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.

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.
CONCLUSIONS: 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.

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.

BACKGROUND: In both lung adenocarcinoma (LUAD) and severe acute respiratory syndrome (SARS), uncontrolled inflammation can be detected in lung tissue. The PDZ-binding motif (PBM) in the SARS-CoV-1 E protein has been demonstrated to be a virulence factor that induces a cytokine storm.
METHODS: To identify gene expression fluctuations induced by PBM, microarray sequencing data of lung tissue infected with wild-type (SARS-CoV-1-E-wt) or recombinant virus (SARS-CoV-1-E-mutPBM) were analyzed, followed by functional enrichment analysis. To understand the role of the screened genes in LUAD, overall survival and immune correlation were calculated.
RESULTS: A total of 12 genes might participate in the initial and developmental stages of LUAD through expression variation and mutation. Moreover, dysregulation of a total of 12 genes could lead to a poorer prognosis. In addition, the downregulation of MAMDC2 and ITGA8 by PBM could also affect patient prognosis. Although the conserved PBM (-D-L-L-V-) can be found at the end of the carboxyl terminus in multiple E proteins of coronaviruses, the specific function of each protein depends on the entire amino acid sequence.
CONCLUSIONS: In summary, PBM containing the SARS-CoV-1 E protein promoted the carcinogenesis of LUAD by dysregulating important gene expression profiles and subsequently influencing the immune response and overall prognosis.

BACKGROUND: According to the 2022 Global Cancer Statistics, lung cancer is the leading cause of cancer-related mortality worldwide. Lung adenocarcinoma (LUAD), which is a histological subtype of Non- Small Cell Lung Cancer (NSCLC), accounts for 40% of primary lung cancer. Therefore, there is an urgent need to identify new prognostic markers as clinical predictive markers for LUAD.
OBJECTIVE: This study aimed to investigate the role of Keratin 80 (KRT80) in the prognosis of LUAD and its underlying mechanisms.
METHODS: Bioinformatics analysis was conducted using data retrieved from The Cancer Genome Atlas (TCGA) databases. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases were employed to predict the involved biological processes and signaling pathways, respectively. The LinkedOmics database was utilized to identify differentially expressed genes (DEGs) correlated with KRT80. Nomograms and Kaplan-Meier plots were constructed to evaluate the survival outcomes of patients diagnosed with LUAD. Moreover, TIMER was employed to conduct correlation analyses between KRT80 expression and immune cell infiltration, shedding light on the intricate interplay between KRT80 and the tumor microenvironment in LUAD. To ascertain the RNA and protein expression levels of KRT80 in LUAD and adjacent normal tissues, Reverse Transcription-quantitative Polymerase Chain Reaction (RT-qPCR) and immunohistochemistry techniques were employed, respectively.
RESULTS: Scrutiny of the TCGA dataset revealed KRT80 up-regulation across pan-cancer tissues, notably elevated in LUAD compared to healthy lung tissues. This finding was validated in our clinical samples, where Kaplan-Meier survival curves indicated poorer survival rates for high KRT80 expression in LUAD. A positive correlation was found between the transcription level of KRT80 in LUAD samples and clinical parameters, such as lymph node metastasis stage, distant metastasis, and pathological stage. Survival, logistic regression, and Cox regression analyses emphasized the clinical prognostic significance of high KRT80 expression in LUAD. Nomogram results underscored the robust predictive potential of KRT80 for the survival of LUAD patients. Gene functional enrichment analyses mainly associated KRT80 with cytokine-cytokine receptor interactions, cell cycle, apoptosis, and chemokine signaling pathways. Based on the results of the immune infiltration analysis, it can be found that the expression of KRT80 is related to the immune cell subsets and survival rate of patients with LUAD.
CONCLUSIONS: Our research revealed a significant upregulation of KRT80 in LUAD, with heightened KRT80 expression correlating with unfavorable prognosis. This study represents a comprehensive and systematic evaluation of KRT80 expression in LUAD, encompassing its prognostic and diagnostic significance, as well as underlying mechanisms. Our findings suggest that KRT80 may emerge as a novel prognostic and predictive biomarker in LUAD.

Lung adenocarcinoma (LUAD), the most common subtype of lung cancer globally, has seen improved prognosis with advancements in diagnostic, surgical, radiotherapy, and molecular therapy techniques, while its 5-year survival rate remains low. Molecular biomarkers provide prognostic value. Oxidative stress factors, such as reactive nitrogen species and ROS, are crucial in various stages of tumor progression, influencing cell transformation, proliferation, angiogenesis, and metastasis. ROS demonstrate dual roles, affecting tumor cells, hypoxia sensitivity, and the microenvironment. Comprehensive analysis of oxidative stress in LUAD has not been conducted to date. Therefore, we systematically investigated the regulatory patterns of oxidative stress in LUAD based on oxidative stress-related genes and correlated these patterns with cellular infiltration characteristics of the tumor immune microenvironment. The model utilizes single-factor Cox analysis to screen key differential genes with prognostic value and employs least absolute shrinkage and selection operator (LASSO) penalized Cox regression analysis to construct a prognostic-related prediction model. Ten candidate genes were selected based on this model. The risk score was constructed using the coefficients and expression levels of these ten genes. Furthermore, the impact of this risk score on overall survival (OS) was determined. Two genes with the most significant differential expression, SFTPB and S100P, were selected through qRT-PCR. Cell experiments including CCK-8, Edu, transwell assays confirmed their effects on lung cancer cells growth, consistent with the results of bioinformatics analysis. These findings suggested that this model held potential clinical value for evaluating the prognosis of lung adenocarcinoma.

Zinc finger proteins (ZNFs) play a significant role in the initiation and progression of tumors. Nevertheless, the specific contribution of ZNF610 to lung adenocarcinoma (LUAD) remains poorly understood. This study sought is to elucidate the role of ZNF610 in LUAD. Transcript data of LUAD were obtained from The Cancer Genome Atlas Program (TCGA) database and processed via R program. The expression of ZNF610 was assessed in various cell lines. To compare the proliferative capacity of cells with or without ZNF610 silencing, CCK8, cell colony formation assay, and Celigo label-free cell counting assay were employed. Furthermore, transwell migration and invasion assays were conducted to evaluate the migratory and invasive abilities of the cells. The expression levels of genes and proteins were assessed using quantitative real-time polymerase chain reaction (qRT-PCR) and western blot techniques. In different LUAD cells, the expression level of ZNF610 was found to be significantly higher in LUAD cells compared to MRC-5 and BASE-2B cells. Moreover, the silencing of ZNF610 resulted in a decrease in cell proliferation and migration abilities. Additionally, the apoptosis rate of cells increased upon silencing ZNF610. Notably, the proportion of cells in the G0/G1 phase increased, while the proportion of cells in the S phase decreased following ZNF610 silencing. Finally, β-catenin and snail were identified as downstream targets of ZNF610 in cells. Our findings suggest that silencing ZNF610 could inhibit LUAD cell proliferation and migration, possibly through the downregulation of β-catenin and snail.

Cisplatin-based chemotherapy is frequently employed as the primary therapeutic approach for advanced lung cancer. Nevertheless, a significant proportion of patients may develop resistance to cisplatin, leading to diminished efficacy of chemotherapy. Through analysis of Gene Expression Omnibus databases, TSPAN6 has been identified as a key factor in conferring resistance to cisplatin, attributed to its activation of the NF-κB signaling pathway. Knockdown of TSPAN6 using siRNA resulted in decreased expression levels of NF-κB in A549 cells. This indicates that TSPAN6 may have dual effects on lung cancer cisplatin resistance and could serve as a promising therapeutic target for individuals with cisplatin resistance.

Aim: The study aims to identify high-impact single nucleotide polymorphisms (SNPs) in miRNA target sites of genes associated with lung cancer. Materials & methods: Lung cancer genes were obtained from Uniprot KB. miRNA target site SNPs were mined from MirSNP, miRdSNP and TargetScan. SNPs were shortlisted based on binding impact, minor allele frequency and conservation. Gene expression was analyzed in genes with high-impact SNPs in healthy versus lung cancer tissue. Additionally, enrichment, pathway and network analyzes were performed. Results: 19 high-impact SNPs were identified in miRNA target sites of lung cancer-associated genes. These SNPs affect miRNA binding and gene expression. The genes are involved in key cancer related pathways. Conclusion: The identified high-impact miRNA target site SNPs and associated genes provide a starting point for case-control studies in lung cancer patients in different populations.
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UNASSIGNED: In situations where pathological acquisition is difficult, there is a lack of consensus on distinguishing between adenocarcinoma and squamous cell carcinoma from imaging images, and each doctor can only make judgments based on their own experience. This study aims to extract imaging features of chest CT, extract sensitive factors through logistic univariate and multivariate analysis, and model to distinguish between lung squamous cell carcinoma and lung adenocarcinoma.
UNASSIGNED: We downloaded chest CT scans with clear diagnosis of adenocarcinoma and squamous cell carcinoma from The Cancer Imaging Archive (TCIA), extracted 19 imaging features by a radiologist and a thoracic surgeon, including location, spicule, lobulation, cavity, vacuolar sign, necrosis, pleural traction sign, vascular bundle sign, air bronchogram sign, calcification, enhancement degree, distance from pulmonary hilum, atelectasis, pulmonary hilum and bronchial lymph nodes, mediastinal lymph nodes, interlobular septal thickening, pulmonary metastasis, adjacent structures invasion, pleural effusion. Firstly, we apply the glm function of R language to perform logistic univariate analysis on all variables to select variables with P < 0.1. Then, perform logistic multivariate analysis on the selected variables to obtain a predictive model. Next, use the roc function in R language to calculate the AUC value and draw the ROC curve, use the val.prob function in R language to draw the Calibrat curve, and use the rmda package in R language to draw the DCA curve and clinical impact curve. At the same time, 45 patients diagnosed with lung squamous cell carcinoma and lung adenocarcinoma through surgery or biopsy in the Radiotherapy Department and Thoracic Surgery Department of our hospital from 2023 to 2024 were included in the validation group. The chest CT features were jointly determined and recorded by the two doctors mentioned above and included in the validation group. The included image feature data are complete and does not require preprocessing, so directly entering statistical calculations. Perform ROC curves, calibration curves, DCA, and clinical impact curves in the validation group to further validate the predictive model. If the predictive model performs well in the validation group, further draw a nomogram to demonstrate.
UNASSIGNED: This study extracted 19 imaging features from the chest CT scans of 75 patients downloaded from TCIA and finally selected 18 complete data for analysis. First, univariate analysis and multivariate analysis were performed, and a total of 5 variables were obtained: spicule, necrosis, air bronchogram Sign, atelectasis, pulmonary hilum and bronchial lymph nodes. After conducting modeling analysis with AUC = 0.887, a validation group was established using clinical cases from our hospital, Draw ROC curve with AUC = 0.865 in the validation group, evaluate the accuracy of the model through Calibrate calibration curve, evaluate the reliability of the model in clinical practice through DCA curve, and further evaluate the practicality of the model in clinical practice through clinical impact curve.
UNASSIGNED: It is possible to extract influential features from ordinary chest CT scans to determine lung adenocarcinoma and squamous cell carcinoma. The model we have set up performs well in terms of discrimination, accuracy, reliability, and practicality.