Integrative pan-cancer analysis and clinical characterization of the N7-methylguanosine (m7G) RNA modification regulators in human cancers

He, Chong; Zhang, Xin-Di; Zhu, Song-Xin; Zheng, Jie; Wang, Yuming; Wang, Qing; Yin, Hang; Fu, Yujie; Song, Xue; Tang, Jian; Zhao, Xiaojing

doi:10.3389/fgene.2022.998147

Cited by 5 publications

(6 citation statements)

References 67 publications

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“…Studies have suggested that NUDT4 is signi cantly downregulated in various cancers, including KIRC[57][58][59] , , which matches our results. Research in other cancer types has also indicated that NUDT4 downregulation affects tumor cell proliferation by impacting the m7G gene[60].Research indicates that the absence of certain m7G-related regulatory factors is linked to disease.…”

supporting

confidence: 91%

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their prediction of immunotherapeutic efficacy

Zhong

Chen

Lin

et al. 2023

Preprint

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Background: Kidney renal clear cell carcinoma (KIRC) is a common malignant tumor of the urinary system. This study aims to develop new biomarkers for KIRC and explore the impact of biomarkers on the immunotherapeutic efficacy for KIRC, providing a theoretical basis for the treatment of KIRC patients. Methods: Transcriptome data for KIRC was obtained from the The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) databases. Weighted gene co-expression network analysis identified KIRC-related modules of long noncoding RNAs (lncRNAs). Intersection analysis was performed differentially expressed lncRNAs between KIRC and normal control samples, and lncRNAs associated with N(7)-methylguanosine (m7G), resulting in differentially expressed m7G-associated lncRNAs in KIRC patients (DE-m7G-lncRNAs). Machine Learning was employed to select biomarkers for KIRC. The prognostic value of biomarkers and clinical features was evaluated using Kaplan-Meier (K-M) survival analysis, univariate and multivariate Cox regression analysis. A nomogram was constructed based on biomarkers and clinical features, and its efficacy was evaluated using calibration curves and decision curves. Functional enrichment analysis was performed to investigate the functional enrichment of biomarkers. Correlation analysis was conducted to explore the relationship between biomarkers and immune cell infiltration levels and common immune checkpoint in KIRC samples. Results: By intersecting 575 KIRC-related module lncRNAs, 1773 differentially expressed lncRNAs, and 62 m7G-related lncRNAs, we identified 42 DE-m7G-lncRNAs. Using XGBoost and Boruta algorithms, 8 biomarkers for KIRC were selected. Kaplan-Meier survival analysis showed significant survival differences in KIRC patients with high and low expression of the PTCSC3 and RP11-321G12.1. Univariate and multivariate Cox regression analyses showed that AP000696.2, PTCSC3 and clinical characteristics were independent prognostic factors for patients with KIRC. A nomogram based on these prognostic factors accurately predicted the prognosis of KIRC patients. The biomarkers showed associations with clinical features of KIRC patients, mainly localized in the cytoplasm and related to cytokine-mediated immune response. Furthermore, immune feature analysis demonstrated a significant decrease in immune cell infiltration levels in KIRC samples compared to normal samples, with a negative correlation observed between the biomarkers and most differentially infiltrating immune cells and common immune checkpoints. Conclusion: In summary, this study discovered eight prognostic biomarkers associated with KIRC patients. These biomarkers showed significant correlations with clinical features, immune cell infiltration, and immune checkpoint expression in KIRC patients, laying a theoretical foundation for the diagnosis and treatment of KIRC.

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supporting

confidence: 91%

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their prediction of immunotherapeutic efficacy

Zhong

Chen

Lin

et al. 2023

Preprint

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“…The association between UPB1 levels and survival outcomes across all cancer types was determined using the Kaplan-Meier plot (http://kmplot.com/analysis/) based on hazard ratios and log-rank P values. Cox univariate regression analysis was used to determine overall survival (OS), disease-specific survival (DSS), disease-free interval, and progression-free interval (PFI) in all cancer samples using the R package “survivalROC.” A P -value of <0.05 was considered to indicate statistical significance, as previously described 18–20 …”

Section: Methodsmentioning

confidence: 99%

“…A P-value of <0.05 was considered to indicate statistical significance, as previously described. [18][19][20] Tumor Immune Estimation Resource (TIMER2.0) Database TIMER2.0 was used to examine the association between UPB1 levels and tumor-infiltrating lymphocytes (TILs) across multiple cancer types based on gene modules. 21 In addition, the association between UPB1 levels and TIL markers, such as CD8 + /CD4 + T cells, B cells, and other related subtypes, was evaluated using correlation modules.…”

Section: Kaplan-meier Plot Analysismentioning

confidence: 99%

Low UPB1 Level Correlates With Poor Prognosis in Lung Adenocarcinoma

Zhang,

Liu,

Wang

et al. 2023

Applied Immunohistochemistry &Amp; Molecular Morphology

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Objectives: Lung adenocarcinoma (LUAD) is a critical cancer with high mortality, worse prognosis, and crucial lymphatic metastasis. Consequently, prognostic biomarkers for LUAD are truly required. β-Ureidopropionase (UPB1) is abnormally expressed in various cancers. However, the function of UPB1 in LUAD is still ambiguous. This study aimed to explore the expression profile and prognostic significance of UPB1 in LUAD. Materials and Methods: The differential UPB1 levels in pan cancers and their prognostic significance were comprehensively investigated through Gene Expression Profiling Interactive Analysis, UALCAN, Tumor Immune Estimation Resource, and Kaplan-Meier plotter platform. The correlation between UPB1 and tumor infiltration immune cells was explored using Tumor Immune Estimation Resource, Gene Expression Profiling Interactive Analysis, and Tumor-Immune System Interactions and Drug Bank database databases. Results: The UPB1 level was abnormally expressed in pan-tumor tissue than in adjacent tissue from The Cancer Genome Atlas tool. Low UPB1 level was correlated with poor overall survival in patients with LUAD. Furthermore, a comparison of the various pathologic characteristics of LUAD between high and low UPB1 level subgroups revealed that low UPB1 expression was correlated with lymph node metastasis. Kaplan-Meier survival analysis indicated that a low UPB1 level was associated with worse progression‑free survival and overall survival in patients with LUAD. Univariate and multivariate analyses suggested that UPB1 could be a useful prognostic indicator for LUAD. Abnormal UPB1 may be correlated with aberrant LUAD immune infiltration, prompting a worse survival outcome. Conclusions: Results showed that low UPB1 is correlated with a worse prognosis of LUAD and may be a valuable prognostic indicator for LUAD.

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“…A study by Han et al demonstrated that m7G tRNA modification drives tumorigenesis through regulating the RPTOR/ULK1/autophagy axis in esophageal squamous cell carcinoma. 12 Recent reports have shown that m7G provides new clues to the clarification of the molecular mechanism of liver cancer and may guide new treatment strategies. 13 Dai et al found that significantly increased m7G tRNA modification and its methyltransferase complex component WDR4 are associated with a poor prognosis of intrahepatic cholangiocarcinoma because they promote carcinogenic mRNA translation and cancer progression.…”

Section: Introductionmentioning

confidence: 99%

“…Great progress has been made in studying the regulation of m7G in cancer. A study by Han et al demonstrated that m7G tRNA modification drives tumorigenesis through regulating the RPTOR/ULK1/autophagy axis in esophageal squamous cell carcinoma 12 . Recent reports have shown that m7G provides new clues to the clarification of the molecular mechanism of liver cancer and may guide new treatment strategies 13 .…”

Section: Introductionmentioning

confidence: 99%

Three molecular subtypes and a five‐gene signature for hepatocellular carcinoma based on m7G‐related classification

Yue,

Tao,

et al. 2023

The Journal of Gene Medicine

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BackgroundThe current research investigated the heterogeneity of hepatocellular carcinoma (HCC) based on the expression of N7‐methylguanosine (m7G)‐related genes as a classification model and developed a risk model predictive of HCC prognosis, key pathological behaviors and molecular events of HCC.MethodsThe RNA sequencing data of HCC were extracted from The Cancer Genome Atlas (TCGA)‐live cancer (LIHC) database, hepatocellular carcinoman database (HCCDB) and Gene Expression Omnibus database, respectively. According to the expression level of 29 m7G‐related genes, a consensus clustering analysis was conducted. The least absolute shrinkage and selection operator (LASSO) regression analysis and COX regression algorithm were applied to create a risk prediction model based on normalized expression of five characteristic genes weighted by coefficients. Tumor microenvironment (TME) analysis was performed using the MCP‐Counter, TIMER, CIBERSORT and ESTIMATE algorithms. The Tumor Immune Dysfunction and Exclusion algorithm was applied to assess the responses to immunotherapy in different clusters and risk groups. In addition, patient sensitivity to common chemotherapeutic drugs was determined by the biochemical half‐maximal inhibitory concentration using the R package pRRophetic.ResultsThree molecular subtypes of HCC were defined based on the expression level of m7G‐associated genes, each of which had its specific survival rate, genomic variation status, TME status and immunotherapy response. In addition, drug sensitivity analysis showed that the C1 subtype was more sensitive to a number of conventional oncolytic drugs (including paclitaxel, imatinib, CGP‐082996, pyrimethamine, salubrinal and vinorelbine). The current five‐gene risk prediction model accurately predicted HCC prognosis and revealed the degree of somatic mutations, immune microenvironment status and specific biological events.ConclusionIn this study, three heterogeneous molecular subtypes of HCC were defined based on m7G‐related genes as a classification model, and a five‐gene risk prediction model was created for predicting HCC prognosis, providing a potential assessment tool for understanding the genomic variation, immune microenvironment status and key pathological mechanisms during HCC development.

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Integrative pan-cancer analysis and clinical characterization of the N7-methylguanosine (m7G) RNA modification regulators in human cancers

Cited by 5 publications

References 67 publications

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their prediction of immunotherapeutic efficacy

Selection of M7G-related lncRNAs in kidney renal clear cell carcinoma and their prediction of immunotherapeutic efficacy

Low UPB1 Level Correlates With Poor Prognosis in Lung Adenocarcinoma

Three molecular subtypes and a five‐gene signature for hepatocellular carcinoma based on m7G‐related classification

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