The functions and prognostic values of m6A RNA methylation regulators in thyroid carcinoma

Diagnostic implications of ubiquitination-related gene signatures in Alzheimer's disease

The purpose of this study was to explore the diagnostic implications of ubiquitination-related gene signatures in Alzheimer's disease. In this study, we first collected 161 samples from the GEO database (including 87 in the AD group and 74 in the normal group). Subsequently, through differential expression analysis and the iUUCD 2.0 database, we obtained 3450 Differentially Expressed Genes (DEGs) and 806 Ubiquitin-related genes (UbRGs). After taking the intersection, we obtained 128 UbR-DEGs. Secondly, by conducting GO and KEGG enrichment analysis on these 128 UbR-DEGs, we identified the main molecular functions and biological pathways related to AD. Furthermore, through the utilization of GSEA analysis, we have gained insight into the enrichment of functions and pathways within both the AD and normal groups. Further, using lasso regression analysis and cross-validation techniques, we identified 22 characteristic genes associated with AD. Subsequently, we constructed a logistic regression model and optimized it, resulting in the identification of 6 RUbR-DEGs: KLHL21, WDR82, DTX3L, UBTD2, CISH, and ATXN3L. In addition, the ROC result showed that the diagnostic model we built has excellent accuracy and reliability in identifying AD patients. Finally, we constructed a lncRNA-miRNA-mRNA (competing endogenous RNA, ceRNA) regulatory network for AD based on six RUbR-DEGs, further elucidating the interaction between UbRGs and lncRNA, miRNA. In conclusion, our findings will contribute to further understanding of the molecular pathogenesis of AD and provide a new perspective for AD risk prediction, early diagnosis and targeted therapy in the population.

Comprehensive analysis of m6A RNA methylation regulators in esophageal carcinoma

Background

N6-methyladenosine (m6A) is the most pervasive modification of RNA methylation in eukaryotic cells. m6A modification plays a pivotal role in tumorigenesis and progression in many types of cancers. Until now, the role of m6A modification in esophageal carcinoma (ESCA) has remained obscure. The aim of the study was to construct and validate prognostic signatures based on m6A regulators for ESCA.

Methods

Transcriptomic data, somatic mutations and clinical information were obtained from The Cancer Genome Atlas (TCGA). Copy number variations were obtained from the UCSC (University of California, Santa Cruz) Xena database. We curated 21 m6A regulators and performed consensus clustering analysis to quantify the m6A modification pattern.

Results

Of the 184 patients, 23 (12.5%) were genetically altered in m6A regulators, with the highest frequency of mutations in ZC3H13 and LRPPRC. We constructed a m6A score system to investigate the prognosis of ESCA. The m6A score was closely related to immune cell infiltration in the tumor immune microenvironment. Patients with a high m6A score had an unfavorable prognosis. The combination of tumor mutation burden and m6A score would improve the prognostic value.

Conclusions

Our study established and validated a strong prognostic signature based on m6A regulators. This can be used to accurately predict the prognosis of ESCA.

m6A modification patterns are associated with copy number burden and tumor immune landscape in thyroid cancer

BACKGROUND

The association involving N6-methyladenosine (m6A) modification, molecular subtype and specific immune cell group in tumor microenvironment has been the focus of recent studies. The underlying function of m6A modification in thyroid cancer (TC) remains elusive.

METHODS

The m6A modification regulations, molecular character and tumor immune profile of 461 TC patients were explored and then the correlation between them were comprehensively evaluated. The m6Ascore was established using principal component analysis (PCA) to quantify the m6A pattern of individual TC patients. The prognostic significance of the m6Ascore was evaluated by multivariate Cox regression analysis.

RESULTS

Four m6Aclusters (mc1, 2, 3, 4)-characterized by differences in extent of aneuploidy, expression of immunomodulatory genes, mRNA or lncRNA expression pattern and prognosis were identified. T Preliminary validation of m6Ascore was a potential independent prognostic factor of TC involving in mc3. Finally, the prognostic value of the m6Ascore and its association with copy number variation (CNV) and tumor immune microenvironment (TIME) of TC in mc3 were verified.

CONCLUSIONS

The correlation between m6A modification, the copy number burden and tumor immune landscape in TC was demonstrated. A m6Acluster-mc3 with low m6Ascore and high CNV molecular subtype was identified with poor clinical prognosis, low infiltrating immunocyte and weak effector T cell. A three-gene clinical prognosis model for TC based on 4 m6a cluster expression was established. Understanding of TIME is enhanced by comprehensive assessment of m6A patterns in individual TC patients and gives a new insight toward improved immunotherapy strategies for TC cancer patients.

Interpretable prediction models for widespread m6A RNA modification across cell lines and tissues

MOTIVATION

RNA N6-methyladenosine (m6A) in Homo sapiens plays vital roles in a variety of biological functions. Precise identification of m6A modifications is thus essential to elucidation of their biological functions and underlying molecular-level mechanisms. Currently available high-throughput single-nucleotide-resolution m6A modification data considerably accelerated the identification of RNA modification sites through the development of data-driven computational methods. Nevertheless, existing methods have limitations in terms of the coverage of single-nucleotide-resolution cell lines and have poor capability in model interpretations, thereby having limited applicability.

RESULTS

In this study, we present CLSM6A, comprising a set of deep learning-based models designed for predicting single-nucleotide-resolution m6A RNA modification sites across eight different cell lines and three tissues. Extensive benchmarking experiments are conducted on well-curated datasets and accordingly, CLSM6A achieves superior performance than current state-of-the-art methods. Furthermore, CLSM6A is capable of interpreting the prediction decision-making process by excavating critical motifs activated by filters and pinpointing highly concerned positions in both forward and backward propagations. CLSM6A exhibits better portability on similar cross-cell line/tissue datasets, reveals a strong association between highly activated motifs and high-impact motifs, and demonstrates complementary attributes of different interpretation strategies.

AVAILABILITY AND IMPLEMENTATION

The webserver is available at http://csbio.njust.edu.cn/bioinf/clsm6a. The datasets and code are available at https://github.com/zhangying-njust/CLSM6A/.

The emerging roles of N6-methyladenosine RNA modifications in thyroid cancer

Thyroid cancer (TC) is the most predominant malignancy of the endocrine system, with steadily growing occurrence and morbidity worldwide. Although diagnostic and therapeutic methods have been rapidly developed in recent years, the underlying molecular mechanisms in the pathogenesis of TC remain enigmatic. The N6-methyladenosine(m6A) RNA modification is designed to impact RNA metabolism and further gene regulation. This process is intricately regulated by a variety of regulators, such as methylases and demethylases. Aberrant m6A regulators expression is related to the occurrence and development of TC and play an important role in drug resistance. This review comprehensively analyzes the effect of m6A methylation on TC progression and the potential clinical value of m6A regulators as prognostic markers and therapeutic targets in this disease.

Identification and verification of characteristic differentially expressed ferroptosis-related genes in osteosarcoma using bioinformatics analysis

BACKGROUND

This study identified and verified the characteristic differentially expressed ferroptosis-related genes (CDEFRGs) in osteosarcoma (OS).

METHODS

We extracted ferroptosis-related genes (FRGs), identified differentially expressed FRGs (DEFRGs) in OS, and conducted correlation analysis between DEFRGs. Next, we conducted GO and KEGG analyses to explore the biological functions and pathways of DEFRGs. Furthermore, we used LASSO and SVM-RFE algorithms to screen CDEFRGs, and evaluated its accuracy in diagnosing OS through ROC curves. Then, we demonstrated the molecular function and pathway enrichment of CDEFRGs through GSEA analysis. In addition, we evaluated the differences in immune cell infiltration between OS and NC groups, as well as the correlation between CDEFRGs expressions and immune cell infiltrations. Finally, the expression of CDEFRGs was verified through qRT-PCR, western blotting, and immunohistochemistry experiments.

RESULTS

We identified 51 DEFRGs and the expression relationship between them. GO and KEGG analysis revealed their key functions and important pathways. Based on four CDEFRGs (PEX3, CPEB1, NOX1, and ALOX5), we built the OS diagnostic model, and verified its accuracy. GSEA analysis further revealed the important functions and pathways of CDEFRGs. In addition, there were differences in immune cell infiltration between OS group and NC group, and CDEFRGs showed significant correlation with certain infiltrating immune cells. Finally, we validated the differential expression levels of four CDEFRGs through external experiments.

CONCLUSIONS

This study has shed light on the molecular pathological mechanism of OS and has offered novel perspectives for the early diagnosis and immune-targeted therapy of OS patients.

Role of m6A modification in regulating the PI3K/AKT signaling pathway in cancer

The phosphoinositide 3-kinase (PI3K)/AKT signaling pathway plays a crucial role in the pathogenesis of cancer. The dysregulation of this pathway has been linked to the development and initiation of various types of cancer. Recently, epigenetic modifications, particularly N6-methyladenosine (m6A), have been recognized as essential contributors to mRNA-related biological processes and translation. The abnormal expression of m6A modification enzymes has been associated with oncogenesis, tumor progression, and drug resistance. Here, we review the role of m6A modification in regulating the PI3K/AKT pathway in cancer and its implications in the development of novel strategies for cancer treatment.

METTL3 inhibition induced by M2 macrophage-derived extracellular vesicles drives anti-PD-1 therapy resistance via M6A-CD70-mediated immune suppression in thyroid cancer

The treatment options for advanced papillary thyroid cancer (PTC) and anaplastic thyroid cancer (ATC) refractory to standard therapies are limited. Although anti-PD-1 therapy has a manageable safety profile and has been effective in a small percentage of patients with advanced PTC and refractory ATC, the majority of the patients either do not respond or develop resistance to anti-PD-1 therapy. N6-methyladenosine (m6A) modification is a critical determinant of the complexity of the tumor microenvironment (TME). However, it is unclear whether and how m6A modification in tumor cells shapes the immune landscape of PTC and ATC. In this study, we performed bulk and single cell RNA sequencing analysis of PTC and ATC tissues, and found that low METTL3 expression not only correlated to poor response to immune checkpoint blockade (ICB) but was also associated with increased TNF family-related ligand-receptor interactions in the immunosuppressive Tregs and exhausted T cells. Furthermore, overexpression of METTL3 in PTC and ATC cells enhanced the efficacy of anti-PD-1 therapy in a peripheral blood mononuclear cell humanized NCG (huPBMC-NCG) mouse model. Mechanistically, M2 macrophage-derived extracellular vesicles (M2 EVs) inhibited METTL3 expression in PTC and ATC cells via miR-21-5p. Downregulation of METTL3 promoted demethylation of CD70 mRNA, which prevented YTHDF2-mediated degradation of the transcripts. The stabilization of CD70 mRNA, and the subsequent upregulation in CD70 protein levels increased the abundance of the immunosuppressive Tregs and terminally exhausted T cells, thereby inducing resistance to anti-PD-1 therapy. Furthermore, blocking CD70 using cusatuzumab, a high-affinity monoclonal antibody, reversed the anti-PD-1 therapy resistance induced by M2 EVs in vivo. Finally, we demonstrated that METTL3 expression negatively correlated with CD70 expression and M2 macrophages and Tregs infiltration in PTC and ATC tissues. Our findings provide new insights into developing novel therapies for advanced PTC and ATC.

FTO promotes cervical cancer cell proliferation, colony formation, migration and invasion via the regulation of the BMP4/Hippo/YAP1/TAZ pathway

Cervical cancer is the fourth most common malignancy tumor worldwide with high incidence and mortality. Accumulating evidence indicated that through an m6A-dependent or m6A-independent mechanism, fat mass and obesity associated gene (FTO) exhibits the tumor-promoting and suppressive roles of FTO involved in various cancers, including cervical cancer. This study aims to verify the biological function and potential mechanisms of FTO in cervical cancer cell proliferation, colony formation, migration, and invasion in vitro as well as tumor growth in vivo. Herein, we confirmed that knockdown of FTO inhibits cell proliferation, colony formation, migration, and invasion of cervical cancer cells in vitro via cell counting kit-8 (CCK8) assay, colony formation assay, and transwell migration and invasion assay. The demethylase activity of FTO is required for cell proliferation, colony formation, migration, and invasion of cervical cancer cells in vitro. RNA sequencing, online database analysis, and western blotting revealed that FTO regulated the BMP4/Hippo/YAP1/TAZ pathway. In addition, FTO upregulates the expression of BMP4 in an m6A-dependent manner and binds to the N-terminal of BMP4 to form a dimer at the C-terminal in cervical cancer cells through protein-protein interaction. We further discovered that BMP4 treatment promoted cell proliferation, colony formation, migration, and invasion of cervical cancer cells, and rescue experiments validated that BMP4 treatment reversed the inhibition of FTO knockdown on the Hippo/YAP1/TAZ pathway and the progression of cervical cancer cells in vitro. Notably, the knockdown of FTO significantly suppressed xenograft tumor growth and the protein level of BMP4 in vivo. Collectively, our results demonstrate that the FTO promotes cervical cancer progression in vitro and in vivo via the regulation of the BMP4/Hippo/YAP1/TAZ pathway, suggesting that FTO acts as an oncogenic molecule and the FTO/BMP4 Hippo/YAP1/TAZ axis may serve as valuable targets for cervical cancer treatment.

The role of lactate metabolism-related LncRNAs in the prognosis, mutation, and tumor microenvironment of papillary thyroid cancer

BACKGROUND

Lactate, a byproduct of glucose metabolism, is primarily utilized for gluconeogenesis and numerous cellular and organismal life processes. Interestingly, many studies have demonstrated a correlation between lactate metabolism and tumor development. However, the relationship between long non-coding RNAs (lncRNAs) and lactate metabolism in papillary thyroid cancer (PTC) remains to be explored.

METHODS

Lactate metabolism-related lncRNAs (LRLs) were obtained by differential expression and correlation analyses, and the risk model was further constructed by least absolute shrinkage and selection operator analysis (Lasso) and Cox analysis. Clinical, immune, tumor mutation, and enrichment analyses were performed based on the risk model. The expression level of six LRLs was tested using RT-PCR.

RESULTS

This study found several lncRNAs linked to lactate metabolism in both The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) datasets. Using Cox regression analysis, 303 lactate LRLs were found to be substantially associated with prognosis. Lasso was done on the TCGA cohort. Six LRLs were identified as independent predictive indicators for the development of a PTC prognostic risk model. The cohort was separated into two groups based on the median risk score (0.39717 -0.39771). Subsequently, Kaplan-Meier survival analysis and multivariate Cox regression analysis revealed that the high-risk group had a lower survival probability and that the risk score was an independent predictive factor of prognosis. In addition, a nomogram that can easily predict the 1-, 3-, and 5-year survival rates of PTC patients was established. Furthermore, the association between PTC prognostic factors and tumor microenvironment (TME), immune escape, as well as tumor somatic mutation status was investigated in high- and low-risk groups. Lastly, gene expression analysis was used to confirm the differential expression levels of the six LRLs.

CONCLUSION

In conclusion, we have constructed a prognostic model that can predict the prognosis, mutation status, and TME of PTC patients. The model may have great clinical significance in the comprehensive evaluation of PTC patients.

Effect of the m6ARNA gene on the prognosis of thyroid cancer, immune infiltration, and promising immunotherapy

BACKGROUND

Accumulating evidence suggests that N6-methyladenosine (m6A) RNA methylation plays an important role in tumor proliferation and growth. However, its effect on the clinical prognosis, immune infiltration, and immunotherapy response of thyroid cancer patients has not been investigated in detail.

METHODS

Clinical data and RNA expression profiles of thyroid cancer were extracted from the Cancer Genome Atlas-thyroid carcinoma (TCGA-THCA) and preprocessed for consensus clustering. The risk model was constructed based on differentially expressed genes (DEGs) using Least Absolute Shrinkage and Selection Operator (LASSO) and Cox regression analyses. The associations between risk score and clinical traits, immune infiltration, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Set Enrichment Analysis (GSEA), immune infiltration, and immunotherapy were assessed. Immunohistochemistry was used to substantiate the clinical traits of our samples.

RESULTS

Gene expression analysis showed that 17 genes, except YHTDF2, had significant differences (vs healthy control, P<0.001). Consensus clustering yielded 2 clusters according to their clinical features and estimated a poorer prognosis for Cluster 1 (P=0.03). The heatmap between the 2 clusters showed differences in T (P<0.01), N (P<0.001) and stage (P<0.01). Based on univariate Cox and LASSO regression, a risk model consisting of three high-risk genes (KIAA1429, RBM15, FTO) was established, and the expression difference between normal and tumor tissues of three genes was confirmed by immunohistochemical results of our clinical tissues. KEGG and GSEA analyses showed that the risk DEGs were related mainly to proteolysis, immune response, and cancer pathways. The levels of immune infiltration in the high- and low-risk groups were different mainly in iDCs (P<0.05), NK cells (P<0.05), and type-INF-II (P<0.001). Immunotherapy analysis yielded 30 drugs associated with the expression of each gene and 20 drugs associated with the risk score.

CONCLUSIONS

Our risk model can act as an independent marker for thyroid cancer and provides promising immunotherapy targets for its treatment.

FTO in cancer: functions, molecular mechanisms, and therapeutic implications

N⁶-methyladenosine (m⁶A) is the most abundant internal modification in mRNA that affects RNA processing, stability, and translation. Discovered as the first RNA m⁶A demethylase, the fat mass and obesity-associated protein (FTO) is frequently dysregulated and plays important roles in various types of cancers. Targeting FTO holds promising therapeutic significance via suppressing tumor growth, potentiating immunotherapy, and attenuating drug resistance. Here, we review recent advances in our understanding of the functions and underlying molecular mechanisms of FTO in tumor development, cancer stem cell (CSC) self-renewal, microenvironment regulation, immunity, and metabolism and discuss the therapeutic potential of targeting FTO for cancer treatment.

Single-Cell RNA Sequencing Revealed a 3-Gene Panel Predicted the Diagnosis and Prognosis of Thyroid Papillary Carcinoma and Associated With Tumor Immune Microenvironment

Objective

The objective of this research was to screen prognostic related genes of thyroid papillary carcinoma (PTC) by single-cell RNA sequencing (scRNA-seq), to construct the diagnostic and prognostic models based on The Cancer Genome Atlas Thyroid Cancer (TCGA-THCA) data, and to evaluate the association between tumor immune microenvironment and the prognostic model.

Method

The differentially expressed genes (DEGs) and tumor evolution were analyzed by scRNA-seq based on public databases. The potential regulatory networks of DEGs related to prognosis were analyzed by multi-omics data in the THCA. Logistic regression and Cox proportional hazards regression were utilized to construct the diagnosis and prognostic model of PTC. The performance of the diagnostic model was verified by bulk RNA sequencing (RNA-seq) of our cohort. The tumor immune microenvironment associated with the prognostic model was evaluated using multi-omics data. In addition, qRT-PCR was performed on tumor tissues and adjacent normal tissues of 20 patients to verify the expression levels of DEGs.

Results

The DEGs screened by scRNA-seq can distinguish between tumor and healthy samples. DEGs play different roles in the evolution from normal epithelial cells to malignant cells. Three DEGs ((FN1, CLU, and ANXA1)) related to prognosis were filtered, which may be regulated by DNA methylation, RNA methylation (m6A) and upstream transcription factors. The area under curve (AUC) of the diagnostic model based on 3-gene in the validation of our RNA-seq was 1. In the prognostic model based on 3-gene, the overall survival (OS) of high-risk patients was shorter. Combined with the clinical information of patients, a nomogram was constructed by using tumor size (pT) and risk score to quantify the prognostic risk. The age and tumor size of high-risk patients in the prognostic model were greater. In addition, the increase of tumor mutation burden (TMB) and diversity of T cell receptor (TCR), and the decrease of CD8⁺ T cells in high-risk group suggest the existence of immunosuppressive microenvironment.

Conclusion

We applied the scRNA-seq pipeline to focus on epithelial cells in PTC, simulated the process of tumor evolution, and revealed a prognostic prediction model based on 3 genes, which is related to tumor immune microenvironment.

TS-m6A-DL: Tissue-specific identification of N6-methyladenosine sites using a universal deep learning model

The most communal post-transcriptional modification, N6-methyladenosine (m6A), is associated with a number of crucial biological processes. The precise detection of m6A sites around the genome is critical for revealing its regulatory function and providing new insights into drug design. Although both experimental and computational models for detecting m6A sites have been introduced, but these conventional methods are laborious and expensive. Furthermore, only a handful of these models are capable of detecting m6A sites in various tissues. Therefore, a more generic and optimized computational method for detecting m6A sites in different tissues is required. In this paper, we proposed a universal model using a deep neural network (DNN) and named it TS-m6A-DL, which can classify m6A sites in several tissues of humans (Homo sapiens), mice (Mus musculus), and rats (Rattus norvegicus). To extract RNA sequence features and to convert the input into numerical format for the network, we utilized one-hot-encoding method. The model was tested using fivefold cross-validation and its stability was measured using independent datasets. The proposed model, TS-m6A-DL, achieved accuracies in the range of 75-85% using the fivefold cross-validation method and 72-84% on the independent datasets. Finally, to authenticate the generalization of the model, we performed cross-species testing and proved the generalization ability by achieving state-of-the-art results.