Deqian Xie

Lipid modifications are critical for membrane anchoring and signal transduction. N‐myristoylation, catalyzed by NMT1/2, irreversibly attaches myristic acid to N‐terminal glycine residues, enabling stable membrane localization and crosstalk with other post‐translational modifications. This review traces NMT research from structural characterization to substrate profiling, highlighting the ordered double‐substitution catalytic mechanism and variations in substrate recognition. While prior reviews have covered NMT biochemistry and innate immunity, we emphasize underappreciated roles of N‐myristoylation in metabolic vulnerability, immune evasion, and acquired resistance to targeted therapies and immunotherapies. We discuss how exogenous myristic acid from dietary sources fuels oncogenic signaling, and how N‐myristoylation regulates key signaling pathways (PI3K/AKT, MAPK, ferroptosis) and targets (Src, AMPK, EZH2) to drive immunosuppressive and pro‐tumor phenotypes. Antitumor potential of NMT inhibitors (e.g., B‐13, Zelenirstat) and allosteric ABL1 inhibitors (asciminib) is evaluated. Recent methodological advances (including metabolic labeling, click chemistry, spatial proteomics, and computational simulations) are reviewed. However, translational challenges such as biomarker absence, blood–brain barrier limitations, and functional redundancy remain. Addressing these will require combination therapies tailored to specific mutational, metabolic, and immune profiles. In summary, N‐myristoylation integrates signaling, metabolism, and immunity, offering a rationale for future precision oncology.

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Background: Renal cell carcinoma (RCC) represents the most common form of invasive kidney cancer in adults. Among the components critical to cellular regulation is Phospholipase C Beta 2 (PLCB2), a member of the phospholipase C enzyme family. This enzyme plays a vital role in managing key cellular functions such as growth, differentiation, migration, and survival. Despite its significant importance, the specific expression patterns and molecular mechanisms of PLCB2 in the progression of RCC are not well understood. Methods: This investigation employed a combination of bioinformatics analyses, scRNA-seq, functional assays, transcriptome sequencing, real-time quantitative PCR (RT-PCR), immunofluorescence, rescue experiments, and Western blotting to explore the regulatory function of PLCB2 in driving the epithelial-mesenchymal transition (EMT) in RCC through the PI3K/AKT signaling pathway. Results:PLCB2 expression is significantly elevated in RCC samples, and this increase is inversely correlated with patient prognosis. The knockdown of PLCB2 in RCC cell lines leads to a marked reduction in cell proliferation, invasion, migration, and EMT. Transcriptome sequencing further revealed that PLCB2 is significantly associated with the PI3K/AKT pathway. Notably, the PI3K activator 740Y-P was able to reverse the reductions in migration, invasion, and EMT caused by the PLCB2 knockdown. Conclusions: Our findings underscore the pivotal role of PLCB2 in regulating RCC invasion and metastasis by modulating the EMT via the PI3K/AKT signaling pathway. This highlights PLCB2 not only as a key prognostic biomarker, but also as a promising therapeutic target in the treatment of advanced-stage RCC, offering new avenues for more effective interventions.

Kidney renal clear cell carcinoma (KIRC) is increasing in incidence worldwide, with poor and unpredictable patient prognosis limited by diagnostic and therapeutic approaches. New genes are urgently needed to improve this situation. The ankyrin repeat and suppressor of the cytokine signaling (SOCS) box (ASB) family are a promising class of tumorigenesis-related genes. We examined the expression and mutation of 18 ASB genes in various tumors for this study. The findings revealed that ASB genes exhibit significant copy number variation (CNV) and single nucleotide variation (SNV). There were substantial variations in ASB gene expression in different tumor tissues, and different levels of methylation of ASB genes affected the gene expression and tumor progression. By applying LASSO regression analysis, we established a KIRC survival model based on five ASB genes (ASB6, ASB7, ASB8, ASB13, and ASB17). Additionally, ROC curve analysis was used to assess the survival model’s accuracy. Through univariate and multivariate COX regression analysis, we demonstrated that the model’s risk score might be an independent risk factor for individuals with KIRC. In summary, our KIRC survival model could accurately predict patients’ future survival. Further, we also quantified the survival model through a nomogram. This series of findings confirmed that ASB genes are potential predictive markers and targeted therapies for KIRC. Our KIRC survival model based on five ASB genes can help more clinical practitioners make accurate judgments about the prognosis of KIRC patients.