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.
ObjectiveTo evaluate the application value of three-dimensional (3D) reconstruction in preoperative surgical diagnosis of new classification criteria for lung adenocarcinoma, which is helpful to develop a deep learning model of artificial intelligence in the auxiliary diagnosis and treatment of lung cancer.MethodsThe clinical data of 173 patients with ground-glass lung nodules with a diameter of ≤2 cm, who were admitted from October 2018 to June 2020 in our hospital were retrospectively analyzed. Among them, 55 were males and 118 were females with a median age of 61 (28-82) years. Pulmonary nodules in different parts of the same patient were treated as independent events, and a total of 181 subjects were included. According to the new classification criteria of pathological types, they were divided into pre-invasive lesions (atypical adenomatous hyperplasia and and adenocarcinoma in situ), minimally invasive adenocarcinoma and invasive adenocarcinoma. The relationship between 3D reconstruction parameters and different pathological subtypes of lung adenocarcinoma, and their diagnostic values were analyzed by multiplanar reconstruction and volume reconstruction techniques.ResultsIn different pathological types of lung adenocarcinoma, the diameter of lung nodules (P<0.001), average CT value (P<0.001), consolidation/tumor ratio (CTR, P<0.001), type of nodules (P<0.001), nodular morphology (P<0.001), pleural indenlation sign (P<0.001), air bronchogram sign (P=0.010), vascular access inside the nodule (P=0.005), TNM staging (P<0.001) were significantly different, while nodule growth sites were not (P=0.054). At the same time, it was also found that with the increased invasiveness of different pathological subtypes of lung adenocarcinoma, the proportion of dominant signs of each group gradually increased. Meanwhile, nodule diameter and the average CT value or CTR were independent risk factors for malignant degree of lung adenocarcinoma.ConclusionImaging signs of lung adenocarcinoma in 3D reconstruction, including nodule diameter, the average CT value, CTR, shape, type, vascular access conditions, air bronchogram sign, pleural indenlation sign, play an important role in the diagnosis of lung adenocarcinoma subtype and can provide guidance for personalized therapy to patients in clinics.
Objective The management of pulmonary nodules is a common clinical problem, and this study constructed a nomogram model based on FUT7 methylation combined with CT imaging features to predict the risk of adenocarcinoma in patients with pulmonary nodules. Methods The clinical data of 219 patients with pulmonary nodules diagnosed by histopathology at the First Affiliated Hospital of Zhengzhou University from 2021 to 2022 were retrospectively analyzed. The FUT7 methylation level in peripheral blood were detected, and the patients were randomly divided into training set (n=154) and validation set (n=65) according to proportion of 7:3. They were divided into a lung adenocarcinoma group and a benign nodule group according to pathological results. Single-factor analysis and multi-factor logistic regression analysis were used to construct a prediction model in the training set and verified in the validation set. The receiver operating characteristic (ROC) curve was used to evaluate the discrimination of the model, the calibration curve was used to evaluate the consistency of the model, and the clinical decision curve analysis (DCA) was used to evaluate the clinical application value of the model. The applicability of the model was further evaluated in the subgroup of high-risk CT signs (located in the upper lobe, vascular sign, and pleural sign). Results Multivariate logistic regression analysis showed that female, age, FUT7_CpG_4, FUT7_CpG_6, sub-solid nodules, lobular sign and burr sign were independent risk factors for lung adenocarcinoma (P<0.05). A column-line graph prediction model was constructed based on the results of the multifactorial analysis, and the area under the ROC curve was 0.925 (95%CI 0.877 - 0.972 ), and the maximum approximate entry index corresponded to a critical value of 0.562, at which time the sensitivity was 89.25%, the specificity was 86.89%, the positive predictive value was 91.21%, and the negative predictive value was 84.13%. The calibration plot predicted the risk of adenocarcinoma of pulmonary nodules was highly consistent with the risk of actual occurrence. The DCA curve showed a good clinical net benefit value when the threshold probability of the model was 0.02 - 0.80, which showed a good clinical net benefit value. In the upper lobe, vascular sign and pleural sign groups, the area under the ROC curve was 0.903 (95%CI 0.847 - 0.959), 0.897 (95%CI 0.848 - 0.945), and 0.894 (95%CI 0.831 - 0.956). Conclusions This study developed a nomogram model to predict the risk of lung adenocarcinoma in patients with pulmonary nodules. The nomogram has high predictive performance and clinical application value, and can provide a theoretical basis for the diagnosis and subsequent clinical management of pulmonary nodules.
ObjectiveTo assess the specific clinicopathological characteristics as well as prognostic value of prognostic significance of spread through air spaces (STAS) in lung adenocarcinoma.MethodsWe systematically searched the databases of PubMed, EMbase and Web of Science databases from their date of inception to March 2019. The quality of the included literature was assessed by the Newcastle-Ottawa scale (NOS). The NOS of the study higher than 6 points was considered as high quality. Software of Stata 12.0 was used for meta-analysis.ResultsTwenty retrospective cohort studies involved with totally 6 225 patients were included. Quality of included studies was high with NOS score equal or higher than 6 points. STAS was associated with male sex, ever smoking history, abnormal carcino-embryonic antigen (CEA) level, air bronchogram negative, anaplasticlymphoma kinase (ALK) arrangement positive, epidermal growth factor receptor (EGFR) mutation positive, advanced pathological tumor stage and more invasive pathological adenocarcinoma subtypes. The presence of STAS indicated significantly poor recurrence free survival (RFS) (HR=1.960, 95%CI 1.718-2.237, P<0.001) as well as poor overall survival (OS) (HR=1.891, 95%CI 1.389-2.574, P<0.001). Further subgroup analyses showed that exhibiting tumor size including diameter less than 2 cm (HR=2.344, 95%CI 1.703-3.225, P<0.001) and diameter over 2 cm (HR=2.571, 95%CI 1.559-4.238, P<0.001), resection type including lobectomy (HR=1.636, 95%CI 1.258-2.127, P<0.001) and sublobar resection (HR=3.549, 95%CI 2.092-6.021, P<0.001) in stageⅠ adenocarcinoma suggested that STAS had a bad effect on RFS.ConclusionPresence of STAS is associated with more aggressive clinicopathological features and independently associated with worse RFS and OS in lung adenocarcinoma. STAS positive has a negative effect on RFS whatever the tumor size (including the diameter<2 cm or >2 cm) and resection types in stageⅠ 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.
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.
Objective To investigate the effects of growth differentiation factor 15 (GDF15) on lung adenocarcinoma bone metastasis in nude mice by regulating phosphatase and tensin homology/phosphatidylinositol 3 kinase/protein kinase B (PTEN/PI3K/AKT) signaling pathway. Methods The bone metastasis model of lung adenocarcinoma in nude mice was established and mice were randomly divided into Control group, sh-NC group, sh-GDF15 group, sh-GDF15+sh-NC group and sh-GDF15+sh-PTEN group. The changes of 50% pain withdrawl threshold (PWT) and thermal withdrawal latency (TWL) were observed. bone destruction was analyzed by Micro-CT. Bone morphology was observed by HE staining. The expression of osteoclast-related factors was detected by immunohistochemistry. The expression of PTEN/PI3K/AKT signaling pathway was detected by Western blot. Results The tibia tissue of nude mice in Control group and sh-NC group was destroyed, the continuity of bone cortex was interrupted, obvious bone tumor lesions were observed, the tumor cells were irregular in shape, densely distributed and disordered, and the nuclei were obviously deformed. Compared with sh-NC group, sh-GDF15 group had less tibial tissue destruction, the bone tumor cell density was significantly reduced, the pathological morphology was significantly improved, and 50% PWT, TWL, bone mineral density (BMD), trabecular bone volume/total volume (BV/TV), trabecular number (Tb.N), trabecular thickness (Tb.Th) and PTEN expression were increased, the expressions of trabecular separation (Tb.Sp), cathepsin K (CTSK), matrix metalloproteinase 9 (MMP-9), p-PI3K PI3K and p-Akt/Akt were decreased (P<0.05). Compared with sh-GDF15+sh-NC group, sh-GDF15+sh-PTEN group had severe tibial tissue damage, the bone tissue tumor cells were dense and the pathological injury was aggravated, and 50%PWT, TWL, BMD, BV/TV, Tb.N, Tb.Th and PTEN expression were decreased, the expressions of Tb.Sp, CTSK, MMP-9, p-PI3K /PI3K and p-Akt /Akt were increased (P<0.05). Conclusion GDF15 can promote bone metastasis of lung adenocarcinoma in nude mice, and its mechanism is related to inhibition of PTEN/PI3K/AKT 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.
Lung adenocarcinoma has become the most common type of lung cancer. According to the 2015 World Health Organization histological classification of lung cancer, invasive lung adenocarcinoma can be divided into 5 subtypes: lepidic, acinar, papillary, solid, and micropapillary. Relevant studies have shown that the local lobectomy or sublobectomy is sufficient for early lepidic predominant adenocarcinoma, while lobectomy should be recommended for tumors containing micropapillary and solid ingredients (≥5%). Currently, the percentage of micropapillary and solid components diagnosed by frozen pathological examination is 65.7%, and the accuracy of diagnosis is limited. Therefore, to improve the accuracy of diagnosis, it is necessary to seek new methods and techniques. This paper summarized the characteristics and rapid diagnosis tools of early lung adenocarcinoma subtypes.