Identification of crucial aberrantly methylated and differentially expressed genes related to cervical cancer using an integrated bioinformatics analysis

Methods in DNA methylation array dataset analysis: A review

Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.

DNA methylation at individual CpG-sites of EPB41L3, HTERT and FAM19A4 are useful for detection of cervical high-grade squamous intraepithelial lesions (HSIL) or worse: Analysis of individual CpG-sites outperforms averaging

Global methylation analysis of gene promoters is promising for detection of high-grade squamous intraepithelial lesions or worse (HSIL+) in high-risk human papillomavirus (hrHPV)-positive women. However, diagnostic performance of methylation data at individual CpG-sites is limited. We explored methylation for predicting HSIL+ in self- and clinician-collected samples from Papua New Guinea. Methylation of EPB41L3 (1-6 CpG-sites), hTERT (1-10 CpG-sites) and FAM19A4 (1-5 CpG-sites) was assessed through pyrosequencing from 44 HPV+ samples (4 cancers, 19 HSIL, 4 low-grade squamous intraepithelial lesions (LSIL), 17 normal). New primers were designed for FAM19A4 directed to the first exon region not explored previously. In clinician-collected samples, methylation at CpG-sites 4 and 5 of EPB41L3 were the best HSIL predictors (AUC >0.83) and CpG-site 4 for cancer (0.925). Combination of EPB41L3 sites 2/4 plus FAM19A4 site 1 were the best HSIL+ markers [100% sensitivity, 63.2% specificity]. Methylation at CpG-site 5 of FAM19A4 was the best HSIL predictor (0.67) in self-collected samples, and CpG-sites 1 and 3 of FAM19A4 for cancer (0.77). Combined, FAM19A4 site 1 plus HPV 16/18 detection yielded sensitivity of 82.6% and specificity of 61.9%. In conclusion, methylation at individual CpG-sites of EPB41L3 and FAM19A4 outperformed global analysis and improved HSIL+ detection, warranting further investigation.

Expression, DNA methylation pattern and transcription factor EPB41L3 in gastric cancer: a study of 262 cases

PURPOSE

DNA methylation prominently inactivates tumor suppressor genes and facilitates oncogenesis. Previously, we delineated a chromosome 18 deletion encompassing the erythrocyte membrane protein band 4.1-like 3 (EPB41L3) gene, a progenitor for the tumor suppressor that is differentially expressed in adenocarcinoma of the lung-1 (DAL-1) in gastric cancer (GC).

METHODS

Our current investigation aimed to elucidate EPB41L3 expression and methylation in GC, identify regulatory transcription factors, and identify affected downstream pathways. Immunohistochemistry demonstrated that DAL-1 expression is markedly reduced in GC tissues, with its downregulation serving as an independent prognostic marker.

RESULTS

High-throughput bisulfite sequencing of 70 GC patient tissue pairs revealed that higher methylation of non-CpGs in the EPB41L3 promoter was correlated with more malignant tumor progression and higher-grade tissue classification. Such hypermethylation was shown to diminish DAL-1 expression, thus contributing to the malignancy of GC phenotypes. The DNA methyltransferase inhibitor 5-aza-2'-deoxycytidine (5-aza-CdR) was found to partially restore DAL-1 expression. Moreover, direct binding of the transcription factor CDC5L to the upstream region of the EPB41L3 promoter was identified via chromosome immunoprecipitation (ChIP)-qPCR and luciferase reporter assays. Immunohistochemistry confirmed the positive correlation between CDC5L and DAL-1 protein levels. Subsequent RNA-seq analysis revealed that DAL-1 significantly influences the extracellular matrix and space-related pathways. GC cell RNA-seq post-5-Aza-CdR treatment and single-cell RNA-seq data of GC tissues confirmed the upregulation of AREG and COL17A1, pivotal tumor suppressors, in response to EPB41L3 demethylation or overexpression in GC epithelial cells.

CONCLUSION

In conclusion, this study elucidates the association between non-CpG methylation of EPB41L3 and GC progression and identifies the key transcription factors and downstream molecules involved. These findings enhance our understanding of the role of EPB41L3 in gastric cancer and provide a solid theoretical foundation for future research and potential clinical applications.

The role of epigenetics in women's reproductive health: the impact of environmental factors

This paper explores the significant role of epigenetics in women's reproductive health, focusing on the impact of environmental factors. It highlights the crucial link between epigenetic modifications-such as DNA methylation and histones post-translational modifications-and reproductive health issues, including infertility and pregnancy complications. The paper reviews the influence of pollutants like PM2.5, heavy metals, and endocrine disruptors on gene expression through epigenetic mechanisms, emphasizing the need for understanding how dietary, lifestyle choices, and exposure to chemicals affect gene expression and reproductive health. Future research directions include deeper investigation into epigenetics in female reproductive health and leveraging gene editing to mitigate epigenetic changes for improving IVF success rates and managing reproductive disorders.

EPB41L3 Inhibits the Progression of Cervical Cancer Via the ERK/p38 MAPK Signaling Pathway

This study was aimed to uncover the character and potential regulatory mechanism of EPB41L3 in cervical cancer (CC). CC cells were injected into BALB/c nude mice (female) to construct a xenograft tumor model. Real-time quantitative polymerase chain reaction (qRT-PCR) and western blot were performed to evaluate the expression of EPB41L3, ERK/p38 MAPK signal markers in CC tissues and cells. Cell counting kit-8 (CCK-8) and Transwell was applied to analyze the viability, invasion, and migration of CC cell lines. EPB41L3 was substantially decreased both in CC tissues and cells. Cell viability, invasion, and migration of CC cells were reduced by overexpressing EPB41L3. Bioinformatics analysis prerdicted that EPB41L3 was strongly related to the ERK/p38 MAPK pathway. Compared with Ad-nc mice, the volume and weight of tumors and ERK/p38 MAPK signal markers were down-regulated in Ad-EPB41L3 mice. After knocking down EPB41L3 with EPB41L3 siRNA (siEPB41L3), the ERK/p38 MAPK pathway was activated. Moreover, SB203580 treatment reversed the effect of EPB41L3 silencing on the improvement in viability, migration, and invasion of CC cells. EPB41L3 suppresses the progression of CC via activating the ERK/p38 MAPK pathway. EPB41L3 may serve as an effective therapeutic target for CC.

Discovery and technical validation of high-performance methylated DNA markers for the detection of cervical lesions at risk of malignant progression in low- and middle-income countries

BACKGROUND

Cervical cancer remains a leading cause of death, particularly in developing countries. WHO screening guidelines recommend human papilloma virus (HPV) detection as a means to identify women at risk of developing cervical cancer. While HPV testing identifies those at risk, it does not specifically distinguish individuals with neoplasia. We investigated whether a quantitative molecular test that measures methylated DNA markers could identify high-risk lesions in the cervix with accuracy.

RESULTS

Marker discovery was performed in TCGA-CESC Infinium Methylation 450 K Array database and verified in three other public datasets. The panel was technically validated using Quantitative Multiplex-Methylation-Specific PCR in tissue sections (N = 252) and cervical smears (N = 244) from the USA, South Africa, and Vietnam. The gene panel consisted of FMN2, EDNRB, ZNF671, TBXT, and MOS. Cervical tissue samples from all three countries showed highly significant differential methylation in squamous cell carcinoma (SCC) with a sensitivity of 100% [95% CI 74.12-100.00], and specificity of 91% [95% CI 62.26-99.53] to 96% [95% CI 79.01-99.78], and receiver operating characteristic area under the curve (ROC AUC) = 1.000 [95% CI 1.00-1.00] compared to benign cervical tissue, and cervical intraepithelial neoplasia 2/3 with sensitivity of 55% [95% CI 37.77-70.84] to 89% [95% CI 67.20-98.03], specificity of 93% [95% CI 84.07-97.38] to 96% [95% CI 79.01-99.78], and a ROC AUC ranging from 0.793 [95% CI 0.68-0.89] to 0.99 [95% CI 0.97-1.00] compared to CIN1. In cervical smears, the marker panel detected SCC with a sensitivity of 87% [95% CI 77.45-92.69], specificity 95% [95% CI 88.64-98.18], and ROC AUC = 0.925 [95% CI 0.878-0.974] compared to normal, and high-grade squamous intraepithelial lesion (HSIL) at a sensitivity of 70% (95% CI 58.11-80.44), specificity of 94% (95% CI 88.30-97.40), and ROC AUC = 0.884 (95% CI 0.822-0.945) compared to low-grade intraepithelial lesion (LSIL)/normal in an analysis of pooled data from the three countries. Similar to HPV-positive, HPV-negative cervical carcinomas were frequently hypermethylated for these markers.

CONCLUSIONS

This 5-marker panel detected SCC and HSIL in cervical smears with a high level of sensitivity and specificity. Molecular tests with the ability to rapidly detect high-risk HSIL will lead to timely treatment for those in need and prevent unnecessary procedures in women with low-risk lesions throughout the world. Validation of these markers in prospectively collected cervical smear cells followed by the development of a hypermethylated marker-based cervical cancer detection test is warranted.

Identification of miRNAs and target genes associated with lymph node metastasis in cervical cancer using bioinformatics analysis

This study was designed to identify the differentially expressed miRNAs (DEMs) and genes (DEGs) in metastatic cervical cancer using bioinformatic tools. In this study, fifty-seven DEMs (48 downregulated and 9 upregulated) were identified, among which miR-4459 and miR-3195 expression was negatively associated with overall survival of cervical cancer patients. Then, 476 target DEGs were determined, and protein-protein interaction (PPI) network was constructed. Seventeen hub genes (LONRF2, CCNE2, AURKA, SYT1, NEGR1, PPP1R12B, GABRP, RAD51, CDK1, FBLN5, PRKG1, CDC6, CACNA1C, MEOX2, ANLN, MYLK, and EDNRB) were finally selected to construct the miRNA-hub gene network. Overall, our study discovered the key miRNAs and mRNAs related to lymph node metastasis (LNM) in cervical cancer, which helps discover candidate therapeutic targets for cervical cancer.

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.

The Bioinformatical Identification of Potential Biomarkers in Heart Failure Diagnosis and Treatment

Background

Heart failure (HF) is defined as the inability of the heart's systolic and diastolic function to properly discharge blood flow from the veins to the heart. The goal of our research is to look into the possible mechanism that causes HF.

Methods

The GSE5406 database was used for screening the differentially expressed genes (DEGs). Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI) network were applied to analyze DEGs. Besides, cell counting Kit-8 (CCK-8) was conducted to observe the knockdown effect of hub genes on cell proliferation.

Results

Finally, 377 upregulated and 461 downregulated DEGs came out, enriched in the extracellular matrix organization and gap junction. According to GSEA results, Hoft cd4 positive alpha beta memory t cell bcg vaccine age 18–45 yo id 7 dy top 100 deg ex vivo up, Sobolev t cell pandemrix age 18–64 yo 7 dy dn, and so on were significantly related to gene set GSE5406. 7 hub genes, such as COL1A1, UBB, COL3A1, HSP90AA1, MYC, STAT3 and MAPK1, were selected from PPI networks. CCK-8 indicated silencing of STAT3 promoted the proliferation of H9C2 cells and silencing of UBB inhibited the proliferation of H9C2 cells.

Conclusion

Our analysis reveals that COL1A1, UBB, COL3A1, HSP90AA1, MYC, STAT3, and MAPK1 might promote the progression of HF and become the biomarkers for diagnosis and treatment of HF.

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.

Screening of Crucial Differentially-Methylated/Expressed Genes for Alzheimer's Disease

Background: We aimed to make an integrated analysis of published transcriptome and DNA methylation dataset to ascertain the key differentially methylated and differentially expressed genes for Alzherimer's disease (AD). Methods: Two gene expression microarrays and 1 gene methylation microarray were downloaded for identification of differentially expressed genes and differentially methylated genes. Then, we used various biological information databases to annotate the functions of the differentially-methylated/expressed genes, and screen out key genes and important signaling pathways. Finally, we validate the differentially-methylated/expressed genes in the additional online datasets and in blood from AD patients.Results: A total of 8 hub hypomethylated-high expression genes were obtained, including Rac family small GTPase 2, FGR proto-oncogene, Src family tyrosine kinase, LYN proto-oncogene, Src family tyrosine kinase, protein kinase C delta, myosin IF, integrin subunit alpha 5, semaphorin 4D, and growth arrest specific protein 7. Some enriched signaling pathways of hypomethylated-high expression genes were identified, including regulation of actin cytoskeleton, chemokine signaling pathway, Fc gamma R-mediated phagocytosis, and axon guidance. Conclusion: Differentially-methylated/expressed genes are likely to be associated with AD.

Autophagy Process in Trophoblast Cells Invasion and Differentiation: Similitude and Differences With Cancer Cells

Early human placental development begins with blastocyst implantation, then the trophoblast differentiates and originates the cells required for a proper fetal nutrition and placental implantation. Among them, extravillous trophoblast corresponds to a non-proliferating trophoblast highly invasive that allows the vascular remodeling which is essential for appropriate placental perfusion and to maintain the adequate fetal growth. This process involves different placental cell types as well as molecules that allow cell growth, cellular adhesion, tissular remodeling, and immune tolerance. Remarkably, some of the cellular processes required for proper placentation are common between placental and cancer cells to finally support tumor growth. Indeed, as in placentation trophoblasts invade and migrate, cancer cells invade and migrate to promote tumor metastasis. However, while these processes respond to a controlled program in trophoblasts, in cancer cells this regulation is lost. Interestingly, it has been shown that autophagy, a process responsible for the degradation of damaged proteins and organelles to maintain cellular homeostasis, is required for invasion of trophoblast cells and for vascular remodeling during placentation. In cancer cells, autophagy has a dual role, as it has been shown both as tumor promoter and inhibitor, depending on the stage and tumor considered. In this review, we summarized the similarities and differences between trophoblast cell invasion and cancer cell metastasis specifically evaluating the role of autophagy in both processes.

Markers of Angiogenesis, Lymphangiogenesis, and Epithelial-Mesenchymal Transition (Plasticity) in CIN and Early Invasive Carcinoma of the Cervix: Exploring Putative Molecular Mechanisms Involved in Early Tumor Invasion

The establishment of a proangiogenic phenotype and epithelial-to-mesenchymal transition (EMT) are considered as critical events that promote the induction of invasive growth in epithelial tumors, and stimulation of lymphangiogenesis is believed to confer the capacity for early dissemination to cancer cells. Recent research has revealed substantial interdependence between these processes at the molecular level as they rely on common signaling networks. Of great interest are the molecular mechanisms of (lymph-)angiogenesis and EMT associated with the earliest stages of transition from intraepithelial development to invasive growth, as they could provide the source of potentially valuable tools for targeting tumor metastasis. However, in the case of early-stage cervical cancer, the players of (lymph-)angiogenesis and EMT processes still remain substantially uncharacterized. In this study, we used RNA sequencing to compare transcriptomes of HPV(+) preinvasive neoplastic lesions and early-stage invasive carcinoma of the cervix and to identify (lymph-)angiogenesis- and EMT-related genes and pathways that may underlie early acquisition of invasive phenotype and metastatic properties by cervical cancer cells. Second, we applied flow cytometric analysis to evaluate the expression of three key lymphangiogenesis/EMT markers (VEGFR3, MET, and SLUG) in epithelial cells derived from enzymatically treated tissue specimens. Overall, among 201 differentially expressed genes, a considerable number of (lymph-)angiogenesis and EMT regulatory factors were identified, including genes encoding cytokines, growth factor receptors, transcription factors, and adhesion molecules. Pathway analysis confirmed enrichment for angiogenesis, epithelial differentiation, and cell guidance pathways at transition from intraepithelial neoplasia to invasive carcinoma and suggested immune-regulatory/inflammatory pathways to be implicated in initiation of invasive growth of cervical cancer. Flow cytometry showed cell phenotype-specific expression pattern for VEGFR3, MET, and SLUG and revealed correlation with the amount of tumor-infiltrating lymphocytes at the early stages of cervical cancer progression. Taken together, these results extend our understanding of driving forces of angiogenesis and metastasis in HPV-associated cervical cancer and may be useful for developing new treatments.