Molecular Characteristics of N1-Methyladenosine Regulators and Their Correlation with Overall Cancer Survival

m1A Regulatory gene signatures are associated with certain immune cell compositions of the tumor microenvironment and predict survival in kidney renal clear cell carcinoma

Adenosine N1 methylation (m1A) of RNA, a type of post-transcriptional modification, has been shown to play a significant role in the progression of cancer. The objective of the current research was to analyze the genetic alteration and prognostic significance of m1A regulators in kidney renal clear cell carcinoma (KIRC). Genomic and clinicopathological characteristics were obtained from 558 KIRC patients in the Cancer Genome Atlas (TCGA) and Gene Omnibus Expression (GEO) databases. Alterations in the gene expression of ten m1A-regulators were analyzed and survival analysis was performed using the Cox regression method. We also identified three clusters of patients based on their distinct m1A alteration patterns, using integrated analysis of the ten m1A-related regulators, which were significantly related to overall survival (OS), disease-free survival (DFS) and tumor microenvironment (TME) immune cell infiltration cells in KIRC. Our findings showed that m1A alteration patterns have critical roles in determining TME complexity and its immune cell composition. Furthermore, different m1A expression patterns were significantly associated with DFS and OS rates in KIRC patients. In conclusion, the identified m1A RNA modification patterns offer a potentially effective way to classify KIRC patients based on their TME immune cell infiltration, enabling the development of more personalized and successful treatment strategies for these patients.

Modifications of noncoding RNAs in cancer and their therapeutic implications

In the last 50 years, over 150 various chemical modifications on RNA molecules, including mRNAs, rRNAs, tRNAs, and other noncoding RNAs (ncRNAs), have been identified and characterized. These RNA modifications regulate RNA biogenesis and biological functions and are widely involved in various physiological processes and diseases, including cancer. In recent decades, broad interest has arisen in the epigenetic modification of ncRNAs due to the increased knowledge of the critical roles of ncRNAs in cancer. In this review, we summarize the various modifications of ncRNAs and highlight their roles in cancer initiation and progression. In particular, we discuss the potential of RNA modifications as novel biomarkers and therapeutic targets in cancer.

Genetic and epigenetic defects of the RNA modification machinery in cancer

Cancer was initially considered to be an exclusively genetic disease, but an interplay of dysregulated genetic and epigenetic mechanisms is now known to contribute to the cancer phenotype. More recently, chemical modifications of RNA molecules - the so-called epitranscriptome - have been found to regulate various aspects of RNA function and homeostasis. Specific enzymes, known as RNA-modifying proteins (RMPs), are responsible for depositing, removing, and reading chemical modifications in RNA. Intensive investigations in the epitranscriptomic field in recent years, in conjunction with great technological advances, have revealed the critical role of RNA modifications in regulating numerous cellular pathways. Furthermore, growing evidence has revealed that RNA modification machinery is often altered in human cancers, highlighting the enormous potential of RMPs as pharmacological targets or diagnostic markers.

MFAP2, upregulated by m1A methylation, promotes colorectal cancer invasiveness via CLK3

BACKGROUND

Distant metastasis is the main cause of mortality in colorectal cancer (CRC) patients. N1-methyladenosine (m1A) is a type of epitranscriptome modification. While its regulatory effect on mRNA and its role in CRC metastasis remain unclear.

METHODS

The m1A methylation profile of mRNAs in CRC was revealed by m1A methylated RNA immunoprecipitation sequencing. The expression of MFAP2 in tumor tissues was measured by immunohistochemistry and then correlated with the clinical characteristics and prognosis of CRC patients. The role of MFAP2 in the invasiveness of CRC cells was evaluated by transwell assays and peritoneal metastatic model in nude mice. The downstream targets of MFAP2 was screened by mass spectrometry analysis. Then the role of MFAP2-CLK3 signaling axis was verified by cotransfecting MFAP2 siRNA and CLK3 plasmid in CRC cells.

RESULTS

Microfibril associated protein 2 (MFAP2) mRNA was overexpressed and m1A-hypermethylated in CRC. High expression of MFAP2 was closely related to lymph node metastasis and distant metastasis, leading to poor prognosis in patients with CRC. In vivo and in vitro studies showed that silencing of MFAP2 inhibited the migration, invasion and metastasis of CRC cells. CDC Like Kinase 3 (CLK3) was a potential downstream target of MFAP2. Further studies showed that MFAP2 depletion might induce autophagic degradation of CLK3, and the role of MFAP2 in the invasiveness of CRC cells was dependent on CLK3.

CONCLUSIONS

Our results uncover a newly identified MFAP2-CLK3 signaling axis, which is a potential therapeutic target for CRC metastasis.

m1A-pred: Prediction of Modified 1-methyladenosine Sites in RNA Sequences through Artificial Intelligence

BACKGROUND

The process of nucleotides modification or methyl groups addition to nucleotides is known as post-transcriptional modification (PTM). 1-methyladenosine (m1A) is a type of PTM formed by adding a methyl group to the nitrogen at the 1st position of the adenosine base. Many human disorders are associated with m1A, which is widely found in ribosomal RNA and transfer RNA.

OBJECTIVE

The conventional methods such as mass spectrometry and site-directed mutagenesis proved to be laborious and burdensome. Systematic identification of modified sites from RNA sequences is gaining much attention nowadays. Consequently, an extreme gradient boost predictor, m1A-Pred, is developed in this study for the prediction of modified m1A sites.

METHODS

The current study involves the extraction of position and composition-based properties within nucleotide sequences. The extraction of features helps in the development of the features vector. Statistical moments were endorsed for dimensionality reduction in the obtained features.

RESULTS

Through a series of experiments using different computational models and evaluation methods, it was revealed that the proposed predictor, m1A-pred, proved to be the most robust and accurate model for the identification of modified sites.

AVAILABILITY AND IMPLEMENTATION

To enhance the research on m¹A sites, a friendly server was also developed, which was the final phase of this research.

m1A and m6A modifications function cooperatively to facilitate rapid mRNA degradation

N⁶-Methyladenosine (m⁶A), the most abundant internal mRNA modification, affects multiple steps in gene expression. Mechanistically, the binding of YTHDF2 to m⁶A on mRNAs elicits rapid mRNA degradation by recruiting several RNA degrading enzymes. Here, we show that N¹-methyladenosine (m¹A), another type of RNA modification, accelerates rapid m⁶A RNA degradation. We identify HRSP12 as an RNA-binding protein that recognizes m¹A. The binding of HRSP12 to m¹A promotes efficient interaction of YTHDF2 with m⁶A, consequently facilitating endoribonucleolytic cleavage via the RNase P/MRP complex. Transcriptome-wide analyses also reveal that mRNAs harboring both m¹A and m⁶A are downregulated in an HRSP12-dependent manner compared with mRNAs harboring m⁶A only. Accordingly, a subset of endogenous circular RNAs that harbor m⁶A and associate with YTHDF2 in an HRSP12-dependent manner is also subjected to m¹A-facilitated rapid degradation. Together, our observations provide compelling evidence for crosstalk between different RNA modifications.

Integrated Bioinformatics Analysis of Serine Racemase as an Independent Prognostic Biomarker in Endometrial Cancer

Endometrial cancer (EC) kills about 76,000 women worldwide, with the highest incidence in industrialized countries. Because of the rise in disease mortality and new diagnoses, EC is now a top priority for women’s health. Serine racemase (SRR) is thought to play a role in the central nervous system, but its role in cancers, particularly in EC, is largely unknown. The current study starts with a pan-cancer examination of SRR’s expression and prognostic value before delving into SRR’s potential cancer-suppressing effect in patients with EC. SRR may affect the endometrial tumor immune microenvironment, according to subsequent immune-related analysis. SRR expression is also linked to several genes involved in specific pathways such as ferroptosis, N6-methyladenosine methylation, and DNA damage repair. Finally, we used the expression, correlation, and survival analyses to investigate the upstream potential regulatory non-coding RNAs of SRR. Overall, our findings highlight the prognostic significance of SRR in patients with EC, and we can formulate a reasonable hypothesis that SRR influences metabolism and obstructs key carcinogenic processes in EC.

Construction of a Novel Prognostic Model in Lung Adenocarcinoma Based on 7-Methylguanosine-Related Gene Signatures

Increasing evidence has implicated the modification of 7-methylguanosine (m7G), a type of RNA modification, in tumor progression. However, no comprehensive analysis to date has summarized the predicted role of m7G-related gene signatures in lung adenocarcinoma (LUAD). Herein, we aimed to develop a novel prognostic model in LUAD based on m7G-related gene signatures. The LUAD transcriptome profiling data and corresponding clinical data were acquired from the Cancer Genome Atlas (TCGA) and two Gene Expression Omnibus datasets. After screening, we first obtained 29 m7G-related genes, most of which were upregulated in tumor tissues and negatively associated with overall survival (OS). According to the expression similarity of m7G-related genes, the combined samples from the TCGA-LUAD and GSE68465 datasets were further classified as two clusters that exhibit distinct OS rates and genetic heterogeneity. Then, we constructed a novel prognostic model involving four genes by using 130 differentially expressed genes among the two clusters. The combined samples were randomly divided into a training cohort and an internal validation cohort in a 1:1 ratio, and the GSE72094 dataset was used as an external validation cohort. The samples were divided into high- and low-risk groups. We demonstrated that a higher risk score was an independent negative prognostic factor and predicted poor OS. A nomogram was further constructed to better predict the survival of LUAD patients. Functional enrichment analyses indicated that cell cycle and DNA replication-related biological processes and pathways were enriched in the high-risk group. More importantly, the low-risk group had greater infiltration and enrichment of most immune cells, as well as higher ESTIMATE, immune, and stromal scores. In addition, the high-risk group had a lower TIDE score and higher expressions of most immune checkpoint-related genes. We finally noticed that patients in the high-risk group were more sensitive to chemotherapeutic agents commonly used in LUAD. In conclusion, we herein summarized for the first time the alterations and prognostic role of m7G-related genes in LUAD and then constructed a prognostic model based on m7G-related gene signatures that could accurately and stably predict survival and guide individualized treatment decision-making in LUAD patients.

A Novel m1A-Score Model Correlated With the Immune Microenvironment Predicts Prognosis in Hepatocellular Carcinoma

RNA methylation plays crucial roles in gene expression and has been indicated to be involved in tumorigenesis, while it is still unclear whether m1A modifications have potential roles in the prognosis of hepatocellular carcinoma (HCC). In this study, we comprehensively analyzed RNA sequencing (RNA-seq) data and clinical information using The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. We collected 10 m1A regulators and performed consensus clustering to determine m1A modification patterns in HCC. The CIBERSORT method was utilized to evaluate the level of immune cell infiltration. Principal component analysis was used to construct the m1A-score model. In the TCGA-LIHC cohort, the expression of all 10 m1A regulators was higher in tumor tissues than in normal control tissues, and 8 of 10 genes were closely related to the prognosis of HCC patients. Two distinct m1A methylation modification patterns (Clusters C1 and C2) were identified by the 10 regulators and were associated with different overall survival, TNM stage and tumor microenvironment (TME) characteristics. Based on the differentially expressed genes (DEGs) between C1 and C2, we identified three gene clusters (Clusters A, B and C). C1 with a better prognosis was mainly distributed in Cluster C, while Cluster A contained the fewest samples of C1. An m1A-score model was constructed using five m1A regulators related to prognosis. Patients with higher m1A scores showed a poorer prognosis than those with lower scores in the TCGA-LIHC and GSE14520 datasets. In conclusions, our study showed the vital role of m1A modification in the TME and progression of HCC. Quantitative evaluation of the m1A modification patterns of individual patients facilitates the development of more effective biomarkers for predicting the prognosis of patients with HCC.

Roles of Major RNA Adenosine Modifications in Head and Neck Squamous Cell Carcinoma

Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer malignancy worldwide and is known to have poor prognosis. The pathogenesis behind the development of HNSCC is not fully understood. Modifications on RNA are involved in many pathophysiological processes, such as tumor development and inflammation. Adenosine-related RNA modifications have shown to be linked to cancer and may play a role in cancer occurrence and development. To date, there are at least 170 different chemical RNA modifications that modify coding and non-coding RNAs (ncRNAs). These modifications affect RNA stability and transcription efficiency. In this review, we focus on the current understanding of the four major RNA adenosine modifications (N⁶-Methyladenosine, N¹-Methyladenosine, Alternative Polyadenylation Modification and A-to-I RNA editing) and their potential molecular mechanisms related to HNSCC development and progression. We also touch on how these RNA modifications affect treatment of HNSCCs.