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N(6)-methyladenosine methylation-regulated polo-like kinase 1 cell cycle homeostasis as a potential target of radiotherapy in pancreatic adenocarcinoma.

ABSTRACT: In pancreatic cancer, methyltransferase-like 3 (METTL3), a N(6)-methyladenosine (m6A) methyltransferase, has a favorable effect on tumors and is a risk factor for patients' prognosis. However, the details of what genes are regulated by METTL3 remain unknown. Several RNAs are methylated, and what genes are favored in pancreatic cancer remains unclear. By epitranscriptomic analysis, we report that polo-like kinase 1 (PLK1) is an important hub gene defining patient prognosis in pancreatic cancer and that RNA methylation is involved in regulating its cell cycle-specific expression. We found that insulin like growth factor 2 mRNA binding protein 2 (IGF2BP2) binds to m6A of PLK1 3' untranslated region and is involved in upregulating PLK1 expression and that demethylation of this site activates the ataxia telangiectasia and Rad3-related protein pathway by replicating stress and increasing mitotic catastrophe, resulting in increased radiosensitivity. This suggests that PLK1 methylation is essential for cell cycle maintenance in pancreatic cancer and is a new therapeutic target.

SUBMITTER: Tatekawa S

PROVIDER: S-EPMC9246847 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature

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N(6)-methyladenosine methylation-regulated polo-like kinase 1 cell cycle homeostasis as a potential target of radiotherapy in pancreatic adenocarcinoma.

Tatekawa Shotaro S Tamari Keisuke K Chijimatsu Ryota R Konno Masamitsu M Motooka Daisuke D Mitsufuji Suguru S Akita Hirofumi H Kobayashi Shogo S Murakumo Yoshiki Y Doki Yuichiro Y Eguchi Hidetoshi H Ishii Hideshi H Ogawa Kazuhiko K

Scientific reports 20220630 1

In pancreatic cancer, methyltransferase-like 3 (METTL3), a N(6)-methyladenosine (m6A) methyltransferase, has a favorable effect on tumors and is a risk factor for patients' prognosis. However, the details of what genes are regulated by METTL3 remain unknown. Several RNAs are methylated, and what genes are favored in pancreatic cancer remains unclear. By epitranscriptomic analysis, we report that polo-like kinase 1 (PLK1) is an important hub gene defining patient prognosis in pancreatic cancer an ...[more]

PMID: 35773310

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Project description:BackgroundSeveral studies have revealed that N6-methyladenosine (m6A) regulation is involved in various biological processes and cancer progression. Nevertheless, the potential effects of m6A modifications in the tumor immune microenvironment (TIME) and on immune regulation in pancreatic adenocarcinoma (PAAD) remains unclear.MethodsA consensus clustering algorithm was used to identify different m6A modification patterns and construct an m6A-associated gene signature based on 23 m6A regulators in PAAD. The CIBERSORT and ssGSEA algorithms were used to estimate the components of the immune cells in each sample. The PCA algorithm was used to develop the m6Ascore system for the evaluation of m6A modification patterns in each sample.ResultsTwo m6A modification patterns with different biological properties and prognoses were identified in 176 PAAD patient samples. The features of TIME between the two patterns were similar, with two definite immune phenotypes: immune-inflamed and immune-excluded. Based on the m6A phenotype-associated signature genes, we constructed an m6Ascore system to investigate the m6A modification pattern of each sample, profile the dissection of physiological processes, immune infiltration, clinical prognosis, immunotherapy, and genetic variation. Patients with low m6Ascore scores had better clinical outcomes, enhanced immune infiltration, and lower expression of immunotherapeutic drug targets, such as CD274 and PDCD1LG2. Further research indicated that the m6Ascore and tumor mutation burden were significantly correlated, and patients with low m6Ascore had higher mutation rates in SMAD4 and TTN. Moreover, TNFRSF21 was significantly upregulated in PAAD tumor tissues and cell lines. Lower expression of TNFRSF21 had a prominent advantage in survival and was correlated with a low level of immune infiltration. PAAD samples with different TNFRSF21 expression levels showed significantly distinct sensitivities to chemotherapeutic agents.ConclusionsThis study revealed that m6A modification patterns could play an important role in the diversity and complexity of TIME, and the m6Ascore system could serve as an independent and powerful prognostic biomarker and is latently related to PAAD immunotherapies. Quantitative determination of m6A modification patterns in individual patients will be instrumental in mapping the TIME landscape and further optimizing precision immunotherapy.

Project description:RNA binding motif protein 15 (RBM15) is a key regulatory factor involved in N6-methyladenosine (m6A) methylation. It has been reported that RBM15 plays an important role in the progress of laryngeal squamous cell carcinoma (LSCC), promoting LSCC migration and invasion. However, the role of RBM15 in human different cancers remains unknown. This study aims to analyze the prognostic value of RBM15, and to demonstrate the correlation between RBM15 expression and tumor immunity, as well as to provide clues for further mechanism research. The results showed that RBM15 was mutated or copy number varied in 25 types of cancer. RBM15 mRNA was abnormally up-regulated across various cancers. Survival analysis suggested high expression of RBM15 was associated with poor prognosis in many cancer types. Among these, it affected patients' overall survival (OS) in 10 cancer types, disease-free interval (DFI) in 8 cancer types, progression-free interval (PFI) in 12 cancer types and disease-specific survival (DSS) in 7 cancer types. Importantly, in pancreatic adenocarcinoma (PAAD), overexpression of RBM15 is associated with patients' OS, DFI, PFI, or DSS. In addition, RBM15 expression was positively correlated with immune infiltrating cells in kidney renal clear cell carcinoma (KIRC), brain lower grade glioma (LGG), and PAAD. Moreover, RBM15 expression showed a strong correlation with immune checkpoint markers in PAAD. Cell counting kit-8 (CCK-8) assay showed that knockdown of RBM15 significantly inhibited the proliferation of pancreatic cancer cells. PPI analysis showed USP10, USP24, SMG1, NRAS were closely connected with RBM15 alterations. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that many biological processes (BP), cellular components (CC), molecular functions (MF), cancer related pathways including "sister chromatid cohesion", "peptidyl-serine phosphorylation", "cell division", "nucleoplasm", "nucleus", "protein binding", "protein serine/threonine kinase activity", "T cell receptor signaling pathway", "Cell cycle" were regulated by RBM15 alterations. Taken together, pan-cancer analysis of RBM15 suggested it may be served as a prognostic biomarker and immunotherapeutic target for PAAD.

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.

Project description:Pancreatic Ductal Adenocarcinoma (PDAC) is an aggressive form of pancreatic cancer that typically manifests itself at an advanced stage and does not respond to most treatment modalities. The survival rate of a PDAC patient is less than 5%, with a median survival of just a couple of months. A better understanding of the molecular pathology of PDAC is needed to guide research for the development of better clinical treatment modalities for PDAC patients. Gene expression studies performed to date have identified different subtypes of PDAC with prognostic and clinical relevance. Subtypes identified to date are highly heterogeneous since pancreatic cancer is heterogeneous cancer. Tumor microenvironment and stroma constitute a major chunk of PDAC and contribute to the heterogeneity. Better subtyping methods are need of the hour for better prognosis and classification of PDAC for future personalized treatment. In this work, we have performed an integrated analysis of DNA methylation and gene expression datasets to provide better mechanistic and molecular insights into Pancreatic cancers, especially PDAC. The use of varied and diverse datasets has provided valuable insights into different cancer types and can play an integral role in revealing the complex nature of underlying biological mechanisms. We performed subtyping of TCGA-PAAD gene expression and methylation datasets into different subtypes using state-of-the-art normalization methods and unsupervised clustering methods that reveal latent hidden factors, leading to additional insights for subtyping. Differential expression and differential methylation were performed for each of the subtypes obtained from clustering. Our analysis gave a consensus of five cluster solution with relevant pathways like MAPK, MET. The five subtypes corresponded to the tumor and stromal subtypes. This analysis helps in distinguishing and identifying different subtypes based on enriched putative genes. These results help propose novel experimentally-verifiable PDAC subtyping and demonstrate that using varied data sets and integrated methods can contribute to disease prognostication and precision medicine in PDAC treatment.

Dataset Information

N(6)-methyladenosine methylation-regulated polo-like kinase 1 cell cycle homeostasis as a potential target of radiotherapy in pancreatic adenocarcinoma.

Publications

N(6)-methyladenosine methylation-regulated polo-like kinase 1 cell cycle homeostasis as a potential target of radiotherapy in pancreatic adenocarcinoma.

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