Identification and Validation of an m6A Modification of JAK-STAT Signaling Pathway–Related Prognostic Prediction Model in Gastric Cancer

Jiang, Fei; Chen, Xiaowei; Shen, Yan; Shen, Xiaobing

doi:10.3389/fgene.2022.891744

Cited by 4 publications

(2 citation statements)

References 48 publications

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“…46 However, there is still little research to explore the impact and mechanism of m 6 A modi cation of JAK-STAT pathway members on the occurrence and development of GC. 47 Herein, our research provides evidence that METTL3-mediated m 6 A modi cation of STAT5A increases the stability and expression of STAT5A. Moreover, STAT5A exerts an oncogenic role in GC by promoting cell proliferation and metastasis.…”

Section: Discussionmentioning

confidence: 66%

METTL3-mediated N6-methyladenosine modification of STAT5A promotes gastric cancer progression through regulating KLF4

Liu,

Zang,

Tian

et al. 2024

Preprint

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N6-methyladenosine (m6A) modification is the predominant post-transcriptional RNA modification in eukaryotes, playing a pivotal regulatory role in various aspects of RNA fate determination, such as mRNA stability, alternative splicing, and translation. The dysregulation of critical m6A methyltransferase METTL3 is implicated in tumorigenesis and development. Here, this work shows that METTL3 is upregulated in gastric cancer tissues and associated with poor prognosis. Helicobacter pylori infection contributes to the increased expression of METTL3 in gastric cancer. Additionally, METTL3 methylates the A2318 site within the coding sequence (CDS) region of STAT5A, thereby enhancing STAT5A mRNA stability and protein expression. Furthermore, IGF2BP2 recognizes and binds METTL3-mediated m6A modification of STAT5A through its GXXG motif in KH3 and KH4 domains, leading to increased stability of STAT5A mRNA. Functional studies indicate that STAT5A overexpression remarkably enhances the proliferation and migration of GC cells, whereas STAT5A knockdown has inhibitory effects. Further nude mouse experiments show that STAT5A knockdown effectively inhibits the growth and metastasis of gastric cancer in vivo. Moreover, as a transcription factor, STAT5A represses KLF4 transcription by binding to its promoter region. The overexpression of KLF4 can counteract the oncogenic impact of STAT5A. Collectively, this study highlights the crucial role of m6A in gastric cancer and identifies potential targets for effectively controlling its progression.

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Section: Discussionmentioning

confidence: 66%

METTL3-mediated N6-methyladenosine modification of STAT5A promotes gastric cancer progression through regulating KLF4

Liu,

Zang,

Tian

et al. 2024

Preprint

View full text Add to dashboard Cite

show abstract

“…In addition, it has been suggested that decreased METTL3 expression increases SOCS stability, thereby inhibiting IL7-STAT5 signaling pathway activation, which further leads to abnormalities in T-cell proliferation and differentiation [47]. However, few studies have explored the role and mechanism of the m 6 A modification of JAK-STAT pathway members on the occurrence and development of GC [48]. Our research provides evidence that METTL3-mediated m 6 A modification of STAT5A increases the stability and expression of STAT5A.…”

Section: Discussionmentioning

confidence: 99%

METTL3-mediated N6-methyladenosine modification of STAT5A promotes gastric cancer progression by regulating KLF4

Zang,

Tian,

Wang

et al. 2024

Oncogene

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N6-methyladenosine (m6A) is the predominant post-transcriptional RNA modification in eukaryotes and plays a pivotal regulatory role in various aspects of RNA fate determination, such as mRNA stability, alternative splicing, and translation. Dysregulation of the critical m6A methyltransferase METTL3 is implicated in tumorigenesis and development. Here, this work showed that METTL3 is upregulated in gastric cancer tissues and is associated with poor prognosis. METTL3 methylates the A2318 site within the coding sequence (CDS) region of STAT5A. IGF2BP2 recognizes and binds METTL3-mediated m6A modification of STAT5A through its GXXG motif in the KH3 and KH4 domains, leading to increased stability of STAT5A mRNA. In addition, both METTL3 and IGF2BP2 are positively correlated with STAT5A in human gastric cancer tissue samples. Helicobacter pylori infection increased the expression level of METTL3 in gastric cancer cells, thereby leading to the upregulation of STAT5A. Functional studies indicated that STAT5A overexpression markedly enhances the proliferation and migration of GC cells, whereas STAT5A knockdown has inhibitory effects. Further nude mouse experiments showed that STAT5A knockdown effectively inhibits the growth and metastasis of gastric cancer in vivo. Moreover, as a transcription factor, STAT5A represses KLF4 transcription by binding to its promoter region. The overexpression of KLF4 can counteract the oncogenic impact of STAT5A. Overall, this study highlights the crucial role of m6A in gastric cancer and provides potential therapeutic targets for gastric cancer.

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Genes selection using deep learning and explainable artificial intelligence for chronic lymphocytic leukemia predicting the need and time to therapy

Morabito,

Adornetto,

Monti

et al. 2023

Front. Oncol.

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Analyzing gene expression profiles (GEP) through artificial intelligence provides meaningful insight into cancer disease. This study introduces DeepSHAP Autoencoder Filter for Genes Selection (DSAF-GS), a novel deep learning and explainable artificial intelligence-based approach for feature selection in genomics-scale data. DSAF-GS exploits the autoencoder’s reconstruction capabilities without changing the original feature space, enhancing the interpretation of the results. Explainable artificial intelligence is then used to select the informative genes for chronic lymphocytic leukemia prognosis of 217 cases from a GEP database comprising roughly 20,000 genes. The model for prognosis prediction achieved an accuracy of 86.4%, a sensitivity of 85.0%, and a specificity of 87.5%. According to the proposed approach, predictions were strongly influenced by CEACAM19 and PIGP, moderately influenced by MKL1 and GNE, and poorly influenced by other genes. The 10 most influential genes were selected for further analysis. Among them, FADD, FIBP, FIBP, GNE, IGF1R, MKL1, PIGP, and SLC39A6 were identified in the Reactome pathway database as involved in signal transduction, transcription, protein metabolism, immune system, cell cycle, and apoptosis. Moreover, according to the network model of the 3D protein-protein interaction (PPI) explored using the NetworkAnalyst tool, FADD, FIBP, IGF1R, QTRT1, GNE, SLC39A6, and MKL1 appear coupled into a complex network. Finally, all 10 selected genes showed a predictive power on time to first treatment (TTFT) in univariate analyses on a basic prognostic model including IGHV mutational status, del(11q) and del(17p), NOTCH1 mutations, β2-microglobulin, Rai stage, and B-lymphocytosis known to predict TTFT in CLL. However, only IGF1R [hazard ratio (HR) 1.41, 95% CI 1.08-1.84, P=0.013), COL28A1 (HR 0.32, 95% CI 0.10-0.97, P=0.045), and QTRT1 (HR 7.73, 95% CI 2.48-24.04, P<0.001) genes were significantly associated with TTFT in multivariable analyses when combined with the prognostic factors of the basic model, ultimately increasing the Harrell’s c-index and the explained variation to 78.6% (versus 76.5% of the basic prognostic model) and 52.6% (versus 42.2% of the basic prognostic model), respectively. Also, the goodness of model fit was enhanced (χ2 = 20.1, P=0.002), indicating its improved performance above the basic prognostic model. In conclusion, DSAF-GS identified a group of significant genes for CLL prognosis, suggesting future directions for bio-molecular research.

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Identification and Validation of an m6A Modification of JAK-STAT Signaling Pathway–Related Prognostic Prediction Model in Gastric Cancer

Cited by 4 publications

References 48 publications

METTL3-mediated N6-methyladenosine modification of STAT5A promotes gastric cancer progression through regulating KLF4

METTL3-mediated N6-methyladenosine modification of STAT5A promotes gastric cancer progression through regulating KLF4

METTL3-mediated N6-methyladenosine modification of STAT5A promotes gastric cancer progression by regulating KLF4

Genes selection using deep learning and explainable artificial intelligence for chronic lymphocytic leukemia predicting the need and time to therapy

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