Abstract
Biomarker discovery and validation are necessary for improving the prediction of clinical outcomes and patient monitoring. Despite considerable interest in biomarker discovery and development, improvements in the range and quality of biomarkers are still needed. The main challenge is how to integrate preclinical data to obtain a reliable biomarker that can be measured with acceptable costs in routine clinical practice. Epigenetic alterations are already being incorporated as valuable candidates in the biomarker field. Furthermore, their reversible nature offers a promising opportunity to ameliorate disease symptoms by using epigenetic-based therapy. Thus, beyond helping to understand disease biology, clinical epigenetics is being incorporated into patient management in oncology, as well as being explored for clinical applicability for other human pathologies such as neurological and infectious diseases and immune system disorders.
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References
Lander, E. S. Initial impact of the sequencing of the human genome. Nature 470, 187–197 (2011).
Roadmap Epigenomics Consortium. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).
Chatterjee, N., Shi, J. & García-Closas, M. Developing and evaluating polygenic risk prediction models for stratified disease prevention. Nat. Rev. Genet. 17, 392–406 (2016).
Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009).
Stunnenberg, H. G. & Hirst, M. & International Human Epigenome Consortium. The International Human Epigenome Consortium: a blueprint for scientific collaboration and discovery. Cell 167, 1897 (2016).
Esteller, M. Non-coding RNAs in human disease. Nat. Rev. Genet. 12, 861–874 (2011).
Adams, B. D., Parsons, C., Walker, L., Zhang, W. C. & Slack, F. J. Targeting noncoding RNAs in disease. J. Clin. Invest. 127, 761–771 (2017).
García-Giménez, J. L. et al. Epigenetic biomarkers: current strategies and future challenges for their use in the clinical laboratory. Crit. Rev. Clin. Lab. Sci. 54, 529–550 (2017).
Bock, C. Epigenetic biomarker development. Epigenomics 1, 99–110 (2009).
García-Giménez, J. L., Mena-Mollá, S., Beltrán-García, J. & Sanchis-Gomar, F. Challenges in the analysis of epigenetic biomarkers in clinical samples. Clin. Chem. Lab. Med. 55, 1474–1477 (2017).
Lorincz, A. T. The promise and the problems of epigenetics biomarkers in cancer. Expert Opin. Med. Diagn. 5, 375–379 (2011).
Lokk, K. et al. DNA methylome profiling of human tissues identifies global and tissue-specific methylation patterns. Genome Biol. 15, r54 (2014).
Ma, F. & Zhang, C. Histone modifying enzymes: novel disease biomarkers and assay development. Expert Rev. Mol. Diagn. 16, 297–306 (2016).
BLUEPRINT consortium. Quantitative comparison of DNA methylation assays for biomarker development and clinical applications. Nat. Biotechnol. 34, 726–737 (2016). In this study, the authors compare global and candidate approaches available for the measurement of CpG methylation with the ultimate goal of validating and optimizing their use in large-scale clinical studies.
Wang, J., Chen, J. & Sen, S. MicroRNA as biomarkers and diagnostics. J. Cell. Physiol. 231, 25–30 (2016).
Larrea, E. et al. New concepts in cancer biomarkers: circulating miRNAs in liquid biopsies. Int. J. Mol. Sci. 17, E627 (2016).
Martínez-Cardús, A. et al. Epigenetic homogeneity within colorectal tumors predicts shorter relapse-free and overall survival times for patients with locoregional cancer. Gastroenterology 151, 961–972 (2016).
Jaffe, A. E. & Irizarry, R. A. Accounting for cellular heterogeneity is critical in epigenome-wide association studies. Genome Biol. 15, R31 (2014).
Videnovic, A., Lazar, A. S., Barker, R. A. & Overeem, S. ‘The clocks that time us’ — circadian rhythms in neurodegenerative disorders. Nat. Rev. Neurol. 10, 683–693 (2014).
Grawenda, A. M. & O’Neill, E. Clinical utility of RASSF1A methylation in human malignancies. Br. J. Cancer 113, 372–381 (2015).
Iglesias-Platas, I., Martín Trujillo, A., Court, F. & Monk, D. Distinct promoter methylation and isoform-specific expression of RASFF1A in placental biopsies from complicated pregnancies. Placenta 36, 397–402 (2015).
Berdasco, M. & Esteller, M. Aberrant epigenetic landscape in cancer: how cellular identity goes awry. Dev. Cell 19, 698–711 (2010).
Esteller, M. et al. hMLH1 promoter hypermethylation is an early event in human endometrial tumorigenesis. Am. J. Pathol. 155, 1767–1772 (1999).
Wang, K. et al. Whole-genome sequencing and comprehensive molecular profiling identify new driver mutations in gastric cancer. Nat. Genet. 46, 573–582 (2014).
Guinney, J. et al. The consensus molecular subtypes of colorectal cancer. Nat. Med. 21, 1350–1356 (2015).
Bormann, F. et al. Cell-of-origin DNA methylation signatures are maintained during colorectal carcinogenesis. Cell Rep. 23, 3407–3418 (2018).
Pajtler, K. W. et al. Molecular classification of ependymal tumors across all CNS compartments, histopathological grades, and age groups. Cancer Cell 27, 728–743 (2015). In this paper, the authors describe a new molecular subclassification of ependymal tumours based on their CpG methylation profiles that complements their histopathological classifications and significantly improves the prognosis prediction of the disease.
Capper, D. et al. DNA methylation-based classification of central nervous system tumours. Nature 555, 469–474 (2018).
Rodríguez-Paredes, M. et al. Methylation profiling identifies two subclasses of squamous cell carcinoma related to distinct cells of origin. Nat. Commun. 9, 577 (2018).
Imperiale, T. F., Ransohoff, D. F. & Itzkowitz, S. H. Multitarget stool DNA testing for colorectal-cancer screening. N. Engl. J. Med. 371, 187–188 (2014).
Lamb, Y. N. & Dhillon, S. Epi proColon® 2.0 CE: a blood-based screening test for colorectal cancer. Mol. Diagn. Ther. 21, 225–232 (2017).
Warren, J. D. et al. Septin 9 methylated DNA is a sensitive and specific blood test for colorectal cancer. BMC Med. 9, 133 (2011).
Ned, R. M., Melillo, S. & Marrone, M. Fecal DNA testing for colorectal cancer screening: the ColoSureTM test. PLOS Curr. 3, RRN1220 (2011).
Ilse, P., Biesterfeld, S., Pomjanski, N., Fink, C. & Schramm, M. SHOX2 DNA methylation is a tumour marker in pleural effusions. Cancer Genom. Proteom. 10, 217–223 (2013).
Church, T. R. et al. Prospective evaluation of methylated SEPT9 in plasma for detection of asymptomatic colorectal cancer. Gut 63, 317–325 (2014).
Wojno, K. J. et al. Reduced rate of repeated prostate biopsies observed in ConfirmMDx clinical utility field study. Am. Heal. Drug Benefits 7, 129–134 (2014).
van Kessel, K. E. M., Van Neste, L., Lurkin, I., Zwarthoff, E. C. & Van Criekinge, W. Evaluation of an epigenetic profile for the detection of bladder cancer in patients with hematuria. J. Urol. 195, 601–607 (2016).
Esteller, M. et al. Inactivation of the DNA-repair gene MGMT and the clinical response of gliomas to alkylating agents. N. Engl. J. Med. 343, 1350–1354 (2000). In this study, the authors describe for first time the connection between CpG methylation at the MGMT promoter and response to therapy in glioblastomas. It is one of the first reports on the use of CpG methylation in pharmacoepigenetics.
Hegi, M. E. et al. MGMT gene silencing and benefit from temozolomide in glioblastoma. N. Engl. J. Med. 352, 997–1003 (2005).
Veeck, J. et al. BRCA1 CpG island hypermethylation predicts sensitivity to poly(adenosine diphosphate)-ribose polymerase inhibitors. J. Clin. Oncol. 28, e563–e564 (2010).
Ter Brugge, P. et al. Mechanisms of therapy resistance in patient-derived xenograft models of BRCA1-deficient breast cancer. J. Natl. Cancer Inst. 108, djw148 (2016).
Duruisseaux, M. et al. Epigenetic prediction of response to anti-PD-1 treatment in non-small-cell lung cancer: a multicenter, retrospective analysis. Lancet. Respir. Med. 6, 771–781 (2018). In this study, the authors describe an epigenomic profile using DNA methylation microarrays that predicts good clinical response to anti-PD-1 therapy in NSCLC.
Moutinho, C. et al. Epigenetic inactivation of the BRCA1 interactor SRBC and resistance to oxaliplatin in colorectal cancer. J. Natl. Cancer Inst. 106, djt322 (2014).
Nogales, V. et al. Epigenetic inactivation of the putative DNA/RNA helicase SLFN11 in human cancer confers resistance to platinum drugs. Oncotarget 7, 3084–3097 (2016).
Diaz-Lagares, A. et al. Epigenetic inactivation of the p53-induced long noncoding RNA TP53 target 1 in human cancer. Proc. Natl Acad. Sci. USA 113, E7535–E7544 (2016).
Lopez-Serra, P. et al. A DERL3-associated defect in the degradation of SLC2A1 mediates the Warburg effect. Nat. Commun. 5, 3608 (2014).
Iorio, F. et al. A landscape of pharmacogenomic interactions in cancer. Cell 166, 740–754 (2016).
Moran, S. et al. Epigenetic profiling to classify cancer of unknown primary: a multicentre, retrospective analysis. Lancet. Oncol. 17, 1386–1395 (2016). In this study, the authors explore the use of an epigenomic strategy based on CpG methylation arrays to unmask the original primary tumour site of cancer of unknown primary cases.
Kang, S. et al. CancerLocator: non-invasive cancer diagnosis and tissue-of-origin prediction using methylation profiles of cell-free DNA. Genome Biol. 18, 53 (2017).
Tang, W., Wan, S., Yang, Z., Teschendorff, A. E. & Zou, Q. Tumor origin detection with tissue-specific miRNA and DNA methylation markers. Bioinformatics 34, 398–406 (2018).
Hoadley, K. A. et al. Cell-of-origin patterns dominate the molecular classification of 10,000 tumors from 33 types of cancer. Cell 173, 291–304 (2018).
Fraga, M. F. et al. Loss of acetylation at Lys16 and trimethylation at Lys20 of histone H4 is a common hallmark of human cancer. Nat. Genet. 37, 391–400 (2005).
Yuen, B. T. K. & Knoepfler, P. S. Histone H3.3 mutations: a variant path to cancer. Cancer Cell 24, 567–574 (2013).
Holdenrieder, S. & Stieber, P. Clinical use of circulating nucleosomes. Crit. Rev. Clin. Lab. Sci. 46, 1–24 (2009).
Snyder, M. W., Kircher, M., Hill, A. J., Daza, R. M. & Shendure, J. Cell-free DNA comprises an in vivo nucleosome footprint that informs its tissues-of-origin. Cell 164, 57–68 (2016). In this study, the authors describe how nucleosome footprints detected in blood can be used to infer cell type of origin. This finding could improve the use of non-invasive samples in the diagnosis and prognosis of cancer, as well as other diseases.
Gezer, U. et al. Histone methylation marks on circulating nucleosomes as novel blood-based biomarker in colorectal cancer. Int. J. Mol. Sci. 16, 29654–29662 (2015).
Bauden, M. et al. Circulating nucleosomes as epigenetic biomarkers in pancreatic cancer. Clin. Epigenet. 7, 106 (2015).
West, A. C. & Johnstone, R. W. New and emerging HDAC inhibitors for cancer treatment. J. Clin. Invest. 124, 30–39 (2014).
Ganesan, A. Multitarget drugs: an epigenetic epiphany. ChemMedChem 11, 1227–1241 (2016).
Jones, P. A., Issa, J.-P. J. & Baylin, S. Targeting the cancer epigenome for therapy. Nat. Rev. Genet. 17, 630–641 (2016).
Roulois, D. et al. DNA-demethylating agents target colorectal cancer cells by inducing viral mimicry by endogenous transcripts. Cell 162, 961–973 (2015).
Prebet, T. et al. Prolonged administration of azacitidine with or without entinostat for myelodysplastic syndrome and acute myeloid leukemia with myelodysplasia-related changes: results of the US Leukemia Intergroup trial E1905. J. Clin. Oncol. 32, 1242–1248 (2014).
Juergens, R. A. et al. Combination epigenetic therapy has efficacy in patients with refractory advanced non-small cell lung cancer. Cancer Discov. 1, 598–607 (2011).
Morera, L., Lübbert, M. & Jung, M. Targeting histone methyltransferases and demethylases in clinical trials for cancer therapy. Clin. Epigenet. 8, 57 (2016).
Daigle, S. R. et al. Potent inhibition of DOT1L as treatment of MLL-fusion leukemia. Blood 122, 1017–1025 (2013).
Mohammad, H. P. et al. A DNA hypomethylation signature predicts antitumor activity of LSD1 inhibitors in SCLC. Cancer Cell 28, 57–69 (2015).
Ocaña, A., Nieto-Jiménez, C. & Pandiella, A. BET inhibitors as novel therapeutic agents in breast cancer. Oncotarget 8, 71285–71291 (2017).
Raynal, N. J.-M. et al. Targeting calcium signaling induces epigenetic reactivation of tumor suppressor genes in cancer. Cancer Res. 76, 1494–1505 (2016).
Delgado-Morales, R., Agís-Balboa, R. C., Esteller, M. & Berdasco, M. Epigenetic mechanisms during ageing and neurogenesis as novel therapeutic avenues in human brain disorders. Clin. Epigenet. 9, 67 (2017).
Hauser, R. M., Henshall, D. C. & Lubin, F. D. The epigenetics of epilepsy and its progression. Neuroscientist 24, 186–200 (2017).
Paez-Colasante, X., Figueroa-Romero, C., Sakowski, S. A., Goutman, S. A. & Feldman, E. L. Amyotrophic lateral sclerosis: mechanisms and therapeutics in the epigenomic era. Nat. Rev. Neurol. 11, 266–279 (2015).
Jakubowski, J. L. & Labrie, V. Epigenetic biomarkers for parkinson’s disease: from diagnostics to therapeutics. J. Parkinsons. Dis. 7, 1–12 (2017).
Qazi, T. J., Quan, Z., Mir, A. & Qing, H. Epigenetics in Alzheimer’s disease: perspective of DNA methylation. Mol. Neurobiol. 55, 1026–1044 (2017).
Birnbaum, R. & Weinberger, D. R. Genetic insights into the neurodevelopmental origins of schizophrenia. Nat. Rev. Neurosci. 18, 727–740 (2017).
Saavedra, K., Molina-Márquez, A. M., Saavedra, N., Zambrano, T. & Salazar, L. A. Epigenetic modifications of major depressive disorder. Int. J. Mol. Sci. 17, E1279 (2016).
Ryan, J., Chaudieu, I., Ancelin, M.-L. & Saffery, R. Biological underpinnings of trauma and post-traumatic stress disorder: focusing on genetics and epigenetics. Epigenomics 8, 1553–1569 (2016).
Sanchez-Mut, J. V. et al. Human DNA methylomes of neurodegenerative diseases show common epigenomic patterns. Transl Psychiatry 6, e718 (2016).
Ai, S. et al. Hypomethylation of SNCA in blood of patients with sporadic Parkinson’s disease. J. Neurol. Sci. 337, 123–128 (2014).
Logan, T., Bendor, J., Toupin, C., Thorn, K. & Edwards, R. H. α-Synuclein promotes dilation of the exocytotic fusion pore. Nat. Neurosci. 20, 681–689 (2017).
Di Francesco, A. et al. Global changes in DNA methylation in Alzheimer’s disease peripheral blood mononuclear cells. Brain. Behav. Immun. 45, 139–144 (2015).
Ferri, E. et al. Gene promoter methylation and expression of Pin1 differ between patients with frontotemporal dementia and Alzheimer’s disease. J. Neurol. Sci. 362, 283–286 (2016).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02868905?term=NCT02868905&rank=1 (2016).
Iwata, A. et al. Altered CpG methylation in sporadic Alzheimer’s disease is associated with APP and MAPT dysregulation. Hum. Mol. Genet. 23, 648–656 (2014).
Marques, S. C. F. et al. Epigenetic regulation of BACE1 in Alzheimer’s disease patients and in transgenic mice. Neuroscience 220, 256–266 (2012).
Sanchez-Mut, J. V. et al. Promoter hypermethylation of the phosphatase DUSP22 mediates PKA-dependent TAU phosphorylation and CREB activation in Alzheimer’s disease. Hippocampus 24, 363–368 (2014).
Nicolia, V., Fuso, A., Cavallaro, R. A., Di Luzio, A. & Scarpa, S. B vitamin deficiency promotes tau phosphorylation through regulation of GSK3beta and PP2A. J. Alzheimers. Dis. 19, 895–907 (2010).
Sanchez-Mut, J. V. et al. PM20D1 is a quantitative trait locus associated with Alzheimer’s disease. Nat. Med. 24, 598–603 (2018).
Lim, D. A. et al. Chromatin remodelling factor Mll1 is essential for neurogenesis from postnatal neural stem cells. Nature 458, 529–533 (2009).
Jawerka, M. et al. The specific role of histone deacetylase 2 in adult neurogenesis. Neuron Glia Biol. 6, 93–107 (2010).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03381482?term=NCT03381482&rank=1 (2017).
Chu, T. et al. Valproic acid-mediated neuroprotection and neurogenesis after spinal cord injury: from mechanism to clinical potential. Regen. Med. 10, 193–209 (2015).
Vukic´evic´, V. et al. Valproic acid enhances neuronal differentiation of sympathoadrenal progenitor cells. Mol. Psychiatry 20, 941–950 (2015).
Abel, T. & Zukin, R. S. Epigenetic targets of HDAC inhibition in neurodegenerative and psychiatric disorders. Curr. Opin. Pharmacol. 8, 57–64 (2008).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02654405?term=NCT02654405&rank=1 (2016).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02094651?term=NCT02094651&rank=1 (2014).
Maes, T. et al. KDM1 histone lysine demethylases as targets for treatments of oncological and neurodegenerative disease. Epigenomics 7, 609–626 (2015).
Ballestar, E. & Li, T. New insights into the epigenetics of inflammatory rheumatic diseases. Nat. Rev. Rheumatol. 13, 593–605 (2017).
Kondilis-Mangum, H. D. & Wade, P. A. Epigenetics and the adaptive immune response. Mol. Aspects Med. 34, 813–825 (2013).
Wang, Z., Chang, C., Peng, M. & Lu, Q. Translating epigenetics into clinic: focus on lupus. Clin. Epigenet. 9, 78 (2017).
Hammaker, D. & Firestein, G. S. Epigenetics of inflammatory arthritis. Curr. Opin. Rheumatol. 30, 188–196 (2018).
Zheleznyakova, G. Y. et al. Epigenetic research in multiple sclerosis: progress, challenges, and opportunities. Physiol. Genom. 49, 447–461 (2017).
Xie, Y.-Q., Ma, H.-D. & Lian, Z.-X. Epigenetics and primary biliary cirrhosis: a comprehensive review and implications for autoimmunity. Clin. Rev. Allergy Immunol. 50, 390–403 (2016).
Pollock, R. A., Abji, F. & Gladman, D. D. Epigenetics of psoriatic disease: a systematic review and critical appraisal. J. Autoimmun. 78, 29–38 (2017).
Potaczek, D. P. et al. Epigenetics and allergy: from basic mechanisms to clinical applications. Epigenomics 9, 539–571 (2017).
Javierre, B. M. et al. Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus. Genome Res. 20, 170–179 (2010).
Selmi, C. et al. Genome-wide analysis of DNA methylation, copy number variation, and gene expression in monozygotic twins discordant for primary biliary cirrhosis. Front. Immunol. 5, 128 (2014).
Absher, D. M. et al. Genome-wide DNA methylation analysis of systemic lupus erythematosus reveals persistent hypomethylation of interferon genes and compositional changes to CD4+ T cell populations. PLOS Genet. 9, e1003678 (2013).
Lin, S.-Y. et al. A whole genome methylation analysis of systemic lupus erythematosus: hypomethylation of the IL10 and IL1R2 promoters is associated with disease activity. Genes Immun. 13, 214–220 (2012).
Vent-Schmidt, J., Han, J. M., MacDonald, K. G. & Levings, M. K. The role of FOXP3 in regulating immune responses. Int. Rev. Immunol. 33, 110–128 (2014).
Neven, K. Y. et al. Repetitive element hypermethylation in multiple sclerosis patients. BMC Genet. 17, 84 (2016).
Ayuso, T. et al. Vitamin D receptor gene is epigenetically altered and transcriptionally up-regulated in multiple sclerosis. PLOS ONE 12, e0174726 (2017).
Field, J. et al. Interleukin-2 receptor-α proximal promoter hypomethylation is associated with multiple sclerosis. Genes Immun. 18, 59–66 (2017).
Lehmann-Werman, R. et al. Identification of tissue-specific cell death using methylation patterns of circulating DNA. Proc. Natl Acad. Sci. USA 113, E1826–E1834 (2016).
Pedre, X. et al. Changed histone acetylation patterns in normal-appearing white matter and early multiple sclerosis lesions. J. Neurosci. 31, 3435–3445 (2011).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02862301?term=NCT02862301&rank=1 (2016).
Shu, J. et al. IRF5 is elevated in childhood-onset SLE and regulated by histone acetyltransferase and histone deacetylase inhibitors. Oncotarget 8, 47184–47194 (2017).
Cribbs, A. P. et al. Methotrexate restores regulatory T cell function through demethylation of the FoxP3 upstream enhancer in patients with rheumatoid arthritis. Arthritis Rheumatol. 67, 1182–1192 (2015).
Hait, N. C. et al. Active, phosphorylated fingolimod inhibits histone deacetylases and facilitates fear extinction memory. Nat. Neurosci. 17, 971–980 (2014).
Sun, X. et al. From genetics and epigenetics to the future of precision treatment for obesity. Gastroenterol. Rep. 5, 266–270 (2017).
Bonàs-Guarch, S. et al. Re-analysis of public genetic data reveals a rare X-chromosomal variant associated with type 2 diabetes. Nat. Commun. 9, 321 (2018).
Yuan, W. et al. An integrated epigenomic analysis for type 2 diabetes susceptibility loci in monozygotic twins. Nat. Commun. 5, 5719 (2014).
Nilsson, E. et al. Altered DNA methylation and differential expression of genes influencing metabolism and inflammation in adipose tissue from subjects with type 2 diabetes. Diabetes 63, 2962–2976 (2014).
Volkmar, M. et al. DNA methylation profiling identifies epigenetic dysregulation in pancreatic islets from type 2 diabetic patients. EMBO J. 31, 1405–1426 (2012).
Nitert, M. D. et al. Impact of an exercise intervention on DNA methylation in skeletal muscle from first-degree relatives of patients with type 2 diabetes. Diabetes 61, 3322–3332 (2012).
Barrès, R. et al. Acute exercise remodels promoter methylation in human skeletal muscle. Cell Metab. 15, 405–411 (2012).
Rönn, T. et al. A six months exercise intervention influences the genome-wide DNA methylation pattern in human adipose tissue. PLOS Genet. 9, e1003572 (2013).
Jacobsen, S. C. et al. Effects of short-term high-fat overfeeding on genome-wide DNA methylation in the skeletal muscle of healthy young men. Diabetologia 55, 3341–3349 (2012).
Perfilyev, A. et al. Impact of polyunsaturated and saturated fat overfeeding on the DNA-methylation pattern in human adipose tissue: a randomized controlled trial. Am. J. Clin. Nutr. 105, 991–1000 (2017).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02982408?term=NCT02982408&rank=1 (2016).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT01911104?term=NCT01911104&rank=1 (2018).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03259984?term=NCT03259984&rank=1 (2017).
Wahl, S. et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature 541, 81–86 (2017). In this study, the authors describe alterations of CpG methylation associated with obesity and concluded that disturbances in DNA methylation are predictors of future development of T2D in obese individuals.
Kumar, A., Darcis, G., Van Lint, C. & Herbein, G. Epigenetic control of HIV-1 post integration latency: implications for therapy. Clin. Epigenet. 7, 1–12 (2015).
Burgos, J., Ribera, E. & Falcó, V. Antiretroviral therapy in advanced HIV disease: which is the best regimen? AIDS Rev. 20, 3–13 (2018).
Archin, N. M. et al. Administration of vorinostat disrupts HIV-1 latency in patients on antiretroviral therapy. Nature 487, 482–485 (2012). This work supports the use of an HDACi as a therapeutic target to unmask latent HIV reservoirs and consequently eradicate HIV infection directly.
Routy, J. P. et al. Valproic acid in association with highly active antiretroviral therapy for reducing systemic HIV-1 reservoirs: results from a multicentre randomized clinical study. HIV Med. 13, 291–296 (2012).
Rasmussen, T. A. et al. Panobinostat, a histone deacetylase inhibitor, for latent-virus reactivation in HIV-infected patients on suppressive antiretroviral therapy: a phase 1/2, single group, clinical trial. Lancet. HIV 1, e13–e21 (2014).
Tripathy, M. K., McManamy, M. E. M., Burch, B. D., Archin, N. M. & Margolis, D. M. H3K27 demethylation at the proviral promoter sensitizes latent HIV to the effects of vorinostat in ex vivo cultures of resting CD4+ T Cells. J. Virol. 89, 8392–8405 (2015).
Jain, S. et al. Comprehensive DNA methylation analysis of hepatitis B virus genome in infected liver tissues. Sci. Rep. 5, 10478 (2015).
Pollicino, T. et al. Hepatitis B virus replication is regulated by the acetylation status of hepatitis B virus cccDNA-bound H3 and H4 histones. Gastroenterology 130, 823–837 (2006).
Fernandez, A. F. et al. The dynamic DNA methylomes of double-stranded DNA viruses associated with human cancer. Genome Res. 19, 438–451 (2008).
Kim, K., Garner-Hamrick, P. A., Fisher, C., Lee, D. & Lambert, P. F. Methylation patterns of papillomavirus DNA, its influence on E2 function, and implications in viral infection. J. Virol. 77, 12450–12459 (2003).
Vinokurova, S. Epigenetics of virus-induced tumors: perspectives for therapeutic targeting. Curr. Pharm. Des. 23, 4842–4861 (2017).
Soto, D., Song, C. & McLaughlin-Drubin, M. E. Epigenetic alterations in human papillomavirus-associated cancers. Viruses 9, 248 (2017).
Clarke, M. A. et al. Human papillomavirus DNA methylation as a biomarker for cervical precancer: consistency across 12 Genotypes and potential impact on management of HPV-positive women. Clin. Cancer Res. 24, 2194–2202 (2018).
Hesselink, A. T. et al. Methylation marker analysis of self-sampled cervico-vaginal lavage specimens to triage high-risk HPV-positive women for colposcopy. Int. J. Cancer 135, 880–886 (2014).
Guerrero-Preston, R. et al. Molecular triage of premalignant lesions in liquid-based cervical cytology and circulating cell-free DNA from urine, using a panel of methylated human papilloma virus and host genes. Cancer Prev. Res. 9, 915–924 (2016).
Kato, N. et al. Trans-ancestry genome-wide association study identifies 12 genetic loci influencing blood pressure and implicates a role for DNA methylation. Nat. Genet. 47, 1282–1293 (2015).
Rask-Andersen, M. et al. Epigenome-wide association study reveals differential DNA methylation in individuals with a history of myocardial infarction. Hum. Mol. Genet. 25, 4739–4748 (2016).
Haas, J. et al. Alterations in cardiac DNA methylation in human dilated cardiomyopathy. EMBO Mol. Med. 5, 413–429 (2013).
Moore, J. B. et al. The epigenetic regulator HDAC1 modulates transcription of a core cardiogenic program in human cardiac mesenchymal stromal cells through a p53-dependent mechanism. Stem Cells 34, 2916–2929 (2016).
Liang, L. et al. An epigenome-wide association study of total serum immunoglobulin E concentration. Nature 520, 670–674 (2015).
Yoo, S. et al. Integrative analysis of DNA methylation and gene expression data identifies EPAS1 as a key regulator of COPD. PLOS Genet. 11, e1004898 (2015).
Huang, S. K., Scruggs, A. M., McEachin, R. C., White, E. S. & Peters-Golden, M. Lung fibroblasts from patients with idiopathic pulmonary fibrosis exhibit genome-wide differences in DNA methylation compared to fibroblasts from nonfibrotic lung. PLOS ONE 9, e107055 (2014).
Hunter, A. et al. DNA methylation is associated with altered gene expression in AMD. Invest. Ophthalmol. Vis. Sci. 53, 2089–2105 (2012).
Burdon, K. P. et al. DNA methylation at the 9p21 glaucoma susceptibility locus is associated with normal-tension glaucoma. Ophthalm. Genet. 39, 221–227 (2017).
Berdasco, M. et al. DNA methylomes reveal biological networks involved in human eye development, functions and associated disorders. Sci. Rep. 7, 11762 (2017).
Reik, W. & Surani, M. A. Germline and pluripotent stem cells. Cold Spring Harb. Perspect. Biol. 7, a019422 (2015).
Tenorio, J. et al. Clinical and molecular analyses of Beckwith-Wiedemann syndrome: comparison between spontaneous conception and assisted reproduction techniques. Am. J. Med. Genet. A 170A, 2740–2749 (2016).
Canovas, S., Ross, P. J., Kelsey, G. & Coy, P. DNA methylation in embryo development: epigenetic impact of ART (Assisted Reproductive Technologies). Bioessays 39, 1700106 (2017).
Lou, H. et al. Assisted reproductive technologies impair the expression and methylation of insulin-induced gene 1 and sterol regulatory element-binding factor 1 in the fetus and placenta. Fertil. Steril. 101, 974–980 (2014).
Sunde, A. et al. Time to take human embryo culture seriously. Hum. Reprod. 31, 2174–2182 (2016).
Berdasco, M. & Esteller, M. Genetic syndromes caused by mutations in epigenetic genes. Hum. Genet. 132, 359–383 (2013).
Cheishvili, D., Boureau, L. & Szyf, M. DNA demethylation and invasive cancer: implications for therapeutics. Br. J. Pharmacol. 172, 2705–2715 (2015).
Schmitz, K.-M., Mayer, C., Postepska, A. & Grummt, I. Interaction of noncoding RNA with the rDNA promoter mediates recruitment of DNMT3b and silencing of rRNA genes. Genes Dev. 24, 2264–2269 (2010).
Holz-Schietinger, C. & Reich, N. O. RNA modulation of the human DNA methyltransferase 3A. Nucleic Acids Res. 40, 8550–8557 (2012).
Brocken, D. J. W., Tark-Dame, M. & Dame, R. T. dCas9: a versatile tool for epigenome editing. Curr. Issues Mol. Biol. 26, 15–32 (2018).
Cano-Rodriguez, D. et al. Writing of H3K4Me3 overcomes epigenetic silencing in a sustained but context-dependent manner. Nat. Commun. 7, 12284 (2016).
Huang, P.-H., Plass, C. & Chen, C.-S. Effects of histone deacetylase inhibitors on modulating H3K4 methylation marks - a novel cross-talk mechanism between histone-modifying enzymes. Mol. Cell. Pharmacol. 3, 39–43 (2011).
Sarkar, S. et al. Histone deacetylase inhibitors reverse CpG methylation by regulating DNMT1 through ERK signaling. Anticancer Res. 31, 2723–2732 (2011).
de Lera, A. R. & Ganesan, A. Epigenetic polypharmacology: from combination therapy to multitargeted drugs. Clin. Epigenetics 8, 105 (2016).
Park, M. A. et al. Vorinostat and sorafenib increase CD95 activation in gastrointestinal tumor cells through a Ca(2+)-de novo ceramide-PP2A-reactive oxygen species-dependent signaling pathway. Cancer Res. 70, 6313–6324 (2010).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02151721?term=NCT02151721&rank=1 (2018).
Mazur, P. K. et al. Combined inhibition of BET family proteins and histone deacetylases as a potential epigenetics-based therapy for pancreatic ductal adenocarcinoma. Nat. Med. 21, 1163–1171 (2015). In this work, the authors examined the beneficial effect of the combination of two epidrugs, a BET inhibitor and a HDACi, on growth inhibition in pancreatic carcinoma.
Mazzone, R., Zwergel, C., Mai, A. & Valente, S. Epi-drugs in combination with immunotherapy: a new avenue to improve anticancer efficacy. Clin. Epigenet. 9, 59 (2017).
Chiappinelli, K. B., Zahnow, C. A., Ahuja, N. &/ Baylin, S. B. Combining epigenetic and immunotherapy to combat cancer. Cancer Res. 76, 1683–1689 (2016).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT01928576?term=NCT01928576&rank=1 (2018).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT02638090?term=NCT02638090&rank=1 (2018).
Topper, M. J. et al. Epigenetic therapy ties MYC depletion to reversing immune evasion and treating lung cancer. Cell 171, 1284–1300 (2017).
Laird, P. W. Principles and challenges of genomewide DNA methylation analysis. Nat. Rev. Genet. 11, 191–203 (2010).
Krueger, F., Kreck, B., Franke, A. & Andrews, S. R. DNA methylome analysis using short bisulfite sequencing data. Nat. Methods 9, 145–151 (2012).
Morente, M. M., Fernández, P. L. & de Alava, E. Biobanking: old activity or young discipline? Semin. Diagn. Pathol. 25, 317–322 (2008).
Kelsey, G., Stegle, O. & Reik, W. Single-cell epigenomics: recording the past and predicting the future. Science 358, 69–75 (2017).
Houseman, E. A., Molitor, J. & Marsit, C. J. Reference-free cell mixture adjustments in analysis of DNA methylation data. Bioinformatics 30, 1431–1439 (2014).
Zou, J., Lippert, C., Heckerman, D., Aryee, M. & Listgarten, J. Epigenome-wide association studies without the need for cell-type composition. Nat. Methods 11, 309–311 (2014).
Liu, Y. et al. Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis. Nat. Biotechnol. 31, 142–147 (2013).
Latvala, A. & Ollikainen, M. Mendelian randomization in (epi)genetic epidemiology: an effective tool to be handled with care. Genome Biol. 17, 156 (2016).
Lister, R. et al. Global epigenomic reconfiguration during mammalian brain development. Science 341, 1237905 (2013).
Esteller, M. & Pandolfi, P. P. The epitranscriptome of noncoding RNAs in cancer. Cancer Discov. 7, 359–368 (2017).
Macaulay, I. C., Ponting, C. P. & Voet, T. Single-cell multiomics: multiple measurements from single cells. Trends Genet. 33, 155–168 (2017).
Toraño, E. G., García, M. G., Fernández-Morera, J. L., Niño-García, P. & Fernández, A. F. The impact of external factors on the epigenome: in utero and over lifetime. Biomed. Res. Int. 2016, 2568635 (2016).
Barker, D. J. P. The origins of the developmental origins theory. J. Intern. Med. 261, 412–417 (2007).
Heijmans, B. T. et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc. Natl Acad. Sci. USA 105, 17046–17049 (2008). In this pioneering work, the authors demonstrate that prenatal exposure to famine can lead to CpG methylation changes that may affect the postnatal life of the offspring.
Zacharasiewicz, A. Maternal smoking in pregnancy and its influence on childhood asthma. ERJ Open Res. 2, 00042–2016 (2016).
Banik, A. et al. Maternal factors that induce epigenetic changes contribute to neurological disorders in offspring. Genes (Basel) 8, (150 (2017).
Kereliuk, S. M., Brawerman, G. M. & Dolinsky, V. W. Maternal macronutrient consumption and the developmental origins of metabolic disease in the offspring. Int. J. Mol. Sci. 18, E1451 (2017).
Hullar, M. A. J. & Fu, B. C. Diet, the gut microbiome, and epigenetics. Cancer J. 20, 170–175 (2014).
Takahashi, K. et al. Epigenetic control of the host gene by commensal bacteria in large intestinal epithelial cells. J. Biol. Chem. 286, 35755–35762 (2011).
Paul, B. et al. Influences of diet and the gut microbiome on epigenetic modulation in cancer and other diseases. Clin. Epigenet. 7, 112 (2015).
de Souza, H. S. P., Fiocchi, C. & Iliopoulos, D. The IBD interactome: an integrated view of aetiology, pathogenesis and therapy. Nat. Rev. Gastroenterol. Hepatol. 14, 739–749 (2017).
Krautkramer, K. A. et al. Diet-microbiota interactions mediate global epigenetic programming in multiple host tissues. Mol. Cell 64, 982–992 (2016).
Watson, M. M. & Søreide, K. in Handbook of Epigenetics 495–510 (Elsevier, 2017).
Kundu, P., Blacher, E., Elinav, E. & Pettersson, S. Our gut microbiome: the evolving inner self. Cell 171, 1481–1493 (2017).
Theunissen, T. W. & Jaenisch, R. Mechanisms of gene regulation in human embryos and pluripotent stem cells. Development 144, 4496–4509 (2017).
Berdasco, M. et al. DNA methylation plasticity of human adipose-derived stem cells in lineage commitment. Am. J. Pathol. 181, 2079–2093 (2012).
Costantino, S. et al. Epigenetics and precision medicine in cardiovascular patients: from basic concepts to the clinical arena. Eur. Heart J. https://doi.org/10.1093/eurheartj/ehx568 (2017).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03205761?term=NCT03205761&rank=1 (2018).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT01182103?term=NCT01182103&rank=1 (2014).
US National Library of Medicine. ClinicalTrials.gov https://clinicaltrials.gov/ct2/show/NCT03152838?term=NCT03152838&rank=1 (2017).
Chung, S. A. et al. Differential genetic associations for systemic lupus erythematosus based on anti-dsDNA autoantibody production. PLOS Genet. 7, e1001323 (2011).
Dai, Y., Zhang, L., Hu, C. & Zhang, Y. Genome-wide analysis of histone H3 lysine 4 trimethylation by ChIP-chip in peripheral blood mononuclear cells of systemic lupus erythematosus patients. Clin. Exp. Rheumatol. 28, 158–168 (2010).
Diesch, J. et al. A clinical-molecular update on azanucleoside-based therapy for the treatment of hematologic cancers. Clin. Epigenet. 8, 71 (2016).
Bubna, A. K. Vorinostat-an overview. Indian J. Dermatol. 60, 419 (2015).
Reddy, S. A. Romidepsin for the treatment of relapsed/refractory cutaneous T cell lymphoma (mycosis fungoides/Sézary syndrome): use in a community setting. Crit. Rev. Oncol. Hematol. 106, 99–107 (2016).
O’Connor, O. A. et al. Belinostat in patients with relapsed or refractory peripheral T-cell lymphoma: results of the pivotal phase II BELIEF (CLN-19) study. J. Clin. Oncol. 33, 2492–2499 (2015).
Cavenagh, J. D. & Popat, R. Optimal management of histone deacetylase inhibitor-related adverse events in patients with multiple myeloma: a focus on panobinostat. Clin. Lymphoma. Myeloma Leuk. 18, 501–507 (2018).
Vojinovic, J. et al. Safety and efficacy of an oral histone deacetylase inhibitor in systemic-onset juvenile idiopathic arthritis. Arthritis Rheum. 63, 1452–1458 (2011).
Cudkowicz, M. E. et al. Phase 2 study of sodium phenylbutyrate in ALS. Amyotroph. Lateral Scler. 10, 99–106 (2009).
Kissel, J. T. et al. SMA CARNIVAL TRIAL PART II: a prospective, single-armed trial of L-carnitine and valproic acid in ambulatory children with spinal muscular atrophy. PLOS ONE 6, e21296 (2011).
Heijnen, W. T., De Fruyt, J., Wierdsma, A. I., Sienaert, P. & Birkenhäger, T. K. Efficacy of tranylcypromine in bipolar depression: a systematic review. J. Clin. Psychopharmacol. 35, 700–705 (2015).
Lee, D. E., Kim, S. Y., Lim, J. H., Park, S. Y. & Ryu, H. M. Non-invasive prenatal testing of trisomy 18 by an epigenetic marker in first trimester maternal plasma. PLOS ONE 8, e78136 (2013).
Acknowledgements
The authors are supported by the Health Department PERIS, project SLT/002/16/00374 and AGAUR projects 2017SGR1080, 2014SGR633 and 2009SGR1315 of the Catalan Government (Generalitat de Catalunya); the Spanish Institute of Health Carlos III (ISCIII) projects DTS16/00153, PI15/00638 and PI18/00910; the Integrated Project of Excellence PIE13/00022 (ONCOPROFILE); the Ministerio de Economía y Competitividad (MINECO) under grant SAF2014-55000-R co-financed by the European Development Regional Fund ‘A way to achieve Europe’ (ERDF); CIBER 2016 CB16/12/00312 (CIBERONC); the Cellex Foundation; ‘la Caixa’ Banking Foundation (LCF/PR/PR15/11100003); COST Action CM1406; and the Scientific Foundation of the Spanish Association Against Cancer (AECC).
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Glossary
- Personalized medicine
-
(Also known as precision medicine). A form of medicine that uses specific information about a person (for example, genes, proteins or environment) to tailor preventive care, disease prognosis or drug therapy.
- Epigenetics
-
The study of heritable changes in gene function that do not involve changes in the DNA sequence. Epigenetic mechanisms include the covalent modifications of DNA and histones.
- Epigenome
-
The complete set of epigenetic modifications across an individual’s entire genome.
- Epidrugs
-
Small-molecule inhibitors that target either the epigenome or an enzyme with epigenetic activity. They are classified according to their respective target enzymes and include the following: DNA methyltransferase inhibitors (DNMTi), histone acetyltransferase inhibitors (HATi), histone methyltransferase inhibitors (HMTi), histone demethylase inhibitors (HDMi), histone deacetylase inhibitors (HDACi) and bromodomain inhibitors.
- CpG methylation
-
Methylation of a cytosine that is 5′ to a guanine. CpG methylation is essential for normal development and is associated with multiple biological processes, including gene regulation, genomic imprinting, X chromosome inactivation or repression of transposable elements.
- Histone modifications
-
Covalent post-translational modifications in the tails of histone proteins that can affect chromatin structure. Modifications include methylation, phosphorylation, acetylation, ubiquitylation and sumoylation, among others.
- Epigenetic biomarkers
-
Any epigenetic mark or altered epigenetic mechanism that is stable and reproducible during sample processing and can be measured in the body fluids or primary types of tissue preparations that may predict risk of future disease development, detection of the disease (diagnosis), outcome of disease (prognosis) and response to therapy (pharmacoepigenetics) or allow simultaneous determination of diagnosis and suitable targeted therapy (theragnosis).
- Circulating cell-free DNA
-
(cfDNA). Degraded DNA fragments released to the blood plasma. These fragments can include circulating tumour DNA or cell-free fetal DNA. Release of circulating tumour DNA may be a consequence of apoptosis and necrosis from dying cells but also as a result of active release from viable tumour cells.
- Chromatin immunoprecipitation
-
(ChIP). A common and powerful technique for analysing histone modifications and other DNA-binding proteins at specific loci.
- Liquid biopsy samples
-
Any samples taken from a non-solid biological tissue, such as blood, saliva or urine, among others. Because of their non-invasive nature, liquid biopsies are mainly used as a diagnosis and prognosis biomarker of diseases.
- Faecal occult blood tests
-
(FOBTs). Non-invasive screening tests for detecting colorectal cancer on the basis of the presence of hidden blood in the stool, which is a sign of early colorectal cancer but also of other gastrointestinal disorders. Chemical faecal occult blood testing is based on the ability of haemoglobin to transfer an oxygen atom from peroxide to a specific chromogen (for example, guaiac). Oxidation of the chromogen can be visualized by the production of a colorimetric reaction.
- Faecal immunochemical tests
-
(FITs). Faecal occult blood tests based on an immunological method that uses a specific antibody for the recognition of human haemoglobin.
- Circulating cell-free nucleosomes
-
(cfnucleosomes). Nucleosomes released from dying cells into the blood.
- Methylation quantitative trait locus
-
(mQTL). A locus where genotype is associated with the DNA methylation level. Individual genotype variation at a given locus may result in different patterns of DNA methylation owing to allele-specific methylation. The methylation effect of a mQTL can be extended across large genomic regions and can vary during development and show cell-type specificity.
- Epigenome editing
-
A set of genome engineering technologies that are able to alter the epigenetic composition of the genome at a specific genomic location.
- Whole-genome bisulfite sequencing
-
(WGBS). Next-generation sequencing technology used to determine the DNA methylation status of single cytosines by sequencing the entire genome after sodium bisulfite treatment. Cytosine methylation protects from bisulfite-mediated deamination of cytosine to uracil, which would be read as thymine during sequencing.
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Berdasco, M., Esteller, M. Clinical epigenetics: seizing opportunities for translation. Nat Rev Genet 20, 109–127 (2019). https://doi.org/10.1038/s41576-018-0074-2
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DOI: https://doi.org/10.1038/s41576-018-0074-2