Lung cancer is one of the malignant tumors with the greatest threat to human health, and studies have shown that some genes play an important regulatory role in the occurrence and development of lung cancer. In this paper, a LightGBM ensemble learning method is proposed to construct a prognostic model based on immune relate gene (IRG) profile data and clinical data to predict the prognostic survival rate of lung adenocarcinoma patients. First, this method used the Limma package for differential gene expression, used CoxPH regression analysis to screen the IRG to prognosis, and then used XGBoost algorithm to score the importance of the IRG features. Finally, the LASSO regression analysis was used to select IRG that could be used to construct a prognostic model, and a total of 17 IRG features were obtained that could be used to construct model. LightGBM was trained according to the IRG screened. The K-means algorithm was used to divide the patients into three groups, and the area under curve (AUC) of receiver operating characteristic (ROC) of the model output showed that the accuracy of the model in predicting the survival rates of the three groups of patients was 96%, 98% and 96%, respectively. The experimental results show that the model proposed in this paper can divide patients with lung adenocarcinoma into three groups [5-year survival rate higher than 65% (group 1), lower than 65% but higher than 30% (group 2) and lower than 30% (group 3)] and can accurately predict the 5-year survival rate of lung adenocarcinoma patients.
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.
Diabetic retinopathy (DR) is a serious complication of diabetes mellitus that not only impairs vision and quality of life but has also emerged as a leading cause of blindness in working-age individuals. Long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (LncMALAT1) is a non-coding RNA molecule that regulates gene expression and has been implicated in the pathogenesis and progression of DR. It exerts its effects through the modulation of various pathological processes, including inflammation, oxidative stress, angiogenesis, and apoptosis. Notably, alterations in the expression levels of LncMALAT1 may serve as potential biomarkers for the early diagnosis of DR. Furthermore, interventions targeting LncMALAT1, employing antioxidants, anti-angiogenic agents, traditional Chinese medicine, and gene therapy, present promising avenues for its potential development as an effective therapeutic target for DR.
With the development of multi-slice spiral computed tomography (CT) technology and the popularization of low-dose spiral CT screening, more and more adenocarcinomas presenting ground-glass nodule (GGN) are found. Pathological invasiveness is one of the important factors affecting the choice of treatment strategy and prognosis of patients with early lung adenocarcinoma. Imaging features have attracted wide attention due to their unique advantages in predicting the pathologic invasiveness of early lung adenocarcinoma. The imaging characteristics of GGN can be used to predict the pathologic invasiveness of lung adenocarcinoma and provide evidence for clinical decisions. However, the imaging parameters and numerical values for predicting pathologic invasiveness are still controversial, which will be reviewed in this paper.
Objective To investigate the relationship between clinical features and lymph node metastasis in lung adenocarcinoma patients with T1 stage. Methods We retrospectively analyzed the clinical data of 253 T1-stage lung adenocarcinoma patients (92 males and 161 females at an average age of 59.45±9.36 years), who received lobectomy and systemic lymph node dissection in the Second Affiliated Hospital of Harbin Medical University from October 2013 to February 2016. Results Lymph node metastasis was negative in 182 patients (71.9%) and positive in 71 (28.1%). Poor differentiation (OR=6.988, P=0.001), moderate differentiation (OR=3.589, P=0.008), micropapillary type (OR=24.000, P<0.001), solid type (OR=5.080, P=0.048), pleural invasion (OR=2.347, P=0.024), age≤53.5 years (OR=2.594, P=0.020) were independent risk factors for lymph node metastasis. In addition, in the tumor with diameter≥1.55 cm (OR=0.615, P=0.183), although the cut-off value of 1.55 cm had no significant difference, it still suggested that tumor diameter was an important risk factor of lymph node metastasis. Conclusion In lung adenocarcinoma with T1 stage, the large tumor diameter, the low degree of differentiation, the high ratio of consolidation, and the micropapillary or solid pathological subtypes are more prone to have lymph node metastasis.
Objective To evaluate the correlation between cyclin B1 (CCNB1) gene expression and the prognosis of lung adenocarcinoma. Methods Oncomine, STRING, Human Protein Atlas, The Cancer Genome Atlas and other databases as well as Kaplan-Meier method, Cox regression, receiver operating characteristic (ROC) curve and Spearman correlation analysis were used to verify the effect of CCNB1 on patients with lung adenocarcinoma. Results CCNB1 was highly expressed in lung adenocarcinoma, and the high expression was correlated with T stage (P=0.001), N stage (P<0.001), pathological stage (P<0.001) and gender (P=0.008). Univariate Cox regression analysis showed that the expression of CCNB1, T stage, N stage, M stage and pathological stage were the factors affecting the overall survival rate of patients with lung adenocarcinoma (P<0.05); multivariate Cox regression analysis showed that the expression of CCNB1 and T stage were independent risk factors for overall survival of patients with lung adenocarcinoma (P<0.05). Kaplan-Meier analysis showed that high expression of CCNB1 was associated with shorter overall survival [hazard ratio (HR)=1.60, 95% confidence interval (CI) (1.20, 2.14), P=0.002], disease-specific survival [HR=1.68, 95%CI (1.16, 2.44), P=0.006] and progression-free interval [HR=1.42, 95%CI (1.09, 1.85), P=0.009]. The ROC curve showed that CCNB1 might be a potential diagnostic molecule for lung adenocarcinoma [area under the curve=0.980, 95%CI (0.967, 0.993)]. Spearman correlation analysis showed that CCNB1 expression was positively correlated with the infiltration of T helper cells 2 (rs=0.805, P<0.001) and T helper cells (rs=0.103, P=0.017), and negatively correlated with the infiltration of natural killer cells (rs=−0.195, P<0.001), macrophages (rs=−0.134, P=0.002), and T cells (rs=−0.092, P=0.033). Conclusion CCNB1 is highly expressed in lung adenocarcinoma compared with normal tissues, which is related to poor prognosis and may provide a potential therapeutic target for patients with lung adenocarcinoma.
ObjectiveTo analyze the expression and clinical significance of cyclin-dependent kinase 1 (CDK1) in lung adenocarcinoma by bioinformatics.MethodsBased on the gene expression data of lung adenocarcinoma patients in The Cancer Genome Atlas (TCGA), the differential expression of CDK1 in lung adenocarcinoma tissues and normal lung tissues was analyzed. The expression of CDK1 gene in lung adenocarcinoma was analyzed by UALCAN at different angles. Survival analysis of different levels of CDK1 gene expression in lung adenocarcinoma was performed using Kaplan-Meier Plotter. Correlation Cox analysis of CDK1 expression and overall survival was based on clinical data of lung adenocarcinoma in TCGA. Gene set enrichment analysis was performed on gene sequences related to CDK1 expression in clinical cases. The protein interaction network of CDK1 from Homo sapiens was obtained by STRING. CDK1-related gene proteins were obtained and analyzed by the web server Gene Expression Profiling Interactive Analysis (GEPIA).ResultsBased on the analysis of TCGA gene expression data, CDK1 expression in lung adenocarcinoma was higher than that in normal lung tissues. UALCAN analysis showed that high CDK1 expression may be associated with smoking. Survival analysis indicated that when CDK1 gene was highly expressed, patients with lung adenocarcinoma had a poor prognosis. Univariate and multivariate Cox regression analysis of CDK1 expression and overall survival showed that high CDK1 expression was an independent risk factor for survival of patients with lung adenocarcinoma. Gene set enrichment analysis revealed that high CDK1 expression was closely related to DNA replication, cell cycle, cancer pathway and p53 signaling pathway.ConclusionCDK1 may be a potential molecular marker for prognosis of lung adenocarcinoma. In addition, CDK1 regulation may play an important role in DNA replication, cell cycle, cancer pathway and p53 signaling pathway in lung adenocarcinoma.
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.
ObjectiveTo investigate the CT signs and clinicopathological features of peripheral cavitary lung adenocarcinoma with the largest diameter less than or equal to 3 cm.Methods From January 2015 to December 2017, the CT signs and clinicopathological fertures of 51 patients with ≤3 cm peripheral cavitary lung adenocarcinoma diagnosed by chest CT and surgical pathology were retrospectively analyzed. Furthermore, CT signs and clinicopathological features of thick-walled cavitary lung adenocarcinoma and thin-walled cavitary lung adenocarcinoma were compared. There were 29 males and 22 females at age of 62 (56, 67) years.ResultsThere were 27 thick-walled cavitary lung adenocarcinoma and 24 thin-walled cavitary lung adenocarcinoma. Thick-walled cavitary adenocarcinoma had greater SUVmax [6.5 (3.7, 9.7) vs. 2.2 (1.4, 3.8), P=0.019], larger cavity wall thickness (11.8±4.6 mm vs. 7.6±3.7 mm, P=0.001), larger tumor tissue size [2.1 (1.7, 2.8) cm vs. 1.6 (1.2, 2.0) cm, P=0.006], and more solid nodules (17 patients vs. 8 patients, P=0.035). Thin-walled cavitary adenocarcinoma had more smoking history (12 patients vs. 6 patients, P=0.038), larger cavity size [12.3 (9.2, 16.6) mm vs. 4.4 (2.8, 7.1) mm, P=0.000], and larger proportion of cavities [0.30 (0.19, 0.37) vs. 0.03 (0.01, 0.09), P=0.000]. On CT signs, there were more features of irregular inner wall (19 patients vs. 6 patients, P=0.000), intra-cystic separation (16 patients vs. 6 patients, P=0.001) and vessels through the cystic cavity (10 patients vs. 1 patient, P=0.001) in thin-walled caviraty lung adenocarcinoma.ConclusionPeripheral cavitary lung adenocarcinoma of ≤3 cm on chest CT has characteristic manifestations in clinical, imaging and pathology, and there is a statistical difference between thick-walled cavitary lung adenocarcinoma and thin-walled cavitary lung adenocarcinoma.