A m1A- , m5C- , m6A-  and m7G- regulators-related lncRNA signature as a prognostic and immune-infiltrated model for lung adenocarcinoma

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer worldwide. Many patients still do not benefit from multitargeted antitumor therapy, even in combination with immunotherapy. m6A-/m1A-/m5C/-m7G- regulators are the major forms of RNA methylation (RM) modification. development is closely related. This study summarizes 64 m6A-/m1A-/m5C/-m7G regulators. Based on the transcriptomic data and clinical information of LUAD in the Cancer Genome Atlas (TCGA), the role of prognosis RNA methylation modification-regulated lncRNAs(RM-lncRNAs) in LUAD and microenvironment was explored. To identify RM-lncRNAs and how they affect survival and prognosis in LUAD, we constructed signatures of RM-lncRNAs by univariate and multivariate regression and least absolute shrinkage and selection operator (LASSO) analysis. Penalized regression was used to screen and establish a prognostic model closely related to the subgroup of clinical variables and the degree of immune cell infiltration, and the risk score of each sample was calculated independently. Using Kaplan-Meier (K-M) analysis, gene enrichment analysis and multi-pathway clinical correlation analysis, the clinical significance and potential mechanism of action of the prognostic model were elucidated, including PLUT, AC091133.4, AC079949.2, and AC068338.3. At the same time, the high mutation frequency genes significantly associated with high risk in the prognostic model were further analyzed in combination with the incidence of somatic mutation of TCGA-LUAD. The risk score and consensus clustering generated by this prognostic model can effectively predict the clinical outcome and immune microenvironment infiltration characteristics of LUAD patients from multiple approaches and multiple methods. The above comprehensive data support the potential clinical application value of our constructed RM-lncRNA signature in the prognosis and immune infiltration status of LUAD. The purpose and originality of this study lies in revealing the potential link between RM modification patterns and LUAD and treatment response by constructing the LUAD prognostic model of RM-lncRNAs. This novel RM-lncRNA prognostic model can be used to assess the prognosis and sensitivity of infiltrating immune cells modulated by immunotherapy in patients with LUAD.

Authors

Publication Details

Journal
Journal of computational genomics and biology
Published
2025-05-16
DOI
https://doi.org/10.59995/j2bdqx49
Citations
1
Primary Topic
RNA modifications and cancer
Type
article
Field-Weighted Citation Impact
0.81

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article

A m1A- , m5C- , m6A-  and m7G- regulators-related lncRNA signature as a prognostic and immune-infiltrated model for lung adenocarcinoma

Er‐Dong Zuo, Shan Li, Xu Cheng, Lian Lian
1 citations
Journal of computational genomics and biology
RNA modifications and cancer
0.81
article

A m1A- , m5C- , m6A-  and m7G- regulators-related lncRNA signature as a prognostic and immune-infiltrated model for lung adenocarcinoma

Er‐Dong Zuo, Shan Li, Xu Cheng, Lian Lian
article en
1 citations

Abstract

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer worldwide. Many patients still do not benefit from multitargeted antitumor therapy, even in combination with immunotherapy. m6A-/m1A-/m5C/-m7G- regulators are the major forms of RNA methylation (RM) modification. development is closely related. This study summarizes 64 m6A-/m1A-/m5C/-m7G regulators. Based on the transcriptomic data and clinical information of LUAD in the Cancer Genome Atlas (TCGA), the role of prognosis RNA methylation modification-regulated lncRNAs(RM-lncRNAs) in LUAD and microenvironment was explored. To identify RM-lncRNAs and how they affect survival and prognosis in LUAD, we constructed signatures of RM-lncRNAs by univariate and multivariate regression and least absolute shrinkage and selection operator (LASSO) analysis. Penalized regression was used to screen and establish a prognostic model closely related to the subgroup of clinical variables and the degree of immune cell infiltration, and the risk score of each sample was calculated independently. Using Kaplan-Meier (K-M) analysis, gene enrichment analysis and multi-pathway clinical correlation analysis, the clinical significance and potential mechanism of action of the prognostic model were elucidated, including PLUT, AC091133.4, AC079949.2, and AC068338.3. At the same time, the high mutation frequency genes significantly associated with high risk in the prognostic model were further analyzed in combination with the incidence of somatic mutation of TCGA-LUAD. The risk score and consensus clustering generated by this prognostic model can effectively predict the clinical outcome and immune microenvironment infiltration characteristics of LUAD patients from multiple approaches and multiple methods. The above comprehensive data support the potential clinical application value of our constructed RM-lncRNA signature in the prognosis and immune infiltration status of LUAD. The purpose and originality of this study lies in revealing the potential link between RM modification patterns and LUAD and treatment response by constructing the LUAD prognostic model of RM-lncRNAs. This novel RM-lncRNA prognostic model can be used to assess the prognosis and sensitivity of infiltrating immune cells modulated by immunotherapy in patients with LUAD.

Journal of computational genomics and biologyVol. 2(1)
Government of Jiangsu Province, Junta de Castilla y León
Openalex Percentile: Top 28%
RNA modifications and cancer
0.81
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