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As the role of RNA modification in gene expression regulation and human diseases, the "epitranscriptome" has been shown to be an important player in regulating many physiological and pathological processes. Meanwhile, the phenomenon of cancer drug resistance is becoming more and more frequent, especially in the case of cancer chemotherapy resistance. In recent years, research on relationship between post-transcriptional modification and cancer including drug resistance has become a hot topic, especially the methylation of the sixth nitrogen site of RNA adenosine-m6A (N6-methyladenosine). m6A modification is the most common post-transcriptional modification of eukaryotic mRNA, accounting for 80% of RNA methylation modifications. At the same time, several other modifications of RNA, such as N1-methyladenosine (m1A), 5-methylcytosine (m5C), 3-methylcytosine (m3C), pseudouridine (Ψ) and N7-methylguanosine (m7G) have also been demonstrated to be involved in cancer and drug resistance. This review mainly discusses the research progress of RNA modifications in the field of cancer and drug resistance and targeting of m6A regulators by small molecule modulators, providing reference for future study and development of combination therapy to reverse cancer drug resistance. [ABSTRACT FROM AUTHOR]

N7-Methylguanosine (m7G) is important RNA modification at internal and the cap structure of five terminal end of message RNA. It is essential for RNA stability of RNA, the efficiency of translation, and various intracellular RNA processing pathways. Given the significance of the m7G modification, numerous studies have been conducted to predict m7G sites. To further elucidate the regulatory mechanisms surrounding m7G, we introduce a novel bioinformatics framework, m7GRegpred, designed to forecast the targets of the m7G methyltransferases METTL1 and WDR4, and m7G readers QKI5, QKI6, and QKI7 for the first time. We integrated different features to build predictors, with AUROC scores of 0.856, 0.857, 0.780, 0.776, 0.818 for METTL1, WDR4, QKI5, QKI6, and QKI7, respectively. In addition, the effect of window lengths and algorism were systemically evaluated in this work. The finial model was summarized in a user-friendly webserver: http://modinfor.com/m7GRegpred/. Our research indicates that the substrates of m7G regulators can be identified and may potentially advance the study of m7G regulators under unique conditions. [ABSTRACT FROM AUTHOR]

Abstract As the role of RNA modification in gene expression regulation and human diseases, the “epitranscriptome” has been shown to be an important player in regulating many physiological and pathological processes. Meanwhile, the phenomenon of cancer drug resistance is becoming more and more frequent, especially in the case of cancer chemotherapy resistance. In recent years, research on relationship between post-transcriptional modification and cancer including drug resistance has become a hot topic, especially the methylation of the sixth nitrogen site of RNA adenosine-m6A (N6-methyladenosine). m6A modification is the most common post-transcriptional modification of eukaryotic mRNA, accounting for 80% of RNA methylation modifications. At the same time, several other modifications of RNA, such as N1-methyladenosine (m1A), 5-methylcytosine (m5C), 3-methylcytosine (m3C), pseudouridine (Ψ) and N7-methylguanosine (m7G) have also been demonstrated to be involved in cancer and drug resistance. This review mainly discusses the research progress of RNA modifications in the field of cancer and drug resistance and targeting of m6A regulators by small molecule modulators, providing reference for future study and development of combination therapy to reverse cancer drug resistance.

Abstract Background tRNA-derived small RNAs (tsRNAs) are newly discovered non-coding RNA, which are generated from tRNAs and are reported to participate in several biological processes in diseases, especially cancer; however, the mechanism of tsRNA involvement in colorectal cancer (CRC) and 5-fluorouracil (5-FU) is still unclear. Methods RNA sequencing was performed to identify differential expression of tsRNAs in CRC tissues. CCK8, colony formation, transwell assays, and tumor sphere assays were used to investigate the role of tsRNA-GlyGCC in 5-FU resistance in CRC. TargetScan and miRanda were used to identify the target genes of tsRNA-GlyGCC. Biotin pull-down, RNA pull-down, luciferase assay, ChIP, and western blotting were used to explore the underlying molecular mechanisms of action of tsRNA-GlyGCC. The MeRIP assay was used to investigate the N(7)-methylguanosine RNA modification of tsRNA-GlyGCC. Results In this study, we uncovered the feature of tsRNAs in human CRC tissues and confirmed a specific 5’ half tRNA, 5’tiRNA-Gly-GCC (tsRNA-GlyGCC), which is upregulated in CRC tissues and modulated by METTL1-mediated N(7)-methylguanosine tRNA modification. In vitro and in vivo experiments revealed the oncogenic role of tsRNA-GlyGCC in 5-FU drug resistance in CRC. Remarkably, our results showed that tsRNA-GlyGCC modulated the JAK1/STAT6 signaling pathway by targeting SPIB. Poly (β-amino esters) were synthesized to assist the delivery of 5-FU and tsRNA-GlyGCC inhibitor, which effectively inhibited tumor growth and enhanced CRC sensitive to 5-FU without obvious adverse effects in subcutaneous tumor. Conclusions Our study revealed a specific tsRNA-GlyGCC-engaged pathway in CRC progression. Targeting tsRNA-GlyGCC in combination with 5-FU may provide a promising nanotherapeutic strategy for the treatment of 5-FU-resistance CRC. Graphical Abstract

Abstract Background Nasopharyngeal carcinoma (NPC) is a type of malignant tumor with high morbidity. Aberrant levels of N7-methylguanosine (m7G) are closely associated with tumor progression. However, the characteristics of the tumor microenvironment (TME) in NPC associated with m7G modification remain unclear. Methods A total of 68,795 single cells from single-cell RNA sequencing data derived from 11 NPC tumor samples and 3 nasopharyngeal lymphatic hyperplasia (NLH) samples were clustered using a nonnegative matrix factorization algorithm according to 61 m7G RNA modification regulators. Results The m7G regulators were found differential expression in the TME cells of NPC, and most m7G-related immune cell clusters in NPC tissues had a higher abundance compared to non-NPC tissues. Specifically, m7G scores in the CD4+ and CD8+ T cell clusters were significantly lower in NPC than in NLH. T cell clusters differentially expressed immune co-stimulators and co-inhibitors. Macrophage clusters differentially expressed EIF4A1, and high EIF4A1 expression was associated with poor survival in patients with head and neck squamous carcinoma. EIF4A1 was upregulated in NPC tissues compared to the non-NPC tissues and mainly expressed in CD86+ macrophages. Moreover, B cell clusters exhibited tumor biological characteristics under the regulation of m7G-related genes in NPC. The fibroblast clusters interacted with the above immune cell clusters and enriched tumor biological pathways, such as FGER2 signaling pathway. Importantly, there were correlations and interactions through various ligand-receptor links among epithelial cells and m7G-related TME cell clusters. Conclusion Our study revealed tumor-associated characteristics and immune dysregulation in the NPC microenvironment under the regulation of m7G-related TME cells. These results demonstrated the underlying regulatory roles of m7G in NPC.

Background: tRNA-derived small RNAs (tsRNAs) are newly discovered non-coding RNA, which are generated from tRNAs and are reported to participate in several biological processes in diseases, especially cancer; however, the mechanism of tsRNA involvement in colorectal cancer (CRC) and 5-fluorouracil (5-FU) is still unclear. Methods: RNA sequencing was performed to identify differential expression of tsRNAs in CRC tissues. CCK8, colony formation, transwell assays, and tumor sphere assays were used to investigate the role of tsRNA-GlyGCC in 5-FU resistance in CRC. TargetScan and miRanda were used to identify the target genes of tsRNA-GlyGCC. Biotin pull-down, RNA pull-down, luciferase assay, ChIP, and western blotting were used to explore the underlying molecular mechanisms of action of tsRNA-GlyGCC. The MeRIP assay was used to investigate the N(7)-methylguanosine RNA modification of tsRNA-GlyGCC. Results: In this study, we uncovered the feature of tsRNAs in human CRC tissues and confirmed a specific 5’ half tRNA, 5’tiRNA-Gly-GCC (tsRNA-GlyGCC), which is upregulated in CRC tissues and modulated by METTL1-mediated N(7)-methylguanosine tRNA modification. In vitro and in vivo experiments revealed the oncogenic role of tsRNA-GlyGCC in 5-FU drug resistance in CRC. Remarkably, our results showed that tsRNA-GlyGCC modulated the JAK1/STAT6 signaling pathway by targeting SPIB. Poly (β-amino esters) were synthesized to assist the delivery of 5-FU and tsRNA-GlyGCC inhibitor, which effectively inhibited tumor growth and enhanced CRC sensitive to 5-FU without obvious adverse effects in subcutaneous tumor. Conclusions: Our study revealed a specific tsRNA-GlyGCC-engaged pathway in CRC progression. Targeting tsRNA-GlyGCC in combination with 5-FU may provide a promising nanotherapeutic strategy for the treatment of 5-FU-resistance CRC. [ABSTRACT FROM AUTHOR]

Cardiac hypertrophy is a key factor driving heart failure (HF), yet its pathogenesis remains incompletely elucidated. Mettl1‐catalyzed RNA N7‐methylguanosine (m7G) modification has been implicated in ischemic cardiac injury and fibrosis. This study aims to elucidate the role of Mettl1 and the mechanism underlying non‐ischemic cardiac hypertrophy and HF. It is found that Mettl1 is upregulated in human failing hearts and hypertrophic murine hearts following transverse aortic constriction (TAC) and Angiotensin II (Ang II) infusion. YY1 acts as a transcriptional factor for Mettl1 during cardiac hypertrophy. Mettl1 knockout alleviates cardiac hypertrophy and dysfunction upon pressure overload from TAC or Ang II stimulation. Conversely, cardiac‐specific overexpression of Mettl1 results in cardiac remodeling. Mechanically, Mettl1 increases SRSF9 expression by inducing m7G modification of SRSF9 mRNA, facilitating alternative splicing and stabilization of NFATc4, thereby promoting cardiac hypertrophy. Moreover, the knockdown of SRSF9 protects against TAC‐ or Mettl1‐induced cardiac hypertrophic phenotypes in vivo and in vitro. The study identifies Mettl1 as a crucial regulator of cardiac hypertrophy, providing a novel therapeutic target for HF. [ABSTRACT FROM AUTHOR]

Background: Nasopharyngeal carcinoma (NPC) is a type of malignant tumor with high morbidity. Aberrant levels of N7-methylguanosine (m7G) are closely associated with tumor progression. However, the characteristics of the tumor microenvironment (TME) in NPC associated with m7G modification remain unclear. Methods: A total of 68,795 single cells from single-cell RNA sequencing data derived from 11 NPC tumor samples and 3 nasopharyngeal lymphatic hyperplasia (NLH) samples were clustered using a nonnegative matrix factorization algorithm according to 61 m7G RNA modification regulators. Results: The m7G regulators were found differential expression in the TME cells of NPC, and most m7G-related immune cell clusters in NPC tissues had a higher abundance compared to non-NPC tissues. Specifically, m7G scores in the CD4+ and CD8+ T cell clusters were significantly lower in NPC than in NLH. T cell clusters differentially expressed immune co-stimulators and co-inhibitors. Macrophage clusters differentially expressed EIF4A1, and high EIF4A1 expression was associated with poor survival in patients with head and neck squamous carcinoma. EIF4A1 was upregulated in NPC tissues compared to the non-NPC tissues and mainly expressed in CD86+ macrophages. Moreover, B cell clusters exhibited tumor biological characteristics under the regulation of m7G-related genes in NPC. The fibroblast clusters interacted with the above immune cell clusters and enriched tumor biological pathways, such as FGER2 signaling pathway. Importantly, there were correlations and interactions through various ligand-receptor links among epithelial cells and m7G-related TME cell clusters. Conclusion: Our study revealed tumor-associated characteristics and immune dysregulation in the NPC microenvironment under the regulation of m7G-related TME cells. These results demonstrated the underlying regulatory roles of m7G in NPC. [ABSTRACT FROM AUTHOR]

Abstract Cardiac hypertrophy is a key factor driving heart failure (HF), yet its pathogenesis remains incompletely elucidated. Mettl1‐catalyzed RNA N7‐methylguanosine (m7G) modification has been implicated in ischemic cardiac injury and fibrosis. This study aims to elucidate the role of Mettl1 and the mechanism underlying non‐ischemic cardiac hypertrophy and HF. It is found that Mettl1 is upregulated in human failing hearts and hypertrophic murine hearts following transverse aortic constriction (TAC) and Angiotensin II (Ang II) infusion. YY1 acts as a transcriptional factor for Mettl1 during cardiac hypertrophy. Mettl1 knockout alleviates cardiac hypertrophy and dysfunction upon pressure overload from TAC or Ang II stimulation. Conversely, cardiac‐specific overexpression of Mettl1 results in cardiac remodeling. Mechanically, Mettl1 increases SRSF9 expression by inducing m7G modification of SRSF9 mRNA, facilitating alternative splicing and stabilization of NFATc4, thereby promoting cardiac hypertrophy. Moreover, the knockdown of SRSF9 protects against TAC‐ or Mettl1‐induced cardiac hypertrophic phenotypes in vivo and in vitro. The study identifies Mettl1 as a crucial regulator of cardiac hypertrophy, providing a novel therapeutic target for HF.

Abstract Background RNA modifications have been proven to play fundamental roles in regulating cellular biology process. Recently, maladjusted N7-methylguanosine (m7G) modification and its modifiers METTL1/WDR4 have been confirmed an oncogene role in multiple cancers. However, the functions and molecular mechanisms of METTL1/WDR4 in acute myeloid leukemia (AML) remain to be determined. Methods METTL1/WDR4 expression levels were quantified using qRT-PCR, western blot analysis on AML clinical samples, and bioinformatics analysis on publicly available AML datasets. CCK-8 assays and cell count assays were performed to determine cell proliferation. Flow cytometry assays were conducted to assess cell cycle and apoptosis rates. Multiple techniques were used for mechanism studies in vitro assays, such as northern blotting, liquid chromatography-coupled mass spectrometry (LC–MS/MS), tRNA stability analysis, transcriptome sequencing, small non-coding RNA sequencing, quantitative proteomics, and protein synthesis measurements. Results METTL1/WDR4 are significantly elevated in AML patients and associated with poor prognosis. METTL1 knockdown resulted in reduced cell proliferation and increased apoptosis in AML cells. Mechanically, METTL1 knockdown leads to significant decrease of m7G modification abundance on tRNA, which further destabilizes tRNAs and facilitates the biogenesis of tsRNAs in AML cells. In addition, profiling of nascent proteins revealed that METTL1 knockdown and transfection of total tRNAs that were isolated from METTL1 knockdown AML cells decreased global translation efficiency in AML cells. Conclusions Taken together, our study demonstrates the important role of METTL1/WDR4 in AML leukaemogenesis, which provides a promising target candidate for AML therapy.

Updates in whole genome sequencing technologies have revealed various RNA modifications in cancer, among which RNA methylation is a frequent posttranscriptional modification. RNA methylation is essential for regulating biological processes such as RNA transcription, splicing, structure, stability, and translation. Its dysfunction is strongly associated with the development of human malignancies. Research advances with respect to the regulatory role of RNA modifications in ovarian cancer include N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), and N7-methylguanosine (m7G). Numerous studies have demonstrated that epigenetic modifications of RNA can influence the progression and metastasis of ovarian cancer and may provide excellent targets for cancer therapy. This review highlights advances in research on RNA methylation modifications and ovarian cancer prognosis, carcinogenesis, and resistance, which could provide a theoretical foundation for designing therapeutic strategies for ovarian cancer based on RNA methylation modifications.

Background: Emerging evidence points to the exceptional importance and value of m7G alteration in the diagnosis and prognosis of cancers. Nonetheless, a biomarker for precise screening of various cancer types has not yet been developed based on serum m7G-harboring miRNAs. Methods: A total of 20,702 serumsamples, covering 12 cancer types and consisting of 7,768 cancer samples and 12,934 cancer-free samples were used in this study. A m7G target miRNA diagnostic signature (m7G-miRDS) was established through the least absolute shrinkage and selection operator (LASSO) analyses in a training dataset (n = 10,351), and validated in a validation dataset (n = 10,351). Results: The m7G-miRDS model, a 12 m7G-target-miRNAs signature, demonstrated high accuracy and was qualified for cancer detection. In the training and validation cohort, the area under the curve (AUC) reached 0.974 (95% CI 0.971-0.977) and 0.972 (95% CI 0.969-0.975), respectively. The m7G-miRDS showed superior sensitivity in each cancer type and had a satisfactory AUCin identifying bladder cancer, lung cancer and esophageal cancer. Additionally, the diagnostic performance of m7G-miRDS was not interfered by the gender, age and benign disease. Conclusion: Our results greatly extended the value of serum circulating miRNAs and m7G in cancer detection, and provided a new direction and strategy for the development of novel biomarkers with high accuracy, low cost and less invasiveness for mass cancer screening, such as ncRNA modification. [ABSTRACT FROM AUTHOR]

Background: RNA modifications have been proven to play fundamental roles in regulating cellular biology process. Recently, maladjusted N7-methylguanosine (m7G) modification and its modifiers METTL1/WDR4 have been confirmed an oncogene role in multiple cancers. However, the functions and molecular mechanisms of METTL1/WDR4 in acute myeloid leukemia (AML) remain to be determined. Methods: METTL1/WDR4 expression levels were quantified using qRT-PCR, western blot analysis on AML clinical samples, and bioinformatics analysis on publicly available AML datasets. CCK-8 assays and cell count assays were performed to determine cell proliferation. Flow cytometry assays were conducted to assess cell cycle and apoptosis rates. Multiple techniques were used for mechanism studies in vitro assays, such as northern blotting, liquid chromatography-coupled mass spectrometry (LC–MS/MS), tRNA stability analysis, transcriptome sequencing, small non-coding RNA sequencing, quantitative proteomics, and protein synthesis measurements. Results: METTL1/WDR4 are significantly elevated in AML patients and associated with poor prognosis. METTL1 knockdown resulted in reduced cell proliferation and increased apoptosis in AML cells. Mechanically, METTL1 knockdown leads to significant decrease of m7G modification abundance on tRNA, which further destabilizes tRNAs and facilitates the biogenesis of tsRNAs in AML cells. In addition, profiling of nascent proteins revealed that METTL1 knockdown and transfection of total tRNAs that were isolated from METTL1 knockdown AML cells decreased global translation efficiency in AML cells. Conclusions: Taken together, our study demonstrates the important role of METTL1/WDR4 in AML leukaemogenesis, which provides a promising target candidate for AML therapy. [ABSTRACT FROM AUTHOR]

Background: Acute myeloid leukemia (AML) patients still suffer from poor 5-year survival and relapse after remission. A better prognostic assessment tool is urgently needed. New evidence demonstrates that 7-methylguanosine (m7G) methylation modifications play an important role in AML, however, the exact role of m7G-related genes in the prognosis of AML remains unclear. Methods: The study obtained AML expression profiles and clinical information from TCGA, GEO, and TARGET databases. Using the patient data from the TCGA cohort as the training set. Consensus clustering was performed based on 29 m7G-related genes. Survival analysis was performed by KM curves. The subgroup characteristic gene sets were screened using WGCNA. And tumor immune infiltration correlation analysis was performed by ssGSEA. Results: The patients were classified into 3 groups based on m7G-related genebased cluster analysis, and the differential genes were screened by differential analysis and WGCNA. After LASSO regression analysis, 6 characteristic genes (including CBR1, CCDC102A, LGALS1, RD3L, SLC29A2, and TWIST1) were screened, and a prognostic risk-score model was constructed. The survival rate of low-risk patients was significantly higher than that of high-risk patients (p < 0.0001). The area under the curve values at 1, 3, and 5 years in the training set were 0.871, 0.874, and 0.951, respectively, indicating that this predictive model has an excellent predictive effect. In addition, after univariate and multivariate Cox regression screening, histograms were constructed with clinical characteristics and prognostic risk score models to better predict individual survival. Further analysis showed that the prognostic risk score model was associated with immune cell infiltration. Conclusion: These findings suggest that the scoring model and essential risk genes could provide potential prognostic biomarkers for patients with acute myeloid leukemia. [ABSTRACT FROM AUTHOR]

Background: Radiotherapy is an effective treatment for hepatocellular carcinoma (HCC). Recent studies indicated that N7-methylguanosine (m7G)-associated genes are involved in radioresistance and prognosis of HCC. However, the prognostic value and underlying mechanism of m7G-and radiosensitivity-associated genes are still lacking. Methods: The related statistics of HCC were downloaded from The Cancer Genome Atlas (TCGA). M7G- and radiosensitivity-associated genes were screened and evaluated using correlation, differential, univariate, and multivariate analysis. The least absolute shrinkage and selection operator (LASSO) algorithm was used to establish a prognostic model. Prognostic efficacy, functional analysis, immune cell infiltration,and drug sensitivity of the prognostic model were assessed. The ceRNA network was predicted and evaluated through the StarBase database, correlation analysis, expression analysis, and survival analysis. Result: METTL1, EIF3D, NCBP2, and WDR4 participated in prognosis model construction. The favorable prediction efficiency has been verified in both the training and verification sets. Different risk groups have differences in prognosis outcome, function analysis, immune cell infiltration, and drug sensitivity. NCBP2 can be used to predict the prognosis and has excellent potential in immunotherapy. A prognostic ceRNA network based on the NCBP2/miR-122-5p axis was established. Conclusion: The prognosis model of m7G- and radiosensitivity-related genes is constructed, and widely used in clinical prognosis, immunotherapy, and drug therapy. NCBP2, as a hub gene, may be a prognostic biomarker for HCC and is related to immunotherapy. Establishing the NCBP2/miR-122-5p axis helps study the mechanism of ceRNA and provides new ideas for finding a new candidate biomarker.

Abstract Background N7-methylguanosine (m7G) modification is, a more common epigenetic modification in addition to m6A modification, mainly found in mRNA capsids, mRNA interiors, transfer RNA (tRNA), pri-miRNA, and ribosomal RNA (rRNA). It has been found that m7G modifications play an important role in mRNA transcription, tRNA stability, rRNA processing maturation, and miRNA biosynthesis. However, the role of m7G modifications within mRNA and its “writer” methyltransferase 1(METTL1) in tumors, particularly prostate cancer (PCa), has not been revealed. Methods The differential expression level of METTL1 between hormone-sensitive prostate cancer (HSPC) and castrate-resistant prostate cancer (CRPC) was evaluated via RNA-seq and in vitro experiments. The effects of METTL1 on CRPC progression were investigated through in vitro and in vivo assays. The upstream molecular mechanism of METTL1 expression upregulation and the downstream mechanism of its action were explored via Chromatin Immunoprecipitation quantitative reverse transcription polymerase chain reaction (CHIP-qPCR), Co-immunoprecipitation (Co-IP), luciferase reporter assay, transcriptome-sequencing, m7G AlkAniline-Seq, and mRNA degradation experiments, etc. Results and conclusion Here, we found that METTL1 was elevated in CRPC and that patients with METTL1 elevation tended to have a poor prognosis. Functionally, the knockdown of METTL1 in CRPC cells significantly limited cell proliferation and invasive capacity. Mechanistically, we unveiled that P300 can form a complex with SP1 and bind to the promoter region of the METTL1 gene via SP1, thereby mediating METTL1 transcriptional upregulation in CRPC. Subsequently, our findings indicated that METTL1 leads to enhanced mRNA stability of CDK14 by adding m7G modifications inside its mRNA, ultimately promoting CRPC progression.

Background: Emerging evidence points to the exceptional importance and value of m7G alteration in the diagnosis and prognosis of cancers. Nonetheless, a biomarker for precise screening of various cancer types has not yet been developed based on serum m7G-harboring miRNAs.Methods: A total of 20,702 serum samples, covering 12 cancer types and consisting of 7,768 cancer samples and 12,934 cancer-free samples were used in this study. A m7G target miRNA diagnostic signature (m7G-miRDS) was established through the least absolute shrinkage and selection operator (LASSO) analyses in a training dataset (n = 10,351), and validated in a validation dataset (n = 10,351).Results: The m7G-miRDS model, a 12 m7G-target-miRNAs signature, demonstrated high accuracy and was qualified for cancer detection. In the training and validation cohort, the area under the curve (AUC) reached 0.974 (95% CI 0.971–0.977) and 0.972 (95% CI 0.969–0.975), respectively. The m7G-miRDS showed superior sensitivity in each cancer type and had a satisfactory AUC in identifying bladder cancer, lung cancer and esophageal cancer. Additionally, the diagnostic performance of m7G-miRDS was not interfered by the gender, age and benign disease.Conclusion: Our results greatly extended the value of serum circulating miRNAs and m7G in cancer detection, and provided a new direction and strategy for the development of novel biomarkers with high accuracy, low cost and less invasiveness for mass cancer screening, such as ncRNA modification.

BackgroundAcute myeloid leukemia (AML) patients still suffer from poor 5-year survival and relapse after remission. A better prognostic assessment tool is urgently needed. New evidence demonstrates that 7-methylguanosine (m7G) methylation modifications play an important role in AML, however, the exact role of m7G-related genes in the prognosis of AML remains unclear.MethodsThe study obtained AML expression profiles and clinical information from TCGA, GEO, and TARGET databases. Using the patient data from the TCGA cohort as the training set. Consensus clustering was performed based on 29 m7G-related genes. Survival analysis was performed by KM curves. The subgroup characteristic gene sets were screened using WGCNA. And tumor immune infiltration correlation analysis was performed by ssGSEA.ResultsThe patients were classified into 3 groups based on m7G-related genebased cluster analysis, and the differential genes were screened by differential analysis and WGCNA. After LASSO regression analysis, 6 characteristic genes (including CBR1, CCDC102A, LGALS1, RD3L, SLC29A2, and TWIST1) were screened, and a prognostic risk-score model was constructed. The survival rate of low-risk patients was significantly higher than that of high-risk patients (p < 0.0001). The area under the curve values at 1, 3, and 5 years in the training set were 0.871, 0.874, and 0.951, respectively, indicating that this predictive model has an excellent predictive effect. In addition, after univariate and multivariate Cox regression screening, histograms were constructed with clinical characteristics and prognostic risk score models to better predict individual survival. Further analysis showed that the prognostic risk score model was associated with immune cell infiltration.ConclusionThese findings suggest that the scoring model and essential risk genes could provide potential prognostic biomarkers for patients with acute myeloid leukemia.

Abstract Presenting with a poor prognosis, gastric cancer (GC) remains one of the leading causes of disease and death worldwide. Long non-coding RNAs (lncRNAs) regulate tumor formation and have been long used to predict tumor prognosis. N7-methylguanosine (m7G) is the most prevalent RNA modification. m7G-lncRNAs regulate GC onset and progression, but their precise mechanism in GC is unclear. The objective of this research was the development of a new m7G-related lncRNA signature as a biomarker for predicting GC survival rate and guiding treatment. The Cancer Genome Atlas database helped extract gene expression data and clinical information for GC. Pearson correlation analysis helped point out m7G-related lncRNAs. Univariate Cox analysis helped in identifying m7G-related lncRNA with predictive capability. The Lasso-Cox method helped point out seven lncRNAs for the purpose of establishing an m7G-related lncRNA prognostic signature (m7G-LPS), followed by the construction of a nomogram. Kaplan–Meier analysis, univariate and multivariate Cox regression analysis, calibration plot of the nomogram model, receiver operating characteristic curve and principal component analysis were utilized for the verification of the risk model’s reliability. Furthermore, q-PCR helped verify the lncRNAs expression of m7G-LPS in-vitro. The study subjects were classified into high and low-risk groups based on the median value of the risk score. Gene enrichment analysis confirmed the constructed m7G-LPS’ correlation with RNA transcription and translation and multiple immune-related pathways. Analysis of the clinicopathological features revealed more progressive features in the high-risk group. CIBERSORT analysis showed the involvement of m7G-LPS in immune cell infiltration. The risk score was correlated with immune checkpoint gene expression, immune cell and immune function score, immune cell infiltration, and chemotherapy drug sensitivity. Therefore, our study shows that m7G-LPS constructed using seven m7G-related lncRNAs can predict the survival time of GC patients and guide chemotherapy and immunotherapy regimens as biomarker.

In recent years, N7-methylguanosine (m7G) methylation, originally considered as messenger RNA (mRNA) 5′ caps modifications, has been identified at defined internal positions within multiple types of RNAs, including transfer RNAs, ribosomal RNAs, miRNA, and mRNAs. Scientists have put substantial efforts to discover m7G methyltransferases and methylated sites in RNAs to unveil the essential roles of m7G modifications in the regulation of gene expression and determine the association of m7G dysregulation in various diseases, including neurological disorders. Here, we review recent findings regarding the distribution, abundance, biogenesis, modifiers, and functions of m7G modifications. We also provide an up-to-date summary of m7G detection and profile mapping techniques, databases for validated and predicted m7G RNA sites, and web servers for m7G methylation prediction. Furthermore, we discuss the pathological roles of METTL1/WDR-driven m7G methylation in neurological disorders. Last, we outline a roadmap for future directions and trends of m7G modification research, particularly in the central nervous system.

Background: Osteosarcoma (OS), a primary malignant bone tumor, confronts therapeutic challenges rooted in multidrug resistance. Comprehensive understanding of disease occurrence and progression is imperative for advancing treatment strategies. m7G modification, an emerging posttranscriptional modification implicated in various diseases, may provide new insights to explore OS pathogenesis and progression. Methods: The m7G-related molecular landscape in OS was probed using diverse bioinformatics analyses, encompassing LASSO Cox regression, immune infiltration assessment, and drug sensitivity analysis. Furthermore, the therapeutic potential of AZD2014 for OS was investigated through cell apoptosis and cycle assays. Eventually, multivariate Cox analysis and experimental validations, were conducted to investigate the independent prognostic m7G-related genes. Results: A comprehensive m7G-related risk model incorporating eight signatures was established, with corresponding risk scores correlated with immune infiltration and drug sensitivity. Drug sensitivity analysis spotlighted AZD2014 as a potential therapeutic candidate for OS. Subsequent experiments corroborated AZD2014's capability to induce G1-phase cell cycle arrest and apoptosis in OS cells. Ultimately, multivariate Cox regression analysis unveiled the independent prognostic importance of CYFIP1 and EIF4A1, differential expressions of which were validated at histological and cytological levels. Conclusion: This study furnishes a profound understanding of the contribution of m7G-related genes to the pathogenesis of OS. The discerned therapeutic potential of AZD2014, in conjunction with the identification of CYFIP1 and EIF4A1 as independent risk factors, opens novel vistas for the treatment of OS. [ABSTRACT FROM AUTHOR]

Background: N7-methylguanosine (m7G) modification is, a more common epigenetic modification in addition to m6A modification, mainly found in mRNA capsids, mRNA interiors, transfer RNA (tRNA), pri-miRNA, and ribosomal RNA (rRNA). It has been found that m7G modifications play an important role in mRNA transcription, tRNA stability, rRNA processing maturation, and miRNA biosynthesis. However, the role of m7G modifications within mRNA and its "writer" methyltransferase 1(METTL1) in tumors, particularly prostate cancer (PCa), has not been revealed. Methods: The differential expression level of METTL1 between hormone-sensitive prostate cancer (HSPC) and castrate-resistant prostate cancer (CRPC) was evaluated via RNA-seq and in vitro experiments. The effects of METTL1 on CRPC progression were investigated through in vitro and in vivo assays. The upstream molecular mechanism of METTL1 expression upregulation and the downstream mechanism of its action were explored via Chromatin Immunoprecipitation quantitative reverse transcription polymerase chain reaction (CHIP-qPCR), Co-immunoprecipitation (Co-IP), luciferase reporter assay, transcriptome-sequencing, m7G AlkAniline-Seq, and mRNA degradation experiments, etc. Results and conclusion: Here, we found that METTL1 was elevated in CRPC and that patients with METTL1 elevation tended to have a poor prognosis. Functionally, the knockdown of METTL1 in CRPC cells significantly limited cell proliferation and invasive capacity. Mechanistically, we unveiled that P300 can form a complex with SP1 and bind to the promoter region of the METTL1 gene via SP1, thereby mediating METTL1 transcriptional upregulation in CRPC. Subsequently, our findings indicated that METTL1 leads to enhanced mRNA stability of CDK14 by adding m7G modifications inside its mRNA, ultimately promoting CRPC progression. [ABSTRACT FROM AUTHOR]

Alterations in the regulators of RNA methylation modifications, such as N7-methylguanosine (m7G), have been implicated in a variety of diseases. Therefore, the analysis and identification of disease-related m7G modification regulators will accelerate advances in understanding disease pathogenesis. However, the implications of alterations in the regulators of m7G modifications remain poorly understood in prostate adenocarcinoma. In the present study, we analyze the expression patterns of 29 m7G RNA modification regulators in prostate adenocarcinoma using The Cancer Genome Atlas (TCGA) and perform consistent clustering analysis of differentially expressed genes (DEGs). We find that 18 m7G-related genes are differentially expressed in tumor and normal tissues. In different cluster subgroups, DEGs are mainly enriched in tumorigenesis and tumor development. Furthermore, immune analyses demonstrate that patients in cluster 1 have significantly higher scores for stromal and immune cells, such as B cells, T cells, and macrophages. Then, a TCGA-related risk model is developed and successfully validated using a Gene Expression Omnibus external dataset. Two genes ( EIF4A1 and NCBP2) are determined to be prognostically significant. Most importantly, we construct tissue microarrays from 26 tumor specimens and 20 normal specimens, and further confirm that EIF4A1 and NCBP2 are associated with tumor progression and Gleason score. Therefore, we conclude that the m7G RNA methylation regulators may be involved in the poor prognosis of patients with prostate adenocarcinoma. The results of this study may provide support for exploring the underlying molecular mechanisms of m7G regulators, especially EIF4A1 and NCBP2.

Abstract Background N7-methylguanosine (m7G) is closely associated with tumor prognosis and immune response in many cancer types. The correlation between m7G and bladder cancer (BC) needs further study. We aimed to orchestrate molecular subtypes and identify key genes for BC from the perspective of m7G. Methods RNA-seq and clinical data of BC patients were extracted from TCGA and GSE13507 datasets. The patients were subtyped by “ConsensusClusterPlus” and “limma.” The clusters were validated by the Kaplan‒Meier curves, univariable and multivariate Cox regression models, the concordance index, and calibration curves. The immunotherapy response was evaluated by immune checkpoints, immune infiltration, TIDE score, and IMvigor210 cohort. Genomics of Drug Sensitivity in Cancer was utilized to predict the chemotherapy response between the clusters. Results The m7G-related cluster was ultimately established by EIF4G1, NUDT11, NUDT10, and CCNB1. The independent prognostic value of the m7G-related cluster was validated by the TCGA and GSE13507 datasets. The cluster was involved in immune-associated pathways, such as neutrophil degranulation, antigen processing cross-presentation, and signaling by interleukins pathways. Meanwhile, cluster 2 was positively correlated with many immune checkpoints, such as CD274, CTLA4, HAVCR2, LAG3, PDCD1, and PDCD1LG2. The cluster 2 was significantly correlated with a higher TIDE score than the cluster 1. Furthermore, in the IMvigor210 cohort, patients in the cluster 1 had a higher response rate than those in the cluster 2. Patients in the cluster 2 were sensitive to many chemotherapies. Conclusions We successfully determined molecular subtypes and identified key genes for BC from the perspective of m7G, thereby providing a roadmap for the evolution of immunotherapy and precision medicine.

Abstract Background N7-methylguanosine (m7G) is present in a wide variety of organisms and has important roles. m7G has been reported to be involved in multiple biological processes, and recent studies have reported that changes in RNA modifications result in tumor cellular transformation and cancer, such as colon adenocarcinoma, lung cancer, and intrahepatic cholangiocarcinoma. However, little is known about the function of the m7G in colon adenocarcinoma. Methods We established two clusters based on the expression of all genes associated with m7G to explore the expression pattern of 31 key regulatory factors of m7G RNA and assess the prognostic value of regulatory factors. Wilcoxon test and differential box line plots were applied for bioinformatics analysis. Receiver Operating and Kaplan‒Meier curves were utilized to evaluate the prognostic value. Finally, four genes' expression in the colon cancer cell line was confirmed by qRT-PCR. Results From The Cancer Genome Atlas database, we found that the expression levels of 25 out of the 31 key N7-methylguanosine RNA modification regulators were significantly different in colon adenocarcinoma. According to 25 methylation regulators’ expression, we identified two subgroups by consensus clustering, in which the prognosis was worse in Group 2 than in Group 1 and was significantly correlated with age. Cluster 2 was significantly enriched in tumor-associated pathways, and immune cells were highly infiltrated in Cluster 1 but weakly infiltrated in Cluster 2. Further results indicated that this risk profile may serve as a standalone predictive factor for colon adenocarcinoma, and the four genetic risk profiles’ prognostic relatedness was successfully verified through Gene Expression Omnibus dataset. At last, A nomogram for prognosis was created according to age, sex, histological grading, clinicopathological staging, and hazard score to accurately predict patient prognosis in colon adenocarcinoma. We successfully validated the differential expression of four genes using qRT-PCR. Conclusions In the present study, we revealed the important contribution of key regulators associated with m7G RNA modifications based on all gene expression in colon adenocarcinoma and developed a signature of risk that serves as a promising prognostic marker for patients with colon adenocarcinoma.

Abstract Background N7-Methylguanosine (m7G) and long non-coding RNAs (lncRNAs) have been widely studied in cancer and have been found to be useful for assessing tumor progression. However, the role of m7G-related lncRNAs in lung squamous cell carcinoma (LUSC) remains unclear. Thus, it is crucial to identify m7G-associated lncRNAs with definitive prognostic value. This study aimed to investigate the prognostic value, correlation with tumor mutation burden, and impact on the tumor immune microenvironment of m7G-related lncRNAs in LUSC. Methods LUSC transcriptome data and clinical data were downloaded from The Cancer Genome Atlas, and an m7G-related lncRNA-mRNA co-expression network was constructed using Pearson’s correlation analysis. Cox regression analyses were used to determine a risk model for m7G-associated lncRNAs with prognostic value. The risk signature was verified using the Kaplan–Meier method, receiver operating characteristic curve analysis, and principal component analysis. A nomogram based on risk scores and clinical characteristics was then developed. Gene set enrichment analysis was used for functional annotation to analyze the risk signature. The association among the risk signature, tumor mutational burden, and tumor-infiltrating immune cells was then analyzed. RT-qPCR was used to investigate the expression of 6 m7G-related lncRNAs in LUSC cells. The cytological function of SRP14-AS1 was verified by wound-healing assay and transwell assay. Results A total of 293 m7G-related lncRNAs were identifed, 27 candidate m7G-related lncRNAs were signifcantly associated with overall survival (OS). Six of these lncRNAs (CYP4F26P, LINC02178, MIR22HG, SRP14-AS1, TMEM99, PTCSC2) were selected for establishment of the risk model. The OS of patients in the low-risk group was higher than that of patients in the high-risk group (p

N7-Methylguanosine (m7G) modification holds significant importance in regulating posttranscriptional gene expression in epigenetics. Long non-coding RNAs (lncRNAs) have been demonstrated to play a crucial role in cancer progression. m7G-related lncRNA may be involved in the progression of pancreatic cancer (PC), although the underlying mechanism of regulation remains obscure. We obtained RNA sequence transcriptome data and relevant clinical information from the TCGA and GTEx databases. Univariate and multivariate Cox proportional risk analyses were performed to build a twelve-m7G-associated lncRNA risk model with prognostic value. The model was verified using receiver operating characteristic curve analysis and Kaplan–Meier analysis. The expression level of m7G-related lncRNAs in vitro was validated. Knockdown of SNHG8 increased the proliferation and migration of PC cells. Differentially expressed genes between high- and low-risk groups were identified for gene set enrichment analysis, immune infiltration, and potential drug exploration. We conducted an m7G-related lncRNA predictive risk model for PC patients. The model had independent prognostic significance and offered an exact survival prediction. The research provided us with better knowledge of the regulation of tumor-infiltrating lymphocytes in PC. The m7G-related lncRNA risk model may serve as a precise prognostic tool and indicate prospective therapeutic targets for PC patients. [ABSTRACT FROM AUTHOR]

Presenting with a poor prognosis, gastric cancer (GC) remains one of the leading causes of disease and death worldwide. Long non-coding RNAs (lncRNAs) regulate tumor formation and have been long used to predict tumor prognosis. N7-methylguanosine (m7G) is the most prevalent RNA modification. m7G-lncRNAs regulate GC onset and progression, but their precise mechanism in GC is unclear. The objective of this research was the development of a new m7G-related lncRNA signature as a biomarker for predicting GC survival rate and guiding treatment. The Cancer Genome Atlas database helped extract gene expression data and clinical information for GC. Pearson correlation analysis helped point out m7G-related lncRNAs. Univariate Cox analysis helped in identifying m7G-related lncRNA with predictive capability. The Lasso-Cox method helped point out seven lncRNAs for the purpose of establishing an m7G-related lncRNA prognostic signature (m7G-LPS), followed by the construction of a nomogram. Kaplan–Meier analysis, univariate and multivariate Cox regression analysis, calibration plot of the nomogram model, receiver operating characteristic curve and principal component analysis were utilized for the verification of the risk model's reliability. Furthermore, q-PCR helped verify the lncRNAs expression of m7G-LPS in-vitro. The study subjects were classified into high and low-risk groups based on the median value of the risk score. Gene enrichment analysis confirmed the constructed m7G-LPS' correlation with RNA transcription and translation and multiple immune-related pathways. Analysis of the clinicopathological features revealed more progressive features in the high-risk group. CIBERSORT analysis showed the involvement of m7G-LPS in immune cell infiltration. The risk score was correlated with immune checkpoint gene expression, immune cell and immune function score, immune cell infiltration, and chemotherapy drug sensitivity. Therefore, our study shows that m7G-LPS constructed using seven m7G-related lncRNAs can predict the survival time of GC patients and guide chemotherapy and immunotherapy regimens as biomarker. [ABSTRACT FROM AUTHOR]

Background: The functional ramifications of internal N7-methylguanosine (m7G) modification on RNAs have recently come to light, yet its regulatory influence on long noncoding RNAs (lncRNAs) during the inflammatory-carcinogenesis transformation process in hepatitis B virus (HBV)-mediated hepatocellular carcinoma (HCC) remains largely unexplored. Methods: Clinical surgical samples encompassing HBV-related HCC, comprising both HCC tissue (tumor group, HBV+) and corresponding adjacent liver tissue (paracancerous group, HBV+), were collected for analysis. Additional adjacent normal liver tissues (normal group, HBV-) were acquired from patients with hepatic hemangioma, serving as controls. Employing MeRIP-seq, differential m7G levels of lncRNAs across these groups were compared to identify a subset of lncRNAs exhibiting continuous and dynamic changes in m7G modification. Subsequently, in vitro validation was conducted. Results: A total of 856 lncRNAs exhibited alterations in m7G modification when compared to paracancerous tissue and normal tissue. Similarly, 1775 lncRNAs displayed changes in m7G modification when comparing HCC tissue to paracancerous tissue. For intergroup comparison, orthogonal analysis revealed that 6 lncRNAs consistently demonstrated hyper-m7G modification. In vitro validation confirmed that among these 6 lncRNAs, TEKT4P2 and DNM1P41 exhibited m7G modification-dependent expression. Conclusions: This study provides a comprehensive analysis of lncRNA m7G modification during the inflammatory-carcinogenesis transformation process in HBV-mediated HCC. The findings highlight the potential for multiple lncRNAs to undergo m7G modification changes, with TEKT4P2 and DNM1P41 identified as promising molecular targets within this intricate regulatory landscape.

Background: N7-methylguanosine (m7G) is closely associated with tumor prognosis and immune response in many cancer types. The correlation between m7G and bladder cancer (BC) needs further study. We aimed to orchestrate molecular subtypes and identify key genes for BC from the perspective of m7G. Methods: RNA-seq and clinical data of BC patients were extracted from TCGA and GSE13507 datasets. The patients were subtyped by "ConsensusClusterPlus" and "limma." The clusters were validated by the Kaplan‒Meier curves, univariable and multivariate Cox regression models, the concordance index, and calibration curves. The immunotherapy response was evaluated by immune checkpoints, immune infiltration, TIDE score, and IMvigor210 cohort. Genomics of Drug Sensitivity in Cancer was utilized to predict the chemotherapy response between the clusters. Results: The m7G-related cluster was ultimately established by EIF4G1, NUDT11, NUDT10, and CCNB1. The independent prognostic value of the m7G-related cluster was validated by the TCGA and GSE13507 datasets. The cluster was involved in immune-associated pathways, such as neutrophil degranulation, antigen processing cross-presentation, and signaling by interleukins pathways. Meanwhile, cluster 2 was positively correlated with many immune checkpoints, such as CD274, CTLA4, HAVCR2, LAG3, PDCD1, and PDCD1LG2. The cluster 2 was significantly correlated with a higher TIDE score than the cluster 1. Furthermore, in the IMvigor210 cohort, patients in the cluster 1 had a higher response rate than those in the cluster 2. Patients in the cluster 2 were sensitive to many chemotherapies. Conclusions: We successfully determined molecular subtypes and identified key genes for BC from the perspective of m7G, thereby providing a roadmap for the evolution of immunotherapy and precision medicine. [ABSTRACT FROM AUTHOR]

Background: Increasing evidence indicates a crucial role for N7-methylguanosine (m7G) methylation modification in human disease development, particularly cancer, and aberrant m7G levels are closely associated with tumorigenesis and progression via regulation of the expression of multiple oncogenes and tumor suppressor genes. However, the role of m7G in sarcomas (SARC) has not been adequately evaluated. Materials and methods: Transcriptome and clinical data were gathered from the TCGA database for this study. Normal and SARC groups were compared for the expression of m7G-related genes (m7GRGs). The expression of m7GRGs was verified using real-time quantitative PCR (RT-qPCR) in SARC cell lines. Then, differentially expressed genes (DEGs) were identified between high and low m7GRGs expression groups in SARC samples, and GO enrichment and KEGG pathways were evaluated. Next, prognostic values of m7GRGs were evaluated by Cox regression analysis. Subsequently, a prognostic model was constructed using m7GRGs with good prognostic values by Lasso regression analysis. Besides, the relationships between prognostic m7GRGs and immune infiltration, clinical features, cuproptosis-related genes, and antitumor drugs were investigated in patients with SARC. Finally, a ceRNA regulatory network based on m7GRGs was constructed. Results: The expression of ten m7GRGs was higher in the SARC group than in the control group. DEGs across groups with high and low m7GRGs expression were enriched for adhesion sites and cGMP-PKG. Besides, we constructed a prognostic model that consists of EIF4A1, EIF4G3, NCBP1, and WDR4 m7GRGs for predicting the survival likelihood of sarcoma patients. And the elevated expression of these four prognostic m7GRGs was substantially associated with poor prognosis and elevated expression in SARC cell lines. Moreover, we discovered that these four m7GRGs expressions were negatively correlated with CD4+ T cell levels, dendritic cell level and tumor purity, and positively correlated with tumor mutational burden, microsatellite instability, drug sensitivity and cuproptosis-related genes in patients with sarcomas. Then, a triple regulatory network of mRNA, miRNA, and lncRNA was established. Conclusion: The current study identified EIF4A1, EIF4G3, NCBP1, andWDR4 as prognostic genes forSARC that are associatedwithm7G. These findings extend our knowledge of m7G methylation in SARC and may guide the development of innovative treatment options. [ABSTRACT FROM AUTHOR]

Background: N7-methylguanosine (m7G) is present in a wide variety of organisms and has important roles. m7G has been reported to be involved in multiple biological processes, and recent studies have reported that changes in RNA modifications result in tumor cellular transformation and cancer, such as colon adenocarcinoma, lung cancer, and intrahepatic cholangiocarcinoma. However, little is known about the function of the m7G in colon adenocarcinoma. Methods: We established two clusters based on the expression of all genes associated with m7G to explore the expression pattern of 31 key regulatory factors of m7G RNA and assess the prognostic value of regulatory factors. Wilcoxon test and differential box line plots were applied for bioinformatics analysis. Receiver Operating and Kaplan‒Meier curves were utilized to evaluate the prognostic value. Finally, four genes' expression in the colon cancer cell line was confirmed by qRT-PCR. Results: From The Cancer Genome Atlas database, we found that the expression levels of 25 out of the 31 key N7-methylguanosine RNA modification regulators were significantly different in colon adenocarcinoma. According to 25 methylation regulators' expression, we identified two subgroups by consensus clustering, in which the prognosis was worse in Group 2 than in Group 1 and was significantly correlated with age. Cluster 2 was significantly enriched in tumor-associated pathways, and immune cells were highly infiltrated in Cluster 1 but weakly infiltrated in Cluster 2. Further results indicated that this risk profile may serve as a standalone predictive factor for colon adenocarcinoma, and the four genetic risk profiles' prognostic relatedness was successfully verified through Gene Expression Omnibus dataset. At last, A nomogram for prognosis was created according to age, sex, histological grading, clinicopathological staging, and hazard score to accurately predict patient prognosis in colon adenocarcinoma. We successfully validated the differential expression of four genes using qRT-PCR. Conclusions: In the present study, we revealed the important contribution of key regulators associated with m7G RNA modifications based on all gene expression in colon adenocarcinoma and developed a signature of risk that serves as a promising prognostic marker for patients with colon adenocarcinoma. [ABSTRACT FROM AUTHOR]

Various kinds of cap structures, such as m7G, triphosphate groups, NAD and dpCoA, protect the 5′ terminus of RNA. The cap structures bond covalently to RNA and affect its stability, translation, and transport. The removal of the caps is mainly executed by Nudix hydrolase family proteins, including Dcp2, RppH and NudC. Numerous efforts have been made to elucidate the mechanism underlying the removal of m7G, triphosphate group, and NAD caps. In contrast, few studies related to the cleavage of the RNA dpCoA cap have been conducted. Here, we report the hydrolytic activity of Escherichia coli NudC towards dpCoA and dpCoA-capped RNA in vitro. We also determined the crystal structure of dimeric NudC in complex with dpCoA at 2.0 Å resolution. Structural analysis revealed that dpCoA is recognized and hydrolysed in a manner similar to NAD. In addition, NudC may also remove other dinucleotide derivative caps of RNA, which comprise the AMP moieties. NudC homologs in Saccharomyces cerevisiae and Arabidopsis thaliana exhibited similar dpCoA decapping (deCoAping) activity. These results together indicate a conserved mechanism underpinning the hydrolysis of dpCoA-capped RNA in both prokaryotes and eukaryotes. [ABSTRACT FROM AUTHOR]

Updates in whole genome sequencing technologies have revealed various RNA modifications in cancer, among which RNA methylation is a frequent posttranscriptional modification. RNA methylation is essential for regulating biological processes such as RNA transcription, splicing, structure, stability, and translation. Its dysfunction is strongly associated with the development of human malignancies. Research advances with respect to the regulatory role of RNA modifications in ovarian cancer include N6-methyladenosine (m6A), 5-methylcytosine (m5C), N1-methyladenosine (m1A), and N7-methylguanosine (m7G). Numerous studies have demonstrated that epigenetic modifications of RNA can influence the progression and metastasis of ovarian cancer and may provide excellent targets for cancer therapy. This review highlights advances in research on RNA methylation modifications and ovarian cancer prognosis, carcinogenesis, and resistance, which could provide a theoretical foundation for designing therapeutic strategies for ovarian cancer based on RNA methylation modifications. [ABSTRACT FROM AUTHOR]

Background: N7-Methylguanosine (m7G) and long non-coding RNAs (lncRNAs) have been widely studied in cancer and have been found to be useful for assessing tumor progression. However, the role of m7G-related lncRNAs in lung squamous cell carcinoma (LUSC) remains unclear. Thus, it is crucial to identify m7G-associated lncRNAs with definitive prognostic value. This study aimed to investigate the prognostic value, correlation with tumor mutation burden, and impact on the tumor immune microenvironment of m7G-related lncRNAs in LUSC.  METHODS: LUSC transcriptome data and clinical data were downloaded from The Cancer Genome Atlas, and an m7G-related lncRNA-mRNA co-expression network was constructed using Pearson's correlation analysis. Cox regression analyses were used to determine a risk model for m7G-associated lncRNAs with prognostic value. The risk signature was verified using the Kaplan-Meier method, receiver operating characteristic curve analysis, and principal component analysis. A nomogram based on risk scores and clinical characteristics was then developed. Gene set enrichment analysis was used for functional annotation to analyze the risk signature. The association among the risk signature, tumor mutational burden, and tumor-infiltrating immune cells was then analyzed. RT-qPCR was used to investigate the expression of 6 m7G-related lncRNAs in LUSC cells. The cytological function of SRP14-AS1 was verified by wound-healing assay and transwell assay.Results: A total of 293 m7G-related lncRNAs were identifed, 27 candidate m7G-related lncRNAs were signifcantly associated with overall survival (OS). Six of these lncRNAs (CYP4F26P, LINC02178, MIR22HG, SRP14-AS1, TMEM99, PTCSC2) were selected for establishment of the risk model. The OS of patients in the low-risk group was higher than that of patients in the high-risk group (p < 0.001). Multivariate cox regression analysis indicated that the model could be an independent prognostic factor for LUSC (HR = 1.859; 95% CI 1.452-2.380, p < 0.001). The ROC curve analysis revealed that the AUCs for OS in the 3-, and 5-year were 0.682, 0.657, respectively. GSEA analysis revealed that the risk model was closely related to immune-related pathways. Compared with normal lung epithelial cells, four m7G-related lncRNAs were higher expressed in cancer cells and two were lower expressed, among which knockdown of SRP14-AS1 promoted the proliferation and migration of LUSC cells.Conclusion: A risk model based on six m7G-related lncRNAs with prognostic value may be a promising prognostic tool in LUSC and guide individualized patient treatment. [ABSTRACT FROM AUTHOR]

Background: Pancreatic adenocarcinoma (PAAD) is a malignant tumor with a high mortality rate. Methylation modifications acted a crucial role to affect cancer progression. The current study aimed to explore the potential role of methylase regulators in PAAD prognosis and immune microenvironment. Methods: PubMed and TCGA databases were used to systematically analyze methylase regulators in PAAD. We identified three methylase clusters based on RNA methylase transcriptome data and obtained three gene clusters based on methylase modification-related differently expressed genes using principal component analysis (PCA) analysis. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and Gene Ontology (GO) biological processes were performed to explore the processes enriched in the different subgroups and single sample gene-set enrichment analysis (ssGSEA) was used to analyze the relationship between subgroups and immune infiltration in PAAD. Results: We systematically screened 43 methylase regulators in PAAD samples and identified three methylase clusters with different clinical outcomes, as well as detected a significant relationship between methylase clusters and tumor immune infiltration. The top ten mutated genes include TP53, Kirsten rat sarcoma viral oncogene homolog (KRAS), titin gene (TTN), mucin 16 (MUC16), SMAD4, cyclin-dependent kinase inhibitor 2a (CDKN2A), Ryanodine receptor isoform-1 (RYR1), ring finger 43 (RNF43), protocadherin-15 (PCDH15), and AT-rich interacting domain-containing protein 1 A gene (ARID1A). Conclusion: The current study constructed an m6A/m5C/m1A/m7G modulator genes and explored methylase modification-related genes, which were related to the prognosis of PAAD patients and the immune checkpoint point cytotoxic T-lymphocyte associated protein 4 (CTLA4). These findings may provide prognostic predictors and direction for immunotherapy strategies for the treatment of PAAD.

BackgroundM7G methylation modification plays an important role in cardiovascular disease development. Dysregulation of the immune microenvironment is closely related to the pathogenesis of PAH. However, it is unclear whether m7G methylation is involved in the progress of PAH by affecting the immune microenvironment.MethodsThe gene expression profile of PAH was obtained from the GEO database, and the m7G regulatory factors were analyzed for differences. Machine learning algorithms were used to screen characteristic genes, including the least absolute shrinkage and selection operator, random forest, and support vector machine recursive feature elimination analysis. Constructed a nomogram model, and receiver operating characteristic was used to evaluate the diagnosis of disease characteristic genes value. Next, we used an unsupervised clustering method to perform consistent clustering analysis on m7G differential genes. Used the ssGSEA algorithm to estimate the relationship between the m7G regulator in PAH and immune cell infiltration and analyze the correlation with disease-characteristic genes. Finally, the listed drugs were evaluated through the screened signature genes.ResultsWe identified 15 kinds of m7G differential genes. CYFIP1, EIF4E, and IFIT5 were identified as signature genes by the machine learning algorithm. Meanwhile, two m7G molecular subtypes were identified by consensus clustering (cluster A/B). In addition, immune cell infiltration analysis showed that activated CD4 T cells, regulatory T cells, and type 2 T helper cells were upregulated in m7G cluster B, CD56 dim natural killer cells, MDSC, and monocyte were upregulated in the m7G cluster A. It might be helpful to select Calpain inhibitor I and Everolimus for the treatment of PAH.ConclusionOur study identified CYFIP1, EIF4E, and IFIT5 as novel diagnostic biomarkers in PAH. Furthermore, their association with immune cell infiltration may facilitate the development of immune therapy in PAH.

Colon adenocarcinoma (COAD) is a prevalent malignant tumor that severely threatens human health across the globe. Immunotherapy is an essential need for patients with COAD. N7-methylguanosine (m7G) has been associated with human diseases, and non-coding RNAs (lncRNAs) regulate various tumorrelated biological processes. Nonetheless, the m7G-related lncRNAs involved in COAD regulation are limited. This study aims to construct the clustering features and prognostic model of m7G-related lncRNAs in COAD. First, The Cancer Genome Atlas (TCGA) database was used to identify m7G-related differentially expressed lncRNAs (DELs), based on which COAD cases could be classified into two subtypes. Subsequently, univariate Cox analysis was used to identify 9 prognostic m7G-related lncRNAs. Further, Five candidates were screened by LASSO-Cox regression to develop new models. The patients were divided into high-risk and low-risk groups based on the median risk score. Consequently, the Kaplan-Meier survival curve demonstrated a statistically significant overall survival (OS) between the high- and low-risk groups (P<0.001). Multivariate Cox regression analysis revealed that risk score is an independent prognostic factor in COAD patients (P<0.001). This confirms the clinical applicability of the model. Additionally, we performed Gene Set Enrichment Analysis (GSEA), which uncovered the biological and functional differences between risk subgroups, i.e., enrichment of immune-related diseases in the high-risk group and enrichment of metabolic-related pathways in the low-risk group. In a drug sensitivity analysis, high-risk group were more sensitive to some chemotherapeutics and targeted drugs than lowrisk group. Eventually, the stability of the model was confirmed by qRT-PCR. Our study unraveled the features of different immune states of COAD and established a prognostic model, including five m7G-related lncRNAs for COAD patients. These results will bolster clinical treatment and survival prediction of COAD. [ABSTRACT FROM AUTHOR]

Background: RNA methylation modification plays an important role in immune regulation. m7G RNA methylation is an emerging research hotspot in the RNA methylation field. However, its role in the tumor immune microenvironment of kidney renal clear cell carcinoma (KIRC) is still unclear. Methods: We analyzed the expression profiles of 29 m7G regulators in KIRC, integrated multiple datasets to identify a novel m7G regulator-mediated molecular subtype, and developed the m7G score. We evaluated the immune tumor microenvironments in m7G clusters and analyzed the correlation of the m7G score with immune cells and drug sensitivity. We tested the predictive power of the m7G score for prognosis of patients with KIRC and verified the predictive accuracy of the m7G score by using the GSE40912 and E-MTAB-1980 datasets. The genes used to develop the m7G score were verified by qRT-PCR. Finally, we experimentally analyzed the effects of WDR4 knockdown on KIRC proliferation, migration, invasion, and drug sensitivity. Results: We identified three m7G clusters. The expression of m7G regulators was higher in cluster C than in other clusters. m7G cluster C was related to immune activation, low tumor purity, good prognosis, and low m7G score. Cluster B was related to drug metabolism, high tumor purity, poor survival, and high m7G score. Cluster A was related to purine metabolism. The m7G score can well-predict the prognosis of patients with KIRC, and its prediction accuracy based on the m7G score nomogram was very high. Patients with high m7G scores were more sensitive to rapamycin, gefitinib, sunitinib, and vinblastine than other patients. Knocking down WDR4 can inhibit the proliferation, migration, and invasion of 786-0 and Caki-1 cells and increase sensitivity to sorafenib and sunitinib. Conclusion: We proposed a novel molecular subtype related to m7G modification and revealed the immune cell infiltration characteristics of different subtypes. The developed m7G score can well-predict the prognosis of patients with KIRC, and our research provides a basis for personalized treatment of patients with KIRC. [ABSTRACT FROM AUTHOR]

N7-methylguanosine (m7G) modification on internal RNA positions plays a vital role in several biological processes. Recent research showsm7G modification is associated with multiple cancers. However, in hepatocellular carcinoma (HCC), its implications remain to be determined. In this place, we need to interrogate the mRNA patterns for 29 key regulators of m7G RNA modification and assess their prognostic value in HCC. Initial, the details from The Cancer Genome Atlas (TCGA) database concerning transcribed gene data and clinical information of HCC patients were inspected systematically. Second, according to the mRNA profiles of 29 m7G RNA methylation regulators, two clusters (named 1 and 2, respectively) were identified by consensus clustering. Furthermore, robust risk signature for sevenm7G RNA modification regulators was constructed. Last, we used the Gene Expression Omnibus (GEO) dataset to validate the prognostic associations of the seven-gene risk signature. We figured out that 24/29 key regulators of m7G RNA modification varied remarkably in their grades of expression between the HCC and the adjacent tumor control tissues. Cluster one compared with cluster two had a substandard prognosis and was also positively correlated with T classification (T), pathological stage, and vital status (fustat) significantly. Consensus clustering results suggested the expression pattern of m7G RNA modification regulators was correlated with the malignancy of HCC strongly. In addition, cluster one was extensively enriched in metabolic-related pathways. Seven optimal genes (METTL1, WDR4, NSUN2, EIF4E, EIF4E2, NCBP1, and NCBP2) were selected to establish the risk model for HCC. Indicating by further analyses and validation, the prognostic model has fine anticipating command and this probability signature might be a self supporting presage factor for HCC. Finally, a new prognostic nomogram based on age, gender, pathological stage, histological grade, and prospects were established to forecast the prognosis of HCC patients accurately. In essence, we detected association of HCC severity and expression levels of m7G RNA modification regulators, and developed a risk score model for predicting prognosis of HCC patients' progression. [ABSTRACT FROM AUTHOR]

Hepatocellular carcinoma (HCC) is a highly mortal type of primary liver cancer. Abnormal epigenetic modifications are present in HCC, and RNA modification is dynamic and reversible and is a key post-transcriptional regulator. With the indepth study of post-transcriptional modifications, RNA modifications are aberrantly expressed in human cancers. Moreover, the regulators of RNA modifications can be used as potential targets for cancer therapy. In RNA modifications, N6-methyladenosine (m6A), N7-methylguanosine (m7G), and 5-methylcytosine (m5C) and their regulators have important regulatory roles in HCC progression and represent potential novel biomarkers for the confirmation of diagnosis and treatment of HCC. This review focuses on RNA modifications in HCC and the roles and mechanisms of m6A, m7G, m5C, N1-methyladenosine (m1A), N3-methylcytosine (m3C), and pseudouridine (ψ) on its development and maintenance. The potential therapeutic strategies of RNA modifications are elaborated for HCC. [ABSTRACT FROM AUTHOR]

Background: 7-Methylguanosine (m7G) is an important posttranscriptional modification that regulates gene expression and is involved in tumorigenesis and development. Tumor microenvironment has been proven to be highly involved in tumor progression and prognosis. However, how m7G-associated genes affect the tumor microenvironment of patients with lung adenocarcinoma (LUAD) remains to be further clarified. Methods: The genetic alterations of m7G-associated genes and their associations with the prognosis and tumor microenvironment in LUAD patients were systemically analyzed. An m7G-Riskscore was established and analyzed for its performance in disease prognosis and association with patient response to immunotherapy. Expression of the model genes at the protein level was investigated through ex vivo experiments. A nomogram was finally obtained based on the m7G-Riskscore and several significant clinical pathological features. Results: m7G-Associated genes were obtained from five LUAD datasets from The Cancer Genome Atlas and Gene Expression Omnibus databases, and their expression pattern was determined. Based on the m7G-associated genes, three LUAD clusters were defined. The differentially expressed genes from the three clusters were screened and used to further divide the LUAD patients into two gene clusters. It was demonstrated that the alterations of m7G-associated genes were associated with the clinical pathological features, prognosis, and tumor immune infiltration in LUAD patients. An m7G-Riskscore including CAND1, RRM2, and SLC2A1 was obtained with robust and accurate prognostic performance. WB and cell immunofluorescence also showed significant dysregulation of CAND1, RRM2, and SLC2A1 in LUAD. In addition, a nomogram was established to improve the clinical feasibility of the m7GRiskscore. Correlation analysis revealed that patients with a lower m7GRiskscore had higher immune and stromal scores, responded well to chemotherapeutics and multiple targeted drugs, and survived longer. Patients with a higher m7G-Riskscore tended to suffer from a higher tumor mutation burden. Furthermore, the m7G-Riskscore exhibited significant associations with immune cell infiltration and cancer stemness. Conclusion: This study systemically analyzed m7G-associated genes and identified their potential role in tumor microenvironment and prognosis in patients with LUAD. The findings of the present study may help better understand LUAD from the m7G perspective and also provide a new thought toward the prognosis and treatment of LUAD. [ABSTRACT FROM AUTHOR]

Clear cell renal cell carcinoma (ccRCC) is one of the most common tumors in the urinary system. ccRCC has obvious immunological characteristics, and the infiltration of immune cells is related to the prognosis of ccRCC. The effect of immune checkpoint therapy is related to the dynamic changes of the tumor immune microenvironment (TIM). The 7-methylguanosine (m7G) is an additional mRNA modification ability besides m6A, which is closely related to the TIM and affects the occurrence and development of tumors. At present, the correlations between m7G and the immune microenvironment, treatment, and prognosis of ccRCC are not clear. As far as we know, there was no study on the relationship between m7G and the immune microenvironment and survival of clear cell renal cell carcinomas. A comprehensive analysis of the correlations between them and the construction of a prognosis model are helpful to improve the treatment strategy. Two different molecular subtypes were identified in 539 ccRCC samples by describing the differences of 29 m7G-related genes. It was found that the clinical features, TIM, and prognosis of ccRCC patients were correlated with the m7G-related genes. We found that there were significant differences in the expression of PD-1, CTLA4, and PD-L1 between high- and low-risk groups. To sum up, m7G-related genes play a potential role in the TIM, treatment, and prognosis of ccRCC. Our results provide new findings for ccRCC and help to improve the immunotherapy strategies and prognosis of patients. [ABSTRACT FROM AUTHOR]

RNA guanine-7 methyltransferase (RNMT), in complex with FAM103A1, plays an important role in tumorigenesis and development. The aim of this study was to establish a prognostic model of RNMT and FAM103A1-based upstream microRNAs and explore its correlation with immune cell infiltration in breast cancer (BC) while investigating its potential prognostic value and verify the model by quantitative real time polymerase chain reaction(qRT-PCR). ThemiRNA expression data upstream of the m7G methyltransferase complex RNMT/FAM103A1 in BC was obtained from The Cancer Genome Atlas and Target Scan databases. We performed univariate Cox regression, LASSO regression, Kaplan-Meier survival, and principal component analyses, along with risk prognostic modelling. Based on multivariate Cox regression analysis, a total of 12 m7G methyltransferase-related miRNAs were found. The model showed good accuracy for predicting the 1-, 3-,5-, and 10- year survival rates, and the areas under the curve were almost >0.7. To characterize the risk-level model constructed from 12miRNAs, 12 differentially expressed mRNAs related to prognosis and immune infiltration were obtained. The prognosis of BC patients is well predicted by the risk model we constructed. This model is also closely related to immune infiltration, and new immunotherapy targets can be explored from this field. [ABSTRACT FROM AUTHOR]

Background: About170 chemical modifications to RNAs have been identified, which significantly affect gene expression. Dysregulation of RNA modifications induced by abnormal expression or mutations in RNA modifiers might result in cancer. The most frequent RNA modifications are N6-methyladenosine (m6A), 5-methylcytosine (m5C), and N7-methylguanosine (m7G). Lung cancer is the leading cause of cancer-related deaths globally. The present study aimed to investigate whether the expression of the m7G-related genes is linked to lung cancer cases with lung adenocarcinoma (LUAD), which accounts for about 40% of lung cancer cases. Methods: A total of 12 m7G-related differentially expressed genes (DEGs) were identified in LUAD patients by The Cancer Genome Atlas (TCGA). The least absolute shrinkage and selection operator (LASSO) Cox regression method was used to build a four-gene risk model. Then, LUAD patients in the TCGA cohort were divided into low- and high-risk groups based on their risk scores for subsequent molecular and clinical research. Results: Compared to the low-risk group, the high-risk group had a decreased overall survival (OS) (P=0.047). The risk score and stage were independent factors for predicting the OS of LUAD (P=0.0004 and P<0.0001, respectively). Gene ontology and Kyoto Encyclopedia of Genes and Genomes analyses based on the two groups showed that the DEGs were metabolically and hormonally related. The high-risk group showed a higher mutation rate and lesser immune cell infiltration, especially in TP53, KRAS, and MET. The expression level of PDL1 and CTLA4 was high in the high-risk group (P<0.05). The high-risk group is more sensitive to anti-cancer therapy with lower IC50 and higher immunophenoscore (IPS). Conclusions: In this study, we developed a novel LUAD stratification model based on m7G-related genes that successfully predicts the prognosis of LUAD patients and serves as a guide for clinically personalized treatment. [ABSTRACT FROM AUTHOR]

With high morbidity and mortality, colon cancer (CC) is considered as one of the most often diagnosed cancers around the world. M7G-related lncRNA may provide a regulatory function in the formation of CC, but the principle of regulation is still unclear. The purpose of this research was to establish a novel signature that may be used to predict survival and tumour immunity in CC patients. Data about CC in TCGA was collected for analysis, coexpression analysis and univariate Cox analysis were used to screen prognostic m7G-related lncRNAs. A consensus clustering analysis based on prognostic m7G-related lncRNAs was applied, and a prognosis model based on least absolute shrinkage and selection operator (LASSO) regression analysis was established. Independent prognostic analysis, nomogram, PCA, clinicopathological correlation analysis, TMB, survival analysis, immune correlation analysis, qRT–PCR and clinical therapeutic compound prediction were also applied. 90 prognostic m7G-related lncRNAs were found, GO and KEGG analysis showed that prognostic m7G-related lncRNAs were mainly related to cell transcription and translation. The results of the consensus clustering analysis revealed substantial disparities in survival prognosis and tumour immune infiltration between two clusters. We built a risk model with 21 signature m7G-related lncRNAs, patients in the high-risk group had a considerably poorer prognosis than those in the low-risk group. Independent prognostic analysis confirmed that patients' prognosis was linked to their tumour stage and risk score. PCA, subgroups with distinct clinicopathological characteristics were studied for survival, multi-index ROC curve, c-index curve, the survival analysis of TMB, and model comparison tested the reliability of risk model. A tumour immunoassay revealed a substantial difference in immune infiltration between high-risk and low-risk individuals. Five chemicals were eliminated, and qRT–PCR indicated that the four lncRNAs were expressed differently. Overall, m7G-related lncRNA is closely related to colon cancer and the 21 signature lncRNAs risk model can efficiently evaluate the prognosis of CC patients, which has a possible positive consequence for the future diagnosis and therapy of CC. [ABSTRACT FROM AUTHOR]

Background: M7G modification is extremely vital for the development of many cancers, especially tumor immunity. M7G modification is a novel functional regulator of miRNA, and the researches on m7G-related miRNAs in kidney renal clear cell carcinoma (KIRC) are still insufficient. This research aims to establish a risk signature on the foundation of m7G-associated miRNAs, which can precisely forecast the prognosis of KIRC patients. Methods: Transcriptome data and clinical data used in this study come from The Cancer Genome Atlas database. Our team utilized univariable Cox, Lasso and multivariable Cox analyses to construct a m7G-associated miRNAs risk signature that can forecast the prognosis of KIRC patients. Kaplan-Meier method, time-dependent receiver operating characteristic (ROC) curve, and the independent analysis of risk signatures were employed to verify the predictability and accuracy of the risk signature. Subsequently, based on CIBERSORT, ESTIMATE and ssGSEA algorithms, we speculated the potential impact of the proposed risk signature on tumor immune microenvironment. Ultimately, by virtue of the risk signature and tumor immunity, the hub genes affecting the prognosis of KIRC patients were screened out. Results: Our team established and verified a prognostic signature comprising 7 m7G-associated miRNAs (miR-342-3p, miR-221-3p, miR-222-3p, miR-1277-3p, miR-6718-5p, miR-1251-5p, and miR-486-5p). The results of the Kaplan-Meier survival analysis revealed that the prognosis of KIRC sufferers in the high-risk group was often unsatisfactory. The accuracy of the prediction ability of the risk signature was verified by calculating the area under the ROC curve. Univariate-multivariate Cox analyses further showed that this risk signature could be utilized as an independent prognosis-related biomarker for KIRC sufferers. The results of the immune analysis revealed that remarkable diversities existed in immune status and tumor microenvironment between high-risk and low-risk groups. On the foundation of the proposed risk signature and other clinical factors, a nomogram was established to quantitatively forecast the survival of KIRC sufferers at 1, 3 and 5 years. Conclusion: Based on m7G-related miRNAs, a risk signature was successfully constructed, which could precisely forecast the prognosis of sufferers and guide personalized immunotherapy for KIRC patients. [ABSTRACT FROM AUTHOR]

Background: Idiopathic pulmonary fibrosis (IPF) is the interstitial lung disease with the highest incidence and mortality. The lack of specific markers results in limited treatment methods for IPF patients. Numerous prognostic signatures represented effective indexes in predicting the survival of patients in various diseases; however, little is investigated on their application in IPF. Methods: This study attempted to explore the clinical markers suitable for IPF by constructing a prognostic signature from the perspective of 7-methylguanosine (m7G). An m7G-related prognostic signature (m7GPS) was established based on the discovery cohort with the LASSO algorithm and was verified by internal and external validation cohorts. The area under the curve (AUC) values were utilized to assess the accuracy of m7GPS in predicting the prognosis of IPF patients and the ability of m7GPS in screening IPF patients. Kaplan-Meier curves and Cox regression analyses were used to identify the relationship of m7GPS with the prognosis of IPF individuals. Enrichment analyses, CIBERSORT algorithm, and weighted gene co-expression network analysis were applied to explore the underlying mechanisms and correlation of m7GPS in IPF. Results: The two m7G regulatory genes can divide IPF into subtypes 1 and 2, and subtype 2 demonstrated a poor prognosis for IPF patients (p < 0.05). For the first time in this field, the m7GPS was constructed. m7GPS made it feasible to predict the 1–5 years survival status of IPF patients (AUC = 0.730–0.971), and it was an independent prognostic risk factor for IPF patients (hazard ratio > 1, p < 0.05). The conspicuous ability of m7GPS to screen IPF patients from the healthy was also revealed by an AUC value of 0.960. The roles of m7GPS in IPF may link to inflammation, immune response, and immune cell levels. Seven genes (CYR61 , etc.) were identified as hub genes of m7GPS in IPF. Three drugs (ZM447439-1050, AZD1332-1463, and Ribociclib-1632) were considered sensitive to patients with high m7GPS risk scores. Conclusion: This study developed a novel m7GPS, which is a reliable indicator for predicting the survival status of IPF patients and is identified as an effective marker for prognosis and screening of IPF patients. [ABSTRACT FROM AUTHOR]

Lung cancer is a major cause of cancer-related deaths globally, with a dismal prognosis. N7-methylguanosine (m7G) is essential for the transcriptional phenotypic modification of messenger RNA (mRNA) and long noncoding RNA (lncRNA). However, research on m7G-related lncRNAs involved in lung adenocarcinoma (LUAD) regulation is still limited. Herein, we aim to establish a prognostic model of m7G-related lncRNAs and investigate their immune properties. Eight prognostic m7G-related lncRNAs were identified using univariate Cox analysis. Six m7G-related lncRNAs were identified using LASSO-Cox regression analysis to construct risk models, and all LUAD patients in The Cancer Genome Atlas (TCGA) cohort was divided into low-risk and high-risk subgroups. The accuracy of the model was verified by Kaplan-Meier analysis, time-dependent receiver operating characteristic, principal component analysis, independent prognostic analysis, nomogram, and calibration curve. Further studies were conducted on the gene set enrichment and disease ontology enrichment analyses. The gene set enrichment analysis (GSEA) revealed that the high-risk group enriched for cancer proliferation pathways, and the enrichment analysis of disease ontology (DO) revealed that lung disease was enriched, rationally explaining the superiority of the risk model. Finally, we found that the low-risk group had higher immune infiltration and checkpoint expression. It can be speculated that the low-risk group has a better effect on immunotherapy. Susceptibility to antitumor drugs in different risk subgroups was assessed, and it found that the high-risk group showed high sensitivity to first-line treatment drugs for non-small cell lung cancer. In conclusion, a risk model based on 6 m7G-related lncRNAs can not only predict the overall survival (OS) rate of LUAD patients but also guide individualized treatment for these patients. [ABSTRACT FROM AUTHOR]