ObjectiveTo investigate the predictive value of thyroid transcription factor-1 (TTF-1) in the treatment of advanced lung adenocarcinoma with different chemotherapy regimens.MethodsA total of 126 patients with advanced lung cancer were divided into three groups according to the chemotherapy regimen, namely a pemetrexed+nedaplatin group (PEM+NDP group), a pemetrexed+cisplatin/carboplatin group (PEM+DDP/CBP group) and a third-generation (3G) chemotherapy+cisplatin/carboplatin group (3G agent+DDP/CBP group). The predictive value of TTF-1 in the above three treatment regimens was analyzed. The patients were followed up by telephone or outpatient visit until April 2017.ResultsThere were no significant differences in disease control rate or objective response rate between the three different chemotherapy regimens (all P>0.05). The survival rate of PEM+NDP group was significantly higher than that of PEM+DDP/CBP group and 3G agent+DDP/CBP group (9.68%vs. 5.56% and 6.80%, both P<0.05). ECOG score and brain metastasis were independent risk factors for the prognosis of chemotherapy regimens. TTF-1 was an independent risk factor for PEM+NDP therapy.ConclusionTTF-1 is an independent risk factor for PEM+NDP chemotherapy, but not for 3G agent + DDP/CBP or PEM+DDP/CBP regimens.
ObjectiveTo explore the mechanism by which the tumor suppressor gene Testin affects the proliferation, migration, and invasive biological activity of lung adenocarcinoma cell lines by regulating the RhoA pathway. MethodThe cbioportal tumor gene expression was used to screen for genes with high correlation with TES gene expression in lung adenocarcinoma, and the 200 genes with the highest correlation were selected for pathway enrichment analysis. Upload these 200 genes to the David gene annotation tool for GO_Biological Process pathway analysis, GO Molecular Function pathway analysis, KEGG pathway analysis, and Reactome pathway analysis. The lung adenocarcinoma cell line H1299 was cultured, and an overexpression Testin plasmid was constructed and transfected into H1299 cells. The mRNA and protein expression of RhoA, Rac1, and Cdc42 were detected using qRT PCR and western blot. On the basis of downregulating RhoA expression through overexpression of Testin, the overexpression plasmid of RhoA (TES+RhoA) was transfected simultaneously to induce a downregulation of RhoA expression, and the changes in malignant phenotype of lung adenocarcinoma cells were detected. The biological activity changes of adenocarcinoma cell lines after the above intervention were verified through CCK-8 experiment, Transwell experiment, and Matrigel experiment. Results The results of pathway analysis prediction showed that Testin may be involved in regulating the Rho GTPase signaling pathway. Overexpression of Testin did not affect the mRNA levels of RhoA, Rac1, and Cdc42 (all P>0.05), nor did it affect the protein expression levels of Rac1 and Cdc42 (all P>0.05), but it significantly reduced the protein level of RhoA (P<0.05). Knocking down RhoA in lung adenocarcinoma cell H1299 can significantly inhibit cell proliferation, migration, and invasion ability (all P<0.05). Simultaneously transfecting RhoA overexpression plasmid on the basis of overexpression of Testin can downregulate RhoA expression, but does not affect Testin expression. ConclusionsRhoA plays a pro-cancer role in lung adenocarcinoma, and Testin can inhibit RhoA expression. Overexpression of RhoA can rescue Testin's effect on lung adenocarcinoma cell proliferation, migration, and invasion. Testin exerts its anti-cancer biological activity by regulating RhoA.
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.
ObjectiveTo predict the probability of lymph node metastasis after thoracoscopic surgery in patients with lung adenocarcinoma based on nomogram. MethodsWe analyzed the clinical data of the patients with lung adenocarcinoma treated in the department of thoracic surgery of our hospital from June 2018 to May 2021. The patients were randomly divided into a training group and a validation group. The variables that may affect the lymph node metastasis of lung adenocarcinoma were screened out by univariate logistic regression, and then the clinical prediction model was constructed by multivariate logistic regression. The nomogram was used to show the model visually, the receiver operating characteristic (ROC) curve, calibration curve and clinical decision curve to evaluate the calibration degree and practicability of the model. ResultsFinally 249 patients were collected, including 117 males aged 53.15±13.95 years and 132 females aged 47.36±13.10 years. There were 180 patients in the training group, and 69 patients in the validation group. There was a significant correlation between the 6 clinicopathological characteristics and lymph node metastasis of lung adenocarcinoma in the univariate logistic regression. The area under the ROC curve in the training group was 0.863, suggesting the ability to distinguish lymph node metastasis, which was confirmed in the validation group (area under the ROC curve was 0.847). The nomogram and clinical decision curve also performed well in the follow-up analysis, which proved its potential clinical value. ConclusionThis study provides a nomogram combined with clinicopathological characteristics, which can be used to predict the risk of lymph node metastasis in patients with lung adenocarcinoma with a diameter≤3 cm.
Objective To externally validate a prediction model based on clinical and CT imaging features for the preoperative identification of high-grade patterns (HGP), such as micropapillary and solid subtypes, in early-stage lung adenocarcinoma, in order to guide clinical treatment decisions. Methods This study conducted an external validation of a previously developed prediction model using a cohort of patients with clinical stage ⅠA lung adenocarcinoma from the Fourth Hospital of Hebei Medical University. The model, which incorporated factors including tumor size, density, and lobulation, was assessed for its discrimination, calibration performance, and clinical impact. Results A total of 650 patients (293 males, 357 females; age range: 30-82 years) were included. The validation showed that the model demonstrated good performance in discriminating HGP (area under the curve>0.7). After recalibration, the model's calibration performance was improved. Decision curve analysis (DCA) indicated that at a threshold probability>0.6, the number of HGP patients predicted by the model closely approximated the actual number of cases. Conclusion This study confirms the effectiveness of a clinical and imaging feature-based prediction model for identifying HGP in stage ⅠA lung adenocarcinoma in a clinical setting. Successful application of this model may be significant for determining surgical strategies and improving patients' prognosis. Despite certain limitations, these findings provide new directions for future research.
This research is to explore the perfusion time-intensity curve parameters of a lung adenocarcinoma xenograft into nude mouse model with contrast enhanced ultrasonography (CEUS); and to investigate the angiogenesis features of tumor at different growth time. Twenty one lung adenocarcinoma xenografted nude mice were divided into three groups and inculcated with human lung adenocarcinoa. Time window for examining CEUS were respectively in 7-day, 14-day and 28-day. The perfusion parameters including rise time (RT), peak intensity (PI), area under the curve (AUC) of lung tumor were obtained on CEUS images by using off-line software Q lab. Immunohistochemically staining for CD34 was used to observe the microvessel density (MVD).The 7-day group had the highest AUC and PI; AUC and PI of 14-day and 28-day group decreased gradually (P < 0.05). RT was increased as tumor growth. In tumor with necrosis, AUC and PI of non-necrosis part were also larger than necrosis part (P < 0.05). Immunohistochemically staining for CD34 of all tumors reflected that the density of microvessels in necrosis tumor was significantly higher than those without necrosis (7.50±3.44 vs.12.44±5.74, P=0.034). Pearson correlation indicated that PI was positively related with MVD (r=0.668, P=0.008). Lung adenocarcinoma perfusion characteristic can be accessed from time-intensity curve parameters by using noninvasively and non-radiative contrast enhanced ultrasonography. Time-intensity curve parameters including AUC, PI and RT may reflect tumor angiogenesis.
[Abstract]The pathogenesis of lung adenocarcinoma (LUAD) is closely associated with the aberrant expression of long non-coding RNAs (lncRNAs), whose functions are precisely regulated by the important post-transcriptional modification N6-methyladenosine (m6A). Recent studies have revealed that m6A modification plays a critical role in malignant phenotypes of LUAD, including proliferation, invasion, metastasis, and drug resistance, by influencing the stability, processing, and function of lncRNAs. This review systematically summarizes recent advances in understanding the role of m6A-modified lncRNAs in LUAD, with a focus on the functional mechanisms of the m6A-lncRNA regulatory network in tumor progression. It also discusses their clinical potential as novel biomarkers and therapeutic targets, aiming to provide new theoretical insights for the precise diagnosis and treatment of LUAD.
Objective To analyze the effects of systematic lymph node dissection (SLND) and lobe-specific lymph node dissection (L-SND) on perioperative and long-term outcomes of patients with clinicalⅠA (cⅠA) stage lung adenocarcinoma. Methods A retrospective analysis was done on the patients with cⅠA stage lung adenocarcinoma who received thoracoscopic radical resection admitted to the Affiliated Hospital of Qingdao University from January 2013 to August 2016. Propensity score matching was conducted to eliminate the biases. The recurrence-free survival was compared between the two groups after matching. Perioperative parameters and postoperative complications were also analyzed. Results A total of 725 patients were enrolled, including 252 males and 473 females, with a median age of 62.0 (31.0-69.0) years. There were 228 patients in the L-SND group and 497 patients in the SLND group. After matching, there were 211 patients in each group and no statistical difference in the incidence of postoperative complications (10.9% vs. 13.7%, P=0.374), identification of metastatic positive lymph nodes (12.3% vs. 9.0%, P=0.270), or recurrence-free survival (P=0.492) were found between two groups, whereas the operation time (163.9±39.4 min vs. 135.4±32.4 min, P＜0.001), intraoperative blood loss [100.0 (20.0-800.0) mL vs. 100.0 (10.0-400.0) mL, P＜0.001], intubation time [4.0 (1.0-18.0) d vs. 4.0 (1.0-9.0) d, P＜0.001] and hospital stay (12.3±3.3 d vs. 10.8±2.4 d, P=0.003) in the SLND group were found to be significantly higher or longer than those in the L-SND group. Conclusion L-SND has a similar efficiency to SLND in terms of postoperative complications, pathological lymph node metastasis, and recurrence-free survival, as well as significant advantages in reducing intraoperative blood loss, and shortening operation time, intubation time and length of hospital stay. Therefore, L-SND can be recommended to replace SLND as a method for lymph node resection in patients with cⅠA stage lung adenocarcinoma.
Objective To determine the prognostic biomarkers and new therapeutic targets of the lung adenocarcinoma (LUAD), based on which to establish a prediction model for the survival of LUAD patients. Methods An integrative analysis was conducted on gene expression and clinicopathologic data of LUAD, which were obtained from the UCSC database. Subsequently, various methods, including screening of differentially expressed genes (DEGs), Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene Set Enrichment Analysis (GSEA), were employed to analyze the data. Cox regression and least absolute shrinkage and selection operator (LASSO) regression were used to establish an assessment model. Based on this model, we constructed a nomogram to predict the probable survival of LUAD patients at different time points (1-year, 2-year, 3-year, 5-year, and 10-year). Finally, we evaluated the predictive ability of our model using Kaplan-Meier survival curves, receiver operating characteristic (ROC) curves, and time-dependent ROC curves. The validation group further verified the prognostic value of the model. Results The different-grade pathological subtypes' DEGs were mainly enriched in biological processes such as metabolism of xenobiotics by cytochrome P450, natural killer cell-mediated cytotoxicity, antigen processing and presentation, and regulation of enzyme activity, which were closely related to tumor development. Through Cox regression and LASSO regression, we constructed a reliable prediction model consisting of a five-gene panel (MELTF, MAGEA1, FGF19, DKK4, C14ORF105). The model demonstrated excellent specificity and sensitivity in ROC curves, with an area under the curve (AUC) of 0.675. The time-dependent ROC analysis revealed AUC values of 0.893, 0.713, and 0.632 for 1-year, 3-year, and 5-year survival, respectively. The advantage of the model was also verified in the validation group. Additionally, we developed a nomogram that accurately predicted survival, as demonstrated by calibration curves and C-index. Conclusion We have developed a prognostic prediction model for LUAD consisting of five genes. This novel approach offers clinical practitioners a personalized tool for making informed decisions regarding the prognosis of their patients.
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.