Our previous research demonstrated that the Wenxia Changfu Formula (WCF), as a neoadjuvant therapy, inhibits M2 macrophage infiltration in the tumor microenvironment and prevents lung cancer metastasis. Given tumor-associated macrophages (TAMs) in epithelial-mesenchymal transition (EMT), this study investigated whether WCF impedes lung cancer metastasis by attenuating TAM-induced EMT in non-small cell lung cancer (NSCLC) cells. Utilizing a co-culture model treated with or without WCF, we observed that WCF downregulated cluster of differentiation 163 (CD163) expression in macrophages, reduced CCL18 levels in the conditioned medium, and inhibited the growth, invasion, and EMT of NSCLC cells induced by macrophage co-culture. Manipulation of CCL18 levels and Src overexpression in NSCLC cells revealed that WCF's effects are mediated through CCL18 and Src signaling. In vivo, WCF inhibited recombinant CCL18 (rCCL18)-induced tumor metastasis in nude mice by blocking Src signaling. These findings indicate that WCF inhibits NSCLC metastasis by impeding TAM-induced EMT via antagonistic modulation of CCL18, providing evidence for its potential development and clinical application in NSCLC patients.
Epithelial-Mesenchymal Transition/drug effects* ; Carcinoma, Non-Small-Cell Lung/metabolism* ; Humans ; Animals ; Lung Neoplasms/metabolism* ; Chemokines, CC/antagonists & inhibitors* ; Mice ; Mice, Nude ; Drugs, Chinese Herbal/administration & dosage* ; Cell Line, Tumor ; Neoplasm Metastasis ; Tumor-Associated Macrophages/drug effects* ; Mice, Inbred BALB C ; Signal Transduction/drug effects*

The lungs are the most common sites of metastases from non-pulmonarymalignancies. Endobronchial metastases are rare and have no specificity in clinical manifestations,thus being prone to misdiagnosis and delayed treatment.The common tumors associated with endobronchial metastasis are renal,breast,and colorectal cancers.This article reported one case of postoperative rectal cancer with endobronchial and lung metastases,which was relieved by high-frequency electrocautery ablation via bronchoscope,chemotherapy,and targeted drugs,aiming to provide a reference for clinical diagnosis and treatment.
Humans ; Rectal Neoplasms/pathology* ; Electrocoagulation/methods* ; Bronchial Neoplasms/drug therapy* ; Bronchoscopy ; Lung Neoplasms/secondary* ; Bronchoscopes

OBJECTIVE: To explore the key target molecules and potential mechanisms of oridonin against non-small cell lung cancer (NSCLC). METHODS: The target molecules of oridonin were retrieved from SEA, STITCH, SuperPred and TargetPred databases; target genes associated with the treatment of NSCLC were retrieved from GeneCards, DisGeNET and TTD databases. Then, the overlapping target molecules between the drug and the disease were identified. The protein-protein interaction (PPI) was constructed using the STRING database according to overlapping targets, and Cytoscape was used to screen for key targets. Molecular docking verification were performed using AutoDockTools and PyMOL software. Using the DAVID database, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were conducted. The impact of oridonin on the proliferation and apoptosis of NSCLC cells was assessed using cell counting kit-8, cell proliferation EdU image kit, and Annexin V-FITC/PI apoptosis kit respectively. Moreover, real-time quantitative PCR and Western blot were used to verify the potential mechanisms. RESULTS: Fifty-six target molecules and 12 key target molecules of oridonin involved in NSCLC treatment were identified, including tumor protein 53 (TP53), Caspase-3, signal transducer and activator of transcription 3 (STAT3), mitogen-activated protein kinase kinase 8 (MAPK8), and mammalian target of rapamycin (mTOR). Molecular docking showed that oridonin and its key target molecules bind spontaneously. GO and KEGG enrichment analyses revealed cancer, apoptosis, phosphoinositide-3 kinase/protein kinase B (PI3K/Akt), and other signaling pathways. In vitro experiments showed that oridonin inhibited the proliferation, induced apoptosis, downregulated the expression of Bcl-2 and Akt, and upregulated the expression of Caspase-3. CONCLUSION Oridonin can act on multiple targets and pathways to exert its inhibitory effects on NSCLC, and its mechanism may be related to upregulating the expression of Caspase-3 and downregulating the expressions of Akt and Bcl-2.
Diterpenes, Kaurane/chemistry* ; Carcinoma, Non-Small-Cell Lung/pathology* ; Humans ; Network Pharmacology ; Lung Neoplasms/pathology* ; Cell Proliferation/drug effects* ; Apoptosis/drug effects* ; Molecular Docking Simulation ; Protein Interaction Maps/drug effects* ; Cell Line, Tumor ; Signal Transduction/drug effects* ; Gene Expression Regulation, Neoplastic/drug effects* ; Reproducibility of Results ; Gene Ontology

OBJECTIVES: Non-small cell lung cancer (NSCLC) is associated with poor prognosis, with 30% of patients diagnosed at an advanced stage. Mutations in the EGFR and KRAS genes are important prognostic factors for NSCLC, and targeted therapies can significantly improve survival in these patients. Although tissue biopsy remains the gold standard for detecting gene mutations, it has limitations, including invasiveness, sampling errors due to tumor heterogeneity, and poor reproducibility. This study aims to develop machine learning models based on radiomic features to predict EGFR and KRAS gene mutation status in NSCLC patients, thereby providing a reference for precision oncology. METHODS: Imaging and mutation data from eligible NSCLC patients were obtained from the publicly available Lung-PET-CT-Dx dataset in The Cancer Imaging Archive (TCIA). A three-dimensional-convolutional neural network (3D-CNN) was used to extract imaging features from the regions of interest (ROI). The LightGBM algorithm was employed to build classification models for predicting EGFR and KRAS gene mutation status. Model performance was evaluated using 5-fold cross-validation, with receiver operator characteristic (ROC) curves, area under the curve (AUC), accuracy, sensitivity, and specificity used for validation. RESULTS: The models effectively predicted EGFR and KRAS mutations in NSCLC patients, achieving an AUC of 0.95 for EGFR mutations and 0.90 for KRAS. The models also demonstrated high accuracy (EGFR 89.66%; KRAS 87.10%), sensitivity (EGFR 93.33%; KRAS 87.50%), and specificity (EGFR 85.71%; KRAS 86.67%). CONCLUSIONS A radiogenomics-machine learning predictive model can serve as a non-invasive tool for anticipating EGFR and KRAS gene mutation status in NSCLC patients.
Humans ; Carcinoma, Non-Small-Cell Lung/diagnostic imaging* ; Lung Neoplasms/diagnostic imaging* ; Mutation ; Proto-Oncogene Proteins p21(ras)/genetics* ; ErbB Receptors/genetics* ; Machine Learning ; Positron Emission Tomography Computed Tomography ; Female ; Male ; Neural Networks, Computer ; Middle Aged ; Aged

Brain metastasis has emerged as a significant challenge in the comprehensive management of patients with non-small cell lung cancer (NSCLC), particularly in those harboring driver gene mutations. Traditional treatments such as radiotherapy and surgery offer limited clinical benefits and are often accompanied by cognitive dysfunction and a decline in quality of life. In recent years, novel small molecule tyrosine kinase inhibitors targeting epidermal growth factor receptor (EGFR), anaplastic lymphoma kinase (ALK), and other pathways have been developed, effectively penetrating the blood-brain barrier while enhancing intracranial drug concentrations and improving patient outcomes. This advancement has transformed the treatment landscape for brain metastases in NSCLC. Consequently, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association and the Brain Metastasis Collaboration Group of the Lung Cancer Youth Expert Committee of the Beijing Medical Reward Foundation have jointly initiated and formulated the Clinical Practice Guidelines for the Management of Brain Metastases from Non-small Cell Lung Cancer with Actionable Gene Alterations in China (2025 Edition). This guideline integrates the latest research findings with clinical experience, adhering to multidisciplinary treatment principles, and encompasses aspects such as diagnosis, timing of intervention, and systemic and local treatment options for driver gene positive NSCLC brain metastases. Additionally, it proposes individualized treatment strategies tailored to different driver gene types, aiming to provide clinicians with a reference to enhance the overall diagnostic and therapeutic standards for NSCLC brain metastases in China.
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Humans ; Brain Neoplasms/drug therapy* ; Carcinoma, Non-Small-Cell Lung/pathology* ; China ; Lung Neoplasms/genetics*

BACKGROUND: In the real world, the plasma drug concentration range of Icotinib treated with epidermal growth factor receptor (EGFR) gene mutant non-small cell lung cancer (NSCLC) is not yet clear, and there may be a correlation between drug concentration and its efficacy, as well as adverse reactions. This study conducted therapeutic drug monitoring (TDM) of Icotinib. The aim of this study was to analyze the drug exposure of Icotinib in targeted therapy for NSCLC, and to investigate the relationship between Icotinib drug concentration and its efficacy and safety. METHODS: Prospective blood samples were collected from NSCLC patients with EGFR-sensitive mutations who received treatment with Icotinib in Peking University Cancer Hospital from April 2022 to July 2024. The drug trough concentration of Icotinib in plasma was detected, and the correlation between drug concentration and efficacy, as well as the toxic side effects, were further analyzed based on the patient's clinical medical records. RESULTS: 22 patients who were treated with Icotinib underwent TDM, but one of them did not acquire the data due to prolonged discontinuation. The remaining 21 patients, each with 1-7 blood draws, obtained a total of 32 plasma drug concentration data. The drug concentration of icotinib is a range of 126.9-2317.1 ng/mL. Among the 21 patients, 18 cases were female (85.7%), and 3 cases were male (14.3%), with an age range of 44-85 years old. The pathological types are all lung adenocarcinoma. Except for 5 patients receiving postoperative adjuvant therapy, 16 patients had assessable tumors. The objective response rate was 43.8% (7/16), and the disease control rate reached 100.0% (16/16). The median value of drug concentration is 805.5 ng/mL among those 21 patients. Compared with the patients who achieved stable disease, the median value of drug concentrations of Icotinib in patients who achieved partial response were 497.2 and 1195.5 ng/mL, respectively (P=0.017). The median value of drug concentrations for patients who did not experience adverse reactions during treatment and those who experienced adverse reactions were 997.0 and 828.6 ng/mL, respectively (P=0.538). CONCLUSIONS Icotinib demonstrates good therapeutic effect and tolerable toxicity on the EGFR gene mutant NSCLC. There is a certain negative correlation between the plasma drug concentration of Icotinib and its efficacy, while there seems no significant correlation with safety.
Humans ; Carcinoma, Non-Small-Cell Lung/genetics* ; ErbB Receptors/metabolism* ; Lung Neoplasms/genetics* ; Male ; Female ; Crown Ethers/blood* ; Middle Aged ; Drug Monitoring ; Aged ; Quinazolines/blood* ; Mutation ; Adult ; Aged, 80 and over ; Antineoplastic Agents/blood* ; Prospective Studies

Small cell lung cancer (SCLC) is a highly malignant disease that has garnered significant attention in terms of treatment modalities and course management. Gaining an understanding of the clinical characteristics of SCLC, acquiring proficiency in screening, diagnosis, and treatment methods for this condition, as well as promptly addressing any adverse reactions to treatment are essential foundations for developing a scientific and rational pathological management plan for SCLC. By utilizing an intelligent whole course follow-up management platform, dynamic follow-up, timely warnings, and early interventions can enable high-quality whole life cycle management. This article aims to review the current treatment landscape of SCLC while exploring the challenges associated with implementing a comprehensive process-oriented management approach. The goal is to provide valuable insights for better managing SCLC patients and ultimately improving their quality of life and prognosis.
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Humans ; Small Cell Lung Carcinoma/diagnosis* ; Lung Neoplasms/diagnosis* ; Quality of Life ; Follow-Up Studies

The mesenchymal-epithelial transition factor (MET) gene, located on human chromosome 7, plays a crucial role in the regulation of physiological processes such as cell proliferation, migration, invasion, and angiogenesis. The MET gene is one of the key drivers in non-small cell lung cancer (NSCLC), with various forms of abnormalities including MET exon 14 (METex14) skipping mutations, MET gene amplification, MET fusions, MET protein overexpression, MET activating mutations and etc. With an increasing understanding of the mechanisms underlying MET abnormalities, therapeutic strategies targeting these abnormalities have gained significant attention, and numerous studies have confirmed that NSCLC patients with MET abnormalities can derive substantial benefits from such treatments. Lung Cancer Specialty Committee of Chinese Elderly Health Care Association organized a panel of experts to provide professional recommendations on current clinical issues in the diagnosis and treatment of MET-aberrant NSCLC, combining clinical practice experiences and evidence-based medical evidences. The "Expert Consensus on Diagnosis and Treatment of NSCLC with MET Abnormalities (2025 Version)" has been formulated to provide standardized guidances for clinical practice in China, with the aim of optimizing the treatment outcomes.
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Humans ; Carcinoma, Non-Small-Cell Lung/drug therapy* ; Lung Neoplasms/drug therapy* ; Proto-Oncogene Proteins c-met/metabolism* ; Consensus ; Mutation

The tertiary lymphoid structure (TLS) plays a crucial role in the tumor microenvironment, influencing tumor development and progression. As an emerging biomarker for predicting the prognosis and treatment response in cancer patients, TLS has received increasing attention. However, there is currently a lack of standardized evaluation criteria for TLS, and significant differences exist in TLS across different tumor tissues. This poses challenges for the clinical application of this biomarker in translation. To meet the clinical diagnosis and treatment needs of non-small cell lung cancer (NSCLC), this consensus focuses on the definition, clinical significance, testing components, and assessment methods of TLS in NSCLC. Combining relevant research and Chinese clinical practice, it provides standardized and normalized suggestions for the clinical assessment and application of TLS, so as to improve the understanding of TLS among clinicians and pathologists, and provide a reference basis for the clinical application of the detection of TLS in NSCLC. 
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Humans ; Carcinoma, Non-Small-Cell Lung/immunology* ; Lung Neoplasms/immunology* ; Tertiary Lymphoid Structures/immunology* ; Consensus ; China ; East Asian People

BACKGROUND: Epidermal growth factor receptor (EGFR) sensitive mutation is one of the effective targets of targeted therapy for non-small cell lung cancer (NSCLC). However, due to the difficulty of obtaining some primary tissues and the economic factors in some underdeveloped areas, some patients cannot undergo traditional genetic testing. The aim of this study is to establish a machine learning (ML) model using non-invasive peripheral blood markers to explore the biomarkers closely related to EGFR mutation status in NSCLC and evaluate their potential prognostic value. METHODS: 2642 lung cancer patients who visited Jiangsu Cancer Hospital from November 2016 to May 2023 were retrospectively enrolled and finally 175 NSCLC patients with complete follow-up data were included in the study. The ML model was constructed based on peripheral blood indicators and divided into training set and test set according to the ratio of 8:2. Unsupervised learning algorithms were used for clustering blood features and mutual information method for feature selection, and an ensemble learning algorithm based on Shapley value was designed to calculate the contribution of each feature to the model prediction result. The receiver operating characteristic (ROC) curve was used to evaluate the predictive ability of the model. RESULTS: Through the feature extraction and contribution analysis of the predictive results of the interpretable ML model based on the Shapley value, the top ten indicators with the highest contribution were: pathological type, phosphorus, eosinophils, monocyte count, activated partial thromboplastin time, potassium, total bilirubin, sodium, eosinophil percentage, and total cholesterol. The area under the curve (AUC) of the model was 0.80. In addition, patients with hyponatremia and squamous cell carcinoma group had a poor prognosis (P<0.05). CONCLUSIONS The interpretable model constructed in this study provides a new approach for the prediction of EGFR mutation status in NSCLC patients, which provides a scientific basis for the diagnosis and treatment of patients who cannot undergo genetic testing.
Humans ; Carcinoma, Non-Small-Cell Lung/diagnosis* ; Machine Learning ; Lung Neoplasms/diagnosis* ; Male ; Female ; Mutation ; Middle Aged ; ErbB Receptors/genetics* ; Prognosis ; Aged ; Retrospective Studies ; Adult ; Biomarkers, Tumor/genetics*