Prognostic Biomarker For Cervical Cancer Research Articles

Elevated expression of protein-L-isoaspartate O-methyltransferase-1 (PCMT1) in cervical cancer.

BackgroundProtein-L-isoaspartate O-methyltransferase-1 (PCMT1) is a protein carboxyl methyltransferase enzyme, which has been found to play roles in cancers. However, no clinical information about the correlation between cervical cancer and PCMT1 expression has been reported.MethodsWe used immunohistochemistry (IHC) to characterize the protein level of PCMT1 in human cervical intraepithelial neoplasia and cervical cancer specimens. The mRNA expression profile of PCMT1 in cervical cancer was also analyzed by using Gene Expression Omnibus (GEO) databases. The prognostic value of PCMT1 in patients with cervical cancer was evaluated by using the Kaplan-Meier plotter. Gene set enrichment analysis (GSEA) was conducted by using The Cancer Genome Atlas (TCGA) cervical cancer dataset.ResultsThe protein level of PCMT1 was increased in cervical high-grade squamous intraepithelial lesion (HSIL) (7.40±0.42) and cervical cancer tissues (10.70±0.54), compared to normal cervix (5.00±0.86) and low-grade squamous intraepithelial lesion (LSIL) (6.22±0.57) (P<0.05). the immunoreactivity score (IRS) of PCMT1 was also higher in cervical cancer tissues than in paired adjacent non-cancerous cervical tissues (9.03±0.52 vs. 6.32±0.46) (P<0.05). High expression of PCMT1 was associated with decreased overall survival (OS) of patients with cervical cancer (P=0.0022). GSEA demonstrated that cervical cancer patients with high expression of PCMT1 were enriched in the various cancer-related signaling pathways.ConclusionsThese results suggest that PCMT1 might be a diagnostic and prognostic biomarker for cervical cancer, and further validation studies should be performed.

Emerging Roles and Potential Applications of Non-Coding RNAs in Cervical Cancer.

Cervical cancer (CC) is a preventable disease using proven interventions, specifically prophylactic vaccination, pervasive disease screening, and treatment, but it is still the most frequently diagnosed cancer in women worldwide. Patients with advanced or metastatic CC have a very dismal prognosis and current therapeutic options are very limited. Therefore, understanding the mechanism of metastasis and discovering new therapeutic targets are crucial. New sequencing tools have given a full visualization of the human transcriptome’s composition. Non-coding RNAs (NcRNAs) perform various functions in transcriptional, translational, and post-translational processes through their interactions with proteins, RNA, and even DNA. It has been suggested that ncRNAs act as key regulators of a variety of biological processes, with their expression being tightly controlled under physiological settings. In recent years, and notably in the past decade, significant effort has been made to examine the role of ncRNAs in a variety of human diseases, including cancer. Therefore, shedding light on the functions of ncRNA will aid in our better understanding of CC. In this review, we summarize the emerging roles of ncRNAs in progression, metastasis, therapeutics, chemo-resistance, human papillomavirus (HPV) regulation, metabolic reprogramming, diagnosis, and as a prognostic biomarker of CC. We also discussed the role of ncRNA in the tumor microenvironment and tumor immunology, including cancer stem cells (CSCs) in CC. We also address contemporary technologies such as antisense oligonucleotides, CRISPR–Cas9, and exosomes, as well as their potential applications in targeting ncRNAs to manage CC.

Prognostic value of lncRNA HOXA-AS3 in cervical cancer by targeting miR-29a-3p and its regulatory effect on tumor progression.

With the promotion of human papillomavirus (HPV) vaccine, cervical cancer has become a current research hotspot, and lncRNA has been confirmed to be used in the research of different diseases. This article systematically expounds the regulation and potential mechanisms of HOXA cluster antisense RNA 3 (HOXA-AS3) in cervical cancer, and discusses its possibility as a prognostic biomarker for cervical cancer. Relative expression levels of HOXA-AS3 and miR-29a-3p in tissues and cells were determined by real-time quantitative polymerase chain reaction (RT-qPCR). The survival of cervical cancer patients was analyzed by Kaplan-Meier method and the cumulative survival function table was drawn. The proliferation, migration, and invasion levels of HOXA-AS3 in cells were detected according to cell counting kit-8 (CCK-8) and transwell method. The dual-luciferase reporter gene assay confirmed the mechanism of action between HOXA-AS3 and miR-29a-3p. HOXA-AS3 was elevated and miR-29a-3p was decreased in tissues and cells of cervical cancer patients. Knockdown of HOXA-AS3 could inhibit the progression of cervical cancer and was more conducive to patient survival. Bioinformatics analysis confirmed that HOXA-AS3 negatively regulates cervical cancer development by sponging miR-29a-3p. In this research, knockdown of HOXA-AS3 could alleviate the process of cervical cancer by sponging miR-29a-3p, suggesting that HOXA-AS3 may be a potential prognostic target of cervical cancer, which could provide a theoretical basis for future clinical research of cervical cancer.

Bioinformatics Analysis Highlights Five Differentially Expressed Genes as Prognostic Biomarkers of Cervical Cancer and Novel Option for Anticancer Treatment.

Cervical cancer is one of the most common gynecological malignancies and is related to human papillomavirus (HPV) infection, especially high-risk type HPV16 and HPV18. Aberrantly expressed genes are involved in the development of cervical cancer, which set a genetic basis for patient prognosis. In this study, we identified a set of aberrantly expressed key genes from The Cancer Genome Atlas (TCGA) database, which could be used to accurately predict the survival rate of patients with cervical squamous cell carcinoma (CESC). A total of 3,570 genes that are differentially expressed between normal and cancerous samples were analyzed by the algorithm of weighted gene co-expression network analysis (WGCNA): 1,606 differentially expressed genes (DEGs) were upregulated, while 1,964 DEGs were downregulated. Analysis of these DEGs divided them into 7 modules including 76 hub genes. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analysis revealed a significant increase of genes related to cell cycle, DNA replication, p53 signaling pathway, cGMP-PKG signaling pathway, and Fanconi anemia (FA) pathway in CESC. These biological activities are previously reported to associate with cervical cancer or/and HPV infection. Finally, we highlighted 5 key genes (EMEMP2, GIMAP4, DYNC2I2, FGF13-AS1, and GIMAP1) as robust prognostic markers to predict patient’s survival rate (p = 3.706e-05) through univariate and multivariate regression analyses. Thus, our study provides a novel option to set up several biomarkers for cervical cancer prognosis and anticancer drug targets.

Monitoring methylation‑driven genes as prognostic biomarkers for cervical cancer

Aberrant DNA methylations are markedly associated with the development of cervical cancer (CC); however, only a limited number of studies have focused on identifying the DNA methylation‑driven genes in CC by integrative bioinformatics analysis to predict the prognosis of CC. In the present study, DNA methylation and transcriptome profiling data were downloaded from The Cancer Genome Atlas database. DNA methylation‑driven genes were obtained using the MethylMix R package. The Database for Annotation, Visualization and Integrated Discovery and ConsensusPathDB were used to perform Gene Ontology and pathway analyses, respectively. The survival R package was used to analyze overall survival rates associated with methylation‑driven genes. In total, data for 125 methylation‑driven mRNAs and 38 methylation‑driven long‑coding RNAs (lncRNAs) were obtained. Based on the univariate and multivariate Cox regression models, it was demonstrated that FLT1 (fms‑related tyrosine kinase 1) mRNA, MKI67 (marker of proliferation Ki‑67), PLEKHG6 (pleckstrin homology domain containing family G with RhoGef domain member 6) and POLE2 (DNA polymerase epsilon 2) lncRNAs were predictors of the overall survival of patients with CC. According to DNA methylation and gene expression, FLT1 mRNA, and the MKI67, PLEKHG6 and POLE2 lncRNAs functioned as independent biomarkers for the prognosis of CC. DNA methylation assays revealed that the promoter methylation levels of FLT1 were significantly upregulated in CC and cervical adenocarcinoma compared with normal controls. The results of immunohistochemical analysis revealed that the expression level of FLT1 in CC tissues was higher than that in normal tissues; however, the PLEKHG6 gene was expressed at high levels in normal tissues. On the whole, the present study demonstrates that methylation‑driven lncRNAs and mRNAs contribute to the survival of patients with CC, and FLT1 mRNA, and the MKI67, PLEKHG6 and POLE2 lncRNAs may be potential biomarkers for the prognosis of CC.

Biological and Clinicopathological Characteristics of OPN in Cervical Cancers.

Background: Cervical cancer (CC) is the most common gynecological malignancy. Recently, an increasing number of studies have indicated that osteopontin (OPN) is a promising diagnostic and prognostic biomarker for CC. However, the biological role and detailed mechanism of OPN in CC remain unclear. Methods: The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets and a clinical sample microarray were used in our study. To identify the clinicopathological characteristics of OPN in CC, we compared the expression of OPN between normal and CC tissue samples and analyzed the correlations between OPN expression and multiple clinicopathological features. To identify biological processes involving OPN, OPN-associated genes were screened with Pearson correlation analysis and applied in hallmark gene set enrichment analysis (GSEA). Additionally, leukocyte infiltration was evaluated based on OPN expression. Finally, OPN-related signaling pathways were identified by GSEA. Results: OPN expression was higher in CC samples than in normal tissue samples and positively correlated with age, FIGO stage, tumor size, lymphovascular invasion and an unfavorable prognosis. OPN-associated genes were mainly enriched in the immune response, and increased OPN expression was accompanied by increased M2 macrophage infiltration. Additionally, OPN was correlated with hypoxia, high glycolytic metabolism, apoptosis, angiogenesis, epithelial-mesenchymal transition and multiple signaling pathways (the p53 pathway, the PI3K/Akt pathway, IL6/STAT3 signaling, mTORC1 signaling and KRAS signaling). Conclusion: Our study showed that OPN is involved in immunological activities and multiple tumor processes, identifying it as a potential therapeutic target and useful prognostic factor in CC patients.

M6A-Related lncRNAs Are Potential Prognostic Biomarkers of Cervical Cancer and Affect Immune Infiltration.

The correlation of m6A-related lncRNAs with the prognosis and immune microenvironment of cervical cancer is not yet clear. In this study, we identified 7 m6A-related prognostic lncRNAs by Pearson correlation and univariate Cox regression analyses based on TCGA-cervical cancer dataset. Then, patients were divided into two clusters by consensus clustering based on the 7 m6A-related prognostic lncRNA expression. Cluster 1 was characterized by survival and stage disadvantage, enrichment of immunosuppressive and carcinogenic activation pathways. Besides, cluster 1 had higher immunosuppressive factor TGFbeta and lower immune cell infiltration compared with cluster 2. According to the expression of 7 m6A-related lncRNA, a 6-m6A-related lncRNA risk score model was established in the training set by LASSO regression analysis. The high-risk group had worse overall survival than the low-risk group. No matter in the training or validation sets, the m6A-related lncRNA risk score was an independent prognostic factor for overall survival. Meanwhile, we validated the independent prognostic value of risk score in the disease-specific survival and progression-free survival by multivariate Cox analysis. The high-risk group was characterized by higher TGFbeta and regulatory T cell and was rich in malignant pathways. Additionally, we also detected and compared the expression levels of four m6A-related prognostic lncRNA in 9 tumor samples and 9 normal tissues using quantitative real-time polymerase chain reaction assay. In conclusion, the novel m6A-related lncRNA risk score is a potential prognostic predictor of cervical cancer patients. These 6 m6A-related lncRNAs might serve as key mediators of the immune microenvironment and represent promising therapeutic targets for improving cervical cancer prognosis.

Comprehensive Molecular Analyses of a TNF Family-Based Gene Signature as a Potentially Novel Prognostic Biomarker for Cervical Cancer.

BackgroundIncreasing evidence suggests that tumour necrosis factor (TNF) family genes play important roles in cervical cancer (CC). However, whether TNF family genes can be used as prognostic biomarkers of CC and the molecular mechanisms of TNF family genes remain unclear.MethodsA total of 306 CC and 13 normal samples were obtained from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases. We identified differentially expressed TNF family genes between CC and normal samples and subjected them to univariate Cox regression analysis for selecting prognostic TNF family genes. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox regression analyses were performed to screen genes to establish a TNF family gene signature. Gene set enrichment analysis (GSEA) was performed to investigate the biological functions of the TNF family gene signature. Finally, methylation and copy number variation data of CC were used to analyse the potential molecular mechanisms of TNF family genes.ResultsA total of 26 differentially expressed TNF family genes were identified between the CC and normal samples. Next, a TNF family gene signature, including CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 was constructed based on univariate Cox, LASSO, and multivariate Cox regression analyses. The TNF family gene signature was related to age, pathological stages M and N, and could predict patient survival independently of clinical factors. Moreover, KEGG enrichment analysis suggested that the TNF family gene signature was mainly involved in the TGF-β signaling pathway, and the TNF family gene signature could affect the immunotherapy response. Finally, we confirmed that the mRNA expressions of CD27, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 were upregulated in CC, while that of EDA was downregulated. The mRNA expressions of CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be influenced by gene methylation and copy number variation.ConclusionOur study is the first to demonstrate that CD27, EDA, TNF, TNFRSF12A, TNFRSF13C, and TNFRSF9 might be used as prognostic biomarkers of CC and are associated with the immunotherapy response of CC.

Clinical Significance and Prognostic Value of Lactate Dehydrogenase Expression in Cervical Cancer.

Background: Lactate dehydrogenase (LDH) is a marker of injury and disease as it is expressed extensively in numerous cell types and tissues. Moreover it is released during tissue breakdown, and is elevated in cancerous tissues. However, the clinical significance and prognostic value of LDH as a tumor marker have been subject to considerable discussion. Objective: In this study, clinical serum LDH data from patients with cervical cancer (CC), CC microarray data, and RNA-seq data were integrated to assess the expression of LDH in CC. Methods: A total of 204 patients with newly diagnosed CC and 204 age-matched healthy controls were included to evaluate serum LDH levels in CC and non-cancer samples. External microarrays and RNA-seq datasets were collected for the differential expression analysis of LDH in CC and non-cancer tissue samples. Kaplan-Meier survival curves of the prognostic value of LDH for CC were plotted for RNA-seq data. Functional enrichment analysis was performed for the genes co-expressed with LDH. Results: The data from our in-house clinical cases as well as the data extracted from microarrays and RNA-seq databases demonstrated significant overexpression of LDH in CC samples. Elevated LDH expression levels were associated with poor overall survival in CC patients. The genes co-expressed with LDH were significantly correlated with the biological processes and pathways, associated with nuclear division, the condensed chromosome, protein serine/threonine kinase activity, and the cell cycle. Conclusion: In conclusion, LDH upregulation might serve as a therapeutic and prognostic biomarker for CC.

An integrated analysis of single-cell and bulk transcriptomics reveals EFNA1 as a novel prognostic biomarker for cervical cancer.

Cervical cancer is a serious threat to women's health and lives worldwide. The recovery and survival of cervical cancer can be improved by customizing therapy strategies based on individual-specific gene expression patterns. EFNA1 was reported to be dysregulated in many cancers and associated with their overall survivals, but its prognostic value in cervical cancer is still unclear. In this study, we performed analyses on the single-cell and bulk RNA sequencing data to study the role of EFNA1 in cervical cancer. EFNA1 was found to be significantly upregulated in cervical cancer tissue, especially the cancer cell subgroup within tumors, which was verified by immunohistochemistry. Through Cox regressions, we found that high EFNA1 expression is an independent risk factor for cervical cancer. Nomogram analysis indicated that EFNA1 could be a predicting factor for the survival probabilities of cervical cancer. Gene ontology and pathway analyses showed that EFNA1 was involved in many tumorigenesis pathways, protein, and virus productions. These findings suggested that EFNA1 could be a prognostic biomarker and potential therapeutic target for cervical cancer.

Identification of COPA as a potential prognostic biomarker and pharmacological intervention target of cervical cancer by quantitative proteomics and experimental verification

BackgroundCervical cancer is the most fatal gynecological carcinoma in the world. It is urgent to explore novel prognostic biomarkers and intervention targets for cervical cancer.MethodsThrough integrated quantitative proteomic strategy, we investigated the protein expression profiles of cervical cancer; 28 fresh frozen tissue samples (11 adenocarcinoma (AC), 12 squamous cell carcinoma (SCC) and 5 normal cervixes (HC)) were included in discover cohort; 45 fresh frozen tissue samples (19 AC, 18 SCC and 8 HC) were included in verification cohort; 140 paraffin-embedded tissues samples of cervical cancer (85 AC and 55 SCC) were used for immunohistochemical evaluation (IHC) of coatomer protein subunit alpha (COPA) as a prognostic biomarker for cervical cancer; how deficiency of COPA affects cell viability and tumorigenic ability of cervical cancer cells (SiHa cells and HeLa cells) were evaluated by cell counting kit-8 and clone formation in vitro.ResultsWe identified COPA is a potential prognostic biomarker for cervical cancer in quantitative proteomics analysis. By retrospective IHC analysis, we additionally verified the proteomics results and demonstrated moderate or strong IHC staining for COPA is an unfavourable independent prognostic factor for cervical cancer. We also identified COPA is a potential pharmacological intervention target of cervical cancer by a series of in vitro experiments.ConclusionThis study is the first to demonstrate that COPA may contribute to progression of cervical cancer. It can serve as a potential prognostic biomarker and promising intervention target for cervical cancer.

Comprehensive Analysis to Identify SPP1 as a Prognostic Biomarker in Cervical Cancer.

Background: SPP1, secreted phosphoprotein 1, is a member of the small integrin-binding ligand N-linked glycoprotein (SIBLING) family. Previous studies have proven SPP1 overexpressed in a variety of cancers and can be identified as a prognostic factor, while no study has explored the function and carcinogenic mechanism of SPP1 in cervical cancer. Methods: We aimed to demonstrate the relationship between SPP1 expression and pan-cancer using The Cancer Genome Atlas (TCGA) database. Next, we validated SPP1 expression of cervical cancer in the Gene Expression Omnibus (GEO) database, including GSE7803, GSE63514, and GSE9750. The receiver operating characteristic (ROC) curve was used to evaluate the feasibility of SPP1 as a differentiating factor by the area under curve (AUC) score. Cox regression and logistic regression were performed to evaluate factors associated with prognosis. The SPP1-binding protein network was built by the STRING tool. Enrichment analysis by the R package clusterProfiler was used to explore potential function of SPP1. The single-sample GSEA (ssGSEA) method from the R package GSVA and TIMER database were used to investigate the association between the immune infiltration level and SPP1 expression in cervical cancer. Results: Pan-cancer data analysis showed that SPP1 expression was higher in most cancer types, including cervical cancer, and we got the same result in the GEO database. The ROC curve suggested that SPP1 could be a potential diagnostic biomarker (AUC = 0.877). High SPP1 expression was associated with poorer overall survival (OS) (P = 0.032). Further enrichment and immune infiltration analysis revealed that high SPP1 expression was correlated with regulating the infiltration level of neutrophil cells and some immune cell types, including macrophage and DC. Conclusion: SPP1 expression was higher in cervical cancer tissues than in normal cervical epithelial tissues. It was significantly associated with poor prognosis and immune cell infiltration. Thus, SPP1 may become a promising prognostic biomarker for cervical cancer patients.

FANCI may serve as a prognostic biomarker for cervical cancer: A systematic review and meta-analysis.

Background:DNA damage is a fundamental process that plays a considerable role in generating protein diversity. FANCI, loaded on the altered chromatin, plays a vital role in DNA damage. Abnormal FANCI expression is potentially associated with carcinogenesis.However, the biological role of FANCI in cervical cancer is yet to be determined.Methods:We analyzed FANCI expression via multiple gene expression databases. Genes co-expressed with FANCI and its regulators were identified using LinkedOmics. The correlations between FANCI and cancer immune infiltrates were investigated via Tumor Immune Estimation Resource (TIMER).Results:FANCI was found upregulated with amplification in tumor tissues of multiple cervical cancer cohorts. High FANCI expression was associated with poorer overall survival (OS). Functional network analysis suggested that FANCI regulates spliceosome, DNA replication, and cell cycle signaling via pathways involving several cancer-related kinases and the E2F family. In additional, FANCI expression was positively correlated with infiltrating levels of CD4+ T and CD8+ T cells, and neutrophils. FANCI expression also showed strong correlations with diverse immune marker sets in cervical cancer.Conclusion:These findings suggested that FANCI is correlated with prognosis of and immune infiltration in cervical cancer, laying a foundation for further study of the immune regulatory role of FANCI in cervical cancer.

HPV16 E6/E7 stabilize PGK1 protein by reducing its poly-ubiquitination in cervical cancer.

This study aimed to explore the expression profile, prognostic value, regulatory effect, and the underlying mechanism of dysregulation of phosphoglycerate kinase 1 (PGK1) in high-risk human papillomavirus (HPV)-positive cervical epithelial squamous cell carcinoma (CESC). Bioinformatic analysis was performed using the CESC subset of The Cancer Genome Atlas (TCGA)-Cervical Cancer (CESC) and normal cervix in The Genotype-Tissue Expression (GTEx) project. HPV-16 positive CaSki and SiHa cells were used as in vitro cell models. Results showed that compared to the normal cervix, CESC tissues had significantly higher expression of PGK1. CESC patients with the higher 50% expression of PGK1 had substantially shorter disease-specific survival (DSS), and progression-free survival (PFS) compared to the cases with the lower 50% expression of PGK1. PGK1 knockdown impaired, but PGK1 overexpression enhanced the proliferation, colony formation, aerobic glycolytic activities (lactate production, intracellular ATP levels, glucose uptake, and extracellular acidification rate), migration, and invasion of CaSki and SiHa cells. HPV-16 E6/E7 knockdown in CaSki and SiHa cells had limited influence on PGK1 transcription but significantly decreased the half-life of PGK1 protein. E6/E7 knockdown mediated PGK1 downregulation could be blocked by adding MG-132. PGK1 poly-ubiquitination was significantly enhanced after E6/E7 knockdown. In conclusion, this study showed that PGK1 expression might serve as a prognostic biomarker in cervical cancer. Its upregulation contributes to enhanced aerobic glycolysis, migration, and invasion of CESC cells. HPV16 E6/E7 stabilizes PGK1 protein by reducing its poly-ubiquitination.

Knockdown of DIAPH3 Inhibits the Proliferation of Cervical Cancer Cells through Inactivating mTOR Signaling Pathway.

Cervical cancer (CC) ranks fourth for both incidence and mortality among females in worldwide. Therefore, it is urgent to explore new therapeutic and diagnostic targets for cervical cancer. Diaphanous-related formin 3 (DIAPH3) has been identified to play crucial roles in many malignant tumors. But its function and potential mechanism in CC remain largely unknown. In our study, DIAPH3 was frequently upregulated in CC tissue samples and increased expression of DIAPH3 was associated with poor overall survival according to several databases. Through in vitro and in vivo experiments, we found that decreased expression levels of DIAPH3 significantly inhibited the progression of CC. The GSEA analysis and western blot assay indicated that DIAPH3 was associated with the mTOR signaling pathway. The univariate and multivariate Cox analysis indicated that DIAPH3 was an independent prognosis risk factor in TCGA-CESC. And we confirmed that DIAPH3 expression was clearly related to tumor immune infiltrating cells (TIICs) by the analysis of CIBERSORT and TIMER databases. Taken together, we revealed that DIAPH3 plays as an oncogene through mTOR signaling pathway and DIAPH3 might be a potential prognostic biomarker in CC.

Analysis of therapeutic targets and prognostic biomarkers of CXC chemokines in cervical cancer microenvironment

BackgroundThe tumor microenvironment (TME) has received an increasing amount of attention. CXC chemokines can regulate immune cell transport and tumor cell activity to exert anti-tumor immunity. However, studies on the expression and prognosis of CXC chemokines in cervical cancer (CC) are more limited.MethodsThe study investigated the role of CXC chemokines in TME of CC by using public databases. Moreover, quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC) of CXC chemokines were performed to further verify.ResultsThe transcriptional levels of CXCL1/3/5/6/8/9/10/11/13/16/17 in CC tissues were significantly elevated while the transcriptional levels of CXCL12/14 were significantly reduced. We reached a consistent conclusion that the expression of CXCL9/10/11/13 was verified by quantitative real-time PCR and immunohistochemistry. Moreover, CC patients with low transcriptional levels of CXCL1/2/3/4/5/8 were significantly associated with longer overall survival (OS). The CCL family was related to CXC chemokines neighboring alteration. RELA, NFKB1, LCK and PAK2 were the key transcription factors and kinase targets of CXC chemokines, respectively. We also found there were significant correlations between the expression of CXCL9/10/11 and the infiltration of immune cells (CD8+ T cell, CD4+ T cell, neutrophils and dendritic cells).ConclusionsIn brief, we conducted a comprehensive analysis of CXC chemokines via clinical data and some online public databases. Our results may provide a new idea for the selection of immunotherapeutic targets and prognostic biomarkers for cervical cancer.

Urine miRNA signature as a potential non-invasive diagnostic and prognostic biomarker in cervical cancer

MicroRNAs as cancer biomarkers in serum, plasma, and other body fluids are often used but analysis of miRNA in urine is limited. We investigated the expression of selected miRNAs in the paired urine, serum, cervical scrape, and tumor tissue specimens from the women with cervical precancer and cancer with a view to identify if urine miRNAs could be used as reliable non-invasive biomarkers for an early diagnosis and prognosis of cervical cancer. Expression of three oncomiRs (miR-21, miR-199a, and miR-155-5p) and three tumor suppressors (miR-34a, miR-145, and miR-218) as selected by database search in cervical pre-cancer, cancer, and normal controls including cervical cancer cell lines were analyzed using qRT-PCR. The expression of miRNAs was correlated with various clinicopathological parameters, including HPV infection and survival outcome. We observed a significant overexpression of the oncomiRs and the downregulation of tumor suppressor miRNAs. A combination of miR-145-5p, miR-218-5p, and miR-34a-5p in urine yielded 100% sensitivity and 92.8% specificity in distinguishing precancer and cancer patients from healthy controls and it well correlates with those of serum and tumor tissues. The expression of miR-34a-5p and miR-218-5p were found to be independent prognostic factors for the overall survival of cervical cancer patients. We conclude that the evaluation of the above specific miRNA expression in non-invasive urine samples may serve as a reliable biomarker for early detection and prognosis of cervical cancer.

Construction of Gene Modules and Analysis of Prognostic Biomarkers for Cervical Cancer by Weighted Gene Co-Expression Network Analysis.

BackgroundDespite advances in the understanding of neoplasm, patients with cervical cancer still have a poor prognosis. Identifying prognostic markers of cervical cancer may enable early detection of recurrence and more effective treatment.MethodsGene expression profiling data were acquired from the Gene Expression Omnibus database. After data normalization, genes with large variation were screened out. Next, we built co-expression modules by using weighted gene co-expression network analysis to investigate the relationship between the modules and clinical traits related to cervical cancer progression. Functional enrichment analysis was also applied on these co-expressed genes. We integrated the genes into a human protein-protein interaction (PPI) network to expand seed genes and build a co-expression network. For further analysis of the dataset, the Cancer Genome Atlas (TCGA) database was used to identify seed genes and their correlation to cervical cancer prognosis. Verification was further conducted by qPCR and the Human Protein Atlas (HPA) database to measure the expression of hub genes.ResultsUsing WGCNA, we identified 25 co-expression modules from 10,016 genes in 128 human cervical cancer samples. After functional enrichment analysis, the magenta, brown, and darkred modules were selected as the three most correlated modules for cancer progression. Additionally, seed genes in the three modules were combined with a PPI network to identify 31 tumor-specific genes. Hierarchical clustering and Gepia results indicated that the expression quantity of hub genes NDC80, TIPIN, MCM3, MCM6, POLA1, and PRC1 may determine the prognosis of cervical cancer. Finally, TIPIN and POLA1 were further filtered by a LASSO model. In addition, their expression was identified by immunohistochemistry in HPA database as well as a biological experiment.ConclusionOur research provides a co-expression network of gene modules and identifies TIPIN and POLA1 as stable potential prognostic biomarkers for cervical cancer.

Clinical significance of miR-1298 in cervical cancer and its biological function in vitro.

Cervical cancer is one of the most malignant tumors in women. miR-1298 was reported to be abnormally expressed and serve crucial role in tumorigenesis of several types of cancer; however, the role of miR-1298 in cervical cancer remains unknown. The present study aimed to evaluate the clinical and biological significance of miR-1298 in cervical cancer. To do so, the expression level of miR-1298 in cervical cancer tissues and cells was evaluated by reverse transcription quantitative PCR. Kaplan-Meier survival analysis and Cox regression analysis were used to explore the prognostic significance of miR-1298 in patients with cervical cancer. Cell Counting Kit-8 and Transwell migration and invasion assays were used to evaluate the effect of miR-1298 on the proliferative, migratory and invasive abilities of cervical cancer cells, respectively. The expression of miR-1298 was lower in cancer tissues and cells compared with normal tissues and cells. Furthermore, miR-1298 expression was associated with lymph node metastasis, tumor diameter and staging from the International Federation of Gynecology and Obstetrics. In addition, patients with low miR-1298 expression had poorer overall survival. These findings suggested that miR-1298 may be considered as an independent prognostic factor for patients with cervical cancer. Furthermore, the results demonstrated that miR-1298 knockdown could promote tumor cell proliferation and migratory and invasive abilities. In addition, nucleus accumbens-associated 1 (NACC1) was demonstrated to be a direct target of miR-1298. Taken together, these findings indicated that miR-1298 overexpression may be considered as a prognostic biomarker for cervical cancer and that miR-1298 may play an inhibitor role in cervical cancer by targeting NACC1.

Five candidate biomarkers associated with the diagnosis and prognosis of cervical cancer.

Purpose: Cervical cancer (CC) is one of the most general gynecological malignancies and is associated with high morbidity and mortality. We aimed to select candidate genes related to the diagnosis and prognosis of CC.Methods: The mRNA expression profile datasets were downloaded. We also downloaded RNA-sequencing gene expression data and related clinical materials from TCGA, which included 307 CC samples and 3 normal samples. Differentially expressed genes (DEGs) were obtained by R software. GO function analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of DEGs were performed in the DAVID dataset. Using machine learning, the optimal diagnostic mRNA biomarkers for CC were identified. We used qRT-PCR and Human Protein Atlas (HPA) database to exhibit the differences in gene and protein levels of candidate genes.Results: A total of 313 DEGs were screened from the microarray expression profile datasets. DNA methyltransferase 1 (DNMT1), Chromatin Assembly Factor 1, subunit B (CHAF1B), Chromatin Assembly Factor 1, subunit A (CHAF1A), MCM2, CDKN2A were identified as optimal diagnostic mRNA biomarkers for CC. Additionally, the GEPIA database showed that the DNMT1, CHAF1B, CHAF1A, MCM2 and CDKN2A were associated with the poor survival of CC patients. HPA database and qRT-PCR confirmed that these genes were highly expressed in CC tissues.Conclusion: The present study identified five DEmRNAs, including DNMT1, CHAF1B, CHAF1A, MCM2 and Kinetochore-related protein 1 (KNTC1), as potential diagnostic and prognostic biomarkers of CC.