TONSL promotes lung adenocarcinoma progression, immune escape and drug sensitivity.

PURPOSE: The tonsoku-like DNA repair protein (TONSL) encoded by the TONSL gene, located on chromosome 8q24.3, is crucial for repairing DNA double-strand breaks through homologous recombination. However, TONSL overexpression in lung adenocarcinoma (LUAD) promotes tumor development, leading to a poor prognosis. METHODS: TONSL was verified as a reliable prognostic marker for LUAD using bioinformatics, and clinical features related to LUAD prognosis were screened from the TCGA database to establish the relationship between risk factors and TONSL expression. In addition, TONSL expression in normal and LUAD tissues was verified using real-time quantitative polymerase chain reaction and immunohistochemistry. To elucidate the possible functions of TONSL, TONSL-related differentially expressed genes were screened, and functional enrichment analysis was performed. Subsequently, siRNA was used to knock down TONSL expression in lung cancer cells for cytobehavioral experiments. The effects of TONSL expression on tumor immune escape were analyzed using the ESTIMATE algorithm and tumor immune-infiltration analysis. In addition, the half-maximal inhibitory concentration of LUAD with varying TONSL expression levels in response to first-line chemotherapeutic drugs and epidermal growth factor receptor-tyrosine kinase inhibitors was analyzed for drug sensitivity. RESULTS: Up-regulation of TONSL in LUAD promotes the proliferation, migration, and invasion of lung cancer cells, thereby contributing to a poor prognosis. Furthermore, TONSL overexpression promotes immune escape and drug sensitivity in LUAD. CONCLUSION: TONSL serves as a reliable prognostic marker for LUAD, and its up-regulation is associated with increased immune escape and drug sensitivity. These findings suggest that TONSL holds potential as a novel therapeutic target for LUAD.

TGF-ß-induced lncRNA TBUR1 promotes EMT and metastasis in lung adenocarcinoma via hnRNPC-mediated GRB2 mRNA stabilization.

The transforming growth factor-ß (TGF-ß) signaling pathway is pivotal in inducing epithelial-mesenchymal transition (EMT) and promoting cancer metastasis. Long non-coding RNAs (lncRNAs) have emerged as significant players in these processes, yet their precise mechanisms remain elusive. Here, we demonstrate that TGF-ß-upregulated lncRNA 1 (TBUR1) is significantly activated by TGF-ß via Smad3/4 signaling in lung adenocarcinoma (LUAD) cells. Functionally, TBUR1 triggers EMT, enhances LUAD cell migration and invasion in vitro, and promotes metastasis in nude mice. Mechanistically, TBUR1 interacts with heterogeneous nuclear ribonucleoproteins C (hnRNPC) to stabilize GRB2 mRNA in an m6A-dependent manner. Clinically, TBUR1 is upregulated in LUAD tissues and correlates with poor prognosis, highlighting its potential as a prognostic biomarker and therapeutic target for LUAD. Taken together, our findings underscore the crucial role of TBUR1 in mediating TGF-ß-induced EMT and metastasis in LUAD, providing insights for future therapeutic interventions.

Peptidyl-prolyl isomerase F as a prognostic biomarker associated with immune infiltrates and mitophagy in lung adenocarcinoma.

Background: Lung adenocarcinoma (LUAD) is among the most prevalent malignancies worldwide, with unfavorable treatment outcomes. Peptidyl-prolyl isomerase F (PPIF) is known to influence the malignancy traits of tumor progression by modulating the bioenergetics and mitochondrial permeability in cancer cells; however, its role in LUAD remains unclear. Our study seeks to investigate the clinical significance, tumor proliferation, and immune regulatory functions of PPIF in LUAD. Methods: The expression of PPIF in LUAD tissues and cells was assessed using bioinformatics analysis, immunohistochemistry (IHC), and Western blotting. Survival curve analysis was conducted to examine the prognostic association between PPIF expression and LUAD. The immunomodulatory role of PPIF in LUAD was assessed through the analysis of PPIF expression and immune cell infiltration. A series of gain- and loss-of-function experiments were conducted on PPIF to investigate its biological functions in LUAD both in vitro and in vivo. The mechanisms underlying PPIF's effects on LUAD were delineated through functional enrichment analysis and Western blotting assays. Results: PPIF exhibited overexpression in LUAD tissues compared to normal controls. Survival curve analysis revealed that patients with LUAD exhibiting higher PPIF expression demonstrated decreased overall survival and a shorter progression-free interval. PPIF was implicated in modulating immune cell infiltration, particularly in regulating the T helper 1-T helper 2 cell balance. Functionally, PPIF was discovered to promote tumor cell proliferation and advance cell-cycle progression. Furthermore, PPIF could impede mitophagy by targeting the FOXO3a/PINK1-Parkin signaling pathway. Conclusions: The findings of this study indicate that the prognosis-related gene PPIF may have a significant role in the regulation of LUAD cell proliferation, tumor-associated immune cell infiltration, and mitophagy, and thus PPIF may be a promising therapeutic target of LUAD.

PSME3 promotes lung adenocarcinoma development by regulating the TGF-ß/SMAD signaling pathway.

Background: Lung adenocarcinoma (LUAD) is one of the most common types of cancer worldwide. Proteasome activator subunit 3 (PSME3) is a subunit of a proteasome activator, and changes in PSME3 can lead to the development of many diseases in organisms. However, the specific mechanism of PSME3 in LUAD has not yet been elucidated. This study initially revealed the mechanism of PSME3 promoting the progression of lung adenocarcinoma, which provided a potential molecular target for clinical treatment. Methods: PSME3 expression in LUAD cells and tissues was assessed by bioinformatics analysis, immunohistochemistry (IHC), Western blotting (WB), and quantitative real time polymerase chain reaction (qRT-PCR). A series of functional experiments were used to evaluate the effects of PSME3 knockdown and overexpression on LUAD cell proliferation, migration, and apoptosis. The potential mechanism of PSME3 was explored by transcriptome sequencing and WB experiments. Results: In this study, our initial findings indicated that PSME3 expression was abnormally high in LUAD and was associated with poor patient prognosis. Further, we found that the downregulation of PSME3 significantly inhibited LUAD cell proliferation, an effect that was verified by subcutaneous tumor formation experiments in nude mice. Similarly, the rate of invasion and migration of LUAD cells significantly decreased after the downregulation of PSME3. Using flow cytometry, we found that the knockdown of PSME3 caused cell cycle arrest at the G1/S phase. Through transcriptome sequencing, we found that the transforming growth factor-beta (TGF-ß)/SMAD signaling pathway was closely related to LUAD, and we then validated the pathway using WB assays. Conclusions: We demonstrated that PSME3 was abnormally highly expressed in LUAD and related to poor patient prognosis; therefore, targeting PSME3 in the treatment of LUAD may represent a novel therapeutic approach.

Bioinformatics analysis of an immunotherapy responsiveness-related gene signature in predicting lung adenocarcinoma prognosis.

Background: Immune therapy has become first-line treatment option for patients with lung cancer, but some patients respond poorly to immune therapy, especially among patients with lung adenocarcinoma (LUAD). Novel tools are needed to screen potential responders to immune therapy in LUAD patients, to better predict the prognosis and guide clinical decision-making. Although many efforts have been made to predict the responsiveness of LUAD patients, the results were limited. During the era of immunotherapy, this study attempts to construct a novel prognostic model for LUAD by utilizing differentially expressed genes (DEGs) among patients with differential immune therapy responses. Methods: Transcriptome data of 598 patients with LUAD were downloaded from The Cancer Genome Atlas (TCGA) database, which included 539 tumor samples and 59 normal control samples, with a mean follow-up time of 29.69 months (63.1% of patients remained alive by the end of follow-up). Other data sources including three datasets from the Gene Expression Omnibus (GEO) database were analyzed, and the DEGs between immunotherapy responders and nonresponders were identified and screened. Univariate Cox regression analysis was applied with the TCGA cohort as the training set and GSE72094 cohort as the validation set, and least absolute shrinkage and selection operator (LASSO) Cox regression were applied in the prognostic-related genes which fulfilled the filter criteria to establish a prognostic formula, which was then tested with time-dependent receiver operating characteristic (ROC) analysis. Enriched pathways of the prognostic-related genes were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, and tumor immune microenvironment (TIME), tumor mutational burden, and drug sensitivity tests were completed with appropriate packages in R (The R Foundation of Statistical Computing). Finally, a nomogram incorporating the prognostic formula was established. Results: A total of 1,636 DEGs were identified, 1,163 prognostic-related DEGs were extracted, and 34 DEGs were selected and incorporated into the immunotherapy responsiveness-related risk score (IRRS) formula. The IRRS formula had good performance in predicting the overall prognoses in patients with LUAD and had excellent performance in prognosis prediction in all LUAD subgroups. Moreover, the IRRS formula could predict anticancer drug sensitivity and immunotherapy responsiveness in patients with LUAD. Mechanistically, immune microenvironments varied profoundly between the two IRRS groups; the most significantly varied pathway between the high-IRRS and low-IRRS groups was ribonucleoprotein complex biogenesis, which correlated closely with the TP53 and TTN mutation burdens. In addition, we established a nomogram incorporating the IRRS, age, sex, clinical stage, T-stage, N-stage, and M-stage as predictors that could predict the prognoses of 1-year, 3-year, and 5-year survival in patients with LUAD, with an area under curve (AUC) of 0.718, 0.702, and 0.68, respectively. Conclusions: The model we established in the present study could predict the prognosis of LUAD patients, help to identify patients with good responses to anticancer drugs and immunotherapy, and serve as a valuable tool to guide clinical decision-making.

Correlation analysis between driver gene mutation and clinicopathological features in lung adenocarcinoma based on real-world cumulative clinical data.

Background: Driver genes are essential predictors of targeted therapeutic efficacy. Detecting driver gene mutations in lung adenocarcinoma (LUAD) patients can help to screen for targeted drugs and improve patient survival benefits. This study aims to investigate the mutation characterization of driver genes and their correlation with clinicopathological features in LUAD. Methods: A total of 440 LUAD patients were selected from Sir Run Run Shaw Hospital between July 2019 and September 2022. Postoperative tissue specimens were analyzed for gene mutations using next-generation sequencing technology, focusing, including epidermal growth factor receptor EGFR, ALK, ROS1, RET, KRAS, MET, BRAF, HER2, PIK3CA and NRAS. At the same time, clinicopathological data were collected and organized for multidimensional correlation analysis. Results: Of 440 LUAD patients, driver gene mutations were not detected in 48 patients. The proportion of patients with driver gene mutations was as high as 89.09%. The top three driver genetic mutations were EGFR, KRAS, and MET. Sixty-nine types of EGFR mutations were detected and distributed in the protein tyrosine kinase catalytic domain (56, 81.16%), Furin-like cysteine-rich region (9, 13.04%), receptor binding domain (3, 4.35%), and EGFR transmembrane domain (1, 1.45%). Single gene locus mutation occurred in 343 LUAD patients, but the mutation gene types covered all tested genes. Our findings showed that EGFR mutations were more commonly observed in non-smoking and female patients (P<0.01), KRAS mutations were more prevalent in male patients and smokers (P<0.01), ROS1 mutations had larger tumor diameters (P<0.01) and RET mutations were more prevalent in smokers (P<0.05). Conclusions: LUAD patients exhibit diverse genetic mutations, which may co-occur simultaneously. Integrated analysis of multiple mutations is essential for accurate diagnosis and effective treatment of the disease. The use of NGS can significantly expand our understanding of gene mutations and facilitate integrated analysis of multiple gene mutations, providing critical evidence for targeted treatment methods.

LncRNA CYTOR knockdown inhibits tumor development via regulating miR-503-5p/PCSK9 in lung adenocarcinoma.

BACKGROUND: The intricate biological mechanism underlying lung adenocarcinoma (LUAD), characterized by a deficiency of distinctive biomarkers, remain elusive. The presence of Long non-coding RNAs (lncRNAs) have been established to play a role in carcinogenesis. Nevertheless, the regulatory effects and mechanisms of lncRNA CYTOR in LUAD have yet to be elucidated. METHODS: In this study, RT-qPCR and Western blot were adopted to examine gene mRNA and protein expression, respectively. Cell proliferation was evaluated by CCK-8 assays. Transwell was performed to assay cell migration and invasion. The function of CYTOR in vivo was investigated through a xenograft animal model. RESULTS: We observed an apparent upregulation of CYTOR in LUAD. Silencing CYTOR significantly reduced proliferation, migration, and invasion capabilities of LUAD cells. Mechanism analysis indicated that CYTOR targeted the miR-503-5p/PCSK9 axis. Additionally, inhibiting of miR-503-5p partially reversed the inhibitory effects of CYTOR silencing on the malignant progression of LUAD cells. Animal experiments revealed that CYTOR/miR-503-5p/PCSK9 curbed tumor formation of nude mice in vivo. CONCLUSION: These findings demonstrated that lncRNA CYTOR acted as an oncogene in LUAD, regulating tumor malignant progression through the miR-503-5p/PCSK9 axis. This study unveiled a new regulation mechanism of LUAD progression, offering potential therapeutic targets for LUAD.

Downregulation of Splicing Factor PTBP1 Curtails FBXO5 Expression to Promote Cellular Senescence in Lung Adenocarcinoma.

Polypyrimidine tract-binding protein 1 (PTBP1) plays an essential role in splicing and post-transcriptional regulation. Moreover, PTBP1 has been implicated as a causal factor in tumorigenesis. However, the involvement of PTBP1 in cellular senescence, a key biological process in aging and cancer suppression, remains to be clarified. Here, it is shown that PTBP1 is associated with the facilitation of tumor growth and the prognosis in lung adenocarcinoma (LUAD). PTBP1 exhibited significantly increased expression in various cancer types including LUAD and showed consistently decreased expression in multiple cellular senescence models. Suppression of PTBP1 induced cellular senescence in LUAD cells. In terms of molecular mechanisms, the silencing of PTBP1 enhanced the skipping of exon 3 in F-box protein 5 (FBXO5), resulting in the generation of a less stable RNA splice variant, FBXO5-S, which subsequently reduces the overall FBXO5 expression. Additionally, downregulation of FBXO5 was found to induce senescence in LUAD. Collectively, these findings illustrate that PTBP1 possesses an oncogenic function in LUAD through inhibiting senescence, and that targeting aberrant splicing mediated by PTBP1 has therapeutic potential in cancer treatment.

GNPNAT1 Serves as a Prognostic Biomarker Correlated with Immune Infiltration and Promotes Cancer Cell Metastasis through Stabilization of Snai2 in Lung Adenocarcinoma.

BACKGROUND: Lung cancer is a common malignant tumor with high morbidity and mortality rate. Glucosamine 6-phosphate N-acetyltransferase (GNPNAT1), which serves as a critical enzyme in hexosamine biosynthetic pathway (HBP), has been identified as a metastasis-associated gene and is upregulated in lung adenocarcinoma (LUAD). However, the exact role and related mechanism of GNPNAT1 in LUAD metastasis remain unknown. METHODS: We analyzed the expression of GNPNAT1 in the public databases and confirmed the results by immunohistochemistry (IHC). The biological functions of GNPNAT1 in LUAD were investigated based on The Cancer Genome Atlas (TCGA). Correlations between GNPNAT1 and cancer immune characteristics were analyzed via the Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data (ESTIMATE) and Cell-type Identification by Estimating Relative Subsets of RNA Transcript (CIBERSORT) R package. The underlying mechanisms of altered GNPNAT1 expression on LUAD cell tumorigenesis, proliferation, migration, invasion, and metastasis were explored in vitro and in vivo. RESULTS: We demonstrated that GNPNAT1 expression was significantly increased in LUAD and negatively associated with the overall survival (OS) of patients. hsa-miR-1-3p and hsa-miR-26a-5p were identified as upstream miRNA targets of GNPNAT1. GNPNAT1 was associated with the infiltration levels of CD8 T cells, memory-activated CD4 T cells, NK cells resting, macrophages M0, macrophages M1, neutrophils, gamma delta T cells, and eosinophils, while it was negatively correlated with memory-resting CD4 T cells, regulatory T cells (Tregs), resting NK cells, monocytes, resting dendritic cells, and resting mast cells. GNPNAT1 knockdown significantly inhibited proliferation, migration, invasion, epithelial-mesenchymal transition (EMT) process, and metastasis of LUAD cells, while overexpression of GNPNAT1 revealed the opposite effects. Rescue assay showed that Snai2 knockdown reversed GNPNAT1-induced LUAD cells migration, invasion, and EMT. Mechanistically, GNPNAT1 promoted cancer cell metastasis via repressing ubiquitination degradation of Snai2 in LUAD. CONCLUSIONS: Taken together, these data indicate that GNPNAT1 serves as a prognostic biomarker for LUAD patient. Additionally, GNPNAT1 is critical for promoting tumorigenesis and metastasis of LUAD cells and may be a potential therapeutic target for preventing LUAD metastasis.

Specific association of MTHFD1 expressions with small cell lung cancer development and chemoradiotherapy outcome.

OBJECTIVES: To identify biomarkers that can discriminated small cell lung cancer (SCLC) from non-SCLC (NSCLC), and explore their association with the prognosis of SCLC under chemoradiotherapy. METHODS: The GSE40275 dataset was used to identify potential targets in SCLC. There were 196 patients of lung cancer (LC) in cohort 1 of this study. MTHFD1 levels in tissues were determined by immunohistochemistry assay in cohort 1. Lung cancer patients who were all underwent local chemoradiotherapy (CRT) were included in cohort 2, and the association of MTHFD1 levels with CRT treatment outcome were determined in cohort 2. Cell experiments were used to determine the function of MTHFD1 on the radio-sensitivity of SCLC and NSCLC cells. RESULTS: The MTHFD1 levels in LC tissues were increased, and could discriminate SCLC from both lung squamous cell carcinoma (LUSC) and lung adenocarcinoma (LUAD). Small cell lung cancer patients with MTHFD1 high phenotype had a poorer prognosis after CRT treatment, whereas no significant correlation was found between MTHFD1 levels and prognosis in LUSC and LUAD group. Cell experiments demonstrated that overexpression of MTHFD1 increases radio-resistance in both SCLC and NSCLC in vitro. CONCLUSION: MTHFD1 expressions might be a novel specifically prognostic biomarker for SCLC and the CRT treatment outcome.

Identification of a combined hypoxia and lactate metabolism prognostic signature in lung adenocarcinoma : Author.

BACKGROUND: In the tumor microenvironment (TME), a bidirectional relationship exists between hypoxia and lactate metabolism, with each component exerting a reciprocal influence on the other, forming an inextricable link. The aim of the present investigation was to develop a prognostic model by amalgamating genes associated with hypoxia and lactate metabolism. This model is intended to serve as a tool for predicting patient outcomes, including survival rates, the status of the immune microenvironment, and responsiveness to therapy in patients with lung adenocarcinoma (LUAD). METHODS: Transcriptomic sequencing data and patient clinical information specific to LUAD were obtained from comprehensive repositories of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A compendium of genes implicated in hypoxia and lactate metabolism was assembled from an array of accessible datasets. Univariate and multivariate Cox regression analyses were employed. Additional investigative procedures, including tumor mutational load (TMB), microsatellite instability (MSI), functional enrichment assessments and the ESTIMATE, CIBERSORT, and TIDE algorithms, were used to evaluate drug sensitivity and predict the efficacy of immune-based therapies. RESULTS: A novel prognostic signature comprising five lactate and hypoxia-related genes (LHRGs), PKFP, SLC2A1, BCAN, CDKN3, and ANLN, was established. This model demonstrated that LUAD patients with elevated LHRG-related risk scores exhibited significantly reduced survival rates. Both univariate and multivariate Cox analyses confirmed that the risk score was a robust prognostic indicator of overall survival. Immunophenotyping revealed increased infiltration of memory CD4 + T cells, dendritic cells and NK cells in patients classified within the high-risk category compared to their low-risk counterparts. Higher probability of mutations in lung adenocarcinoma driver genes in high-risk groups, and the MSI was associated with the risk-score. Functional enrichment analyses indicated a predominance of cell cycle-related pathways in the high-risk group, whereas metabolic pathways were more prevalent in the low-risk group. Moreover, drug sensitivity analyses revealed increased sensitivity to a variety of drugs in the high-risk group, especially inhibitors of the PI3K-AKT, EGFR, and ELK pathways. CONCLUSIONS: This prognostic model integrates lactate metabolism and hypoxia parameters, offering predictive insights regarding survival, immune cell infiltration and functionality, as well as therapeutic responsiveness in LUAD patients. This model may facilitate personalized treatment strategies, tailoring interventions to the unique molecular profile of each patient's disease.

Single cell transcriptomic analysis reveals tumor immune infiltration by NK cells gene signature in lung adenocarcinoma.

Background: Natural Killer (NK) cells are vital components of the innate immune system, crucial for combating infections and tumor growth, making them pivotal in cancer prognosis and immunotherapy. We sought to understand the diverse characteristics of NK cells within lung adenocarcinoma (LUAD) by conducting single-cell RNA sequencing analyses. Methods: Using the scRNA-seq dataset for multiple primary lung cancers (MPLCs), we examined two major NK cell groups, NK1 and NK2, comparing the expression profiles of 422 differentially expressed NK signature genes. We identified eight genes (SPON2, PLEKHG3, CAMK2N1, RAB27B, CTBP2, EFHD2, GOLM1, and PLOD1) that distinguish NK1 from NK2 cells. A prognostic signature, the NK gene signature (NKGS) score, was established through LASSO Cox regression. High NKGS scores were linked to poorer overall survival in TCGA-LUAD patients and consistently validated in other datasets (GSE31210 and GSE14814). Results: Functional analysis revealed an enrichment of genes related to the TGF-ß signaling pathway in the high NKGS score group. Moreover, a high NKGS score correlated with an immunosuppressive tumor microenvironment (TME) driven by immune evasion mechanisms. We also observed reduced T-cell receptor (TCR) repertoire diversity in the high-risk NKGS group, indicating a negative association between inflammation and risk score. Conclusion: This study introduced the innovative NKGS score, differentiating NK1 from NK2 cells. High NKGS scores were associated with the TGF-ß pathway and provided insights into LUAD prognosis and immune activities.

Spinosad blocks CHRNA5 mediated EGFR signaling pathway activation to inhibit lung adenocarcinoma proliferation.

Lung adenocarcinoma (LUAD) is the leading cause of cancer death worldwide, with high incidence and low survival rates. Nicotinic acetylcholine receptors play an important role in the progression of LUAD. In this study, a screening of 17 nicotinic acetylcholine receptor allosteric agents revealed that spinosad effectively suppressed the proliferation of LUAD cells. The experiments demonstrated that spinosad induced cell cycle arrest in the G1 phase and stimulated apoptosis, thereby impeding the growth of LUAD and enhancing the responsiveness to gefitinib in vitro and vivo. Mechanistic insights obtained through transcriptome sequencing, Co-IP, and protein immunoblots indicated that spinosad disrupted the interaction between CHRNA5 and EGFR, thereby inhibiting the formation of downstream complexes and activation of the EGFR signaling pathway. The supplementation of exogenous acetylcholine showed to mitigate the inhibition of LUAD cell proliferation induced by spinosad. This study elucidates the therapeutic effects and mechanisms of spinosad in LUAD, and offers a theoretical and experimental foundation for novel LUAD treatments.

Advancing lung adenocarcinoma prognosis and immunotherapy prediction with a multi-omics consensus machine learning approach.

Lung adenocarcinoma (LUAD) is a tumour characterized by high tumour heterogeneity. Although there are numerous prognostic and immunotherapeutic options available for LUAD, there is a dearth of precise, individualized treatment plans. We integrated mRNA, lncRNA, microRNA, methylation and mutation data from the TCGA database for LUAD. Utilizing ten clustering algorithms, we identified stable multi-omics consensus clusters (MOCs). These data were then amalgamated with ten machine learning approaches to develop a robust model capable of reliably identifying patient prognosis and predicting immunotherapy outcomes. Through ten clustering algorithms, two prognostically relevant MOCs were identified, with MOC2 showing more favourable outcomes. We subsequently constructed a MOCs-associated machine learning model (MOCM) based on eight MOCs-specific hub genes. Patients characterized by a lower MOCM score exhibited better overall survival and responses to immunotherapy. These findings were consistent across multiple datasets, and compared to many previously published LUAD biomarkers, our MOCM score demonstrated superior predictive performance. Notably, the low MOCM group was more inclined towards 'hot' tumours, characterized by higher levels of immune cell infiltration. Intriguingly, a significant positive correlation between GJB3 and the MOCM score (R = 0.77, p < 0.01) was discovered. Further experiments confirmed that GJB3 significantly enhances LUAD proliferation, invasion and migration, indicating its potential as a key target for LUAD treatment. Our developed MOCM score accurately predicts the prognosis of LUAD patients and identifies potential beneficiaries of immunotherapy, offering broad clinical applicability.

Hyper-methylation and DNMT3A mediated LTC4S downregulation promoted lung adenocarcinoma tumorigenesis via mTORC1 signaling pathway.

Background: Lung adenocarcinoma is a malignancy characterized by high mortality rates and unfavorable prognosis. However, the role of Leukotriene C4 Synthase (LTC4S) in lung cancer remains uninvestigated. Methods: The expression and prognostic value of LTC4S in LUAD were analyzed using the GEPIA online database. Subsequently, the function of LTC4S in lung cancer cells was examined through gain-of function experiments, using assays to evaluate tumor malignant behavior. Subcutaneous xenograft experiments in vivo was used for investigating the functions of LTC4S. Then, tumor hallmark pathways were analyzed by GSEA. Western blot assay was used to validate the impact of LTC4S on mTORC1 pathway. Finally, the correlation of mRNA and methylation of LTC4S were analyzed by cBioPortal. qRT-PCR, ChIP-qPCR and ChIP-Atlas were used to verify the regulation factors of LTC4S low expression in LUAD cells. Results: LTC4S presented significant decreased expression and favorable prognostic significance in LUAD. LTC4S was correlated with clinical stages in LUAD, which showed decreased expression gradually and significantly along with TNM stages. LTC4S-co-expressed genes were closely related to Ras signaling pathway, and MAPK signaling pathway. Overexpression of LTC4S inhibited cancer malignant phenotype and tumor growth in vitro and vivo. GSEA analysis and Western blot assay suggested low expression of LTC4S activated mTORC1 signaling pathway in LUAD. Moreover, the DNA methylation level of LTC4S in LUAD tissue was markedly elevated compared to normal tissue. The hypermethylation of the LTC4S promoter by DNMT3A leads to the decreased expression of LTC4S in LUAD. Conclusions: In conclusion, low expression of LTC4S serves as an unfavorable prognostic marker and the critical function of LTC4S in controlling the progression of LUAD. This highlights the promise for exploring the clinical benefits of manipulating LTC4S in LUAD targeted therapies.

Knockdown of GNL3 inhibits LUAD cell growth by regulating Wnt-ß-catenin pathway.

BACKGROUND: Lung adenocarcinoma (LUAD) is a leading cause of tumor-associated mortality, and it is needed to find new target to combat this disease. Guanine nucleotide-binding -protein-like 3 (GNL3) mediates cell proliferation and apoptosis in several cancers, but its role in LUAD remains unclear. OBJECTIVE: To explore the expression and function of Guanine nucleotide-binding protein-like 3 (GNL3) in lung adenocarcinoma (LUAD) and its potential mechanism in inhibiting the growth of LUAD cells. METHODS: We evaluated the expression of GNL3 in LUAD tissues and its association with patient prognosis using databases and immunohistochemistry. Cell proliferation was assessed by CCK-8 assay as well as colony formation, while apoptosis was evaluated by FCM. The effect of GNL3 knockdown on the Wnt/ß-catenin axis was investigated by Immunoblot analysis. RESULTS: GNL3 is overexpressed in LUAD tissues and is correlated with poor prognosis. Knockdown of GNL3 significantly inhibited the growth as well as induced apoptosis in A549 as well as H1299 cells. Furthermore, we found that the inhibitory effect of GNL3 knockdown on LUAD cell growth is associated with the downregulation of the Wnt/ß-catenin axis. CONCLUSION: GNL3 is key in the progression of LUAD by metiating Wnt/ß-catenin axis. Targeting GNL3 may represent a novel therapeutic method for LUAD treatment.

The prognostic value of immune escape-related genes in lung adenocarcinoma.

Background: Lung cancer is one of the most common cancers in humans, and lung adenocarcinoma (LUAD) has become the most common histological type of lung cancer. Immune escape promotes progression of LUAD from the early to metastatic late stages and is one of the main obstacles to improving clinical outcomes for immunotherapy targeting immune detection points. Our study aims to explore the immune escape related genes that are abnormally expressed in lung adenocarcinoma, providing assistance in predicting the prognosis of lung adenocarcinoma and targeted. Methods: RNA data and related clinical details of patients with LUAD were obtained from The Cancer Genome Atlas (TCGA) database. Through weighted gene coexpression network analysis (WGCNA), 3112 key genes were screened and intersected with 182 immune escape genes obtained from a previous study to identify the immune escape-related genes (IERGs). The role of IERGs in LUAD was systematically explored through gene ontology (GO) and Kyoto Encyclopedia of Genes and Genome (KEGG) analyses, which were used to enrich the relevant pathways of IERGs. The least absolute shrinkage and selection operator (LASSO) algorithm and multivariate Cox regression analysis were used to identify the key prognostic genes, and a prognostic risk model was constructed. Estimation of Stromal and Immune Cells in Malignant Tumor Tissues Using Expression Data (ESTIMATE) and microenvironment cell populations (MCP) counter methods (which can accurately assess the amount of eight immune cell populations and two stromal cell groups) were used to analyze the tumor immune status of the high and low risk subgroups. The protein expression level of the differentially expressed genes in lung cancer samples was determined by using the Human Protein Atlas (HPA) database. A nomogram was constructed, and the prognostic risk model was verified via the Gene Expression Omnibus (GEO) datasets GSE72094 and GSE30219. Results: Twenty differentially expressed IERGs were obtained. GO analysis of these 20 IERGs revealed that they were mainly associated with the regulation of immune system processes, immune responses, and interferon-γ enrichment in mediating signaling pathways and apoptotic signaling pathways; meanwhile, KEGG analysis revealed that IERGs were associated with necroptosis, antigen processing and presentation, programmed cell death ligand 1 (PD-L1) expression and programmed cell death 1 (PD-1) pathway in tumors, cytokine-cytokine receptor interactions, T helper cell 1 (Th1) and Th2 differentiation, and tumor necrosis factor signaling pathways. Using LASSO and Cox regression analysis, we constructed a four-gene model that could predict the prognosis of patients with LUAD, and the model was validated with a validation cohort. The immunohistochemical results of the HPA database showed that AHSA1 and CEP55 had low expression in normal lung tissue but high expression in lung cancer tissue. Conclusions: We constructed an IERG-based model for predicting the prognosis of LUAD. Among the genes identified, CEP55 and AHSA1 may be potential prognostic and therapeutic targets, and reducing their expression may represent a novel approach in the treatment of LUAD.

Integrative metagenomic, transcriptomic, and proteomic analysis reveal the microbiota-host interplay in early-stage lung adenocarcinoma among non-smokers.

BACKGROUND: The incidence of early-stage lung adenocarcinoma (ES-LUAD) is steadily increasing among non-smokers. Previous research has identified dysbiosis in the gut microbiota of patients with lung cancer. However, the local microbial profile of non-smokers with ES-LUAD remains largely unknown. In this study, we systematically characterized the local microbial community and its associated features to enable early intervention. METHODS: A prospective collection of ES-LUAD samples (46 cases) and their corresponding normal tissues adjacent to the tumor (41 cases), along with normal lung tissue samples adjacent to pulmonary bullae in patients with spontaneous pneumothorax (42 cases), were subjected to ultra-deep metagenomic sequencing, host transcriptomic sequencing, and proteomic sequencing. The obtained omics data were subjected to both individual and integrated analysis using Spearman correlation coefficients. RESULTS: We concurrently detected the presence of bacteria, fungi, and viruses in the lung tissues. The microbial profile of ES-LUAD exhibited similarities to NAT but demonstrated significant differences from the healthy controls (HCs), characterized by an overall reduction in species diversity. Patients with ES-LUAD exhibited local microbial dysbiosis, suggesting the potential pathogenicity of certain microbial species. Through multi-omics correlations, intricate local crosstalk between the host and local microbial communities was observed. Additionally, we identified a significant positive correlation (rho > 0.6) between Methyloversatilis discipulorum and GOLM1 at both the transcriptional and protein levels using multi-omics data. This correlated axis may be associated with prognosis. Finally, a diagnostic model composed of six bacterial markers successfully achieved precise differentiation between patients with ES-LUAD and HCs. CONCLUSIONS: Our study depicts the microbial spectrum in patients with ES-LUAD and provides evidence of alterations in lung microbiota and their interplay with the host, enhancing comprehension of the pathogenic mechanisms that underlie ES-LUAD. The specific model incorporating lung microbiota can serve as a potential diagnostic tool for distinguishing between ES-LUAD and HCs.

KLRB1 expression is associated with lung adenocarcinoma prognosis and immune infiltration and regulates lung adenocarcinoma cell proliferation and metastasis through the MAPK/ERK pathway.

Background: Lung cancer is the most common primary malignant tumor of the lung, and as one of the malignant tumors that pose the greatest threat to the health of the population, the incidence rate has remained high in recent years. Previous studies have shown that KLRB1 is transcriptionally repressed in lung adenocarcinoma and correlates with lung adenocarcinoma prognosis. The objective of this study is to investigate the intrinsic mechanisms by which KLRB1 affects the malignant phenotypes of lung adenocarcinoma such as immune infiltration, proliferation, growth and metastasis. Methods: We assessed the expression levels of KLRB1 in publicly available databases and investigated its associations with clinical and pathological variables. Enrichment analysis was subsequently conducted to investigate possible signaling pathways and their associated biological functions. Statistical analysis, including Spearman correlation and the application of multigene prediction models, was utilized to assess the relationship between the expression of KLRB1 and the infiltration of immune cells. The diagnostic and prognostic value of KLRB1 was evaluated using Kaplan-Meier survival curves, diagnostic receptor operating characteristic (ROC) curves, histogram models, and Cox regression analysis. Specimens from lung adenocarcinoma (LUAD) patients were collected, the expression level of KLRB1 was detected by protein blotting analysis, and the expression level of KLRB1 was detected at the mRNA level by real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR). Small interfering RNA (siRNA) was used to silence gene expression, and Transwell, Cell Counting Kit-8 (CCK-8) and colony formation assays were subsequently performed to analyze the effects of KLRB1 on LUAD cell migration, invasion and proliferation. Results: KLRB1 expression was lower in lung cancer tissue than in surrounding healthy tissue. Genes differentially expressed in the low and high KLRB1 expression groups were found to be significantly enriched in pathways related to immunity. KLRB1 exerted an impact on the MAPK/ERK signaling pathway, thereby modulating the growth and proliferation of LUAD cells. KLRB1 expression is linked to prognosis, immune infiltration, and cell migration and proliferation in LUAD. Conclusions: The evidence revealed a correlation between KLRB1 and both prognosis and immune infiltration in LUAD patients.

Silencing of the long non-coding RNA LINC00265 triggers autophagy and apoptosis in lung cancer by reducing protein stability of SIN3A oncogene.

Background: Long non-coding RNAs are important regulators in cancer biology and function either as tumor suppressors or as oncogenes. Their dysregulation has been closely associated with tumorigenesis. LINC00265 is upregulated in lung adenocarcinoma and is a prognostic biomarker of this cancer. However, the mechanism underlying its function in cancer progression remains poorly understood. Methods: Here, the regulatory role of LINC00265 in lung adenocarcinoma was examined using lung cancer cell lines, clinical samples, and xenografts. Results: We found that high levels of LINC00265 expression were associated with shorter overall survival rate of patients, whereas knockdown of LINC00265 inhibited proliferation of cancer cell lines and tumor growth in xenografts. Western blot and flow cytometry analyses indicated that silencing of LINC00265 induced autophagy and apoptosis. Moreover, we showed that LINC00265 interacted with and stabilized the transcriptional co-repressor Switch-independent 3a (SIN3A), which is a scaffold protein functioning either as a tumor repressor or as an oncogene in a context-dependent manner. Silencing of SIN3A also reduced proliferation of lung cancer cells, which was correlated with the induction of autophagy. These observations raise the possibility that LINC00265 functions to promote the oncogenic activity of SIN3A in lung adenocarcinoma. Conclusions: Our findings thus identify SIN3A as a LINC00265-associated protein and should help to understand the mechanism underlying LINC00265-mediated oncogenesis.