Treatment Of Lung Adenocarcinoma Research Articles

COPZ1 regulates ferroptosis through NCOA4-mediated ferritinophagy in lung adenocarcinoma

BackgroundFerroptosis, a type of autophagy-dependent cell death, has been implicated in the pathogenesis of lung adenocarcinoma (LUAD). This study aimed to investigate the involvement of coatomer protein complex I subunit zeta 1 (COPZ1) in ferroptosis and ferritinophagy in LUAD. MethodsPublicly available human LUAD sample data were obtained from the TCGA database to analyze the association of COPZ1 expression with LUAD grade and patient survival. Clinical samples of LUAD and para-carcinoma tissues were collected. COPZ1-deficient LUAD cell model and xenograft model were established. These models were analyzed to evaluate tumor growth, lipid peroxidation levels, mitochondrial structure, autophagy activation, and iron metabolism. ResultsHigh expression of COPZ1 was indicative of malignancy and poor overall survival. Clinical LUAD tissues showed increased COPZ1 expression and decreased nuclear receptor coactivator 4 (NCOA4) expression. COPZ1 knockdown inhibited xenograft tumor growth and induced apoptosis. COPZ1 knockdown elevated the levels of ROS, Fe2+ and lipid peroxidation. COPZ1 knockdown also caused mitochondrial shrinkage. Liproxstatin-1, deferoxamine, and z-VAD-FMK reversed the effects of COPZ1 knockdown on LUAD cell proliferation and ferroptosis. Furthermore, COPZ1 was directly bound to NCOA4. COPZ1 knockdown restricted FTH1 expression and promoted NCOA4 and LC3 expression. NCOA4 knockdown reversed the regulation of iron metabolism, lipid peroxidation, and mitochondrial structure induced by COPZ1 knockdown. COPZ1 knockdown induced the translocation of ferritin to lysosomes for degradation, whereas NCOA4 knockdown disrupted this process. ConclusionThis study provides novel evidence that COPZ1 regulates NCOA4-mediated ferritinophagy and ferroptosis. These findings provide new insights into the pathogenesis and potential treatment of LUAD.

Unveiling key genes in esophageal and lung adenocarcinoma progression: A combined high-throughput analysis and molecular docking approach for targeted therapies

BackgroundEsophageal carcinoma (ESCA) and Lung adenocarcinoma (LUAD) are the prominent causes of death worldwide. There is an urgent need to identify and characterize potential biomarkers for these malignancies to enhance early cancer prognosis. Integrating computational-based early cancer detection with wet lab-based research offers a promising approach toward early-stage cancer prognosis. MethodologyTwo ESCA datasets (GSE17351, GSE23400) with 58 cancerous and 58 normal samples, along with two LUAD datasets (GSE18842, GSE74706) totaling 64 cancer samples and 63 controls, were used to identify DEGs. Visualization of DEGs was achieved using heat-maps, volcano plots, and Venn diagrams. Hub genes were predicted via PPI analysis and the cytoHubba plugin in Cytoscape. Potential hub gene expressions were evaluated with box plots, stage plots, and survival plots for prognostic assessment via GEPIA2. AutoDockVina wizard of PyRx was utilized for molecular docking to determine optimal binding interactions between proteins and hit compounds. FindingsSixty common DEGs were identified, focusing on significant pathways in ESCA and LUAD. The top ten hub genes (KIF4A, HMMR, CENPF, CDK1, ASPM, CDKN3, KIF2C, TTK, UBE2C, and MELK) were found to be linked to both cancers via PPI analysis. Notably, high expression of CDK1 was significantly associated with ESCA and LUAD progression, as evidenced by box plots, stage plots, and survival analysis. Upregulated expression of the targeted genes (CDK1) promotes multi-variant cancer progression that is observed by analyzing and comparing of all findings. Molecular docking with CDK1 highlighted four top compounds: Tanshinone I, Withanolide, Artemether, and Epigallocatechin, suggesting their potential as drug candidates for ESCA and LUAD treatment. ConclusionsIn conclusion, our discoveries unveil potential biomarker candidates, offer insights into ESCA and LUAD treatment strategies, and outline directions for further investigation, enriching our understanding of the pathogenesis of ESCA and LUAD.

Trochlear nerve schwannoma with concomitant osimertinib-responsive stage IV lung adenocarcinoma: illustrative case.

The prognosis for cancer patients has been improved because of the development of molecularly targeted drugs. Treatment of intracranial tumors must be personalized while prioritizing the treatment of comorbid cancers. A 38-year-old man presented with bloody sputum, bilateral multiple nodules, and a mass in the lower lobe of his right lung. Bronchoscopy revealed stage IV lung adenocarcinoma with an epidermal growth factor receptor (EGFR) mutation. Screening head magnetic resonance imaging revealed a 38-mm-diameter mass in the left petroclival area. Because the patient was neurologically intact, the treatment of lung adenocarcinoma was prioritized, and the third-generation EGFR-tyrosine kinase inhibitor osimertinib was used. Although nodules in the lung began to shrink, the intracranial lesion expanded and caused hydrocephalus, necessitating a ventriculoperitoneal shunt. The tumor also caused diplopia, dysarthria, and gait abnormalities. A left anterior transpetrosal approach was used to remove the tumor derived from the trochlear nerve. The pathological examination revealed schwannoma. Neurological symptoms improved following surgery. Osimertinib was continued during the perioperative period. Osimertinib was effective for lung adenocarcinoma but not for trochlear nerve schwannoma, which required surgical intervention. It is necessary to tailor the treatment of benign brain tumors in patients with concurrent malignant cancers. https://thejns.org/doi/10.3171/CASE24144.

GSFM: A genome-scale functional module transformation to represent drug efficacy for in silico drug discovery

Pharmacotranscriptomic profiles, which capture drug-induced changes in gene expression, offer vast potential for computational drug discovery and are widely used in modern medicine. However, current computational approaches neglected the associations within gene‒gene functional networks and unrevealed the systematic relationship between drug efficacy and the reversal effect. Here, we developed a new genome-scale functional module (GSFM) transformation framework to quantitatively evaluate drug efficacy for in silico drug discovery. GSFM employs four biologically interpretable quantifiers: GSFM_Up, GSFM_Down, GSFM_ssGSEA, and GSFM_TF to comprehensively evaluate the multi-dimension activities of each functional module (FM) at gene-level, pathway-level, and transcriptional regulatory network-level. Through a data transformation strategy, GSFM effectively converts noisy and potentially unreliable gene expression data into a more dependable FM active matrix, significantly outperforming other methods in terms of both robustness and accuracy. Besides, we found a positive correlation between RSGSFM and drug efficacy, suggesting that RSGSFM could serve as representative measure of drug efficacy. Furthermore, we identified WYE-354, perhexiline, and NTNCB as candidate therapeutic agents for the treatment of breast-invasive carcinoma, lung adenocarcinoma, and castration-resistant prostate cancer, respectively. The results from in vitro and in vivo experiments have validated that all identified compounds exhibit potent anti-tumor effects, providing proof-of-concept for our computational approach.

Identification of Biomarkers for Lung Adenocarcinoma With Qi Deficiency and Phlegm Dampness.

Qi deficiency and phlegm dampness (QPD) is one of the most common traditional Chinese medicine (TCM) syndromes in lung adenocarcinoma (LUAD). This study aimed to identify syndrome-specific biomarkers for LUAD with QPD syndrome. Peripheral blood mononuclear cells (PBMCs) from LUAD patients with QPD, LUAD patients with non-QPD (N-QPD), and healthy control (H) were collected and analyzed with RNA-seq to identify differentially expressed genes (DEGs). The area under the receiver operator characteristic curve (AUC) of each DEG was calculated, and the top 10 highest AUC DEGs were validated by qRT-PCR. Logistic regression analysis was used to develop a diagnostic model evaluated with AUC. A total of 135 individuals were enrolled in this study (training set: 15 QPD, 15 N-QPD, 15 H; validation set: 30 QPD, 30 N-QPD, 30 H). A total of 1480 DEGs were identified between QPD and N-QPD. The qRT-PCR results showed that the expression of DDR2 was downregulated, and PPARG was upregulated, which was in line with the finding of the training set. We developed a diagnostic model with these two genes. The AUC of the diagnostic model in the training cohort and validation cohort was 0.891 and 0.777, respectively. We identified the two genes (DDR2 and PPARG) as syndrome-specific biomarkers for LUAD with QPD syndrome and developed a novel diagnostic model, which may help to improve the accuracy and sensibility of clinical diagnosis and provide a new target for natural drug treatment of LUAD.

Construction of lncRNA prognostic model related to disulfidptosis in lung adenocarcinoma

BackgroundLung cancer is one of the malignant tumors with the highest rates of morbidity and mortality worldwide. One of the most common histological types of lung cancer is lung adenocarcinoma (LUAD). Despite the fact that development in medicine has significantly improved some patients’ prognoses, the overall survival (OS) rate is still very low. In glucose-deficient SLC7A11-overexpressed cancer cells, the accumulation of disulfide molecules leads to abnormal disulfide bonding between actin cytoskeletal proteins, interferes with their tissues, and eventually leads to actin network collapse and cell death. This mode of cell death is called disulfidptosis. Studies have shown that disulfidptosis may be a new target for cancer treatment. However, the role of disulfidptosis in LUAD is still unknown. MethodsLUAD transcriptome and clinical information from The Cancer Genome Atlas (TCGA) was downloaded. The co-expression analysis, Least Absolute Shrinkage and Selection Operator (LASSO) regression, and Cox regression analysis was performed to screen the disulfidptosis-related lncRNAs (DRLs) and build the prognostic model. Kaplan-Meier curve, Cox regression analysis, and receiver operating characteristic (ROC) curve was used to validate the model. Then a nomogram is made to predict the prognosis of LUAD patients. Finally, fresh-collected clinical samples were used to verify the expression of DRLs in LUAD. ResultsThe prognostic model with six DRLs was developed to predict the prognosis of LUAD, with superior prognosis value compared to other clinical variables. The Cox regression analysis revealed that T stage, N stage and the risk score were identified as independent variables that affected LUAD prognosis. ROC curve revealed that the model has a moderate diagnostic value, with an AUC of 1-year 0.684, 3-year 0.664, and 5-year 0.588. Moreover, nine medications connected to LUAD treatment were acquired through drug sensitivity analysis. LUAD tissue validation showed that AC012073.1, AC012615.1, EMSLR, and SNHG12 were highly expressed, while AL606834.1 and AL365181.2 with low expression. ConclusionSix DRLs were screened and verified to construct the prognostic model, which can accurately predict the LUAD prognosis. It establishes a basis for further exploration into the molecular mechanisms underlying LUAD and identification of potential biomarkers for diagnosis, prognosis, and therapeutic targets.

TFAP2A Activates S100A2 to Mediate Glutamine Metabolism and Promote Lung Adenocarcinoma Metastasis.

Lung adenocarcinoma (LUAD) is a fatal disease with metabolic abnormalities. The dysregulation of S100 calcium-binding protein A2 (S100A2), a member of the S100 protein family, is connected to the development of various cancers. The impact of S100A2 on the LUAD occurrence and metastasis, however, has not yet been reported. The functional mechanism of S100A2 on LUAD cell metastasis was examined in this article. The expression of TFAP2A and S100A2 in LUAD tissues and cells was analyzed by bioinformatics and qRT-PCR, respectively. The enrichment pathway analysis was performed on S100A2. Bioinformatics analysis determined the binding relationship between TFAP2A and S100A2, and their interaction was validated through dual-luciferase and chromatin immunoprecipitation experiments. Cell viability was determined using cell counting kit-8 (CCK-8). A transwell assay was performed to analyze the invasion and migration of cells. Immunofluorescence was conducted to obtain vimentin and E-cadherin expression, and a western blot was used to detect the expression of MMP-2, MMP-9, GLS, and GLUD1. The kits measured the NADPH/NADP ratio, glutathione (GSH)/glutathione disulfide (GSSG) levels, and the contents of glutamine, α-KG, and glutamate. S100A2 was upregulated in LUAD tissues and cells, and S100A2 mediated glutamine metabolism to induce LUAD metastasis. Additionally, the transcriptional regulator TFAP2A was discovered upstream of S100A2, and TFAP2A expression was upregulated in LUAD, which indicated that TFAP2A promoted the S100A2 expression. The rescue experiment found that upregulation of S100A2 could reverse the inhibitory effects of silencing TFAP2A on glutamine metabolism and cell metastasis. In conclusion, by regulating glutamine metabolism, the TFAP2A/S100A2 axis facilitated LUAD metastasis. This suggested that targeting S100A2 could be beneficial for LUAD treatment.

CDT1, transcriptionally regulated by E2F2, promotes lung adenocarcinoma progression

CDT1, a gene that shows excessive expression in various malignancies, functions as a pivotal regulator of replication licensing. In this study, we observed a positive correlation in expression between CDT1 and E2F2 among patients with lung adenocarcinoma (LUAD). Our findings substantiated that E2F2 directly interacted with the promoter region of CDT1, as confirmed by ChIP-qPCR assays, and depletion of E2F2 resulted in a downregulation of CDT1 expression in LUAD cell lines by gene interference technology. Furthermore, we identified an upregulation of CDT1 mRNA level in Chinese LUAD samples. Notably, in the loss-of-function assays, depletion of CDT1 in LUAD cell lines inhibited cell proliferation, migration, and invasion. Concurrently, it promoted cell apoptosis and induced G0/G1 phase arrest using MTT, flow cytometry, and Transwell assays, reinforcing its role as an oncogene.Furthermore, enhanced tumor ablation was determined in a CDT1-downregulated LUAD tumor-bearing nude mouse model. Collectively, our results strongly suggest that E2F2 positively regulates CDT1 expression and actively participates in the progression of lung adenocarcinoma, thereby providing valuable insights into identifying novel therapeutic targets for LUAD treatment.

A Six-gene Prognostic Model Based on Neutrophil Extracellular Traps (NETs)-related Gene Signature for Lung Adenocarcinoma.

Lung adenocarcinoma (LUAD) is one of the most common malignant cancers. Neutrophil extracellular traps (NETs) have been discovered to play a crucial role in the pathogenesis of LUAD. We aimed to establish an innovative prognostic model for LUAD based on the distinct expression patterns of NETs-related genes. The TCGA LUAD dataset was utilized as the training set, while GSE31210, GSE37745, and GSE50081 were undertaken as the verification sets. The patients were grouped into clusters based on the expression signature of NETs-related genes. Differentially expressed genes between clusters were identified through the utilization of the random forest and LASSO algorithms. The NETs score model for LUAD prognosis was developed by multiplying the expression levels of specific genes with their corresponding LASSO coefficients and then summing them. The validity of the model was confirmed by analysis of the survival curves and ROC curves. Additionally, immune infiltration, GSEA, mutation analysis, and drug analysis were conducted. Silencing ABCC2 in A549 cells was achieved to investigate its effect. We identified six novel NETs-related genes, namely UPK1B, SFTA3, GGTLC1, SCGB3A1, ABCC2, and NTS, and developed a NETs score signature, which exhibited a significant correlation with the clinicopathological and immune traits of the LUAD patients. High-risk patients showed inhibition of immune-related processes. Mutation patterns exhibited variability among the different groups. AZD3759, lapatinib, and dasatinib have been identified as potential candidates for LUAD treatment. Moreover, the downregulation of ABCC2 resulted in the induction of apoptosis and suppression of migration and invasion in A549 cells. Altogether, this study has identified a novel NET-score signature based on six novel NET-related genes to predict the prognosis of LUAD and ABCC2 and has also explored a new method for personalized chemo-/immuno-therapy of LUAD.

PSIP1 promotes gefitinib resistance in lung adenocarcinoma by inducing the expression of WASF3 and its downstream ITGB3/AKT signaling.

Gefitinib (GR), a representative drug of epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI), is a key pillar in the treatment of lung adenocarcinoma (LUAD), but drug resistance is universal. Identifying the potential factors of drug resistance to GR is essential to treat patients with EGFR mutant LUAD. The GR-resistant LUAD cells were established and confirmed by MTT assay. The effects of PC4 and SRSF1 interacting protein 1 (PSIP1) on GR-resistant cell proliferation and apoptosis in vitro and in vivo were detected by colony formation, flow cytometry, tumor-bearing animal model, immunohistochemistry, and TUNEL staining. Western blotting and qPCR were used to determine the expression of relevant markers. The effect of PSIP1 on the promoter region of Wiskott-Aldrich syndrome protein family member 3 (WASF3) was detected by the dual-luciferase assay. The interaction between PSIP1 and RNA polymerase II was evaluated using ChIP-qPCR and Co-IP assays. PSIP1 was highly enriched in GR-resistant LUAD cells. Downregulation of PSIP1 expression significantly inhibited the proliferation of LUAD-resistant cells and promoted apoptosis. WASF3 was shown to have similar effects as PSIP1 in promoting drug resistance in LUAD cells. PSIP1 promoted the transcriptional activity of WASF3, which was achieved by increasing RNA polymerase II recruitment on the WASF3 promoter. Furthermore, PSIP1 positively regulated the expression of the pro-EGFR-TKI resistance factor integrin subunit beta 3 (ITGB3). Our work suggests that PSIP1 promotes resistance to GR in LUAD cells by inducing the expression of WASF3 and its downstream regulator ITGB3.

SLC4A4 as a novel biomarker involved in immune system response and lung adenocarcinoma progression

BackgroundAltered expression and activity of solute carrier family 4 member 4 (SLC4A4) could affect the growth, survival and metastasis of tumor cells. Currently, the role of SLC4A4 in lung adenocarcinoma (LUAD) immunotherapy and prognosis was not entirely clear. MethodsWe analyzed SLC4A4 expression in LUAD tissues and cell lines using quantitative reverse transcription-polymerase chain reaction, Western blotting, and immunohistochemistry. The effects of SLC4A4 overexpression on angiogenesis, cell migration, invasion, and epithelial-mesenchymal transition were examined. Public databases helped construct a risk model evaluating SLC4A4′s expression on LUAD prognosis and immunotherapy response. Additionally, a xenograft model, flow cytometry, and enzyme-linked immunosorbent assay further explored SLC4A4′s role in tumor immune microenvironment infiltration. ResultsUpregulation of SLC4A4 promoted apoptosis in the LUAD cell line and significantly inhibited the migration and invasive ability of cancer cells (P<0.01). A total of 10 key genes (including SIGLEC6, RHOV, PIR, MOB3B, MIR3135B, LPAR6, KRT8, ITGA2, CPS1, and C6) were screened according to SLC4A4 expression, immune score and stromal score, and a prognostic model with good outcome was constructed (AUC values of which in the training cohort at 1,3, and 5 years reached 0.73, 0.73, and 0.72, respectively). Importantly, we demonstrated that high expression of SLC4A4 was able to increase the proliferation level and cytokine secretion of CD8+ T cells for the purpose of promoting the immune system response to LUAD. ConclusionOur study revealed that SLC4A4 can serve as a prognostic indicator for LUAD, providing new insights into the treatment and diagnosis of LUAD.

Astragalus Polysaccharides and Metformin May Have Synergistic Effects on the Apoptosis and Ferroptosis of Lung Adenocarcinoma A549 Cells.

Astragalus polysaccharides (APSs), the compounds extracted from the common herb Astragalus membranaceus, have been extensively studied for their antitumor properties. In this study, we investigated the effect of APS on lung adenocarcinoma A549 cells. The effects of APS and the anti-diabetic drug metformin on apoptosis and ferroptosis were compared. Furthermore, the combination treatment of APS and metformin was also investigated. We found that APS not only reduced the growth of lung cancer cells but also had a synergistic effect with metformin on A549 cells. The study results showed that it may be promising to use APS and metformin as a combination therapy for the treatment of lung adenocarcinoma.

Dihydroisotanshinone I regulates ferroptosis via PI3K/AKT pathway to enhance cisplatin sensitivity in lung adenocarcinoma.

Dihydroisotanshinone I (DT) is a kind of diterpenoid compound extracted from the dried roots of Salvia miltiorrhiza Bunge, and exhibits multiple biological activities including anti-tumor activity. Cisplatin is one of the first-line drugs for the treatment of lung adenocarcinoma (LAUD), but the drug resistance and toxicity limit its efficacy. DT is known to induce apoptosis and ferroptosis, but it is unclear whether DT can inhibit the cisplatin-resistant LAUD cells and reverse the drug resistance in LAUD. Therefore, our study intends to establish the cisplatin-resistant human LAUD cells (A549/DDP), and figure out the influence and related mechanisms of DT reversing cisplatin resistance in A549/DDP cells, so as to provide a theoretical basis for the DT as a new natural candidate for the treatment of LAUD. The establishment of A549/DDP was the continuous stimulation by exposing A549 to gradient concentrations of Cisplatin. The cell viability of A549 and A549/DDP was detected by CCK-8 kit, and the IC50 value was calculated. The morphological changes of A549 and A549/DDP cells were observed by an inverted microscope. The contents of malondialdehyde (MDA) and glutathione (GSH) in A549/DDP cells after drug treatment were detected by related kits. The levels of Fe2+, cytosolic reactive oxygen species (ROS), and lipid reactive oxygen species (lipid ROS) were detected by a fluorescence microplate reader or fluorescence cell imager according to the related fluorescent probe kit instructions. Western blot was used to detect the expressions of PI3K, phospho-PI3K, AKT, phospho-AKT, MDM2, p53, GPX4, and SLC7A11 in A549/DDP after different drug treatments. Our study demonstrated that the inhibitory effect of DT on A549 and A549/DDP cells was time-dependent and concentration-dependent, and DT and DDP had a synergistic effect on inhibiting the proliferation of A549/DDP cells. Furthermore, DT mainly induced ferroptosis in A549/DDP cells and synergized with cisplatin to promote ferroptosis in A549/DDP cells. The result of KEGG pathway analysis, molecular docking and western blot showed that DT could enhance the cisplatin sensitivity of A549/DDP by inhibiting PI3K/MDM2/P53 signaling pathway. Consequently, we concluded that DT promotes ferroptosis in cisplatin-resistant LAUD A549/DDP cells. Additionally, DT reverses cisplatin resistance by promoting ferroptosis via PI3K/MDM2/P53 pathway in A549/DDP cells.

A novel cancer-associated fibroblasts risk score model predict survival and immunotherapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) is the leading cause of cancer-related death worldwide. Cancer-associated fibroblasts (CAFs) are a special type of fibroblasts, which play an important role in the development and immune escape of tumors. Weighted gene co-expression network analysis (WGCNA) was used to construct the co-expression module. In combination with univariate Cox regression and analysis of least absolute shrinkage operator (LASSO), characteristics associated with CAFs were developed for a prognostic model. The migration and proliferation of lung cancer cells were evaluated in vitro. Finally, the expression levels of proteins were analyzed by Western blot. LASSO Cox regression algorithm was then performed to select hub genes. Finally, a total of 2 Genes (COL5A2, COL6A2) were obtained. We then divided LUAD patients into high- and low-risk groups based on CAFs risk scores. Survival analysis, CAFs score correlation analysis and tumor mutation load analysis showed that COL5A2 and COL6A2 were high-risk genes for LUAD. Human Protein Atlas (HPA), western blot and PCR results showed that COL5A2 and COL6A2 were up-regulated in LUAD tissues. When COL5A2 and COL6A2 were knocked down, the proliferation, invasion and migration of lung cancer cells were significantly decreased. Finally, COL5A2 can affect LUAD progression through the Wnt/β-Catenin and TGF-β signaling pathways. Our CAFs risk score model offers a new approach for predicting the prognosis of LUAD patients. Furthermore, the identification of high-risk genes COL5A2 and COL6A2 and drug sensitivity analysis can provide valuable candidate clues for clinical treatment of LUAD.

Synergistic anticancer effects of omega-3 fatty acids (EPA/DHA) and anticancer drug Doxorubicin against human lung adenocarcinoma

Single agent therapy in the treatment of cancer did not provide satisfactory clinical outcome in a long term due to drug resistance, cumulative toxicity and suboptimal efficacy. Therefore, combination therapies are apt to improve the quality of life in patients. In the present study, combinatorial effect of EPA and/or DHA with doxorubicin (Dox) was evaluated for their potential synergistic effect on human lung adenocarcinoma (A549) cells. The respective IC50 values obtained for EPA, DHA and Dox were 170, 140 and 2.5 μmol/L and thus EPA and DHA were separately combined with Dox at constant ratio of 68:1 and 56:1 respectively, depending on the ratio of their IC50 values. Different combinations of drugs revealed dose-dependent inhibition of cell viability and IC50 values were reduced to nearly 3-fold (58.75 μmol/L) and 4.5-fold (31.5 μmol/L) in EPA-Dox and DHA-Dox combination respectively. Combination index (CI) revealed strong synergism (CI < 0.5) in DHA-Dox (0.49) and moderate synergism (CI > 0.5) in EPA-Dox (0.79) at 0.5 Fa (Fraction affected), which is further confirmed by dose reduction index and isobologram. The mechanisms underlying synergistic interactions involve intracellular ROS generation and MMP depolarisation which causes changes in the cell morphology viz. Nuclear fragmentation/condensation, membrane blebbing and early/late apoptotic cells. Moreover, cell cycle arrest was observed at the S and G2/M phase, with more prominent effect in G2/M phase. No toxicity was imposed on non-cancerous HEK-293 T cells. These findings suggest that EPA-Dox and DHA-Dox could be explored further for animal studies and clinical trials for lung adenocarcinoma treatment.

Prognostic signature based on S100 calcium-binding protein family members for lung adenocarcinoma and its clinical significance

The S100 family proteins (S100s) participate in multiple stages of tumorigenesis and are considered to have potential value as biomarkers for detecting and predicting various cancers. But the role of S100s in lung adenocarcinoma (LUAD) prognosis is elusive. Transcriptional data of LUAD patients were retrieved from TCGA, and relevant literature was extensively reviewed to collect S100 genes. Differential gene expression analysis was performed on the LUAD data, followed by intersection analysis between the differentially expressed genes (DEGs) and S100 genes. Unsupervised consensus clustering analysis identified two clusters. Significant variations in overall survival between the two clusters were shown by Kaplan-Meier analysis. DEGs between the two clusters were analyzed using Lasso regression and univariate/multivariate Cox regression analysis, leading to construction of an 11-gene prognostic signature. The signature exhibited stable and accurate predictive capability in TCGA and GEO datasets. Subsequently, we observed distinct immune cell infiltration, immunotherapy response, and tumor mutation characteristics in high and low-risk groups. Finally, small molecular compounds targeting prognostic genes were screened using CellMiner database, and molecular docking confirmed the binding of AMG-176, Estramustine, and TAK-632 with prognostic genes. In conclusion, we generated a prognostic signature with robust and reliable predictive ability, which may provide guidance for prognosis and treatment of LUAD.

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

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. 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. 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/β-catenin axis was investigated by Immunoblot analysis. 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/β-catenin axis. GNL3 is key in the progression of LUAD by metiating Wnt/β-catenin axis. Targeting GNL3 may represent a novel therapeutic method for LUAD treatment.

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.

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

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. 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. 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-β)/SMAD signaling pathway was closely related to LUAD, and we then validated the pathway using WB assays. 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.

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

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. 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. 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. 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.