BACKGROUND AND OBJECTIVE:Spread through air spaces (STAS) is an important factor in determining the aggressiveness and recurrence risk of lung cancer, especially in early-stage adenocarcinoma. Preoperative identification of STAS is crucial for optimizing surgical strategies. This study aimed to develop and validate machine learning models to predict the presence of STAS using preoperative clinical, radiological, and pathological data in lung cancer patients. PATIENTS AND METHODS:A retrospective analysis was conducted on 1,290 lung cancer patients from two hospitals: Qilu Hospital of Shandong University and Qianfoshan Hospital. Data from 1,174 patients from Qilu Hospital were used for model training and internal validation, while 116 patients from Qianfoshan Hospital were used for external validation. Thirteen key variables, identified using least absolute shrinkage and selection operator (LASSO) regression, were included in the construction of eight machine learning models: decision tree (DT), random forest (RF), regularized support vector machine (RSVM), logistic regression (LR), extreme gradient boosting (XGBoost), multilayer perceptron (MLP), light gradient boosting machine (LightGBM), and K-nearest neighbors (KNN). Model performance was evaluated using receiver operating characteristic (ROC) curves, area under the curve (AUC), calibration curves, decision curve analysis (DCA), and SHapley additive explanations (SHAP) plots. RESULTS:The XGBoost model achieved the best performance with an AUC of 0.931 (95% CI: 0.897-0.964) in the internal validation cohort and 0.904 (95% CI: 0.835-0.973) in the external validation cohort, outperforming other models. DCA demonstrated the clinical utility of XGBoost, LightGBM, and RF models, which provided superior net benefit across various threshold probabilities. SHAP analysis revealed that the most influential factors in predicting STAS were carcinoembryonic antigen (CEA), forced expiratory volume in one second (FEV1), consolidation-to-tumor ratio (CTR), maximal voluntary ventilation (MVV), and CT value. CONCLUSION:The XGBoost model demonstrated robust predictive performance for preoperative identification of STAS in lung cancer patients, showing high generalizability in external validation. These findings suggest that machine learning-based predictions could guide clinical decision-making and improve surgical outcomes by identifying high-risk patients for more aggressive treatment strategies.

BackgroundNeoadjuvant therapy (NT) has increased survival rates for patients with locally advanced esophageal cancer (EC), but estimating the impact of NT treatment prior to surgery is still very difficult.MethodsA retrospective study of the clinical information of 150 patients with locally advanced EC who got NT at Qilu Hospital of Shandong University between June 2018 and June 2023. Patients were randomized into training and internal validation groups at a 3:1 ratio. Furthermore, an external validation cohort comprised 38 patients who underwent neoadjuvant therapy at Qianfoshan Hospital in the Shandong Province between June 2021 and June 2023. Independent risk factors were identified using univariate and multivariate logistic regression (forward stepwise regression). Predictive models and dynamic web nomograms were developed by integrating these risk factors.ResultsA total of 188 patients with locally advanced EC were enrolled, of whom 118 achieved stage I of neoadjuvant pathologic TNM (ypTNM) after receiving NT and 129 achieved grades 0-1 in the tumor regression grade (TRG). Logistic regression analysis identified five independent predictors of TRG grades 0-1: pulmonary function tests (PFT), prognostic nutritional index (PNI), triglyceride (TG) levels, squamous cell carcinoma antigen (SCC-Ag) levels, and combination immunotherapy. The areas under the receiver operating characteristic (ROC) curves for the training, internal validation, and external validation groups were 0.87, 0.75, and 0.80, respectively. Meanwhile, two independent predictors of stage I of ypTNM were identified: prealbumin (PA) and SCC antigen. The areas under the ROC curves for the training, internal validation, and external validation groups were 0.78, 0.67, and 0.70, respectively. The Hosmer-Lemeshow test for both predictive models showed excellent calibration, with well-fitted calibration curves. Decision curve analysis (DCA) and clinical impact curves (CIC) have demonstrated that nomograms are of clinical utility.ConclusionThe nomograms performed well in predicting the likelihood of stage I of ypTNM and TRG grade 0-1 after NT in patients with locally advanced EC. It helps thoracic surgeons to predict the sensitivity of patients to NT before surgery, which enables precise treatment of patients with locally advanced EC.

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-β)/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.

The role of Basic leucine zipper and W2 domains 2 (BZW2) in the advancement of different types of tumors is noteworthy, but its involvement and molecular mechanisms in lung adenocarcinoma (LUAD) remain uncertain. Through this investigation, it was found that the upregulation of BZW2 was observed in LUAD tissues, which was associated with an unfavorable prognosis for individuals diagnosed with LUAD, as indicated by data from Gene Expression Omnibus and The Cancer Genome Atlas databases. Based on the clinicopathologic characteristics of LUAD patients from the tissue microarray, both univariate and multivariate analyses indicated that BZW2 functioned as an independent prognostic factor for LUAD. In terms of mechanism, BZW2 interacted with glycogen synthase kinase-3 beta (GSK3β) and enhanced the ubiquitination-mediated degradation of GSK3β through slowing down of the dissociation of the ubiquitin ligase complex, which consists of GSK3β and TNF receptor-associated factor 6. Moreover, BZW2 stimulated Wnt/β-catenin signaling pathway through GSK3β, thereby facilitating the advancement of LUAD. In conclusion, BZW2 was a significant promoter of LUAD. The research we conducted identified a promising diagnostic and therapeutic target for LUAD.

BACKGROUND:Effective targeted therapy for lung adenocarcinoma (LUAD), the number one cancer killer worldwide, continues to be a difficult problem because of the limitation of number of applicable patients and acquired resistance. Identifying more promising drug targets for LUAD treatment holds immense clinical significance. Recent studies have revealed that the U2 auxiliary factor (U2AF) homology motif kinase 1 (UHMK1) is a robust pro-oncogenic factor in many cancers. However, its biological functions and the underlying molecular mechanisms in LUAD have not been investigated. METHODS:The UHMK1 expression in LUAD cells and tissues was evaluated by bioinformatics analysis, immunohistochemistry (IHC), western blotting (WB), and real time quantitative polymerase chain reaction (RT-qPCR) assays. A series of gain- and loss-of-function experiments for UHMK1 were carried out to investigate its biological functions in LUAD in vitro and in vivo. The mechanisms underlying UHMK1's effects in LUAD were analyzed by transcriptome sequencing and WB assays. RESULTS:UHMK1 expression was aberrantly elevated in LUAD tumors and cell lines and positively correlated with tumor size and unfavorable patient prognosis. Functionally, UHMK1 displayed robust pro-oncogenic capacity in LUAD and mechanistically exerted its biological effects via the phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) signaling pathway. CONCLUSION:UHMK1 is a potent oncogene in LUAD. Targeting UHMK1 may significantly improve the effect of LUAD treatment via inhibiting multiple biological ways of LUAD progression.

Background:Cyclin O (CCNO) is a novel cyclin family protein containing a cyclin-like domain, which plays a role in cell cycle regulation. Recent research suggests that inhibition of CCNO leads to cell apoptosis in gastric cancer, cervical squamous cell carcinoma, and post-operative lung cancer.Methods:The protein expression and signal transduction were detected by Western blot (WB) and immunohistochemistry (IHC). Overexpression or lacking CCNO stable cell lines were transfected with lentiviruses and selected with puromycin. The tumor behaviors of lung adenocarcinoma (LUAD) cells were assessed: cell proliferation by 5-Ethynyl-2'-deoxyuridine (EdU) staining and Cell Counting Kit-8 (CCK8) assay, cell cycle and by flow cytometry analysis, and migration and invasion using wound healing and Transwell system. Co-immunoprecipitation was used to detect protein-protein interactions. Xenograft models for evaluating tumor growth and anti-tumor drug efficacy.Results:A higher expression of CCNO was observed in LUAD cancer tissues and predicted the overall survival of LUAD patients. Moreover, CCNO expression was negatively correlated with cancer cell proliferation, migration, and invasion. Co-immunoprecipitation and western blot indicated that CCNO interacted with CDK13 to promote cancer cell proliferation signaling activation. Furthermore, CCNO promoted tumor cell growth and cetuximab resistance in vivo, and a CDK13 inhibitor effectively inhibited the oncological effect of CCNO.Conclusions:The current study suggests that CCNO may be a driver in the development of LUAD and that its function is related to CDK13 interaction that promotes proliferation signaling activation.

[This corrects the article DOI: 10.3389/fcell.2021.771824.].

BACKGROUND:Circular RNA (circRNA) has become a new focus in the field of tumor biology research in recent years. Many circRNAs have been showed to play an important role in the progression of lung adenocarcinoma (LUAD). In this work, we studied the oncological role of hsa-circ-000881 in LUAD and attempted to explore the related mechanism.METHODS:The relative expressions of hsa-circ-000881, miR-665, and PRICKLE2 were detected by RT-qPCR or western blot. Functional assays were conducted to analyze the role of hsa-circ-000881 in the proliferation, migration, and invasion of LUAD cells. A luciferase reporter assay was performed to verify whether hsa-circ-000881, miR-665, and PRICKLE2 interact with each other.RESULTS:Circ-000881 was remarkably downregulated in LUAD. Overexpression of circ-000881 attenuated cell growth, migration, and invasion, whereas its knockdown enhanced the malignancy of LUAD cells. The results of luciferase reporter assay and bioinformatics analysis confirmed that circ-000881 served as a sponge for miR-665, and PRICKLE2 was a direct target of miR-665.Overexpression of miR-665 or silencing of PRICKLE2 abolished circ-000881-mediated inhibition of malignant tumor behavior in LUAD cells.CONCLUSIONS:Circ-000881 has inhibitory effects on LUAD via a miR-665/PRICKLE2 axis, suggesting that circ-000881 may be an underlying therapeutic target for LUAD.

Lung adenocarcinoma (LUAD) is a common malignant cancer worldwide. It is urgent to explore its underlying molecular mechanism and identify novel diagnostic biomarkers. Abnormal spindle-like microcephaly (ASPM) has recently received considerable attention due to its function in tumor progression. However, its role in LUAD is unclear. The present study aimed to explore the clinical role of ASPM in LUAD. Seven pairs of LUAD and adjacent normal tissues were collected to identify potential LUAD biomarkers using transcriptome sequencing. The association between ASPM expression and LUAD progression was evaluated using bioinformatics analysis and data obtained from clinical specimens. Using small interfering RNA technology, the function of ASPM was analyzed in the LUAD H1299 and A549 cell lines. Transcriptional profiling of ASPM-deficient H1299 cells was then performed to determine the downstream targets of ASPM. Using databases and clinical specimens, it was revealed that ASPM expression was frequently elevated in LUAD tissues, and this upregulation was highly associated with LUAD progression. ASPM served as an oncogenic regulator of LUAD cell proliferation and metastasis. Mechanistically, ASPM facilitated epithelial-mesenchymal transition (EMT) via the PI3K/AKT signaling pathway and 740 Y-P, an activator of this pathway, restored the migratory ability of ASPM-knockdown LUAD cells. The current study identified ASPM as an independent prognostic biomarker of LUAD that served an important oncogenic role in regulating LUAD cell metastasis by promoting EMT via the PI3K/AKT signaling pathway. Targeting ASPM may therefore be a therapeutic strategy for treating LUAD.

Background: Lung adenocarcinoma (LUAD) is the major form of lung cancer that presents a major peril to public health. Owing to the high rates of morbidity, mortality and chemoresistance, it is necessary to develop more effective therapeutic targets of LUAD. Mitochondrial fission regulator 1 (MTFR1) affects the occurrence and development of some diseases by regulating mitochondrial dynamics and is dysregulated in LUAD. However, the functions and molecular mechanisms of MTFR1 in LUAD have not been investigated.Methods: Immunohistochemical (IHC) analysis, real-time quantitative polymerase chain reaction (RT-qPCR), bioinformatic analysis and western blot (WB) were performed to assess the expression of MTFR1 at both protein and mRNA levels. The biological functions of MTFR1 in LUAD cells were assessed based on various in vivo and in vitro experiments. The dual-luciferase reporter assay and some rescue experiments were performed to evaluate the underlying mechanism of MTFR1 in LUAD.Results: MTFR1 was upregulated in LUAD cells and tissues and correlated with dismal clinicopathologic features and a worse prognosis of patients with LUAD. Functionally, MTFR1 overexpression stimulated the proliferation, invasion, migration and glycolytic capacity and impeded the apoptosis of LUAD cells; however, opposite results were obtained when MTFR1 expression was knocked down. MTFR1, which was directly targeted by miR-29c-3p, may exert its biological functions through the AMPK/mTOR signalling pathway.Conclusion: MTFR1 promotes the progression of LUAD. Therefore, targeting MTFR1 can offer an effective therapeutic strategy for LUAD treatment.

Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer that results in the majority of cancer-associated mortality. Multiple copies in T-cell lymphoma-1 (MCTS1) is an oncogene that is expressed at high levels in several types of cancer tissues. However, its exact role and pathomechanism in the development of LUAD remains unknown. Reverse transcription-quantitative PCR analysis was performed to detect MCTS1 expression. Immunohistochemistry analysis was performed to detect MCTS1 expression in LUAD tissues and normal tissues. The MTT, colony formation, EdU, flow cytometry, wound healing and Transwell assays were performed to assess the proliferation, apoptosis, migration and invasion of LUAD cells. Western blot analysis was performed to detect protein expression levels. The present study aimed to investigate the effects of MCTS1 on the progression of LUAD and the potential mechanisms underlying its effects. The results demonstrated that MCTS1 expression was upregulated in LUAD tissues and cells, which was associated with an unfavorable outcome in patients with LUAD. MCTS1 knockdown inhibited LUAD progression by suppressing cell viability and motility, and promoting apoptosis. In addition, E2F1 protein expression was attenuated following MCTS1 knockdown. The silencing MCTS1-induced inhibitory effect on LUAD malignancy was reversed following overexpression of E2F1 by modulating the c-Myc signaling pathway. Taken together, the results of the present study suggest that MCTS1 facilitates cell proliferation and migration, and suppresses apoptosis of LUAD cells by regulating E2F1 expression and the c-Myc signaling pathway.

Esophageal squamous cell carcinoma (ESCC) is a life-threatening thoracic tumor with a poor prognosis. The role of molecular alterations and the immune microenvironment in ESCC development has not been fully elucidated. The present study aimed to elucidate key candidate genes and immune cell infiltration characteristics in ESCC by integrated bioinformatics analysis. Nine gene expression datasets from the Gene Expression Omnibus (GEO) database were analysed to identify robust differentially expressed genes (DEGs) using the robust rank aggregation (RRA) algorithm. Functional enrichment analyses showed that the 152 robust DEGs are involved in multiple processes in the tumor microenvironment (TME). Immune cell infiltration analysis based on the 9 normalized GEO microarray datasets was conducted with the CIBERSORT algorithm. The changes in macrophages between ESCC and normal tissues were particularly obvious. In ESCC tissues, M0 and M1 macrophages were increased dramatically, while M2 macrophages were decreased. A robust DEG-based protein–protein interaction (PPI) network was used for hub gene selection with the CytoHubba plugin in Cytoscape. Nine hub genes (CDA, CXCL1, IGFBP3, MMP3, MMP11, PLAU, SERPINE1, SPP1 and VCAN) had high diagnostic efficiency for ESCC according to receiver operating characteristic (ROC) curve analysis. The expression of all hub genes except MMP3 and PLAU was significantly related to macrophage infiltration. Univariate and multivariate regression analyses showed that a 7-gene signature constructed from the robust DEGs was useful for predicting ESCC prognosis. Our results might facilitate the exploration of potential targeted TME therapies and prognostic evaluation in ESCC.

Background Lung cancer is a malignant tumor with the highest morbidity and mortality rates worldwide, of which lung adenocarcinoma (LUAD) is the most common subtype. Overall, current treatments of LUAD are not satisfactory; therefore, novel targets need to be explored. Let-7b-3p is an important member of the let-7 family of microRNAs (miRNAs), and has not been studied separately in LUAD. This study aimed to investigate the role and molecular mechanism of let-7b-3p in LUAD. Methods Herein, let-7b-3p expression was detected by quantitative real-time polymerase chain reaction (qRT-PCR) and fluorescence in situ hybridization (FISH) assays. MTT, colony formation assay, flow cytometry analysis, wound-healing, Transwell and in vivo experiments were conducted to assess let-7b-3p’s function in LUAD. The downstream target TFIIB-related factor 2 (BRF2) was predicted using bioinformatics analyses and confirmed by dual-luciferase reporter assay and rescue experiments. Additionally, BRF2 was found to affect the MAPK/ERK pathway through transcriptome sequencing analysis and western blot (WB) assay. Results Let-7b-3p is downregulated in LUAD cells and tissue samples and low let-7b-3p expression is correlated with a poor prognosis in LUAD patients. Let-7b-3p suppresses the proliferation and metastasis of LUAD cells both in vivo and in vitro by directly targeting the BRF2-mediated MAPK/ERK pathway. Conclusions Let-7b-3p inhibits the development of LUAD and is an ideal novel therapeutic target for the treatment of LUAD.

Abstract Background: Increasing studies have found the dysregulated FAM83A as a potential biomarker in various cancers. Its function in cancer cells is largely unknown, and especially their role in LUSC remains unclear. We detected the expression level and prognosis role of FAM83A in LUSC.Methods: The bioinformatics methods were performed initially to predict the expression level and prognostic value of FAM83A mRNA in LUSC. We used IHC to examine its protein expression level and identify its prognostic value using 132 pairs of tissues.Results: Results from TCGA and Oncomine databases revealed that FAM83A mRNA expression level was significantly higher in LUSC than that in normal lung tissue. TCGA and GEO databases revealed FAM83A mRNA overexpression was significantly associated with poorer OS of LUSC patients (all P<0.05). Furtherly, our IHC results revealed that FAM83A was overexpressed in 78 (59.1%) patients and 19(14.4%) pancancerous tissues (P<0.001). Kaplan-Meier analyses revealed that high FAM83A protein expression was significantly associated with decreased 5-years’ OS (P = 0.007) and PFS (P = 0.007). Via multivariate analysis, FAM83A expression level was independent prognostic factor for both OS (P = 0.006) and PFS (P = 0.002).Conclusion: FAM83A was overexpressed in LUSC and it could serve as a prognosis prediction biomarker for LUSC. FAM83A could act as one new potential therapeutic target for LUSC treatment.

Lung adenocarcinoma (LUAD) is the main subtype of lung cancer. In this study, we found that RBP Mex3a was significantly upregulated in LUAD tissues and elevated Mex3a expression was associated with poor LUAD prognosis and metastasis. Furthermore, we demonstrated that Mex3a knockdown significantly inhibited LUAD cell migration and invasion in vitro and metastasis in nude mice. Transcriptome sequencing indicated that Mex3a affected gene expression linked to ECM-receptor interactions, including laminin subunit alpha 2(LAMA2). RNA immunoprecipitation (RIP) assay revealed Mex3a directly bound to LAMA2 mRNA and Mex3a increased the instability of LAMA2 mRNA in LUAD cells. Furthermore, we discovered that LAMA2 was surprisingly downregulated in LUAD and inhibited LUAD metastasis. LAMA2 knockdown partially reverse the decrease of cell migration and invasion caused by Mex3a knockdown. In addition, we found that both Mex3a and LAMA2 could influence PI3K-AKT pathway, which are downstream effectors of the ECM-receptor pathway. Moreover, the reduced activation of PI3K-AKT pathway in caused by Mex3a depletion was rescued by LAMA2 knockdown. In conclusion, we demonstrated that Mex3a downregulates LAMA2 expression to exert a prometastatic role in LUAD. Our study revealed the prognostic and prometastatic effects of Mex3a in LUAD, suggesting that Mex3a can serve as a prognostic biomarker and a target for metastatic therapy.