Dataset Information

A noval prognostic signature of the N7-methylguanosine (m7G)-related miRNA in lung adenocarcinoma.

ABSTRACT:

Background

Lung adenocarcinoma (LUAD) is characterized by high morbidity and mortality rates and poor prognosis. N7-methylguanosine play an increasingly vital role in lung adenocarcinoma. However, the prognostic value of N7-methylguanosine related-miRNAs in lung adenocarcinoma remains unclear.

Methods

In the study, the mRNA and miRNA expression profiles and corresponding clinical informations were downloaded from the public database. The prognostic signature was built using least absolute shrinkage and selection operator Cox analysis. The Kaplan-Meier method was used to compare survival outcomes between the high- and low-risk groups. Signatures for the development of lung adenocarcinoma were tested using univariate and multivariate Cox regression models. Single-sample gene set enrichment analysis was used to determine the immune cell infiltration score. First, we predicted METTL1 and WDR4 chemosensitivities based on a public pharmacogenomics database. The area under the receiver operating characteristic curve showed that the performance of signature in 1-,3-, and 5-year survival predictions were 0.68, 0.65, and 0.683, respectively.

Results

We established a novel prognostic signature consisting of 9 N7-Methylguanosine related miRNAs using least absolute shrinkage and selection operator Cox analysis. Patients in the high-risk group had shorter survival times than those in the low-risk group did. The calibration curves at 1, 3, and 5-year also illustrate the high predictive power of the structure. Signature was corrected using the Toumor stage. The expression levels of METTL1 and WDR4 significantly correlated with the sensitivity of cancer cells to antitumor drugs.

Conclusions

A novel signature constructed using 9 N7-methylguanosine related-miRNAs can be used for prognostic prediction.

SUBMITTER: Duan HP

PROVIDER: S-EPMC9838007 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

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Publications

A noval prognostic signature of the N7-methylguanosine (m7G)-related miRNA in lung adenocarcinoma.

Duan Han-Ping HP Yan Jian-Hui JH Nie Lin L Wang Ye Y Xie Hui H

BMC pulmonary medicine 20230112 1

<h4>Background</h4>Lung adenocarcinoma (LUAD) is characterized by high morbidity and mortality rates and poor prognosis. N7-methylguanosine play an increasingly vital role in lung adenocarcinoma. However, the prognostic value of N7-methylguanosine related-miRNAs in lung adenocarcinoma remains unclear.<h4>Methods</h4>In the study, the mRNA and miRNA expression profiles and corresponding clinical informations were downloaded from the public database. The prognostic signature was built using least ...[more]

PMID: 36635678

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Project description:BackgroundLung adenocarcinoma (LUAD) is one of the most frequent causes of tumor-related mortality worldwide. Recently, the role of N7-methylguanosine (m7G) in tumors has begun to receive attention, but no investigation on the impact of m7G on LUAD. This study aims to elucidate the significance of m7G on the prognosis and immunotherapy in LUAD.MethodsConsensus clustering was employed to determine the molecular subtype according to m7G-related regulators extracted from The Cancer Genome Atlas (TCGA) database. Survival, clinicopathological features and tumor mutational burden (TMB) analysis were applied to research molecular characteristics of each subtype. Subsequently, "limma" package was used to screen differentially expressed genes (DEGs) between subtypes. In the TCGA train cohort (n = 245), a prognostic signature was established by univariate Cox regression, lasso regression and multivariate Cox regression analysis according to DEGs and survival analysis was employed to assess the prognosis. Then the prognostic value of the signature was verified by TCGA test cohort (n = 245), TCGA entire cohort (n = 490) and GSE31210 cohort (n = 226). Moreover, the association among immune infiltration, clinical features and the signature was investigated. The immune checkpoints, TMB and tumor immune dysfunction and exclusion (TIDE) were applied to predict the immunotherapy response.ResultsTwo novel molecular subtypes (C1 and C2) of LUAD were identified. Compared to C2 subtype, C1 subtype had poorer prognosis and higher TMB. Subsequently, the signature (called the "m7G score") was constructed according to four key genes (E2F7, FAM83A, PITX3, and HOXA13). The distribution of m7G score were significantly different between two molecular subtypes. The patients with lower m7G score had better prognosis in TCGA train cohort and three verification cohort. The m7G score was intensively related to immune infiltration. Compared with the lower score, the higher m7G score was related to remarkable upregulation of the PD-1 and PD-L1, the higher TMB and the lower TIDE score.ConclusionThis study established a m7G-related signature for predicting prognosis and immunotherapy in LUAD, which may contribute to the development of new therapeutic strategies for LUAD.

Project description:BackgroundMucinous colonic adenocarcinoma remains a challenging disease due to its high propensity for metastasis and recurrence. N7-methylguanosine (m7G) and long non-coding RNA (lncRNA) are closely associated with the occurrence and progression of tumors. However, research on m7G-related lncRNA in mucinous colonic adenocarcinoma is lacking. Therefore, we sought to explore the prognostic impact of m7G-related lncRNAs in mucinous adenocarcinoma (MC) patients.MethodsIn this study, Pearson analysis was used to identify m7G-related lncRNAs from transcriptome data in The Cancer Genome Atlas (TCGA). Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression were used to further screen m7G-related lncRNAs and incorporate them into a prognostic signature. Based on the risk model, patients were divided into low- and high-risk groups and randomly assigned to the training set and test sets in a 6:4 ratio. Kaplan-Meier, receiver operating characteristic (ROC) curve, multivariate regression, and nomogram analyses were used to confirm the accuracy of the signature. The CIBERSORT algorithm was used to calculate the degree of immune cell infiltration (ICI). Finally, the correlation of the prognostic signature with tumor mutational burden (TMB) and immunophenotype score (IPS) was evaluated.ResultsA total of 432 m7G-related lncRNAs were identified by Pearson analysis. Univariate Cox regression, LASSO regression and survival analysis were performed to further select six m7G-related lncRNAs (P<0.05): AC254629.1, LINC01133, LINC01134, MHENCR, SMIM2-AS1, and XACT. Based on the risk model, heat maps, Kaplan-Meier curves, and ROC curves were constructed, and the results showed that there were significant differences in expression levels and survival status between the two risk groups. The area under the ROC curve (AUC) values for 3-, 5-, and 10-year survival in the training set were 0.944, 0.957, and 1.000, respectively. And in the test set were 0.964, 1.000, and 1.000, respectively. Subsequently, univariate and multivariate regression analyses of clinical characteristics and risk score were performed. The results of risk score were [hazard ratio (HR): 6.458, 95% confidence interval (CI): 2.708-15.403, P<0.001; HR: 7.280, 95% CI: 2.500-21.203, P<0.001], respectively. Using the risk score as an independent prognostic factor, the AUC of it over 3, 5, and 10 years was 0.911, 0.955, and 0.961, respectively. Calibration plots for the nomogram show that the model calibration line is very close to the ideal calibration line, indicating good calibration. The level of ICI was significantly different in the different risk groups. Survival analysis showed that, regardless of TMB risk, patients with MC and a high-risk score consistently had a poor overall survival (OS).ConclusionsThe m7G-related lncRNA prognostic signature has potential value for the prognosis of mucinous colonic adenocarcinoma.

Project description:Background: Long non-coding RNA (LncRNA) is a prognostic factor for malignancies, and N7-Methylguanosine (m7G) is crucial in the occurrence and progression of tumors. However, it has not been documented how well m7G-related LncRNAs predict the development of breast cancer (BC). This study aims to develop a predictive signature based on long non-coding RNAs (LncRNAs) associated with m7G to predict the prognosis of breast cancer patients. Methods: The Cancer Genome Atlas (TCGA) database provided us with the RNA-seq data and matching clinical information of individuals with breast cancer. To identify the signature of N7-Methylguanosine-Related LncRNAs and create a prognostic model, we employed co-expression network analysis, least absolute shrinkage selection operator (LASSO) regression analysis, univariate Cox regression analysis, and multivariate Cox regression analysis. The signature was assessed using the Kaplan-Meier analysis and Receiver Operating Characteristic (ROC) curve. A nomogram and principal component analysis (PCA) were employed to confirm the predictive signature's usefulness. Then, we examined the drug sensitivity between the two risk groups and utilized single-sample gene set enrichment analysis (ssGSEA) to investigate the association between predictive factors and the tumor immune microenvironment in high-risk and low-risk groups. Results: Nine m7G-related LncRNAs (LINC01871, AP003469.4, Z68871.1, AC245297.3, EGOT, TFAP2A-AS1, AL136531.1, SEMA3B-AS1, AL606834.2) that are independently associated with the overall survival time (OS) of BC patients make up the signature we developed. For predicting 1-, 3-, and 5-year survival rates, the areas under the ROC curve (AUC) were 0.715, 0.724, and 0.726, respectively. The Kaplan-Meier analysis revealed that the prognosis of BC patients in the high-risk group was worse than that of those in the low-risk group. When compared to clinicopathological variables, multiple regression analysis demonstrated that risk score was a significant independent predictive factor for BC patients. The results of the ssGSEA study revealed a substantial correlation between the predictive traits and the BC patients' immunological status, low-risk BC patients had more active immune systems, and they responded better to PD1/L1 immunotherapy. Conclusion: The prognostic signature, which is based on m7G-related LncRNAs, can be utilized to inform patients' customized treatment plans by independently predicting their prognosis and how well they would respond to immunotherapy.

Project description: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 m7G-Riskscore. Correlation analysis revealed that patients with a lower m7G-Riskscore 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.

Dataset Information

A noval prognostic signature of the N7-methylguanosine (m7G)-related miRNA in lung adenocarcinoma.

Background

Methods

Results

Conclusions

Publications

A noval prognostic signature of the N7-methylguanosine (m7G)-related miRNA in lung adenocarcinoma.

Similar Datasets

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