An N6-Methyladenosine-Related Gene Set Variation Score as a Prognostic Tool for Lung Adenocarcinoma.
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ABSTRACT:
SUBMITTER: Zhang H
PROVIDER: S-EPMC8295598 | biostudies-literature | 2021
REPOSITORIES: biostudies-literature
Publications
An N6-Methyladenosine-Related Gene Set Variation Score as a Prognostic Tool for Lung Adenocarcinoma.
Zhang Huijuan H Hu Jing J Liu Aina A Qu Huajun H Jiang Fenge F Wang Congcong C Mo Steven S Sun Ping P
Frontiers in cell and developmental biology 20210708
N6-methyladenosine (m6A) is the most prevalent type of RNA modification, and we hypothesized that patterns of m6A-related genes may be useful for estimating risk of lung adenocarcinoma (LUAD). An m6A-related gene set variation score (m6A-GSVS) was generated using RNA-sequencing data from LUAD patients in The Cancer Genome Atlas (TCGA). We investigated the association of m6A-GSVS with stemness, tumor mutational burden (TMB), expression of three immune checkpoints, levels of tumor-infiltrating lym ...[more]
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Project description:PurposeThe prognostic value of an N6-methyladenosine (m6A) methylation-related immune gene signature for lung adenocarcinoma (LUAD) was investigated.Patients and methodsGene expression and clinical phenotype data of LUAD patients were downloaded from The Cancer Genome Atlas database. A list of immune-related genes was retrieved from the InnateDB database. Correlation analysis, survival analysis, and univariate and multivariate Cox regression analyses were performed. After allocating patients into a high-risk or a low-risk group, the corresponding survival rates, immune microenvironment, expression of immune checkpoint genes, and modulation of Kyoto Encyclopedia of Genes and Genomes pathways were examined. Finally, the expression levels of prognostic biomarkers were assessed in the GSE126044 dataset.ResultsSeven m6A-related immune prognostic genes were identified. High expression of PSMD10P1, DIDO1, ABCA5, and CIITA was associated with high survival rates, while that of PRC1, ZWILCH, and ANLN was associated with low survival rates. The high- and low-risk groups showed significant differences in terms of the abundance of six tumor-infiltrating immune cell types and expression of 12 immune checkpoint genes. The risk group acted as an independent prognostic factor (hazard ratio = 0.398, 95% confidence interval = 0.217-0.729, P = 0.003). Finally, the developed nomogram could predict most efficiently the 1-, 2-, and 3-year survival probability of LUAD patients with a C-index of 0.833.ConclusionA seven-gene risk signature, associated with the immune microenvironment in LUAD, showed independent prognostic value.
| S-EPMC8643173 | biostudies-literature
Project description:Aberrant regulation of m6A mRNA modification can lead to changes in gene expression, thus contributing to tumorigenesis in several types of solid tumors. In this study, by integrating analyses of m6A methylation and mRNA expression, we identified 84 m6A-regulated mRNAs in lung adenocarcinoma (LUAD). Although the m6A methylation levels of total RNA in LUAD patient tumor tissue were reduced, the majority (75.2%) of m6A-regulated mRNAs were hypermethylated. The m6A-hypermethylated mRNAs were mainly enriched in terms related to transcription factor activity. We established a 10-m6A-regulated-mRNA signature score system through least absolute shrinkage and selection operator Cox regression analysis, with its predictive value validated by Kaplan-Meier curve and time-dependent receiver operating characteristic curves. RFXAP and KHDRBS2 from the signature also exhibited an independent prognostic value. The co-expression and interaction network analyses demonstrated the strong correlation between m6A regulators and the genes in the signature, further supporting the results of the m6A methylation modification patterns. These findings highlight the potential utility of integrating multi-omics data (m6A methylation level and mRNA expression) to accurately obtain potential prognostic biomarkers, which may provide important insights into developing novel and effective therapies for LUAD.
| S-EPMC8377381 | biostudies-literature
Project description:Comprehensive N6-methyladenosine (m6A) epitranscriptomic profiling of primary tumors remains largely uncharted. Here, we profiled the m6A epitranscriptome of 10 nonneoplastic lung tissues and 51 lung adenocarcinoma (LUAD) tumors, integrating the corresponding transcriptomic, proteomic, and extensive clinical annotations. We identified distinct clusters and genes that were exclusively linked to disease progression through m6A modifications. In comparison with nonneoplastic lung tissues, we identified 430 transcripts to be hypo-methylated and 222 to be hyper-methylated in tumors. Among these genes, EML4 emerged as a novel metastatic driver, displaying significant hypermethylation in tumors. m6A modification promoted the translation of EML4, leading to its widespread overexpression in primary tumors. Functionally, EML4 modulated cytoskeleton dynamics by interacting with ARPC1A, enhancing lamellipodia formation, cellular motility, local invasion, and metastasis. Clinically, high EML4 protein abundance correlated with features of metastasis. METTL3 small-molecule inhibitor markedly diminished both EML4 m6A and protein abundance and efficiently suppressed lung metastases in vivo. Significance: Our study reveals a dynamic and functional epitranscriptomic landscape in LUAD, offering a valuable resource for further research in the field. We identified EML4 hypermethylation as a key driver of tumor metastasis, highlighting a novel therapeutic strategy of targeting EML4 to prevent LUAD metastasis.
| S-EPMC11528209 | biostudies-literature
Project description:Background: Mounting research studies have suggested the indispensable roles of N6-methyladenosine (m6A) RNA modification in carcinogenesis. Nevertheless, it was little known about the potential function of m6A-related lncRNAs in sample clustering, underlying mechanism, and anticancer immunity of pancreatic ductal adenocarcinoma (PDAC). Methods: PDAC sample data were obtained from TCGA-PAAD project, and a total of 23 m6A regulators were employed based on published articles. Pearson correlation and univariate Cox regression were analyzed to determine m6A-related lncRNAs with prognostic significance to identify distinct m6A-related lncRNA subtypes by consensus clustering. Next, the least absolute shrinkage and selection operator (LASSO) algorithm was applied for constructing an m6A-related lncRNA scoring system, further quantifying the m6A-related lncRNA patterns in individual samples. Gene set variation analysis (GSVA) was employed to assign pathway activity estimates to individual samples. To decode the comprehensive landscape of TME, the CIBERSORT method and ESTIMATE algorithm were analyzed. The half-maximal inhibitory concentration (IC50) of chemotherapeutic agents was predicted with the R package pRRophetic. Finally, a quantitative real-time polymerase chain reaction was used to determine TRPC7-AS1 mRNA expression in PDAC. Results: Two distinct m6A-related lncRNA patterns with different clinical outcomes, TEM features, and biological enrichment were identified based on 45 prognostic m6A-related lncRNAs. The identification of m6A-related lncRNA patterns within individual samples based on risk scores contributed to revealing biological signatures, clinical outcomes, TEM characterization, and chemotherapeutic effects. A prognostic risk-clinical nomogram was constructed and confirmed to estimate m6A-related lncRNA patterns in individual samples. Finally, the biological roles of TRPC7-AS1 were revealed in PDAC. Conclusion: This work comprehensively elucidated that m6A-related lncRNA patterns served as an indispensable player in prognostic prediction and TEM features. Quantitative identification of m6A-related lncRNA patterns in individual tumors will contribute to sample stratification for further optimizing therapeutic strategies.
| S-EPMC9549010 | biostudies-literature
Project description:Aberrant expression of adipogenic regulatory factors (ADIRF) in tumor cells is critical for tumor growth and metastasis. N6-methyladenosine (m6A) modifications have an important role in a variety of biological activities. Our study aimed to investigate the role of ADIRF in adenocarcinoma and to elucidate the regulatory role of m6A signaling on ADIRF. Differential expression of genes in tumor and normal tissues was analyzed using the LUAD dataset (GSE1987). The Kaplan-Meier method and receiver operating characteristic (ROC) curve analysis were performed to evaluate the prognostic and diagnostic value of ADIRF in LUAD. Loss-of-function or gain-of-function experiments were performed to study the effect of ADIRF on LUAD growth in vitro. The molecular mechanism of action of ADIRF in LUAD was confirmed using a dual-luciferase reporter system and MeRIP-qPCR. We identified a loss of ADIRF expression in LUAD tissues and cells. Furthermore, the restoration of ADIRF levels attenuated LUAD cell growth and metastasis in vitro. Mechanistically, an m6A "eraser," α-ketoglutarate-dependent dioxygenase alkB homolog 5 (ALKBH5), eliminated the ADIRF m6A modification motif and further blocked the binding of the YTH domain-containing 2 (YTHDC2)-binding protein to ADIRF. At the molecular level, ALKBH5 enrichment increased ADIRF mRNA levels and prevented the attenuation of ADIRF mRNA by YTHDC2. The effects of ALKBH5 overexpression could also extend to the inhibition of LUAD cell proliferation and metastasis. This study linked ADIRF with the m6A modifying regulators ALKBH5 and YTHDC2, providing a promising molecular intervention for LUAD and deepening the understanding of LUAD mechanisms.
| S-EPMC10501161 | biostudies-literature
Project description:Background Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer, which is one of the most commonly diagnosed tumors and the leading causes of death from cancer around the world. Since RNA methylation is a posttranscriptional modification and affects so much biological progress, it is urged to explore the role of N6-methyladenosine (m6A) methylation in LUAD. Methods We explored the expression of 24 m6A methylation genes, as well as their correlations with LAG3 in 561 LUAD samples from TCGA. Consensus clustering was applied to m6A methylation genes, and two LUAD subgroups were identified. The expression of m6A genes was analyzed by the Wilcoxon test. KEGG and GO enrichment analyses were performed to indicate the pathway affected by differentially expressed genes in the two groups. A prognostic model based on LASSO regression using an eleven-m6A gene signature was constructed according to the expression of these genes. Receiver operating characteristic (ROC) curve was used to confirm the accuracy of the model in the TCGA cohort, as well as in the test cohort from the Gene Expression Omnibus (GEO) database. Results Compared to cluster 1, cluster 2 showed poorer overall survival (OS) and higher LAG3 expression. In addition, KEGG and GO enrichment analyses indicated that differentially expressed genes are enriched in the immune response. We also observed that the expression of LAG3 is positively correlated with IGF2BP2, CBLL1, and HNRNPA2B1 and negatively correlated with YTHDF2, YTHDF3, and FTO. For patients in the TCGA cohort, the AUC score is 0.7, and the AUC score for the GSE50081 cohort is 0.675. Patients with lower risk scores exhibited better overall survival and lower expression of LAG3 than patients with higher risk scores. Conclusions In brief, our results indicated the important role of m6 methylation in affecting the tumor immune microenvironment and the survival of patients with LUAD. The m6A methylation gene signatures might serve as promising therapeutic targets and help the immunotherapy of LUAD in the future.
| S-EPMC9427291 | biostudies-literature
Project description:The RNA N6-methyladenosine (m6A) modification has become an essential hotspot in epigenetic modulation. Serine-arginine protein kinase 1 (SRPK1) is associated with the pathogenesis of various cancers. However, the m6A modification of SRPK1 and its association with the mechanism of in lung adenocarcinoma (LUAD) remains unclear. Western blotting and polymerase chain reaction (PCR) analyses were carried out to identify gene and protein expression. m6A epitranscriptomic microarray was utilized to the assess m6A profile. Loss and gain-of-function assays were carried out elucidate the impact of METTL3 and SRPK1 on LUAD glycolysis and tumorigenesis. RNA immunoprecipitation (RIP), m6A RNA immunoprecipitation (MeRIP), and RNA stability tests were employed to elucidate the SRPK1's METTL3-mediated m6A modification mechanism in LUAD. Metabolic quantification and co-immunoprecipitation assays were applied to investigate the molecular mechanism by which SRPK1 mediates LUAD metabolism. The epitranscriptomic microarray assay revealed that SRPK1 could be hypermethylated and upregulated in LUAD. The main transmethylase METTL3 was upregulated and induced the aberrant high m6A levels of SRPK1. Mechanistically, SRPK1's m6A sites were directly methylated by METTL3, which also stabilized SRPK1 in an IGF2BP2-dependent manner. Methylated SRPK1 subsequently promoted LUAD progression through enhancing glycolysis. Further metabolic quantification, co-immunoprecipitation and western blot assays revealed that SRPK1 interacts with hnRNPA1, an important modulator of PKM splicing, and thus facilitates glycolysis by upregulating PKM2 in LUAD. Nevertheless, METTL3 inhibitor STM2457 can reverse the above effects in vitro and in vivo by suppressing SRPK1 and glycolysis in LUAD. It was revealed that in LUAD, aberrantly expressed METTL3 upregulated SRPK1 levels via an m6A-IGF2BP2-dependent mechanism. METTL3-induced SRPK1 fostered LUAD cell proliferation by enhancing glycolysis, and the small-molecule inhibitor STM2457 of METTL3 could be an alternative novel therapeutic strategy for individuals with LUAD.
| S-EPMC11295518 | biostudies-literature
Project description:N6-methyladenosine (m6A) modification is the most abundant modification in long noncoding RNAs (lncRNAs). Current studies have shown that the abnormal expression of m6A-related genes is closely associated with the tumorigenesis and progression of glioma. However, the role of m6A-related lncRNAs in glioma development is still unclear. Herein, we screened 566 m6A-related lncRNAs in glioma from The Cancer Genome Atlas (TCGA) database. The expression pattern of these lncRNAs could cluster samples into two groups, in which various classical tumor-related functions and the tumor immune microenvironment were significantly different. Subsequently, a nine-factor m6A-related lncRNA prognostic signature (MLPS) was constructed by using a LASSO regression analysis in the training set and was validated in the test set and independent datasets. The AUC values of the MLPS were 0.881, 0.918 and 0.887 for 1-, 3- and 5-year survival in the training set, respectively, and 0.856, 0.916 and 0.909 for 1-, 3-, and 5-year survival in the test set, respectively. Stratification analyses of the MLPS illustrated its prognostic performance in gliomas with different characteristics. Correlation analyses showed that the infiltrations of monocytes and tumor-associated macrophages (TAMs) were significantly relevant to the risk score in the MLPS. Moreover, we detected the expression of four MLPS factors with defined sequences in glioma and normal cells by using RT-PCR. Afterwards, we investigated the functions of LNCTAM34A (one of the MLPS factors) in glioma cells, which have rarely been reported. Via in vitro experiments, LNCTAM34A was demonstrated to promote the proliferation, migration and epithelial-mesenchymal transition (EMT) of glioma cells. Overall, our study revealed the critical role of m6A-related lncRNAs in glioma and elucidated that LNCTAM34A could promote glioma proliferation, migration and EMT.
| S-EPMC8927984 | biostudies-literature
Project description: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.
| S-EPMC8585518 | biostudies-literature
Project description:Background: Immune and stromal cells in the tumor microenvironment (TME) significantly contribute to the prognosis of lung adenocarcinoma; however, the TME-related immune prognostic signature is unknown. The aim of this study was to develop a novel immune prognostic model of the TME in lung adenocarcinoma. Methods: First, the immune and stromal scores among lung adenocarcinoma patients were determined using the ESTIMATE algorithm in accordance with The Cancer Genome Atlas (TCGA) database. Differentially expressed immune-related genes (IRGs) between high and low immune/stromal score groups were analyzed, and a univariate Cox regression analysis was performed to identify IRGs significantly correlated with overall survival (OS) among patients with lung adenocarcinoma. Furthermore, a least absolute shrinkage and selection operator (LASSO) regression analysis was performed to generate TME-related immune prognostic signatures. Gene set enrichment analysis was performed to analyze the mechanisms underlying these immune prognostic signatures. Finally, the functions of hub IRGs were further analyzed to delineate the potential prognostic mechanisms in comprehensive TCGA datasets. Results: In total, 702 intersecting differentially expressed IRGs (589 upregulated and 113 downregulated) were screened. Univariate Cox regression analysis revealed that 58 significant differentially expressed IRGs were correlated with patient prognosis in the training cohort, of which three IRGs (CLEC17A, INHA, and XIRP1) were identified through LASSO regression analysis. A robust prognostic model was generated on the basis of this three-IRG signature. Furthermore, functional enrichment analysis of the high-risk-score group was performed primarily on the basis of metabolic pathways, whereas analysis of the low-risk-score group was performed primarily on the basis of immunoregulation and immune cell activation. Finally, hub IRGs CLEC17A, INHA, and XIRP1 were considered novel prognostic biomarkers for lung adenocarcinoma. These hub genes had different mutation frequencies and forms in lung adenocarcinoma and participated in different signaling pathways. More importantly, these hub genes were significantly correlated with the infiltration of CD4+ T cells, CD8+ T cells, macrophages, B cells, and neutrophils. Conclusions: The robust novel TME-related immune prognostic signature effectively predicted the prognosis of patients with lung adenocarcinoma. Further studies are required to further elucidate the regulatory mechanisms of these hub IRGs in the TME and to develop new treatment strategies.
| S-EPMC7538811 | biostudies-literature