Aberrant CpG-methylation affects genes expression predicting survival in lung adenocarcinoma

Tensins in Kidney Function and Diseases

Tensins are focal adhesion proteins that regulate various biological processes, such as mechanical sensing, cell adhesion, migration, invasion, and proliferation, through their multiple binding activities that transduce critical signals across the plasma membrane. When these molecular interactions and/or mediated signaling are disrupted, cellular activities and tissue functions are compromised, leading to disease development. Here, we focus on the significance of the tensin family in renal function and diseases. The expression pattern of each tensin in the kidney, their roles in chronic kidney diseases, renal cell carcinoma, and their potentials as prognostic markers and/or therapeutic targets are discussed in this review.

A 70‑RNA model based on SVR and RFE for predicting the pancreatic cancer clinical prognosis

Researches on the prognosis of pancreatic cancer is of great significance to improve the patient treatment effect and survival. Current researches mainly focus on the prediction of the survival status and the determination of prognostic markers. Each patient has its own characteristics, there is no report about the prediction of survival time. However, accurate prediction of survival time is critical for personalized medicine. In this paper, a hybrid algorithm of Support Vector Regression (SVR) and Recursive Feature Elimination (RFE) was used to construct a quantitative prediction model of Overall Survival (OS) for pancreatic cancer patients, 70 RNAs related to OS were determined, including 33 mRNAs, 28 lncRNAs, and 9 miRNAs. The results of 10-fold cross-validation (R2 is 0.9693) and the generalization ability (R2 is 0.9666) showed that the model has reliable predictive performance and these 70 RNAs are important factors influencing the OS of pancreatic cancer patients. To further study the relationship between RNA-RNA interaction and the survival, competitive endogenous RNA (ceRNA) regulation network was constructed. Degree centrality, betweenness centrality and closeness centrality of nodes in the ceRNA network showed that hsa-mir-570, hsa-mir-944, hsa-mir-6506, hsa-mir-3136, MMP16, PLGLB2, HPGD, FUT1, MFSD2A, SULT1E1, SLC13A5, ZNF488, F2RL2, TNFRSF8, TNFSF11, FHDC1, ISLR2 and THSD7B are hub nodes, which are key RNAs closely determining the OS of pancreatic cancer patients.

InterTADs: integration of multi-omics data on topologically associated domains, application to chronic lymphocytic leukemia

The integration of multi-omics data can greatly facilitate the advancement of research in Life Sciences by highlighting new interactions. However, there is currently no widespread procedure for meaningful multi-omics data integration. Here, we present a robust framework, called InterTADs, for integrating multi-omics data derived from the same sample, and considering the chromatin configuration of the genome, i.e. the topologically associating domains (TADs). Following the integration process, statistical analysis highlights the differences between the groups of interest (normal versus cancer cells) relating to (i) independent and (ii) integrated events through TADs. Finally, enrichment analysis using KEGG database, Gene Ontology and transcription factor binding sites and visualization approaches are available. We applied InterTADs to multi-omics datasets from 135 patients with chronic lymphocytic leukemia (CLL) and found that the integration through TADs resulted in a dramatic reduction of heterogeneity compared to individual events. Significant differences for individual events and on TADs level were identified between patients differing in the somatic hypermutation status of the clonotypic immunoglobulin genes, the core biological stratifier in CLL, attesting to the biomedical relevance of InterTADs. In conclusion, our approach suggests a new perspective towards analyzing multi-omics data, by offering reasonable execution time, biological benchmarking and potentially contributing to pattern discovery through TADs.

An N6-methyladenosine and target genes-based study on subtypes and prognosis of lung adenocarcinoma

Purpose: Lung adenocarcinoma (LUAD) is a highly lethal subtype of primary lung cancer with a poor prognosis. N6-methyladenosine (m⁶A), the most predominant form of RNA modification, regulates biological processes and has critical prognostic implications for LUAD. Our study aimed to mine potential target genes of m⁶A regulators to explore their biological significance in subtyping LUAD and predicting survival. Methods: Using gene expression data from TCGA database, candidate target genes of m⁶A were predicted from differentially expressed genes (DEGs) in tumor based on M⁶A2 Target database. The survival-related target DEGs identified by Cox-regression analysis was used for consensus clustering analysis to subtype LUAD. Uni-and multi-variable Cox regression analysis and LASSO Cox-PH regression analysis were used to select the optimal prognostic genes for constructing prognostic score (PS) model. Nomogram encompassing PS score and independent prognostic factors was built to predict 3-year and 5-year survival probability. Results: We obtained 2429 DEGs in tumor tissue, within which, 1267 were predicted to m⁶A target genes. A prognostic m⁶A-DEGs network of 224 survival-related target DEGs was established. We classified LUAD into 2 subtypes, which were significantly different in OS time, clinicopathological characteristics, and fractions of 12 immune cell types. A PS model of five genes (C1QTNF6, THSD1, GRIK2, E2F7 and SLCO1B3) successfully split the training set or an independent GEO dataset into two subgroups with significantly different OS time (p < 0.001, AUC = 0.723; p = 0.017, AUC = 0.705).A nomogram model combining PS status, pathologic stage, and recurrence was built, showing good performance in predicting 3-year and 5-year survival probability (C-index = 0.708, 0.723, p-value = 0). Conclusion: Using candidate m⁶A target genes, we obtained two molecular subtypes and designed a reliable five-gene PS score model for survival prediction in LUAD.

Gene Expression Profiles of Multiple Synchronous Lesions in Lung Adenocarcinoma

Many studies support a stepwise continuum of morphologic changes between atypical adenomatous hyperplasia (AAH) and lung adenocarcinoma (ADC). Here we characterized gene expression patterns and the association of differentially expressed genes and immune tumor microenvironment behaviors in AAH to ADC during ADC development. Tumor tissues from nine patients with ADC and synchronous multiple ground glass nodules/lesions (GGN/Ls) were analyzed using RNA sequencing. Using clustering, we identified genes differentially and sequentially expressed in AAH and ADC compared to normal tissues. Functional enrichment analysis using gene ontology terms was performed, and the fraction of immune cell types was estimated. We identified up-regulated genes (ACSL5 and SERINC2) with a stepwise change of expression from AAH to ADC and validated those expressions by quantitative PCR and immunohistochemistry. The immune cell profiles revealed increased B cell activities and decreased natural killer cell activities in AAH and ADC. A stepwise change of differential expression during ADC development revealed potential effects on immune function in synchronous precursors and in tumor lesions in patients with lung cancer.

A functional methylation signature to predict the prognosis of Chinese lung adenocarcinoma based on TCGA

Background

Lung cancer is the leading cause of cancer morbidity and mortality worldwide, however, the individualized treatment is still unsatisfactory. DNA methylation can affect gene regulation and may be one of the most valuable biomarkers in predicting the prognosis of lung adenocarcinoma. This study was aimed to identify methylation CpG sites that may be used to predict lung adenocarcinoma prognosis.

Methods

The Cancer Genome Atlas (TCGA) database was used to detect methylation CpG sites associated with lung adenocarcinoma prognosis and construct a methylation signature model. Then, a Chinese cohort was carried out to estimate the association between methylation and lung adenocarcinoma prognosis. Biological function studies, including demethylation treatment, cell proliferative capacity, and gene expression changes in lung adenocarcinoma cell lines, were further performed.

Results

In the TCGA set, three methylation CpG sites were selected that were associated with lung adenocarcinoma prognosis (cg14517217, cg15386964, and cg18878992). The risk of mortality was increased in lung adenocarcinoma patients with the gradual increase level of methylation signature based on three methylation sites levels (HR = 45.30, 95% CI = 26.69–66.83; p < 0.001). The C‐statistic value increased to 0.77 when age, gender, and other clinical variables were added to the signature to prediction model. A similar situation was confirmed in Chinese lung adenocarcinoma cohort. In the biological function studies, the proliferative capacity of cell lines was inhibited when the cells were demethylated with 5‐aza‐2'‐deoxycytidine (5‐aza‐2dC). The mRNA and protein expression levels of SEPT9 and HIST1H2BH (cg14517217 and cg15386964) were downregulated with different concentrations of 5‐aza‐2dC treatment, while cg18878992 showed the opposite result.

Conclusion

This study is the first to develop a three‐CpG‐based model for lung adenocarcinoma, which is a practical and useful tool for prognostic prediction that has been validated in a Chinese population.

Aberrantly DNA Methylated-Differentially Expressed Genes in Pancreatic Cancer Through an Integrated Bioinformatics Approach

Pancreatic cancer remains one of the chief contributors to cancer related deaths on a global scale, with its diagnosis often associated with poor prognosis and high mortality. Accumulating literature continues to highlight the role of aberrant DNA methylation in relation to pancreatic cancer progression. Integrated bioinformatics approaches in the characterization of methylated-differentially expressed genes (MeDEGs) in pancreatic cancer were employed to enhance our understanding of the potential underlying molecular mechanisms of this cancer. We initially identified differentially expressed genes (DEGs) between 178 pancreatic cancer samples and 4 normal samples and differentially methylated genes (DMGs) based on 185 pancreatic cancer samples as well as 10 normal samples by analyzing RNA sequencing data in the TCGA database. Eventually, 31 MeDEGs including 5 hypomethylated/upregulated genes and 26 hypermethylated/downregulated genes were identified. Univariate Cox model and Kaplan–Meier method revealed that, among 31 MeDEGs, 5 hypermethylated/downregulated genes (ZNF804A, ZFP82, TRIM58, SOX17, and C12orf42) were correlated with poor survival of patients with pancreatic cancer. KEGG pathway enrichment analysis by GSEA 3.0 and the protein–protein interaction (PPI) network revealed that these 5 MeDEGs were enriched in numerous cancer-related pathways in addition to interacting with each other, highlighting a significant role in the development of pancreatic cancer. Taken together, the key findings of the current study demonstrate that ZNF804A, ZFP82, TRIM58, SOX17, and C12orf42 are hypermethylated/downregulated genes in pancreatic cancer and may be associated, through their modulation of specific pathways, with unfavorable pancreatic cancer prognosis.

Tensins - emerging insights into their domain functions, biological roles and disease relevance

Tensins are a family of focal adhesion proteins consisting of four members in mammals (TNS1, TNS2, TNS3 and TNS4). Their multiple domains and activities contribute to the molecular linkage between the extracellular matrix and cytoskeletal networks, as well as mediating signal transduction pathways, leading to a variety of physiological processes, including cell proliferation, attachment, migration and mechanical sensing in a cell. Tensins are required for maintaining normal tissue structures and functions, especially in the kidney and heart, as well as in muscle regeneration, in animals. This Review discusses our current understanding of the domain functions and biological roles of tensins in cells and mice, as well as highlighting their relevance to human diseases.

Identification of the Different Gene Expression Characteristics from Liver Cirrhosis to Hepatocellular Carcinoma Using Single-Cell Sequencing Analyses

The occurrence of hepatocellular carcinoma (HCC) is closely related to the chronic inflammation which caused liver fibrosis and cirrhosis, and the interaction between HCC and its microenvironment further drives tumorigenesis. However, the single-cell resolution in vivo study is lacking, which limits our molecular understanding of tumour biology in the liver. Here, using published single-cell sequencing technology (scRNA-seq) database, we analyzed the liver microenvironment at high resolution in an unbiased manner and demonstrated the transcriptomic comparison between various cell populations and subpopulations in HCC and cirrhosis tissues. We found that eight genes that are specifically expressed in the endothelial cell and stellate cell of the HCC patients and correlated them with their survival rate, which may provide novel diagnosis and treatment targets for the clinical application.

Methylation biomarkers with discriminating ability are potential therapeutic targets in lung adenocarcinoma

Aims: Given the reversibility of methylation, biomarkers with discriminating ability are of great interest for targeted therapeutic sites. Materials & methods: Methylation array data of 461 lung adenocarcinoma (LUAD) patients comprising of 458 tumor and 32 LUAD paracancerous samples were compared using partial least squares discrimination analysis and receiver operating characteristics analysis. Results: A six-DNA methylation signature (corresponding to five genes) was found to significantly discriminate normal and LUAD samples. Kyoto Encyclopedia of Genes and Genomes analysis indicated enrichment of methylation sites in the Wnt pathway in LUAD compared with controls. Conclusion: This six-DNA methylation signature demonstrated potential as a novel biomarker for diagnosis and therapeutic targets. Further, inhibition of Wnt signaling pathway may be an important step in LUAD progression.

Screening of Methylation Gene Sites as Prognostic Signature in Lung Adenocarcinoma

PURPOSE

Most lung adenocarcinoma (LUAD) patients are diagnosed at the advanced stage and have poor prognosis. DNA methylation plays an important role in the prognosis prediction of cancers. The objective of this study was to identify new DNA methylation sites as biomarkers for LUAD prognosis.

MATERIALS AND METHODS

We downloaded DNA methylation data from The Cancer Genome Atlas data portal. Cox proportional hazard regression model and random survival forest algorithm were applied to identify the DNA-methylation sites. Methylation of sites were validated in the Gene Expression Omnibus cohorts. Function annotation were done to explore the biological function of DNA methylated sites signature.

RESULTS

Six DNA methylation sites were identified as prognosis signature. The signature yielded acceptable discrimination between the high-risk group and low-risk group. The discrimination effect of this DNA methylation signature for the OS was obvious, with a median OS of 21.89 months vs. 17.74 months for high-risk vs. low-risk groups. This prognostic prediction model was validated by the test group and GEO dataset. The predictive survival value was higher for the prognostic prediction model than that for the tumor node metastasis stage. Adjuvant hemotherapy could not affect the prediction of the signature. Functional analysis indicated that these signature genes were involved in protein binding and cytoplasm.

CONCLUSION

We identified the prognostic signature for LUAD by combining six DNA methylation sites. This could service as potential robust and specificity signature in the prognosis prediction of LUAD.

Molecular subtypes based on DNA promoter methylation predict prognosis in lung adenocarcinoma patients

BACKGROUND

The heterogeneity of lung adenocarcinoma (LADC) makes the early diagnosis and treatment of the disease difficult. Gene silencing of DNA methylation is an important mechanism of tumorigenesis. A combination of methylation and clinical features can improve the classification of LADC heterogeneity.

RESULTS

We investigated the prognostic significance of 335 specimen subgroups of Lung adenocarcinoma based on the DNA methylation level. The differences in DNA methylation levels were related to the TNM stage classification, age, gender, and prognostic values. Seven subtypes were determined using 774 CpG sites that significantly affected the survival rate based on the consensus clustering. Finally, we constructed a prognostic model that performed well and further verified it in our test group.

CONCLUSIONS

This study shows that classification based on DNA methylation might aid in demonstrating heterogeneity within formerly characterized LADC molecular subtypes, assisting in the development of efficient, personalized therapy.

METHODS

Methylation data of lung adenocarcinoma were downloaded from the University of California Santa Cruz (UCSC) cancer browser, and the clinical patient information and RNA-seq archives were acquired from the Cancer Genome Atlas (TCGA). CpG sites were identified based on the significant correlation with the prognosis and used further to cluster the cases uniformly into several subtypes.

DNA methylation-based lung adenocarcinoma subtypes can predict prognosis, recurrence, and immunotherapeutic implications

The marked heterogeneity of lung adenocarcinoma (LUAD) makes its diagnosis and treatment difficult. In addition, the aberrant DNA methylation profile contributes to tumor heterogeneity and alters the immune response. We used DNA methylation array data from publicly available databases to establish a predictive model for LUAD prognosis. Thirty-three methylation sites were identified as specific prognostic biomarkers, independent of patients' clinical characteristics. These methylation profiles were used to identify potential drug candidates and study the immune microenvironment of LUAD and response to immunotherapy. When compared with the high-risk group, the low-risk group had a lower recurrence rate and favorable prognosis. The tumor microenvironment differed between the two groups as reflected by the higher number of resting dendritic cells and a lower number of monocytes and resting mast cells in the low-risk group. Moreover, low-risk patients reported higher immune and stromal scores, lower tumor purity, and higher expression of HLA genes. Low-risk patients responded well to immunotherapy due to higher expression of immune checkpoint molecules and lower stemness index. Thus, our model predicted a favorable prognosis and increased overall survival for patients in the low-risk methylation group. Further, this model could provide potential drug targets to develop effective immunotherapies for LUAD.

Development and Validation of a Seven-Gene Signature for Predicting the Prognosis of Lung Adenocarcinoma

Background

Prognosis is a main factor affecting the survival of patients with lung adenocarcinoma (LUAD), yet no robust prognostic model of high effectiveness has been developed. This study is aimed at constructing a stable and practicable gene signature-based model via bioinformatics methods for predicting the prognosis of LUAD sufferers.

Methods

The mRNA expression data were accessed from the TCGA-LUAD dataset, and paired clinical information was collected from the GDC website. R package “edgeR” was employed to select the differentially expressed genes (DEGs), which were then used for the construction of a gene signature-based model via univariate COX, Lasso, and multivariate COX regression analyses. Kaplan-Meier and ROC survival analyses were conducted to comprehensively evaluate the performance of the model in predicting LUAD prognosis, and an independent dataset GSE26939 was accessed for further validation.

Results

Totally, 1,655 DEGs were obtained, and a 7-gene signature-based risk score was developed and formulated as risk_score = 0.000245∗NTSR1 + (7.13E − 05)∗RHOV + 0.000505∗KLK8 + (7.01E − 05)∗TNS4 + 0.000288∗C1QTNF6 + 0.00044∗IVL + 0.000161∗B4GALNT2. Kaplan-Meier survival curves revealed that the survival rate of patients in the high-risk group was lower in both the TCGA-LUAD dataset and GSE26939 relative to that of patients in the low-risk group. The relationship between the risk score and clinical characteristics was further investigated, finding that the model was effective in prognosis prediction in the patients with different age (age > 65, age < 65) and TNM stage (N0&N1, T1&T2, and tumor stage I/II). In sum, our study provides a robust predictive model for LUAD prognosis, which boosts the clinical research on LUAD and helps to explore the mechanism underlying the occurrence and progression of LUAD.

Aberrant Methylation and Differential Expression of SLC2A1, TNS4, GAPDH, ATP8A2, and CASZ1 Are Associated with the Prognosis of Lung Adenocarcinoma

Lung cancer is one of the leading triggers for cancer death worldwide. In this study, the relationship of the aberrantly methylated and differentially expressed genes in lung adenocarcinoma (LUAD) with cancer prognosis was investigated, and 5 feature genes were identified eventually. Specifically, we firstly downloaded the LUAD-related mRNA expression profile (including 57 normal tissue samples and 464 LUAD tissue samples) and Methy450 expression data (including 32 normal tissue samples and 373 LUAD tissue samples) from the TCGA database. The package "limma" was used to screen differentially expressed genes and aberrantly methylated genes, which were intersected for identifying the hypermethylated downregulated genes (DGs Hyper) and the hypomethylated upregulated genes (UGs Hypo). GO annotation and KEGG pathway enrichment analysis were further performed, and it was found that these DGs Hyper and UGs Hypo were predominantly activated in the biological processes and signaling pathways such as the regulation of vasculature development, DNA-binding transcription activator activity, and Ras signaling pathway, indicating that these genes play a vital role in the initiation and progression of LUAD. Additionally, univariate and multivariate Cox regression analyses were conducted to find the genes significantly associated with LUAD prognosis. Five genes including SLC2A1, TNS4, GAPDH, ATP8A2, and CASZ1 were identified, with the former three highly expressed and the latter two poorly expressed in LUAD, indicating poor prognosis of LUAD patients as judged by survival analysis.

Ubiquitin specific peptidase 19 is a prognostic biomarker and affect the proliferation and migration of clear cell renal cell carcinoma

Ubiquitin specific peptidase 19 (USP19) is a member of the USP family and exhibits diverse roles in various biological processes, such as cell differentiation, cell cycle progression and apoptosis. There is limited knowledge regarding the role and impact of USP19 in cancer, particularly clear cell renal cell carcinoma (ccRCC). To examine the function of USP19 in ccRCC, The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus databases were examined to determine USP19 mRNA expression levels. USP19 mRNA levels were significantly lower in ccRCC tissues than in normal tissues. USP19 downregulation was associated with ccRCC progression and poor prognostic outcomes in TCGA cohort. Furthermore, the functional involvement of USP19 in ccRCC was examined using Cell Counting Kit-8, soft agar, Transwell and wound healing assays in vitro following overexpression or knockdown of USP19 in the Caki-1 cell line. USP19 overexpression inhibited ccRCC proliferation and migration, whereas USP19 knockdown promoted ccRCC proliferation and migration in vitro. Consistent with these results, it was further demonstrated that USP19 downregulation promoted tumor growth in vivo in a xenograft model. Mechanistically, it was found that USP19 exerted its inhibitory effect on ccRCC proliferation and migration by suppressing the activation of ERK. Collectively, the present findings identified a role for USP19 as a tumor suppressor in ccRCC and demonstrated that USP19 is a potential prognostic biomarker that could be applied in ccRCC therapy.

Comprehensive analysis of gene expression and DNA methylation for human nasopharyngeal carcinoma

PURPOSE

Nasopharyngeal carcinoma (NPC) is one of the most malignant head and neck carcinomas with unique epidemiological features. In this study, we aimed to identify the novel NPC-related genes and biological pathways, shedding light on the potential molecular mechanisms of NPC.

METHODS

Based on Gene Expression Omnibus (GEO) database, an integrated analysis of microarrays studies was performed to identify differentially expressed genes (DEGs) and differentially methylated genes (DMGs) in NPC compared to normal control. The genes which were both differentially expressed and differentially methylated were identified. Functional annotation and protein-protein interaction (PPI) network construction were used to uncover biological functions of DEGs.

RESULTS

Two DNA methylation and five gene expression datasets were incorporated. A total of 1074 genes were up-regulated and 939 genes were down-regulated in NPC were identified. A total of 719 differential methylation CpG sites (DMCs) including 1 hypermethylated sites and 718 hypomethylated sites were identified. Among which, 11 genes were both DEGs and DMGs in NPC. Pathways in cancer, p53 signaling pathway and Epstein-Barr virus infection were three pathways significantly enriched pathways in DEmRNAs of NPC. The PPI network of top 50 DEGs were consisted of 191 nodes and 191 edges.

CONCLUSIONS

Our study was helpful to elucidate the underlying mechanism of NPC and provide clues for therapeutic methods.

Genome-Wide Analysis of Lung Adenocarcinoma Identifies Novel Prognostic Factors and a Prognostic Score

Background and Objective

Lung adenocarcinoma (LUAD) is the most common histological type of all lung cancers and is associated with genetic and epigenetic aberrations. The tumor, node, and metastasis (TNM) stage is the most authoritative indicator of the clinical outcome in LUAD patients in current clinical practice. In this study, we attempted to identify novel genetic and epigenetic modifications and integrate them as a predictor of the prognosis for LUAD, to supplement the TNM stage with additional information.

Methods

A dataset of 445 patients with LUAD was obtained from The Cancer Genome Atlas database. Both genetic and epigenetic aberrations were screened for their prognostic impact on overall survival (OS). A prognostic score (PS) integrating all the candidate prognostic factors was then developed and its prognostic value validated.

Results

A total of two micro-RNAs, two mRNAs and two DNA methylation sites were identified as prognostic factors associated with OS. The low- and high-risk patient groups, divided by their PS level, showed significantly different OS (p < 0.001) and recurrence-free survival (RFS; p = 0.005). Patients in the early stages (stages I/II) and advanced stages (stages III/IV) of LUAD could be further subdivided by PS into four subgroups. PS remained efficient in stratifying patients into different OS (p < 0.001) and RFS (p = 0.005) when the low- and high-risk subgroups were in the early stages of the disease. However, there was only a significant difference in OS (p = 0.04) but not RFS (p = 0.2), between the low-risk and high-risk subgroups when both were in advanced stages.

Conclusion

PS, in combination with the TNM stage, provides additional precision in stratifying patients with significantly different OS and RFS prognoses. Further studies are warranted to assess the efficiency of PS and to explain the effects of the genetic and epigenetic aberrations observed in LUAD.

DNA hypomethylation-related overexpression of SFN, GORASP2 and ZYG11A is a novel prognostic biomarker for early stage lung adenocarcinoma

Although alteration of DNA methylation in advanced cancer has been extensively investigated, few data for early-stage lung adenocarcinoma are available. Here, we compared DNA methylation profiles between adenocarcinoma in situ (AIS) and early invasive adenocarcinoma using the Infinium methylation array to investigate methylation abnormalities causing early progression of adenocarcinomas. We focused on differentially methylated sites which were located in promoter CpG islands or shore regions, and identified 579 hypermethylated sites and 23 hypomethylated sites in early invasive adenocarcinoma relative to AIS and normal lung. These hypermethylated genes were significantly associated with neuronal pathways such as the GABA receptor and serotonin signaling pathways. Among the hypomethylated genes, we found that GORASP2, ZYG11A, and SFN had significantly lower methylation rates at the shore regions and significantly higher protein expression in invasive adenocarcinoma. Moreover, overexpression of those proteins was strongly associated with patient’s poor outcome. Despite DNA demethylation at the promoter region might be rare relative to DNA hypermethylation, we identified 2 new genes, GORASP2 and ZYG11A, which show hypomethylation and overexpression in invasive adenocarcinoma, suggesting that they have important functions in tumor cells. These genes may be clinically applicable as prognostic indicators and could be potential novel target molecules for drug development.

Aberrant CpG-methylation affects genes expression predicting survival in lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a common diagnosed disease with high-mortality rate, and its prognostic implications are under discovered. DNA methylation aberrations are not only an important event for dysregulation of gene expression during tumorigenesis but also a revolution in epigenetics by identifying key prognostic biomarkers for multiple cancers. In this study, we analyzed methylation status of 485 578 CpG sites and RNA-seq transcriptomes of 20 532 genes for 1095 LUAD samples in TCGA database. The association between DNA methylation and the prognostic value of the corresponding gene expression was identified as well. In total, ten aberrantly methylated and dysregulated genes (AURKA, BLK, CNTN2, HMGA1, PTTG1, TNS4, DAPK2, MFSD2A, THSD1, and WNT7A) were highlighted which were significantly correlated with overall survival of 492 LUAD patients, which were all reported as tumor-associated genes in other various cancers and worthy of further investigated and might be used as therapeutic targets for LUAD. Together, methylation aberrances regulate gene expression level during tumorigenesis and influence prognosis of LUAD patients. Integrating knowledge of epigenetics and expression of genes can be useful for an in-depth understanding of cancer mechanism and for the eventual purpose of precisely prognostic and therapeutic target verification.