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.
ObjectiveTo analyze the expression of cold-induced RNA-binding protein (CIRBP) in lung adenocarcinoma and its clinical significance based on bioinformatics, in order to provide a new direction for the study of therapeutic targets for lung adenocarcinoma.MethodsThe CIRBP gene expression data and patient clinical information data in lung adenocarcinoma tissues and adjacent tissues were downloaded from The Cancer Genome Atlas and Gene Expression Omnibus databases. The expression of CIRBP in lung adenocarcinoma was analyzed. Furthermore, its relationship with clinicopathological features and prognosis in patients with lung adenocarcinoma was analyzed. GO and KEGG enrichment analysis were carried out for the screened genes. The CIRBP protein interaction network was constructed by STRING, and the correlation analysis was carried out using the GEPIA online website.ResultsThe expression level of CIRBP gene in lung adenocarcinoma tissues was significantly lower than that in adjacent tissues (P<0.01), and its expression level was correlated with T stage and N stage in clinicopathological features. The prognosis of patients with high CIRBP expression in lung adenocarcinoma was significantly better than that with low CIRBP expression. Univariate and multivariate Cox regression analysis showed that CIRBP was an independent prognostic factor in patients with lung adenocarcinoma. GO functional annotation showed its enrichment in organelle fission, nuclear fission, chromosome separation, and DNA replication, etc. KEGG analysis showed that it was mainly involved in cell cycle and DNA replication. Protein interaction network and GEPIA online analysis showed that the expression level of CIRBP was negatively correlated with the expression level of cyclin B2.ConclusionCIRBP gene is down-regulated in lung adenocarcinoma tissues, and its expression level is closely related to patient prognosis. CIRBP gene may be a potential therapeutic target and prognostic marker for lung adenocarcinoma.
[Abstract]With the widespread adoption of lung cancer screening, an increasing number of patients are being diagnosed with early-stage lung adenocarcinoma. For stage ⅠA lung adenocarcinoma, sublobar resection is the primary treatment approach. However, in patients with concomitant spread through air spaces (STAS), numerous studies advocate for lobectomy as the mainstay of treatment. Due to the limitations in preoperative prediction and intraoperative frozen section evaluation for assessing STAS, current research is largely restricted to using clinical and imaging features to predict STAS occurrence, with results that are inconsistent and unsatisfactory. Furthermore, most studies focus on individual clinical or imaging characteristics, and there is a lack of large-sample investigations. The rise of artificial intelligence in recent years has provided new insights into solving this problem, and existing studies have shown that artificial intelligence demonstrates better performance in STAS prediction compared to conventional methods. This article reviews the value of artificial intelligence in predicting STAS.
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 observe the effect of lncRNA-metastasis-associated lung adenocarcinoma transcript 1(MALAT1)on colorectal cancer cells-induced angiogenesis, and explore the potential underlying mechanism. MethodsMALAT1 was overexpressed in colorectal cancer cells SW48 by plasmids transfection, then SW48 cells were cultured at normoxia or hypoxia conditions. The culture media was collected, and the concentration of vascular endothelial growth factor (VEGF) in the media was measured by the enzyme-linked immuno sorbent assay (ELISA), and the human umbilical vein endothelial cells (HUVEC) were incubated with the media collected above. Meanwhile, the expression of hypoxia-inducible factor-1α(HIF-1α) in SW48 cells was detected by western blot. ResultsOverexpression of MALAT1 increased the VEGF level in the culture media, normoxia:the MALAT1 group (514±32) mg/L vs. the control group (110±14) mg/L, P < 0.05; hypoxia:the MALAT1 group (928±18) mg/L vs. the control group (230±21) mg/L, P < 0.05. Meanwhile, the tube formation activity of HUVEC was enhanced, and the expression of HIF-1αwas elevated in the MALAT1 group by western blot. ConclusionOverexpression of MALAT1 could promote colorectal cancer cells-mediated angiogenesis, it may be developed as a new drug target for colorectal cancer treatment.
Objective To investigate the effect of microRNA-27a (miR-27a) on the apoptosis of human lung adenocarcinoma cells A549 induced by lipopolysaccharide (LPS) by regulating the phosphatidylinositol-3-kinase (PI3K)/protein kinase B (AKT) pathway, and its mechanism is discussed preliminarily. Methods The complementary binding sites of miR-27a and phosphatidylinositol-3 kinase catalytic subunit delta (PIK3CD) were analyzed by Starbase and verified by double luciferase. The A549 cells were divided into normal group, LPS group, LPS+miR-27a mimic negative control group, LPS+miR-27a mimic group, LPS+miR-27a mimic+PI3K activator group. In the LPS+miR-27a mimic negative control group, LPS+miR-27a mimic group and LPS+miR-27a mimic+PI3K activator group, the cells were transfected with miR-27a mimic negative control, miR-27a mimic and miR-27a mimic, respectively, and were cultured for 6 h. After that, the cells were cultured in complete medium for 24 h, and then, except for the normal group, the cells in the other groups were stimulated with 10 mg/L LPS for 24 h, and the PI3K activator 740 Y-P was added to the LPS+miR-27a mimic+PI3K activator group, and cells in normal group were cultured in complete medium for the same time. Real-time quantitative polymerase chain reaction was used to detect the expression level of miR-27a in cells; cell counting kit 8 was used to detect cell proliferation; Hoechst33342 staining and flow cytometry was used to detect apoptosis; autophagy of A549 cells was observed by transmission electron microscope; Western blot was used to detect the expression of PIK3CD, phosphorylated-AKT (p-AKT), B-cell lymphoma-2 (Bcl-2), Bcl-2-associated X protein (Bax), cleaved caspase-3 and microtubule-associated protein 1 light chain 3 II (LC3II) protein. Results There was a binding site between miR-27a and PIK3CD, which was verified by double luciferase. Compared with those in normal group, the expression level of miR-27a, proliferation rate and protein expression level of Bcl-2 in LPS group and LPS+miR-27a mimic negative control group were lower (P<0.05), the apoptosis rate, protein expression levels of PIK3CD, p-AKT, Bax, cleaved caspase-3, LC3Ⅱ were higher (P<0.05); compared with those in LPS group and LPS+miR-27a mimic negative control group, the expression level of miR-27a, proliferation rate and protein expression level of Bcl-2 in LPS+miR-27a mimic group were higher (P<0.05), the apoptosis rate, protein expression levels of PIK3CD, p-AKT, Bax, cleaved caspase-3, LC3Ⅱ were lower (P<0.05); compared with those in LPS+miR-27a mimic group, the expression level of miR-27a and proliferation rate in LPS+miR-27a mimic+PI3K activator group were lower (P<0.05), the apoptosis rate, protein expression levels of PIK3CD, p-AKT, cleaved caspase-3, LC3Ⅱ were higher (P<0.05). The number of cells in the normal group was more, the cells were closely arranged, the nucleus size was uniform, and the organelle structure was normal; in LPS group and LPS+miR-27a mimic negative control group, cells became round, nuclei pyknosis, formed clumps, and showed multiple round autophagic vesicles of different sizes; the number of nuclear pyknotic cells in LPS+miR-27a mimic group decreased, and the number of nuclear pyknotic cells in LPS+miR-27a mimic+PI3K activator group increased compared with LPS+miR-27a mimic group, a small number of circular autophagic vesicles were observed, but the number was different. Conclusion Overexpression of miR-27a can inhibit PI3K/Akt pathway and reduce LPS induced apoptosis of human lung adenocarcinoma cells A549, which may be related to the reduction of autophagy.
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 compare the the effectiveness of robot-assisted thoracic surgery (RATS) with video-assisted thoracic surgery (VATS), in stageⅠ lung adenocarcinoma.MethodsFrom January 2012 to December 2018, 291 patients were included. The patients were allocated into two groups including a RATS group with 125 patients and a VATS group with 166 patients. Two cohorts (RATS, VATS ) of clinical stageⅠ lung adenocarcinoma patients were matched by propensity score. Then there were 114 patients in each group (228 patients in total). There were 45 males and 69 females at age of 62±9 years in the RATS group; 44 males, 70 females at age of 62±8 years in the VATS group. Overall survival (OS) and disease-free survival (DFS) were assessed. Univariate and multivariate analyses were performed to identify factors associated with the outcomes.Results Compared with the VATS group, the RATS group got less blood loss (P<0.05) and postoperative drainage (P<0.05) with a statistical difference. There was no statistical difference in drainage time (P>0.05) or postoperative hospital stay (P>0.05) between the two groups. The RATS group harvested more stations and number of the lymph nodes with a statistical difference (P<0.05). There was no statistical difference in 1-year, 3-year and 5-year OS and mean survival time (P>0.05). While there was a statistical difference in DFS between the two groups (1-year DFS: 94.1% vs. 95.6%; 3-year DFS: 92.6% vs. 75.2%; 5-year DFS: 92.6% vs. 68.4%, P<0.05; mean DFS time: 78 months vs. 63 months, P<0.05) between the two groups. The univariate analysis found that the number of the lymph nodes dissection was the prognostic factor for OS, and tumor diameter, surgical approach, stations and number of the lymph nodes dissection were the prognostic factors for DFS. However, multivariate analysis found that there was no independent risk factor for OS, but the tumor diameter and surgical approach were independently associated with DFS.ConclusionThere is no statistical difference in OS between the two groups, but the RATS group gets better DFS.
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.