Identification of Significant Gene Signatures and Prognostic Biomarkers for Patients With Cervical Cancer by Integrated Bioinformatic Methods

3D Printing for Cancer Diagnosis: What Unique Advantages Are Gained?

Cancer is a complex disease with global significance, necessitating continuous advancements in diagnostics and treatment. 3D printing technology has emerged as a revolutionary tool in cancer diagnostics, offering immense potential in detection and monitoring. Traditional diagnostic methods have limitations in providing molecular and genetic tumor information that is crucial for personalized treatment decisions. Biomarkers have become invaluable in cancer diagnostics, but their detection often requires specialized facilities and resources. 3D printing technology enables the fabrication of customized sensor arrays, enhancing the detection of multiple biomarkers specific to different types of cancer. These 3D-printed arrays offer improved sensitivity, allowing the detection of low levels of biomarkers, even in complex samples. Moreover, their specificity can be fine-tuned, reducing false-positive and false-negative results. The streamlined and cost-effective fabrication process of 3D printing makes these sensor arrays accessible, potentially improving cancer diagnostics on a global scale. By harnessing 3D printing, researchers and clinicians can enhance early detection, monitor treatment response, and improve patient outcomes. The integration of 3D printing in cancer diagnostics holds significant promise for the future of personalized cancer care.

Integrating network pharmacology approaches for the investigation of multi-target pharmacological mechanism of 6-shogaol against cervical cancer

Traditional treatment of cancer has been plagued by a number of obstacles, such as multiple drug resistance, toxicity and financial constraints. In contrast, phytochemicals that modulate a variety of molecular mechanisms are garnering increasing interest in complementary and alternative medicine. Therefore, an approach based on network pharmacology was used in the present study to explore possible regulatory mechanisms of 6-shogaol as a potential treatment for cervical cancer (CC). A number of public databases were screened to collect information on the target genes of 6-shogaol (SuperPred, Targetnet, Swiss target prediction and PharmMapper), while targets pertaining to CC were taken from disease databases (DisGeNet and Genecards) and gene expression omnibus (GEO) provided expression datasets. With STRING and Cytoscape, protein-protein interactions (PPI) were generated and topology analysis along with CytoNCA were used to identify the Hub genes. The Gene Ontology (GO) database Enrichr was used to annotate the target proteins, while, using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database, signaling pathway enrichment analysis was conducted. Molecular docking and survival analysis for the Hub genes revealed four genes (HSP90AA1, HRAS, ESR1 and EGFR) with lowest binding energy and majority of the Hub genes (EGFR, SRC, CASP-3, HSP90AA1, MTOR, MAPK-1, MDM2 and ESR1) were linked with the overall survival of CC patients. In conclusion, the present study provides the scientific evidence which strongly supports the use of 6-shogoal as an inhibitor of cellular proliferation, growth, migration as well as inducer of apoptosis via targeting the hub genes involved in the growth of CC.Communicated by Ramaswamy H. Sarma.

Bioinformatics and cheminformatics approaches to identify pathways, molecular mechanisms and drug substances related to genetic basis of cervical cancer

Cervical cancer (CC) is a global threat to women and our knowledge is frighteningly little about its underlying genomic contributors. Our research aimed to understand the underlying molecular and genetic mechanisms of CC by integrating bioinformatics and network-based study. Transcriptomic analyses of three microarray datasets identified 218 common differentially expressed genes (DEGs) within control samples and CC specimens. KEGG pathway analysis revealed pathways in cell cycle, drug metabolism, DNA replication and the significant GO terms were cornification, proteolysis, cell division and DNA replication. Protein-protein interaction (PPI) network analysis identified 20 hub genes and survival analyses validated CDC45, MCM2, PCNA and TOP2A as CC biomarkers. Subsequently, 10 transcriptional factors (TFs) and 10 post-transcriptional regulators were detected through TFs-DEGs and miRNAs-DEGs regulatory network assessment. Finally, the CC biomarkers were subjected to a drug-gene relationship analysis to find the best target inhibitors. Standard cheminformatics method including in silico ADMET and molecular docking study substantiated PD0325901 and Selumetinib as the most potent candidate-drug for CC treatment. Overall, this meticulous study holds promises for further in vitro and in vivo research on CC diagnosis, prognosis and therapies. Communicated by Ramaswamy H. Sarma.

Human Papillomavirus 16 E6 and E7 Oncoproteins Alter the Abundance of Proteins Associated with DNA Damage Response, Immune Signaling and Epidermal Differentiation

The high-risk human papillomaviruses are oncogenic viruses associated with almost all cases of cervical carcinomas, and increasing numbers of anal, and oral cancers. Two oncogenic HPV proteins, E6 and E7, are capable of immortalizing keratinocytes and are required for HPV associated cell transformation. Currently, the influence of these oncoproteins on the global regulation of the host proteome is not well defined. Liquid chromatography coupled with quantitative tandem mass spectrometry using isobaric-tagged peptides was used to investigate the effects of the HPV16 oncoproteins E6 and E7 on protein levels in human neonatal keratinocytes (HEKn). Pathway and gene ontology enrichment analyses revealed that the cells expressing the HPV oncoproteins have elevated levels of proteins related to interferon response, inflammation and DNA damage response, while the proteins related to cell organization and epithelial development are downregulated. This study identifies dysregulated pathways and potential biomarkers associated with HPV oncoproteins in primary keratinocytes which may have therapeutic implications. Most notably, DNA damage response pathways, DNA replication, and interferon signaling pathways were affected in cells transduced with HPV16 E6 and E7 lentiviruses. Moreover, proteins associated with cell organization and differentiation were significantly downregulated in keratinocytes expressing HPV16 E6 + E7. High-risk HPV E6 and E7 oncoproteins are necessary for the HPV-associated transformation of keratinocytes. However their influence on the global dysregulation of keratinocyte proteome is not well documented. Here shotgun proteomics using TMT-labeling detected over 2500 significantly dysregulated proteins associated with E6 and E7 expression. Networks of proteins related to interferon response, inflammation and DNA damage repair pathways were altered.

Gene expression profiling of HPV-associated cervical carcinogenesis in formalin-fixed paraffin-embedded (FFPE) tissues using the NanoString nCounterTM platform

Infection by high-risk human papillomavirus (HPV) causes genetic alterations in host cervical cells with consequent changes in gene expression affecting downstream molecular pathways, leading to the development of cervical cancer. In this exploratory study, we aimed to identify the perturbed cellular pathways during the various stages of cervical carcinogenesis. Total RNA was extracted from three formalin-fixed paraffin-embedded (FFPE) samples each of normal cervix, HPV-infected low-grade squamous intraepithelial lesion (LSIL), high-grade SIL (HSIL) and squamous cell carcinoma (SCC). Gene expression profiling was performed using the 770-gene panel from NanoString nCounter® PanCancer Pathways Panel to identify differentially expressed genes (DEGs) and significantly associated pathways in each stage of cervical cancer development. We identified 121 DEGs involved in cervical carcinogenesis. In the transformation from normal cells to LSIL, the MAPK, transcriptional misregulation and JAK-STAT pathways are implicated, while IL1B may promote inflammation and indirectly activates MMP9, resulting in collagen breakdown and cell migration. The cell cycle - apoptosis pathway with upregulation of E2F1 and MCM2, and DNA repair genes BRCA2-BRIP1 and FANCA are crucial during the progression from LSIL to HSIL. In the final stage of progression to SCC, the cell cycle and signaling pathways, as well as upregulation of c-MYC appear essential. In conclusion, archived FFPE-derived tissue samples are a valuable resource for gene expression profiling. The postulated dysregulated pathways and genes provide a guide of the molecular mechanisms that may be involved in the development of HPV-associated cervical cancer, for further investigation and validation studies.

Transcriptional factor 3 binds to sirtuin 1 to activate the Wnt/β-catenin signaling in cervical cancer

Transcriptional factor 3 (TCF3, also termed E2A), first reported to exert crucial functions during lymphocyte development, has been revealed to participate in the pathogenesis of human cancers. The aim of this work was to investigate the function of TCF3 in cervical cancer (CC) and the molecular interactions. The bioinformatics prediction suggested that TCF3 was highly expressed in CC and linked to poor prognosis. Increased TCF3 expression was identified in CC cell lines, and its downregulation reduced proliferation and migration of CC cells in vitro as well as growth of xenograft tumors in vivo. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the TCF-3-related genes and genes showed differential expression between CC and normal tissues were mainly enriched in the Wnt/β-catenin pathway. TCF3 bound to sirtuin 1 (SIRT1) promoter for transcriptional activation, and SIRT1 promoted deacetylation and nuclear translocation of β-catenin in CC. SIRT1 overexpression blocked the role of TCF3 silencing and restored cell proliferation in vitro and tumor growth in vivo. Treatment with XAV-939, a β-catenin inhibitor, significantly suppressed the cell proliferation and tumor growth induced by SIRT1 overexpression. In conclusion, this study demonstrates that TCF3 augments progression of CC by activating SIRT1-mediated β-catenin signaling.

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.

Research Progress of PCNA in Reproductive System Diseases

Reproductive system diseases have become a public health problem that endangers human physical and mental health. The causes of reproductive diseases are complex and diverse. From a biological point of view, abnormal cell proliferation may affect important physiological functions of reproductive organs and cause various gynecological or andrological diseases. Proliferating cell nuclear antigen (PCNA) is the most commonly used indicator for detecting cell proliferation activity. The up- or downregulation of its expression is of great significance in reproductive system diseases. This review summarizes the significance of the latest research on PCNA expression in reproductive system diseases.

Identifying a cervical cancer survival signature based on mRNA expression and genome-wide copy number variations

Cervical cancer mortality is the second highest in gynecological cancers. This study developed a new model based on copy number variation data and mRNA data for overall survival prediction of cervical cancer. Differentially expressed genes from The Cancer Genome Atlas dataset detected by univariate Cox regression analysis were further simplified to six by least absolute shrinkage and selection operator (Lasso) and stepwise Akaike information criterion (stepAIC). The study developed a six-gene signature, which was further verified in independent dataset. Association between immune infiltration and risk score was investigated by immune score. The relation between the signature and functional pathways was examined by gene set enrichment analysis. Ninety-nine differentially expressed genes were detected, and C11orf80, FOXP3, GSN, HCCS, PGAM5, and RIBC2 were identified as key genes to construct a six-gene signature. The prognostic signature showed a significant correlation with overall survival (hazard ratio, HR = 3.45, 95% confidence interval (CI) = 2.08-5.72, p < 0.00001). Immune score showed a negative correlation with the risk score calculated by the signature (p < 0.05). Four immune-related pathways were closely associated with risk score (p < 0.0001). The six-gene prognostic signature was an effective tool to predict overall survival of cervical cancer. In conclusion, the newly identified six genes may be considered as new drug targets for cervical cancer treatment.

Molecular markers for cervical cancer screening

INTRODUCTION

Cervical cancer remains a significant healthcare problem, notably in low- to middle-income countries. While a negative test for hrHPV has a predictive value of more than 99.5%, its positive predictive value is less than 10% for CIN2+ stages. This makes the use of a so-called triage test indispensable for population-based screening to avoid referring women, that are ultimately at low risk of developing cervical cancer, to a gynecologist. This review will give an overview of tests that are based on epigenetic marker panels and protein markers.

AREAS COVERED

There is a medical need for molecular markers with a better predictive value to discriminate hrHPV-positive women that are at risk of developing cervical cancer from those that are not. Areas covered are epigenetic and protein markers as well as health economic considerations in view of the fact that most cases of cervical cancer arise in low-to-middle-income countries.

EXPERT OPINION

While there are biomarker assays based on changes at the nucleic acid (DNA methylation patterns, miRNAs) and at the protein level, they are not widely used in population screening. Combining nucleic acid-based and protein-based tests could improve the overall specificity for discriminating CIN2+ lesions that carry a low risk of progressing to cervical cancer within the screening interval from those that carry an elevated risk. The challenge is to reduce unnecessary referrals without an undesired increase in false-negative diagnoses resulting in cases of cervical cancer that could have been prevented. A further challenge is to develop tests for low-and middle-income countries, which is critical to reduce the worldwide burden of cervical cancer.

Prioritizing the candidate genes related to cervical cancer using the moment of inertia tensor

It is well known that cervical cancer poses the fourth most malignancy threat to women worldwide among all cancer types. There is a tremendous improvement in realizing the underlying molecular associations in cervical cancer. Several studies reported pieces of evidence for the involvement of various genes in the disease progression. However, with the ever-evolving bioinformatics tools, there has been an upsurge in predicting numerous genes responsible for cervical cancer progression and making it highly complex to target the genes for further evaluation. In this article, we prioritized the candidate genes based on the sequence similarity analysis with known cancer genes. For this purpose, we used the concept of the moment of inertia tensor, which reveals the similarities between the protein sequences more efficiently. Tensor for moment of inertia explores the similarity of the protein sequences based on the physicochemical properties of amino acids. From our analysis, we obtained 14 candidate cervical cancer genes, which are highly similar to known cervical cancer genes. Further, we analyzed the GO terms and prioritized these genes based on the number of hits with biological process, molecular functions, and their involvement in KEGG pathways. We also discussed the evidence-based involvement of the prioritized genes in other cancers and listed the available drugs for those genes.

Analysis of Nuclear Encoded Mitochondrial Gene Networks in Cervical Cancer

BACKGROUND

Cervical cancer (CC) is one of the most common female cancers in many developing and underdeveloped countries. High incidence, late presentation, and mortality suggested the need for molecular markers. Mitochondrial defects due to abnormal expression of nuclear-encoded mitochondrial genes (NEMG) have been reported during cancer progression. Nevertheless, the application of NEMG for the prognosis of CC is still elusive. Herein, we aimed to investigate the associations between NEMG and CC prognosis.

MATERIALS AND METHODS

The differentially expressed genes (DEG) in the TCGA-CESC dataset and NEMGs were retrieved from TACCO and Mitocarta2.0 databases, respectively. The impact of methylation on NEMG expression were predicted using DNMIVD and UALCAN tools. HCMDB tool was used to predict genes having metastatic potential. The prognostic models were constructed using DNMIVD, TACCO, GEPIA2, and SurvExpress. The functional enrichment analysis (FEA) was performed using clusterProfiler. The protein-protein interaction network (PPIN) was constructed to identify the hub genes (HG) using String and CytoHubba tools. Independent validation of the HG was performed using Oncomine and Human Protein Atlas databases. The druggable genes were predicted using DGIdb.

RESULTS

Among the 52 differentially expressed NEMG, 15 were regulated by DNA methylation. The expression level of 16, 10, and 7 has the potential for CC staging, prediction of metastasis, and prognosis. Moreover, 1 driver gene and 16 druggable genes were also identified. The FEA identified the enrichment of cancer-related pathways, including AMPK and carbon metabolism in cancer. The combined expression of 10 HG has been shown to affect patient survival.

CONCLUSION

Our findings suggest that the abnormal expression of NEMGs may play a critical role in CC development and progression. The genes identified in our study may serve as a prognostic indicator and therapeutic target in CC.
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Integrative Systems Biology Approaches to Identify Potential Biomarkers and Pathways of Cervical Cancer

Nowadays, cervical cancer (CC) is treated as the leading cancer among women throughout the world. Despite effective vaccination and improved surgery and treatment, CC retains its fatality rate of about half of the infected population globally. The major screening biomarkers and therapeutic target identification have now become a global concern. In the present study, we have employed systems biology approaches to retrieve the potential biomarkers and pathways from transcriptomic profiling. Initially, we have identified 76 of each up-regulated and down-regulated gene from a total of 4643 differentially expressed genes. The up-regulatory genes mainly concentrate on immune-inflammatory responses, and the down-regulatory genes are on receptor binding and gamma-glutamyltransferase. The involved pathways associated with these genes were also assessed through pathway enrichment, and we mainly focused on different cancer pathways, immunoresponse, and cell cycle pathways. After the subsequent enrichment of these genes, we have identified 12 hub genes, which play a crucial role in CC and are verified by expression profile analysis. From our study, we have found that genes LILRB2 and CYBB play crucial roles in CC, as reported here for the first time. Furthermore, the survivability of the hub genes was also assessed, and among them, finally, CXCR4 has been identified as one of the most potential differentially expressed genes that might play a vital role in the survival of CC patients. Thus, CXCR4 could be used as a prognostic and/or diagnostic biomarker and a drug target for CC.

Identification of an immune-based mRNA-lncRNA signature for overall survival in cervical squamous cell carcinoma

Aim: To better predict the survival of cervical squamous cell carcinoma (CESC) patients, we aimed to construct a signature according to different immune infiltration. Methods: We downloaded the RNA sequences of CESC patients from the Cancer Genome Atlas database. By using single-sample gene set enrichment analysis, we separated the samples into high- and low-immunity groups. Then we separated the samples into training and testing datasets and performed the following analyses: univariate, least absolute shrinkage and selection operator analysis, multivariate Cox regression analyses and weighted gene coexpression network analysis using R software. Gene ontology and Kyoto Encyclopedia of Genes and Genomes studies were performed using the Database for Annotation, Visualization and Integrated Discovery website. Results & conclusion: We finally identified a signature with three mRNAs and two lncRNAs: ADGRG5, HSH2D, ZMAT4, RBAKDN and LINC00200. In short, our study constructed an mRNA-lncRNA signature related to immune infiltration to better predict the survival of CESC patients.

Identification of an autophagy-related gene signature for survival prediction in patients with cervical cancer

Cervical cancer is one of the most common female malignancy that occurs worldwide and is reported to cause over 300,000 deaths in 2018. Autophagy controls the survival and death of cancerous cells by regulating the degradation process of cytoplasm and cellular organelle. In the present study, the differentially expressed autophagy-related genes (ARGs) between healthy and cancerous cervical tissues (squamous cell neoplasms) were obtained using data from GTEx and The Cancer Genome Atlas (TCGA) database. The functionalities of the differentially expressed ARGs were analyzed using Gene Ontology (GO) as well as the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Next, we conducted univariate Cox regression assay and obtained 12 ARGs that were associated with the prognosis of cervical cancer patients. We carried out a multivariate Cox regression analysis and developed six ARG-related prognostic signature for the survival prediction of patients with squamous cell cervical cancer (Risk score = − 0.63*ATG3–0.42*BCL2 + 0.85*CD46–0.38*IFNG+ 0.23*NAMPT+ 0.82*TM9SF1). Following the calculation of risk score using the signature, the patients were divided into high and low-risk groups according to the median value. Kaplan-Meier curve demonstrated that patients with a high-risk score tend to have a poor prognosis (P < 0.001). The value for area under the curves corresponding to the receiver operating characteristic (ROC) was 0.740. As observed, the expression of IFNG was negatively associated with lymph node metastasis (P = 0.026), while a high-risk score was significantly associated with increased age (P = 0.008). To further validate the prognostic signature, we carried out a permutation test and confirmed the performance of the risk score. In conclusion, our study developed six ARG-related prognostic signature for patients with squamous cell cervical cancer, which might help in improving the prognostic predictions of such patients.

A multiple genomic data fused SF2 prediction model, signature identification, and gene regulatory network inference for personalized radiotherapy

Radiotherapy is one of the most important cancer treatments, but its response varies greatly among individual patients. Therefore, the prediction of radiosensitivity, identification of potential signature genes, and inference of their regulatory networks are important for clinical and oncological reasons. Here, we proposed a novel multiple genomic fused partial least squares deep regression method to simultaneously analyze multi-genomic data. Using 60 National Cancer Institute cell lines as examples, we aimed to identify signature genes by optimizing the radiosensitivity prediction model and uncovering regulatory relationships. A total of 113 signature genes were selected from more than 20,000 genes. The root mean square error of the model was only 0.0025, which was much lower than previously published results, suggesting that our method can predict radiosensitivity with the highest accuracy. Additionally, our regulatory network analysis identified 24 highly important ‘hub’ genes. The data analysis workflow we propose provides a unified and computational framework to harness the full potential of large-scale integrated cancer genomic data for integrative signature discovery. Furthermore, the regression model, signature genes, and their regulatory network should provide a reliable quantitative reference for optimizing personalized treatment options, and may aid our understanding of cancer progress mechanisms.

Comparative transcriptomic profiling in HPV-associated cervical carcinogenesis: Implication of MHC class II and immunoglobulin heavy chain genes

AIM

We aimed to determine the biological processes and pathways involved in cervical carcinogenesis associated with high-risk human papillomavirus (HPV) infection.

MATERIALS AND METHODS

Total RNA was extracted from three formalin-fixed paraffin-embedded (FFPE) samples each of normal cervix, HPV-infected low-grade squamous intraepithelial lesion (LSIL), high-grade SIL (HSIL) and squamous cell carcinoma (SCC). Transcriptomic profiling by microarrays was conducted followed by downstream Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses.

RESULTS

We examined the difference in GOs enriched for each transition stage from normal cervix to LSIL, HSIL, and SCC, and found 307 genes to be differentially expressed. In the transition from normal cervix to LSIL, the extracellular matrix (ECM) genes were significantly downregulated. The MHC class II genes were significantly upregulated in the LSIL to HSIL transition. In the final transition from HSIL to SCC, the immunoglobulin heavy locus genes were significantly upregulated and the ECM pathway was implicated.

CONCLUSION

Deregulation of the immune-related genes including MHC II and immunoglobulin heavy chain genes were involved in the transitions from LSIL to HSIL and SCC, suggesting immune escape from host anti-tumour response. The extracellular matrix plays an important role during the early and late stages of cervical carcinogenesis.

A prognostic nomogram integrating novel biomarkers identified by machine learning for cervical squamous cell carcinoma

Background

Cervical cancer (CC) represents the fourth most frequently diagnosed malignancy affecting women all over the world. However, effective prognostic biomarkers are still limited for accurately identifying high-risk patients. Here, we provided a combination machine learning algorithm-based signature to predict the prognosis of cervical squamous cell carcinoma (CSCC).

Methods and materials

After utilizing RNA sequencing (RNA-seq) data from 36 formalin-fixed and paraffin-embedded (FFPE) samples, the most significant modules were highlighted by the weighted gene co-expression network analysis (WGCNA). A candidate genes-based prognostic classifier was constructed by the least absolute shrinkage and selection operator (LASSO) and then validated in an independent validation set. Finally, based on the multivariate analysis, a nomogram including the FIGO stage, therapy outcome, and risk score level was built to predict progression-free survival (PFS) probability.

Results

A mRNA-based signature was developed to classify patients into high- and low-risk groups with significantly different PFS and overall survival (OS) rate (training set: p < 0.001 for PFS, p = 0.016 for OS; validation set: p = 0.002 for PFS, p = 0.028 for OS). The prognostic classifier was an independent and powerful prognostic biomarker for PFS in both cohorts (training set: hazard ratio [HR] = 0.13, 95% CI 0.05–0.33, p < 0.001; validation set: HR = 0.02, 95% CI 0.01–0.04, p < 0.001). A nomogram that integrated the independent prognostic factors was constructed for clinical application. The calibration curve showed that the nomogram was able to predict 1-, 3-, and 5-year PFS accurately, and it performed well in the external validation cohorts (concordance index: 0.828 and 0.864, respectively).

Conclusion

The mRNA-based biomarker is a powerful and independent prognostic factor. Furthermore, the nomogram comprising our prognostic classifier is a promising predictor in identifying the progression risk of CSCC patients.

Minichromosome Maintenance Complex (MCM) Genes Profiling and MCM2 Protein Expression in Cervical Cancer Development

OBJECTIVE

Minichromosome maintenance complex (MCM) proteins are essential for the process of DNA replication and cell division. This study aimed to evaluate MCM genes expression profiles and MCM2 protein in HPV-associated cervical carcinogenesis.

METHODOLOGY

MCM2, 4, 5 and 7 genes expression profiles were evaluated in three cervical tissue samples each of normal cervix, human papillomavirus (HPV)-infected low grade squamous intraepithelial lesion (LSIL), high grade squamous intraepithelial lesion (HSIL) and squamous cell carcinoma (SCC), using Human Transcriptome Array 2.0 and validated by nCounter® PanCancer Pathway NanoString Array. Immunohistochemical expression of MCM2 protein was semi-quantitatively assessed by histoscore in tissue microarrays containing 9 cases of normal cervix, 10 LSIL, 10 HSIL and 42 cases of SCC.

RESULTS

MCM2, 4, 5 and 7 genes expressions were upregulated with increasing fold change during the progression from LSIL to HSIL and the highest in SCC. MCM2 gene had the highest fold change in SCC compared to normal cervix. Immunohistochemically, MCM2 protein was localised in the nuclei of basal cells of normal cervical epithelium and dysplastic-neoplastic cells of CIN and SCC. There was a significant difference in MCM2 protein expression between the histological groups (P = 0.039), and histoscore was the highest in HSIL compared to normal cervix (P = 0.010).

CONCLUSION

The upregulation of MCM genes expressions in cervical carcinogenesis reaffirms MCM as a proliferative marker in DNA replication pathway, whereby proliferation of dysplastic and cancer cells become increasingly dysregulated and uncontrolled. A strong expression of MCM2 protein in HSIL may aid as a concatenated screening tool in detecting pre-cancerous cervical lesions.

Proteomic Screening for Serum Biomarkers for Cervical Cancer and Their Clinical Significance

Background

The present study aimed to determine serum markers for cervical cancer (CC) and to provide valuable references for clinical diagnosis and treatment.

Material/Methods

Serum samples were collected from age-matched healthy control women, and from female CC patients before and after surgery. Serum biomarkers were selected by comparing serum peptides profiles among the 3 groups by magnetic bead-based weak cation – exchange chromatography fractionation combined with matrix-assisted laser desorption/ionization-time of flight mass spectrometry. Probable serum biomarkers for cervical cancer were then further identified by liquid chromatography-electrospray ionization-tandem mass spectrometry system and the identified proteins were verified by enzyme-linked immunosorbent assay (ELISA).

Results

Three peptide biomarkers were identified for distinguishing CC patients from normal individuals, and distinguishing preoperative CC patients from postoperative CC patients. Of these 3 identified protein peptide regions, 2 peptide regions – TKT (Peak 2, 2435.63 m/z, 499–524) and FGA (Peak 4, 2761.79 m/z, 603–629) – were identified as upregulated markers, and peptide region of APOA1 (Peak 9, 2575.3 m/z, 245–260) was identified as a downregulated biomarker in preoperative CC patients compared with healthy women.

Conclusions

The present study provides a new method for identifying potential serum biomarkers for CC patients.

A Comprehensive RNA Expression Signature for Cervical Squamous Cell Carcinoma Prognosis

Clinicopathological characteristics alone are not enough to predict the survival of patients with cervical squamous cell carcinoma (CESC) due to clinical heterogeneity. In recent years, many genes and non-coding RNAs have been shown to be oncogenes or tumor-suppressors in CESC cells. This study aimed to develop a comprehensive transcriptomic signature for CESC patient prognosis. Univariate, multivariate, and Least Absolute Shrinkage and Selection Operator penalized Cox regression were used to identify prognostic signatures for CESC patients from transcriptomic data of The Cancer Genome Atlas. A normalized prognostic index (NPI) was formulated as a synthetical index for CESC prognosis. Time-dependent receiver operating characteristic curve analysis was used to compare prognostic signatures. A prognostic transcriptomic signature was identified, including 1 microRNA, 1 long non-coding RNA, and 6 messenger RNAs. Decreased survival was associated with CESC patients being in the high-risk group stratified by NPI. The NPI was an independent predictor for CESC patient prognosis and it outperformed the known clinicopathological characteristics, microRNA-only signature, gene-only signature, and previously identified microRNA and gene signatures. Function and pathway enrichment analysis revealed that the identified prognostic RNAs were mainly involved in angiogenesis. In conclusion, we proposed a transcriptomic signature for CESC prognosis and it may be useful for effective clinical risk management of CESC patients. Moreover, RNAs in the transcriptomic signature provided clues for downstream experimental validation and mechanism exploration.

Epithelial RNase H2 Maintains Genome Integrity and Prevents Intestinal Tumorigenesis in Mice

BACKGROUND & AIMS

RNase H2 is a holoenzyme, composed of 3 subunits (ribonuclease H2 subunits A, B, and C), that cleaves RNA:DNA hybrids and removes mis-incorporated ribonucleotides from genomic DNA through ribonucleotide excision repair. Ribonucleotide incorporation by eukaryotic DNA polymerases occurs during every round of genome duplication and produces the most frequent type of naturally occurring DNA lesion. We investigated whether intestinal epithelial proliferation requires RNase H2 function and whether RNase H2 activity is disrupted during intestinal carcinogenesis.

METHODS

We generated mice with epithelial-specific deletion of ribonuclease H2 subunit B (H2b^ΔIEC) and mice that also had deletion of tumor-suppressor protein p53 (H2b/p53^ΔIEC); we compared phenotypes with those of littermate H2b^fl/fl or H2b/p53^fl/fl (control) mice at young and old ages. Intestinal tissues were collected and analyzed by histology. We isolated epithelial cells, generated intestinal organoids, and performed RNA sequence analyses. Mutation signatures of spontaneous tumors from H2b/p53^ΔIEC mice were characterized by exome sequencing. We collected colorectal tumor specimens from 467 patients, measured levels of ribonuclease H2 subunit B, and associated these with patient survival times and transcriptome data.

RESULTS

The H2b^ΔIEC mice had DNA damage to intestinal epithelial cells and proliferative exhaustion of the intestinal stem cell compartment compared with controls and H2b/p53^ΔIEC mice. However, H2b/p53^ΔIEC mice spontaneously developed small intestine and colon carcinomas. DNA from these tumors contained T>G base substitutions at GTG trinucleotides. Analyses of transcriptomes of human colorectal tumors associated lower levels of RNase H2 with shorter survival times.

CONCLUSIONS

In analyses of mice with disruption of the ribonuclease H2 subunit B gene and colorectal tumors from patients, we provide evidence that RNase H2 functions as a colorectal tumor suppressor. H2b/p53^ΔIEC mice can be used to study the roles of RNase H2 in tissue-specific carcinogenesis.

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.