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Menadi S, Kucuk B, Cacan E. Promoter Hypomethylation Upregulates ANXA2 Expression in Pancreatic Cancer and is Associated with Poor Prognosis. Biochem Genet 2024; 62:2721-2742. [PMID: 38001391 DOI: 10.1007/s10528-023-10577-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2022] [Accepted: 10/26/2023] [Indexed: 11/26/2023]
Abstract
Pancreatic cancer (PC) is one of the world's most aggressive and deadly cancers, owing to non-specific early clinical symptoms, late-stage diagnosis, and poor survival. Therefore, it is critical to identify specific biomarkers for its early diagnosis. Annexin A2 (ANXA2) is a calcium-dependent phospholipid-binding protein that has been reported to be upregulated in several cancer types, making it an emerging biomarker and potential cancer therapeutic target. However, the mechanism underlying the regulation of ANXA2 overexpression is still unclear. It is well established that genetic and epigenetic alterations may lead to widespread dysregulation of gene expression. Hence, in this study, we focused on exploring the regulatory mechanism of ANXA2 by investigating the transcriptional profile, methylation pattern, somatic mutation, and prognostic value of ANXA2 in PC using several bioinformatics databases. Our results revealed that the expression levels of ANXA2 were remarkably increased in PC tissues comparing to normal tissues. Furthermore, the high expression of ANXA2 was significantly related to the poor prognosis of PC patients. More importantly, we demonstrated for the first time that the ANXA2 promoter is hypomethylated in PC tissues compared to normal tissues which may result in ANXA2 overexpression in PC. However, more experimental research is required to corroborate our findings.
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Affiliation(s)
- Soumaya Menadi
- Department of Molecular Biology and Genetics, Tokat Gaziosmanpasa University, 60250, Tokat, Turkey
| | - Burak Kucuk
- Department of Molecular Biology and Genetics, Tokat Gaziosmanpasa University, 60250, Tokat, Turkey
| | - Ercan Cacan
- Department of Molecular Biology and Genetics, Tokat Gaziosmanpasa University, 60250, Tokat, Turkey.
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2
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Liu A, Dai Y, Mendez EF, Hu R, Fries GR, Najera KE, Jiang S, Meyer TD, Stertz L, Jia P, Walss-Bass C, Zhao Z. Genome-Wide Correlation of DNA Methylation and Gene Expression in Postmortem Brain Tissues of Opioid Use Disorder Patients. Int J Neuropsychopharmacol 2021; 24:879-891. [PMID: 34214162 PMCID: PMC8598308 DOI: 10.1093/ijnp/pyab043] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Revised: 06/01/2021] [Accepted: 06/29/2021] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND Opioid use disorder (OUD) affects millions of people, causing nearly 50 000 deaths annually in the United States. While opioid exposure and OUD are known to cause widespread transcriptomic and epigenetic changes, few studies in human samples have been conducted. Understanding how OUD affects the brain at the molecular level could help decipher disease pathogenesis and shed light on OUD treatment. METHODS We generated genome-wide transcriptomic and DNA methylation profiles of 22 OUD subjects and 19 non-psychiatric controls. We applied weighted gene co-expression network analysis to identify genetic markers consistently associated with OUD at both transcriptomic and methylomic levels. We then performed functional enrichment for biological interpretation. We employed cross-omics analysis to uncover OUD-specific regulatory networks. RESULTS We found 6 OUD-associated co-expression gene modules and 6 co-methylation modules (false discovery rate <0.1). Genes in these modules are involved in astrocyte and glial cell differentiation, gliogenesis, response to organic substance, and response to cytokine (false discovery rate <0.05). Cross-omics analysis revealed immune-related transcription regulators, suggesting the role of transcription factor-targeted regulatory networks in OUD pathogenesis. CONCLUSIONS Our integrative analysis of multi-omics data in OUD postmortem brain samples suggested complex gene regulatory mechanisms involved in OUD-associated expression patterns. Candidate genes and their upstream regulators revealed in astrocyte, and glial cells could provide new insights into OUD treatment development.
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Affiliation(s)
- Andi Liu
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Yulin Dai
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX,USA
| | - Emily F Mendez
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX,USA
| | - Ruifeng Hu
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX,USA
| | - Gabriel R Fries
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX,USA,Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX,USA
| | - Katherine E Najera
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX,USA
| | - Shan Jiang
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX,USA
| | - Thomas D Meyer
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX,USA
| | - Laura Stertz
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX,USA
| | - Peilin Jia
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX,USA
| | - Consuelo Walss-Bass
- Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX,USA,Correspondence: Zhongming Zhao, PhD, Center for Precision Health, School of Biomedical Informatics, University of Texas Health Science Center at Houston, 7000 Fannin St #600, Houston, TX, USA () and Consuelo Walss-Bass, PhD, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA ()
| | - Zhongming Zhao
- Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA,Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX,USA,Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX,USA,MD Anderson Cancer Center UTHealth Graduate School of Biomedical Sciences, Houston, TX, USA,Correspondence: Zhongming Zhao, PhD, Center for Precision Health, School of Biomedical Informatics, University of Texas Health Science Center at Houston, 7000 Fannin St #600, Houston, TX, USA () and Consuelo Walss-Bass, PhD, Louis A. Faillace, MD, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA ()
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Song M, Zhong H. Efficient weighted univariate clustering maps outstanding dysregulated genomic zones in human cancers. Bioinformatics 2021; 36:5027-5036. [PMID: 32619008 PMCID: PMC7755420 DOI: 10.1093/bioinformatics/btaa613] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2019] [Revised: 05/24/2020] [Accepted: 06/26/2020] [Indexed: 12/14/2022] Open
Abstract
Motivation Chromosomal patterning of gene expression in cancer can arise from aneuploidy, genome disorganization or abnormal DNA methylation. To map such patterns, we introduce a weighted univariate clustering algorithm to guarantee linear runtime, optimality and reproducibility. Results We present the chromosome clustering method, establish its optimality and runtime and evaluate its performance. It uses dynamic programming enhanced with an algorithm to reduce search-space in-place to decrease runtime overhead. Using the method, we delineated outstanding genomic zones in 17 human cancer types. We identified strong continuity in dysregulation polarity—dominance by either up- or downregulated genes in a zone—along chromosomes in all cancer types. Significantly polarized dysregulation zones specific to cancer types are found, offering potential diagnostic biomarkers. Unreported previously, a total of 109 loci with conserved dysregulation polarity across cancer types give insights into pan-cancer mechanisms. Efficient chromosomal clustering opens a window to characterize molecular patterns in cancer genome and beyond. Availability and implementation Weighted univariate clustering algorithms are implemented within the R package ‘Ckmeans.1d.dp’ (4.0.0 or above), freely available at https://cran.r-project.org/package=Ckmeans.1d.dp. Supplementary information Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Mingzhou Song
- Department of Computer Science.,Molecular Biology Graduate Program, New Mexico State University, Las Cruces, NM 88003, USA
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Dalgıç E, Konu Ö, Öz ZS, Chan C. Lower connectivity of tumor coexpression networks is not specific to cancer. In Silico Biol 2019; 13:41-53. [PMID: 31156157 PMCID: PMC6597990 DOI: 10.3233/isb-190472] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Global level network analysis of molecular links is necessary for systems level view of complex diseases like cancer. Using genome-wide expression datasets, we constructed and compared gene co-expression based specific networks of pre-cancerous tumors (adenoma) and cancerous tumors (carcinoma) with paired normal networks to assess for any possible changes in network connectivity. Previously, loss of connectivity was reported as a characteristic of cancer samples. Here, we observed that pre-cancerous conditions also had significantly less connections than paired normal samples. We observed a loss of connectivity trend for colorectal adenoma, aldosterone producing adenoma and uterine leiomyoma. We also showed that the loss of connectivity trend is not specific to positive or negative correlation based networks. Differential hub genes, which were the most highly differentially less connected genes in tumor, were mostly different between different datasets. No common gene list could be defined which underlies the lower connectivity of tumor specific networks. Connectivity of colorectal cancer methylation targets was different from other genes. Extracellular space related terms were enriched in negative correlation based differential hubs and common methylation targets of colorectal carcinoma. Our results indicate a systems level change of lower connectivity as cells transform to not only cancer but also pre-cancerous conditions. This systems level behavior could not be attributed to a group of genes.
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Affiliation(s)
- Ertuğrul Dalgıç
- Department of Medical Biology, Zonguldak Bülent Ecevit University School of Medicine, Zonguldak, Turkey
| | - Özlen Konu
- Department of Molecular Biology and Genetics, Bilkent University, Ankara, Turkey
| | - Zehra Safi Öz
- Department of Medical Biology, Zonguldak Bülent Ecevit University School of Medicine, Zonguldak, Turkey
| | - Christina Chan
- Department of Chemical Engineering and Materials Science, Michigan State University, East Lansing, MI, USA
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Gao HL, Wang X, Sun HR, Zhou JD, Lin SQ, Xing YH, Zhu L, Zhou HB, Zhao YS, Chi Q, Liu YP. Methylation Status of Transcriptional Modulatory Genes Associated with Colorectal Cancer in Northeast China. Gut Liver 2018; 12:173-182. [PMID: 29291617 PMCID: PMC5832342 DOI: 10.5009/gnl17163] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/31/2017] [Revised: 05/08/2017] [Accepted: 05/22/2017] [Indexed: 12/13/2022] Open
Abstract
Background/Aims Methylation status plays a causal role in carcinogenesis in targeted tissues. However, the relationship between the DNA methylation status of multiple genes in blood leukocytes and colorectal cancer (CRC) susceptibility as well as interactions between dietary factors and CRC risks are unclear. Methods We performed a case-control study with 466 CRC patients and 507 cancer-free controls to investigate the association among the methylation status of individual genes, multiple CpG site methylation (MCSM), multiple CpG site heterogeneous methylation and CRC susceptibility. Peripheral blood DNA methylation levels were detected by performing methylation-sensitive high-resolution melting. Results Total heterogeneous methylation of CA10 and WT1 conferred a significantly higher risk of CRC (adjusted odds ratio [ORadjusted], 5.445; 95% confidence interval [CI], 3.075 to 9.643; ORadjusted, 1.831; 95% CI, 1.100 to 3.047; respectively). Subjects with high-level MCSM (MCSM-H) status demonstrated a higher risk of CRC (ORadjusted, 4.318; 95% CI, 1.529 to 12.197). Additionally, interactions between the high-level intake of fruit and CRH, WT1, and MCSM on CRC were statistically significant. Conclusions The gene methylation status of blood leukocytes may be associated with CRC risk. MCSM-H of blood leukocytes was associated with CRC, especially in younger people. Some dietary factors may affect hypermethylation status and influence susceptibility to CRC.
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Affiliation(s)
- Han-Lu Gao
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin, China
| | - Xuan Wang
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin, China
| | - Hong-Ru Sun
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin, China
| | - Jun-De Zhou
- Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Shang-Qun Lin
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin, China
| | - Yu-Hang Xing
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin, China
| | - Lin Zhu
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin, China
| | - Hai-Bo Zhou
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin, China
| | - Ya-Shuang Zhao
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin, China
| | - Qiang Chi
- Department of General Surgery, The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Yu-Peng Liu
- Department of Epidemiology, Public Health College, Harbin Medical University, Harbin, China
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Genome-wide DNA methylation analysis reveals molecular subtypes of pancreatic cancer. Oncotarget 2018; 8:28990-29012. [PMID: 28423671 PMCID: PMC5438707 DOI: 10.18632/oncotarget.15993] [Citation(s) in RCA: 60] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2016] [Accepted: 02/12/2017] [Indexed: 12/13/2022] Open
Abstract
Pancreatic cancer (PC) is the fourth leading cause of cancer deaths in the United States with a five-year patient survival rate of only 6%. Early detection and treatment of this disease is hampered due to lack of reliable diagnostic and prognostic markers. Recent studies have shown that dynamic changes in the global DNA methylation and gene expression patterns play key roles in the PC development; hence, provide valuable insights for better understanding the initiation and progression of PC. In the current study, we used DNA methylation, gene expression, copy number, mutational and clinical data from pancreatic patients. We independently investigated the DNA methylation and differential gene expression profiles between normal and tumor samples and correlated methylation levels with gene expression patterns. We observed a total of ~23-thousand differentially methylated CpG sites (Δβ≥0.1) between normal and tumor samples, where majority of the CpG sites are hypermethylated in PC, and this phenomenon is more prominent in the 5′UTRs and promoter regions compared to the gene bodies. Differential methylation is observed in genes associated with the homeobox domain, cell division and differentiation, cytoskeleton, epigenetic regulation and development, pancreatic development and pancreatic signaling and pancreatic cancer core signaling pathways. Correlation analysis suggests that methylation in the promoter region and 5′UTR has mostly negative correlations with gene expression while gene body and 3′UTR associated methylation has positive correlations. Regulatory element analysis suggests that HOX cluster and histone core proteins are upstream regulators of hypomethylation, while SMAD4, STAT4, STAT5B and zinc finger proteins (ZNF) are upstream regulators of hypermethylation. Non-negative matrix factorization (NMF) clustering of differentially methylated sites generated three clusters in PCs suggesting the existence of distinct molecular subtypes. Cluster 1 and cluster 2 showed samples enriched with clinical phenotypes like neoplasm histological grade and pathologic T-stage T3, respectively, while cluster 3 showed the enrichment of samples with neoplasm histological grade G1. To the best of our knowledge, this is the first genome-scale methylome analysis of PC data from TCGA. Our clustering analysis provides a strong basis for future work on the molecular subtyping of epigenetic regulation in pancreatic cancer.
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Cheng F, Hong H, Yang S, Wei Y. Individualized network-based drug repositioning infrastructure for precision oncology in the panomics era. Brief Bioinform 2017; 18:682-697. [PMID: 27296652 DOI: 10.1093/bib/bbw051] [Citation(s) in RCA: 37] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2016] [Indexed: 12/12/2022] Open
Abstract
Advances in next-generation sequencing technologies have generated the data supporting a large volume of somatic alterations in several national and international cancer genome projects, such as The Cancer Genome Atlas and the International Cancer Genome Consortium. These cancer genomics data have facilitated the revolution of a novel oncology drug discovery paradigm from candidate target or gene studies toward targeting clinically relevant driver mutations or molecular features for precision cancer therapy. This focuses on identifying the most appropriately targeted therapy to an individual patient harboring a particularly genetic profile or molecular feature. However, traditional experimental approaches that are used to develop new chemical entities for targeting the clinically relevant driver mutations are costly and high-risk. Drug repositioning, also known as drug repurposing, re-tasking or re-profiling, has been demonstrated as a promising strategy for drug discovery and development. Recently, computational techniques and methods have been proposed for oncology drug repositioning and identifying pharmacogenomics biomarkers, but overall progress remains to be seen. In this review, we focus on introducing new developments and advances of the individualized network-based drug repositioning approaches by targeting the clinically relevant driver events or molecular features derived from cancer panomics data for the development of precision oncology drug therapies (e.g. one-person trials) to fully realize the promise of precision medicine. We discuss several potential challenges (e.g. tumor heterogeneity and cancer subclones) for precision oncology. Finally, we highlight several new directions for the precision oncology drug discovery via biotherapies (e.g. gene therapy and immunotherapy) that target the 'undruggable' cancer genome in the functional genomics era.
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Mallik S, Zhao Z. Towards integrated oncogenic marker recognition through mutual information-based statistically significant feature extraction: an association rule mining based study on cancer expression and methylation profiles. QUANTITATIVE BIOLOGY 2017; 5:302-327. [PMID: 30221015 DOI: 10.1007/s40484-017-0119-0] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Background Marker detection is an important task in complex disease studies. Here we provide an association rule mining (ARM) based approach for identifying integrated markers through mutual information (MI) based statistically significant feature extraction, and apply it to acute myeloid leukemia (AML) and prostate carcinoma (PC) gene expression and methylation profiles. Methods We first collect the genes having both expression and methylation values in AML as well as PC. Next, we run Jarque-Bera normality test on the expression/methylation data to divide the whole dataset into two parts: one that ollows normal distribution and the other that does not follow normal distribution. Thus, we have now four parts of the dataset: normally distributed expression data, normally distributed methylation data, non-normally distributed expression data, and non-normally distributed methylated data. A feature-extraction technique, "mRMR" is then utilized on each part. This results in a list of top-ranked genes. Next, we apply Welch t-test (parametric test) and Shrink t-test (non-parametric test) on the expression/methylation data for the top selected normally distributed genes and non-normally distributed genes, respectively. We then use a recent weighted ARM method, "RANWAR" to combine all/specific resultant genes to generate top oncogenic rules along with respective integrated markers. Finally, we perform literature search as well as KEGG pathway and Gene-Ontology (GO) analyses using Enrichr database for in silico validation of the prioritized oncogenes as the markers and labeling the markers as existing or novel. Results The novel markers of AML are {ABCB11↑∪KRT17↓} (i.e., ABCB11 as up-regulated, & KRT17 as down-regulated), and {AP1S1-∪KRT17↓∪NEIL2-∪DYDC1↓}) (i.e., AP1S1 and NEIL2 both as hypo-methylated, & KRT17 and DYDC1 both as down-regulated). The novel marker of PC is {UBIAD1¶∪APBA2‡∪C4orf31‡} (i.e., UBIAD1 as up-regulated and hypo-methylated, & APBA2 and C4orf31 both as down-regulated and hyper-methylated). Conclusion The identified novel markers might have critical roles in AML as well as PC. The approach can be applied to other complex disease.
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Affiliation(s)
- Saurav Mallik
- Computer Science & Engineering, Aliah University, Newtown, Newtown 700156, India
| | - Zhongming Zhao
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
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Sinha P, Singh K, Sachan M. Heterogeneous pattern of DNA methylation in developmentally important genes correlates with its chromatin conformation. BMC Mol Biol 2017; 18:1. [PMID: 28081716 PMCID: PMC5234095 DOI: 10.1186/s12867-016-0078-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2016] [Accepted: 12/13/2016] [Indexed: 11/13/2022] Open
Abstract
Background DNA methylation is a major epigenetic modification, playing a crucial role in the development and differentiation of higher organisms. DNA methylation is also known to regulate transcription by gene repression. Various developmental genes such as c-mos, HoxB5, Sox11, and Sry show tissue-specific gene expression that was shown to be regulated by promoter DNA methylation. The aim of the present study is to investigate the establishment of chromatin marks (active or repressive) in relation to heterogeneous methylation in the promoter regions of these developmentally important genes. Results Chromatin-immunoprecipitation (ChIP) assays were performed to immuno-precipitate chromatin by antibodies against both active (H3K4me3) and repressive (H3K9me3) chromatin regions. The analysis of ChIP results showed that both the percentage input and fold enrichment of activated chromatin was higher in tissues expressing the respective genes as compared to the tissues not expressing the same set of genes. This was true for all the genes selected for the study (c-mos, HoxB5, Sox11, and Sry). These findings illustrate that inconsistent DNA methylation patterns (sporadic, mosaic and heterogeneous) may also influence gene regulation, thereby resulting in the modulation of chromatin conformation. Conclusions These findings illustrate that various patterns of DNA methylation (asynchronous, mosaic and heterogeneous) correlates with chromatin modification, resulting in the gene regulation.
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Affiliation(s)
- Puja Sinha
- Department of Biotechnology, Motilal Nehru National Institute of Technology, Allahabad, 211004, India
| | - Kiran Singh
- Department of Molecular and Human Genetics, Banaras Hindu University, Varanasi, India
| | - Manisha Sachan
- Department of Biotechnology, Motilal Nehru National Institute of Technology, Allahabad, 211004, India.
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Saito D, Suyama M. Linkage disequilibrium analysis of allelic heterogeneity in DNA methylation. Epigenetics 2016; 10:1093-8. [PMID: 26575360 DOI: 10.1080/15592294.2015.1115176] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022] Open
Abstract
Heterogeneity of DNA methylation status among alleles is observed in various cell types and is involved in epigenetic gene regulation and cancer biology. However, the individual methylation profile within each allele has not yet been examined at the whole-genome level. In the present study, we applied linkage disequilibrium analysis to the DNA methylation data obtained from whole-genome bisulfite sequencing studies in mouse germline and other types of cells. We found that the methylation status of 2 consecutive CpG sites showed deviation from equilibrium frequency toward concordant linkage (both methylated or both unmethylated) in germline cells. In the imprinting loci where methylation of constituent alleles is known, our analysis detected the deviation toward the concordant linkage as expected. In addition, we applied this analysis to the transitional zone between methylated and unmethylated regions and to the cells undergoing epigenetic reprogramming. In both cases, deviation to the concordant-linked alleles was conspicuous, indicating that the methylation pattern is not random but rather concordant within each allele. These results will provide the key to understanding the mechanism underlying allelic heterogeneity.
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Affiliation(s)
- Daisuke Saito
- a Division of Bioinformatics; Medical Institute of Bioregulation; Kyushu University ; Fukuoka , Japan
| | - Mikita Suyama
- a Division of Bioinformatics; Medical Institute of Bioregulation; Kyushu University ; Fukuoka , Japan
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Cheng F, Zhao J, Hanker AB, Brewer MR, Arteaga CL, Zhao Z. Transcriptome- and proteome-oriented identification of dysregulated eIF4G, STAT3, and Hippo pathways altered by PIK3CA H1047R in HER2/ER-positive breast cancer. Breast Cancer Res Treat 2016; 160:457-474. [PMID: 27771839 PMCID: PMC10183099 DOI: 10.1007/s10549-016-4011-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2016] [Accepted: 10/05/2016] [Indexed: 01/25/2023]
Abstract
PURPOSE Phosphatidylinositol 3-kinase (PI3K)/AKT pathway aberrations are common in human breast cancer. Furthermore, PIK3CA mutations are commonly associated with resistance to anti-epidermal growth factor receptor 2 (HER2) or anti-estrogen receptor (ER) agents in HER2 or ER positive (HER2+/ER+) breast cancer. Hence, deciphering the underlying mechanisms of PIK3CA mutations in HER2+/ER+ breast cancer would provide novel insights into elucidating resistance to anti-HER2/ER therapies. METHODS In this study, we systematically investigated the biological consequences of PIK3CA H1047R in HER2+/ER+ breast cancer by uniquely incorporating mRNA transcriptomic data from The Cancer Genome Atlas and proteomic data from reverse-phase protein arrays. RESULTS Our integrative bioinformatics analyses revealed that several important pathways such as STAT3 and VEGF/hypoxia were selectively altered by PIK3CA H1047R in HER2+/ER+ breast cancer. Protein differential expression analysis indicated that an elevated eIF4G might promote tumor angiogenesis and growth via regulation of the hypoxia-activated switch in HER2+ PIK3CA H1047R breast cancer. We observed hypo-phosphorylation of EGFR in HER2+ PIK3CA H1047R breast cancer versus HER2+PIK3CAwild-type (PIK3CA WT). In addition, ER and PIK3CA H1047R might cooperate to activate STAT3, MAPK, AKT, and Hippo pathways in ER+ PIK3CA H1047R breast cancer. A higher YAPpS127 level was observed in ER+ PIK3CA H1047R patients than that in an ER+ PIK3CA WT subgroup. By examining breast cancer cell lines having both microarray gene expression and drug treatment data from the Genomics of Drug Sensitivity in Cancer and the Stand Up to Cancer datasets, we found that the elevated YAP1 mRNA expression was associated with the resistance of BCL-2 family inhibitors, but with the sensitivity to MEK/MAPK inhibitors in breast cancer cells. CONCLUSIONS In summary, these findings shed light on the functional consequences of PIK3CA H1047R-driven breast tumorigenesis and resistance to the existing therapeutic agents in HER2+/ER+ breast cancer.
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Affiliation(s)
- Feixiong Cheng
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37203, USA.,Center for Cancer Systems Biology (CCSB), Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA, 02215, USA.,Center for Complex Networks Research, Northeastern University, Boston, MA, 02115, USA
| | - Junfei Zhao
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37203, USA.,Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Ariella B Hanker
- Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Monica Red Brewer
- Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Carlos L Arteaga
- Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37232, USA. .,Department of Cancer Biology, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37232, USA. .,Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
| | - Zhongming Zhao
- Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN, 37203, USA. .,Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA. .,Department of Cancer Biology, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37232, USA. .,Breast Cancer Research Program, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, 37232, USA.
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Sokolova V, Crippa E, Gariboldi M. Integration of genome scale data for identifying new players in colorectal cancer. World J Gastroenterol 2016; 22:534-45. [PMID: 26811605 PMCID: PMC4716057 DOI: 10.3748/wjg.v22.i2.534] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2015] [Revised: 10/13/2015] [Accepted: 11/09/2015] [Indexed: 02/06/2023] Open
Abstract
Colorectal cancers (CRCs) display a wide variety of genomic aberrations that may be either causally linked to their development and progression, or might serve as biomarkers for their presence. Recent advances in rapid high-throughput genetic and genomic analysis have helped to identify a plethora of alterations that can potentially serve as new cancer biomarkers, and thus help to improve CRC diagnosis, prognosis, and treatment. Each distinct data type (copy number variations, gene and microRNAs expression, CpG island methylation) provides an investigator with a different, partially independent, and complementary view of the entire genome. However, elucidation of gene function will require more information than can be provided by analyzing a single type of data. The integration of knowledge obtained from different sources is becoming increasingly essential for obtaining an interdisciplinary view of large amounts of information, and also for cross-validating experimental results. The integration of numerous types of genetic and genomic data derived from public sources, and via the use of ad-hoc bioinformatics tools and statistical methods facilitates the discovery and validation of novel, informative biomarkers. This combinatory approach will also enable researchers to more accurately and comprehensively understand the associations between different biologic pathways, mechanisms, and phenomena, and gain new insights into the etiology of CRC.
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Almeida FGO, de Aquino PF, de Souza ADL, de Souza AQL, do Carmo Vinhote S, Mac-Cormick TM, da Mota Silva MS, Chalub SRS, de Saldanha da Gama Fischer J, Carvalho PC, da Gloria da Costa Carvalho M. Colorectal cancer DNA methylation patterns from patients in Manaus, Brazil. Biol Res 2015; 48:50. [PMID: 26363785 PMCID: PMC4567825 DOI: 10.1186/s40659-015-0042-7] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2015] [Accepted: 09/01/2015] [Indexed: 02/07/2023] Open
Abstract
Background DNA methylation is commonly linked with the silencing of the gene expression for many tumor suppressor genes. As such, determining DNA methylation patterns should aid, in times to come, in the diagnosis and personal treatment for various types of cancers. Here, we analyzed the methylation pattern from five colorectal cancer patients from the Amazon state in Brazil for four tumor suppressor genes, viz.: DAPK, CDH1, CDKN2A, and TIMP2 by employing a polymerase chain reaction (PCR) specific to methylation. Efforts in the study of colorectal cancer are fundamental as it is the third most of highest incidence in the world. Results Tumor biopsies were methylated in 1/5 (20 %), 2/5 (40 %), 4/5 (80 %), and 4/5 (80 %) for CDH1, CDKN2A, DAPK, and TIMP2 genes, respectively. The margin biopsies were methylated in 3/7 (43 %), 2/7 (28 %), 7/7 (100 %), and 6/7 (86 %) for CDH1, CDKN2A, DAPK, and TIMP2, respectively. Conclusions Our findings showed DAPK and TIMP2 to be methylated in most samples from both tumor tissues and adjacent non-neoplastic margins; thus presenting distinct methylation patterns. This emphasizes the importance of better understanding of the relation of these patterns with cancer in the context of different populations.
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Affiliation(s)
- Fabiana Greyce Oliveira Almeida
- Laboratory of Chromatography and Mass Spectrometry, Institute of Exact Sciences, Federal University of Amazonas, Manaus, Brazil.
| | | | - Afonso Duarte Leão de Souza
- Laboratory of Chromatography and Mass Spectrometry, Institute of Exact Sciences, Federal University of Amazonas, Manaus, Brazil.
| | - Antonia Queiroz Lima de Souza
- Laboratory of Chromatography and Mass Spectrometry, Institute of Exact Sciences, Federal University of Amazonas, Manaus, Brazil.
| | | | - Thaís Messias Mac-Cormick
- Laboratory of Molecular Pathology, Department of Pathology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
| | - Marcelo Soares da Mota Silva
- Laboratory of Molecular Pathology, Department of Pathology, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil.
| | | | | | - Paulo Costa Carvalho
- Laboratory of Proteomics and Protein Engineering, Carlos Chagas Institute, Curitiba, Brazil.
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Pisanic TR, Athamanolap P, Poh W, Chen C, Hulbert A, Brock MV, Herman JG, Wang TH. DREAMing: a simple and ultrasensitive method for assessing intratumor epigenetic heterogeneity directly from liquid biopsies. Nucleic Acids Res 2015; 43:e154. [PMID: 26304549 PMCID: PMC4678844 DOI: 10.1093/nar/gkv795] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2015] [Accepted: 07/25/2015] [Indexed: 01/15/2023] Open
Abstract
Many cancers comprise heterogeneous populations of cells at primary and metastatic sites throughout the body. The presence or emergence of distinct subclones with drug-resistant genetic and epigenetic phenotypes within these populations can greatly complicate therapeutic intervention. Liquid biopsies of peripheral blood from cancer patients have been suggested as an ideal means of sampling intratumor genetic and epigenetic heterogeneity for diagnostics, monitoring and therapeutic guidance. However, current molecular diagnostic and sequencing methods are not well suited to the routine assessment of epigenetic heterogeneity in difficult samples such as liquid biopsies that contain intrinsically low fractional concentrations of circulating tumor DNA (ctDNA) and rare epigenetic subclonal populations. Here we report an alternative approach, deemed DREAMing (Discrimination of Rare EpiAlleles by Melt), which uses semi-limiting dilution and precise melt curve analysis to distinguish and enumerate individual copies of epiallelic species at single-CpG-site resolution in fractions as low as 0.005%, providing facile and inexpensive ultrasensitive assessment of locus-specific epigenetic heterogeneity directly from liquid biopsies. The technique is demonstrated here for the evaluation of epigenetic heterogeneity at p14ARF and BRCA1 gene-promoter loci in liquid biopsies obtained from patients in association with non-small cell lung cancer (NSCLC) and myelodysplastic/myeloproliferative neoplasms (MDS/MPN), respectively.
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Affiliation(s)
- Thomas R Pisanic
- Johns Hopkins Institute for NanoBioTechnology, Baltimore, MD 21218, USA
| | - Pornpat Athamanolap
- Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Weijie Poh
- Cancer Biology Program, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD 21287, USA
| | - Chen Chen
- Cancer Biology Program, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD 21287, USA Department of Thoracic Surgery, The Second Xiangya Hospital of Central South University, Changsha, Hunan 410011, China
| | - Alicia Hulbert
- Cancer Biology Program, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD 21287, USA
| | - Malcolm V Brock
- Cancer Biology Program, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD 21287, USA
| | - James G Herman
- Cancer Biology Program, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD 21287, USA
| | - Tza-Huei Wang
- Johns Hopkins Institute for NanoBioTechnology, Baltimore, MD 21218, USA Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA Cancer Biology Program, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD 21287, USA Department of Mechanical Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
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