scholarly journals Identification of a novel prognostic DNA methylation signature for lung adenocarcinoma based on consensus clustering method

2020 ◽  
Vol 9 (20) ◽  
pp. 7488-7502
Author(s):  
Qidong Cai ◽  
Boxue He ◽  
Hui Xie ◽  
Pengfei Zhang ◽  
Xiong Peng ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Lung Adenocarcinoma ◽  
Consensus Clustering ◽  
Clustering Method

scholarly journals DNA Methylation Based Molecular Subtypes Predict Prognosis in Breast Cancer Patients

2021 ◽  
Vol 28 ◽  
pp. 107327482098851
Author(s):  
Zeng-Hong Wu ◽  
Yun Tang ◽  
Yan Zhou
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Molecular Subtypes ◽  
Methylation Status ◽  
The Cancer Genome Atlas ◽  
Training Dataset ◽  
Consensus Clustering ◽  
Breast Cancer Patients ◽  
Cancer Subtypes ◽  
Novel Biomarkers

Background: Epigenetic changes are tightly linked to tumorigenesis development and malignant transformation’ However, DNA methylation occurs earlier and is constant during tumorigenesis. It plays an important role in controlling gene expression in cancer cells. Methods: In this study, we determining the prognostic value of molecular subtypes based on DNA methylation status in breast cancer samples obtained from The Cancer Genome Atlas database (TCGA). Results: Seven clusters and 204 corresponding promoter genes were identified based on consensus clustering using 166 CpG sites that significantly influenced survival outcomes. The overall survival (OS) analysis showed a significant prognostic difference among the 7 groups (p<0.05). Finally, a prognostic model was used to estimate the results of patients on the testing set based on the classification findings of a training dataset DNA methylation subgroups. Conclusions: The model was found to be important in the identification of novel biomarkers and could be of help to patients with different breast cancer subtypes when predicting prognosis, clinical diagnosis and management.

DNA Methylation-Mediated Low Expression of CFTR Stimulates the Progression of Lung Adenocarcinoma

2021 ◽  
Author(s):  
Yue Wang ◽  
Lu Tang ◽  
Liangliang Yang ◽  
Peiyun Lv ◽  
Shixiong Mai ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Lung Adenocarcinoma ◽  
Low Expression

scholarly journals P2-017: DNA Methylation Changes in Developing Lung Adenocarcinoma

2007 ◽  
Vol 2 (8) ◽  
pp. S488
Author(s):  
Janice S. Galler ◽  
Keith M. Kerr ◽  
Ite A. Laird-Offringa
Keyword(s):  
Dna Methylation ◽  
Lung Adenocarcinoma

scholarly journals Advanced Glycation End Products Receptor DNA Methylation Is Associated with Immune Infiltration and Prognosis of Lung adenocarcinoma and lung squamous cell carcinoma

2021 ◽  
Author(s):  
Jun Yang ◽  
Xiaohui Chen ◽  
Mingqiang Lin ◽  
Mengyan Zhang ◽  
Zhiping Wang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Squamous Cell Carcinoma ◽  
Lung Adenocarcinoma ◽  
Cell Carcinoma ◽  
Squamous Cell ◽  
Advanced Glycation End Products ◽  
Lung Squamous Cell Carcinoma ◽  
Advanced Glycation ◽  
Glycation End Products ◽  
End Products

Abstract Background: Lung cancer has become the leading cause of cancer-related deaths worldwide with a rising trend of incidence and mortality. Lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) account for the major numbers, which should be paid enough attention. Advanced glycation end products receptor (AGER) is a multi-ligand receptor that interacts with a wide range of ligands. Previous studies have shown that abnormal AGER expression is closely related to immune infiltration and tumorigenesis. Nevertheless, the AGER DNA methylation relationship between prognosis and infiltrating immune cells in LUAD and LUSC is still unclear. Results: Compared with the normal lung tissues, the expression level of AGER was significantly reduced in LUAD and LUSC. Low expression of AGER was markedly correlated with histology, stage, lymph node metastasis and Tumor protein 53 (TP53) mutation and could be used as a potential indicator of poor prognosis of LUAD and LUSC. Further analysis showed that copy number variation (CNV), mutation and DNA methylation involved in the low level of AGER. Additionally, we found that AGER DNA hypermethylation meant a worse prognosis in LUAD and LUSC. In addition, we also found that hypermethylated AGER was significantly correlated with tumor infiltrating lymphocytes. Conclusion: AGER may be a candidate for the prognostic biomarker of LUAD and LUSC related with tumor immune microenvironment.

scholarly journals Identification of Immune-Related Biomarkers for Sciatica in Peripheral Blood

2021 ◽  
Vol 12 ◽  
Author(s):  
Xin Jin ◽  
Jun Wang ◽  
Lina Ge ◽  
Qing Hu
Keyword(s):  
Peripheral Blood ◽  
Training Model ◽  
Gene Signature ◽  
Training Dataset ◽  
Support Vector ◽  
Consensus Clustering ◽  
Related Gene ◽  
Clustering Method ◽  
Immune Related Gene ◽  
Immune Related Genes

Objective: Sciatica pertains to neuropathic pain that has been associated with inflammatory response. We aimed to identify significant immune-related biomarkers for sciatica in peripheral blood.Methods: We utilized the GSE150408 expression profiling data from the Gene Expression Omnibus (GEO) database as the training dataset and extracted immune-related genes for further analysis. Differentially expressed immune-related genes (DEIRGs) between healthy controls and patients with sciatica were selected using the “limma” package and verified in clinical specimens by quantitative reverse transcription PCR (RT-qPCR). A diagnostic immune-related gene signature was established using the training model and random forest (RF), generalized linear model (GLM), and support vector machine (SVM) models. Sciatica patient subtypes were identified using the consensus clustering method.Results: Thirteen significant DEIRGs were acquired, of which five (CRP, EREG, FAM19A4, RLN1, and WFIKKN1) were selected to establish a diagnostic immune-related gene signature according to the most appropriate training model, namely, the RF model. A clinical application nomogram model was established based on the expression level of the five DEIRGs. The sciatica patients were divided into two subtypes (C1 and C2) according to the consensus clustering method.Conclusions: Our research established a diagnostic five immune-related gene signature to discriminate sciatica and identified two sciatica subtypes, which may be beneficial to the clinical diagnosis and treatment of sciatica.

scholarly journals EGFR DNA Methylation Correlates With EGFR Expression, Immune Cell Infiltration, and Overall Survival in Lung Adenocarcinoma

2021 ◽  
Vol 11 ◽  
Author(s):  
Zhanyu Xu ◽  
Fanglu Qin ◽  
Liqiang Yuan ◽  
Jiangbo Wei ◽  
Yu Sun ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Protein Expression ◽  
Lung Adenocarcinoma ◽  
Methylation Level ◽  
Promoter Region ◽  
Body Region ◽  
Gene Body ◽  
Immune Infiltration ◽  
Cpg Sites ◽  
Gene Body Region

BackgroundThe epidermal growth factor receptor (EGFR) is a primary target of molecular targeted therapy for lung adenocarcinoma (LUAD). The mechanisms that lead to epigenetic abnormalities of EGFR in LUAD are still unclear. The purpose of our study was to evaluate the abnormal methylation of EGFR CpG sites as potential biomarkers for LUAD.MethodsTo assess the differentially methylation CpG sites of EGFR in LUAD, we used an integrative study of Illumina HumanMethylation450K and RNA-seq data from The Cancer Genome Atlas (TCGA). We evaluated and compared EGFR multiple-omics data to explore the role of CpG sites located in EGFR promoter regions and gene body regions and the association with transcripts, protein expression levels, mutations, and somatic copy number variation. We calculated the correlation coefficients between CpG sites of EGFR and immune infiltration fraction (by MCPcounter and ESTIMATE) and immune-related pathways in LUAD. Finally, we validated the differential methylation of clinically and prognostically relevant CpG sites using quantitative methylation-specific PCR (qMSP).ResultsWe found that the methylation level of many EGFR CpGs in the promoter region was negatively correlated with the transcription level, protein expression, and SCNV, while the methylation at the gene body region was positively correlated with these features. The methylation level of EGFR CpGs in the promoter region was positively correlated with the level of immune infiltration and IFN-γ signature, while the opposite was found for methylation of the gene body region. The qMSP results showed that cg02316066 had a high methylation level, while cg02166842 had a low methylation level in LUAD. There was a high degree of co-methylation between cg02316066 and cg03046247.ConclusionOur data indicate that EGFR is an epigenetic regulator in LUAD acting through DNA methylation. Our research provides a theoretical basis for the further detection of EGFR DNA methylation as a predictive biomarker for LUAD survival and immunotherapy.

EPCO-32. IDENTIFICATION OF PROGNOSTIC CHORDOMA SUBGROUPS USING DNA METHYLATION SIGNATURES IN TISSUE AND PLASMA

2021 ◽  
Vol 23 (Supplement_6) ◽  
pp. vi9-vi9
Author(s):  
Jeffrey Zuccato ◽  
Vikas Patil ◽  
Sheila Mansouri ◽  
Jeffrey Liu ◽  
Farshad Nassiri ◽  
...  
Keyword(s):  
Dna Methylation ◽  
High Throughput Sequencing ◽  
Linear Models ◽  
Immune Cell ◽  
Spinal Metastases ◽  
Treatment Decision ◽  
Cell Interaction ◽  
Patient Treatment ◽  
Consensus Clustering ◽  
Treatment Decision Making

Abstract BACKGROUND Chordomas are malignant bone cancers arising from the skull-base and spine that are rare but cause devastating central nervous system morbidities. Survival is highly variable despite surgery and radiotherapy as 10% live under 1 year and 30-35% survive over 20 years. There are currently no reliable prognostic factors and this limits our ability to tailor patient treatment to their risk. Accordingly, this work identifies epigenetic prognostic chordoma subgroups that are detectable non-invasively through plasma methylomes to guide treatment. METHODS A total of 68 chordoma surgical specimens resected between 1996-2018 across three international centres underwent DNA methylation profiling. Cell-free methylated tumor DNA immunoprecipitation and high-throughput sequencing was performed on available matched plasma samples. RESULTS Two stable tumor clusters were identified through consensus clustering of tissue methylation data. Clusters had statistically significantly different disease-specific survivals (log-rank p=0.0062) independent of clinical factors in a multivariable Cox analysis (HR=16.5, 95%CI: 2.8-96, p=0.0018). The poorer-performing “Immune-infiltrated” cluster had genes hypomethylated at promoters, typically resulting in transcription, within immune-related pathways and higher immune cell abundance within tumors. The better-performing “Cellular” cluster showed higher tumor cellularity plus cell-to-cell interaction and extracellular matrix pathway hypomethylation. Fifty chordoma-versus-other binomial generalized linear models built using plasma methylome data distinguished chordomas from meningiomas and spinal metastases, as representative clinical differential diagnoses, in random left-out 20% testing sets (mean AUROC=0.84, 95%CI: 0.52-1.00). Plasma-based methylation signatures were highly correlated with tissue-based signals within both poor-performing (median r=0.69, 95%CI: 0.66-0.72) and better-performing cluster tumors (median r=0.67, 95%CI: 0.62-0.72). CONCLUSIONS The first identification of two distinct prognostic epigenetic chordoma subgroups is shown here with “Immune-infiltrated” tumors having a poorer prognosis than “Cellular” tumors. Plasma methylomes can be utilized for non-invasive chordoma diagnosis and subtyping. This work may transform chordoma treatment decision-making by guiding surgical planning in advance to match resection aggressiveness with patient prognosis.

scholarly journals From tobacco smoking to cancer mutational signature: a mediation analysis strategy to explore the role of epigenetic changes

BMC Cancer ◽  
2020 ◽  
Vol 20 (1) ◽  
Author(s):  
Zhishan Chen ◽  
Wanqing Wen ◽  
Qiuyin Cai ◽  
Jirong Long ◽  
Ying Wang ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Lung Adenocarcinoma ◽  
Tobacco Smoking ◽  
Mediation Analysis ◽  
Target Genes ◽  
Cancer Genome ◽  
Gene Expressions ◽  
Mutational Signature ◽  
Tumor Tissues ◽  
Dna Methylations

Abstract Background Tobacco smoking is associated with a unique mutational signature in the human cancer genome. It is unclear whether tobacco smoking-altered DNA methylations and gene expressions affect smoking-related mutational signature. Methods We systematically analyzed the smoking-related DNA methylation sites reported from five previous casecontrol studies in peripheral blood cells to identify possible target genes. Using the mediation analysis approach, we evaluated whether the association of tobacco smoking with mutational signature is mediated through altered DNA methylation and expression of these target genes in lung adenocarcinoma tumor tissues. Results Based on data obtained from 21,108 blood samples, we identified 374 smoking-related DNA methylation sites, annotated to 248 target genes. Using data from DNA methylations, gene expressions and smoking-related mutational signature generated from ~ 7700 tumor tissue samples across 26 cancer types from The Cancer Genome Atlas (TCGA), we found 11 of the 248 target genes whose expressions were associated with smoking-related mutational signature at a Bonferroni-correction P < 0.001. This included four for head and neck cancer, and seven for lung adenocarcinoma. In lung adenocarcinoma, our results showed that smoking increased the expression of three genes, AHRR, GPR15, and HDGF, and decreased the expression of two genes, CAPN8, and RPS6KA1, which were consequently associated with increased smoking-related mutational signature. Additional evidence showed that the elevated expression of AHRR and GPR15 were associated with smoking-altered hypomethylations at cg14817490 and cg19859270, respectively, in lung adenocarcinoma tumor tissues. Lastly, we showed that decreased expression of RPS6KA1, were associated with poor survival of lung cancer patients. Conclusions Our findings provide novel insight into the contributions of tobacco smoking to carcinogenesis through the underlying mechanisms of the elevated mutational signature by altered DNA methylations and gene expressions.

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