Profiling of Discrete Gynecological Cancers Reveals Novel Transcriptional Modules and Common Features Shared by Other Cancer Types and Embryonic Stem Cells

Comparative Analysis of Shapley Values Enhances Transcriptomics Insights across Some Common Uterine Pathologies

Uterine pathologies pose a challenge to women's health on a global scale. Despite extensive research, the causes and origin of some of these common disorders are not well defined yet. This study presents a comprehensive analysis of transcriptome data from diverse datasets encompassing relevant uterine pathologies such as endometriosis, endometrial cancer and uterine leiomyomas. Leveraging the Comparative Analysis of Shapley values (CASh) technique, we demonstrate its efficacy in improving the outcomes of the classical differential expression analysis on transcriptomic data derived from microarray experiments. CASh integrates the microarray game algorithm with Bootstrap resampling, offering a robust statistical framework to mitigate the impact of potential outliers in the expression data. Our findings unveil novel insights into the molecular signatures underlying these gynecological disorders, highlighting CASh as a valuable tool for enhancing the precision of transcriptomics analyses in complex biological contexts. This research contributes to a deeper understanding of gene expression patterns and potential biomarkers associated with these pathologies, offering implications for future diagnostic and therapeutic strategies.

Immune Profiling of Vulvar Squamous Cell Cancer Discovers a Macrophage-rich Subtype Associated with Poor Prognosis

The incidence rates of vulvar squamous cell cancer (VSCC) have increased over the past decades, requiring personalized oncologic approaches. Currently, lymph node involvement is a key factor in determining prognosis and treatment options. However, there is a need for additional immune-related biomarkers to provide more precise treatment and prognostic information. Here, we used IHC and expression data to characterize immune cells and their spatial distribution in VSCC. Hierarchical clustering analysis identified distinct immune subtypes, of which the macrophage-rich subtype was associated with adverse outcome. This is consistent with our findings of increased lymphogenesis, lymphatic invasion, and lymph node involvement associated with high macrophage infiltration. Further in vitro studies showed that VSCC-associated macrophages expressed VEGF-A and subsequently induced VEGF-A in the VSCC cell line A-431, providing experimental support for a pro-lymphangiogenic role of macrophages in VSCC. Taken together, immune profiling in VSCC revealed tumor processes, identified a subset of patients with adverse outcome, and provided a valuable biomarker for risk stratification and therapeutic decision making for anti-VEGF treatment, ultimately contributing to the advancement of precision medicine in VSCC.

SIGNIFICANCE

Immunoprofiling in VSCC reveals subtypes with distinct clinical and biological behavior. Of these, the macrophage-rich VSCC subtype is characterized by poor clinical outcome and increased VEGF-A expression, providing a biomarker for risk stratification and therapeutic sensitivity.

A comprehensive analysis and experimental validation of TK1 in uterine corpus endometrial carcinoma

Uterine corpus endometrial carcinoma (UCEC) is becoming a main malignant cancer that threaten to women's health. Thymidine kinase 1 (TK1) is considering to be associated with tumorigenesis and development. Nevertheless, the function of TK1 in UCEC is still unclear. Herein, we analyzed the TK1 expression level in pan-cancer and found that TK1 was upregulated in a variety of cancers including UCEC. Patients of UCEC with high expression of TK1 were related to poor outcome. TK1 was also related to clinical stage, histologic grade and lymph node metastasis. Abnormal expression of TK1 in UCEC was related to promoter methylation while gene mutation was not frequent. TK1 and its associated genes appeared to be prominent in cell cycle and DNA replication, according to GO and KEGG analysis. Analysis of immune infiltration revealed a negative correlation between TK1 and CD8 + T cells, macrophages, and dendritic cells. In vitro experiments, TK1 knockdown resulted in the inhibition of proliferation, migration, invasion and EMT in UCEC cell lines.

Expression and function of NF-Y subunits in cancer

NF-Y is a Transcription Factor (TF) targeting the CCAAT box regulatory element. It consists of the NF-YB/NF-YC heterodimer, each containing an Histone Fold Domain (HFD), and the sequence-specific subunit NF-YA. NF-YA expression is associated with cell proliferation and absent in some post-mitotic cells. The review summarizes recent findings impacting on cancer development. The logic of the NF-Y regulome points to pro-growth, oncogenic genes in the cell-cycle, metabolism and transcriptional regulation routes. NF-YA is involved in growth/differentiation decisions upon cell-cycle re-entry after mitosis and it is widely overexpressed in tumors, the HFD subunits in some tumor types or subtypes. Overexpression of NF-Y -mostly NF-YA- is oncogenic and decreases sensitivity to anti-neoplastic drugs. The specific roles of NF-YA and NF-YC isoforms generated by alternative splicing -AS- are discussed, including the prognostic value of their levels, although the specific molecular mechanisms of activity are still to be deciphered.

An Interaction Network Driven Approach for Identifying Cervical, Endometrial, Vulvar Carcinomic Biomarkers and Their Multi-targeted Inhibitory Agents from Few Widely Available Medicinal Plants

Differently expressed genes (DEGs) across cervical (CC), endometrial (EC), and vulvar carcinoma (VC) may serve as potential biomarkers for these progressive tumor conditions. In this study, DEGs of cervical (CC), endometrial (EC), and vulvar carcinoma (VC) were identified by microarray analysis. The interaction network between the identified 124 DEGs was constructed and analyzed to identify the hub genes and genes with high stress centrality. DEGs, namely, CDK1 and MMP9, were found to show highest degree and highest stress centrality respectively from the gene interaction network of 124 nodes and 1171 edges. DEG CDK1 is found to be overlapping in both cervical and endometrial carcinomic conditions while DEG MMP9 is found in vulvar carcinomic condition. Further, as it is studied that many phytochemicals play an important role as medicinal drugs, we have identified phytochemicals from few widely available medicinal plants and performed comprehensive computational study to identify a multi-targeted phytochemical against the identified DEGs, which are crucially responsible for the progression of these carcinomic conditions. Virtual screening of the phytochemicals against the target DEG protein structures with PDB IDs 4Y72 and 1GKC resulted in identifying the multi-targeted phytochemical against both the proteins. The molecular docking and dynamics simulation studies reveal that luteolin can act as a multi-targeted agent. Thus, the interactional and structural insights of luteolin toward the DEG proteins signify that it can be further explored as a multi-targeted agent against the cervical, endometrial, and vulvar carcinoma.

The diagnostic or prognostic values of FADD in cancers based on pan‑cancer analysis

Previous studies have determined that aberrant expression of the fas-associated death domain (FADD) contributes to the development of cancer. However, no pan-cancer analysis has been reported to explore the relationship between FADD and various cancers. Multiple databases were screened to identify cancer datasets for the present study and to validate the expression of FADD in various tumors. The association of FADD alteration with cancer prognosis, clinical features and tumor immunity was also evaluated. Reverse transcription-quantitative PCR (RT-qPCR) was utilized to confirm the expression of FADD in breast, colon, liver and gastric cancer cells. Analysis of Gene Expression Omnibus database and The Cancer Genome Atlas database indicated that FADD was highly expressed in breast invasive carcinoma (BRCA), cervical squamous cell carcinoma and endocervical adenocarcinoma, cholangiocarcinoma, colon adenocarcinoma (COAD), esophageal carcinoma (ESCA), kidney renal clear cell carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD) and prostate adenocarcinoma, whereas RT-qPCR results revealed that FADD was highly expressed in breast cancer and colon cancer. Further analyses demonstrated that FADD expression was significantly altered in ESCA, head and neck squamous cell carcinoma (HNSC), lung squamous cell carcinoma and BRCA. FADD expression was observed to be a risk factor of the overall survival in patients with HNSC, LIHC and LUAD as demonstrated by Kaplan-Meier and Cox regression analyses. The results of the present study demonstrated that FADD is highly expressed in numerous malignancies and can be utilized as a biomarker for the diagnosis of BRCA, COAD, LIHC and stomach adenocarcinoma. Moreover, FADD expression is a predictive risk factor for the development of HNSC, LIHC and LUAD and can potentially be used as a prognostic marker for these cancers.

TRIM28 modulates nuclear receptor signaling to regulate uterine function

Estrogen and progesterone, acting through their cognate receptors the estrogen receptor α (ERα) and the progesterone receptor (PR) respectively, regulate uterine biology. Using rapid immunoprecipitation and mass spectrometry (RIME) and co-immunoprecipitation, we identified TRIM28 (Tripartite motif containing 28) as a protein which complexes with ERα and PR in the regulation of uterine function. Impairment of TRIM28 expression results in the inability of the uterus to support early pregnancy through altered PR and ERα action in the uterine epithelium and stroma by suppressing PR and ERα chromatin binding. Furthermore, TRIM28 ablation in PR-expressing uterine cells results in the enrichment of a subset of TRIM28 positive and PR negative pericytes and epithelial cells with progenitor potential. In summary, our study reveals the important roles of TRIM28 in regulating endometrial cell composition and function in women, and also implies its critical functions in other hormone regulated systems.

Immunogenetic Profiles and Associations of Breast, Cervical, Ovarian, and Uterine Cancers

It is increasingly recognized that the human immune response influences cancer risk, progression, and survival; consequently, there is growing interest in the role of human leukocyte antigen (HLA), genes that play a critical role in initiating the immune response, on cancer. Recent evidence documented clustering of cancers based on immunogenetic profiles such that breast and ovarian cancers clustered together as did uterine and cervical cancers. Here we extend that line of research to evaluate the HLA profile of those 4 cancers and their associations. Specifically, we evaluated the associations between the frequencies of 127 HLA alleles and the population prevalences of breast, ovarian, cervical, and uterine cancer in 14 countries in Continental Western Europe. Factor analysis and hierarchical clustering were used to evaluate groupings of cancers based on their immunogenetic profiles. The results documented highly similar immunogenetic profiles for breast and ovarian cancers that were characterized predominantly by protective HLA effects. In addition, highly similar immunogenetic profiles for cervical and uterine cancers were observed that were, conversely, characterized by susceptibility effects. In light of the role of HLA in host immune system protection against non-self antigens, these findings suggest that certain cancers may be associated with similar contributory factors such as viral oncoproteins or neoantigens.

Bioinformatics and In silico approaches to identify novel biomarkers and key pathways for cancers that are linked to the progression of female infertility: A comprehensive approach for drug discovery

Despite modern treatment, infertility remains one of the most common gynecologic diseases causing severe health effects worldwide. The clinical and epidemiological data have shown that several cancerous risk factors are strongly linked to Female Infertility (FI) development, but the exact causes remain unknown. Understanding how these risk factors affect FI-affected cell pathways might pave the door for the discovery of critical signaling pathways and hub proteins that may be targeted for therapeutic intervention. To deal with this, we have used a bioinformatics pipeline to build a transcriptome study of FI with four carcinogenic risk factors: Endometrial Cancer (EC), Ovarian Cancer (OC), Cervical Cancer (CC), and Thyroid Cancer (TC). We identified FI sharing 97, 211, 87 and 33 differentially expressed genes (DEGs) with EC, OC, CC, and TC, respectively. We have built gene-disease association networks from the identified genes based on the multilayer network and neighbour-based benchmarking. Identified TNF signalling pathways, ovarian infertility genes, cholesterol metabolic process, and cellular response to cytokine stimulus were significant molecular and GO pathways, both of which improved our understanding the fundamental molecular mechanisms of cancers associated with FI progression. For therapeutic intervention, we have targeted the two most significant hub proteins VEGFA and PIK3R1, out of ten proteins based on Maximal Clique Centrality (MCC) value of cytoscape and literature analysis for molecular docking with 27 phytoestrogenic compounds. Among them, sesamin, galangin and coumestrol showed the highest binding affinity for VEGFA and PIK3R1 proteins together with favourable ADMET properties. We recommended that our identified pathway, hub proteins and phytocompounds may be served as new targets and therapeutic interventions for accurate diagnosis and treatment of multiple diseases.

BCHE as a Prognostic Biomarker in Endometrial Cancer and Its Correlation with Immunity

Background

In developed countries, the most common gynecologic malignancy is endometrial carcinoma (EC), making the identification of EC biomarkers extremely essential. As a natural enzyme, butyrylcholinesterase (BCHE) is found in hepatocytes and plasma. There is a strong correlation between BCHE gene mutations and cancers and other diseases. The aim of this study was to analyze the role of BCHE in patients with EC.

Methods

A variety of analyses were conducted on The Cancer Genome Atlas (TCGA) data, including differential expression analysis, enrichment analysis, immunity, clinicopathology, and survival analysis. The Gene Expression Omnibus (GEO) database was used to validate outcomes. Using R tools, Gene Set Enrichment Analysis (GSEA) and Gene Ontology (GO) analyses revealed the potential mechanisms of BCHE in EC. Sangerbox tools were used to delve into the relations between BCHE expression and tumor microenvironment, including microsatellite instability (MSI), tumor neoantigen count (TNC), and tumor mutation burden (TMB). BCHE's genetic alteration analysis was conducted by cBioPortal. In addition, the Human Protein Atlas (HPA) was used to validate the outcomes by immunohistochemistry, and an analysis of the protein-protein interaction network (PPI) was performed with the help of the STRING database.

Results

Based on our results, BCHE was a significant independent prognostic factor for patients with EC. The prognosis with EC was affected by age, stage, grade, histological type, and BCHE. GSEA showed that BCHE was closely related to pathways regulating immune response, including transforming growth factor-β (TGF-β) signaling pathways and cancer immunotherapy through PD1 blockade pathways. The immune analysis revealed that CD4+ regulatory T cells (Tregs) were negatively correlated with BCHE expression and the immune checkpoint molecules CD28, ADORA2A, BTNL2, and TNFRSF18 were all significantly related to BCHE. BCHE expression was also associated with TMB by genetic alteration analysis.

Conclusions

Identifying BCHE as a biomarker for EC might help predict its prognosis and could have important implications for immunotherapy.

Exploring the Pharmacological Mechanism of the Effective Chinese Medicines Against Gynecological Cancer Based on Meta-Analysis Combined With Network Pharmacology Analysis

This meta-analysis plus network pharmacology aimed to investigate whether traditional Chinese medicine (TCM) combined with chemotherapy is associated with more beneficial efficacy data in the treatment of gynecological cancer (GC). A total of 11 randomized controlled trials (RCTs) consisting of 863 GC patients were included. Results showed a better ORR (RR: 1.42, 95% CI: 1.18–1.71; I² = 21.4%; p = 0.282), DCR (RR: 1.13, 95% CI: 1.03–1.25; I² = 0.0%; p = 0.492), PD (RR: 0.27, 95% CI: 0.11–0.65, p = 0.003; I² = 0.0%, p = 0.930), and QOL (SMD: 0.85, 95% CI: 0.38–1.33, p = 0.005) and higher proportions of CD3⁺ T (WMD: 5.65, 95% CI: 4.23–7.08, p = 0.000; I² = 68.3%, p = 0.004), CD4⁺ T (WMD: 6.97, 95% CI: 5.35–8.59, p = 0.000; I² = 83.4%, p = 0.000), and the CD4⁺/CD8⁺ T ratio (WMD: 0.32, 95% CI: 0.23–0.42, p = 0.000; I² = 78.0%, p = 0.000). The number of adverse events (AEs) was significantly lower in the TCM + chemotherapy group. The active components and targets of 19 high-frequency Chinese medicines obtained from the meta-analysis were screened and explored in network pharmacology analysis. Also, a regulatory network of active components and targets, a core network and key genes, a diagram of protein interaction, network topology analysis, and gene body GO function and KEGG pathway enrichment analysis were performed. A total of 120 active components were identified. NPM1 and HSPA8 are the most critical target proteins in the core network of protein interaction. HSP90AA1 is the most important target protein in the TCM group. KEGG enrichment analysis showed that it was highly significant in the lipid and atherosclerotic pathways. Therefore, moderate evidence revealed that TCM plus chemotherapy has obvious advantages over chemotherapy alone in terms of tumor responses, QOL, peripheral blood lymphocyte levels, and fewer AEs in the treatment of GC. The potential important targets and core genes were displayed.

Identifying and optimizing human endometrial gene expression signatures for endometrial dating

STUDY QUESTION

What are the key considerations for developing an enhanced transcriptomic method for secretory endometrial tissue dating?

SUMMARY ANSWER

Multiple gene expression signature combinations can serve as biomarkers for endometrial dating, but their predictive performance is variable and depends on the number and identity of the genes included in the prediction model, the dataset characteristics and the technology employed for measuring gene expression.

WHAT IS KNOWN ALREADY

Among the new generation of transcriptomic endometrial dating (TED) tools developed in the last decade, there exists variation in the technology used for measuring gene expression, the gene makeup and the prediction model design. A detailed study, comparing prediction performance across signatures for understanding signature behaviour and discrepancies in gene content between them, is lacking.

STUDY DESIGN, SIZE, DURATION

A multicentre prospective study was performed between July 2018 and October 2020 at five different centres from the same group of clinics (Spain). This study recruited 281 patients and finally included in the gene expression analysis 225 Caucasian patients who underwent IVF treatment. After preprocessing and batch effect filtering, gene expression measurements from 217 patients were combined with artificial intelligence algorithms (support vector machine, random forest and k-nearest neighbours) allowing evaluation of different prediction models. In addition, secretory-phase endometrial transcriptomes from gene expression omnibus (GEO) datasets were analysed for 137 women, to study the endometrial dating capacity of genes independently and grouped by signatures. This provided data on the consistency of prediction across different gene expression technologies and datasets.

PARTICIPANTS/MATERIALS, SETTING, METHODS

Endometrial biopsies were analysed using a targeted TruSeq (Illumina) custom RNA expression panel called the endometrial dating panel (ED panel). This panel included 301 genes previously considered relevant for endometrial dating as well as new genes selected for their anticipated value in detecting the secretory phase. Final samples (n = 217) were divided into a training set for signature discovery and an independent testing set for evaluation of predictive performance of the new signature. In addition, secretory-phase endometrial transcriptomes from GEO were analysed for 137 women to study endometrial dating capacity of genes independently and grouped by signatures. Predictive performance among these signatures was compared according to signature gene set size.

MAIN RESULTS AND THE ROLE OF CHANCE

Testing of the ED panel allowed development of a model based on a new signature of 73 genes, which we termed 'TED' and delivers an enhanced tool for the consistent dating of the secretory phase progression, especially during the mid-secretory endometrium (3-8 days after progesterone (P) administration (P + 3-P + 8) in a hormone replacement therapy cycle). This new model showed the best predictive capacity in an independent test set for staging the endometrial tissue in the secretory phase, especially in the expected window of implantation (average of 114.5 ± 7.2 h of progesterone administered; range in our patient population of 82-172 h). Published sets of genes, in current use for endometrial dating and the new TED genes, were evaluated in parallel in whole-transcriptome datasets and in the ED panel dataset. TED signature performance was consistently excellent for all datasets assessed, frequently outperforming previously published sets of genes with a smaller number of genes for dating the endometrium in the secretory phase. Thus, this optimized set exhibited prediction consistency across datasets.

LARGE SCALE DATA

The data used in this study is partially available at GEO database. GEO identifiers GSE4888, GSE29981, GSE58144, GSE98386.

LIMITATIONS, REASONS FOR CAUTION

Although dating the endometrial biopsy is crucial for investigating endometrial progression and the receptivity process, further studies are needed to confirm whether or not endometrial dating methods in general are clinically useful and to guide the specific use of TED in the clinical setting.

WIDER IMPLICATIONS OF THE FINDINGS

Multiple gene signature combinations provide adequate endometrial dating, but their predictive performance depends on the identity of the genes included, the gene expression platform, the algorithms used and dataset characteristics. TED is a next-generation endometrial assessment tool based on gene expression for accurate endometrial progression dating especially during the mid-secretory.

STUDY FUNDING/COMPETING INTEREST(S)

Research funded by IVI Foundation (1810-FIVI-066-PD). P.D.-G. visiting scientist fellowship at Oxford University (BEFPI/2010/032) and Josefa Maria Sanchez-Reyes' predoctoral fellowship (ACIF/2018/072) were supported by a program from the Generalitat Valenciana funded by the Spanish government. A.D.-P. is supported by the FPU/15/01398 predoctoral fellowship from the Ministry of Science, Innovation and Universities (Spanish Government). D.W. received support from the NIHR Oxford Biomedical Research Centre. The authors do not have any competing interests to declare.

Functional New Transcription Factors (TFs) Associated with Cervical Cancer

The goal of this research was to find noval transcription factors (TFs) that are involved in cervical carcinogenesis. The Gene Expression Omnibus (GEO) database was utilized to analyze ten cervical cancer datasets using the Robust Rank Aggregation (RRA) technique. Survival and differential expression were validated using GEPIA (Gene Expression Profiling Interactive Analysis). The transcriptional regulatory network and putative targets were built using Cytoscape. A real-time PCR (quantitative real-time polymerase chain reaction) experiment was used to confirm the mRNA expression. Using public cervical cancer single-cell RNA-sequencing (scRNA-seq), bulk TCGA-CESC RNA-seq, and microarray datasets, coexpression correlations between putative targets and TFs were confirmed. After combining the results of 10 datasets, 8 TFs, including EMX2 (Empty Spiracles Homeobox 2), were chosen among 385 robust DEGs. In the normal female reproductive tract, EMX2 is extensively expressed, but it is reduced in cervical cancer. Overexpression EMX2 suppresses the proliferation of HeLa cells. 12 potential targets of EMX2 were selected. Our research has revealed evidence that EMX2 acted as a tumor suppressor in cervical cancer and PDZRN3 might be possible target of EMX2 in cervical cancer. It might be a therapeutic target in the future.

99mTc-labeled peptide targeting interleukin 13 receptor α 2 for tumor imaging in a cervical cancer mouse model

OBJECTIVE

Pep-1 (CGEMGWVRC) can potently bind to interleukin 13 receptor α 2 (IL-13Rα2), a tumor-restricted receptor found to be expressed in various malignancies. In this study, we intended to prepare a ^99mTc-labeled probe and evaluate its in vivo tumor accumulation properties in a cervical cancer xenograft model.

METHODS

The Pep-1 was designed and radiolabeled with ^99mTc by conjugation with mercaptoacetyl-triglycine (MAG₃). The labeling yield, radiochemical purity and stability were characterized in vitro. Cell uptake assays and fluorescence imaging were conducted for qualitative and quantitative evaluation of the specificity and affinity of Pep-1. Flow cytometry and tissue immunofluorescence were used to confirm the IL-13Rα2 expression in cervical cancer. Biodistribution and in vivo imaging were performed periodically to evaluate the imaging value of ^99mTc-MAG₃-Pep-1 in cervical cancer xenograft model.

RESULTS

^99mTc-MAG₃-Pep-1 was successfully prepared with a high labeling yield and radiochemical purity (> 95%). Specific cell uptake was demonstrated by scramble control and unlabeled MAG₃-Pep-1 blockade. Flow cytometry and tissue immunofluorescence also confirmed the mild IL-13Rα2 expression of HeLa. In the gamma imaging study and biodistribution, the tumors were imaged clearly at 2-6 h after injection of ^99mTc-MAG₃-Pep-1 and the accumulation of ^99mTc-MAG₃-Pep-1 in tumor was significantly higher than that in the blocking and scramble controls, demonstrating ligand-receptor binding specificity.

CONCLUSIONS

This work demonstrated that ^99mTc-MAG₃-Pep-1 can bind to cervical cancer with high affinity and specificity. MAG₃-Pep-1 may be a prospective precursor for IL-13Rα2-expressing cancer therapy.

Long noncoding RNA ALOX12-AS1 inhibits cervical cancer cells proliferation via targeting miR-3171

Cervical cancer is a common female malignancy worldwide, and the molecular mechanism of cervical tumorigenesis remains poorly understood. A large piece of evidence have demonstrated the important roles of long noncoding RNAs (lncRNAs) in tumorigenesis, cancer progression and drug resistance. In this study, we comprehensively analyzed the lncRNAs expression pattern in cervical cancer using RNA sequencing and microarray data from the cancer genome atlas, gene expression omnibus and Genotype Tissue Expression. Moreover, we assessed the correlation between lncRNA expression levels and cervical cancer patient's survival. We uncovered hundreds of lncRNAs that are upregulated or downregulated in cervical cancer tissues. Among these aberrantly lncRNAs, some are significantly associated with cervical patients' poorer prognosis, such as ALOX12-AS1 and LINC00173. ALOX12-AS1 expression is downregulated in cervical cancer, and over-expression of ALOX12-AS1 could inhibit cervical cancer cells proliferation in vitro. Further, mechanistically investigation revealed that ALOX12-AS1 could interact with AGO2 and sponge miR-3171, thereby antagonizing its' repression of tumor suppressor phosphatase and tensin homolog expression in cervical cancer cell. Taken together, this study provides lncRNA candidates in cervical cancer and highlights the critical role of ALOX12-AS1 in cervical cancer.

PCNA in Cervical Intraepithelial Neoplasia and Cervical Cancer: An Interaction Network Analysis of Differentially Expressed Genes

The investigation of differentially expressed genes (DEGs) and their interactome could provide valuable insights for the development of markers to optimize cervical intraepithelial neoplasia (CIN) screening and treatment. This study investigated patients with cervical disease to identify gene markers whose dysregulated expression and protein interaction interface were linked with CIN and cervical cancer (CC). Literature search of microarray datasets containing cervical epithelial samples was conducted in Gene Expression Omnibus and Pubmed/Medline from inception until March 2021. Retrieved DEGs were used to construct two protein-protein interaction (PPI) networks. Module DEGs that overlapped between CIN and CC samples, were ranked based on 11 topological algorithms. The highest-ranked hub gene was retrieved and its correlation with prognosis, tissue expression and tumor purity in patients with CC, was evaluated. Screening of the literature yielded 9 microarray datasets (GSE7803, GSE27678, GSE63514, GSE6791, GSE9750, GSE29570, GSE39001, GSE63678, GSE67522). Two PPI networks from CIN and CC samples were constructed and consisted of 1704 and 3748 DEGs along 21393 and 79828 interactions, respectively. Two gene clusters were retrieved in the CIN network and three in the CC network. Multi-algorithmic topological analysis revealed PCNA as the highest ranked hub gene between the two networks, both in terms of expression and interactions. Further analysis revealed that while PCNA was overexpressed in CC tissues, it was correlated with favorable prognosis (log-rank P=0.022, HR=0.58) and tumor purity (P=9.86 × 10^-4, partial rho=0.197) in CC patients. This study identified that cervical PCNA exhibited multi-algorithmic topological significance among DEGs from CIN and CC samples. Overall, PCNA may serve as a potential gene marker of CIN progression. Experimental validation is necessary to examine its value in patients with cervical disease.

Integrative meta-analysis of gene expression profiles identifies FEN1 and ENDOU as potential diagnostic biomarkers for cervical squamous cell carcinoma

Cervical carcinoma is a global public health burden. Given that it is usually asymptomatic at potentially curative stages, the development of clinically accurate tests is critical for early detection and individual risk stratification. The present study performed an integrative meta-analysis of the transcriptomes from 10 cervical carcinoma cohorts, with the aim of identifying biomarkers that are associated with malignant transformation of cervical epithelium, and establish their clinical applicability. From among the top ranked differentially expressed genes, flap structure-specific endonuclease 1 (FEN1) and poly (U)-specific endoribonuclease (ENDOU) were selected for further validation, and their clinical applicability was assessed using immunohistochemically stained microarrays comprising 110 tissue cores, using p16 and Ki67 staining as the comparator tests. The results demonstrated that FEN1 expression was significantly upregulated in 65% of tumor specimens (P=0.0001), with no detectable expression in the non-tumor tissues. Furthermore, its expression was significantly associated with Ki67 staining in tumor samples (P<0.0001), but no association was observed with p16 expression or the presence of human papilloma virus types 16/18, patient age, tumor grade or stage. FEN1 staining demonstrated lower sensitivity than p16 (69.3 vs. 96.8%) and Ki67 (69.3 vs. 76.3%); however, the specificity was identical to p16 and higher than that of Ki67 (100 vs. 71.4%).ENDOU staining was consistent with the microarray results, demonstrating 1% positivity in tumors and 40% positivity in non-tumor tissues. Gene set enrichment analysis of cervical tumors overexpressing FEN1 revealed its association with enhanced growth factor signaling, immune response inhibition and extracellular matrix remodeling, whereas tumors with low ENDOU expression exhibited inhibition of epithelial development and differentiation processes. Taken together, the results of the present study demonstrate the feasibility of the integrative meta-analysis approach to identify relevant biomarkers associated with cervical carcinogenesis. Thus, FEN1 and ENDOU may be useful diagnostic biomarkers for squamous cervical carcinoma. However, further studies are required to determine their diagnostic performance in larger patient cohorts and validate the results presented here.

Tumor-Infiltrating CD8+ T Cells Driven by the Immune Checkpoint-Associated Gene IDO1 Are Associated With Cervical Cancer Prognosis

Tumor-infiltrating immune cells, associated with tumor progression, are promising prognostic biomarkers. However, the relationship between levels of gene expression and that of immune cell infiltration in cervical cancer prognosis is unknown. In this study, three cervical cancer gene expression microarrays (GSE6791, GSE63678 and GSE55940) were obtained from the GEO database. The IDO1 gene was identified by differentially expressed gene screening. The gene expression profiles of TCGA and GTEx databases along with comprehensive bioinformatics analysis identified that the IDO1 gene was upregulated in cervical cancer with significant difference in expression at different N stages. In addition, it was also upregulated in HPV16 positive sample. The pan-cancer analysis identified that IDO1 was highly expressed in most cancers. TIMER analysis revealed that the expression of IDO1 in CESC shows positive correlation with CD8⁺ T cells, CD4⁺ T cells, neutrophils, dendritic cells. IDO1 expression showed remarkable positive correlation with all immune cell markers except M1 macrophages. CD8⁺ T cell infiltration GSEA results showed that IDO1 was mainly associated with tumor immune-related signaling pathways.

The modulatory properties of Astragalus membranaceus treatment on endometrial cancer: an integrated pharmacological method

Astragalus membranaceus is a traditional Chinese medicine and has been used for adjuvant clinical therapy for a variety of cancers. However, the mechanism of its action on endometrial carcinoma is unclear. Based on the Gene Expression Omnibus (GEO) database, the Cancer Genome Atlas (TCGA) database, and the Traditional Chinese Medicine System Pharmacology Database (TCMSP™), the drug and target compounds were initially screened to construct a common network module. Twenty active compounds in Astragalus membranaceus were successfully identified, which hit by 463 potential targets related to endometrial cancer. Eight of the more highly predictive compounds (such as Jaranol, Bifendate, Isorhamnetin, Calycosin, 7-O-methylisomucronulatol, Formononetin, Kaempferol, Quercetin) were involved in DNA integrity checkpoint, cyclin-dependent protein kinase holoenzyme complex, and histone kinase activity. Additionally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway confirmed that Astragalus membranaceus might play a role in the treatment of endometrial cancer through p53 signalling pathway, transcriptional misregulation in cancer, and endometrial cancer signalling pathway. Drug-target-pathway networks were constructed using Cytoscape to provide a visual perspective. In addition, we verified that formononetin inhibited the proliferation of endometrial cancer cells through cell viability tests and clone formation tests. And qPCR and western blot found that formononetin exerts anti-cancer effects by promoting the expression of estrogen receptor beta (ERβ) and p53. Based on a systematic network pharmacology approach, our works successfully predict the active ingredients and potential targets of Astragalus membranaceus for application to endometrial cancer and helps to illustrate mechanism of action on a comprehensive level.

Metabolic rewiring is associated with HPV-specific profiles in cervical cancer cell lines

Both HPV-positive and HPV-negative cervical cancers are associated with aberrant metabolism, although the oncogenic drivers remain elusive. Here we show the assessment of the metabolomic profiles of four distinct cervical cell lines, a normal and three cancer cell lines, one HPV-negative (C33A) and two HPV-positive (SiHa HPV16+, HeLa HPV18+), employing an ultra performance liquid chromatography and a high resolution mass spectrometry. Out of the total 462 metabolites, 248 to 326 exhibited statistically significant differences, while Random Forests analysis identified unique molecules for each cell line. The two HPV+ cell lines exhibited features of Warburg metabolism, consistent with the role of the HPV E6 protein. SiHa and HeLa cells displayed purine salvage pathway activity, while C33A cells revealed synthesis of cytidine, via a novel mechanism. These data document a highly dynamic HPV-specific rewiring of metabolic pathways occurring in cervical cancer. Therefore, this approach can eventually provide novel mechanistic insights into cervical carcinogenesis.

SNX10 and PTGDS are associated with the progression and prognosis of cervical squamous cell carcinoma

Background

Cervical cancer (CC) is the primary cause of death in women. This study sought to investigate the potential mechanism and prognostic genes of CC.

Methods

We downloaded four gene expression profiles from GEO. The RRA method was used to integrate and screen differentially expressed genes (DEGs) between CC and normal samples. Functional analysis was performed by clusterprofiler. We built PPI network by Search Tool for the Retrieval of Interacting Genes Database (STRING) and selected hub modules via Molecular COmplex Detection (MCODE). CMap database was used to find molecules with therapeutic potential for CC. The hub genes were validated in GEO datasets, Gene Expession Profiling Interactive Analysis (GEPIA), immunohistochemistry, Cox regression analysis, TCGA methylation analysis and ONCOMINE were carried out. ROC curve analysis and GSEA were also performed to describe the prognostic significance of hub genes.

Results

Functional analysis revealed that 147 DEGs were significantly enriched in binding, cell proliferation, transcriptional activity and cell cycle regulation. PPI network screened 30 hub genes, with CDK1 having the strongest connectivity with CC. Cmap showed that apigenin, thioguanine and trichostatin A might be used to treat CC(P < 0.05). Eight genes (APOD, CXCL8, MMP1, MMP3, PLOD2, PTGDS, SNX10 and SPP1) were screened out through GEPIA. Of them, only PTGDS and SNX10 had not appeared in previous studies about CC. The validation in GEO showed that PTGDS showed low expression while SNX10 presented high expression in tumor tissues. Their expression profiles were consistent with the results in immunohistochemistry. ROC curve analysis indicated that the model had a good diagnostic efficiency (AUC = 0.738). GSEA analysis demonstrated that the two genes were correlated with the chemokine signaling pathway (P < 0.05). TCGA methylation analysis showed that patients with lowly-expressed and highly-methylated PTGDS had a worse prognosis than those with highly-expressed and lowly-methylated PTGDS (p = 0.037). Cox regression analysis showed that SNX10 and PTGDS were independent prognostic indicators for OS among CC patients (P = 0.007 and 0.003).

Conclusions

PTGDS and SNX10 showed abnormal expression and methylation in CC. Both genes might have high prognostic value of CC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08212-w.

Expression Profiles Reveal Involvement of VEGF, IGF1, BIRC5, and MMP1 in Vulvar Carcinogenesis

OBJECTIVE

The objective of this study was to identify key genes and shed light on the underlying molecular mechanisms of vulvar squamous cell carcinoma (VSCC).

METHODS

Bioinformatic software was utilized for the identification and characterization of key differentially expressed genes (DEGs) from microarrays GSE63678 and GSE38228, which contain VSCC and normal vulvar tissue data. These microarrays were obtained from Gene Expression Omnibus (GEO). Immunohistochemical assays (55 VSCC and 50 normal vulvar tissues) were utilized to validate the expression of VEGF, IGF1, BIRC5, and MMP1 screened from the identified DEGs. SPSS 18.0 software was used for statistical analyses of the relationships between IGF1, BIRC5, VEGF, MMP1 expression levels and patient clinicopathological characteristics.

RESULTS

A total of 141 DEGs were identified, among which 18 genes were closely correlated with the biological characteristics of VSCC. Four of the 18 genes (VEGF, IGF1, BIRC5, and MMP1) screened from the GEO database were markedly enriched in pathways in cancer (P < 0.05), and could be considered key genes in VSCC based on KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway analysis in DAVID (Database for Annotation, Visualization and Integrated Discovery).The expression levels of these 4 hub genes, determined by immunohistochemical assays, were consistent with the bioinformatics results. Higher expression of IGF1 showed significant association with well-differentiated carcinomas (P = 0.017).BIRC5 expression levels showed a positive correlation with clinical stage (P = 0.039); compared with those in menopause for over 10 years, patients in menopause for less than 10 years at the time of diagnosis tended to have significantly higher expression of BIRC5 (P = 0.003). VEGF and MMP1 expression levels were not correlated with any of the tested clinicopathological characteristics.

CONCLUSION

VEGF, IGF1, BIRC5, and MMP1 were identified as being associated with VSCC using integrated bioinformatic methods, which may provide important insights into the pathogenesis of this disease and help to identify new biomarkers.

Overexpression of <em>MYBL2</em> predicts poor prognosis and promotes oncogenesis in endometrial carcinoma

Endometrial cancer (EC) is the most common gynecologic malignancy and still remains clinically challenging. We aimed to explore the potential biomarkers of EC and provide a theoretical basis for early screening and targeted therapy. The available transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify differentially expressed genes. Immunohistochemistry was performed to detect gene expression. We analyzed the associations of MYBL2 with clinicopathological features and survival time and the biological effect of MYBL2 on the proliferation of EC cells. The effect of MYBL2 silencing on the transcriptome of EC cell model was analyzed by RNA-Seq. MYBL2 was significantly upregulated with obvious copy number alteration in EC. Copy number amplification significantly increased MYBL2 mRNA expression, which led to a poor prognosis and severe pathological types of EC. Additionally, MYBL2 silencing significantly inhibited proliferation and induced apoptosis and G¹-phase cell cycle arrest in EC cell lines. Our results indicate that MYBL2 is closely related to the cell cycle and apoptosis pathways in EC. The findings in this study provide evidence that MYBL2 can serve as a new candidate prognostic marker and a target for future therapeutic intervention in EC.

A Risk Signature with Nine Stemness Index-Associated Genes for Predicting Survival of Patients with Uterine Corpus Endometrial Carcinoma

Purpose

To identify mRNA expression-based stemness index- (mRNAsi-) related genes and build an mRNAsi-related risk signature for endometrial cancer.

Methods

We collected mRNAsi data of endometrial cancer samples from The Cancer Genome Atlas (TCGA) and analyzed their relationship with the main clinicopathological characteristics and prognosis of endometrial cancer patients. We screened the top 50% of the genes in TCGA for weighted gene correlation network analysis (WGCNA) to explore mRNAsi-related gene sets. Among these mRNAsi-related genes, we further screened for those related to the prognosis of endometrial cancer patients via univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Using stepwise multivariate Cox regression analysis, a stemness index-related risk signature was constructed. Finally, we identified potential prognostic biomarkers for endometrial cancer by combining the GEO database and immunohistochemical staining.

Results

The mRNAsi of endometrial cancer samples was significantly higher than that of normal samples and was related to the International Federation of Gynecology and Obstetrics (FIGO) stage, pathological grade, postoperative tumor status, and overall survival of endometrial cancer patients. We identified 21 mRNAsi-related gene modules, and 1,324 genes were obtained from the most relevant module. TCGA samples were divided into training and validation cohorts, and the training cohort was used to construct a nine-mRNAsi-related gene signature (B3GAT2, CD3EAP, DMC1, FRMPD3, LINC01224, LINC02068, LY6H, NR6A1, and TLE2). High-risk and low-risk patients had significant prognostic differences, and the risk signature could accurately predict their 1-, 3-, and 5-year survival. The nomogram composed of risk score and multiple clinicopathological features could accurately predict 1-, 3-, and 5-year survival. Finally, CD3EAP was found to be a novel prognostic biomarker for endometrial cancer.

Conclusion

Endometrial cancer cell stemness is related to patient prognosis. The nine-gene risk signature is an independent prognostic factor and can accurately predict endometrial cancer patient prognosis.

Uterine disorders affecting female fertility: what are the molecular functions altered in endometrium?

OBJECTIVE

To determine the molecular functions of genes exhibiting altered expression in the endometrium of women with uterine disorders affecting fertility.

DESIGN

Retrospective analysis integrating case and control data from multiple cohorts with endometrium gene expression in women with uterine disorders.

SETTING

Infertility research department affiliated with a university hospital.

PATIENT(S)

Two hundred and forty women, 121 of whom were controls, 119 of whom had endometrial adenocarcinoma (ADC), recurrent implantation failure (RIF), recurrent pregnancy loss (RPL), or stage II-IV endometriosis.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Genomewide gene expression and altered molecular functions in the endometrium of each uterine disorder.

RESULT(S)

Using robust analysis methods, we identified statistically significantly altered endometrial functions in all the uterine disorders. Cell cycle alterations were shared among all the pathologies investigated. Endometriosis was characterized by the down-regulation of ciliary processes. Among the endometriosis, ADC, and RIF samples, mitochondrial dysfunction and protein degradation were shared dysregulated processes. In addition, RPL had the most distinct functional profile, and 95% of affected functions were down-regulated.

CONCLUSION(S)

The most robust functions dysregulated in the endometrium of patients with uterine disorders across sample cohorts implicated an endometrial factor at the gene expression level. This shared endometrial factor affects endometrial receptivity processes.

Identification and Validation of Six Autophagy-related Long Non-coding RNAs as Prognostic Signature in Colorectal Cancer

Colorectal cancer (CRC) is a commonly occurring tumour with poor prognosis. Autophagy-related long non-coding RNAs (lncRNAs) have received much attention as biomarkers for cancer prognosis and diagnosis. However, few studies have focused on their prognostic predictive value specifically in CRC. This research aimed to construct a robust autophagy-related lncRNA prognostic signature for CRC. Autophagy-related lncRNAs from The Cancer Genome Atlas database were screened using univariate Cox, LASSO, and multivariate Cox regression analyses, and the resulting key lncRNAs were used to establish a prognostic risk score model. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) analysis was performed to detect the expression of several lncRNAs in cancer tissues from CRC patients and in normal tissues adjacent to the cancer tissues. A prognostic signature comprising lncRNAs AC125603.2, LINC00909, AC016876.1, MIR210HG, AC009237.14, and LINC01063 was identified in patients with CRC. A graphical nomogram based on the autophagy-related lncRNA signature was developed to predict CRC patients' 1-, 3-, and 5-year survival. Overall survival in patients with low risk scores was significantly better than in those with high risk scores (P < 0.0001); a similar result was obtained in an internal validation sample. The nomogram was shown to be suitable for clinical use and gave correct predictions. The 1- and 3-year values of the area under the receiver operating characteristic curve were 0.797 and 0.771 in the model sample, and 0.656 and 0.642 in the internal validation sample, respectively. The C-index values for the verification samples and training samples were 0.756 (95% CI = 0.668-0.762) and 0.715 (95% CI = 0.683-0.829), respectively. Gene set enrichment analysis showed that the six autophagy-related lncRNAs were greatly enriched in CRC-related signalling pathways, including p53 and VEGF signalling. The qRT-PCR results showed that the expression of lncRNAs in CRC was higher than that in adjacent tissues, consistent with the expression trends of lncRNAs in the CRC data set. In summary, we established a signature of six autophagy-related lncRNAs that could effectively guide clinical prediction of prognosis in patients with CRC. This lncRNA signature has significant clinical implications for improving the prediction of outcomes and, with further prospective validation, could be used to guide tailored therapy for CRC patients.

On the NF-Y regulome as in ENCODE (2019)

NF-Y is a trimeric Transcription Factor -TF- which binds with high selectivity to the conserved CCAAT element. Individual ChIP-seq analysis as well as ENCODE have progressively identified locations shared by other TFs. Here, we have analyzed data introduced by ENCODE over the last five years in K562, HeLa-S3 and GM12878, including several chromatin features, as well RNA-seq profiling of HeLa cells after NF-Y inactivation. We double the number of sequence-specific TFs and co-factors reported. We catalogue them in 4 classes based on co-association criteria, infer target genes categorizations, identify positional bias of binding sites and gene expression changes. Larger and novel co-associations emerge, specifically concerning subunits of repressive complexes as well as RNA-binding proteins. On the one hand, these data better define NF-Y association with single members of major classes of TFs, on the other, they suggest that it might have a wider role in the control of mRNA production.

The ongoing ENCODE consortium represents a useful compendium of locations of TFs, chromatin marks, gene expression data. In previous reports, we identified modules of CCAAT-binding NF-Y with individual TFs. Here, we analyzed all 363 factors currently present: 68 with enrichment of CCAAT in their locations, 38 with overlap of peaks. New sequence-specific TFs, co-activators and co-repressors are reported. Co-association patterns correspond to specific targeted genes categorizations and gene expression changes, as assessed by RNA-seq after NF-Y inactivation. These data widen and better define a coherent model of synergy of NF-Y with selected groups of TFs and co-factors.

Bioinformatics Analysis of Key Genes and Pathways of Cervical Cancer

Background and Objective

Globally, cervical cancer (CC) is the fourth most common cancer affecting women. Although effective screening reduces its incidence, it remains one of the most serious cancers threatening the health of women. Therefore, the purpose of this study is to find new genes that can be used as potential biomarkers for the prognosis of CC.

Methods and Results

After downloading three datasets such as GSE6791, GSE63678, and GSE63514 from the Gene Expression Omnibus (GEO), we combined the expression matrixes and analyzed them to obtain the differential expressed genes (DEGs). Next, using the STRING website, we performed the protein interaction network analysis. Subsequently, hub genes were screened using the R and Cytoscape software. Then, the expression difference and survival analyses of the hub genes were confirmed using GIPIA. Here, we established that the KNTC1 gene was correlated to the overall survival prognosis of CC. Besides, the expression of the KNTC1 gene in the GSE63514 dataset was significantly different from that of the normal cervix, cervical pre-cancerous lesions, and CC. Consequently, immunohistochemistry analysis showed that the results have a definite diagnostic value.

Conclusion

The KNTC1 gene could be linked with the pathophysiology of CC and maybe one of the early diagnostic markers for the diagnosis of cervical pre-cancerous lesions.

TTK, CDC25A, and ESPL1 as Prognostic Biomarkers for Endometrial Cancer

Objective

Endometrial cancer (EC) is one of the most common malignant gynaecological tumours worldwide. This study was aimed at identifying EC prognostic genes and investigating the molecular mechanisms of these genes in EC.

Methods

Two mRNA datasets of EC were downloaded from the Gene Expression Omnibus (GEO). The GEO2R tool and Draw Venn Diagram were used to identify differentially expressed genes (DEGs) between normal endometrial tissues and EC tissues. Then, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Next, the protein-protein interactions (PPIs) of these DEGs were determined by the Search Tool for the Retrieval of Interacting Genes (STRING) tool and Cytoscape with Molecular Complex Detection (MCODE). Furthermore, Kaplan-Meier survival analysis was performed by UALCAN to verify genes associated with significantly poor prognosis. Next, Gene Expression Profiling Interactive Analysis (GEPIA) was used to verify the expression levels of these selected genes. Additionally, a reanalysis of the KEGG pathways was performed to understand the potential biological functions of selected genes. Finally, the associations between these genes and clinical features were analysed based on TCGA cancer genomic datasets for EC.

Results

In EC tissues, compared with normal endometrial tissues, 147 of 249 DEGs were upregulated and 102 were downregulated. A total of 64 upregulated genes were assembled into a PPI network. Next, 14 genes were found to be both associated with significantly poor prognosis and highly expressed in EC tissues. Reanalysis of the KEGG pathways found that three of these genes were enriched in the cell cycle pathway. TTK, CDC25A, and ESPL1 showed higher expression in cancers with late stage and higher tumour grade.

Conclusion

In summary, through integrated bioinformatics approaches, we found three significant prognostic genes of EC, which might be potential therapeutic targets for EC patients.

Identification and prognostic value of DLGAP5 in endometrial cancer

Background

Endometrial cancer poses a serious threat to women’s health worldwide, and its pathogenesis, although actively explored, is not fully understood. DLGAP5 is a recently identified cell cycle-regulation gene not reported in endometrial cancer. This study was aiming to analyze the role of DLGAP5 in tumorigenesis and development and to investigate its prognostic significance of patients with endometrial cancer.

Methodology

Microarray datasets (GSE17025, GSE39099 and GSE63678) from the GEO database were used for comparative analysis, and their intersection was obtained by applying the Venn diagram, and DLGAP5 was selected as the target gene. Next, transcriptome data (n = 578) was downloaded from TCGA-UCEC to analyze the mRNA expression profile of DLGAP5. Then, immunohistochemical data provided by HPA were used to identify the different protein expression levels of DLGAP5 in tumor tissues and normal tissues. Subsequently, the prognostic meaning of DLGAP5 in patients with endometrial cancer was explored based on survival data from TCGA-UCEC (n = 541). Finally, the reliability of DLGAP5 expression was verified by RT-qPCR.

Results

Transcriptome data from TCGA-UCEC, immunohistochemical data from HPA, and RT-qPCR results from clinical samples were used for triple validation to confirm that the expression of DLGAP5 in endometrial cancer tissues was significantly higher than that in normal endometrial tissues. Kaplan–Meier survival analysis announced that the expression level of DLGAP5 was negatively correlated with the overall survival of patients with endometrial cancer.

Conclusions

DLGAP5 is a potential oncogene with cell cycle regulation, and its overexpression can predict the poor prognosis of patients with endometrial cancer. As a candidate target for the diagnosis and treatment of endometrial cancer, it is worthwhile to make further study to reveal the carcinogenicity of DLGAP5 and the mechanism of its resistance of organisms.

Integrating pathology, chromosomal instability and mutations for risk stratification in early-stage endometrioid endometrial carcinoma

Background

Risk stratifications for endometrial carcinoma (EC) depend on histopathology and molecular pathology. Histopathological risk stratification lacks reproducibility, neglects heterogeneity and contributes little to surgical procedures. Existing molecular stratification is useless in patients with specific pathological or molecular characteristics and cannot guide postoperative adjuvant radiotherapies. Chromosomal instability (CIN), the numerical and structural alterations of chromosomes resulting from ongoing errors of chromosome segregation, is an intrinsic biological mechanism for the evolution of different prognostic factors of histopathology and molecular pathology and may be applicable to the risk stratification of EC.

Results

By analyzing CIN25 and CIN70, two reliable gene expression signatures for CIN, we found that EC with unfavorable prognostic factors of histopathology or molecular pathology had serious CIN. However, the POLE mutant, as a favorable prognostic factor, had elevated CIN signatures, and the CTNNB1 mutant, as an unfavorable prognostic factor, had decreased CIN signatures. Only if these two mutations were excluded were CIN signatures strongly prognostic for outcomes in different adjuvant radiotherapy subgroups. Integrating pathology, CIN signatures and POLE/CTNNB1 mutation stratified stageIendometrioid EC into four groups with improved risk prognostication and treatment recommendations.

Conclusions

We revealed the possibility of integrating histopathology and molecular pathology by CIN for risk stratification in early-stage EC. Our integrated risk model deserves further improvement and validation.

TOP2A and CENPF are synergistic master regulators activated in cervical cancer

Background

Identification of master regulators (MRs) using transcriptome data in cervical cancer (CC) could help us to develop biomarkers and find novel drug targets to fight this disease.

Methods

We performed differential expression (DE) analyses of public microarray and RNA-seq transcriptome data of CC and normal cervical tissues (N). Virtual Inference of Protein activity by Enriched Regulon analysis (VIPER) was used to convert the DE outcomes to differential activity (DA) signature for MRs. Synergy analysis was conducted to study synergistic effect of MR-pairs. TCGA and microarray data were used to test the association of expression of a MR and a clinical feature or a molecular feature (e.g. somatic mutations). Various bioinformatic tools/websites (DAVID, GEPIA2, Oncomine, cBioPortal) were used to analyze the expression of the top MRs and their regulons.

Results

Ten DE and 10 DA signatures were generated for CC. Two MRs, DNA topoisomerase II alpha (TOP2A) and centromere protein F (CENPF) were found to be up-regulated, activated and synergistic in CC compared to N across the 10 datasets. The two MRs activate a common set of genes (regulons) with functions in cell cycle, chromosome, DNA damage etc. Higher expression of CENPF was associated with metastasis. High expression of both MRs is associated with somatic mutation of a set of genes including tumor suppressors (TP53, MSH2, RB1) and genes involved in cancer pathways, cell cycle, DNA damage and repair. The magnitude of up-regulation and the absolute expression level of both MRs in CC are significantly higher compared to many other cancer types.

Conclusion

TOP2A and CENPF are a synergistic pair of MRs that are overexpressed and activated in CC. Their high expression is correlated with some prognosis features (e.g. metastasis) and molecular features (e.g. somatic mutations) and distinctly high in CC vs. many other cancer types. They may be good biomarkers and anticancer drug targets for CC.

Identification of core genes in the progression of endometrial cancer and cancer cell-derived exosomes by an integrative analysis

Endometrial cancer is one of the most prevalent tumors of the female reproductive system causing serious health effects to women worldwide. Although numerous studies, including analysis of gene expression profile and cellular microenvironment have been reported in this field, pathogenesis of this disease remains unclear. In this study, we performed a system bioinformatics analysis of endometrial cancer using the Gene Expression Omnibus (GEO) datasets (GSE17025, GSE63678, and GSE115810) to identify the core genes. In addition, exosomes derived from endometrial cancer cells were also isolated and identified. First, we analyzed the differentially expressed genes (DEGs) between endometrial cancer tissues and normal tissues in clinic samples. We found that HAND2-AS1, PEG3, OGN, SFRP4, and OSR2 were co-expressed across all 3 datasets. Pathways analysis showed that several pathways associated with endometrial cancer, including "p53 signaling pathway", "Glutathione metabolism", "Cell cycle", and etc. Next, we selected DEGs with highly significant fold change and co-expressed across the 3 datasets and validated them in the TCGA database using Gene Expression Profiling Interactive Analysis (GEPIA). Finally, we performed a survival analysis and identified four genes (TOP2A, ASPM, EFEMP1, and FOXL2) that play key roles in endometrial cancer. We found up-regulation of TOP2A and ASPM in endometrial cancer tissues or cells, while EFEMP1 and FOXL2 were down-regulated. Furthermore, we isolated exosomes from the culturing supernatants of endometrial cancer cells (Ishikawa and HEC-1-A) and found that miR-133a, which regulates expression of FOXL2, were present in exosomes and that they could be delivered to normal endometrial cells. The common DEGs, pathways, and exosomal miRNAs identified in this study might play an important role in progression as well as diagnosis of endometrial cancer. In conclusion, our results provide insights into the pathogenesis and risk assessment of endometrial cancer. Even so, further studies are required to elucidate on the precise mechanism of action of these genes in endometrial cancer.

Combining Bioinformatics and Experiments to Identify and Verify Key Genes with Prognostic Values in Endometrial Carcinoma

Endometrial carcinoma(EC) is the most common cancer of female reproductive system, thus requiring for new effective biomarkers which could predict the onset of EC and poor prognosis. Our study integrated two GEO datasets(i.e.GSE63678, GSE17025) and TCGA(The Cancer Genome Atlas ) UCEC data to screen out 344 common differentially expressed genes(DEGs), which were further analyzed by GO(gene ontology) functions and KEGG(Kyoto Encyclopedia of Gene and Genome) pathways. KEGG analysis results showed these DEGs were mainly enriched in cell cycle, oocyte meiosis, cellular senescence, carbon metabolism and p53 signaling pathway. Top 20 hub genes with higher degree were selected from PPI(protein-protein interaction) network and 15 of them were associated with the prognosis of EC, that is, CCNB2, CDC20, BUB1B, UBE2C, AURKB, FOXM1, NCAPG, RRM2, TPX2, DLGAP5, CDCA8, CDC45, MKI67, BUB1, KIF2C. UBE2C(Ubiquitin Conjugating Enzyme E2 C) was chosen for further validation in TCGA cohort on mRNA level and in our patient samples on protein level by immunohistochemistry. UBE2C was significantly highly expressed in endometrial carcinoma, and its expression level was associated with advanced FIGO staging and poor prognosis. Cox risk model demonstrated high UBE2C expression was an independent risk factor. Somatic mutations, elevated copy number, DNA hypomethylation all contributed to its overexpression. Therefore, by combination of bioinformatics and experiment, our study provided a unique insight into the pathogenesis and molecular mechanisms underlying EC and discovered new biomarkers for early diagnosis and prognostic prediction. UBE2C could serve as a potential marker to predict poor prognosis and as a therapeutic target.

Identification of key candidate genes and pathways in endometrial cancer: Evidence from bioinformatics analysis

Endometrial cancer (EC) is the fourth most common cancer in women worldwide. Although researchers are exploring the biological processes of tumorigenesis and development of EC, the gene interactions and biological pathways of EC are not accurately verified. In the present study, bioinformatics methods were used to screen for key candidate genes and pathways that were associated with EC and to reveal the possible mechanisms at molecular level. Microarray datasets (GSE63678, GSE17025 and GSE3013) from the Gene Expression Omnibus database were downloaded and 118 differentially expressed genes (DEGs) were selected using a Venn diagram. Functional enrichment analyses were performed on the DEGs. A protein-protein interaction network was constructed, including the module analysis. A total of 11 hub genes were identified from the DEGs, and functional enrichment analyses were performed to clarify their possible biological processes. A total of 118 DEGs were selected from three mRNA datasets. Functional enrichment demonstrated 27 downregulated genes that were primarily involved in the positive regulation of transcription from RNA polymerase II promoter, protein binding and the nucleus. A total of 91 upregulated DEGs were mainly associated with cell division, protein binding and the nucleus. Pathway analysis indicated that the downregulated DEGs were mainly enriched in pathways associated with cancer, and the upregulated DEGs were mainly enriched in the cell cycle. The 11 hub genes were primarily enriched in the cell cycle, oocyte meiosis, progesterone-mediated oocyte maturation, the p53 signaling pathway and viral carcinogenesis. The integrated analysis showed that cyclin B1, ubiquitin conjugating enzyme E2 C and cell division cycle 20 may participate in the tumorigenesis, development and invasion of EC. In conclusion, the hub genes and pathways identified in the present study contributed to the understanding of carcinogenesis and progression of EC at the mechanistic and molecular-biological level. As candidate targets for the diagnosis and treatment of EC, these genes deserve further investigation.

Novel Genomic Biomarker Candidates for Cervical Cancer As Identified by Differential Co-Expression Network Analysis

Cervical cancer is the second most common malignancy and the third reason for mortality among women in developing countries. Although infection by the oncogenic human papilloma viruses is a major cause, genomic contributors are still largely unknown. Network analyses, compared with candidate gene studies, offer greater promise to map the interactions among genomic loci contributing to cervical cancer risk. We report here a differential co-expression network analysis in five gene expression datasets (GSE7803, GSE9750, GSE39001, GSE52903, and GSE63514, from the Gene Expression Omnibus) in patients with cervical cancer and healthy controls. Kaplan-Meier Survival and principle component analyses were employed to evaluate prognostic and diagnostic performances of biomarker candidates, respectively. As a result, seven distinct co-expressed gene modules were identified. Among these, five modules (with sizes of 9-45 genes) presented high prognostic and diagnostic capabilities with hazard ratios of 2.28-11.3, and diagnostic odds ratios of 85.2-548.8. Moreover, these modules were associated with several key biological processes such as cell cycle regulation, keratinization, neutrophil degranulation, and the phospholipase D signaling pathway. In addition, transcription factors ETS1 and GATA2 were noted as common regulatory elements. These genomic biomarker candidates identified by differential co-expression network analysis offer new prospects for translational cancer research, not to mention personalized medicine to forecast cervical cancer susceptibility and prognosis. Looking into the future, we also suggest that the search for a molecular basis of common complex diseases should be complemented by differential co-expression analyses to obtain a systems-level understanding of disease phenotype variability.

Identification of key pathways and genes in endometrial cancer using bioinformatics analyses

Endometrial cancer (EC) is one of the most common gynecological cancer types worldwide. However, to the best of our knowledge, its underlying mechanisms remain unknown. The current study downloaded three mRNA and microRNA (miRNA) datasets of EC and normal tissue samples, GSE17025, GSE63678 and GSE35794, from the Gene Expression Omnibus to identify differentially expressed genes (DEGs) and miRNAs (DEMs) in EC tumor tissues. The DEGs and DEMs were then validated using data from The Cancer Genome Atlas and subjected to gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis. STRING and Cytoscape were used to construct a protein-protein interaction network and the prognostic effects of the hub genes were analyzed. Finally, miRecords was used to predict DEM targets and an miRNA-gene network was constructed. A total of 160 DEGs were identified, of which 51 genes were highly expressed and 100 DEGs were discovered from the PPI network. Three overlapping genes between the DEGs and the DEM targets, BIRC5, CENPF and HJURP, were associated with significantly worse overall survival of patients with EC. A number of DEGs were enriched in cell cycle, human T-lymphotropic virus infection and cancer-associated pathways. A total of 20 DEMs and 29 miRNA gene pairs were identified. In conclusion, the identified DEGs, DEMs and pathways in EC may provide new insights into understanding the underlying molecular mechanisms that facilitate EC tumorigenesis and progression.

Identification of key candidate genes and small molecule drugs in cervical cancer by bioinformatics strategy

Purpose

Cervical cancer (CC) is one of the most common malignant tumors among women. The present study aimed at integrating two expression profile datasets to identify critical genes and potential drugs in CC.

Materials and methods

Expression profiles, GSE7803 and GSE9750, were integrated using bioinformatics methods, including differentially expressed genes analysis, Kyoto Encyclopedia of Genes and Genomes pathway analysis, and protein–protein interaction (PPI) network construction. Subsequently, survival analysis was performed among the key genes using Gene Expression Profiling Interactive Analysis websites. Connectivity Map (CMap) was used to query potential drugs for CC.

Results

A total of 145 upregulated genes and 135 downregulated genes in CC were identified. The functional changes of these differentially expressed genes related to CC were mainly associated with cell cycle, DNA replication, p53 signaling pathway, and oocyte meiosis. A PPI network was identified by STRING with 220 nodes and 2,111 edges. Thirteen key genes were identified as the intersecting genes of the enrichment pathways and the top 20 nodes in PPI network. Survival analysis revealed that high mRNA expression of MCM2, PCNA, and RFC4 was significantly associated with longer overall survival, and the survival was significantly better in the low-expression RRM2 group. Moreover, CMap predicted nine small molecules as possible adjuvant drugs to treat CC.

Conclusion

Our study found key dysregulated genes involved in CC and potential drugs to combat it, which might provide insights into CC pathogenesis and might shed light on potential CC treatments.

FOXM1 as a prognostic biomarker promotes endometrial cancer progression via transactivation of SLC27A2 expression

Endometrial cancer (EC) is one of the most important gynecological cancers, but its pathogenesis is not clearly understood, and it also lacks an effective treatment. The nuclear transcriptional protein forkhead box protein M1 (FOXM1) has crucial functions in the development and progression of cancer and is treated as a prognostic biomarker and therapeutic target in many types of cancers. However, the situation and underlying mechanisms of FOXM1's involvement in EC is largely underestimated. In our present study, we found FOXM1 was overexpressed in EC, including endometrioid (EEC) and serous (SEC). High expression of FOXM1 was meaningfully associated with a poor prognosis of EC patients as well as with EC pathological stages and clinical grades. Knocking down FOXM1 could significantly reduce the proliferation and migration capacity of AN3CA and ISHIKAWA cells. Furthermore, our RNA-seq results indicated that the knockdown of FOXM1 mainly affects downstream metabolic genes in EC cells. Finally, we also discovered one potential functional pathway, FOXM1-SLC27A2, which may contribute to EC progression. Taken together, the high expression of FOXM1 is closely associated with the prognosis, pathological stages, and clinical grades of EC patients. FOXM1 can promote the proliferation and migration of EC cells. Through SLC27A2, FOXM1 may influence the metabolic activity of EC cells, and FOXM1-SLC27A signaling could be treated as a potential cellular target for a therapeutic strategy of EC.

Exploration of the molecular mechanisms of cervical cancer based on mRNA expression profiles and predicted microRNA interactions

The molecular mechanisms of cervical cancer have been minimally explored with multi-omics data. In the present study, mRNA expression profiles were analyzed and combined with predicted miRNA interactions to contribute to the characterization of the underlying regulatory mechanisms of cervical cancer. A total of 92 significantly differentially expressed genes (DEGs) were identified in 33 tumor samples by comparison with 29 normal samples. mRNA-miRNA interaction network analysis revealed that 16 out of the 92 DEGs, including checkpoint kinase 1 (CHEK1), SRY-box 17 (SOX17), centrosomal protein 55, cyclin dependent kinase inhibitor 2A (CDKN2A), and inhibitor of DNA binding 4, were the targets of 4 miRNAs which were previously reported to be involved in the regulation of cervical cancer. Tumor and normal samples could be distinctly classified into two groups based on the expression of the 16 DEGs. Furthermore, survival analysis using the SurvExpress database indicated that the 16 DEGs could individually significantly differentiate low- and high-risk cervical cancer groups. Overall, multiple biological processes are likely to participate in the progression of cervical cancer based on the pathway and function enrichment identified for the DEGs. The dysregulation of SOX17 is associated with the regulation of embryonic development, the determination of cell fate and likely promotes cancer cell transformation. The dysregulation of CHEK1 and CDKN2A further promote cancer cell proliferation by affecting the cell cycle checkpoint in response to DNA damage. The identification of critical genes and biological processes associated with cervical cancer may be beneficial for the exploration of the molecular mechanisms.

Proteomic Analysis of Normal and Cancer Cervical Cell Lines Reveals Deregulation of Cytoskeleton-associated Proteins

BACKGROUND

Both HPV-positive and -negative cervical cancers are primarily associated with features of cell cycle and cytoskeletal disruption; however, the actual biological processes affected remain elusive. To this end, we systematically characterized the intracellular proteomic profiles of four distinct and informative cervical cell lines.

MATERIALS AND METHODS

Cell extracts from a normal cervical (HCK1T) and three cervical cancer cell lines, one HPV-negative (C33A), and two HPV-positive, SiHa (HPV16+) and HeLa (HPV18+), were analyzed by 2-dimensional electrophoresis and differentially expressed proteins were identified by MALDI-TOF mass spectrometry, while differential expression was confirmed by western blot analysis.

RESULTS

In total, 113 proteins were found differentially expressed between the normal and the cervical cancer lines. Bioinformatics analysis revealed the actin cytoskeleton signaling pathway to be significantly affected, while up-regulation of cofilin-1, an actin depolymerizing factor, was documented and further validated by western blotting. Furthermore, two-way comparisons among the four cell lines, revealed a set of 18 informative differentially expressed proteins.

CONCLUSION

These novel identified proteins provide the impetus for further functional studies to dissect the mechanisms operating in the two distinct pathways of cervical carcinogenesis.

Prognostic role of NF-YA splicing isoforms and Lamin A status in low grade endometrial cancer

Although most cases of low grade (G1) endometrial cancer (EC) do not behave aggressively, in rare instances, can progress in a highly aggressive manner. In this study we analyzed formalin-fixed, paraffin-embedded (FFPE) EC tissues to find novel clinical and biological features to help diagnosis and treatment of G1 ECs s in order to better stratify patient risk of recurrence. A retrospective cohort of FFPE specimens from patients with EC (n=87) and benign tissue specimens (NE) from patients who underwent a hysterectomy to treat other benign disease (n = 13) were collected. Total RNA and proteins were extracted and analyzed, respectively, by quantitative PCR and western blotting. NF-YAs is expressed and lamin A is down-modulated in all high grade (G2 and G3) ECs. In G1 ECs, NF-YAs expression is heterogeneous being expressed only in a subset of these tumours. Interestingly, the G1 ECs that express NF-YAs display low levels of lamin A similar to those present in G2 and G3 ECs. Of note, this pattern of NF-YAs and lamin A expression correlates with tumor aggressiveness assessed by comparative analysis with estrogen receptor (ER) status and epithelial-mesenchymal transition (EMT) markers thus suggesting its potential role as biomarker of tumour aggressiveness in G1 EC. In all grade ECs, lamin A is strongly downmodulated, being its expression inversely correlated with tumor aggressiveness and its loss of expression. We identified NF-YAs and lamin A expression levels as novel potential biomarkers useful to identify G1 ECs patients with risk of recurrence.

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice.

Network analysis revealed aurora kinase dysregulation in five gynecological types of cancer

Gene markers are crucial for cancer prognosis and treatment. Previous studies have placed greater emphasis on individual diagnostic genes, thereby ignoring systemic-level attributes across diseases. Female-specific cells namely, breast, endometrium, cervical, ovarian and vulvar cells are highly susceptible to cancer. To date, a limited number of molecular studies have been performed that evaluate common biological processes across gynecological types of cancer. Differentially expressed genes in breast, cervical, endometrial, vulvar and ovarian cancer were utilized to construct protein-protein interaction networks, and to identify a common module across the five cancer types. A single common module with 8 nodes and 26 edges was mined among the five cancer systems. In total, four hub genes were present across the five cancer gene sets. Genes in the common module were enriched for the common pathways and associated diseases. The aurora kinase pathway was revealed to be conserved across the five cancer types surveyed. The present study, therefore, revealed that the aurora kinase pathway has a crucial function in the pathogenesis of the five aforementioned gynecological types of cancer through cross-tumor conservation.

High-Risk Alphapapillomavirus Oncogenes Impair the Homologous Recombination Pathway

Persistent high-risk genus human Alphapapillomavirus (HPV) infections cause nearly every cervical carcinoma and a subset of tumors in the oropharyngeal tract. During the decades required for HPV-associated tumorigenesis, the cellular genome becomes significantly destabilized. Our analysis of cervical tumors from four separate data sets found a significant upregulation of the homologous-recombination (HR) pathway genes. The increased abundance of HR proteins can be replicated in primary cells by expression of the two HPV oncogenes (E6 and E7) required for HPV-associated transformation. HPV E6 and E7 also enhanced the ability of HR proteins to form repair foci, and yet both E6 and E7 reduce the ability of the HR pathway to complete double-strand break (DSB) repair by about 50%. The HPV oncogenes hinder HR by allowing the process to begin at points in the cell cycle when the lack of a sister chromatid to serve as a homologous template prevents completion of the repair. Further, HPV E6 attenuates repair by causing RAD51 to be mislocalized away from both transient and persistent DSBs, whereas HPV E7 is only capable of impairing RAD51 localization to transient lesions. Finally, we show that the inability to robustly repair DSBs causes some of these lesions to be more persistent, a phenotype that correlates with increased integration of episomal DNA. Together, these data support our hypothesis that HPV oncogenes contribute to the genomic instability observed in HPV-associated malignancies by attenuating the repair of damaged DNA.IMPORTANCE This study expands the understanding of HPV biology, establishing a direct role for both HPV E6 and E7 in the destabilization of the host genome by blocking the homologous repair of DSBs. To our knowledge, this is the first time that both viral oncogenes were shown to disrupt this DSB repair pathway. We show that HPV E6 and E7 allow HR to initiate at an inappropriate part of the cell cycle. The mislocalization of RAD51 away from DSBs in cells expressing HPV E6 and E7 hinders HR through a distinct mechanism. These observations have broad implications. The impairment of HR by HPV oncogenes may be targeted for treatment of HPV⁺ malignancies. Further, this attenuation of repair suggests HPV oncogenes may contribute to tumorigenesis by promoting the integration of the HPV genome, a common feature of HPV-transformed cells. Our data support this idea since HPV E6 stimulates the integration of episomes.

Cervical Cancer Cell Line Secretome Highlights the Roles of Transforming Growth Factor-Beta-Induced Protein ig-h3, Peroxiredoxin-2, and NRF2 on Cervical Carcinogenesis

Cancer cells acquire unique secretome compositions that contribute to tumor development and metastasis. The aim of our study was to elucidate the biological processes involved in cervical cancer, by performing a proteomic analysis of the secretome from the following informative cervical cell lines: SiHa (HPV16+), HeLa (HPV18+), C33A (HPV-), and HCK1T (normal). Proteins were analyzed by 2D gel electrophoresis coupled to MALDI-TOF-MS. Enrichment of secreted proteins with characteristic profiles for each cell line was followed by the identification of differentially expressed proteins. Particularly, transforming growth factor-beta-induced protein ig-h3 (Beta ig-h3) and peroxiredoxin-2 (PRDX2) overexpression in the secretome of cancer cell lines was detected and confirmed by Western blot. Bioinformatics analysis identified the transcription factor NRF2 as a regulator of differentially expressed proteins in the cervical cancer secretome. NRF2 levels were measured by both Western blot and Multiple Reaction Monitoring (MRM) in the total cell extract of the four cell lines. NRF2 was upregulated in SiHa and C33A compared to HCK1T. In conclusion, the secreted proteins identified in cervical cancer cell lines indicate that aberrant NRF2-mediated oxidative stress response (OSR) is a prominent feature of cervical carcinogenesis.

NF-Y in cancer: Impact on cell transformation of a gene essential for proliferation

NF-Y is a ubiquitous heterotrimeric transcription factor with a binding affinity for the CCAAT consensus motif, one of the most common cis-acting element in the promoter and enhancer regions of eukaryote genes in direct (CCAAT) or reverse (ATTGG) orientation. NF-Y consists of three subunits, NF-YA, the regulatory subunit of the trimer, NF-YB, and NF-YC, all required for CCAAT binding. Growing evidence in cells and animal models support the notion that NF-Y, driving transcription of a plethora of cell cycle regulatory genes, is a key player in the regulation of proliferation. Proper control of cellular growth is critical for cancer prevention and uncontrolled proliferation is a hallmark of cancer cells. Indeed, during cell transformation aberrant molecular pathways disrupt mechanisms controlling proliferation and many growth regulatory genes are altered in tumors. Here, we review bioinformatics, molecular and functional evidence indicating the involvement of the cell cycle regulator NF-Y in cancer-associated pathways. This article is part of a Special Issue entitled: Nuclear Factor Y in Development and Disease, edited by Prof. Roberto Mantovani.