The dysregulation of microarray gene expression in cervical cancer is associated with overexpression of a unique messenger RNA signature

Cervical cancer heterogeneity: a constant battle against viruses and drugs

Cervical cancer is the first identified human papillomavirus (HPV) associated cancer and the most promising malignancy to be eliminated. However, the ever-changing virus subtypes and acquired multiple drug resistance continue to induce failure of tumor prevention and treatment. The exploration of cervical cancer heterogeneity is the crucial way to achieve effective prevention and precise treatment. Tumor heterogeneity exists in various aspects including the immune clearance of viruses, tumorigenesis, neoplasm recurrence, metastasis and drug resistance. Tumor development and drug resistance are often driven by potential gene amplification and deletion, not only somatic genomic alterations, but also copy number amplifications, histone modification and DNA methylation. Genomic rearrangements may occur by selection effects from chemotherapy or radiotherapy which exhibits genetic intra-tumor heterogeneity in advanced cervical cancers. The combined application of cervical cancer therapeutic vaccine and immune checkpoint inhibitors has become an effective strategy to address the heterogeneity of treatment. In this review, we will integrate classic and recently updated epidemiological data on vaccination rates, screening rates, incidence and mortality of cervical cancer patients worldwide aiming to understand the current situation of disease prevention and control and identify the direction of urgent efforts. Additionally, we will focus on the tumor environment to summarize the conditions of immune clearance and gene integration after different HPV infections and to explore the genomic factors of tumor heterogeneity. Finally, we will make a thorough inquiry into completed and ongoing phase III clinical trials in cervical cancer and summarize molecular mechanisms of drug resistance among chemotherapy, radiotherapy, biotherapy, and immunotherapy.

Metadata analysis to explore hub of the hub-genes highlighting their functions, pathways and regulators for cervical cancer diagnosis and therapies

Cervical cancer (CC) is considered as the fourth most common women cancer globally.that shows malignant features of local infiltration and invasion into adjacent organs and tissues. There are several individual studies in the literature that explored CC-causing hub-genes (HubGs), however, we observed that their results are not so consistent. Therefore, the main objective of this study was to explore hub of the HubGs (hHubGs) that might be more representative CC-causing HubGs compare to the single study based HubGs. We reviewed 52 published articles and found 255 HubGs/studied-genes in total. Among them, we selected 10 HubGs (CDK1, CDK2, CHEK1, MKI67, TOP2A, BRCA1, PLK1, CCNA2, CCNB1, TYMS) as the hHubGs by the protein-protein interaction (PPI) network analysis. Then, we validated their differential expression patterns between CC and control samples through the GPEA database. The enrichment analysis of HubGs revealed some crucial CC-causing biological processes (BPs), molecular functions (MFs) and cellular components (CCs) by involving hHubGs. The gene regulatory network (GRN) analysis identified four TFs proteins and three miRNAs as the key transcriptional and post-transcriptional regulators of hHubGs. Then, we identified hHubGs-guided top-ranked FDA-approved 10 candidate drugs and validated them against the state-of-the-arts independent receptors by molecular docking analysis. Finally, we investigated the binding stability of the top-ranked three candidate drugs (Docetaxel, Temsirolimus, Paclitaxel) by using 100 ns MD-based MM-PBSA simulations and observed their stable performance. Therefore the finding of this study might be the useful resources for CC diagnosis and therapies.

Bioinformatics Screening of Potential Biomarkers from mRNA Expression Profiles to Discover Drug Targets and Agents for Cervical Cancer

Bioinformatics analysis has been playing a vital role in identifying potential genomic biomarkers more accurately from an enormous number of candidates by reducing time and cost compared to the wet-lab-based experimental procedures for disease diagnosis, prognosis, and therapies. Cervical cancer (CC) is one of the most malignant diseases seen in women worldwide. This study aimed at identifying potential key genes (KGs), highlighting their functions, signaling pathways, and candidate drugs for CC diagnosis and targeting therapies. Four publicly available microarray datasets of CC were analyzed for identifying differentially expressed genes (DEGs) by the LIMMA approach through GEO2R online tool. We identified 116 common DEGs (cDEGs) that were utilized to identify seven KGs (AURKA, BRCA1, CCNB1, CDK1, MCM2, NCAPG2, and TOP2A) by the protein–protein interaction (PPI) network analysis. The GO functional and KEGG pathway enrichment analyses of KGs revealed some important functions and signaling pathways that were significantly associated with CC infections. The interaction network analysis identified four TFs proteins and two miRNAs as the key transcriptional and post-transcriptional regulators of KGs. Considering seven KGs-based proteins, four key TFs proteins, and already published top-ranked seven KGs-based proteins (where five KGs were common with our proposed seven KGs) as drug target receptors, we performed their docking analysis with the 80 meta-drug agents that were already published by different reputed journals as CC drugs. We found Paclitaxel, Vinorelbine, Vincristine, Docetaxel, Everolimus, Temsirolimus, and Cabazitaxel as the top-ranked seven candidate drugs. Finally, we investigated the binding stability of the top-ranked three drugs (Paclitaxel, Vincristine, Vinorelbine) by using 100 ns MD-based MM-PBSA simulations with the three top-ranked proposed receptors (AURKA, CDK1, TOP2A) and observed their stable performance. Therefore, the proposed drugs might play a vital role in the treatment against CC.