Identification of DAPK1 Promoter Hypermethylation as a Biomarker for Intra-Epithelial Lesion and Cervical Cancer: A Meta-Analysis of Published Studies, TCGA, and GEO Datasets

Methylation biomarkers for early cancer detection and diagnosis: Current and future perspectives

The increase in recent scientific studies on cancer biomarkers has brought great new insights into the field. Moreover, novel technological breakthroughs such as long read sequencing and microarrays have enabled high throughput profiling of many biomarkers, while advances in bioinformatic tools have made the possibility of developing highly reliable and accurate biomarkers a reality. These changes triggered renewed interest in biomarker research and provided tremendous opportunities for enhancing cancer management and improving early disease detection. DNA methylation alterations are known to accompany and contribute to carcinogenesis, making them promising biomarkers for cancer, namely due to their stability, frequency and accessibility in bodily fluids. The advent of newer minimally invasive experimental methods such as liquid biopsies provide the perfect setting for methylation-based biomarker development and application. Despite their huge potential, accurate and robust biomarkers for the conclusive diagnosis of most cancer types are still not routinely used, hence a strong need for sustained research in this field is still needed. This review provides a brief exposition of current methylation biomarkers for cancer diagnosis and early detection, including markers already in clinical use as well as various upcoming ones. It also outlines how recent big data and novel technologies will revolutionise the next generation of cancer tests in supplementing or replacing currently existing invasive techniques.

Integrated bioinformatics analysis of IFITM1 as a prognostic biomarker and investigation of its immunological role in prostate adenocarcinoma

Introduction

Prostate adenocarcinoma (PRAD) is a highly aggressive malignancy with high mortality and poor prognosis, and its potential mechanism remains unclear. Our study aimed to identify novel markers for the prognosis of PRAD using bioinformatics technology.

Methods

The GSE32571 dataset was downloaded from the GEO database, and analyzed via the limma R package to identify differentially expressed genes (DEGs) and differentially expressed immune score-related genes (DEISRGs). The immune-related genes (IRGs) were further obtained by overlapping DEISRGs and DEGs, and the core gene was identified via survival analysis. Furthermore, the expression level, prognostic value, and potential functions of the core gene were evaluated via multiple bioinformatics databases.

Results

A total of 301 IRGs were identified from the GSE32571 dataset, and IFITM1 was a down-regulated gene in several types of cancer, including PRAD. Besides, low expression of IFITM1 was associated with a poor prognosis in PRAD. GSEA indicated that the vital pathways of IFITM1-associated genes were mainly enriched in primary immunodeficiency, Th17 cell differentiation, Th1, and Th2 cell differentiation, natural killer cell-mediated cytotoxicity, myeloid dendritic cell activation, regulation of leukocyte activation, etc. Furthermore, IFITM1 was closely correlated with 22 types of tumor-infiltrating immune cells.

Discussion

IFITM1 was a prognostic biomarker for PRAD patients, and it can be acted as a potential immune therapy target in PRAD.

Alteration of Gene and miRNA Expression in Cervical Intraepithelial Neoplasia and Cervical Cancer

Background: Cervical cancer is one of the most common malignancies in women in terms of prevalence and mortality. Cervical cancer has some particularities that distinguish it from any other oncologic pathology: first, it is completely preventable by prompt detection of its precursor, cervical intraepithelial neoplasia (CIN); second, the Human Papillomavirus (HPV) infection is a known etiological agent; third, the mean age at diagnosis is much lower than in other oncologic conditions, as a consequence of the sexually-transmitted HPV. Methods: We evaluated the expression level of several long noncoding RNAs and a microRNA in samples from 30 patients with CIN, 9 with cervical cancer and 38 normal samples using qRT-PCR technology. Results: We observed higher expression levels for MEG3, DAPK1, MLH1 and MALAT1 in CIN samples than in normal samples, whereas TIMP3 and SOX1 had lower expression levels. For cancer samples, DAPK1, MLH1 and MALAT1 had higher expression, and MEG3, TIMP3 and SOX1 had lower expression when compared to normal samples. In the case of CIN versus cancer samples, only MEG3 gene showed a statistically significant difference. The expression of miR-205-5p was lower in both CIN and cancer samples compared to normal samples. Conclusion: Decreased MEG3 expression could be considered an alarm signal in the transition from a premalignant cervical lesion to invasive cancer, while altered expression levels of TIMP3, SOX1, MLH1, MALAT1 and miR-205-5p could serve as early biomarkers in the diagnosis of premalignant cervical lesions. Future studies, including a larger number of patients with CIN, will be of particular importance in validating these observations.

The Role of Autophagy in Tumor Immune Infiltration in Colorectal Cancer

Objective. This study is aimed at exploring the association between autophagy and tumor immune infiltration (TII) in colorectal cancer (CRC). Methods and Materials. We downloaded the transcriptome profiling and clinical data for CRC from The Cancer Genome Atlas (TCGA) database and obtained the normal colon transcriptome profiling data from Genotype-Tissue Expression Project (GTEx) database. The list of autophagy-related signatures was obtained from the Human Autophagy Database. We isolated the autophagy-related genes from the CRC gene expression matrix and constructed an autophagy-related prognostic (ARP) risk model. Then, we constructed a multiROC curve to validate the prognostic ability of the ARP risk model. CIBERSORT was used to determine the fractions of 22 immune cells in each CRC sample, and the association between these TII cells and CRC clinical variables was further investigated. Finally, we estimated the association of 3 hub-ARP signatures and 20 different types of TII cell distribution. Results. We classified 447 CRC patients into 224 low-risk and 223 high-risk patients using the median ARP risk score. According to the univariate survival test results, except for gender ( $P=0.672$ ), age ( $P=0.008$ ), cancer stage, and pathological stage T, M, and N were closely correlated with the prognosis of CRC patients ( $P<0.001$ ). Multivariate survival analysis results indicate that age and rescore were the only independent prognostic indicators with significant differences ( $P<0.05$ ). After merging the immune cell distribution (by CIBERSORT) with the CRC clinical data, the results indicate that activated macrophage M0 cells exhibited the highest clinical response, which included cancer stage and stage T, N, and M. Additionally, six immune cells were closely associated with cancer stage, including regulatory T cells (Tregs), gamma delta T cells, follicular helper T cells, activated memory CD4 T cells, activated NK cells, and resting dendritic cells. Finally, we evaluated the correlation of ARP signatures with TII cell distribution. Compared with the other correlation, NRG1 and plasma cells (↑), risk score and macrophage M1 (↑), NRG1 and dendritic cell activated (↑), CDKN2A and T cell CD4 memory resting (↓), risk score and T cell CD8 (↑), risk score and T cell CD4 memory resting (↓), and DAPK1 and T cell CD4 memory activated (↓) exhibited a stronger association ( $P<0.0001$ ). Conclusions. In summary, we explored the correlation between the risk of autophagy and the TII microenvironment in CRC patients. Furthermore, we integrated different CAR signatures with tumor-infiltrating immune cells and found robust associations between different levels of CAR signature expression and immune cell infiltrating density.

Transposons: Unexpected players in cancer

Transposons are repetitive DNA sequences encompassing about half of the human genome. They play a vital role in genome stability maintenance and contribute to genomic diversity and evolution. Their activity is regulated by various mechanisms considering the deleterious effects of these mobile elements. Various genetic risk factors and environmental stress conditions affect the regulatory pathways causing alteration of transposon expression. Our knowledge of the biological role of transposons is limited especially in various types of cancers. Retrotransposons of different types (LTR-retrotransposons, LINEs and SINEs) regulate a plethora of genes that have a role in cell reprogramming, tumor suppression, cell cycle, apoptosis, cell adhesion and migration, and DNA repair. The regulatory mechanisms of transposons, their deregulation and different mechanisms underlying transposon-mediated carcinogenesis in humans focusing on the three most prevalent types, lung, breast and colorectal cancers, were reviewed. The modes of regulation employed include alternative splicing, deletion, insertion, duplication in genes and promoters resulting in upregulation, downregulation or silencing of genes.

Cervical Carcinoma: Oncobiology and Biomarkers

Cervical cancer is one of the most common types of carcinomas causing morbidity and mortality in women in all countries of the world. At the moment, the oncology, oncobiology, and oncomorphology of cervical cancer are characterized by the accumulation of new information; various molecular biological, genetic, and immunohistochemical methods of investigation of the mechanisms of cervical carcinogenesis are tested and applied; targeted antitumour drugs and diagnostic, prognostic, and predictive biomarkers are being searched for. Many issues of the etiopathogenesis of cervical cancer have not been sufficiently studied, and the role of many biomarkers characterizing various stages of cervical carcinogenesis remains unclear. Therefore, the target of this review is to systematize and understand several problems in the pathogenesis of cervical cancer and to evaluate the significance and role of biomarkers in cervical carcinogenesis.

Identification of autophagy-related risk signatures for the prognosis, diagnosis, and targeted therapy in cervical cancer

Background

To rummage autophagy-related prognostic, diagnostic, and therapeutic biomarkers in cervical cancer (CC).

Methods

The RNA-sequence and clinical information were from the TCGA and GTEx databases. We operated Cox regression to determine signatures related to overall survival (OS) and recurrence-free survival (RFS) respectively. The diagnostic and therapeutic effectiveness of prognostic biomarkers were further explored.

Results

We identified nine (VAMP7, MTMR14, ATG4D, KLHL24, TP73, NAMPT, CD46, HGS, ATG4C) and three risk signatures (SERPINA1, HSPB8, SUPT20H) with prognostic values for OS and RFS respectively. Six risk signatures (ATG4C, ATG4D, CD46, TP73, SERPINA1, HSPB8) were selected for qPCR. We screened five prognostic signatures(ATG4C, CD46, HSPB8, MTMR14, NAMPT) with diagnostic function through the GEO database. Correlation between our models and treatment targets certificated the prognostic score provided a reference for precision medicine.

Conclusions

We constructed OS and RFS prognostic models in CC. Autophagy-related risk signatures might serve as diagnostic and therapeutic biomarkers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02073-w.

Identification and Analysis of Potential Key Genes Associated With Hepatocellular Carcinoma Based on Integrated Bioinformatics Methods

BACKGROUND

Hepatocellular carcinoma (HCC) is a type of primary liver tumor with poor prognosis and high mortality, and its molecular mechanism remains incompletely understood. This study aimed to use bioinformatics technology to identify differentially expressed genes (DEGs) in HCC pathogenesis, hoping to identify novel biomarkers or potential therapeutic targets for HCC research.

METHODS

The bioinformatics analysis of our research mostly involved the following two datasets: Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). First, we screened DEGs based on the R packages (limma and edgeR). Using the DAVID database, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of DEGs were carried out. Next, the protein-protein interaction (PPI) network of the DEGs was built in the STRING database. Then, hub genes were screened through the cytoHubba plug-in, followed by verification using the GEPIA and Oncomine databases. We demonstrated differences in levels of the protein in hub genes using the Human Protein Atlas (HPA) database. Finally, the hub genes prognostic values were analyzed by the GEPIA database. Additionally, using the Comparative Toxicogenomics Database (CTD), we constructed the drug-gene interaction network.

RESULTS

We ended up with 763 DEGs, including 247 upregulated and 516 downregulated DEGs, that were mainly enriched in the epoxygenase P450 pathway, oxidation-reduction process, and metabolism-related pathways. Through the constructed PPI network, it can be concluded that the P53 signaling pathway and the cell cycle are the most obvious in module analysis. From the PPI, we filtered out eight hub genes, and these genes were significantly upregulated in HCC samples, findings consistent with the expression validation results. Additionally, survival analysis showed that high level gene expression of CDC20, CDK1, MAD2L1, BUB1, BUB1B, CCNB1, and CCNA2 were connected with the poor overall survival of HCC patients. Toxicogenomics analysis showed that only topotecan, oxaliplatin, and azathioprine could reduce the gene expression levels of all seven hub genes.

CONCLUSION

The present study screened out the key genes and pathways that were related to HCC pathogenesis, which could provide new insight for the future molecularly targeted therapy and prognosis evaluation of HCC.

DNA methylation for cervical cancer screening: a training set in China

Background

Despite rapid improvements in DNA methylation tools for cervical cancer screening, few robust, exploratory studies have been performed using the combination of two host genes, EPB41L3 and JAM3, newly developed assays.

Methods

A review of abnormal liquid-based cytology and/or high-risk human papillomavirus (hrHPV) data from outpatient clinics in the study center from March 2018 to March 2019 was performed. Eligible patients with definitive histological pathology results were included, and their residual cytology samples were assessed for EPB41L3 and JAM3 methylation. The diagnostic accuracies of various screening strategies for definitive pathology and for cervical intraepithelial neoplasia (CIN) 2 or more severe lesions (CIN2+) were compared.

Results

In total, 306 patients were successfully tested; 301 cases with cervical histological pathology were included in the final analysis, including 118 (39.2%) and 183 (60.8%) cases of inflammation/CIN1 and CIN2+, respectively. Regarding CIN2+ detection, methylation status and hrHPV plus methylation had similar positive predictive values (0.930 and 0.954, respectively, p = 0.395). Additionally, hrHPV, methylation, and hrHPV plus methylation had similar negative predictive values (0.612, 0.679, and 0.655, p = 0.677) that were significantly higher than that of cytology alone (0.250, p values 0.012, 0.001, and 0.001, respectively). For 49 cases with negative hrHPV results, positive methylation alone was able to differentiate CIN2+ from inflammation/CIN1.

Conclusions

Methylation of both EPB41L3 and JAM3 is an accurate and feasible screening method for CIN2+.

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

Methylation functions in the pathogenesis of cervical cancer. In the present study, we applied an integrated bioinformatics analysis to identify the aberrantly methylated and differentially expressed genes (DEGS), and their related pathways in cervical cancer. Data of gene expression microarrays (GSE9750) and gene methylation microarrays (GSE46306) were gained from Gene Expression Omnibus (GEO) databases. Hub genes were identified by 'limma' packages and Venn diagram tool. Functional analysis was conducted by FunRich. Search Tool for the Retrieval of Interacting Genes Database (STRING) was used to analyze protein-protein interaction (PPI) information. Gene Expression Profiling Interactive Analysis (GEPIA), immunohistochemistry staining, and ROC curve analysis were conducted for validation. Gene Set Enrichment Analysis (GSEA) was also performed to identify potential functions.We retrieved two upregulated-hypomethylated oncogenes and eight downregulated-hypermethylated tumor suppressor genes (TSGs) for functional analysis. Hypomethylated and highly expressed genes (Hypo-HGs) were significantly enriched in cell cycle and autophagy, and hypermethylated and lowly expressed genes (Hyper-LGs) in estrogen receptor pathway and Wnt/β-catenin signaling pathway. Estrogen receptor 1 (ESR1), Erythrocyte membrane protein band 4.1 like 3 (EPB41L3), Endothelin receptor B (EDNRB), Inhibitor of DNA binding 4 (ID4) and placenta-specific 8 (PLAC8) were hub genes. Kaplan-Meier method was used to evaluate survival data of each identified gene. Lower expression levels of ESR1 and EPB41L3 were correlated with a shorter survival time. GSEA results showed that 'cell adhesion molecules' was the most enriched item. This research inferred the candidate genes and pathways that might be used in the diagnosis, treatment, and prognosis of cervical cancer.

DNA Methylation and Hydroxymethylation in Cervical Cancer: Diagnosis, Prognosis and Treatment

Recent discoveries have led to the development of novel ideas and techniques that have helped elucidate the correlation between epigenetics and tumor biology. Nowadays, the field of tumor genetics has evolved to include a new type of regulation by epigenetics. An increasing number of studies have demonstrated the importance of DNA methylation and hydroxymethylation in specific genes in the progression of cervical cancer. Determining the methylation and hydroxymethylation profiles of these genes will help in the early prevention and diagnosis, monitoring recurrence, prognosis, and treatment of patients with cervical cancer. In this review, we focus on the significance of aberrant DNA methylation and hydroxymethylation in cervical cancer and the use of these epigenetic signatures in clinical settings.

Integrated analysis of transcriptome data revealed MMP3 and MMP13 as critical genes in anaplastic thyroid cancer progression

To better understand the molecular mechanisms of anaplastic thyroid carcinoma (ATC), we aimed to identify the hub genes specifically involved in ATC by integrated bioinformatics analysis. In this study, using three Gene Expression Omnibus data sets with the same platform GPL570, we screened hub genes involved in ATC progression. In vitro experiments, such as western blot analysis, Transwell assays, and coimmunoprecipitation, was performed to verify our findings. By comparing three subtypes of thyroid cancer with normal tissue, we found ATC harbored more changed genes than well and poorly differentiated thyroid cancer. Using specifically differentially expressed genes between ATC and normal thyroid tissues to perform Gene ontology (GO) analysis, ATC showed enrichments of GO terms involved in lymphocyte migration and activation, collagen catabolic and metabolic process, thyroid hormone synthesis, and embolism. Using genes involved in extracellular matrix, coexpression network analysis and protein-protein interaction analysis were performed to identify matrix metalloproteinase 3 (MMP3) and MMP13 as two hub genes. Our experimental data indicated that both MMP3 and MMP13 were upregulated in ATC and knockdown of either of them could notably suppress ATC cell invasion and migration. Mechanistically, Gene Set Enrichment Analysis, coimmunoprecipitation, and rescue experiments revealed MMP3 and MMP13 not only interacted with each other, but also regulated each other through the janus kinase/signal transducer and activator of transcription 3 and mammalian target of rapamycin pathways. In conclusion, we identified a specific molecular mechanisms for the development of ATC by integrated analysis of transcriptome and in vitro experiments, which suggested that MMP3 and MMP13 might be developed as novel therapeutic targets for ATC.

DNA methylation data-based molecular subtype classification related to the prognosis of patients with cervical cancer

Cervical cancer is one of the leading female health-killers among all types of malignancies globally. Human papillomavirus infection combined with genetic and epigenetic alterations have been indicated to be closely associated with the pathogenesis, progression, and malignant transformation of cervical cancer. Notably, during the complex tumorigenesis process, a series of DNA methylations occurs early and is the most frequent molecular behavior. In this study, to exploit the specific DNA methylation sites influencing the prognosis of patients with cervical cancer, 275 samples were downloaded from The Cancer Genome Atlas database and further analyzed. As a result, 1253 CpGs were found to have a significant correlation with patient prognosis and were further selected for the consistent clustering of samples into six subgroups. Specifically, the samples in every subgroup were different regarding the following: race, age, tumor stage, receptor status, histological type, metastasis status, and patient prognosis. In addition, we calculated the levels of methylation sites in all subgroups, with 79 methylation sites (corresponding to 81 genes) screened as the intrasubgroup-specific methylation sites. Moreover, signaling pathway enrichment analysis was conducted on the genes of the corresponding promoter regions of the above-described specific methylation sites, revealing that these genes were enriched in biological pathways closely associated with tumors, such as the cyclic guanosine monophosphate-dependent protein kinase and focal adhesion signaling pathways. Finally, the least absolute shrinkage and selection operator algorithm was employed to establish a prognostic prediction model for cervical cancer patients, with training and test sets used for testing and validation, respectively. In summary, the specific DNA methylation site-based classification is able to reflect the heterogeneity of cervical cancer tissue, contributing to the development of personalized therapy and the accurate prediction of patient prognosis.

Death associated protein kinase 1 (DAPK-1) is increased in preeclampsia

INTRODUCTION

Death associated protein kinase-1 (DAPK-1) is highly expressed in the placenta relative to all other human tissues. We examine whether it is differentially expressed with preeclampsia.

METHODS

We examined samples from a large prospective collection of plasma from 2002 women. We split the samples into two cohorts: Cohort 1 (n = 1000) and Cohort 2 (n = 1002). We first measured circulating DAPK-1 at 36 weeks' gestation in a nested case-control group (from Cohort 1) of 39 women who developed preeclampsia and 98 controls. We then validated our findings by measuring circulating levels in all samples from both cohorts. We also measured DAPK-1 in the circulation and placentas of women who were diagnosed with preterm preeclampsia or delivered a growth restricted infant at <34 weeks' gestation.

RESULTS

In the case-control study, circulating DAPK-1 was significantly increased in women destined to develop preeclampsia (p < 0.01). We validated this by measuring circulating levels in Cohorts 1 and 2. Again, circulating DAPK-1 was significantly higher (p < 0.001) among women destined to develop preeclampsia (Cohort 1, Area under the receiver operator characteristic curve (AUC) = 0.66; Cohort 2 AUC = 0.67). Circulating DAPK-1 was also significantly elevated in women with established preterm preeclampsia. Placental DAPK-1 mRNA and protein expression were elevated in women with established preeclampsia.

DISCUSSION

DAPK-1 is a novel placenta-enriched molecule that is elevated in the circulation of women preceding the diagnosis of preeclampsia and is likely to be secreted from the placenta.