Characterization and clinical validation of MCM2 and TOP2A monoclonal antibodies in the BD ProEx™ C assay: An immunoassay which detects aberrant S-phase induction in cervical tissue

Association between serum P16ink4A concentration and CIN and cervical cancer among women attending a cervical cancer clinic in western Uganda: A case control study

Introduction

Tissue expression of P16ink4A is correlated with cervical lesions. In this study we determined the association between serum P16ink4A concentrations and cervical lesions among women attending the cervical cancer clinic at Mbarara Regional Hospital (MRRH) South Western Uganda.

Material and Methods

We recruited 90 cervical intraepithelial neoplasia (CIN) cases, 90 cervical cancer (CC) cases before treatment and 90 controls. Clinical and demographic data were recorded. Serum P16ink4A concentrations were measured by quantitative Elisa. Cases were confirmed with cytology and/or histology. Descriptive statistics and logistic regression were done with STATA 17 and P-values of <0.05 were considered statistically significant.

Results

The mean serum P16ink4A concentration among CIN cases, CC cases and controls was 1.11(+/-0.66) ng/ml, 1.45(+/-1.11) ng/ml and 1.13(+/-0.61) ng/ml respectively (p = 0.008). 50 % of CIN cases and controls as well as 60 % of CC cases had P16ink4A concentration above 0.946 ng/ml. There were increased odds of CIN for serum P16ink4A though statistically insignificant (AOR: 1.11, p-value: 0.70). There was also a statistically significant reduction in odds of CC for serum P16ink4A (AOR: 0.55, p-value: 0.01).

Conclusion

Serum P16ink4A may likely be associated with cervical lesions especially CC in our study population and this may aid detection of such lesions. Diagnostic utility studies for circulating P16ink4A in detection of cervical cancer are recommended.

Expression analysis of p16 and TOP2A protein biomarkers in cervical cancer lesions and their correlation with clinico-histopathological characteristics in a referral hospital, Tanzania

Introduction

Biomarkers yield important information for early diagnosis of cervical cancer. However, they are rarely applied for prognosis of cervical cancer in Tanzania, where visual inspection assay with acetic acid or Lugol’s iodine and Pap test are being used as the standard screening/ diagnostic methods.

Methods

This was a retrospective hospital-based cross-sectional study that was conducted to assess cyclin-dependent kinase inhibitor (p16) and topoisomerase II-alpha (TOP2A) proteins expression among women seeking cervical cancer care at Kilimanjaro Christian Medical Centre, Tanzania between May 1, 2017 and May 10, 2018. Immunohistochemistry technique was used to detect the expressions of p16 and TOP2A proteins from the retrieved formalin-fixed and paraffin-embedded (FFPE) cervical biopsies.

Results

A total of 145 patients, with a mean age of 52.1 ± 12.9 years, were included in this study. Upon immunohistochemistry staining, 103 (71.0%) and 90 (62.1%) were p16 and TOP2A positive respectively. There was a strong association between histopathological class and p16/TOP2A expression levels (Fisher’s exact test, p<0.001). Moreover, there was a strong positive correlation between p16/TOP2A and cancerous cervical lesions (Spearman’s rank correlation coefficients = 0.833 and 0.687, p = 0.006 and 0.005, respectively). The age-adjusted odds ratio for predicting cervical cancer lesions were independently significant for p16/TOP2A biomarkers in FFPE cervical tissues [p16: OR = 1.142 (95% CI: 1.059–1.232, p<0.001) and TOP2A: OR = 1.046 (95% CI: 1.008–1.085, p = 0.015)]. Importantly, the diagnostic performance of p16 was higher than that of TOP2A in the diagnosis of cancerous lesions from non-cancerous cervical lesions (sensitivity: 97.2% versus 77.6%, accuracy: 92.8% versus 87.8%, respectively).

Conclusion

Our study has highlighted that over-expression of TOP2A is related to the grade of cervical intraepithelial neoplasia but does not predict prognosis in cervical cancer. Similarly, expression of p16 is related to degree of histological dysplasia and malignancy, suggesting its prognostic and predictive value in the management of cervical cancers. Further bigger studies are needed to validate their applications in the early diagnosis of cervical cancer.

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.

Detection of Cervical Lesions and Cancer in Air-Dried Cytologic Smears by Combined Analysis of mRNA and miRNA Expression Levels

Cervical cancer screening is based on cytologic analysis and high-risk human papillomavirus (HR-HPV) testing, each having their drawbacks. Implementation of new biomarker-based methods may improve screening accuracy. Here, the levels of 25 microRNAs (miRNAs, miRs) and 12 mRNAs involved in cervical carcinogenesis in 327 air-dried Papanicolaou-stained cervical smears from patients with cervical precancerous lesions, cancer, or without the disease were estimated by real-time PCR. Using logistic regression analysis, small-scale miRNA-based, mRNA-based, and combined molecular classifiers were built based on paired ratios of miRNA or mRNA concentrations; their ability to detect high-grade cervical lesions and cancer was then compared. Combined mRNA-miRNA classifiers manifested a better combination of sensitivity and specificity than miRNA- and mRNA-based classifiers. The best classifier, combining miR-375, miR-20, miR-96, CDKN2A, TSP4, and ECM1, predicted high-grade lesions with diagnostic sensitivity of 89.0%, specificity of 84.2%, and a receiver-operating characteristic area under the curve of 0.913. Additionally, in a subsample of the same specimens, the levels of MIR124-2 and MAL promoter methylation, HR-HPV genotypes, and viral loads were analyzed. The relative high-grade lesion risk estimated by the classifier correlated with the frequency of MAL and MIR124-2 methylation but not with the HR-HPV genotype or viral load. The results support the feasibility of cellular biomarker-based methods for cervical screening and patient management.

TOP2A/MCM2, p16INK4a, and cyclin E1 expression in liquid-based cytology: a biomarkers panel for progression risk of cervical premalignant lesions

BACKGROUND

To improve the efficiency of early diagnosis systems for cervical cancer, the use of cellular and viral markers for identifying precancerous lesions with a greater probability to progress to cancer has been proposed. Several cellular proteins and markers of oxidative DNA damage have been suggested as possible biomarkers of cervical carcinogenesis; however, they have not been evaluated together. In this study, we analyzed the expression of the cellular markers p16^INK4a, Ki-67, CyclinE1, TOP2A/MCM2, and telomerase, as well as the DNA oxidative damage markers ROS and 8-OHdG. The analyses were performed in liquid-based cervical cytology samples or biopsies with premalignant lesions or cervical cancer diagnosis, with the purpose of selecting a panel of biomarkers that allow the identification of precursor lesions with greater risk of progression to cervical cancer.

METHODS

We analyzed 1485 liquid-based cytology samples, including 239 non-squamous intraepithelial lesions (NSIL), 901 low-grade squamous intraepithelial lesions (LSIL), 54 high-grade squamous intraepithelial lesions (HSIL), and 291 cervical cancers (CC). The biomarkers were analyzed by immunocytochemistry and Human Papilloma Virus (HPV) genotyping with the INNO-LiPA genotyping Extra kit.

RESULTS

We found that all tested cellular biomarkers were overexpressed in samples with high risk-HPV infection, and the expression levels increased with the severity of the lesion. TOP2A/MCM2 was the best biomarker for discriminating between LSIL and HSIL, followed by p16^INK4a and cyclinE1. Statistical analysis showed that TOP2A/MCM2 provided the largest explanation of HSIL and CC cases (93.8%), followed by p16^INK4a (91%), cyclin E1 (91%), Ki-67 (89.3%), and telomerase (88.9%).

CONCLUSIONS

We propose that the detection of TOP2A/MCM2, p16^INK4a and cyclin E1 expression levels is useful as a panel of biomarkers that allow identification of cervical lesions with a higher risk for progression to CC with high sensitivity and precision; this can be done inexpensively, in a single and non-invasive liquid-based cytology sample.

Cervical cancer risk profiling: molecular biomarkers predicting the outcome of hrHPV infection

INTRODUCTION

Cervical cancer affects half a million women worldwide annually. Given the association between high-risk human papillomavirus (hrHPV) infection and carcinogenesis, hrHPV DNA testing became an essential diagnostic tool. However, hrHPV alone does not cause the disease, and, most importantly, many cervical lesions regress to normal in a year because of the host immune system. Hence, the low specificity of hrHPV DNA tests and their inability to predict the outcome of infections have triggered a further search for biomarkers.

AREAS COVERED

We evaluated the latest viral and cellular biomarkers validated for clinical use as primary screening or triage for cervical cancer and assessed their promise for prevention as well as potential use in the future. The literature search focused on effective biomarkers for different stages of the disease, aiming to determine their significance in predicting the outcome of hrHPV infections.

EXPERT OPINION

Biomarkers such as p16/Ki-67, hrHPV genotyping, hrHPV transcriptional status, and methylation patterns have demonstrated promising results. Their eventual implementation in the screening programs may support the prompt diagnosis of hrHPV infection and its progression to cancer. These biomarkers will help in making clinical management decisions on time, thus, saving the lives of hrHPV-infected women, particularly in developing countries.

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.

Transcriptome analysis reveals key signature genes involved in the oncogenesis of lung cancer

Previous studies have suggested potential signature genes for lung cancer, however, due to factors such as sequencing platform, control, data selection and filtration conditions, the results of lung cancer-related gene expression analysis are quite different. Here, we performed a meta-analysis on existing lung cancer gene expression results to identify Meta-signature genes without noise. In this study, functional enrichment, protein-protein interaction network, the DAVID, String, TfactS, and transcription factor binding were performed based on the gene expression profiles of lung adenocarcinoma and non-small cell lung cancer deposited in the GEO database. As a result, a total of 574 differentially expressed genes (DEGs) affecting the pathogenesis of lung cancer were identified (207 up-regulated expression and 367 down-regulated expression in lung cancer tissues). A total of 5,093 interactions existed among the 507 (88.3%) proteins, and 10 Meta-signatures were identified: AURKA, CCNB1, KIF11, CCNA2, TOP2A, CENPF, KIF2C, TPX2, HMMR, and MAD2L1. The potential biological functions of Meta-signature DEGs were revealed. In summary, this study identified key genes involved in the process of lung cancer. Our results would help the developing of novel biomarkers for lung cancer.

Identification of key genes and pathways of diagnosis and prognosis in cervical cancer by bioinformatics analysis

Background

Cervical cancer as one of the most common malignant tumors lead to bad prognosis among women. Some researches already focus on the carcinogenesis and pathogenesis of cervical cancer, but it is still necessary to identify more key genes and pathways.

Methods

Differentially expressed genes were identified by GEO2R from the gene expression omnibus (GEO) website, then gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyzed by DAVID. Meanwhile, protein–protein interaction network was constructed by STRING, and both key genes and modules were found in visualizing network through Cytoscape. Besides, GEPIA did the differential expression of key genes and survival analysis. Finally, the expression of genes related to prognosis was further explored by UNLCAN, oncomine, and the human protein atlas.

Results

Totally 57 differentially expressed genes were founded, not only enriched in G1/S transition of mitotic cell cycle, mitotic nuclear division, and cell division but also participated in cytokine–cytokine receptor interaction, toll‐like receptor signaling pathway, and amoebiasis. Additionally, 12 hub genes and 3 key modules were screened in the Cytoscape visualization network. Further survival analysis showed that TYMS (OMIM accession number 188350), MCM2 (OMIM accession number 116945), HELLS (OMIM accession number 603946), TOP2A (OMIM accession number 126430), and CXCL8 (OMIM accession number 146930) were associated with the prognosis of cervical cancer.

Conclusion

This study aim to better understand the characteristics of some genes and signaling pathways about cervical cancer by bioinformatics, and could provide further research ideas to find new mechanism, more prognostic factors, and potential therapeutic targets for cervical cancer.