Relationships of N6-Methyladenosine-Related Long Non-Coding RNAs With Tumor Immune Microenvironment and Clinical Prognosis in Lung Adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and is associated with very high mortality. Emerging studies have shown that N6-methyladenosine (m6A)-related long non-coding (lnc) RNAs play crucial roles in tumor prognosis and the tumor immune microenvironment (TME). We aimed to explore the expression patterns of different m6A-related lncRNAs concerning patient prognosis and construct an m6A-related lncRNA prognostic model for LUAD. Methods: The prognostic value of m6A-related lncRNAs was investigated in LUAD samples from The Cancer Genome Atlas (TCGA). Potential prognostic m6A-related lncRNAs were selected by Pearson's correlation and univariate Cox regression analysis. Patients were divided into clusters using principal component analysis and the m6A-related lncRNA prognostic signature was calculated using least absolute shrinkage and selection operator (LASSO) Cox regression analysis. Results: Based on 91 prognostic m6A-related lncRNAs, we identified two m6A-related-lncRNA pattern clusters with different overall survival (OS) and different TMEs. We subsequently verified our findings multidimensionally by constructing a 13 m6A-related lncRNA prognostic signature (m6A-LPS) to calculate the risk score, which was robust in different subgroups. The receiver operating characteristic (ROC) curves and concordance index demonstrated that m6A-LPS harbored a promising ability to predict OS in TCGA data set and independent GSE11969 cohort. The risk score was also related to OS, TME, and clinical stage, and the risk score calculated by our model was also identified as independent prognostic predictive factors for LUAD patients after adjustment for age, smoking, gender, and stage. Enrichment analysis indicated that malignancy and drug resistance-associated pathways were more common in cluster2 (LUAD-unfavorable m6A-LPS). Furthermore, the results indicated that the signaling pathway enriched by the target gene of 13 m6A-related lncRNAs may be associated with metastasis and progression of cancer according to current studies. Conclusion: The current results indicated that different m6A-related-lncRNA patterns could affect OS and TME in patients with LUAD, and the prognostic signature based on 13 m6A-related lncRNAs may help to predict the prognosis in LUAD patients.

Zhao J ，Lin X ，Zhuang J ，He F ... -  《Frontiers in Genetics》

Development and validation of the potential biomarkers based on m6A-related lncRNAs for the predictions of overall survival in the lung adenocarcinoma and differential analysis with cuproptosis.

The treatment and prognosis of lung adenocarcinoma (LUAD) remains a challenge. The study aimed to conduct a systematic analysis of the predictive capacity of N6-methyladenosine (m6A)-related long non-coding RNAs (lncRNAs) in the prognosis of LUAD. 594 samples were totally selected from a dataset from The Cancer Genome Atlas. The identification of prognostic m6A-related lncRNAs were performed by Pearson correlation analysis and Cox regression analysis. Systematic analyses, including cluster analysis, survival analysis, and immuno-correlated analysis, were conducted. A prognosis model was built from the optimized subset of m6A-related lncRNAs. The assessment of model was performed by survival analysis, and receiver operating characteristic (ROC) curve. Finally, the risk score of patients with LUAD calculated by the prognosis model was implemented by the analysis of Cox regression. Differential analysis was for further evaluation of the cuproptosis-related genes in two risk sets. These patients were grouped into two clusters according to the expression levels of 22 prognostic m6A-related lncRNAs. The patients with LUAD in cluster 2 was significantly worse in the overall survival (OS) (P = 0.006). Three scores calculated by the ESTIMATE methods in cluster 2 were significantly lower. After the least absolute shrinkage and selection operator algorithm, 10 prognostic m6A-related lncRNAs were totally selected to construct the final model to obtain the risk score. Then the area under the ROC curve of the prognosis model for 1, 3, and 5-year OS was 0.767, 0.709, and 0.736 in the training set, and 0.707, 0.691, and 0.675 in the test set. The OS of the low-risk cohort was significantly higher than that of the high-risk cohort in both the training set (P < 0.001) and test set (P < 0.001). After the analysis of Cox regression, the risk score [Hazard ratio (HR) = 5.792; P < 0.001] and stage (HR = 1.576; P < 0.001) were both considered as independent indicators of prognosis for LUAD. The expression levels of five cuproptosis-related genes were significantly different in two risk sets. The study constructed a predictive model for the OS of patients with LUAD and these OS-related m6A-lncRNAs might have potential roles in LUAD progression.

Gao C ，Kong N ，Zhang F ，Zhou L ，Xu M ，Wu L ... -  《BMC BIOINFORMATICS》

Construction of a Novel Signature and Prediction of the Immune Landscape in Soft Tissue Sarcomas Based on N6-Methylandenosine-Related LncRNAs.

Background: N6-methylandenosine-related long non-coding RNAs (m6A-related lncRNAs) are critically involved in cancer development. However, the roles and clinical significance of m6A-related lncRNAs in soft tissue sarcomas (STS) are inconclusive, thereby warranting further investigations. Methods: Transcriptome profiling data were extracted from The Cancer Genome Atlas (TCGA) database and Genotype-Tissue Expression (GTEx). Consensus clustering was employed to divide patients into clusters and Kaplan-Meier analysis was used to explore the prognostic differences between the subgroups. Gene set enrichment analysis (GSEA) was conducted to identify the biological processes and signaling pathways associated with m6A-Related lncRNAs. Finally, patients were randomly divided into training and validation cohorts, and least absolute shrinkage and selection operator (LASSO) Cox regression was conducted to establish the m6A-related lncRNA-based risk signature. Results: A total of 259 STS patients from TCGA-SARC dataset were enrolled in our study. Thirteen m6A-Related lncRNAs were identified to be closely related to the prognosis of STS patients. Patients were divided into two clusters, and patients in cluster 2 had a better overall survival (OS) than those in cluster 1. Patients in different clusters also showed differences in immune scores, infiltrating immune cells, and immune checkpoint expression. Patients were further classified into high-risk and low-risk subgroups according to risk scores, and high-risk patients were found to have a worse prognosis. The receiver operating characteristic (ROC) curve indicated that the risk signature displayed excellent performance at predicting the prognosis of patients with STS. Further, the risk signature was remarkably connected with the immune microenvironment and chemosensitivity in STS. Conclusion: Our study demonstrated that m6A-related lncRNAs were significantly associated with prognosis and tumor immune microenvironment and could function as independent prognosis-specific predictors in STS, thereby providing novel insights into the roles of m6A-related lncRNAs in STS.

Zhang L ，Tang X ，Wan J ，Zhang X ，Zheng T ，Lin Z ，Liu T ... -  《Frontiers in Molecular Biosciences》

Comprehensive Analysis of N6-Methylandenosine-Related Long Non-Coding RNAs Signature in Prognosis and Tumor Microenvironment of Bladder Cancer.

To investigate the role of N6-methyladenosine (m6A)- related long non-coding RNAs (lncRNAs) in bladder cancer (BC). 50 m6A-related lncRNAs were screened out and were correlated with prognosis from BC samples in The Cancer Genome Atlas (TCGA). The lncRNAs were subdivided into cluster 1 and cluster 2 with consensus cluster analysis, and it was found that lncRNAs in cluster 2 were associated with poor prognosis and increased PD-L1 expression. Gene set enrichment analysis (GSEA) revealed tumor-related pathways in cluster 2. Through least absolute shrinkage and selection operator (LASSO) Cox regression analysis, univariate and multivariate Cox regression, and ROC analyses, 14 prognostic lncRNAs were selected and used to construct the m6A-related lncRNA prognostic signature (m6A-LPS), furthermore, that m6A-LPS was as a valuable independent prognostic factor. Interestingly, the m6A-LPS risk score was positively correlated with the immune score, PD-L1 expression, and the infiltration of immune cell subtypes in BC. SNHG16, a member of the high-risk group based on m6A-LPS, was highly expressed in BC tissues and cell lines and interfered with siRNA resulted in suppressed proliferation, migration, and invasion in vitro. Our study illustrates the role of m6A-related lncRNAs in BC. The m6A-LPS may be an important regulatory target of the tumor microenvironment (TME) in BC.

Chen K ，Zhu S ，Yu W ，Xia Y ，Xing J ，Geng J ，Cheng F ... -  《Frontiers in Oncology》

Analysis of N6-methyladenosine-related lncRNAs in the tumor immune microenvironment and their prognostic role in pancreatic cancer.

Pancreatic cancer (PC) is a rare solid malignancy with a poor prognosis. N6-methyladenosine (m6A) and long noncoding RNAs (lncRNAs) play essential roles in tumorigenesis and progression. However, little is known about the role of m6A-related lncRNAs in PC. m6A-related lncRNAs were extracted by Pearson analysis, and then prognosis-related lncRNAs were filtered from the m6A-related lncRNAs by univariate Cox regression analysis. Based on the expression patterns of the prognosis-related lncRNAs, samples were classified into distinct clusters. Least absolute shrinkage and selection operator (LASSO) Cox regression was used to construct a m6A-lncRNA-related prognostic signature for PC patients. Receiver operating characteristic (ROC) curves and the corresponding area under the curve (AUC) values were used to evaluate the prognostic ability of the model. A total of 178 tumor and 4 normal samples were extracted from The Cancer Genome Atlas (TCGA) database in our study. Based on the expression of 12 filtered prognosis-related lncRNAs, two distinct clusters were eventually identified; these clusters were characterized by differences in the tumor immune microenvironment (TIME) and prognosis. A risk model comprising ten m6A-related lncRNAs was identified as an independent predictor of prognosis. ROC analysis revealed that this model had an acceptable prognostic value for PC patients. The prognostic signature was related to the TIME and the expression of critical immune checkpoint molecules. This study comprehensively assessed the expression pattern and prognostic value of m6A-related lncRNAs in PC. The different clusters correlated with distinct TIMEs and prognoses. The study also constructed a ten-gene signature prognostic model based on m6A-related lncRNAs, which showed good accuracy in predicting overall survival.

Liu Y ，Wang T ，Fang Z ，Kong J ，Liu J ... -  《-》