Insufficient T-cell infiltration is a major barrier to the efficacy of immune checkpoint inhibitors (ICIs) in lung adenocarcinoma (LUAD). We aimed to investigate how the tumor-intrinsic m5C methyltransferase NSUN2 shapes the immune landscape of LUAD. Nsun2 conditional knockout mice and syngeneic mice models were employed. Single-cell RNA sequencing (scRNA-seq) and m5C sequencing were performed to elucidate the downstream pathway regulated by NSUN2. LUAD specimens from patients receiving neoadjuvant immunotherapy were used to assess the correlation between NSUN2 expression and immune infiltration. Elevated tumoral NSUN2 expression was correlated with a marked lack of CD8+ T-cell infiltration and immunotherapy resistance. Mechanistically, NSUN2 enhances the translation of histone deacetylase HDAC8 in an m⁵C-YBX1-dependent manner, which in turn directly represses the transcription of the chemoattractant CCL5, thereby impairing CD8+ T-cell recruitment into the tumor. NSUN2 depletion reversed this immunosuppressive axis and converted immunologically “cold” tumors into “hot”. Tumor-targeted liposomes loaded with the NSUN2 inhibitor synergized with anti-PD-1 therapy to induce significant tumor regression. Our findings identify NSUN2 as a critical orchestrator of T-cell exclusion in LUAD. It serves as both a candidate predictive biomarker for ICI failure and a promising druggable target. Targeting NSUN2 offers a potential strategy to overcome immunotherapy resistance and improve clinical outcomes in LUAD patients.

Antibiotic resistance and biofilm formation have represented a major public health concern to the treatment of infectious diseases. Photodynamic therapy can not only generate toxic reactive oxygen species (ROS) to kill bacteria but also stimulate the immune response, which is less likely to induce bacterial resistance and represented as an effective antibacterial treatment. In this study, we presented a porphyrin (TPP) /ciprofloxacin (CIP) based supramolecular photosensitizer nanoparticles (TPP-CIP NPs) which could generate ROS, cascade release antibiotics, and trigger immune response for antibacterial, biofilm dispersion and wound healing via photodynamic-immunotherapy and enhanced antibiotic penetration. Upon light irradiation, the porphyrins in the system generated ROS and cleaved the thioketal linkers, releasing ciprofloxacin for killing antibiotic-sensitive bacteria that have developed because of the destruction of their external structure by ROS. Furthermore, the ROS simultaneously activated effective immune responses including the activation of dendritic cells and T cells. In vitro studies illustrated that the supramolecular nanoparticles exhibited effective antibacterial performance against both Gram-positive and Gram-negative bacteria, and biofilm dispersion capacity. In vivo studies confirmed TPP-CIP NPs possessed effective antibacterial effect and wound healing against methicillin resistant staphylococcus aureus infection. This research provides a promising synergistic strategy for combating multi-drug resistant bacterial infections.

BACKGROUND:Many studies have demonstrated the relationship between METTL3 protein expression and clinical outcomes in various cancers and elucidated the mechanism by which METTL3 disrupts the behavior of cancer cells. Here, we attempted to define the prognostic value of METTL3 protein in patients with cancer via systematic analysis and explored the potential effect of inhibiting METTL3 using its specific inhibitor. METHODS:We searched PubMed, Embase, and the Web of Science databases for studies that elucidated the prognostic value of METTL3 protein expression in all cancer types and then calculated the pooled hazard ratios with 95% confidence intervals for the overall survival (OS) of all cancer types and subgroups. Data from The Cancer Genome Atlas dataset were used to study METTL3 mRNA expression in cancers. Further, the effects of a METTL3-specific inhibitor were studied in cancer cells via the colony formation assay, the cell proliferation assay, and apoptosis detection. RESULTS:Meta-analysis of the 33 cohorts in 32 studies (3666 patients in total) revealed that higher METTL3 protein expression indicated poor OS in the majority of cancers. Bioinformatics analysis of METTL3 mRNA expression and cancer prognosis did not show the extremely prominent prognostic value of METTL3 mRNA. Nevertheless, the METTL3-specific inhibitor attenuated cell proliferation and cell cloning formation and promoted apoptosis. CONCLUSIONS:METTL3 protein expression is associated with poor prognosis in most cancer types and could be a biomarker for OS. Further, METTL3 inhibition might be a potential treatment strategy for cancers.

BACKGROUND:METTL3 plays a significant role as a catalytic enzyme in mediating N6-methyladenosine (m6A) modification, and its importance in tumour progression has been extensively studied in recent years. However, the precise involvement of METTL3 in the regulation of translation in non-small cell lung cancer (NSCLC) remains unclear.RESULTS:Here we discovered by clinical investigation that METTL3 expression is correlated with NSCLC metastasis. Ablation of METTL3 in NSCLC cells inhibits invasion and metastasis in vitro and in vivo. Subsequently, through translatomics data mining and experimental validation, we demonstrated that METTL3 enhances the translation of aromatase (CYP19A1), a key enzyme in oestrogen synthesis, thereby promoting oestrogen production and mediating the invasion and metastasis of NSCLC. Mechanistically, METTL3 interacts with translation initiation factors and binds to CYP19A1 mRNA, thus enhancing the translation efficiency of CYP19A1 in an m6A-dependent manner. Pharmacological inhibition of METTL3 enzymatic activity or translation initiation factor eIF4E abolishes CYP19A1 protein synthesis.CONCLUSIONS:Our findings indicate the crucial role of METTL3-mediated translation regulation in NSCLC and reveal the significance of METTL3/eIF4E/CYP19A1 signaling as a promising therapeutic target for anti-metastatic strategies against NSCLC.

Respiratory diseases are highly prevalent in the general population, and the morbidity, mortality, and healthcare burden on society at large have been on the rise worldwide. For example, lung cancer is a major contributor to cancer-related mortality around the globe, and identifying clinically relevant biomarkers for lung cancer detection at both early and metastatic stages has been a pressing need. Human metabolism is complicated and may vary with different individuals. Despite advances in the treatment and the early screening of respiratory diseases, most diagnoses are established at a late stage, i.e., when genetic and epigenetic changes have developed. A promising source of biomarkers indicative of the pathogenesis of respiratory diseases is exhaled breath condensate (EBC), a biological fluid and a natural matrix of the respiratory tract. Molecules, such as DNAs, RNAs, proteins, metabolites, and others, are found in EBC, and their presence/absence or changes in concentrations can serve as biomarkers. This review discusses the exhaled breath composition, candidate EBC biomarkers, and the potential to use EBC for diagnosing diseases, therapeutic monitoring, and screening high-risk individuals.

Intratumor heterogeneity significantly challenges the accuracy of existing prognostic models for esophageal squamous cell carcinoma (ESCC) by introducing biases related to the varied genetic and molecular landscapes within tumors. Traditional models, relying on single-sample, single-region bulk RNA sequencing, fall short of capturing the complexity of intratumor heterogeneity. To fill this gap, we developed a computational model for intratumor heterogeneity corrected signature (ITHCS) by employing both multiregion bulk and single-cell RNA sequencing to pinpoint genes that exhibit consistent expression patterns across different tumor regions but vary significantly among patients. Utilizing these genes, we applied multiple machine-learning algorithms for sophisticated feature selection and model construction. The ITHCS model significantly outperforms existing prognostic indicators in accuracy and generalizability, markedly reducing sampling biases caused by intratumor heterogeneity. This improvement is especially notable in the prognostic assessment of early-stage ESCC patients, where the model exhibits exceptional predictive power. Additionally, we found that the risk score based on ITHCS may be associated with epithelial-mesenchymal transition characteristics, indicating that high-risk patients may exhibit a diminished efficacy to immunotherapy.

The emergence of antimicrobial-resistant bacterial infections poses a significant threat to public health, necessitating the development of innovative and effective alternatives to antibiotics. Photodynamic therapy (PDT) and immunotherapy show promise in combating bacteria. However, PDT's effectiveness is hindered by its low specificity to bacteria, while immunotherapy struggles to eliminate bacteria in immunosuppressive environments. In this work, we introduce an innovative near-infrared antimicrobial nanoplatform (ZFC) driven by bacterial metabolism. ZFC, comprising d-cysteine-functionalized pentafluorophenyl bacteriochlorin (FBC-Cy) coordinated with Zn2+, is designed for antimicrobial photodynamic-immune therapy (aPIT) against systemic bacterial infections. By specifically targeting bacteria via d-amino acid incorporation into bacterial surface peptidoglycans during metabolism, ZFC achieves precise bacterial clearance in wound and pulmonary infections, exhibiting an antimicrobial efficacy of up to 90 % with minimal damage to normal cells under 750 nm light. Additionally, ZFC enhances the activation of antigen-presenting cells by 3.2-fold compared to control groups. Furthermore, aPIT induced by ZFC triggers systemic immune responses and establishes immune memory, resulting in a 1.84-fold increase in antibody expression against bacterial infections throughout the body of mice. In conclusion, aPIT prompted by ZFC presents a approach to treating bacterial infections, offering a broad-spectrum solution for systemic bacterial infections. STATEMENT OF SIGNIFICANCE: The new concept demonstrated focuses on an innovative near-infrared antimicrobial nanoplatform (ZFC) for antimicrobial photodynamic-immune therapy (aPIT), highlighting its reliance on bacterial metabolism and its non-damaging effect on normal tissues. ZFC efficiently targets deep-tissue bacterial infections by harnessing bacterial metabolism, thereby enhancing therapeutic efficacy while sparing normal tissues from harm. This approach not only clears bacterial infections effectively but also induces potent adaptive immune responses, leading to the eradication of distant bacterial infections. By emphasizing ZFC's unique mechanism driven by bacterial metabolism and its tissue-sparing properties, this work underscores the potential for groundbreaking advancements in antimicrobial therapy. Such advancements hold promise for minimizing collateral damage to healthy tissues, thereby improving treatment outcomes and mitigating the threat of antimicrobial resistance. This integrated approach represents a significant progress forward in the development of next-generation antimicrobial therapies with enhanced precision and efficacy.

In "immune-cold" tumors, the upregulation of immunosuppressive cells and insufficient infiltration of lymphocytes contribute to the resistance against immune therapy. Herein, we have developed a dual-enzyme-like photosensitive nanozyme (PBAF) to remodel the tumor immunosuppressive microenvironment (TIME) and induce the tumor infiltration of cytotoxic T lymphocytes (CTLs). Specifically, PBAF exhibits peroxidase (POD)-like activity and glutathione oxidase (GSHOx)-like activity and can be stimulated by 750 nm laser, promoting oxidative stress at the tumor site. Consequently, this process further leads to the reconstruction of TIME in animal experiments, inducing tumor-associated macrophages (TAMs) toward the immunostimulatory M1 phenotype, eliminating myeloid-derived suppressor cells (MDSCs) and regulatory T cells (Tregs). Simultaneously, PBAF also promotes dendritic cells (DCs) maturation to enhance CTLs infiltration into the tumor. The remodeled TIME and enhanced immune responses by PBAF demonstrate significant post-administration inhibition of recurrence and metastasis in the treatment of malignant tumors.

Objective Lung squamous cell carcinoma (LUSC) is associated with a low survival rate. Evidence suggests that bone morphogenetic proteins (BMPs) and their receptors (BMPRs) play crucial roles in tumorigenesis and progression. However, a comprehensive analysis of their role in LUSC is lacking. Our study aimed to explore the relationship between BMPs/BMPRs expression levels and the tumorigenesis and prognosis of LUSC. Methods The “R/Limma” package was utilized to analyze the differential expression characteristics of BMPs/BMPRs in LUSC, using data from TCGA, GTEx, and GEO databases. Concurrently, the “survminer” packages were employed to investigate their prognostic value and correlation with clinical features in LUSC. The core gene associated with LUSC progression was further explored through weighted gene correlation network analysis (WGCNA). LASSO analysis was conducted to construct a prognostic risk model for LUSC. Clinical specimens were examined by immunohistochemical analysis to confirm the diagnostic value in LUSC. Furthermore, based on the tumor immune estimation resource database and tumor-immune system interaction database, the role of the core gene in the tumor microenvironment of LUSC was explored. Results GDF10 had a significant correlation only with the pathological T stage of LUSC, and the protein expression level of GDF10 decreased with the tumorigenesis of LUSC. A prognostic risk model was constructed with GDF10 as the core gene and 5 hub genes ( HRASLS, HIST1H2BH, FLRT3, CHEK2 , and ALPL ) for LUSC. GDF10 showed a significant positive correlation with immune cell infiltration and immune checkpoint expression. Conclusion GDF10 might serve as a diagnostic biomarker reflecting the tumorigenesis of LUSC and regulating the tumor immune microenvironment to guide more effective treatment for LUSC.

Aberrant translation, a characteristic feature of cancer, is regulated by the complex and sophisticated RNA binding proteins (RBPs) in the canonical translation machinery. N6-methyladenosine (m(6)A) modifications are the most abundant internal modifications in mRNAs mediated by methyltransferase-like 3 (METTL3). METTL3 is commonly aberrantly expressed in different tumors and affects the mRNA translation of many oncogenes or dysregulated tumor suppressor genes in a variety of ways. In this review, we discuss the critical roles of METTL3 in translation regulation and how METTL3 and m(6)A reader proteins in collaboration with RBPs within the canonical translation machinery promote aberrant translation in tumorigenesis, providing an overview of recent efforts aiming to 'translate' these results to the clinic.

In non-small cell lung cancer (NSCLC), the heterogeneity promotes drug resistance, and the restricted expression of programmed death-ligand 1 (PD-L1) limits the immunotherapy benefits. Based on the mechanisms related to translation regulation and the association with PD-L1 of methyltransferase-like 3 (METTL3), the novel small-molecule inhibitor STM2457 is assumed to be useful for the treatment of NSCLC. We evaluated the efficacy of STM2457 in vivo and in vitro and confirmed the effects of its inhibition on disease progression. Next, we explored the effect of STM2457 on METTL3 and revealed its effects on the inhibition of catalytic activity and upregulation of METTL3 protein expression. Importantly, we described the genome-wide characteristics of multiple omics data acquired from RNA sequencing, ribosome profiling, and methylated RNA immunoprecipitation sequencing data under STM2457 treatment or METTL3 knockout. We also constructed a model for the regulation of the translation of METTL3 and PD-L1. Finally, we found PD-L1 upregulation by STM2457 in vivo and in vitro. In conclusion, STM2457 is a potential novel suppressor based on its inhibitory effect on tumor progression and may be able to overcome the heterogeneity based on its impact on the translatome. Furthermore, it can improve the immunotherapy outcomes based on PD-L1 upregulation in NSCLC.

In a previous study, our research group observed that estrogen promotes the metastasis of non‐small cell lung cancer (NSCLC) through the estrogen receptor β (ERβ). Invadopodia are key structures involved in tumor metastasis. However, it is unclear whether ERβ is involved in the promotion of NSCLC metastasis through invadopodia. In our study, we used scanning electron microscopy to observe the formation of invadopodia following the overexpression of ERβ and treatment with E2. In vitro experiments using multiple NSCLC cell lines demonstrated that ERβ can increase the formation of invadopodia and cell invasion. Mechanistic studies revealed that ERβ can upregulate the expression of ICAM1 by directly binding to estrogen‐responsive elements (EREs) located on the ICAM1 promoter, which in turn can enhance the phosphorylation of Src/cortactin. We also confirmed these findings in vivo using an orthotopic lung transplantation mouse model, which validated the results obtained from the in vitro experiments. Finally, we examined the expressions of ERβ and ICAM1 using immunohistochemistry in both NSCLC tissue and paired metastatic lymph nodes. The results confirmed that ERβ promotes the formation of invadopodia in NSCLC cells through the ICAM1/p‐Src/p‐Cortactin signaling pathway.

Lung adenocarcinoma (LUAD) is one of the malignant tumors worldwide. The purpose of this study is to identify the hub genes related to LUAD using bioinformatics analysis. Three gene expression datasets (GSE27262, GSE74706, GSE75037) were obtained from GEO database. Identification of DEGs was performed using GEO2R and constructed protein-protein interaction network using STRING and cytoscape. GO, KEGG and GSEA analysis were carried out through R package “clusterprofiler”. GEPIA was used to verify the survival of hub genes, UALCAN database and HPA database were used to determine protein expression, complemented by IHC staining results. Lastly, CCK-8 and colony formation assays were used to verify PC9 cell growth ability and we used western blot, Transwell and scratch wound assays for validation of PC9 cells migration and EMT markers. We identified 107 up-regulated genes and 344 down-regulated genes. Thirty hub genes were identified and the 12 hub genes with a rank of degrees > 30 are as follow: CCNA2, AURKA, HMMR, EZH2, TTK, TPX2, CCNB1, ANLN, ECT2, CEP55, MAD2L1 and PBK. CCNA2 as one of the genes having the highest node degree of 35 was chosen for subsequent analysis. Our findings indicated that high expression of CCNA2 had the highest enrichment effects on cell cycle and was associated with poor prognosis. CCK-8 and colony formation analysis further verified that CCNA2 contributed to the progression of LUAD and the protein expression was significantly elevated in tumor tissues compared to the normal lung tissues. In addition, high expression of CCNA2 is related to the EMT process and may play a role in EMT-induced metastasis in LUAD. Briefly, CCNA2 was identified as one of the hub genes and can promote lung cancer cell growth, migration and invasion via epithelial-mesenchymal transition. Moreover, could avail as a biomarker or therapeutic target to judge the prognosis of LUAD.

Esophageal cancer is one of the major life-threatening diseases in the world. RNA methylation is the most common post-transcriptional modification and a wide-ranging regulatory system controlling gene expression. Numerous studies have revealed that dysregulation of RNA methylation is critical for cancer development and progression. However, the diverse role of RNA methylation and its regulators in esophageal cancer remains to be elucidated and summarized. In this review, we focus on the regulation of major RNA methylation, including m 6A, m 5C, and m 7G, as well as the expression patterns and clinical implications of its regulators in esophageal cancer. We systematically summarize how these RNA modifications affect the "life cycle" of target RNAs, including mRNA, microRNA, long non-coding RNA, and tRNA. The downstream signaling pathways associated with RNA methylation during the development and treatment of esophageal cancer are also discussed in detail. Further studies on how these modifications function together in the microenvironment of esophageal cancer will draw a clearer picture of the clinical application of novel and specific therapeutic strategies.

Metastases contribute to the low survival rate of non-small cell lung cancer (NSCLC) patients. Targeting lipid metabolism for anticancer therapies is attractive. Accumulative evidence shows that stearoyl-CoA desaturases1 (SCD1), a key enzyme in lipid metabolism, enables tumor metastasis and the underlying mechanism remains unknown. In this study, immunohistochemical staining of 96 clinical specimens showed that the expression of SCD1 was increased in tumor tissues (p < 0.001). SCD1 knockdown reduced the migration and invasion of HCC827 and PC9 cells in transwell and wound healing assays. Aromatase (CYP19A1) knockdown eliminated cell migration and invasion caused by SCD1 overexpression. Western blotting assays demonstrated that CYP19A1, along with β-catenin protein levels, was reduced in SCD1 knocked-down cells, and estrogen concentration was reduced (p < 0.05) in cell culture medium measured by enzyme-linked immunosorbent assay. SCD1 overexpression preserving β-catenin protein stability was evaluated by coimmunoprecipitation and Western blotting. The SCD1 inhibitor A939572, and a potential SCD1 inhibitor, grape seed extract (GSE), significantly inhibited cell migration and invasion by blocking SCD1 and its downstream β-catenin, CYP19A1 expression, and estrogen concentration. In vivo tumor formation assay and a tail vein metastasis model indicated that knockdown of SCD1 blocked tumor growth and metastasis. In conclusion, SCD1 could accelerate metastasis by maintaining the protein stability of β-catenin and then promoting CYP19A1 transcription to improve estrogen synthesis. SCD1 is expected to be a promised therapeutic target, and its novel inhibitor, GSE, has great therapeutic potential in NSCLC.

Esophageal cancer (ESCA) is a lethal malignancy and is associated with the alterations of various genes and epigenetic modifications. The protein dpy-30 homolog (DPY30) is a core member of histone H3K4 methylation catalase and its dysfunction is associated with the occurrence and development of cancer. Therefore, the present study investigated the role of DPY30 in ESCA and evaluated the association between the expression of DPY30, the clinicopathological characteristics of ESCA and the tumor immune microenvironment. It conducted a comprehensive analysis of DPY30 in patients with ESCA using The Cancer Genome Atlas (TCGA) database and clinical tissue microarray specimens of ESCA. Immunohistochemistry was performed to assess the expression levels of DPY30 in tissues. Receiver operating curve analysis, Kaplan-Meier survival analysis and Cox regression analysis were performed to identify the diagnostic and prognostic value of DPY30. Gene Set Enrichment Analysis, protein-protein interaction network and Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression data were used to screen DPY30-associated genes and evaluate the immune score of the TCGA samples. The results demonstrated that the expression of mRNA and protein levels of DPY30 were significantly upregulated in tumor tissues compared with normal tissue samples. The expression of DPY30 was closely associated with the poor prognosis of patients with ESCA. The present study also found that DPY30 expression and the pathological characteristics of ESCA were significantly correlated. Additionally, the expression of DPY30 demonstrated a significant positive correlation with various immune cells infiltration. The results suggested that DPY30 might influence tumor immune infiltration. In conclusion, the findings suggested that DPY30 might be a potential prognostic biomarker and an immunotherapeutic target in ESCA.

Background:Comprehensive analysis of transcriptomic profiles of non-small cell lung cancer (NSCLC) may provide novel evidence for biomarkers associated with response to PD-1/PD-L1 immune checkpoint blockade (ICB).Methods:We utilized weighted gene co-expression network analysis (WGCNA) to analyze transcriptomic data from two NSCLC datasets from Gene Expression Omnibus (GSE135222 and GSE126044) that involved patients received ICB treatment. We evaluated the correlation of co-expression modules with ICB responsiveness and functionally annotated ICB-related modules using pathway enrichment analysis, single-cell RNA sequencing, flow cytometry and alternative splicing analysis. We built a risk score using Lasso-COX regression based on hub genes from ICB-related modules. We investigated the alteration of tumor microenvironment between high- and low- risk groups and the association of the risk score with previously established predictive biomarkers.Results:Our results identified a black with positive correlation and a blue module with negative correlation to ICB responsiveness. The black module was enriched in pathway of T cell activation and antigen processing and presentation, and the genes assigned to it were consistently expressed on myeloid cells. We observed decreased alternative splicing events in samples with high signature scores of the blue module. The Lasso-COX analysis screened out three genes (EVI2B, DHX9, HNRNPM) and constructed a risk score from the hub genes of the two modules. We validated the predictive value of the risk score for poor response to ICB therapy in an in-house NSCLC cohort and a pan-cancer cohort from the KM-plotter database. The low-risk group had more immune-infiltrated microenvironment, with higher frequencies of precursor exhausted CD8+ T cells, tissue-resident CD8+ T cells, plasmacytoid dendritic cells and type 1 conventional dendritic cells, and a lower frequency of terminal exhausted CD8+ T cells, which may explain its superior response to ICB therapy. The significant correlation of the risk score to gene signature of tertiary lymphoid structure also implicated the possible mechanism of this predictive biomarker.Conclusions:Our study identified two co-expression modules related to ICB responsiveness in NSCLC and developed a risk score accordingly, which could potentially serve as a predictive biomarker for ICB response.