Lung cancer, particularly non-small cell lung cancer (NSCLC), is a leading cause of cancer-related mortality worldwide. In recent years, metabolomics has emerged as a key systems biology approach for analyzing small-molecule metabolites in cells, tissues and organisms. It provides new strategies for early diagnosis and metabolic profiling. Additionally, metabolomics plays a crucial role in studying resistance mechanisms in lung cancer. Tumor cell metabolic reprogramming is a key driving factor in the initiation and progression of lung cancer. Metabolomics studies have revealed how lung cancer cells regulate critical pathways such as energy metabolism, lipid metabolism, and amino acid metabolism to adapt to the demands of rapid proliferation and invasive metastasis. This review summarizes the latest advances in metabolomics research in lung cancer, focusing on the characteristics of metabolic reprogramming, the identification of potential metabolic biomarkers, and the prospects of metabolomics in early diagnosis and the elucidation of resistance mechanisms in lung cancer.
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Humans ; Metabolomics/methods* ; Lung Neoplasms/pathology* ; Animals ; Biomarkers, Tumor/metabolism*

Objective To explore the application of artificial intelligence (AI) in the standardized training of thoracic surgery residents, specifically in enhancing clinical skills and anatomical understanding through AI-assisted lung nodule identification and lung segment anatomy teaching. Methods Thoracic surgery residents undergoing standardized training at Peking Union Medical College Hospital from September 2023 to September 2024 were selected. They were randomly assigned to a trial group and a control group using a random number table. The trial group used AI-assisted three-dimensional reconstruction technology for lung nodule identification, while the control group used conventional chest CT images. After basic teaching and self-practice, the ability to identify lung nodules on the same patient CT images was evaluated, and feedback was collected through questionnaires. Results A total of 72 residents participated in the study, including 30 (41.7%) males and 42 (58.3%) females, with an average age of (24.0±3.0) years. The trial group showed significantly better overall diagnostic accuracy for lung nodules (91.9% vs. 73.3%) and lung segment identification (100.0% vs. 83.70%) compared to the control group, and the reading time was significantly shorter [ (118.5±10.5) s vs. (332.1±20.2) s, P<0.01]. Questionnaire results indicated that 94.4% of the residents had a positive attitude toward AI technology, and 91.7% believed that it improved diagnostic accuracy. Conclusion AI-assisted teaching significantly improves thoracic surgery residents’ ability to read images and clinical thinking, providing a new direction for the reform of standardized training.

To investigate the influencing factors of postoperative complications following thoracoscopic lung resection in elderly patients and to provide a scientific basis for developing preoperative prehabilitation strategies for high-risk elderly populations.

Due to the advancement of 16S rRNA sequencing technology, the lower respiratory tract microbiota, which was considered non-existent, has been revealed. The correlation between these microorganisms and diseases such as tumor has been a hot topic in recent years. As the bacteria in the surrounding can infiltrate the tumors, researchers have also begun to pay attention to the biological behavior of tumor bacteria and their interaction with tumors. In this review, we present the characteristic of the lower respiratory tract bacteria and summarize recent research findings on the relationship between these microbiota and lung cancer. On top of that, we also summarize the basic feature of bacteria in tumors and focus on the characteristic of the bacteria in lung cancer. The relationship between bacteria in lung cancer and tumor development is also been discussed. Finally, we review the potential clinical applications of bacterial communities in the lower respiratory tract and lung cancer, and summarize key points of sample collection, sequencing, and contamination control, hoping to provide new ideas for the screening and treatment of tumors.
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Humans ; Lung Neoplasms ; RNA, Ribosomal, 16S/genetics* ; Bacteria/genetics* ; Microbiota ; Respiratory System ; Lung/microbiology*

The continuous advancement of molecular detection technology has greatly propelled the develop-ment of precision medicine for lung cancer.However,tumor heterogeneity is closely associated with tumor metastasis,recurrence,and drug resistance.Additionally,different lung cancer patients with the same genetic mutation may exhibit varying treatment responses to different therapeutic strategies.Therefore,the development of modern precision medicine urgently requires the precise formulation of personalized treatment strategies through personalized tumor models.Lung cancer organoid(LCO)can highly simulate the biological characteristics of tumor in vivo,facilitating the application of innovative drugs such as antibody-drug conjugate in precision medicine for lung cancer.With the development of co-culture model of LCO with tumor microenvironment and tissue engineering technology such as microfluidic chip,LCO can better preserve the biological characteristics and functions of tumor tissue,further improving high-throughput and automated drug sensitivity experiment.In this review,we combine the latest research progress to summarize the applica-tion progress and challenges of LCO in precision medicine for lung cancer.

Minute pulmonary meningothelial-like nodules (MPMNs) are benign small lesions in the lungs, with similar pathological characteristics to the meningeal epithelium. MPMNs have similar imaging manifestations to malignant tumors, which can lead to misdiagnosis in clinical practice. There is no consensus on the pathogenesis of MPMNs, with some suggest that MPMNs derive from reactive proliferation, while others suggest that MPMNs share a common origin and molecular mechanism with meningiomas in the central nervous system. Understanding the characteristics of MPMNs and studying their pathogenesis will help improve the understanding and diagnosis of MPMNs. In this article, we reviewed the clinical, pathological, imaging characteristics, differential diagnosis and pathogenesis of MPMNs. We also analyze the existing research advances regarding the pathogenesis and propose prospects for further research.
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Thymic epithelial tumor is a rare anterior mediastinal tumor. Surgery is the most important treatment for thymic tumors. However, non-surgical treatment is still an inevitable choice for unresectable advanced thymic tumors. The traditional treatment methods include chemotherapy and radiotherapy, but the effect is limited. With the development of immunotherapy therapy, some studies have attempted the exploration of immunotherapy for thymic tumors. Because of the low incidence rate of thymic tumors, these studies are mostly small retrospective analyses. This article review the clinical and basic research progress of immunotherapy for thymic tumors

Lung cancer is one of the leading causes of cancer-related morbidity and mortality. Epidermal growth factor receptor tyrosine kinase inhibitor (EGFR-TKI) have become the standard treatment for EGFR-mutated advanced non-small cell lung cancer (NSCLC). Unfortunately, drug resistance is inevitable in most cases. EGFR-TKI combined with angiogenesis inhibitors is a treatment scheme being explored to delay the therapeutic resistance, which is called "A+T treatment". Several clinical trials have demonstrated that the A+T treatment can improve the progression free survival (PFS) of the NSCLC patients. However, compared to EGFR-TKI monotherapy, the benefits of the A+T treatment based on different EGFR-TKIs, as well as its safety and exploration prospects are still unclear. Therefore, we reviewed the literature related to all three generations EGFR-TKIs combined with angiogenesis inhibitors, and summarized the mechanism, benefit, safety, optimal target population of A+T treatment.
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Angiogenesis Inhibitors/therapeutic use* ; Carcinoma, Non-Small-Cell Lung/genetics* ; ErbB Receptors/genetics* ; Humans ; Lung Neoplasms/genetics* ; Mutation ; Protein Kinase Inhibitors/therapeutic use*

Lung cancer is the most frequent cancer and the leading cause of cancer death all around the world. Anti-programmed cell death 1 (PD-1)/programmed cell death-ligand 1 (PD-L1) therapies have significantly improved the outcomes of non-small cell lung cancer (NSCLC) patients in recent years. However, the objective response rate in non-screened patients is only about 20%. It is very important to screen out the potential patients suitable for immunotherapy. Immunohistochemical staining of tumor tissue biopsies with PD-L1 antibodies can predict the therapeutic response to immunotherapy to some extent, but it still has some limitations. Recently some clinical studies have shown that PD-L1 expression in circulating tumor cells (CTC-PD-L1) is a potential independent biomarker and may provide important information for immunotherapy in NSCLC. This article will review technology for CTC-PD-L1 detection and the predictive value of CTC-PD-L1 for immunotherapy in NSCLC and review the latest clinical research progress.

With the broad application of high-resolution computed tomography (CT) and high rates of early lung cancer screening, the number of patients diagnosed with synchronous multiple primary lung cancer (sMPLC) has been increasing. It becomes of great prominence to distinct sMPLC from intrapulmonary metastases in clinical practice. An increasing number of studies have developed high-throughput sequencing based genetic approaches to specify the molecular characteristics of sMPLC, which contributes to a better understanding of its tumorigenesis. The genetic profile of sMPLC also benefits its diagnosis, which mainly relies on its clinicopathological criteria. Here, we summarize the progresses on the diagnostic criteria for sMPLC, and also molecular features of sMPLC from the perspective of clonality analysis.