected by microarray analysis in GSE9750. NF-κB signaling pathway was enriched base on GSEA results. The expression of miR-218-5p was lower but LYN was higher in CC primary tumors compared with normal control. In addition, miR-218-5p could regulate the expression of LYN in HeLa cells negatively. Overexpression of LYN could promote cell migration and invasion, but inhibit cell death in vitro, and also promote tumor formation in vivo via activating NF-κB signaling pathway which could be reversed by miR-218-5p.

Conclusions

MiR-218-5p suppressed the progression of CC via LYN/NF-κB signaling pathway.

Identification of differentially expressed miRNAs in early-stage cervical cancer with lymph node metastasis across The Cancer Genome Atlas datasets

Background and aim

Previous studies have suggested that lymph node metastasis (LNM) in early-stage cervical cancer (CESC) may affect the prognosis of patients and the outcomes of subsequent adjuvant therapy. However, research focused on miRNA expression in early-stage CESC patients with LNM remains limited. Therefore, it is necessary to identify prognostic miRNAs and determine their molecular mechanisms.

Methods

We evaluated the differentially expressed genes in early-stage CESC patients with LNM compared to patients without LNM and evaluated the prognostic significance of these differentially expressed genes by analyzing a public dataset from The Cancer Genome Atlas. Potential molecular mechanisms were investigated by gene ontology, the Kyoto Encyclopedia of Genes and Genomes, and protein–protein interaction network analyses.

Results

According to the The Cancer Genome Atlas data, hsa-miR-508, hsa-miR-509-2, and hsa-miR-526b expression levels were significantly lower in early-stage CESC patients with LNM than in patients without LNM. A multivariate analysis suggested that three miRNAs were prognostic factors for CESC (P<0.05). The target genes were identified to be involved in the MAPK, cAMP, PI3K/Akt, mTOR, and estrogen cancer signaling pathways. Protein–protein interaction network analysis showed that TP53, MMP1, NOTCH1, SMAD4, and NFKB1 were the most significant hub proteins.

Conclusion

Our results indicate that hsa-miR-508, hsa-miR-509-2, and hsa-miR-526b may be potential diagnostic biomarkers for early-stage CESC with LNM, and serve as prognostic predictors for patients with CESC.

Fifteen hub genes associated with progression and prognosis of clear cell renal cell carcinoma identified by coexpression analysis

Renal cell carcinoma (RCC) is the most common type of renal tumor, and the clear cell renal cell carcinoma (ccRCC) is the most frequent subtype. In this study, our aim is to identify potential biomarkers that could effectively predict the prognosis and progression of ccRCC. First, we used The Cancer Genome Atlas (TCGA) RNA-sequencing (RNA-seq) data of ccRCC to identify 2370 differentially expressed genes (DEGs). Second, the DEGs were used to construct a coexpression network by weighted gene coexpression network analysis (WGCNA). Moreover, we identified the yellow module, which was strongly related to the histologic grade and pathological stage of ccRCC. Then, the functional annotation of the yellow module and single-samples gene-set enrichment analysis of DEGs were performed and mainly enriched in cell cycle. Subsequently, 18 candidate hub genes were screened through WGCNA and protein-protein interaction (PPI) network analysis. After verification of TCGA's ccRCC data set, Gene Expression Omnibus (GEO) data set (GSE73731) and tissue validation, we finally identified 15 hub genes that can actually predict the progression of ccRCC. In addition, by using survival analysis, we found that patients of ccRCC with high expression of each hub gene were more likely to have poor prognosis than those with low expression. The receiver operating characteristic curve showed that each hub gene could effectively distinguish between localized and advanced ccRCC. In summary, our study indicates that 15 hub genes have great predictive value for the prognosis and progression of ccRCC, and may contribute to the exploration of the pathogenesis of ccRCC.