Malignant Evaluation and Clinical Prognostic Values of M6A RNA Methylation Regulators in Prostate Cancer

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.

The current landscape of m6A modification in urological cancers

N6-methyladenosine (m6A) methylation is a dynamic and reversible procession of epigenetic modifications. It is increasingly recognized that m6A modification has been involved in the tumorigenesis, development, and progression of urological tumors. Emerging research explored the role of m6A modification in urological cancer. In this review, we will summarize the relationship between m6A modification, renal cell carcinoma, bladder cancer, and prostate cancer, and discover the biological function of m6A regulators in tumor cells. We will also discuss the possible mechanism and future application value used as a potential biomarker or therapeutic target to benefit patients with urological cancers.

Effect of N6-methyladenosine (m6A) regulator-related immunogenes on the prognosis and immune microenvironment of breast cancer

Background

Breast cancer is one of the most common malignant tumor and the prognosis remains unsatisfying. Various studies demonstrate that m6A modulators are new predictors of prognosis in immune microenvironment. We aimed to identify several m6A regulator-related immunogenes and explore the relationship between m6A regulator-related immunogenes and breast cancer prognosis as well as the tumor immune microenvironment (TIME).

Methods

RNA sequencing data and clinical information on 21 m6A regulators in 1,047 breast cancer samples were downloaded from The Cancer Genome Atlas (TCGA), and immune gene data were downloaded from InnateDB. Kaplan-Meier survival analysis was conducted with log-rank test using the survival package. An m6A-related immunogene-prognostic signature was then constructed, followed by immune infiltration and checkpoint analyses.

Results

A risk prognostic signature of m6A regulator-related immunogenes, including TOX, PSME2, MCTS1, NFKBIE, SH3BP4, RSPH1, JAK1, MLLT4, and PTGES3, was constructed. Furthermore, univariate and multivariate Cox regression analyses suggested that the tumor stage and risk score could be independent prognostic factors for patients with breast cancer. Immune infiltration analysis showed that the infiltration levels of T cells, memory B cells, activated NK cells, and macrophages between the high- and low-risk groups were significantly different. In addition, checkpoint analyses demonstrated that the levels of immune checkpoint genes, such as those of LAG3, PDCD1, CTLA4, and HAVCR2, were downregulated in the high-risk group compared to those in the low-risk group.

Conclusions

Our findings suggest that the m6A regulator-related risk prognostic signature can predict the prognosis of breast cancer and that it is related to the immune microenvironment.

Construction of N-7 methylguanine-related mRNA prognostic model in uterine corpus endometrial carcinoma based on multi-omics data and immune-related analysis

N-7 methylguanine (m7G) is one of the most common RNA base modifications in post-transcriptional regulation, which participates in multiple processes such as transcription, mRNA splicing and translation during the mRNA life cycle. However, its expression and prognostic value in uterine corpus endometrial carcinoma (UCEC) have not been systematically studied. In this paper, the data such as gene expression profiles, clinical data of UCEC patients, somatic mutations and copy number variants (CNVs) are obtained from the cancer genome atlas (TCGA) and UCSC Xena. By analyzing the expression differences of m7G-related mRNA in UCEC and plotting the correlation network maps, a risk score model composed of four m7G-related mRNAs (NSUN2, NUDT3, LARP1 and NCBP3) is constructed using least absolute shrinkage and selection operator (LASSO), univariate and multivariate Cox regression in order to identify prognosis and immune response. The correlation of clinical prognosis is analyzed between the m7G-related mRNA and UCEC via Kaplan-Meier method, receiver operating characteristic (ROC) curve, principal component analysis (PCA), t-SNE, decision curve analysis (DCA) curve and nomogram etc. It is concluded that the high risk is significantly correlated with (P < 0.001) the poorer overall survival (OS) in patients with UCEC. It is one of the independent risk factors affecting the OS. Differentially expressed genes are identified by R software in the high and low risk groups. The functional analysis and pathway enrichment analysis have been performed. Single sample gene set enrichment analysis (ssGSEA), immune checkpoints, m6A-related genes, tumor mutation burden (TMB), stem cell correlation, tumor immune dysfunction and rejection (TIDE) scores and drug sensitivity are also used to study the risk model. In addition, we have obtained 3 genotypes based on consensus clustering, which are significantly related to (P < 0.001) the OS and progression-free survival (PFS). The deconvolution algorithm (CIBERSORT) is applied to calculate the proportion of 22 tumor infiltrating immune cells (TIC) in UCEC patients and the estimation algorithm (ESTIMATE) is applied to work out the number of immune and matrix components. In summary, m7G-related mRNA may become a potential biomarker for UCEC prognosis, which may promote UCEC occurrence and development by regulating cell cycles and immune cell infiltration. It is expected to become a potential therapeutic target of UECE.

Epigenetic and Epitranscriptomic Control in Prostate Cancer

The initiation of prostate cancer has been long associated with DNA copy-number alterations, the loss of specific chromosomal regions and gene fusions, and driver mutations, especially those of the Androgen Receptor. Non-mutational events, particularly DNA and RNA epigenetic dysregulation, are emerging as key players in tumorigenesis. In this review we summarize the molecular changes linked to epigenetic and epitranscriptomic dysregulation in prostate cancer and the role that alterations to DNA and RNA modifications play in the initiation and progression of prostate cancer.

A novel defined risk signature based on pyroptosis-related genes can predict the prognosis of prostate cancer

Background

Pyroptosis can not only inhibit the occurrence and development of tumors but also develop a microenvironment conducive to cancer growth. However, pyroptosis research in prostate cancer (PCa) has rarely been reported.

Methods

The expression profile and corresponding clinical data were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Patients were divided into different clusters using consensus clustering analysis, and differential genes were obtained. We developed and validated a prognostic biomarker for biochemical recurrence (BCR) of PCa using univariate Cox analysis, Lasso-Cox analysis, Kaplan–Meier (K–M) survival analysis, and time-dependent receiver operating characteristics (ROC) curves.

Results

The expression levels of most pyroptosis-related genes (PRGs) are different not only between normal and tumor tissues but also between different clusters. Cluster 2 patients have a better prognosis than cluster 1 patients, and there are significant differences in immune cell content and biological pathway between them. Based on the classification of different clusters, we constructed an eight genes signature that can independently predict the progression-free survival (PFS) rate of a patient, and this signature was validated using a GEO data set (GSE70769). Finally, we established a nomogram model with good accuracy.

Conclusions

In this study, PRGs were used as the starting point and based on the expression profile and clinical data, a prognostic signature with a high predictive value for biochemical recurrence (BCR) following radical prostatectomy (RP) was finally constructed, and the relationship between pyroptosis, immune microenvironment, and PCa was explored, providing important clues for future research on pyroptosis and immunity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01172-5.

Construction of a risk prediction model using m6A RNA methylation regulators in prostate cancer: comprehensive bioinformatic analysis and histological validation

Background

Epigenetic reprogramming reportedly has a crucial role in prostate cancer (PCa) progression. RNA modification is a hot topic in epigenetics, and N6-methyladenosine (m6A) accounts for approximately 60% of RNA chemical modifications. The aim of this study was to evaluate the m6A modification patterns in PCa patients and construct a risk prediction model using m6A RNA regulators.

Materials and methods

Analyses were based on the levels of 25 m6A regulators in The Cancer Genome Atlas (TCGA). Differentially expressed gene (DEG) and survival analyses were performed according to TCGA-PRAD clinicopathologic and follow-up information. To detect the influences of m6A regulators and their DEGs, consensus clustering analysis was performed, and tumor mutational burden (TMB) estimation and tumor microenvironment (TME) cell infiltration were assessed. mRNA levels of representative genes were verified using clinical PCa data.

Results

Diverse expression patterns of m6A regulators between tumor and normal (TN) tissues were detected regarding Gleason score (GS), pathological T stage (pT), TP53 mutation, and survival comparisons, with HNRNPA2B1 and IGFBP3 being intersecting genes. HNRNPA2B1 was upregulated in advanced stages (GS > 7, pT3, HR > 1, and TP53 mutation), as verified using clinical PCa tissue. Three distinct m6A modification patterns were identified through consensus clustering analysis, but no significant difference was found among these groups in recurrence-free survival (RFS) analysis. Six DEGs of m6A clusters (m6Aclusters) were screened through univariate Cox regression analysis. MMAB and PAIAP2 were intersecting genes for the five clinical factors. MMAB, which was upregulated in PCa compared with TN, was verified using clinical PCa samples. Three distinct subgroups were established according to the 6 DEGs. Cluster A involved the most advanced stages and had the poorest RFS. The m6A score (m6Ascore) was calculated based on the 6 genes, and the low m6Ascore group showed poor RFS with a negative association with infiltration for 16 of 23 immune-related cells.

Conclusion

We screened DEGs of m6Aclusters and identified 6 genes (BAIAP2, TEX264, MMAB, JAGN1, TIMM8AP1, and IMP3), with which we constructed a highly predictive model with prognostic value by dividing TCGA-PRAD into three distinct subgroups and performing m6Ascore analysis. This study helps to elucidate the integral effects of m6A modification patterns on PCa progression.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02438-1.

RNA m6A Methylation Regulators Multi-Omics Analysis in Prostate Cancer

RNA N6-methyladenosine (m6A) methylation is known to be the most popular RNA modification in animals. Many research reports have elaborated on the effects of m6A regulators in medical practice, such as diagnosis, prognosis, and treatment. M6A modification has evident impacts on many aspects of RNA metabolism, just like RNA splicing, processing, translation, and stability. M6A also has a magnificent role in numerous types of cancers. We analyzed the prostate cancer datasets, from The Cancer Genome Atlas (TCGA) database, for every recognized m6A regulator in their gene expression, DNA methylation status and copy number variations (CNVs). We also systematically analyzed the relationship between different m6A regulators and the prognosis of prostate cancer. The results illustrated considerable differences in the expression of various m6A regulators between the prostate and normal cancer samples. At the same time, there were evident differences in the expression of various m6A regulators in prostate cancers with different Gleason scores. Subsequently, we determined CBLL1, FTO, YTHDC1, HNRNPA2B1 as crucial m6A regulators of prostate cancer. Premised on the expression of CBLL1, we also identified potential therapeutic agents for prostate cancer, and knockdown of FTO prominently inhibited prostate cells migration and invasion in vitro experiment.