Identification and validation of novel DNA methylation markers for early diagnosis of lung adenocarcinoma.
ABSTRACT: Lung cancer has the highest mortality of all cancers worldwide. Epigenetic alterations have emerged as potential biomarkers for early diagnosis of various cancer tissue types. To identify methylation markers for early diagnosis of lung adenocarcinoma, we aimed to integrate genome-wide DNA methylation and gene expression data from The Cancer Genome Atlas. To this end, we first examined the global DNA methylation pattern of lung adenocarcinoma and investigated the relationship between DNA methylation subtypes and clinical features. We then extracted differentially methylated and expressed genes, and adopted feature selection techniques to determine the final methylation markers. The performance of the markers in predicting lung adenocarcinoma was evaluated on three independent datasets from Gene Expression Omnibus. Protein levels of marker genes were validated by immunohistochemistry, and their biological function was further verified in vivo. We identified three novel methylation markers in lung adenocarcinoma including cg08032924, cg14823851, and cg19161124, mapping to CMTM2, TBX4, and DPP6, respectively. Validating these results on three independent datasets indicated that the three markers can achieve extremely high sensitivity and specificity in distinguishing lung adenocarcinoma from normal samples. Immunohistochemistry quantification results confirmed that markers are weakly expressed in human lung adenocarcinoma, and CMTM2 decreased tumor growth of mouse Lewis lung carcinoma in vivo. Overall, our study identified three novel methylation markers in lung adenocarcinoma which may contribute toward an improved diagnosis potentially leading to a better outcome for patients with lung adenocarcinoma.
Project description:Background: Aberrant methylation of CpG islands in tumor cells in promoter regions is a critical event in non-small cell lung carcinoma (NSCLC) tumorigenesis and can be a potential diagnostic biomarker for NSCLC patients. The present study systemically and quantitatively reviewed the diagnostic ability of CDH13 methylation in NSCLC as well as in its subsets. Eligible studies were identified through searching PubMed, Web of Science, Cochrane Library and Embase. The pooled odds of CDH13 promoter methylation in lung cancer tissues versus normal controls were calculated by meta-analysis method. Simultaneously, four independent DNA methylation datasets of NSCLC from TCGA and GEO database were downloaded and analyzed to validate the results from meta-analysis. Results: Thirteen studies, including 1850 samples were included in this meta-analysis. The pooled odds ratio of CDH13 promoter methylation in cancer tissues was 7.41 (95% CI: 5.34 to 10.29, P < 0.00001) compared with that in controls under fixed-effect model. In validation stage, 126 paired samples from TCGA were analyzed and 5 out of the 6 CpG sites in the CpG island of CDH13 were significantly hypermethylated in lung adenocarcinoma tissues but none of the 6 CpG sites was hypermethylated in squamous cell carcinoma tissues. Concordantly, the results from other three datasets, which were subsequently obtained from GEO database consisting of 568 tumors and 256 normal tissues, also consisted with those from TCGA dataset. Conclusion: The pooled data showed that the methylation status of the CDH13 promoter is strongly associated with lung adenocarcinoma. The CDH13 methylation status could be a promising diagnostic biomarker for diagnosis of lung adenocarcinoma.
Project description:BACKGROUND: Lung adenocarcinoma is the leading cause of cancer-related deaths among both men and women in the world. Despite recent advances in diagnosis and treatment, the mortality rates with an overall 5-year survival of only 15%. This high mortality is probably attributable to early metastasis. Although several well-known markers correlated with poor/metastasis prognosis in lung adenocarcinoma patients by immunohistochemistry was reported, the molecular mechanisms of lung adenocarcinoma development are still not clear. To explore novel molecular markers and their signaling pathways will be crucial for aiding in treatment of lung adenocarcinoma patients. METHODOLOGY/PRINCIPAL FINDINGS: To identify novel lung adenocarcinoma-associated /metastasis genes and to clarify the underlying molecular mechanisms of these targets in lung cancer progression, we created a bioinformatics scheme consisting of integrating three gene expression profile datasets, including pairwise lung adenocarcinoma, secondary metastatic tumors vs. benign tumors, and a series of invasive cell lines. Among the novel targets identified, FLJ10540 was overexpressed in lung cancer tissues and is associated with cell migration and invasion. Furthermore, we employed two co-expression strategies to identify in which pathway FLJ10540 was involved. Lung adenocarcinoma array profiles and tissue microarray IHC staining data showed that FLJ10540 and VEGF-A, as well as FLJ10540 and phospho-AKT exhibit positive correlations, respectively. Stimulation of lung cancer cells with VEGF-A results in an increase in FLJ10540 protein expression and enhances complex formation with PI3K. Treatment with VEGFR2 and PI3K inhibitors affects cell migration and invasion by activating the PI3K/AKT pathway. Moreover, knockdown of FLJ10540 destabilizes formation of the P110-alpha/P85-alpha-(PI3K) complex, further supporting the participation of FLJ10540 in the VEGF-A/PI3K/AKT pathway. CONCLUSIONS/SIGNIFICANCE: This finding set the stage for further testing of FLJ10540 as a new therapeutic target for treating lung cancer and may contribute to the development of new therapeutic strategies that are able to block the PI3K/AKT pathway in lung cancer cells.
Project description:BACKGROUND:Hypermethylation of gene promoters plays an important role in tumorigenesis. The present study aimed to identify and validate promoter methylation-driven genes (PMDGs) for pancreatic ductal adenocarcinoma (PDAC). METHODS:Based on GSE49149 and the PDAC cohort of The Cancer Genome Atlas (TCGA), differential analyses of promoter methylation, correlation analysis, and Cox regression analysis were performed to identify PMDGs. The promoter methylation level was assessed by bisulfite sequencing polymerase chain reaction (BSP) in paired tumor and normal tissues of 72 PDAC patients. Kaplan-Meier survival analyses were performed to evaluate the clinical value of PMDGs. RESULTS:In GSE49149, the ?-value of the dipeptidyl peptidase like 6 (DPP6) promoter was significantly higher in tumor compared with normal samples (0.50 vs. 0.24, P<0.001). In the PDAC cohort of TCGA, the methylation level of the DPP6 promoter was negatively correlated with mRNA expression (r = -0.54, P<0.001). In a multivariate Cox regression analysis, hypermethylation of the DPP6 promoter was an independent risk factor for PDAC (hazard ratio (HR) = 543.91, P=0.002). The results of BSP revealed that the number of methylated CG sites in the DPP6 promoter was greater in tumor samples than in normal samples (7.43 vs. 2.78, P<0.001). The methylation level of the DPP6 promoter was moderately effective at distinguishing tumor from normal samples (area under ROC curve (AUC) = 0.74, P<0.001). Hypermethylation of the DPP6 promoter was associated with poor overall (HR = 3.61, P<0.001) and disease-free (HR = 2.01, P=0.016) survivals for PDAC patients. CONCLUSION:These results indicate that DPP6 promoter methylation is a potential prognostic biomarker for PDAC.
Project description:Lung adenocarcinoma is frequently occurring type of lung cancer with high metastatic risk. We performed a DNA methylation profiling analysis to identify possible prognostic markers involved in lung adenocarcinoma. DNA methylation profiling data (GSE66386) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially methylated genes were identified using a limma package. GO enrichment analysis was performed to identify vital functions related to differential gene methylation, and pathway analysis was performed to assess the associations between different proteins with regard to regulation of cell function and metabolism. The screening results showed a total of 112,662 differentially methylated genes in lung adenocarcinoma patients compared with those of the normal controls. These CpGs were involved in 16,705 genes. The skeletal system development (P=9.46E-27) and embryonic organ morphogenesis (P=8.67E-24) were found to be involved in lung adenocarcinoma. The cancer (P=3.64E-07), Rap1 signaling (P=9.21E-05) and calcium signaling (P=9.21E-05) pathways constituted the important pathways associated with lung adenocarcinoma. In conclusion, methylated PTPRF, HOXD3, HOXD13 and CACNA1A are potential markers and may be utilized for the diagnosis and therapy of lung adenocarcinoma.
Project description:Lung cancer has one of the highest mortality rates of malignant neoplasms. Lung adenocarcinoma (LUAD) is one of the most common types of lung cancer. DNA methylation is more stable than gene expression and could be used as a biomarker for early tumor diagnosis. This study is aimed to screen potential DNA methylation signatures to facilitate the diagnosis and prognosis of LUAD and integrate gene expression and DNA methylation data of LUAD to identify functional epigenetic modules. We systematically integrated gene expression and DNA methylation data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), bioinformatic models and algorithms were implemented to identify signatures and functional modules for LUAD. Three promising diagnostic and five potential prognostic signatures for LUAD were screened by rigorous filtration, and our tumor-normal classifier and prognostic model were validated in two separate data sets. Additionally, we identified functional epigenetic modules in the TCGA LUAD dataset and GEO independent validation data set. Interestingly, the MUC1 module was identified in both datasets. The potential biomarkers for the diagnosis and prognosis of LUAD are expected to be further verified in clinical practice to aid in the diagnosis and treatment of LUAD.
Project description:<h4>Background</h4>Reciprocal interactions between lung mesenchymal and epithelial cells play essential roles in lung organogenesis and homeostasis. Although the molecular markers and related animal models that target lung epithelial cells are relatively well studied, molecular markers of lung mesenchymal cells and the genetic tools to target and/or manipulate gene expression in a lung mesenchyme-specific manner are not available, which becomes a critical barrier to the study of lung mesenchymal biology and the related pulmonary diseases.<h4>Results</h4>We have identified a mouse Tbx4 gene enhancer that contains conserved DNA sequences across many vertebrate species with lung or lung-like gas exchange organ. We then generate a mouse line to express rtTA/LacZ under the control of the Tbx4 lung enhancer, and therefore a Tet-On inducible transgenic system to target lung mesenchymal cells at different developmental stages. By combining a Tbx4-rtTA driven Tet-On inducible Cre expression mouse line with a Cre reporter mouse line, the spatial-temporal patterns of Tbx4 lung enhancer targeted lung mesenchymal cells were defined. Pulmonary endothelial cells and vascular smooth muscle cells were targeted by the Tbx4-rtTA driver line prior to E11.5 and E15.5, respectively, while other subtypes of lung mesenchymal cells including airway smooth muscle cells, fibroblasts, pericytes could be targeted during the entire developmental stage.<h4>Conclusions</h4>Developmental lung mesenchymal cells can be specifically marked by Tbx4 lung enhancer activity. With our newly created Tbx4 lung enhancer-driven Tet-On inducible system, lung mesenchymal cells can be specifically and differentially targeted in vivo for the first time by controlling the doxycycline induction time window. This novel system provides a unique tool to study lung mesenchymal cell lineages and gene functions in lung mesenchymal development, injury repair, and regeneration in mice.
Project description:Pathologic differentiation of tissue of origin in tumors found in the lung can be challenging, with differentiation of mesothelioma and lung adenocarcinoma emblematic of this problem. Indeed, proper classification is essential for determination of treatment regimen for these diseases, making accurate and early diagnosis critical. Here, we investigate the potential of epigenetic profiles of lung adenocarcinoma, mesothelioma, and nonmalignant pulmonary tissues (n = 285) as differentiation markers in an analysis of DNA methylation at 1413 autosomal CpG loci associated with 773 cancer-related genes. Using an unsupervised recursively partitioned mixture modeling technique for all samples, the derived methylation profile classes were significantly associated with sample type (P < 0.0001). In a similar analysis restricted to tumors, methylation profile classes significantly predicted tumor type (P < 0.0001). Random forests classification of CpG methylation of tumors--which splits the data into training and test sets--accurately differentiated mesothelioma from lung adenocarcinoma over 99% of the time (P < 0.0001). In a locus-by-locus comparison of CpG methylation between tumor types, 1266 CpG loci had significantly different methylation between tumors following correction for multiple comparisons (Q < 0.05); 61% had higher methylation in adenocarcinoma. Using the CpG loci with significant differential methylation in a pathway analysis revealed significant enrichment of methylated gene-loci in Cell Cycle Regulation, DNA Damage Response, PTEN Signaling, and Apoptosis Signaling pathways in lung adenocarcinoma when compared with mesothelioma. Methylation profile-based differentiation of lung adenocarcinoma and mesothelioma is highly accurate, informs on the distinct etiologies of these diseases, and holds promise for clinical application.
Project description:BACKGROUND:Lung adenocarcinoma is the most common type of lung cancer, with high mortality worldwide. Its occurrence and development were thoroughly studied by high-throughput expression microarray, which produced abundant data on gene expression, DNA methylation, and miRNA quantification. However, the hub genes, which can be served as bio-markers for discriminating cancer and healthy individuals, are not well screened. RESULT:Here we present a new method for extracting gene predictors, aiming to obtain the least predictors without losing the efficiency. We firstly analyzed three different expression microarrays and constructed multi-interaction network, since the individual expression dataset is not enough for describing biological behaviors dynamically and systematically. Then, we transformed the undirected interaction network to directed network by employing Granger causality test, followed by the predictors screened with the use of the stepwise character selection algorithm. Six predictors, including TOP2A, GRK5, SIRT7, MCM7, EGFR, and COL1A2, were ultimately identified. All the predictors are the cancer-related, and the number is very small fascinating diagnosis. Finally, the validation of this approach was verified by robustness analyses applied to six independent datasets; the precision is up to 95.3% ??100%. CONCLUSION:Although there are complicated differences between cancer and normal cells in gene functions, cancer cells could be differentiated in case that a group of special genes expresses abnormally. Here we presented a new, robust, and effective method for extracting gene predictors. We identified as low as 6 genes which can be taken as predictors for diagnosing lung adenocarcinoma.
Project description:BACKGROUND:Little is known about epigenetic silencing of genes by promoter hypermethylation in renal cell carcinoma (RCC). The aim of this study was to identify prognostic methylation markers in surgically treated clear cell RCC (ccRCC). METHODS:Methylation patterns were assayed using the Infinium HumanMethylation450 BeadChip array on pairs of ccRCC and normal tissue from 12 patients. Using quantitative PSQ analysis, tumor-specific hypermethylated genes were validated in 25 independent cohorts and their clinical relevance was also verified in 152 independent cohorts. RESULTS:Using genome-wide methylation array, Zinc finger protein 278 (ZNF278), Family with sequence similarity 155 member A (FAM155A) and Dipeptidyl peptidase 6 (DPP6) were selected for tumor-specific hypermethylated genes in primary ccRCC. The promoter methylation of these genes occurred more frequently in ccRCC than normal kidney in independent validation cohort. The hypermethylation of three genes were associated with advanced tumor stage and high grade tumor in ccRCC. During median follow-up of 39.2 (interquartile range, 15.4-79.1) months, 22 (14.5%) patients experienced distant metastasis. Multivariate analysis identified the methylation status of these three genes, either alone, or in a combined risk score as an independent predictor of distant metastasis. CONCLUSION:The promoter methylation of ZNF278, FAM155A and DPP6 genes are associated with aggressive tumor phenotype and early development of distant metastasis in patients with surgically treated ccRCC. These potential methylation markers, either alone, or in combination, could provide novel targets for development of individualized therapeutic and prevention regimens.
Project description:SPC24 is over-expressed in clinical lung adenocarcinoma samples, and high level of SPC24 is associated with advanced stages of lung tumors. Knocking down SPC24 repressed cell growth and promoted apoptosis. SPC24 deficiency reduced cancer cell migration as well. E-cadherin, one of the epithelial-mesenchymal transition markers, was up-regulated in the knockdown cells, along with down-regulation of N-cadherin and Vimentin. Oncomine expression analyses further confirmed that high level of SPC24 is associated with tumors from smokers, recurrent patients, or patients with shorter survivals.To reveal the role of SPC24, an important component of kinetochore, in the tumorigenesis of lung cancer, we performed Oncomine and immunohistochemistry (IHC) analyses for SPC24 in human lung adenocarcinoma tumors. We knocked down SPC24 in two non-small cell lung cancer (NSCLC) cell lines, PC9 and A549, by siRNA and evaluated cell proliferation, apoptosis, and migration in the SPC24-deficient cells. Using a mouse xenograft model, we compared in vivo tumor growth of the knockdown and control cells. We further performed multiple Oncomine expression analyses for SPC24 in various lung cancer datasets with important clinical characteristics and risk factors, including survival, recurrence, and smoking status.SPC24 is a novel oncogene of lung cancer, and can serve as a promising prognostic biomarker to differentiate lung tumors that have various clinicopathological characteristics. The findings of the current study will benefit the diagnosis, management, and targeted therapy of lung cancer.