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.
ObjectiveA competing endogenous RNA (ceRNA) regulatory network associated with long non-coding RNA (lncRNA) specific for lung adenocarcinoma (LUAD) was constructed based on bioinformatics methods, and the functional mechanism of actinfilament-associated protein 1-antisense RNA1 (AFAP1-AS1) in LUAD was analyzed, in order to provide a new direction for the study of LUAD therapeutic targets. MethodsThe gene chip of LUAD was downloaded from the Gene Expression Omnibus (GEO), and lncRNA and mRNA with differential expression between LUAD and normal tissues were screened using GEO2R online software, and their target genes were predicted by online databases to construct ceRNA networks and perform enrichment analysis. In cell experiments, AFAP1-AS1 was genetically knocked down and siRNA was constructed and transfected into LUAD cells A549 by cell transfection. CCK8, transwell, scratch assay and flow cytometry were used to detect the ability of cells to proliferate, invade, migrate and apoptosis. ResultsA total of 6 differentially expressed lncRNA and 494 differentially expressed mRNA were identified in the microarray of LUAD. The ceRNA network involved a total of 6 lncRNA, 22 miRNA, and 55 mRNA. Enrichment analysis revealed that mRNA was associated with cancer-related pathways. In cell assays, knockdown of AFAP1-AS1 inhibited cell proliferation, invasion, and migration, and AFAP1-AS1 promoted apoptosis. ConclusionIn this study, we construct a lncRNA-mediated ceRNA network, which may help to further investigate the mechanism of action of LUAD. In addition, through cellular experiments, AFAP1-AS1 is found to have potential as a therapeutic target for LUAD.
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 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.
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.
Lung ground glass opacity (GGO), which is associated with the pathology of the lung adenocarcinoma, is drawing more and more attention with the increased detection rate. However, it is still in the research stage for the imaging interpretation of GGO lesions. In this paper, we reviewed and analyzed the new classification of lung adenocarcinoma corresponding to the interpretation of GGO imaging feature, which emphasizes on how to determine the GGO lesions comprehensively and quantitative determination of the invasive extent of GGO.
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.
With the development of technology, the detection rate of ground-glass opacity (GGO) is rapidly increasing. GGO comprises of pure GGO and mixed GGO. Many researches have studied the characteristics of GGO, and they found that different malignant probability of GGO was associated with different image characteristics. It is obvious that there is a close relationship between the image characteristics of GGO and its prognosis. However, due to the various image characteristics of GGO, it is essential to assess the prognosis of lung adenocarcinoma patients in a more comprehensive way. In this review, we summarize the correlation between the main GGO image features (solid proportion, size, mean CT value, shape characteristics) and the prognosis of lung adenocarcinoma patients, to provide clinical reference for prognosis prediction and decision-making for patients with lung adenocarcinoma.
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.
