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Hajebi Khaniki S, Shokoohi F, Esmaily H, Kerachian MA. Analyzing aberrant DNA methylation in colorectal cancer uncovered intangible heterogeneity of gene effects in the survival time of patients. Sci Rep 2023; 13:22104. [PMID: 38092774 PMCID: PMC10719305 DOI: 10.1038/s41598-023-47377-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 11/13/2023] [Indexed: 12/17/2023] Open
Abstract
Colorectal cancer (CRC) involves epigenetic alterations. Irregular gene-methylation alteration causes and advances CRC tumor growth. Detecting differentially methylated genes (DMGs) in CRC and patient survival time paves the way to early cancer detection and prognosis. However, CRC data including survival times are heterogeneous. Almost all studies tend to ignore the heterogeneity of DMG effects on survival. To this end, we utilized a sparse estimation method in the finite mixture of accelerated failure time (AFT) regression models to capture such heterogeneity. We analyzed a dataset of CRC and normal colon tissues and identified 3406 DMGs. Analysis of overlapped DMGs with several Gene Expression Omnibus datasets led to 917 hypo- and 654 hyper-methylated DMGs. CRC pathways were revealed via gene ontology enrichment. Hub genes were selected based on Protein-Protein-Interaction network including SEMA7A, GATA4, LHX2, SOST, and CTLA4, regulating the Wnt signaling pathway. The relationship between identified DMGs/hub genes and patient survival time uncovered a two-component mixture of AFT regression model. The genes NMNAT2, ZFP42, NPAS2, MYLK3, NUDT13, KIRREL3, and FKBP6 and hub genes SOST, NFATC1, and TLE4 were associated with survival time in the most aggressive form of the disease that can serve as potential diagnostic targets for early CRC detection.
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Affiliation(s)
- Saeedeh Hajebi Khaniki
- Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran
- Department of Mathematical Sciences, University of Nevada Las Vegas, Las Vegas, NV, 89154, USA
| | - Farhad Shokoohi
- Department of Mathematical Sciences, University of Nevada Las Vegas, Las Vegas, NV, 89154, USA.
| | - Habibollah Esmaily
- Department of Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran
- Social Determinants of Health Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
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Hong J, Rhee JK. Genomic Effect of DNA Methylation on Gene Expression in Colorectal Cancer. Biology 2022; 11:biology11101388. [PMID: 36290295 PMCID: PMC9598958 DOI: 10.3390/biology11101388] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Revised: 09/16/2022] [Accepted: 09/20/2022] [Indexed: 11/25/2022]
Abstract
Simple Summary Abnormal DNA methylation is known to regulate gene expression, and its features have been frequently observed in colorectal cancer (CRC) patients. In addition, alterations in DNA methylation can be proposed as biomarkers for cancer prognosis, as they occur in the early stage of carcinogenesis. Although numerous studies have attempted to shed light on the impacts of DNA methylation on gene expression, it is still unclear which specific regions regulate gene expression and how they are associated with patient survival. In this study, we elucidated the intricate relationship between DNA methylation and gene expression. Furthermore, we found genes that were influenced by DNA methylation and were associated with survival; these genes were mainly enriched in immune-related pathways. Abstract The aberrant expression of cancer-related genes can lead to colorectal cancer (CRC) carcinogenesis, and DNA methylation is one of the causes of abnormal expression. Although many studies have been conducted to reveal how DNA methylation affects transcription regulation, the ways in which it modulates gene expression and the regions that significantly affect DNA methylation-mediated gene regulation remain unclear. In this study, we investigated how DNA methylation in specific genomic areas can influence gene expression. Several regression models were constructed for gene expression prediction based on DNA methylation. Among these models, ElasticNet, which had the best performance, was chosen for further analysis. DNA methylation near transcription start sites (TSS), especially from 2 kb upstream to 7 kb downstream of TSS, had an essential regulatory role in gene expression. Moreover, methylation-affected and survival-associated genes were compiled and found to be mainly enriched in immune-related pathways. This study investigated genomic regions in which methylation changes can affect gene expression. In addition, this study proposed that aberrantly expressed genes due to DNA methylation can lead to CRC pathogenesis by the immune system.
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Cao L, Ma X, Rong P, Zhang J, Yang M, Wang W, Mi Y. Comprehensive Analysis of DNA Methylation and Transcriptome to Identify PD-1-Negative Prognostic Methylated Signature in Endometrial Carcinoma. Disease Markers 2022; 2022:1-24. [PMID: 35634444 PMCID: PMC9133896 DOI: 10.1155/2022/3085289] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Revised: 04/15/2022] [Accepted: 04/25/2022] [Indexed: 11/23/2022]
Abstract
Background Epigenetic mechanism plays an important role in endometrial carcinoma (EC). This study was designed to analyze the epigenetic mechanism between DNA methylation-driven genes (DEDGs) and drugs targeting DEDGs and to develop a DEDG score model for predicting the prognosis of EC. Methods Expression profile and methylation profile data of PD-1-negative EC samples were obtained from TCGA. To obtain intersected DEDGs, differentially expressed genes (DEGs) and differentially methylated genes from tumor tissues and normal tissues were analyzed by limma. A linear discriminant classification model was constructed using the gene expression profile of DMDGs, methylation profile of TSS1500, TSS200, and gene body regions. Principal component analysis (PCA) and ROC analysis were conducted. The protein-drug interactions analysis of DMDGs was performed using Network Analyst 3.0 tool. Lasso Cox regression analysis was used to screen prognostic DNA methylation driving gene and to build a risk score model. The ROC curve and Kaplan-Meier survival curve were plotted to evaluate the model prediction capability. Results A total of 96 DMDGs were screened from the three regions, distributed on 22 chromosomes, with consistent methylation patterns in different gene regions. Both the expression profile and methylation profile of the three regions can neatly distinguish tumor samples from normal ones, with a high classifying performance. A gene signature, which consisted of ELFN1-AS1 and ZNF132, could classify EC patients into a high-risk group and low-risk group. Prognosis of the high-risk group was significantly worse than that of the low-risk group. The risk model showed a high performance in predicting the prognosis of EC. Conclusion We successfully established a risk score system with two DMDGs, which showed a high prediction accuracy of EC prognosis.
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Aziz S, Rasheed F, Zahra R, König S. Gastric Cancer Pre-Stage Detection and Early Diagnosis of Gastritis Using Serum Protein Signatures. Molecules 2022; 27:molecules27092857. [PMID: 35566209 PMCID: PMC9099457 DOI: 10.3390/molecules27092857] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 04/22/2022] [Accepted: 04/27/2022] [Indexed: 02/04/2023] Open
Abstract
Background: A gastric cancer (GC) diagnosis relies on histopathology. Endoscopy rates are increasing. Helicobacter pylori infection is a major GC risk factor. In an effort to elucidate abundant blood biomarkers, and potentially reduce the number of diagnostic surgical interventions, we investigated sera and biopsies from a cohort of 219 H. pylori positive and negative patients diagnosed with GC, gastritis, and ulcers. This allowed the comparative investigation of the different gastroduodenal diseases, and the exclusion of protein changes resulting from bacterial infection or inflammation of the gastric mucosa when searching for GC-dependent proteins. Methods: High-definition mass spectrometry-based expression analysis of tryptically digested proteins was performed, followed by multivariate statistical and network analyses for the different disease groups, with respect to H. pylori infection status. Significantly regulated proteins differing more than two-fold between groups were shortlisted, and their role in gastritis and GC discussed. Results: We present data of comparative protein analyses of biopsies and sera from patients suffering from mild to advanced gastritis, ulcers, and early to advanced GC, in conjunction with a wealth of metadata, clinical information, histopathological evaluation, and H. pylori infection status. We used samples from pre-malignant stages to extract prospective serum markers for early-stage GC, and present a 29-protein marker panel containing, amongst others, integrin β-6 and glutathione peroxidase. Furthermore, ten serum markers specific for advanced GC, independent of H. pylori infection, are provided. They include CRP, protein S100A9, and kallistatin. The majority of these proteins were previously discussed in the context of cancer or GC. In addition, we detected hypoalbuminemia and increased fibrinogen serum levels in gastritis. Conclusion: Two protein panels were suggested for the development of multiplex tests for GC serum diagnostics. For most of the elements contained in these panels, individual commercial tests are available. Thus, we envision the design of multi-protein assays, incorporating several to all of the panel members, in order to gain a level of specificity that cannot be achieved by testing a single protein alone. As their development and validation will take time, gastritis diagnosis based on the fibrinogen to albumin serum ratio may be a quick way forward. Its determination at the primary/secondary care level for early diagnosis could significantly reduce the number of referrals to endoscopy. Preventive measures are in high demand. The protein marker panels presented in this work will contribute to improved GC diagnostics, once they have been transferred from a research result to a practical tool.
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Affiliation(s)
- Shahid Aziz
- BreathMAT Lab, Pakistan Institute of Nuclear Science and Technology (PINSTEC), Islamabad 44000, Pakistan; (S.A.); (F.R.)
- Department of Microbiology, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan;
- IZKF Core Unit Proteomics, University of Münster, 48149 Münster, Germany
| | - Faisal Rasheed
- BreathMAT Lab, Pakistan Institute of Nuclear Science and Technology (PINSTEC), Islamabad 44000, Pakistan; (S.A.); (F.R.)
| | - Rabaab Zahra
- Department of Microbiology, Faculty of Biological Sciences, Quaid-i-Azam University, Islamabad 45320, Pakistan;
| | - Simone König
- IZKF Core Unit Proteomics, University of Münster, 48149 Münster, Germany
- Correspondence:
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Jia C, Ma Y, Wang M, Liu W, Tang F, Chen J. Evidence of Omics, Immune Infiltration, and Pharmacogenomics for BATF in a Pan-Cancer Cohort. Front Mol Biosci 2022; 9:844721. [PMID: 35573731 PMCID: PMC9098817 DOI: 10.3389/fmolb.2022.844721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2021] [Accepted: 03/29/2022] [Indexed: 11/18/2022] Open
Abstract
Background: Cytotoxic CD8+ T-cell exhaustion is the major barrier for immunotherapy in tumors. Recent studies have reported that the basic leucine zipper activating transcription factor–like transcription factor (BATF) is responsible for countering cytotoxic CD8+ T-cell exhaustion. Nevertheless, the expression and roles of BATF in tumors have been poorly explored. Methods: In the present study, we conducted a multi-omics analysis, including gene expression, methylation status, DNA alterations, pharmacogenomics, and survival status based on data from the Cancer Genome Atlas (TCGA) database to discern expression patterns and prognostic roles of BATF in tumors. We also explored potential roles of BATF in a pan-cancer cohort by performing immune infiltration, Gene Ontology (GO) enrichment, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. In vitro assay was also performed to explore roles of BATF in tumor cells. Results: We found that BATF was aberrantly upregulated in 27 types of tumors with respect to the corresponding normal tissues. Abnormal BATF expression in tumors predicted survival times of patients in a tissue-dependent manner. The results of GO, immune infiltration, and KEGG analysis revealed that increased BATF expression in tumors participated in modulating immune cell infiltration via immune-related pathways. BATF expression could also predict immunotherapeutic and chemotherapy responses in cancers. Moreover, knockdown of BATF suppresses tumor cell viability. Conclusion: Our present study reports the vital roles of BATF in tumors and provides a theoretical basis for targeting BATF therapy.
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Wang Z, Huang Y, Chu F, Liao K, Cui Z, Chen J, Tang S. Integrated Analysis of DNA methylation and transcriptome profile to identify key features of age-related macular degeneration. Bioengineered 2021; 12:7061-7078. [PMID: 34569899 PMCID: PMC8806579 DOI: 10.1080/21655979.2021.1976502] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Age-related macular degeneration (AMD) is a common vision-threatening disease. The current study sought to integrate DNA methylation with transcriptome profile to explore key features in AMD. Gene expression data were obtained from the Gene Expression Omnibus (GEO, accession ID: GSE135092) and DNA methylation data were obtained from the ArrayExpress repository (E-MTAB-7183). A total of 456 differentially expressed genes (DEGs) and 4827 intragenic differentially methylated CpGs (DMCs) were identified between AMD and controls. DEGs and DMCs were intersected and 19 epigenetically induced (EI) genes and 15 epigenetically suppressed (ES) genes were identified. Immune cell infiltration analysis was performed to estimate the abundance of different types of immune cell in each sample. Enrichment scores of inflammatory response and tumor necrosis factor-alpha (TNFα) signaling via nuclear factor kappa B (NF-κb) were positively correlated with abundance of activated memory CD4 T cells and M1 macrophages. Subsequently, two significant random forest classifiers were constructed based on DNA methylation and transcriptome data. SMAD2 and NGFR were selected as key genes through functional epigenetic modules (FEM) analysis. Expression level of SMAD2, NGFR and their integrating proteins was validated in hydrogen peroxide (H2O2) and TNFα co-treated retinal pigment epithelium (RPE) in vitro. The findings of the current study showed that local inflammation and systemic inflammatory host response play key roles in pathogenesis of AMD. SMAD2 and NGFR provide new insight in understanding the molecular mechanism and are potential therapeutic targets for development of AMD therapy.
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Affiliation(s)
- Zhijie Wang
- Aier School of Ophthalmology, Central South University, Changsha, China.,Aier Eye Institute, Changsha, China
| | - Yinhua Huang
- Aier School of Ophthalmology, Central South University, Changsha, China.,Aier Eye Institute, Changsha, China
| | - Feixue Chu
- Hangzhou Xihu Zhijiang Eye Hospital, Hangzhou, China
| | - Kai Liao
- Aier School of Ophthalmology, Central South University, Changsha, China.,Aier Eye Institute, Changsha, China
| | | | - Jiansu Chen
- Aier School of Ophthalmology, Central South University, Changsha, China.,Aier Eye Institute, Changsha, China.,Key Laboratory for Regenerative Medicine, Ministry of Education, Jinan University, Guangzhou, China.,Institute of Ophthalmology, Medical College, Jinan University, Guangzhou, China
| | - Shibo Tang
- Aier School of Ophthalmology, Central South University, Changsha, China.,Aier Eye Institute, Changsha, China.,Cas Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
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