The Interaction Between N6-Methyladenosine Modification and Non-Coding RNAs in Gastrointestinal Tract Cancers

Molecular characterization of colorectal mucinous adenocarcinoma and adenocarcinoma, not otherwise specified, identified by multiomic data analysis

Adenocarcinoma not otherwise specified (AC) and mucinous adenocarcinoma (MC) have different biological behaviors and clinical features. We utilized our previous proteomic data and public transcriptome, single-cell transcriptome, and spatial transcriptome databases to profile the molecular atlas of the tumor microenvironments of MC, AC, and normal colon tissues. By exploring the general and specific molecular features of AC and MC, we found that AC was immune-active but exposed to a hypoxic microenvironment. MC cells could protect against DNA damage, and the microenvironment was unfavorable to leukocyte transendothelial migration. We identified several potential molecular and cellular targets of AC and MC for future research. We also highlighted that the major difference between AC and MC was not the variety of cell types and functions but possibly cell interactions. Stromal and epithelial cell interactions play important roles in both MC and AC, but different regulatory pathways were involved.

N6-methyladenosine (m6A) methyltransferase METTL3 regulates sepsis-induced myocardial injury through IGF2BP1/HDAC4 dependent manner

Recent studies have identified that N⁶-methyladenosine (m⁶A) extensively participates in the myocardial injury pathophysiological process. However, the role of m⁶A on sepsis-induced myocardial injury is still unclear. Here, we investigated the functions and mechanism of m⁶A methyltransferase METTL3 for septic myocardial injury. Results illustrated that the m⁶A modification level and METTL3 up-regulated in the lipopolysaccharide (LPS)-induced cardiomyocytes (H9C2 cells). Methylated RNA immunoprecipitation sequencing (MeRIP-Seq) revealed the m⁶A profile of the septic myocardial injury cellular model. Functionally, METTL3 knockdown repressed the inflammatory damage of cardiomyocytes induced by LPS. Mechanistically, we found that HDAC4 had remarkable m⁶A modification sites on its 3'-UTR genome, acting as the downstream target of METTL3. Besides, m⁶A reader IGF2BP1 recognized the m⁶A modification sites on HDAC4 mRNA and enhanced its RNA stability. In conclusion, the findings illustrated a role of METTL3/IGF2BP1/m⁶A/HDAC4 axis on sepsis-induced myocardial injury, which might provide novel therapeutic strategy for septic myocardial injury.

[Comprehensive Analysis of the Relationship between m6A Methylation Patterns and Immune Microenvironment in Lung Adenocarcinoma]

BACKGROUND

m6A RNA methylation modification plays an important role in the occurrence and progression of lung cancer and regulates tumor immunity. Current studies mostly focus on the differential expression of some specific m6A effectors and infiltrating immune cell. m6A methylation modification is the result of mutual adjustment and balance between effectors, and changes in the expression of one or two effectors are far from enough to reflect the panorama of m6A methylation. The role of m6A in the immune microenvironment of lung adenocarcinoma (LUAD) is still poorly understood. The aim of this study is to investigate the effect of different m6A modification patterns in immune microenvironment of LUAD.

METHODS

LUAD data was obtained from The Cancer Genome Atlas (TCGA), University of California Santa Cruz Xena (UCSC Xena) and Gene Expression Omnibus (GEO) databases. Gene mutation, differential expression and survival analysis were performed for 24 m6A effectors. The m6A modification pattern was constructed by unsupervised clustering method, and the m6A clusters survival analysis, gene set variation analysis, immune score and immune cell infiltration analysis were performed. The association between LRPPRC protein expression levels and infiltration of CD8+ cytotoxic T lymphocytes and CD68+ macrophages in the tumor microenvironment was validated by immunohistochemistry in LUAD tissue microarray with 68 cases.

RESULTS

The mutations of m6A effector were found in 150 of 567 LUAD cases with a frequency of 26.46%. 6 readers and 3 writers were significantly up regulated in LUAD tissues compared with normal tissues. IGF2BP1 and HNRNPC are the independent risk factors for prognosis of LUAD. Abundant cross-talks among writers, erasers and readers were demonstrated. Three m6A modification patterns with different immune cell infiltration characteristics and clinical prognosis were established. Among m6A effectors, LRPPRC was found to be inversely associated with the infiltration of CD8+ cytotoxic T lymphocytes and CD68+ macrophages, and was validated in 68 LUAD tissues.

CONCLUSIONS

m6A modification patterns play non-negligible roles in regulating the immune microenvironment. LRPPRC has potential to be a new biomarker for checkpoint inhibitor immunotherapy.

Identification of RNA Methylation-Related lncRNAs Signature for Predicting Hot and Cold Tumors and Prognosis in Colon Cancer

N6-methyladenosine (m6A), N1-methyladenosine (m1A), 5-methylcytosine (m5C), and 7-methylguanosine (m7G) are the major forms of RNA methylation modifications, which are closely associated with the development of many tumors. However, the prognostic value of RNA methylation-related long non-coding RNAs (lncRNAs) in colon cancer (CC) has not been defined. This study summarised 50 m6A/m1A/m5C/m7G-related genes and downloaded 41 normal and 471 CC tumor samples with RNA-seq data and clinicopathological information from The Cancer Genome Atlas (TCGA) database. A total of 1057 RNA methylation-related lncRNAs (RMlncRNAs) were identified with Pearson correlation analysis. Twenty-three RMlncRNAs with prognostic values were screened using univariate Cox regression analysis. By consensus clustering analysis, CC patients were classified into two molecular subtypes (Cluster 1 and Cluster 2) with different clinical outcomes and immune microenvironmental infiltration characteristics. Cluster 2 was considered to be the “hot tumor” with a better prognosis, while cluster 1 was regarded as the “cold tumor” with a poorer prognosis. Subsequently, we constructed a seven-lncRNA prognostic signature using the least absolute shrinkage and selection operator (LASSO) Cox regression. In combination with other clinical traits, we found that the RNA methylation-related lncRNA prognostic signature (called the “RMlnc-score”) was an independent prognostic factor for patients with colon cancer. In addition, immune infiltration, immunotherapy response analysis, and half-maximum inhibitory concentration (IC50) showed that the low RMlnc-score group was more sensitive to immunotherapy, while the high RMlnc-score group was sensitive to more chemotherapeutic agents. In summary, the RMlnc-score we developed could be used to predict the prognosis, immunotherapy response, and drug sensitivity of CC patients, guiding more accurate, and personalized treatment regimens.

Association Among the Gut Microbiome, the Serum Metabolomic Profile and RNA m6A Methylation in Sepsis-Associated Encephalopathy

Objective: To investigate the relationship among the gut microbiome, serum metabolomic profile and RNA m6A methylation in patients with sepsis-associated encephalopathy (SAE), 16S rDNA technology, metabolomics and gene expression validation were applied.

Methods: Serum and feces were collected from patients with and without (SAE group and non-SAE group, respectively, n = 20). The expression of serum markers and IL-6 was detected by enzyme-linked immunosorbent assay (ELISA), and blood clinical indicators were detected using a double antibody sandwich immunochemiluminescence method. The expression of RNA m⁶A regulator were checked by Q-RTPCR. The gut microbiome was analyzed by 16S rDNA sequencing and the metabolite profile was revealed by liquid chromatography-mass spectrometry (LC-MS/MS).

Results: In the SAE group, the IL-6, ICAM-5 and METTL3 levels were significantly more than those in the non-SAE group, while the FTO levels were significantly decreased in the SAE group. The diversity was decreased in the SAE gut microbiome, as characterized by a profound increase in commensals of the Acinetobacter, Methanobrevibacter, and Syner-01 genera, a decrease in [Eubacterium]_hallii_group, while depletion of opportunistic organisms of the Anaerofilum, Catenibacterium, and Senegalimassilia genera were observed in both groups. The abundance of Acinetobacter was positively correlated with the expression of METTL3. The changes between the intestinal flora and the metabolite profile showed a significant correlation. Sphingorhabdus was negatively correlated with 2-ketobutyric acid, 9-decenoic acid, and l-leucine, and positively correlated with Glycyl-Valine [Eubacterium]_hallii_group was positively correlated with 2-methoxy-3-methylpyazine, acetaminophen, and synephrine acetonide.

Conclusion: The gut microbiota diversity was decreased. The serum metabolites and expression of RNA m6A regulators in PBMC were significantly changed in the SAE group compared to the non-SAE group. The results revealed that serum and fecal biomarkers could be used for SAE screening.