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.

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.

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.

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.

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.

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.

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.

The role of EMG1 in lung adenocarcinoma progression: Implications for prognosis and immune cell infiltration.

BACKGROUND AND AIMS: Lung adenocarcinoma (LUAD) is the most common and aggressive cancer with a high incidence. N1-specific pseudouridine methyltransferase (EMG1), a highly conserved nucleolus protein, plays an important role in the biological development of ribosomes. However, the role of EMG1 in the progression of LUAD is still unclear. METHODS: The expression of EMG1 in LUAD cells, and LUAD tissues, and adjacent noncancerous tissues was quantified using real-time polymerase chain reaction (PCR) and western blotting. The roles of EMG1 in LUAD cell proliferation, migration, invasion and tumorigenicity were explored in vitro and in vivo. Western blot analysis to underlying molecular mechanism of EMG1 regulating the biological function of LUAD. EMG1 expression and its impact on tumor prognosis were analyzed using a range of databases including GEPIA, UALCAN, cBioPortal, LinkedOmics, and Kaplan-Meier Plotter. RESULTS: EMG1 expression was elevated in LUAD patients compared to normal tissues, and EMG1 expression was strongly correlated with prognosis in LUAD patients. EMG1 expression correlated with age, gender, N stage, T stage, and pathologic stage. EMG1 expression was strongly positively correlated with MRPL51, PHB2, SNRPG, ATP5MD, and TPI1, and strongly negatively correlated with MACF1, DOCK9, RAPGEF2, SYNJ1, and KIDINS220, the major enrichment pathways for EMG1 and related genes include Cell cycle, DNA Replication and Pathways in cancer signaling pathways. EMG1 expression level was significantly increased in LUAD cell lines and tissues. Knockdown of EMG1 could inhibit LUAD cell proliferation, migration, invasion, and tumorigenicity. Besides, EMG1 overexpression could promote LUAD cell proliferation, migration, and invasion. High expression of EMG1 predicts poor prognosis in LUAD patients, and EMG1 may play an oncogenic role in the tumor microenvironment by participating in the infiltration of LUAD immune cells. CONCLUSIONS: EMG1 regulated various functions in LUAD by directly mediating Akt/mTOR/p70s6k signaling pathways activation. The results suggest that EMG1 may be a novel biomarker for assessing prognosis and immune cell infiltration in LUAD.

Identification of a novel prognostic signature based on vitamin metabolism clustering-related genes in lung adenocarcinoma.

Background: Vitamins, and their metabolic processes play essential regulatory roles in controlling proliferation, differentiation, and growth in carcinogenesis. However, the role of vitamin metabolism in lung adenocarcinoma (LUAD) has rarely been reported. Here, we established a novel prognostic model based on vitamin metabolism-related genes in LUAD. Methods: In this research, we aimed to identify vitamin metabolism associated with differentially expressed genes (DEGs) in LUAD utilizing The Cancer Genome Atlas (TCGA)-LUAD, GSE68465 and GSE72094 data. Unsupervised clustering classified patients into distinct subgroups. By utilizing least absolute shrinkage and selection operator (LASSO)-Cox regression analysis, vitamin metabolism-related genes could be used to construct prognostic model. Then the vitamin metabolism gene-related risk score (VRS) was calculated based on best cut-off splitting. Kaplan-Meier analysis, time-dependent receiver operating characteristic (ROC) analysis, univariate and multivariate Cox analyses, chemotherapeutic drugs sensitivity analysis, immune infiltration analysis and nomogram were conducted to verify our models' accuracy. Finally, CPS1 was identified as a relevant diagnostic marker using Random Forests algorithms, single-cell RNA sequencing data was used to confirm its expression. Results: We investigated the relationship between vitamin metabolism patterns, overall survival (OS), and immune infiltration levels of patients with LUAD. A prognostic signature consisting of 11 genes was developed, which was able to classify patients into high and low VRS groups. Through gene enrichment analysis, cell cycle was mainly enriched. Compared to the low VRS group, the high VRS group exhibited poorer OS, as demonstrated by the Kaplan-Meier survival analysis. Furthermore, VRS was identified as an independent predictor of poor prognosis and poor OS, as indicated by both univariate and multivariate Cox regression analyses. Additionally, a nomogram was constructed to improve the accuracy of survival predictions in LUAD patients. We also found that the two groups of patients might respond differently to immune targets and anti-tumor drugs. CPS1 was identified as a relevant diagnostic marker and the expression was also as confirmed by single-cell RNA sequencing data. Conclusions: Overall, our findings suggest that vitamin metabolism can influence the prognosis of LUAD patients, and our prognostic signature represents a potentially helpful resource for predicting patient outcomes and informing clinical decision-making.

Significance of Ribonucleoside-diphosphate Reductase Subunit M2 in Lung Adenocarcinoma.

INTRODUCTION: The Ribonucleoside-diphosphate Reductase subunit M2 (RRM2) is known to be overexpressed in various cancers, though its specific functional implications remain unclear. This aims to elucidate the role of RRM2 in the progression of Lung Adenocarcinoma (LUAD) by exploring its involvement and potential impact. METHODS: RRM2 data were sourced from multiple databases to assess its diagnostic and prognostic significance in LUAD. We evaluated the association between RRM2 expression and immune cell infiltration, analyzed its function, and explored the effects of modulating RRM2 expression on LUAD cell characteristics through laboratory experiments. RESULTS: RRM2 was significantly upregulated in LUAD tissues and cells compared to normal counterparts (p<0.05), with rare genetic alterations noted (approximately 2%). This overexpression clearly distinguished LUAD from normal tissue (area under the curve (AUC): 0.963, 95% confidence intervals (CI): 0.946-0.981). Elevated RRM2 expression was significantly associated with adverse clinicopathological characteristics and poor prognosis in LUAD patients. Furthermore, a positive association was observed between RRM2 expression and immune cell infiltration. Pathway analysis revealed a critical connection between RRM2 and the cell cycle signaling pathway within LUAD. Targeting RRM2 inhibition effectively suppressed LUAD cell proliferation, migration, and invasion while promoting apoptosis. This intervention also modified the expression of several crucial proteins, including the downregulation of CDC25A, CDC25C, RAD1, Bcl-2, and PPM1D and the upregulation of TP53 and Bax (p < 0.05). CONCLUSION: Our findings highlight the potential utility of RRM2 expression as a biomarker for diagnosing and predicting prognosis in LUAD, shedding new light on the role of RRM2 in this malignancy.

Comprehensive proteomic profiling of lung adenocarcinoma: development and validation of an innovative prognostic model.

Background: Lung adenocarcinoma (LUAD), a global leading cause of cancer deaths, remains inadequately addressed by current protein biomarkers. Our study focuses on developing a protein-based risk signature for improved prognosis of LUAD. Methods: We employed the least absolute shrinkage and selection operator (LASSO)-COX algorithm on The Cancer Genome Atlas database to construct a prognostic model incorporating six proteins (CD49B, UQCRC2, SMAD1, FOXM1, CD38, and KAP1). The model's performance was assessed using principal component, Kaplan-Meier (KM), and receiver operating characteristic (ROC) analysis, indicating strong predictive capability. The model stratifies LUAD patients into distinct risk groups, with further analysis revealing its potential as an independent prognostic factor. Additionally, we developed a predictive nomogram integrating clinicopathologic factors, aimed at assisting clinicians in survival prediction. Gene set enrichment analysis (GSEA) and examination of the tumor immune microenvironment were conducted, highlighting metabolic pathways in high-risk genes and immune-related pathways in low-risk genes, indicating varied immunotherapy sensitivity. Validation through immunohistochemistry from the Human Protein Atlas (HPA) database and immunofluorescence staining of clinical samples was performed, particularly focusing on CD38 expression. Results: Our six-protein model (CD49B, UQCRC2, SMAD1, FOXM1, CD38, KAP1) effectively categorized LUAD patients into high and low-risk groups, confirmed by principal component, KM, and ROC analyses. The model showed high predictive accuracy, with distinct survival differences between risk groups. Notably, CD38, traditionally seen as protective, was paradoxically associated with poor prognosis in LUAD, a finding supported by immunohistochemistry and immunofluorescence data. GSEA revealed that high-risk genes are enriched in metabolic pathways, while low-risk genes align with immune-related pathways, suggesting better immunotherapy response in the latter group. Conclusions: This study presented a novel prognostic protein model for LUAD, highlighting the CD38 expression paradox and enhancing our understanding of protein roles in lung cancer progression. It offered new clinical tools for prognosis prediction and provided assistance for future lung cancer pathogenesis research.

SIRT2 as a Potential Biomarker in Lung Adenocarcinoma: Implications for Immune Infiltration.

SIRT2 play important roles in cell cycle and cellular metabolism in the development of non-small cell lung cancer (NSCLC), and SIRT2 exhibits its therapeutic effect on NSCLC tumors with high expression of SIRT2. Nevertheless, the clinical relevance of SIRT2 in lung adenocarcinoma (LUAD), particularly its impact on tumor growth and prognostic implications, remains obscure. This investigation entailed a comprehensive analysis of SIRT2 mRNA and protein expression levels in diverse tumor and corresponding healthy tissues, utilizing databases such as TIMER 2.0, UALCAN, and HPA. Prognostic correlations of SIRT2 expression in LUAD patients, stratified by distinct clinicopathological characteristics, were evaluated using the KM Plotter database. Additionally, the TCGA and TIMER 2.0 databases were employed to assess the relationship between SIRT2 and immune infiltration, as well as to calculate immunity, stromal, and estimation scores, thus elucidating the role of SIRT2 in modulating tumor immunotherapy responses. Furthermore, Gene Set Enrichment Analysis (GSEA) was utilized to elucidate SIRT2's biological functions in pan-cancer cells. Our findings revealed a marked reduction in both mRNA and protein levels of SIRT2 in LUAD tumors relative to healthy tissue. Survival analysis indicated that diminished SIRT2 expression correlates with adverse prognostic outcomes in LUAD. Furthermore, SIRT2 expression demonstrated a significant association with various clinicopathologic attributes of LUAD patients, influencing survival outcomes across different clinicopathologic states. Functional enrichment analyses highlighted SIRT2's involvement in cell cycle regulation and immune response. Notably, SIRT2 exhibited a positive correlation with immune cell infiltration, including natural killer (NK) cells, macrophages, and dendritic cells (DCs). In summary, SIRT2 was a potential prognostic biomarker for LUAD and and a new immunotherapy target.

Investigation of RBM10 mutation and its associations with clinical and molecular characteristics in EGFR-mutant and EGFR-wildtype lung adenocarcinoma.

Background: RBM10 is commonly mutated in lung adenocarcinoma (LUAD). However, its role in the pathogenesis of LUAD remains undefined. EGFR-mutant LUAD represents a distinct subset of non-small cell lung cancer (NSCLC). The function of RBM10 in tumor pathogenesis is supposed to differ between EGFR-mutant and EGFR-wt LUAD. This study aimed to interrogate the prevalence of RBM10 mutation in a large cohort of Chinese patients with LUAD and investigate the association of RBM10 mutation with clinical and molecular characteristics of EGFR-mutant and EGFR-wt LUAD. Methods: Tumor sequencing data from 2848 Chinese patients with LUAD were retrospectively reviewed and analyzed. The prevalence of RBM10 was also compared with other three cohorts: OrigMed (n = 1222), MSKCC (n = 1267), and TCGA (n = 566). The associations of RBM10 mutation with clinical and molecular characteristics were assessed. An external cohort of 182 patients with LUAD who received PD-1 inhibitor were used to investigate the association of RBM10 mutation with clinical outcomes upon immunotherapy. Results: Our cohort showed a higher prevalence of RBM10 in EGFR-mutant LUAD than in EGFR-wt LUAD (14.8 % vs. 6.5 %, p < 0.001). The enrichment of RBM10 mutations in EGFR-mutant LUAD was also seen in another Chinese cohort (OrigMed: 14.9 % vs. 7.8 %, p < 0.001), but not in the two western cohorts (MSKCC: 7.4 % vs. 9.5 %, p = 0.272; TCGA: 8.1 % vs. 6.7 %, p = 0.624). RBM10 mutations co-occurred more frequently with EGFR L858R mutations (23.7 %) than with other types of EGFR mutations (19 del: 7.7 %; other: 7.1 % in others, p < 0.001). In EGFR-mutant LUAD, RBM10 mutations were more commonly found in stage I (18.2 %) and II (21.8 %) vs. stage III (9.4 %) and IV (11.3 %) tumors (p < 0.001). The proportion of PD-L1 positive expression in EGFR-mutant LUAD with concomitant RBM10 mutation was not different from that those without RBM10 mutations (41.8 % vs. 47.9 %, p = 0.566). In contrast, RBM10 mutation occurred more frequently in EGFR-wt LUAD at stage II-IV (stage II: 12.0 %, stage III: 8.7 %, stage IV: 6.6 %) than at stage I (2.8 %). EGFR-wt LUAD with concomitant RBM10 mutations had higher proportions of PD-L1 expression positivity (78.9 % vs. 61.9 %, p = 0.014) and higher tumor mutational load (8.97 vs. 2.99 muts/Mb, p < 0.001) than those without. Patients with EGFR-wt LUAD who also harbored RBM10 loss of function (LOF) mutations had a longer median PFS upon immunotherapy than those with RBM10 non-LOF mutations (7.15 m vs. 2.60 m, HR = 4.83 [1.30-17.94], p = 0.010). Conclusion: We comprehensively investigated RBM10 mutations in a Chinese cohort with LUAD. Compared to western cohorts, a significant enrichment of RBM10 mutations in EGFR-mutant LUAD compared to EGFR-wildtype LUAD in the Chinese population. RBM10 mutation shows different associations with clinical and molecular characteristics between EGFR-mutant and EGFR-wt LUAD, suggesting a divergent mechanism between these two subsets via which RBM10 deficiency contribute to tumor pathogenesis. The findings contribute to our understanding of the molecular landscape of LUAD and highlight the importance of considering population-specific factors in cancer genomics research.

Prognostic value and immunological function of cuproptosis-related genes in lung adenocarcinoma.

Background: Lung cancer is one of the malignant tumors with the highest morbidity and fatality rates worldwide. The overall survival (OS) of lung adenocarcinoma (LUAD) is poor. Cuproptosis is a copper-triggered modality of mitochondrial cell death, however, its contribution to the emergence of lung cancer is unknown. The clinical implication and immunological function of cuproptosis-related genes (CRGs) in LUAD has yet to be established. Methods: TCGA, HPA, GEPIA, Kaplan-Meier, TIMER and CancerSEA database were used to explore the prognostic value and biological function of CRGs in LUAD. Results: CRGs are primarily involved in copper ion transport, the citrate cycle (TCA cycle) and central carbon metabolism in LUAD. The mRNA expression of COA6, UBE2D1, DLAT, SLC25A3, and DBH was significantly increased. The expression of COA6, DLAT, SLC25A3, DBH, and LOXL2 were all strongly associated with the clinicopathological stages in LUAD. Moreover, high expression of COA6, UBE2D1, DLAT, SLC25A3 and LOXL2 was related to poor OS. The expression of SLC25A3 and LOXL2 showed different association with immune cell infiltration. The single cell sequencing demonstrated that CRGs play important roles in the regulation of DNA damage response, inflammation and metastasis in LUAD. Conclusions: In summary, this study comprehensively uncovered that CRGs could be identified as potential prognostic and immunological biomarkers in LUAD. Our current research could provide a solid theoretical basis for LUAD survival research and clinical decision-making.

Identification of risk factors of EGFR-TKIs primary resistance in lung adenocarcinoma patients and construction of a risk predictive model: a case-control study.

Background: Lung cancer is one of the malignancies with the highest incidence and mortality rates. Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) are recommended as the first-line treatment for patients with EGFR-mutated lung adenocarcinoma (LUAD). However, some patients with EGFR-sensitive mutations develop primary resistance to EGFR-TKIs. This study aims to analyze the clinical characteristics of LUAD patients with primary resistance to EGFR-TKIs, identify independent risk factors for primary resistance, and establish a risk predictive model to provide reference for clinical decision-making. Methods: We collected data from LUAD patients with EGFR-sensitive mutations (19del/21L858R) who were hospitalized in our institution between 2020 and 2022 and received first-generation EGFR-TKIs with follow-up exceeding 6 months. These patients were categorized into primary resistance and sensitive groups based on treatment outcomes. We compared general clinical data, laboratory tests, and tumor-related characteristics between the two groups, analyzed risk factors for primary resistance to EGFR-TKIs, and constructed a risk predictive model. The model's predictive value was comprehensively assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves. Results: Serum neuron-specific enolase (NSE) concentration (P=0.03), serum pro-gastrin-releasing peptide (ProGRP) concentration (P=0.01), and Ki67 expression (P<0.001) were identified as independent risk factors for primary resistance to EGFR-TKIs in LUAD. The combined presence of these three risk factors had the highest predictive value [area under the curve (AUC) =0.975, P<0.001]. We constructed a predictive model for the risk of primary resistance to EGFR-TKIs in LUAD patients, incorporating these three parameters, and represented it through a visually interpretable nomogram. The calibration curve of the nomogram demonstrated its strong predictive ability. Further decision curve analysis indicated the model's clinical utility. Conclusions: Based on a single-center retrospective case-control study, we identified serum NSE concentration, ProGRP concentration, and Ki67 expression as independent risk factors for primary resistance to EGFR-TKIs in LUAD patients. We constructed and validated a risk predictive model based on these findings. This predictive model holds promise for clinical application, aiding in the development of personalized treatment strategies and providing a scientific basis for early identification of primary resistance patients.

Anoikis-related gene signatures predict prognosis of lung adenocarcinoma patients and reveal immune infiltration.

Background: Lung adenocarcinoma (LUAD), a type of lung cancer, is one of the most aggressive and deadly malignancies worldwide. Malignant tumor cells exhibit strong anti-anoikis properties to achieve distant metastasis through the circulatory system. However, more research is needed to understand how anoikis is involved in the progression, metastasis and especially the prognosis of LUAD. Methods: We obtained anoikis-related genes (ARGs) from two websites, Harmonizome and Genecards, and integrated them to select and model the genes associated with LUAD prognosis. In addition, we investigated differences in the immune cell microenvironment and pathways of enrichment analysis between subtypes. We finally constructed a nomogram based on ARGs and used decision curve analysis (DCA) to demonstrate that this model could help clinicians make clinical decisions. Results: Sixty-four differentially expressed genes (DEGs) were found to be associated with survival, and of these, six were chosen to build a prognostic model. The time-dependent receiver operating characteristic (ROC) curves showed that the model had a satisfactory predictive ability. Enrichment analysis and immune microenvironment analysis revealed that the immune status and drug sensitivity of populations at high and low risk were different. We integrated the clinicopathological features of LUAD with the risk score to build the nomogram. The nomogram was shown to be a good predictor of short- and long-term survival in LUAD patients through DCA analysis. Conclusions: This new model based on six ARGs and nomograms in our study could help patients with LUAD develop personalized treatment plans.

CTBP2 contributes to cisplatin resistance in lung adenocarcinoma by inhibiting generation of reactive oxygen species.

Background: Cisplatin (CP) is commonly used for the initial treatment of lung adenocarcinoma (LUAD). Resistance to CP has long been recognized as a significant obstacle to achieving improved therapeutic outcomes. Nevertheless, the intricate molecular mechanisms underlying the phenomenon remain incompletely understood. Methods: The present study utilized the University of ALabama at Birmingham CANcer data analysis Portal (UALCAN) and Gene Expression Profiling Interactive Analysis (GEPIA) databases to conduct an analysis of the expression of C-terminal binding protein 2 (CTBP2) in LUAD. The correlation between CTBP2 expression and survival data was investigated by the Kaplan-Meier (K-M) plotter. Subsequently, the roles of CTBP2 in CP resistance were explored by analyzing cell viability, cell apoptosis, reactive oxygen species (ROS), and mitochondrial membrane potential (MMP) in CP-resistant cells (A549/DDP). Results: Our data indicated that the CTBP2 expression in LUAD exhibited a significant increase compared to the non-malignant tissues. CTBP2 overexpression showed a correlation to poor survival. CTBP2 knockdown significantly enhanced cell sensitivity to CP in A549/DDP cells. The underlying mechanism is related to promoting ROS production and decreasing MMP after CP treatment. Conclusions: CTBP2 expression has been identified as a novel biomarker for resistance to CP, and its downregulation has been found to enhance sensitivity to CP. Therefore, CTBP2 can serve as a predictor related to CP resistance and a viable therapeutic target for CP resistance in LUAD.