m6A Regulator-Mediated Tumour Infiltration and Methylation Modification in Cervical Cancer Microenvironment

Comprehensive landscape of m6A regulator-related gene patterns and tumor microenvironment infiltration characterization in gastric cancer

The epigenetic regulation of N6-methyladenosine (m6A) has attracted considerable interest in tumor research, but the potential roles of m6A regulator-related genes, remain largely unknown within the context of gastric cancer (GC) and tumor microenvironment (TME). Here, a comprehensive strategy of data mining and computational biology utilizing multiple datasets based on 28 m6A regulators (including novel anti-readers) was employed to identify m6A regulator-related genes and patterns and elucidate their underlying mechanisms in GC. Subsequently, a scoring system was constructed to evaluate individual prognosis and immunotherapy response. Three distinct m6A regulator-related patterns were identified through the unsupervised clustering of 56 m6A regulator-related genes (all significantly associated with GC prognosis). TME characterization revealed that these patterns highly corresponded to immune-inflamed, immune-excluded, and immune-desert phenotypes, and their TME characteristics were highly consistent with different clinical outcomes and biological processes. Additionally, an m6A-related scoring system was developed to quantify the m6A modification pattern of individual samples. Low scores indicated high survival rates and high levels of immune activation, whereas high scores indicated stromal activation and tumor malignancy. Furthermore, the m6A-related scores were correlated with tumor mutation loads and various clinical traits, including molecular or histological subtypes and clinical stage or grade, and the score had predictive values across all digestive system tumors and even in all tumor types. Notably, a low score was linked to improved responses to anti-PD-1/L1 and anti-CTLA4 immunotherapy in three independent cohorts. This study has expanded the important role of m6A regulator-related genes in shaping TME diversity and clinical/biological traits of GC. The developed scoring system could help develop more effective immunotherapy strategies and personalized treatment guidance.

Manipulating the tumour immune microenvironment by N6-methyladenosine RNA modification

N6-methyladenosine (m6A), a posttranscriptional regulatory mechanism, is the most common epigenetic modification in mammalian mRNA. M6A modifications play a crucial role in the developmental network of immune cells. The expression of m6A-related regulators often affects carcinogenesis and tumour suppression networks. In the tumour microenvironment, m6A-modified enzymes can affect the occurrence and progression of tumours by regulating the activation and invasion of tumour-associated immune cells. Immunotherapy, which utilises immune cells, has been demonstrated to be a powerful weapon in tumour treatment and is increasingly being used in the clinic. Here, we provide an updated and comprehensive overview of how m6A modifications affect invasive immune cells and their potential role in immune regulation. In addition, we summarise the regulation of epigenetic regulators associated with m6A modifications in tumour cells on the antitumour response of immune cells in the tumour immune microenvironment. These findings provide new insights into the role of m6A modifications in the immune response and tumour development, leading to the development of novel immunotherapies for cancer treatment.

A comprehensive review of m6A research in cervical cancer

Cervical cancer (CC) remains one of the most common malignancies among women worldwide, posing a serious threat to women's health. N6-methyladenosine (m6A) modification, as the most abundant type of RNA methylation modification, and has been found to play a crucial role in various cancers. Current research suggests a close association between RNA m6A modification and the occurrence and progression of CC, encompassing disruptions in m6A levels and its regulatory machinery. This review summarizes the current status of m6A modification research in CC, explores the mechanisms underlying m6A levels and regulators (methyltransferases, demethylases, reader proteins) in CC and examines the application of small-molecule inhibitors of m6A regulators in disease treatment. The findings provide new insights into the future treatment of CC.

The m6A methyltransferase METTL5 promotes neutrophil extracellular trap network release to regulate hepatocellular carcinoma progression

BACKGROUND

Hepatocellular carcinoma (HCC) is one of the most common malignant tumors worldwide, it has a poor prognosis due to its highly invasive and metastatic nature. Consequently, identifying effective prognostic markers and potential therapeutic targets has been extensively investigated. METTL5, an 18S rRNA methyltransferase, is abnormally high in HCC. But its biological function and prognostic significance in HCC remain largely unelucidated. This study aimed to investigate the role of METTL5 in HCC progression, and elucidate its possible molecular mechanisms in HCC via transcriptome sequencing, providing new insights for identifying new HCC prognostic markers and therapeutic targets.

METHODS

The METTL5 expression in HCC and paracancerous tissues was analyzed using HCC immunohistochemical microarrays and bioinformatic retrieval methods to correlate METTL5 with clinicopathological features and survival prognosis. We constructed a METTL5 knockdown hepatocellular carcinoma cell line model and an animal model to determine the effect of METTL5 on hepatocellular carcinoma progression. Subsequently, RNA sequencing was performed to analyze the molecular mechanism of METTL5 in HCC based on the sequencing results, and relevant experiments were performed to verify it.

RESULTS

We found that METTL5 expression was elevated in hepatocellular carcinoma tissues and correlated with poor patient prognosis, and in the analysis of clinicopathological features showed a correlation with TNM staging. In hepatocellular carcinoma cell lines with knockdown of METTL5, the malignant biological behavior was significantly reduced both in vitro and in vivo. Based on the sequencing results as well as the results of GO functional enrichment analysis and KEGG pathway enrichment analysis, we found that METTL5 could promote the generation and release of neutrophil extracellular capture network (NETs) and might further accelerate the progression of HCC.

CONCLUSION

The m6A methyltransferase METTL5 is overexpressed in hepatocellular carcinoma (HCC) and correlates with poor prognosis. METTL5 accelerates malignant progression of HCC by promoting generation and release of the neutrophil extracellular traps (NETs) network, providing new insights for clinical biomarkers and immunotherapeutic targets in HCC prognosis.

m6A-mediated lncRNA NEAT1 plays an oncogenic role in non-small cell lung cancer by upregulating the HMGA1 expression through binding miR-361-3p

BACKGROUND

Lung cancer is the most common primary malignant tumor of the lung, and 85% of lung cancer is non-small cell lung cancer (NSCLC). The N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) have been widely reported to participate in the development of non-small cell lung cancer.

OBJECTIVE

However, the potential molecular mechanisms of m6A-regulated lncRNAs in NSCLC still need further investigation.

METHODS

The expression levels and the role of lncRNA NEAT1 in NSCLC tissues or cells were measured by RT-qPCR, Western blot, cell counting kit 8 (CCK-8), flow cytometry assay. RNA immunoprecipitation (RIP) was used to measure the levels of m6A modification of NEAT1. Bioinformatics analysis and dual-luciferase reporter gene assay were detected the relationship between miR-361-3p and NEAT1/HMGA1. Mouse xenograft tumor models were established to confirm the effects of lncRNA NEAT1 in vivo.

RESULTS

In this study, we verified whether m6A-modified lncRNA nuclear enriched abundant transcript 1 (NEAT1) is involved in NSCLC progression via miR-361-3p/HMGA1 axis. Firstly, we found that lncRNA NEAT1 was upregulated in NSCLC, and was associated with a poor survival in NSCLC patients. Methyltransferase like 3 (METTL3)-mediated m6A modification stabilized and upregulated NEAT1 expression. Next, function experiment indicated that depletion of METTL3 and NEAT1 induced cell apoptosis and inhibited cell proliferation, epithelial-mesenchymal transition (EMT). Likewise, in vivo experiments further supported the oncogenic role of NEAT1 in NSCLC. In addition, the molecular mechanism was uncovered in our study, and we found that lncRNA NEAT1 promoted the expression of high-mobility group AT-hook 1 (HMGA1) by sponging miR-361-3p and then promoted tumorigenesis of NSCLC.

CONCLUSION

In conclusion, our findings demonstrated that METTL3-mediated m6A modification accelerated NSCLC progression by regulating the NEAT1/miR-361-3p/HMGA1 axis, which provides important targets for the treatment of NSCLC.

Four Markers Useful for the Distinction of Intrauterine Growth Restriction in Sheep

Intrauterine growth restriction (IUGR) is a common perinatal complication in animal reproduction, with long-lasting negative effects on neonates and postnatal animals, which seriously negatively affects livestock production. In this study, we aimed to identify potential genes associated with the diagnosis of IUGR through bioinformatics analysis. Based on the 73 differentially expressed related genes obtained by differential analysis and weighted gene co-expression network analysis, we used three machine learning algorithms to identify 4 IUGR-related hub genes (IUGR-HGs), namely, ADAM9, CRYL1, NDP52, and SERPINA7, whose ROC curves showed that they are a good diagnostic target for IUGR. Next, we identified two molecular subtypes of IUGR through consensus clustering analysis and constructed a gene scoring system based on the IUGR-HGs. The results showed that the IUGR score was positively correlated with the risk of IUGR. The AUC value of IUGR scoring accuracy was 0.970. Finally, we constructed a new artificial neural network model based on the four IUGR-HGs to diagnose sheep IUGR, and its accuracy reached 0.956. In conclusion, the IUGR-HGs we identified provide new potential molecular markers and models for the diagnosis of IUGR in sheep; they can better diagnose whether sheep have IUGR. The present findings provide new perspectives on the diagnosis of IUGR.

Identification of the expression patterns and potential prognostic role of m6A-RNA methylation regulators in Wilms Tumor

BACKGROUND

To explore the potential role of m6A methylation modification in Wilms Tumor (WT) by m6A-RNA Methylation (m6A) regulators.

METHODOLOGY

The association of m6A modification patterns with immune and prognostic characteristics of tumors was systematically evaluated using 19 m6A regulators extracted from Wilms Tumor's samples in public databases. A comprehensive model of "m6Ascore" was constructed using principal component analysis, and its prognostic value was evaluated.

RESULTS

Almost all m6A regulators were differentially expressed between WT and normal tissues. Unsupervised clustering identified three distinct m6A clusters that differed in both immune cell infiltration and biological pathways. The m6Ascore was constructed to quantify m6A modifications in individual patients. Our analysis suggests that m6Ascore is an independent prognostic factor for WT and can be used as a novel predictor of WT prognosis.

CONCLUSIONS

This study comprehensively explored and systematically characterized m6A modifications in WT. m6A modification patterns play a critical role in the tumor immune microenvironment (TIME) and WT prognosis. m6Ascore provides a more comprehensive understanding of m6A modifications in WT and offers a practical tool for predicting WT prognosis. This study will help clinicians to identify valid indicators of WT to improve the poor prognosis of this disease.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at https://www.aliyundrive.com/drive/folder/64be739cd6956a741fb24670baeea53422be6024 .

Comprehensive analysis of cuproptosis-related lncRNAs model in tumor immune microenvironment and prognostic value of cervical cancer

Cervical cancer (CC) is the fourth leading gynecological malignancy in females worldwide. Cuproptosis, a form of cell death induced by copper, elicits a novel therapeutic strategy in anticancer therapy. Nonetheless, the effects of cuproptosis-related lncRNAs in CC remain unclear. Therefore, we aim to investigate cuproptosis-related lncRNAs, develop a risk model for prognostic prediction, and elucidate the immunological profile of CC. Transcription profiles and clinical follow-up data of CC were retrieved from The Cancer Genome Atlas (TCGA) database. Afterward, the risk model was built by distinguishing prognostic cuproptosis-related lncRNAs using the least absolute shrinkage and selection operator (LASSO) Cox regression. The correctness of the risk model was validated, and a nomogram was established followed by tumor immune microenvironment analysis. Tumor immune dysfunction and exclusion (TIDE) scores were used to assess immunotherapy response, and anticancer pharmaceutical half-maximal inhibitory concentration (IC50) prediction was performed for potential chemotherapy medicines. Finally, through coexpression analysis, 199 cuproptosis-related lncRNAs were collected. A unique risk model was generated using 6 selected prognostic cuproptosis-related lncRNAs. The risk score performed a reliable independent prediction of CC survival with higher diagnostic effectiveness compared to generic clinical characteristics. Immunological cell infiltration investigation indicated that the risk model was substantially linked with CC patients’ immunology, and the low-risk patients had lower TIDE scores and increased checkpoint expression, suggesting a stronger immunotherapy response. Besides, the high-risk group exhibited distinct sensitivity to anticancer medications. The immune-related progression was connected to the differentially expressed genes (DEGs) between risk groups. Generally, the risk model comprised 6 cuproptosis-related lncRNAs that may help predict CC patients’ overall survival, indicate immunocyte infiltration, and identify individualized treatment.

A signal recognition particle-related joint model of LASSO regression, SVM-RFE and artificial neural network for the diagnosis of systemic sclerosis-associated pulmonary hypertension

Background: Systemic sclerosis-associated pulmonary hypertension (SSc-PH) is one of the most common causes of death in patients with systemic sclerosis (SSc). The complexity of SSc-PH and the heterogeneity of clinical features in SSc-PH patients contribute to the difficulty of diagnosis. Therefore, there is a pressing need to develop and optimize models for the diagnosis of SSc-PH. Signal recognition particle (SRP) deficiency has been found to promote the progression of multiple cancers, but the relationship between SRP and SSc-PH has not been explored. Methods: First, we obtained the GSE19617 and GSE33463 datasets from the Gene Expression Omnibus (GEO) database as the training set, GSE22356 as the test set, and the SRP-related gene set from the MSigDB database. Next, we identified differentially expressed SRP-related genes (DE-SRPGs) and performed unsupervised clustering and gene enrichment analyses. Then, we used least absolute shrinkage and selection operator (LASSO) regression and support vector machine-recursive feature elimination (SVM-RFE) to identify SRP-related diagnostic genes (SRP-DGs). We constructed an SRP scoring system and a nomogram model based on the SRP-DGs and established an artificial neural network (ANN) for diagnosis. We used receiver operating characteristic (ROC) curves to identify the SRP-related signature in the training and test sets. Finally, we analyzed immune features, signaling pathways, and drugs associated with SRP and investigated SRP-DGs' functions using single gene batch correlation analysis-based GSEA. Results: We obtained 30 DE-SRPGs and found that they were enriched in functions and pathways such as "protein targeting to ER," "cytosolic ribosome," and "coronavirus disease-COVID-19". Subsequently, we identified seven SRP-DGs whose expression levels and diagnostic efficacy were validated in the test set. As one signature, the area under the ROC curve (AUC) values for seven SRP-DGs were 0.769 and 1.000 in the training and test sets, respectively. Predictions made using the nomogram model are likely beneficial for SSc-PH patients. The AUC values of the ANN were 0.999 and 0.860 in the training and test sets, respectively. Finally, we discovered that some immune cells and pathways, such as activated dendritic cells, complement activation, and heme metabolism, were significantly associated with SRP-DGs and identified ten drugs targeting SRP-DGs. Conclusion: We constructed a reliable SRP-related ANN model for the diagnosis of SSc-PH and investigated the possible role of SRP in the etiopathogenesis of SSc-PH by bioinformatics methods to provide a basis for precision and personalized medicine.

Knockdown of METTL5 inhibits the Myc pathway to downregulate PD-L1 expression and inhibits immune escape of hepatocellular carcinoma cells

The incidence of hepatocellular carcinoma (HCC) is raised annually, which causes a great harm to people's health. This research aimed to investigate the influence and mechanism of methyltransferase-like 5 (METTL5) in HCC. According to The Cancer Genome Atlas (TCGA) database, METTL5 levels and prognosis was analyzed in HCC. Next, in HCC tissues and cells, METTL5 expression was examined via quantitative real-time polymerase chain reaction (qRT-PCR). Biological behaviors of HCC cells were assessed by Cell Counting Kit-8 (CCK-8), colony formation, transwell and flow cytometry assays. Gene Set Enrichment Analysis (GSEA) was applied to predict METTL5 related pathway. The possible binding sites of programmed cell death 1 ligand 1 (PD-L1) and myelocytomatosis viral oncogene (Myc) was predicted by JASPAR database. Western blot was utilized to test the change of PD-L1 and Myc pathway related proteins [cellular (c)-Myc, chaperonin containing TCP1 subunit 2 (CCT2) and chromobox protein homolog 3 (CBX3)]. In HCC tissues and cells, METTL5 expression was increased. High METTL5 expression was associated with poor prognosis. Knockdown of METTL5 inhibited HCC cell proliferation and invasion, induced cell apoptosis and reduced the expression of PD-L1, c-Myc, CCT2 and CBX3. The bind between PD-L1 and the Myc promoter in HCC cells was confirmed using Chip and luciferase reporter assays. Moreover, the influences of knockdown of METTL5 on PD-L1 expression and HCC cell biological behaviors were reversed by overexpression of Myc. Knockdown of METTL5 inhibited PD-L1 expression and malignant cell behavior of HCC through inhibiting the Myc pathway.

M6A regulator-mediated immune infiltration and methylation modification in hepatocellular carcinoma microenvironment and immunotherapy

Introduction: Tremendous evidence indicates that N6-methyladenosine (m6A) epigenetic modification and m6A-related enzymes constitute a complex network, which jointly regulates prevailing pathological processes and various signaling pathways in humankind. Currently, the role of the m6A-mediated molecular regulatory network in hepatocellular carcinoma (HCC) remains elusive. Methods: We recruited expression and pathological files of 368 HCC patients from The Cancer Genome Atlas cohort. Four public datasets serve as external authentication sets for nearest template prediction (NTP) validation. The correlation between 35 regulators and their prognostic value was compared. Gene set variation analysis (GSVA) was used to explore the latent mechanism. Four independent algorithms (ssGSEA, xCell, MCP-counter, and TIMER) were used to calculate the ratio of tumor cells and non-tumor cells to evaluate the tumor immune microenvironment. The m6Ascore model was established by principal component analysis (PCA). Prediction of immunotherapy and potential drugs was performed using TIDE and SubMap. Results: A total of 35 m6A regulators were widely associated, most of which were risk factors for HCC patients. The m6A phenotypic-cluster revealed differences in regulator transcriptional level, gene mutation frequency, functional pathways, and immune cell infiltration abundance under distinct m6A patterns. As expected, the m6A gene cluster confirmed the aforementioned results. The m6Ascore model further found that patients in the high-m6Ascore group were associated with lower tumor purity, higher enrichment of immune and stromal cells, upregulation of metabolic pathways, lower expression of m6A regulators, and favorable outcomes. Low-m6Ascore patients were associated with adverse outcomes. Notably, low-m6Ascore patients might be more sensitive to anti-PD-L1 therapy. Conclusion: This study found that a classification model based on the m6A manner could predict HCC prognosis and response to immunotherapy for HCC patients, which might improve prognosis and contribute to clinical individualized decision-making.

MiR-95-3p acts as a prognostic marker and promotes cervical cancer progression by targeting VCAM1

BACKGROUND

Cervical cancer patients have a high risk of metastasis and a poor prognosis with shorter disease-free survival. Thus, novel biomarkers and feasible therapies urgently need to be discovered. Previous studies have shown that miR-95-3p plays crucial roles in several cancer types. However, the roles of miR-95-3p in cervical cancer remain unknown.

METHODS

The micro ribonucleic acid (miRNA) expression data and clinical characteristics of cervical cancer samples were downloaded from The Cancer Genome Atlas (TCGA) database. Univariate and multivariate Cox regression analyses were conducted to identify the prognostic-related miRNAs. The potential target genes of miR-95-3p were predicted by the TargetScan database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted to explore the target gene of miR-95-3p. The effects of miR-95-3p inhibition and overexpression on cell proliferation were inspected by cell counting kit-8 (CCK-8) assays and cell colony formation assays. Wound-healing assays and transwell assays were also used to examine cell migration ability in HeLa and SiHa cells.

RESULTS

MiR-95-3p was the only miRNA significantly associated with the poor prognosis of cervical squamous cell carcinoma. A further analysis suggested that vascular cell adhesion molecule 1 (VCAM1) is a target gene of miR-95-3p in cervical cancer, and miR-95-3p promotes the malignant behavior of cervical cancer cells by inhibiting the expression of VCAM1. The CCK-8 and cell colony assays showed that miR-95-3p downregulation significantly suppressed cell proliferation in the HeLa and SiHa cells. The transwell and wound-healing assays showed that miR-95-3p inhibition suppressed cell migration in the HeLa and SiHa cells. Further the Western blot analysis and the quantitative real-time-polymerase chain reaction (qRT-PCR) showed that the knockdown of miR-95-3p in HeLa cells resulted in increased VCAM1 expression. And VCAM1 was highly expressed in the paired adjacent normal cervical epithelium tissue samples, but lowly expressed in the cervical tumor tissue samples.

CONCLUSIONS

Our study was the first to show that miR-95-3p could serve as a prognostic biomarker of cervical cancer. Mechanistically, we discovered that miR-95-3p inhibited the expression of the cell adhesion molecule VCAM1 and thus promoted further tumor progression.

Gene signature of m6A RNA regulators in diagnosis, prognosis, treatment, and immune microenvironment for cervical cancer

Continuing studies imply that m⁶A RNA modification is involved in the development of cervical cancer (CC), but lack strong support on recurrence and diagnosis prediction. In this research, a comprehensive analysis of 33 m⁶A regulators was performed to fulfill them. Here, we performed diagnostic and prognosis models and identified key regulators, respectively. Then the CC patients were separated into two clusters in accordance with 33 regulators, and participants in the cluster 1 had a worse prognosis. Subsequently, the m⁶AScore was calculated to quantify the m⁶A modification pattern based on regulators and we found that patients in cluster 1 had higher m⁶AScore. Afterwards, immune microenvironment, cell infiltration, escape analyses and tumor burden mutation analyses were executed, and results showed that m⁶AScore was correlated with them, but to a limited extent. Interestingly, HLAs and immune checkpoint expression, and immunophenoscore in patients with high-m⁶AScores were significantly lower than those in the low-m⁶AScore group. These suggested the m⁶AScores might be used to predict the feasibility of immunotherapy in patients. Results provided a distinctive perspective on m⁶A modification and theoretical basis for CC diagnosis, prognosis, clinical treatment strategies, and potential mechanism exploration.