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 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.
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 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.
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.
ObjectiveTo investigate the radiomics features to distinguish invasive lung adenocarcinoma with micropapillary or solid structure. MethodsA retrospective analysis was conducted on patients who received surgeries and pathologically confirmed invasive lung adenocarcinoma in our hospital from April 2016 to August 2019. The dataset was randomly divided into a training set [including a micropapillary/solid structure positive group (positive group) and a micropapillary/solid structure negative group (negative group)] and a testing set (including a positive group and a negative group) with a ratio of 7∶3. Two radiologists drew regions of interest on preoperative high-resolution CT images to extract radiomics features. Before analysis, the intraclass correlation coefficient was used to determine the stable features, and the training set data were balanced using synthetic minority oversampling technique. After mean normalization processing, further radiomics features selection was conducted using the least absolute shrinkage and selection operator algorithm, and a 5-fold cross validation was performed. Receiver operating characteristic (ROC) curves were depicted on the training and testing sets to evaluate the diagnostic performance of the radiomics model. ResultsA total of 340 patients were enrolled, including 178 males and 162 females with an average age of 60.31±6.69 years. There were 238 patients in the training set, including 120 patients in the positive group and 118 patients in the negative group. There were 102 patients in the testing set, including 52 patients in the positive group and 50 patients in the negative group. The radiomics model contained 107 features, with the final 2 features selected for the radiomics model, that is, Original_ glszm_ SizeZoneNonUniformityNormalized and Original_ shape_ SurfaceVolumeRatio. The areas under the ROC curve of the training and the testing sets of the radiomics model were 0.863 (95%CI 0.815-0.912) and 0.857 (95%CI 0.783-0.932), respectively. The sensitivity was 91.7% and 73.7%, the specificity was 78.8% and 84.0%, and the accuracy was 85.3% and 78.4%, respectively. ConclusionThere are differences in radiomics features between invasive pulmonary adenocarcinoma with or without micropapillary and solid structures, and the radiomics model is demonstrated to be with good diagnostic value.
Objective To evaluate the effect of regiono-perfusional chemotherapy of pancreatic adenocarcinoma, and to seek the management of its complications. MethodsThirty-six patients with unresectable pancreatic adenocarcinoma received selectively intra-arterial catheterization and perfused with 5-Fu, ADM, DDP. Results Six patients had complete response, 15 partial response, and one underwent radical resection subsequently. Cmplications occurred in 14 patients with 2 patients died of complications.Conclusion Regiono-perfusional chemotherapy of pancreatic adenocarcinoma is effective, but the complications can not be neglected.
Objective To explore the correlation between the quantitative and qualitative features of CT images and the invasiveness of pulmonary ground-glass nodules, providing reference value for preoperative planning of patients with ground-glass nodules. MethodsThe patients with ground-glass nodules who underwent surgical treatment and were diagnosed with pulmonary adenocarcinoma from September 2020 to July 2022 at the Third Affiliated Hospital of Kunming Medical University were collected. Based on the pathological diagnosis results, they were divided into two groups: a non-invasive adenocarcinoma group with in situ and minimally invasive adenocarcinoma, and an invasive adenocarcinoma group. Imaging features were collected, and a univariate logistic regression analysis was conducted on the clinical and imaging data of the patients. Variables with statistical difference were selected for multivariate logistic regression analysis to establish a predictive model of invasive adenocarcinoma based on independent risk factors. Finally, the sensitivity and specificity were calculated based on the Youden index. Results A total of 555 patients were collected. The were 310 patients in the non-invasive adenocarcinoma group, including 235 females and 75 males, with a meadian age of 49 (43, 58) years, and 245 patients in the invasive adenocarcinoma group, including 163 females and 82 males, with a meadian age of 53 (46, 61) years. The binary logistic regression analysis showed that the maximum diameter (OR=4.707, 95%CI 2.060 to 10.758), consolidation/tumor ratio (CTR, OR=1.027, 95%CI 1.011 to 1.043), maximum CT value (OR=1.025, 95%CI 1.004 to 1.047), mean CT value (OR=1.035, 95%CI 1.008 to 1.063), spiculation sign (OR=2.055, 95%CI 1.148 to 3.679), and vascular convergence sign (OR=2.508, 95%CI 1.345 to 4.676) were independent risk factors for the occurrence of invasive adenocarcinoma (P<0.05). Based on the independent predictive factors, a predictive model of invasive adenocarcinoma was constructed. The formula for the model prediction was: Logit(P)=–1.293+1.549×maximum diameter of lesion+0.026×CTR+0.025×maximum CT value+0.034×mean CT value+0.72×spiculation sign+0.919×vascular convergence sign. The area under the receiver operating characteristic curve of the model was 0.910 (95%CI 0.885 to 0.934), indicating that the model had good discrimination ability. The calibration curve showed that the predictive model had good calibration, and the decision analysis curve showed that the model had good clinical utility. Conclusion The predictive model combining quantitative and qualitative features of CT has a good predictive ability for the invasiveness of ground-glass nodules. Its predictive performance is higher than any single indicator.
ObjectivesTo investigate the diagnostic value of different diffusion-weighted MRI (DWI) models between two Gaussian DWI models including mono-exponential and bi-exponential, and the non-Gaussian kurtosis model in poorly differentiated pancreatic ductal adenocarcinoma.MethodsSubjects comprised 52 patients with poorly differentiated pancreatic ductal adenocarcinoma which had been confirmed by surgery. All patients underwent DWI (1.5T, multi-b values: 0, 50, 100, 150, 200, 500, 800, 1000, 1 500, 2 000s/mm2). Mean values of DWI-derived metrics ADCstandard, ADCslow, ADCfast, f, MD, MK and ADCstandard were calculated from regions of interest in all tumours and non-tumorous parenchyma and compared. ANOVA and Mann Whitney U test was used to compare the MRI paremeters. ROC was used to evaluate the diagnostic efficiency.ResultsMean ADCstandard, ADCfast, f and MK values showed significant differences between tumours and non-tumorous parenchyma (P<0.05). AUC for ADCstandard, MD, ADCfast and f were 0.705, 0.665, 0.648, 0.614, respectively. The ROC curve integrated with ADCstandard and MD had better diagnostic efficiency (AUC was about 0.754).ConclusionsADCstandard, ADCfast, f and MK values can differentiate tumours from non-tumorous parenchyma. The combination of Gaussion distribution model and non-Gaussion distribution model has the potential to increase the diagnostic accuracy of DWI in patients with pancreatic ductal adenocarcinoma.
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.