ObjectiveTo investigate the risk factors for lymph node metastasis in resectable lung adenocarcinoma by combining spatial location, clinical, and imaging features, and to construct a lymph node metastasis prediction model. MethodsA retrospective study on patients who underwent chest computed tomography (CT) at the First Affiliated Hospital of Nanjing Medical University from June 2016 to June 2020 and were surgically confirmed to have invasive lung adenocarcinoma with or without lymph node metastasis was conducted. Patients were divided into a positive group and a negative group based on the presence or absence of lymph node metastasis. Clinical and imaging data of the patients were collected, and the independent risk factors for lymph node metastasis in resectable lung adenocarcinoma were analyzed using univariate and multivariate logistic regression. A combined spatial location-clinical-imaging feature prediction model for lymph node metastasis was established and compared with the traditional lymph node metastasis prediction model that does not include spatial location features. ResultsA total of 611 patients were included, with 333 in the positive group, including 172 males and 161 females, with an average age of (58.9±9.7) years; and 278 in the negative group, including 127 males and 151 females, with an average age of (60.1±11.4) years. Univariate and multivariate logistic regression analyses showed that the spatial relationship of the lesion to the lung hilum, nodule type, pleural changes, and serum carcinoembryonic antigen (CEA) levels were independent risk factors for lymph node metastasis. Based on this, the combined spatial location-clinical-imaging feature prediction model had a sensitivity of 91.67%, specificity of 74.05%, accuracy of 87.88%, and area under the curve (AUC) of 0.885. The traditional lymph node metastasis prediction model, which did not include spatial location features, had a sensitivity of 76.40%, specificity of 72.10%, accuracy of 53.86%, and AUC of 0.827. The difference in AUC between the two prediction methods was statistically significant (P=0.026). Compared with the traditional prediction model, the predictive performance of the combined spatial location-clinical-imaging feature prediction model was significantly improved. ConclusionIn patients with resectable lung adenocarcinoma, those with basal spatial location, solid density, pleural changes with wide base depression, and elevated serum CEA levels have a higher risk of lymph node metastasis.
Objective To analyze the expression of H2A histone family, member X (H2AFX) gene in lung adenocarcinoma and its influence on prognosis. Methods We analyzed the expression level of H2AFX gene in the tumor tissues (497 cases) and normal adjacent tissues (54 cases) of lung adenocarcinoma patients via The Cancer Genome Atlas. The patients were divided into high expression group and low expression group according to the expression level of H2AFX gene in lung adenocarcinoma samples. The relationship between H2AFX and clinicopathological features of patients was analyzed through logistic regression. Kaplan-Meier survival curve and log-rank test were used to study the correlation between H2AFX expression and the prognosis of lung adenocarcinoma patients. Univariate and multiple Cox regression analyses were performed to determine the prognostic significance of H2AFX expression in lung adenocarcinoma patients. The research also covered H2AFX-related pathways of genes in the development of lung adenocarcinoma with gene set enrichment analysis (GSEA). Results The H2AFX expression was higher in lung adenocarcinoma tissues than that in normal adjacent tissues (P<0.001). Besides, it was significantly correlated with age (P<0.001), T staging (P=0.007), and N staging (P=0.010), but had little to do with M staging or gender (P>0.05). Kaplan-Meier survival curve and log-rank test showed that the survival rate of patients with high H2AFX expression was vastly lower than that of patients with low H2AFX expression (P<0.001). Multiple Cox regression analysis demonstrated that H2AFX could be an independent prognostic factor for lung adenocarcinoma [hazard ratio=1.41, 95% confidence interval (1.11, 1.78), P=0.004]. The results of GSEA displayed that H2AFX was involved in cell cycle, homologous recombination, DNA replication, base excision and repair, spliceosome, mismatch repair, p53 signaling pathway, nucleotide excision and repair, RNA degradation, RNA polymerase, and other pathways. Conclusions The expression of H2AFX gene is high in lung adenocarcinoma, and closely connected to the prognosis, occurrence, and evolution of lung adenocarcinoma. This gene can be one of the new molecular markers and therapeutic targets for lung adenocarcinoma.
ObjectiveTo investigate the effect of different lymph node dissection methods on the prognosis of patients with stage ⅠA spread through air space (STAS)-positive lung adenocarcinoma≤ 2 cm. MethodsClinical data of 3148 patients with lung adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, the First Affiliated Hospital of University of Science and Technology of China from 2016 to 2018 were retrospectively analyzed. Patients with stage ⅠA STAS-positive lung adenocarcinoma≤ 2 cm were included and divided into two groups based on lymph node dissection methods: systematic lymph node dissection group and limited lymph node dissection group. Compare the clinical and pathological data of two groups of patients and use Cox proportional hazards regression model for multivariate survival analysis. ResultsA total of 209 STAS-positive patients were enrolled in the study, including 98 males and 111 females, aged 28-83 (60.42±10.15) years. Univariate analysis showed that the mode of lymph node dissection, past history, micropapillary histological subtype, and papillary histological subtype were risk factors for patient prognosis. Multifactorial analysis showed that lymph node dissection method, age, and micropapillary histological subtype were risk factors for patient prognosis. Meanwhile, among STAS-positive patients, systematic lymph node dissection had a better prognosis than limited lymph node dissection patients. ConclusionSTAS plays an important role in patient prognosis as an independent risk factor for prognosis of stage ⅠA ≤2 cm lung adenocarcinoma. When STAS is positive, the choice of systematic lymph node dissection may be more favourable to patients' long-term prognosis.
Objective To identify the immune cell-related biomarkers in lung adenocarcinoma using weighted gene co-expression network. Methods In this study, based on TCGA database, gene co-expression network was constructed in TCGA-LUAD by WGCNA package, and different gene modules were formed by clustering. At the same time, ESTIMATE analysis was performed on lung adenocarcinoma tumor samples in the TCGA-LUAD dataset. Gene enrichment pathways in the most significant related modules were evaluated by GO and KEGG assays. Candidate hub genes in the selected key modules were used to construct protein-protein interaction (PPI) network for intersection to obtain hub genes. The prognostic properties of these hub genes and patient immune cell infiltration were verified by Kaplan-Meier curve and TIMER algorithm. Multivariate Cox regression analysis was performed on the acquired hub gene and a prognostic risk model was constructed. Results In the co-expression network, we observed that the brown module was closely related to ImmuneScore, StromalScore and ESTIMATE Score. Five immune-related hub genes CD53, PLEK, SPI1, IL10RA and C3AR1 were obtained. The enrichment analysis of brown module found that module genes were mainly enriched in GO items such as innate immune response regulation and KEGG pathways such as NF-kappa B signaling pathway. In addition, the results of this study also found that the expression levels of 5 hub genes were significantly positively correlated with the infiltration abundance of immune cells. IPS and TIDE validated the immune relevance of the model. At the same time, we found that the RiskScore we established has great potential in predicting immunotherapy. Conclusion In summary, the five key genes related to immune cells obtained may provide new and effective potential targets for the immunotherapy of lung adenocarcinoma, which is also beneficial to provide personalized diagnosis and treatment strategies for patients with lung adenocarcinoma in the later stage.
Objective To investigate the effects of tobacco smoke exposure on histone deacetylase 2 (HDAC2),interleukin-8(IL-8)and tumor necrosis factor-α(TNF-α)expression in peripheral blood of patients with lung adenocarcinoma and analyze the relationships among them. Methods Seventy-three cases diagnosed as lung adenocarcinoma were collected in the First Affiliated Hospital and Affiliated Tumor Hospital of Guangxi Medical University from April 2014 to March 2015.All patients underwent lung function test preoperatively.Fourteen healthy volunteers without tobacco smoke exposure and chronic obstructive pulmonary disease (COPD)were recruited as healthy control.According to the lung function and tobacco smoke exposure,all cases were divided into four groups,ie. a healthy control group (group A,14 cases),a group without tobacco smoke exposure and COPD(group B,19 cases),a group with tobacco smoke exposure and without COPD(group C,33 cases),and a group with tobacco smoke exposure and COPD(group D,21 cases).The expressions of HDAC2 mRNA,IL-8 mRNA and TNF-α mRNA in peripheral blood mononuclear cells (PBMCs)were detected by real-time polymerase chain reaction (PCR).The contents of IL-8 and TNF-α in serum were detected by ELISA. Results Compared with group A,the HDAC2 mRNA expression in PBMCs had no difference in group B(P>0.05),and was down-regulated significantly in group C and D (P<0.05),which in group D was the most obvious.Compared with group A,the expressions of IL-8 mRNA and TNF-α mRNA in PBMCs and the contents of IL-8 and TNF-α in serum were significantly higher in all lung adenocarcinoma patients(all P<0.05),and the up-regulation was more obvious in group D.The relative expression of HDAC2 mRNA in PBMCs showed no significant difference with respect to age,gender or TNM stage (P>0.05).IL-8 and TNF-α in PBMCs and serum showed no significant difference with respect to age and gender (P>0.05),and were higher in the patients with TNM stage Ⅲ lung adenocarcinoma than those with stage Ⅰ and Ⅱ(P<0.05),with no obvious difference between stage Ⅰ and stage Ⅱ (P>0.05). Conclusion Tobacco smoke exposure causes lower expression of HDAC2 and over-expression of IL-8 and TNF-α in peripheral blood of patients with lung adenocarcinoma,can aggravate inflammatory response especially when complicated with COPD,which may be related to the prognosis of lung adenocarcinoma.
[Abstract]High-grade histologic subtypes of lung adenocarcinoma, such as micropapillary and solid patterns, are characterized by high invasiveness, increased risk of recurrence, and poor prognosis. Early preoperative identification of these subtypes is crucial for achieving individualized treatment and improving clinical outcomes. This review summarizes the clinical features, imaging manifestations, molecular mechanisms, and diagnostic advances related to these aggressive patterns. Studies have shown that micropapillary and solid subtypes are more common in male smokers, often present as solid nodules, and demonstrate strong predictive value in FDG-PET metabolic parameters and CT-based radiomics models. At the molecular level, EGFR mutations are more frequently observed in micropapillary types, whereas solid subtypes are often associated with high PD-L1 expression and TP53 mutations, indicating distinct therapeutic strategies for targeted and immunotherapies. In addition, serum markers such as CEA and CYFRA21-1, along with inflammatory indices like NLR and SII, may serve as auxiliary tools for subtype identification. Histologic subtypes of lung adenocarcinoma are evolving from descriptive classifications into critical determinants of treatment decisions and precision management. Clinicians should incorporate comprehensive histologic evaluation into individualized therapeutic planning. Multimodal integration technologies, combined with artificial intelligence algorithms, are advancing the accurate preoperative prediction and management of high-risk subtypes, thereby facilitating early diagnosis and stratified treatment of lung adenocarcinoma.
ObjectiveTo investigate the correlation between histological subtypes of invasive lung adenocarcinoma and epithelial growth factor receptor (EGFR) gene mutation, and to provide a reference for clinical prediction of EGFR gene mutation status.MethodsFrom October 2017 to May 2019, 102 patients with invasive lung adenocarcinoma were collected, including 58 males and 44 females aged 62 (31-84) years. Invasive lung adenocarcinoma was classified into different histological subtypes. Scorpion probe amplification block mutation system (ARMS) real-time PCR was used to detect the mutation of EGFR gene in adenocarcinoma specimens, and the relationship between invasive lung adenocarcinoma subtypes and EGFR mutation status was analyzed.ResultsIn 102 patients with invasive lung adenocarcinoma, EGFR gene mutations were detected in 68 patients, and the mutation rate was 66.7% (68/102). The mutation sites were mainly concentrated in the exons 19 and 21; the mutation rate was higher in female patients (34/44, 77.3%) and non-smokers (34/58, 58.6%). EGFR mutation was mostly caused by acinar-like invasive lung adenocarcinoma, and was rare in solid-type lung adenocarcinoma. The EGFR gene mutation rates in different subtypes of adenocarcinoma were statistically different (P<0.05).ConclusionThe EGFR mutation status is related to gender, smoking status and histological subtype of invasive lung adenocarcinoma. EGFR mutation rates are higher in female, non-smoking and acinar-like invasive lung adenocarcinoma patients, and are lower in patients with solid type lung adenocarcinoma.
Lung ground glass opacity (GGO), which is associated with the pathology of the lung adenocarcinoma, is drawing more and more attention with the increased detection rate. However, it is still in the research stage for the imaging interpretation of GGO lesions. In this paper, we reviewed and analyzed the new classification of lung adenocarcinoma corresponding to the interpretation of GGO imaging feature, which emphasizes on how to determine the GGO lesions comprehensively and quantitative determination of the invasive extent of GGO.
ObjectiveTo evaluate the clinical manifestation, radiological, pathological features and treatment of organizing pneumonia (OP) induced by aerosolized recombinant super compound interferon (rSIFN-co). MethodsClinical features and related laboratory examinations of a patient with OP developing after initiation of rSIFN-co for treatment of lung adenocarcinoma were analyzed, and the relevant literature was reviewed. ResultsA 48-year-old man developed cough, fevers, shortness of breath and weight loss, shortly half a month after initiation of therapy with rSIFN-co for lung adenocarcinoma. Chest high resolution computerized tomography (HRCT) showed multiple lung infection diseases. However, the anti-infection treatment was invalid. Lung tissue biopsy by bronchofibroscope was consistent with OP. After discontinuation of rSIFN-co and receiving pulse corticosteroid therapy followed by oral methylprednisolone, the pneumonic symptoms and chest manifestations markedly improved. After eight-month follow-up, the patient's condition was stable. The relative literature screening from Pubmed and Wanfangdata was implemented, but there was no report about OP caused by aerosolized rSIFN-co for lung adenocarcinoma. ConclusionThis report suggests that treatment with aerosolized rSIFN-co for lung adenocarcinoma may induce OP, a rare complication, and clinicians should have vigilance on it.
Lung adenocarcinoma is a prevalent histological subtype of non-small cell lung cancer with different morphologic and molecular features that are critical for prognosis and treatment planning. In recent years, with the development of artificial intelligence technology, its application in the study of pathological subtypes and gene expression of lung adenocarcinoma has gained widespread attention. This paper reviews the research progress of machine learning and deep learning in pathological subtypes classification and gene expression analysis of lung adenocarcinoma, and some problems and challenges at the present stage are summarized and the future directions of artificial intelligence in lung adenocarcinoma research are foreseen.