METTL3-mediated m6A modification enhances ZDHHC16 expression in nonsmall- cell lung cancer patients, attenuating ferroptosis by suppressing CREB ubiquitination.

At present, the early diagnosis and treatment of non-small cell lung cancer (NSCLC) is still an urgent problem to be solved worldwide, including in China. The present work investigated the possible protective effect of ZDHHC16 in cell proliferation and metastasis of NSCLC and explored its possible mechanisms. ZDHHC16 expression level in patients with Non-Small-Cell Lung Cancer was up-regulation. ZDHHC16 gene is stabilized by m6A methylation. ZDHHC16 gene reduced ferroptosis of NSCLC by the rehabilitation of the mitochondrial structure. ZDHHC16 promoted CREB expression through the inhibition of CREB Ubiquitination. Confocal microscopy showed that ZDHHC16 reduced the CREB expression of NSCLC. ZDHHC16 up-regulation reduced CREB Ubiquitination, and down-regulation of ZDHHC16 promoted CREB Ubiquitination of NSCLC. CREB Agonists reduced the effects of ZDHHC16 on ferroptosis, not affecting the Warburg effect of NSCLC. CREB inhibitor reduced the effects of si-ZDHHC16 on ferroptosis, not affecting the Warburg effect of NSCLC. METTL3-mediated m6A modification increases ZDHHC16 stability. Our study revealed that the m6A-forming enzyme METTL3 upregulates ZDHHC16 expression in NSCLC patients, leading to the reduction of ferroptosis by inhibiting CREB ubiquitination.

A comprehensive cuproptosis score and associated gene signatures reveal prognostic and immunological features of idiopathic pulmonary fibrosis.

Background: Cuproptosis, the most recently identified and regulated cell death, depends on copper ions in vivo. Copper regulates the pathogenesis of Idiopathic pulmonary fibrosis (IPF), but the mechanism of action underlying cuproptosis in IPF remains unclear. Methods: We identified three cuproptosis patterns based on ten cuproptosis-related genes using unsupervised consensus clustering. We quantified these patterns using a PCA algorithm to construct a cuproptosis score. ssGSEA and the Cibersort algorithm assessed the immune profile of IPF patients. GSEA and GSVA were used to analyze the functional differences in different molecular patterns. Drug susceptibility prediction based on cuproptosis scores and meaningful gene markers was eventually screened in combination with external public data sets,in vitro experiments and our cases. Results: Of the three types of cuproptosis-related clusters identified in the study, patients in the clusterA, geneclusterB, and score-high groups showed improved prognoses. Moreover, each cluster exhibited differential immune characteristics, with the subtype showing a poorer prognosis associated with an immune overreaction. Cuproptosis score can be an independent risk factor for predicting the prognosis of IPF patients. GSEA showed a significant functional correlation between the score and cuproptosis. The genes AKAP9, ANK3, C6orf106, LYRM7, and MBNL1, were identified as prognostic-related signatures in IPF patients. The functional role of immune regulation in IPF was further explored by correlating essential genes with immune factors. Also, the nomogram constructed by cumulative information from gene markers and cuproptosis score showed reliable clinical application. Conclusions: Cuproptosis patterns differ significantly in the prognosis and immune characteristics of IPF patients. The cuproptosis score and five gene signatures can provide a reliable reference in the prognosis and diagnosis of IPF.

Identifying oxidative stress-related biomarkers in idiopathic pulmonary fibrosis in the context of predictive, preventive, and personalized medicine using integrative omics approaches and machine-learning strategies.

Background: Idiopathic pulmonary fibrosis (IPF) is a rare interstitial lung disease with a poor prognosis that currently lacks effective treatment methods. Preventing the acute exacerbation of IPF, identifying the molecular subtypes of patients, providing personalized treatment, and developing individualized drugs are guidelines for predictive, preventive, and personalized medicine (PPPM / 3PM) to promote the development of IPF. Oxidative stress (OS) is an important pathological process of IPF. However, the relationship between the expression levels of oxidative stress-related genes (OSRGs) and clinical indices in patients with IPF is unclear; therefore, it is still a challenge to identify potential beneficiaries of antioxidant therapy. Because PPPM aims to recognize and manage diseases by integrating multiple methods, patient stratification and analysis based on OSRGs and identifying biomarkers can help achieve the above goals. Methods: Transcriptome data from 250 IPF patients were divided into training and validation sets. Core OSRGs were identified in the training set and subsequently clustered to identify oxidative stress-related subtypes. The oxidative stress scores, clinical characteristics, and expression levels of senescence-associated secretory phenotypes (SASPs) of different subtypes were compared to identify patients who were sensitive to antioxidant therapy to conduct differential gene functional enrichment analysis and predict potential therapeutic drugs. Diagnostic markers between subtypes were obtained by integrating multiple machine learning methods, their expression levels were tested in rat models with different degrees of pulmonary fibrosis and validation sets, and nomogram models were constructed. CIBERSORT, single-cell RNA sequencing, and immunofluorescence staining were used to explore the effects of OSRGs on the immune microenvironment. Results: Core OSRGs classified IPF into two subtypes. Patients classified into subtypes with low oxidative stress levels had better clinical scores, less severe fibrosis, and lower expression of SASP-related molecules. A reliable nomogram model based on five diagnostic markers was constructed, and these markers' expression stability was verified in animal experiments. The number of neutrophils in the immune microenvironment was significantly different between the two subtypes and was closely related to the degree of fibrosis. Conclusion: Within the framework of PPPM, this work comprehensively explored the role of OSRGs and their mediated cellular senescence and immune processes in the progress of IPF and assessed their capabilities aspredictors of high oxidative stress and disease progression,targets of the vicious loop between regulated pulmonary fibrosis and OS for targeted secondary and tertiary prevention, andreferences for personalized antioxidant and antifibrotic therapies. Supplementary Information: The online version contains supplementary material available at 10.1007/s13167-023-00334-4.

MRPL13 Act as a Novel Therapeutic Target and Could Promote Cell Proliferation in Non-Small Cell Lung Cancer.

BACKGROUND: The latent involvement of MRPL13 in non-small cell lung cancer (NSCLC) remains unclear. This study aimed to explore the role of MRPL13 in NSCLC. METHODS: All analyses were performed in R software 4.0, SPSS version 23, and GraphPad Prism 8. The "limma" package was used to identify differentially expressed genes. Univariate and multivariate cox analyses were used to identify prognosis-related genes. A549 and H1299 lung cancer cell lines were selected for phenotypic experiments. RESULTS: The high level of MRPL13 was correlated with poor T classification and overall survival. In vitro experiments showed that MRPL13 was highly expressed in NSCLC tissue and cell lines. MRPL13 knockdown inhibited the proliferation of lung cancer A549 and H1299 cell lines, which was further validated by in vivo experiment. Moreover, GSEA analysis suggested that the pathway of MYC target, PI3K/AKT/mTOR/ signaling, oxidative phosphorylation, and G2/M checkpoints may be the potential pathway where MRPL13 was involved. Meanwhile, MRPL13 demonstrated a negative correlation with M1 macrophage, CD8+ T cells, and CD4+ T cells, making it an underlying immunotherapy target of NSCLC. CONCLUSION: MRPL13 may promote the proliferation of NSCLC cells and serve as an independent tumor marker and an emerging therapeutic target.

Prognostic Significance of Serum PD-L1 Level in Patients with Locally Advanced or Metastatic Esophageal Squamous Cell Carcinoma Treated with Combination Cytotoxic Chemotherapy.

BACKGROUND: There are no useful biomarkers for the clinical outcome of advanced esophageal squamous cell carcinoma (ESCC). In this study, we aimed to investigate the prognostic value of soluble PD-L1 (sPD-L1) in serum of patients with locally advanced or metastatic ESCC who received cytotoxic chemotherapy as first-line treatment. MATERIALS AND METHODS: This study evaluated the expression pattern of PD-L1 by immunohistochemistry and sPD-L1 concentration, and correlation with clinicopathological factors and overall survival (OS) in 190 patients with ESCC. RESULTS: sPD-L1 concentration was highly expressed in ESCC, especially in female patients. Patients with a high sPD-L1 level (≥0.63 ng/mL) had a shorter OS than those with a low sPD-L1 level (<0.63 ng/mL). In a multivariate analysis, high sPD-L1 concentration remained an independent prognostic factor of OS after adjustment for possible confounders. However, tissue PD-L1 expression level was non-prognostic in this study. CONCLUSION: There was no significant correlation between serum sPD-L1 concentration and tissue PD-L1 expression level. sPD-L1 concentration before treatment could be an effective and convenient biomarker of prognosis in patients with locally advanced or metastatic ESCC treated with combination cytotoxic chemotherapy.