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.
Lung adenocarcinoma is a prevalent histological subtype of non-small cell lung cancer with different morphologic and molecular features that are critical for prognosis and treatment planning. In recent years, with the development of artificial intelligence technology, its application in the study of pathological subtypes and gene expression of lung adenocarcinoma has gained widespread attention. This paper reviews the research progress of machine learning and deep learning in pathological subtypes classification and gene expression analysis of lung adenocarcinoma, and some problems and challenges at the present stage are summarized and the future directions of artificial intelligence in lung adenocarcinoma research are foreseen.
ObjectiveTo investigate the correlation between histological subtypes of invasive lung adenocarcinoma and epithelial growth factor receptor (EGFR) gene mutation, and to provide a reference for clinical prediction of EGFR gene mutation status.MethodsFrom October 2017 to May 2019, 102 patients with invasive lung adenocarcinoma were collected, including 58 males and 44 females aged 62 (31-84) years. Invasive lung adenocarcinoma was classified into different histological subtypes. Scorpion probe amplification block mutation system (ARMS) real-time PCR was used to detect the mutation of EGFR gene in adenocarcinoma specimens, and the relationship between invasive lung adenocarcinoma subtypes and EGFR mutation status was analyzed.ResultsIn 102 patients with invasive lung adenocarcinoma, EGFR gene mutations were detected in 68 patients, and the mutation rate was 66.7% (68/102). The mutation sites were mainly concentrated in the exons 19 and 21; the mutation rate was higher in female patients (34/44, 77.3%) and non-smokers (34/58, 58.6%). EGFR mutation was mostly caused by acinar-like invasive lung adenocarcinoma, and was rare in solid-type lung adenocarcinoma. The EGFR gene mutation rates in different subtypes of adenocarcinoma were statistically different (P<0.05).ConclusionThe EGFR mutation status is related to gender, smoking status and histological subtype of invasive lung adenocarcinoma. EGFR mutation rates are higher in female, non-smoking and acinar-like invasive lung adenocarcinoma patients, and are lower in patients with solid type lung 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.
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.
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.
Objective To explore the role of cyclin B1 (CCNB1), cyclin B2 (CCNB2) and cyclin dependent kinase 1 (CDK1) in lung adenocarcinoma (LUAD) using bioinformatic data. Methods First, RNA expression data were downloaded from two datasets in Gene Expression Omnibus (GEO), and DESeq2 software was used to identify deferentially expressed genes (DEGs). Subsequent analyses were conducted based on the results of these DEGs: protein-protein interaction (PPI) network was constructed with STRING database; the modules in PPI network were analyzed by Molecular Complex Detection software, and the most significant modules were selected, the genes included in these modules were the hub genes; high-throughput RNA sequencing data from other databases were used to verify the expression of these hub genes to confirm whether they were DEGs; survival curve analyses of the confirmed DEGs were conducted to select genes that had significant influence on the survival of LUAD; the expression of these hub genes in different stages of LUAD were also analyzed. Then, Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed for these selected hub genes using KOBAS database. MuTarget tool was used to analyze the correlations between the expression of these selected hub genes and gene mutation status in LUAD. The potential value of these hub genes in the treatment of LUAD was explored based on the drug information in GDSC database. Finally, immunohistochemical data from Human Protein Atlas (HPA) database were used to verify the expression of these hub genes in LUAD again. Results According to the expression data in GEO, 594 up-regulated genes and 651 down-regulated genes were identified (P<0.05), among which 30 hub genes were selected for subsequent analyses. The RNA high-throughput sequencing data of other databases verified that 18 genes were DEGs, among which 8 hub genes had significant impact on disease-free survival in LUAD (P<0.05). Moreover, the 8 genes were differentially expressed in different stages of LUAD, which were higher in the middle and late stage of LUAD. Among the 8 genes. CCNB1, CCNB2 and CDK1 were significantly enriched in the cell cycle pathway. The expression of CCNB1, CCNB2 and CDK1 in LUAD was closely related to the TP53 mutation status. In addition, CDK1 was associated with four drugs, revealing the potential value of CDK1 in the treatment of LUAD. Finally, immunohistochemical data from HPA database verified that CCNB1, CCNB2 and CDK1 were highly expressed in LUAD in the protein level. Conclusion Overexpression of CCNB1, CCNB2 and CDK1 are associated with poor prognosis of LUAD, indicating that the three genes may be prognostic biomarkers of LUAD and CDK1 is a potential therapeutic target for LUAD.
ObjectiveTo evaluate the clinical manifestation, radiological, pathological features and treatment of organizing pneumonia (OP) induced by aerosolized recombinant super compound interferon (rSIFN-co). MethodsClinical features and related laboratory examinations of a patient with OP developing after initiation of rSIFN-co for treatment of lung adenocarcinoma were analyzed, and the relevant literature was reviewed. ResultsA 48-year-old man developed cough, fevers, shortness of breath and weight loss, shortly half a month after initiation of therapy with rSIFN-co for lung adenocarcinoma. Chest high resolution computerized tomography (HRCT) showed multiple lung infection diseases. However, the anti-infection treatment was invalid. Lung tissue biopsy by bronchofibroscope was consistent with OP. After discontinuation of rSIFN-co and receiving pulse corticosteroid therapy followed by oral methylprednisolone, the pneumonic symptoms and chest manifestations markedly improved. After eight-month follow-up, the patient's condition was stable. The relative literature screening from Pubmed and Wanfangdata was implemented, but there was no report about OP caused by aerosolized rSIFN-co for lung adenocarcinoma. ConclusionThis report suggests that treatment with aerosolized rSIFN-co for lung adenocarcinoma may induce OP, a rare complication, and clinicians should have vigilance on it.
Objective To select relatively specific biomarkers in serum from lung adenocarcinoma patients using surface-enhanced laser desorption ionization time of flight mass spectrometry （SELDI-TOF-MS） Protein Chip technology, and study the follow-up results of postoperative serum proteomic patterns. Methods Serum samples from 71 lung adenocarcinoma patients. 71 healthy volunteers with matched gender, age and history of smoking were analyzed by using weak cation exchange 2（WCX2） Protein Chip to select potentially biomarkers. Seventy-one patients were followed-up till 9 months after surgery. Compare the serum proteomic patterns 3,6 and 9 months after surgery. Results Five highly expressed potential biomarkers were identified with the relative molecular weights of 4 047.79, 4 203. 99, 4 959. 81, 5 329. 30 and 7 760. 12 Da. The postoperative serum proteomic patterns changed among individuals, and correlated with patients＇ clinical stage. Conclusions SELDI-TOF-MS Protein Chip technology is a quick, easy, convenient, and high-throughout analyzing method capable of selecting relatively specific, potential biomarkers from the serum of lung adenocarcinoma patients and may have attractive clinical value.
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.