Objective To investigate the molecular mechanisms by which the long non-coding RNA (lncRNA) MIR223HG affects the proliferation, migration and apoptosis of lung adenocarcinoma cells. MethodsDNA damaging agent Zeocin was used to treat human embryo lung cell (MRC-5) and lung cancer cell (A549 and H1299), and the expression of MIR223HG was tested by quantitative real-time polymerase chain reaction (qRT-PCR) analysis. Moreover, the ataxia-telangiectasia mutated (ATM) protein and ATM pathway downstream factor Cell cycle checkpoint kinase 2 (Chk2), p53 tumor suppressor protein (p53) in the lung cancer cell (A549 and H1299) with Zeocin were also tested by qRT-PCR. Cell transfection and Transwell migration assay, colony formation assays, apoptosis assays were performed to verify the role of ATM in the expression of MIR223HG in lung adenocarcinoma. ResultsThe expression of MIR223HG was reduced markedly in the lung cancer cells (A549 and H1299) compared with human embryo lung cell (MRC-5) after treated with Zeocin. ATM protein and its downstream factors Chk2, p53 involved in the process, and ATM regulated the expression of MIR223HG in the lung cancer cells with Zeocin. Futhermore, ATM joined in the processes that MIR223HG regulated the lung cancer cells proliferation, migration and apoptosis. Conclusions The expression of MIR223HG is related to the DNA damage response in the lung cancer, and MIR223HG regulates lung cancer cells proliferation, migration and apoptosis by ATM/Chk2/p53 pathway. MIR223HG may be a potential therapeutic target for lung adenocarcinoma treatment.
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.
Objective To explore the molecular mechanism of LINC00626 regulating malignant progression of lung adenocarcinoma metastasis through JAK1/STAT3/KHSRP axis. Methods Quantitative real-time polymerase chain polymerase chain reaction was used to detect the expression of LINC00626 and KHSRP mRNA in human non-small-cell lung carcinoma cell lines (A549, H1299, H1975, H1437), human normal bronchial epithelial cell line (16HBE) and 144 lung adenocarcinoma tissues. The knockdown LINC00626 lentivirus and the control lentivirus were transferred into H1299 and H1437 cells, and named as sh-LINC00626 group (silencing of LINC00626 by transfecting short hairpin RNA lentiviral vector and sh-NC Group negative control by transfecting short hairpin RNA lentiviral). The overexpressed LINC00626 lentivirus and the control lentivirus were transferred into A549 and H1975 cells and named as LINC00626 group and Vector group. KHSRP vector on the basis of silencing LINC00626 and blank vector on the basis of silencing LINC00626 were added in H1437 cells. Cell counting kit-8 assay and Transwell migration/invasion assay were used to detect cell proliferation, migration and invasion. The expression levels of JAK/STAT and KHSRP in stably transfected cells were detected by Western blot. The effect of LINC00626 in vivo was studied in nude mice. Nuclear-cytoplasmic separation and RNA fluorescence in situ hybridization assay are used to predict the subcellular localization of LINC00626 and KHSRP. RNA pull down and mass spectrometry analysis were used to identify LINC00626 binding proteins. Results The expression levels of LINC00626 and KHSRP in non-small-cell lung carcinoma cell lines were significantly higher than those in normal human bronchial epithelial cells. LINC00626 and KHSRP were highly expressed in lung adenocarcinoma. Compared with the control group, the cell proliferation rate, colony formation, cell migration and invasion of H1437 cells were significantly decreased in knockdown group, while the reverse was true for over-expression. LINC00626 and KHSRP were located in the nucleus. LINC00626 directly binded to the KHSRP protein. Compared with the control group, H1437 cells transfected with knockdown LINC00626 and KHSRP significantly increased cell proliferation rate, cell migration, number of invasions. Compared with the control group, knockdown group showed a significant decrease in tumor volume and weight, cell proliferation rate and proliferation index, and the number of lung metastases. While the overexpression group showed an opposite effect, there were significant differences among the groups (P<0.01). The expression of JAK1 and STAT3 mRNA and protein in sh-LINC00626 group was lower than that in sh-NC Group (P<0.05), and the expression of JAK1 and STAT3 mRNA and protein in sh-LINC00626 group was higher than that in Vector group (P<0.05). Conclusion LINC00626 promotes malignant progression of lung adenocarcinoma metastasis through JAK1/STAT3/KHSRP signaling axis.
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 clinical and pathological characteristics, prognosis and treatment strategies of adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA). Methods We retrospectively analyzed the clinical data of 489 patients with AIS and MIA in our hospital from January 2007 to August 2015. There were 122 males and 367 females with an average age of 26–78 (51±9) years. According to the pathological types, they were divided into the AIS group (246 patients) and the MIA group (243 patients). In the AIS group, there were 60 males and 186 females with an average age of 50±7 years. In the MIA group, there were 62 males and 181 females with an average age of 54±5 years. The clinicopathological features, surgical methods and prognosis of the two groups were compared. Results There were significant differences in age, value of carcino-embryonic antigen (CEA), nodule shape and nodule size between the AIS and MIA groups (P<0.05). AIS patients were mostly under the age of 60 years with the value of CEA in the normal range which often appeared as pure ground-glass opacity lung nodules <1 cm in diameter on the CT scan. MIA often appeared as mixed ground-glass nodules <1.5 cm in diameter, accompanied by bronchiectasis and pleural indentation. The 5-year disease-free survival rate of the AIS and MIA groups reached 100%, and there was no statistical difference in the prognosis between the two groups after subtotal lobectomy (pulmonary resection and wedge resection) and lobectomy, systematic lymph node dissection and mediastinal lymph node sampling. Conclusion The analysis of preoperative clinical and imaging features can predict the AIS and MIA and provide individualized surgery and postoperative treatment program.
ObjectiveTo explore the accuracy of machine learning algorithms based on SHOX2 and RASSF1A methylation levels in predicting early-stage lung adenocarcinoma pathological types. MethodsA retrospective analysis was conducted on formalin-fixed paraffin-embedded (FFPE) specimens from patients who underwent lung tumor resection surgery at Affiliated Hospital of Nantong University from January 2021 to January 2023. Based on the pathological classification of the tumors, patients were divided into three groups: a benign tumor/adenocarcinoma in situ (BT/AIS) group, a minimally invasive adenocarcinoma (MIA) group, and an invasive adenocarcinoma (IA) group. The methylation levels of SHOX2 and RASSF1A in FFPE specimens were measured using the LungMe kit through methylation-specific PCR (MS-PCR). Using the methylation levels of SHOX2 and RASSF1A as predictive variables, various machine learning algorithms (including logistic regression, XGBoost, random forest, and naive Bayes) were employed to predict different lung adenocarcinoma pathological types. ResultsA total of 272 patients were included. The average ages of patients in the BT/AIS, MIA, and IA groups were 57.97, 61.31, and 63.84 years, respectively. The proportions of female patients were 55.38%, 61.11%, and 61.36%, respectively. In the early-stage lung adenocarcinoma prediction model established based on SHOX2 and RASSF1A methylation levels, the random forest and XGBoost models performed well in predicting each pathological type. The C-statistics of the random forest model for the BT/AIS, MIA, and IA groups were 0.71, 0.72, and 0.78, respectively. The C-statistics of the XGBoost model for the BT/AIS, MIA, and IA groups were 0.70, 0.75, and 0.77, respectively. The naive Bayes model only showed robust performance in the IA group, with a C-statistic of 0.73, indicating some predictive ability. The logistic regression model performed the worst among all groups, showing no predictive ability for any group. Through decision curve analysis, the random forest model demonstrated higher net benefit in predicting BT/AIS and MIA pathological types, indicating its potential value in clinical application. ConclusionMachine learning algorithms based on SHOX2 and RASSF1A methylation levels have high accuracy in predicting early-stage lung adenocarcinoma pathological types.
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.
Objective To investigate the expression of SAPCD2 in the lung adenocarcinoma cells, and to study the effect of SAPCD2 regulating Hippo signaling pathway on the proliferation, invasion, migration and apoptosis of the lung adenocarcinoma cells and its mechanism. Methods Quantitative real-time PCR (qRT-PCR) and Western blot were used to detect the expression levels of SAPCD2 mRNA and protein in four types of lung cancer cells (HCC827, H1650, SK-MES-1, A549) and human normal lung epithelial cells (BESA-2B), respectively. Then, lung cancer cells with relatively high levels of SAPCD2 expression were selected for subsequent experiments. The experiment cells were divided into a normal control group (NC group), a si-SAPCD2 group, and a pathway inhibitor group (si-SAPCD2+XMU-MP-1 group). Firstly, SAPCD2 mRNA was silenced using small interfering RNA (siRNA) technology, and then qRT-PCR was used to detect the expression of SAPCD2 in transfected lung cancer cells; using clone plate assay to detect the proliferation of lung cancer cells after silencing; using flow cytometry to detect the apoptosis of lung cancer cells after silencing; observe the number of lung cancer cells at different stages through cell cycle experiments; then Transwell experiment was used to analyze the effect of silencing SAPCD2 on the migration and invasion of lung cancer cell migration. Finally, Western blot was used to detect the expression of ki-67, Bcl-2, Caspase-3, NF2, P-MST1, P-LATS1, P-YAP, YAP, and TAZ proteins.Results SAPCD2 had the highest expression level in lung adenocarcinoma A549 cells (P<0.01). Silencing SAPCD2 significantly decreased the proliferation ability of A549 cells (P<0.01), inhibited their migration (P<0.05) and invasion (P<0.01), and promoted A549 cell apoptosis (P<0.01); more than half of the cells remained in the G0/G1 phase. Compared with the NC group, A549 cells showed a significant increase in G0/G1 phase cells (P<0.01), a significant decrease in G2/M and S phase cells (P<0.01), and a significant increase in the proportion of early apoptotic cells (P<0.01). Western blot results showed that silencing SAPCD2 down-regulated the expression of ki-67, Bcl-2, YAP, and TAZ proteins compared to the NC group (P<0.01), and up-regulated the expression of Caspase-3, NF2, P-MST1, P-LATS1, and P-YAP proteins (P<0.01). Conclusions The expression of SAPCD2 in lung adenocarcinoma A549 cells is significantly higher than that in normal lung epithelial cells (BESA-2B), which promotes the proliferation, migration and invasion of A549 cells and inhibits apoptosis. The mechanism may be related to the inhibition of Hippo signaling pathway.
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.