Dynamic transcriptomic m5 C and its regulatory role in RNA processing

m5C-Related Signatures for Predicting Prognosis in Cutaneous Melanoma with Machine Learning

Background

Cutaneous melanoma (CM) is one of the most life-threatening primary skin cancers and is prone to distant metastases. A widespread presence of posttranscriptional modification of RNA, 5-methylcytosine (m5C), has been observed in human cancers. However, the potential mechanism of the tumorigenesis and prognosis in CM by dysregulated m5C-related regulators is obscure.

Methods

We use comprehensive bioinformatics analyses to explore the expression of m5C regulators in CM, the prognostic implications of the m5C regulators, the frequency of the copy number variant (CNV), and somatic mutations in m5C regulators. Additionally, the CM patients were divided into three clusters for better predicting clinical features and outcomes via consensus clustering of m5C regulators. Then, the risk score was established via Lasso Cox regression analysis. Next, the prognosis value and clinical characteristics of m5C-related signatures were further explored. Then, machine learning was used to recognize the outstanding m5C regulators to risk score. Finally, the expression level and clinical value of USUN6 were analyzed via the tissue microarray (TMA) cohort.

Results

We found that m5C regulators were dysregulated in CM, with a high frequency of somatic mutations and CNV alterations of the m5C regulatory gene in CM. Furthermore, 16 m5C-related proteins interacted with each other frequently, and we divided CM patients into three clusters to better predicting clinical features and outcomes. Then, five m5C regulators were selected as a risk score based on the LASSO model. The XGBoost algorithm recognized that NOP2 and NSUN6 were the most significant risk score contributors. Immunohistochemistry has verified that low expression of USUN6 was closely correlated with CM progression.

Conclusion

The m5C-related signatures can be used as new prognostic biomarkers and therapeutic targets for CM, and NSUN6 might play a vital role in tumorigenesis and malignant progression.

Long Non-Coding RNA Epigenetics

Long noncoding RNAs exceeding a length of 200 nucleotides play an important role in ensuring cell functions and proper organism development by interacting with cellular compounds such as miRNA, mRNA, DNA and proteins. However, there is an additional level of lncRNA regulation, called lncRNA epigenetics, in gene expression control. In this review, we describe the most common modified nucleosides found in lncRNA, 6-methyladenosine, 5-methylcytidine, pseudouridine and inosine. The biosynthetic pathways of these nucleosides modified by the writer, eraser and reader enzymes are important to understanding these processes. The characteristics of the individual methylases, pseudouridine synthases and adenine-inosine editing enzymes and the methods of lncRNA epigenetics for the detection of modified nucleosides, as well as the advantages and disadvantages of these methods, are discussed in detail. The final sections are devoted to the role of modifications in the most abundant lncRNAs and their functions in pathogenic processes.

RNA modifications in cardiovascular diseases, the potential therapeutic targets

More than one hundred RNA modifications decorate the chemical and topological properties of these ribose nucleotides, thereby executing their biological functions through post-transcriptional regulation. In cardiovascular diseases, a wide range of RNA modifications including m⁶A (N6-adenosine methylation), m⁵C (5-methylcytidin), Nm (2'-O-ribose-methylation), Ψ (pseudouridine), m⁷G (N7-methylguanosine), and m¹A (N1-adenosine methylation) have been found in tRNA, rRNA, mRNA and other noncoding RNA, which can function as a novel mechanism in metabolic syndrome, heart failure, coronary heart disease, and hypertension. In this review, we will summarize the current understanding of the regulatory roles and significance of several types of RNA modifications in CVDs (cardiovascular diseases) and the interplay between RNA modifications and noncoding RNA, epigenetics. Finally, we will focus on the potential therapeutic strategies by using RNA modifications.