Dataset Information

CSTF2 mediated mRNA N⁶-methyladenosine modification drives pancreatic ductal adenocarcinoma m⁶A subtypes.

ABSTRACT: N⁶-methyladenosine (m⁶A) modification of gene transcripts plays critical roles in cancer. Here we report transcriptomic m⁶A profiling in 98 tissue samples from 65 individuals with pancreatic ductal adenocarcinoma (PDAC). We identify 17,996 m⁶A peaks with 195 hyper-methylated and 93 hypo-methylated in PDAC compared with adjacent normal tissues. The differential m⁶A modifications distinguish two PDAC subtypes with different prognosis outcomes. The formation of the two subtypes is driven by a newly identified m⁶A regulator CSTF2 that co-transcriptionally regulates m⁶A installation through slowing the RNA Pol II elongation rate during gene transcription. We find that most of the CSTF2-regulated m⁶As have positive effects on the RNA level of host genes, and CSTF2-regulated m⁶As are mainly recognized by IGF2BP2, an m⁶A reader that stabilizes mRNAs. These results provide a promising PDAC subtyping strategy and potential therapeutic targets for precision medicine of PDAC.

SUBMITTER: Zheng Y

PROVIDER: S-EPMC10564946 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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CSTF2 mediated mRNA N6-methyladenosine modification drives pancreatic ductal adenocarcinoma m6A subtypes.

Zheng Yanfen Y Li Xingyang X Deng Shuang S Zhao Hongzhe H Ye Ying Y Zhang Shaoping S Huang Xudong X Bai Ruihong R Zhuang Lisha L Zhou Quanbo Q Li Mei M Su Jiachun J Li Rui R Bao Xiaoqiong X Zeng Lingxing L Chen Rufu R Zheng Jian J Lin Dongxin D He Chuan C Zhang Jialiang J Zuo Zhixiang Z

Nature communications 20231010 1

N6-methyladenosine (m6A) modification of gene transcripts plays critical roles in cancer. Here we report transcriptomic m6A profiling in 98 tissue samples from 65 individuals with pancreatic ductal adenocarcinoma (PDAC). We identify 17,996 m6A peaks with 195 hyper-methylated and 93 hypo-methylated in PDAC compared with adjacent normal tissues. The differential m6A modifications distinguish two PDAC subtypes with different prognosis outcomes. ...[more]

PMID: 37816727

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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:Comprehensive characterization of signaling in pancreatic ductal adenocarcinoma (PDAC) promises to enhance our understanding of the molecular aberrations driving this devastating disease, and may identify novel therapeutic targets as well as biomarkers that enable stratification of patients for optimal therapy. Here, we use immunoaffinity-coupled high-resolution mass spectrometry to characterize global tyrosine phosphorylation patterns across two large panels of human PDAC cell lines: the ATCC series (19 cell lines) and TKCC series (17 cell lines). This resulted in the identification and quantification of over 1800 class 1 tyrosine phosphorylation sites and the consistent segregation of both PDAC cell line series into three subtypes with distinct tyrosine phosphorylation profiles. Subtype-selective signaling networks were characterized by identification of subtype-enriched phosphosites together with pathway and network analyses. This revealed that the three subtypes characteristic of the ATCC series were associated with perturbations in signaling networks associated with cell-cell adhesion and epithelial-mesenchyme transition, mRNA metabolism, and receptor tyrosine kinase (RTK) signaling, respectively. Specifically, the third subtype exhibited enhanced tyrosine phosphorylation of multiple RTKs including the EGFR, ERBB3 and MET. Interestingly, a similar RTK-enriched subtype was identified in the TKCC series, and 'classifier' sites for each series identified using Random Forest models were able to predict the subtypes of the alternate series with high accuracy, highlighting the conservation of the three subtypes across the two series. Finally, RTK-enriched cell lines from both series exhibited enhanced sensitivity to the small molecule EGFR inhibitor erlotinib, indicating that their phosphosignature may provide a predictive biomarker for response to this targeted therapy. These studies highlight how resolution of subtype-selective signaling networks can provide a novel taxonomy for particular cancers, and provide insights into PDAC biology that can be exploited for improved patient management.

Project description:BackgroundPancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer related death in the world with a five-year survival rate of less than 5%. Not all PDAC are the same, because there exist intra-tumoral heterogeneity between PDAC, which poses a great challenge to personalized treatments for PDAC.MethodsTo dissect the molecular heterogeneity of PDAC, we performed a retrospective meta-analysis on whole transcriptome data from more than 1200 PDAC patients. Subtypes were identified based on non-negative matrix factorization (NMF) biclustering method. We used the gene set enrichment analysis (GSEA) and survival analysis to conduct the molecular and clinical characterization of the identified subtypes, respectively.ResultsSix molecular and clinical distinct subtypes of PDAC: L1-L6, are identified and grouped into tumor-specific (L1, L2 and L6) and stroma-specific subtypes (L3, L4 and L5). For tumor-specific subtypes, L1 (~ 22%) has enriched carbohydrate metabolism-related gene sets and has intermediate survival. L2 (~ 22%) has the worst clinical outcomes, and is enriched for cell proliferation-related gene sets. About 23% patients can be classified into L6, which leads to intermediate survival and is enriched for lipid and protein metabolism-related gene sets. Stroma-specific subtypes may contain high non-epithelial contents such as collagen, immune and islet cells, respectively. For instance, L3 (~ 12%) has poor survival and is enriched for collagen-associated gene sets. L4 (~ 14%) is enriched for various immune-related gene sets and has relatively good survival. And L5 (~ 7%) has good clinical outcomes and is enriched for neurotransmitter and insulin secretion related gene sets. In the meantime, we identified 160 subtype-specific markers and built a deep learning-based classifier for PDAC. We also applied our classification system on validation datasets and observed much similar molecular and clinical characteristics between subtypes.ConclusionsOur study is the largest cohort of PDAC gene expression profiles investigated so far, which greatly increased the statistical power and provided more robust results. We identified six molecular and clinical distinct subtypes to describe a more complete picture of the PDAC heterogeneity. The 160 subtype-specific markers and a deep learning based classification system may be used to better stratify PDAC patients for personalized treatments.

Dataset Information

CSTF2 mediated mRNA N⁶-methyladenosine modification drives pancreatic ductal adenocarcinoma m⁶A subtypes.

Publications

CSTF2 mediated mRNA N<sup>6</sup>-methyladenosine modification drives pancreatic ductal adenocarcinoma m<sup>6</sup>A subtypes.

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