- Email: [email protected]
Conclusions and perspectives: Major challenges and future prospects for prognostic epigenetics
CHAPTER
Conclusions and perspectives: Major challenges and future prospects for prognostic epigenetics
15
Shilpy Sharma Department of Biotechnology, Savitribai Phule Pune University (Formerly University of Pune), Pune, India
1 Introduction With the advent of the human genome-sequencing era, it became clear that genetic variation alone cannot be used to predict susceptibility toward developing complex multigene disorders [1, 2]. As discussed through the length of this book, epigenetics—the study of any potentially heritable changes in gene expression or phenotype that occurs without any changes in the underlying DNA sequence—has a bigger role to play in regulating cellular pathways. Epigenetic modifications have not only shown to be associated with the onset but also with the progression and maintenance of several life-threatening and debilitating complex disorders including cancer, asthma, allergy, autoimmune diseases, cardiovascular diseases, diabetes, adiposity, etc. [2–9]. Interestingly, the epigenome, that is, the complete array of chemical modifications to DNA and histone proteins that regulate the expression of genes, is highly dynamic and can be greatly influenced by the intracellular and extracellular environment [10–13]. Epigenetic modifications may occur at the level of DNA (methylation of promoter regions resulting in gene silencing); could affect higher order of structural organization of DNA by causing posttranslational modifications in histones; mediate chromatin remodeling; or could regulate gene expression through noncoding RNAs (ncRNAs) [7, 14–16]. An accurate, yet reproducible measure of these changes could be used to reflect DNA regulation in a system. Hence, researchers and clinicians worldwide are making several attempts to develop these epigenetic marks as prognostic and/or diagnostic biomarkers for a variety diseases, given the fact that these changes can occur much earlier than when the disease actually manifests itself in the system and would thereby help in improving patient outcomes [2, 3, 7, 9, 17, 18]. In addition to this, given the reversible nature of these marks, several epi-drugs—epigenetic drugs, chemical compounds that alter the chromatin and DNA structure and could reactivate epigenetically silenced genes—are being developed to specifically target diseases [19–21].
2 Epigenetic biomarkers The prevalence of complex lifestyle associated disorders including cancer, type 2 diabetes mellitus (T2DM), cardiovascular diseases, etc., is increasing worldwide [22, 23]. This increased prevalence has Prognostic Epigenetics. https://doi.org/10.1016/B978-0-12-814259-2.00016-9 © 2019 Elsevier Inc. All rights reserved.
397
398
Chapter 15 Challenges and prospects in epigenetic studies
also been coupled with a considerable economic burden both for the patients and health-care systems. Most of these diseases, like T2DM and cardiovascular disease, are silent and go unnoticed till the disease manifests in the system [24, 25]. Part of the problem with these disorders is the lack of good diagnostic tests that could help predict the susceptibility of an individual toward developing disease [26]. These concerns together have raised the need for designing cost effective and minimally invasive tests for the screening of population for identification of individuals are at risk much before the disease develops and/or the patient becomes symptomatic. In case of cancers, for example, surveillance of high-risk patients, identified through population screening, would aid in the earlier diagnosis of cancer, much before the tumor growth and spread via metastasis. This approach would not only help in reducing the morbidity but also allow for less invasive treatment, associated with lesser side effects and complications, to the patient. In this regard, dysregulation of the epigenome has been identified as the primary event associated with many complex diseases [27]. In addition to this, as mentioned before as well, epigenetic modifications can change during the different phases of a disease, relapse, or during therapy [28–30]. Thus, measuring the epigenetic biomarkers could act as a promising tool and could greatly help advance clinical practice. A few representative examples citing the use of epigenetic biomarkers in different contexts have been described in the following subsections.
2.1 Early diagnosis, classification, and prognosis Colorectal cancer (CRC) is the third most common cause of cancer and is one of the leading causes of cancer-related mortality worldwide. CRC has been shown to develop from precancerous polyps in the colon/rectum and can be prevented and cured if diagnosed early by the removal of the polyp [31]. Therefore, a reliable screening test that can diagnose CRC before the development of the polyp or in its early precancerous stages would allow for early intervention that would greatly help in reducing the mortality and morbidity associated with the disease. The FDA has approved certain epigenetic markers for the CRC that have been launched in the market. For example, ColoSure test kit (developed by Laboratory Corporation of America) is a commercially available kit that is used for screening CRC in the United States with a specificity and sensitivity for CRC cancer as 53%–86.9% and 72.5%–83%, respectively, from fecal samples [31, 32]. This kit relies on the identification of hypermethylation of Vimentin gene, found to be hypermethylated in 53%–84% of CRC patients [33]. Likewise, ColoVantage Home is a fecal immunochemical test kit that has been used for screening purposes in Australia and New Zealand wherein methylated SPET9 gene has been used as a marker for CRC identification [34]. Likewise, Cologuard detects the methylation of NDRG4 promoter as a potential biomarker for the detection of colon cancer and large adenomas [31]. OncoGxOne Plus panel from Rosetta Genomics (http://www.rosettagenomics.com/) uses next- generation sequencing and targets 333 cancer-specific genes for detection of primary and metastatic liver cancers and intratumor heterogeneity [35]. In addition to this, miRNA-based test kits are available from Rosetta genomics that have been helpful in detecting cancer, including kidney tumors, lung, and thyroid cancer from body fluids such as urine, saliva, and serum. For kidney tumors, a panel of 24 miRNAs has been used to differentiate between four different types of kidney tumor, such as namely papillary (chromaphil) renal cell carcinoma (RCC), clear cell RCC, oncocytoma, and chromophobe RCC, and also to determine the therapy for these patients [36, 37]. Likewise, the miRNA-based Rosetta lung cancer test kit displays 93.7% sensitivity and 98% specificity for the identification of four subtypes of lung cancer [36, 38].
3 Major challenges in epigenetic studies
399
Among the different histone modifications, the lack of histone H4K20 trimethylation has also been proposed as a biomarker for early detection and therapeutic approaches to lung cancer [39]. Histone H2A variant (H2AX) has been recently proposed as a promising prognostic biomarker for lung cancer [40]. In addition to this, the presence of circulating cell-free DNA (cfDNA) has been investigated to use as a potential biomarker in breast cancer diagnosis with a sensitivity and specificity of >90% [41].
2.2 Disease progression As mentioned before, the management of diseases will be easier and more efficient if detected earlier as the severity of the disease increases with its progression through different stages. The rate of progression of different diseases, however, may vary. It has been noted that epigenetic modifications vary through the course of the disease and hence developing epigenetic markers that can predict disease progression could help in making clinical decisions. For example, ESR1 methylation detection from circulating cfDNA has been proposed for advanced breast cancer screening, metastasis, and for determining response to everolimus/exemestane treatment [42]. Aberrant epigenetic regulation of GABRP has been associated with the aggressive phenotype of ovarian cancer cells, and the methylation status of GABRP—963 CpG site has been proposed to be useful for predicting the metastatic potential in ovarian cancer patients [43].
2.3 Therapeutic response assessment and personalized medicine Due to the existence of cellular heterogeneity in diseases, existing therapies show different efficacies [44]. Therefore, information about the epigenomic state of a particular gene and/or gene cluster could help predict drug response and help determine the best combination of drugs that can be used for therapy. For example, O6-methylguaninine-DNA methyltransferase (MGMT) is a repair enzyme that repairs DNA damage caused due to DNA alkylating agents [45]. Methylation of MGMT promoter region has been associated with less DNA repair and hence, increases the sensitivity toward treatment with temozolomide—an alkylating agent, used as a first-line therapeutic agent for glioblastomas. MGMT activity has been shown to promote resistance to temozolomide; hence, MGMT promoter methylation could be used biomarker for determining personalized therapeutic options in patients with glioblastomas [46]. The therascreen MGMT Pyro kit (Qiagen) has been developed to identify methylation marks at 4 CpG sites human MGMT exon 1 from human FFPE samples [47]. Likewise, methylation of GSTP1 promoter has not only been correlated with survival in breast cancer patients, but also to determine the treatment response to Doxorubicin and DNA methyl transferase (DNMT) inhibitors [48, 49]. Hypermethylation of the BRCA1 gene promoter has been proposed to predict the sensitivity toward platinum-derived drugs as well as relapse and survival in ovarian cancer patients on cisplatin therapy [41, 50]. DNA methylation detection from serum samples has been proposed to use as an independent marker of drug response and survival in metastatic breast cancer patients [51, 52].
3 Major challenges in epigenetic studies leading to epigenetics-based biomarker development The epigenome is highly dynamic and responds quickly to intracellular and extracellular cues with the environment playing a major role [10–12]. In addition to this, the epigenetic marks are often t issue
400
Chapter 15 Challenges and prospects in epigenetic studies
and/or cell-type specific [53, 54] and can be confounded by several factors that might bias the interpretation of results obtained from such studies [55, 56]. A few of the confounding factors that limit the utility of epigenetic marks as biomarkers have been discussed in the following subsections.
3.1 Disease etiology Epigenetic markers have shown significant clinical potential for several complex disorders with multifactorial etiologies, including cancer [7, 28, 57]. However, there are certain concerns for developing epigenetic markers for such disorders which have multiple genes playing a role in the causation. For instance, different cancer types have their own cellular origin (lung, colon, ovary, etc.) and hence the epigenetic influences that have worked individually or synergistically to turn oncogenes ON might possibly be different [4, 7, 58]. Indeed, the expression of the oncogenes linked with the causation of a particular cancer can be said to be regulated by the coordinated effect of local genetic and epigenetic influences and thus would have a unique epigenetic code. For example, if attempts are being made to develop a biomarker chip that evaluates only the DNA methylation levels of a particular gene for a particular disease, the picture would be incomplete and would not reflect the global disease status. In addition to this, being complex in nature and involving multiple genes, it will be difficult to decide epigenetic marks in which gene (s) needs to be developed as biomarkers that may be used in clinical settings. To overcome this caveat, global DNA methylation status is being developed to assess global gene expression and disease phenotype [16, 59]. These tests however fail to identify the key genes and thus other epigenetic biomarkers need to be simultaneously tested. Next, there can be multiple epigenetic mechanisms operating to influence the expression of a particular gene. For instance, in addition to the DNA methylation in the promoter region, the expression of a particular gene can also be modulated by the histone modifications and the miRNA influence in that region of the genome. As an example, miR-29b has been shown to regulate the expression of DNMTs by directly targeting DNMT3a and indirectly DNMT1 [60] and these DNMTs in turn regulate the expression of the downstream genes. However, multiple testing would also lead to escalation of the time required to perform the tests and would also be associated with increased costs. In addition to this, before getting these tests in the clinical setting and prior to developing them as biomarkers, the results obtained from these analyses need to be further validated by performing molecular biology experiments (like in vitro luciferase reporter assays) along with mRNA and protein expression tests [16].
3.2 Lack of suitable tissue sample and tissue heterogeneity As has been mentioned before, epigenetic influences appear to be tissue specific [53, 54, 61]. Therefore, the epigenetic tests should ideally be designed by performing experiments on primary disease-affected tissues. However, getting a suitable sample by biopsy becomes challenging in several diseases, including neurological disorders, where tissue access is limited. In addition to this, for conducting a case-control trial with the required number of samples, obtaining tissue biopsies from healthy volunteers becomes challenging for such disorders. Hence, the use of a surrogate tissue that is easily accessible—peripheral blood, has been suggested with the assumption that few epigenetic changes in the tissues would also be reflected in the blood [16]. However, the suitability of the use of surrogate tissue is still under question [62, 63]. Moreover, the results obtained from such investigations would need to be v alidated in diseased
3 Major challenges in epigenetic studies
401
tissue as well before blood-based biomarkers are introduced into the clinical settings. This raises the need for large tissue biobanks for the validation and replication of such findings [16]. The other significant challenge working with biopsy samples is the heterogeneous nature of the cell population obtained. Even with whole blood, the scenario becomes complicated due to the presence of different cell types with distinct biological functions [55]. A mixed population of cells with varying epigenetic marks will have a dilution effect on the epigenetic marks [59]. In addition to this, the number of cell types in the heterogeneous population might be influenced by the disease status of the individual. Even though certain reference-based approaches have used to identify epigenetic signatures like DNA methylation, which are specific to a particular cell type and can be used for adjustment [55, 56], this heterogeneity could act as a potential confounder and bias the results obtained. In addition to this, the reference DNA methylation profiles are available for a few cell types, including peripheral blood mononuclear cells [6, 56, 64, 65], cord blood [66, 67], and prefrontal cortex [68]. Several referencefree algorithms such as FaST-LMM-EWASher, ReFACTOR, RefFreeEWAS, RefFreeCellMix, removing unwanted variation (RUV), and SVA have been developed to adjust for this cellular heterogeneity [16, 65]. However, the performance of these algorithms is highly dependent on the validity of model assumptions [69]. Liquid biopsies have come up as an attractive alternative in cancer diagnostics over repeated tissue biopsies simply because tumors shed DNA and cells which can be detected easily in the body fluids such as blood, urine, or saliva [70]. However, these tend to be expensive and there exists a need to develop methods that could not only prove less expensive but also would be faster, more sensitive and easier to perform with very little false discovery rate. For instance, with the current methodologies, the accurate detection of cancer in early stages does not occur as in most clinical practices the amount of blood and hence the amount of circulating cfDNA thus obtained could be limiting. Also, the amount of cfDNA could be less than 0.1% in such patients with small tumors [70]. In addition to this, cfDNA yield may be affected due to contamination from the lysed blood cells (if blood is not processed immediately after collection); the DNA isolation protocol used; and the instrument and technique used for its measurement [70–72]. Hence, gold-standard protocols need to be made and followed to implement the use of cfDNA for routine use in clinical diagnosis.
3.3 Study population heterogeneity and environmental influence The epigenome of an individual undergoes vigorous changes over the lifetime and thus can be greatly influenced by the age, sex, and ethnicity and by environmental influences including, diet, smoking status, exercise, exposure to drugs, pollutants, toxins, etc. [14, 73, 74]. Therefore, these factors need to be considered as potential confounders in an epidemiological setting while performing an epigeneticbased investigation. Indeed, the environmental influence in a particular disease setting can be rather complicated. For instance, age-associated changes in epigenetic marks including DNA methylation— referred to as epigenetic drift—have been a matter of debate for several years wherein most studies have reported them to be tissue specific [75–77]. However, a recent study by Zhu et al using matched multicell type and multi-tissue methylation profiles from the same individuals (after adjusting for celltype heterogeneity) have reported that possibly over ~70% of the epigenetic drift is shared between a significant number of different types of cell/tissues [55]. Therefore, in a clinical setting, the age of a patient needs to be considered prior to performing epigenetic testing.
402
Chapter 15 Challenges and prospects in epigenetic studies
In addition to this, additional parameters such as the definition of symptoms, treatment modalities used, duration of the disease, general health status, patient selection criteria, etc. are likely to confound the results obtained. For example, insufficiency and/or deficiency of micronutrients like Vitamin B12 (a cofactor required for nucleotide metabolism) has been known to induce cholesterol biosynthesis by limiting the S-adenosylmethionine (SAM) levels and modulating the methylation of SREBF1 and LDLR genes [78]. Therefore, to implement the correct usage of this epigenetic mark, that is, methylation of SREBF1 and LDLR genes, as biomarker for the development of metabolic syndrome, serum B12 level measurement needs to be made mandatory. Likewise, therapeutic drugs can influence the epigenetic modifications [15, 79, 80]. For instance, the antihypertensive drug—hydralazine—inhibits DNA methylation [80]. Most chemotherapeutic drugs induce DNA damage and affect DNA repair mechanisms and hence might induce changes in DNA methylation and other epigenetic modifications [81, 82]. Most cancer patients in the clinic are under the influence of these drugs. Hence, clinicians need to consider these as well when assessing the results of biomarker analysis from such patients. Most importantly, studies aiming at epigenetics-based biomarker discovery have been performed with an inadequate number of samples, lesser than those required for the validation [83, 84]. Therefore, for the successful implication of epigenetic-based markers in clinical use, large-scale epigenome-wide association studies (EWAS) studies using homogenous samples in population cohorts of different ethnicities are warranted.
3.4 Gene and environmental interactions In contrast to Mendelian disorders (wherein the phenotype is directly correlated to the phenotype) and infectious diseases (affected by the environment alone), a dynamic cross-talk exists between epigenetic modifications and genetic background in case of complex disorders. While on one hand, polymorphisms in and around genes can significantly impact the chromatin architecture, and expression and activity of epigenetic modifiers; epigenetic modifications in these genes can regulate the expression of genes [85, 86]. Mutations in several epigenetic modifiers have been reported in human cancers. For example, mutations in the histone methyltransferase—EZH2, and histone demethylase—LSD1, have been reported in breast and prostate cancer, respectively [18, 87, 88]. These mutations lead to aberrant DNA methylation, histone modifications and hence, increased genomic instability associated with cancer [4, 17]. Therefore, epigenetic marks should not be considered alone for defining precision medicine and/or biomarkers for complex diseases; rather, integration of the epigenetic and genetic maps needs to be performed while designing the same [5].
3.5 Establishment of the causal role of epigenetic changes Yet another challenge that exists for epigenetic epidemiology studies is to establish the causal role for the identified epigenetic modifications. While it has already been stated that epigenetic changes are rigorously occurring in the body and can be used as marks associated with the disease causation, these are vulnerable and can be influenced by the disease itself. This can complicate the situation and a dire need exists to separate the causal changes from those associated with the disease biology. In this regard, certain statistical approaches including causal inference test (CIT) and Mendelian randomization (MR) have been developed to distinguish between them [5, 6, 56, 89–91]. Both these methods use genetic variants as an instrument to infer the causal relationships between DNA methylation and the outcome [16].
4 Epigenetic therapy
403
In addition to this, some epigenetic marks tend to be more rigorously affected than others over time. Hence, multiple measurements overtime may be required to validate the significantly affected ones in these cases [92, 93].
3.6 Technological challenges The first and most important requirement is sample biobanks and patient registries that contain elaborate information. It should be ensured that the samples have been collected, stored, and processed as per the well-established standard operating protocols (SOPs) to eliminate any confounding effects on the results obtained [94, 95]. Secondly, even though different complementary assays have been developed for the study of epigenetic markers, there exists a great need for standardization and clinical validation. The differences in the detection levels, as well as the technological limitations associated with these assays have often led to noncomparable results being produced in different studies [96]. For instance, DNA methylation detection assays that depend on bisulfite conversion, PCR, and/or the presence of a restriction enzyme site could greatly be affected by the quality of DNA, the presence of inhibitors, primer design, and optimization [96, 97]. Hence, rigorous quality control and inclusion of appropriate controls would warrant the success of these tests to be developed in the clinical setting while keeping the false discovery rate low. While on one hand, assays including high-density DNA methylation microarrays tend to be expensive for routine testing; they are more useful for biomarker discovery on the other. In addition to this, rather than depending on nonquantitative or semiquantitative assays, recent assays are being developed that provide absolute quantitative data, like in case of DNA methylation, percentage of methylated DNA by employing PCR pyrosequencing, high-throughput whole-genome bisulfite sequencing, epiTYPER, DNA melting analysis, to name a few [98–100].
4 Epigenetic therapy The dynamic and reversible nature of epigenetic modifications make them a promising target for therapy wherein the possibility of reprogramming the epigenome and rewiring the cell landscape with the help of these drugs exists. In this regard, epi-drugs (epigenetic drugs)— compounds that alter the DNA and chromatin structure, promote disruption of transcriptional and posttranscriptional modifications and are capable of reactivating epigenetically silenced tumor suppressor and DNA repair genes—are being developed [20, 21, 101]. These drugs mostly target DNMTs and HDACs—the enzymes necessary for the maintenance and establishment of epigenetic marks. Several epigenetic therapies have been approved by the US FDA for cancer treatment and several of these compounds have been tested in preclinical as well as phase I, II, III, and IV clinical trials [20]. A few representative examples have been discussed below. The first epi-drug approved for cancer treatment—Vorinostat—is an HDAC inhibitor and has been used for the treatment of cutaneous T-cell lymphoma. It acts by enabling histone acetylation by blocking the catalytic sites of HDACs and thereby induces growth arrest and death in a wide range of transformed cells by altering the acetylation patterns [102]. The FDA approved DNMT inhibitors include cytidine analogs (azacytidine, decitabine) that act by inhibiting DNA methylation and restoration of
404
Chapter 15 Challenges and prospects in epigenetic studies
a berrantly silenced genes. These inhibitors have been successfully used for the treatment of all subtypes of myelodysplastic syndrome (MDS), other hematologic malignancies and solid tumors [20, 103]. miRNA supplementation, in diseases where they are downregulated, can potentially be used to restore the normal state. For example, miR-34—involved in regulating important cell cycle control and proliferation genes like MYC—has been reported to be silenced in several cancers [104]. Based on this observation, Synlogic Therapeutics have performed preclinical and phase I clinical trials with miR-34 (MRX34), and have found it to effectively reduce tumor size in colon cancer [105–107]. Likewise, miRNA inhibitor has been shown to be helpful in disease where they are upregulated. For example, the miR-122 repressor, miravirsen, have been successfully initiated into the clinical trial aiming at treatment of Hepatitis C infection [108, 109]. A locked nucleic acid (LNA) modified antisense oligonucleotide has been approved for phase I clinical trials of the drug MRG110 which aims at inhibiting the function of miR-92. miRagen is aiming it toward wound healing and heart failure [110].
5 Future perspectives and conclusions Epigenetic biomarkers hold a significant potential to be developed as biomarkers that can be used in the clinic. Although different epigenetic modifications—DNA methylation, histone modifications, ncRNAs—have been identified, there exists a need to learn more about the cross-links between these epigenetic processes and how they are regulated in normal as well as diseased condition. In addition to this, further improvements in the technologies that involve much-simplified sample processing steps, are high throughput and can be used to identify these modifications in a much lesser amount of time, are warranted [94]. For example, even though, next-generation technologies are being developed to study miRNA profiles [111], these tend to be expensive and difficult to apply in the clinical settings. In addition to this, a database needs to be built that is based on results obtained from EWAS studies carried out in subjects from ethnically different backgrounds. This database should also be able to categorize the epigenetic variations in the different phases of a disease (i.e., early-stage, mid-staged, and metastasis stages of a particular cancer, say breast cancer) in sex-matched age groups of patients. Information on complete epigenetic profiles throughout the different phases of the disease would aid in setting up criteria for evaluating clinical prognosis and more effective patient management. Similar information should also be available from a set of age- and sex-matched set of disease-free subjects (healthy volunteers or controls) from the same population. Along these lines, the International Human Epigenome Consortium (IHEC; http://ihec-epigenomes.org/welcome/) is being developed with the aim of providing free access to human epigenome maps (normal as well as diseased) to the research community [94]. This information would be useful in developing tools for clinical practice. Along similar lines, further exploratory research is required to understand the potential of epi-drugs that are capable of modifying aberrant epigenetic profiles in diseased cells and would promote a cell toward a healthy phenotype by stopping the progression of disease any further [19, 20].
Acknowledgments SS acknowledges the funding from Ramalingaswami fellowship (BT/RLF/Re-entry/11/2012; Department of Biotechnology—DBT, Government of India) and University Grants Commission (UGC, Government of India
References
405
F.4-5(18-FRP)(IV-Cycle)/2017(BSR)). SS lab has been generously supported by Research and Development grant and DST-Purse grant to the Department of Biotechnology, SPPU; and Board of College and University Development (BCUD) grant (SPPU) to SS; and UPE Phase II grant to SPPU.
References [1] Y. Hasin, M. Seldin, A. Lusis, Multi-omics approaches to disease, Genome Biol. 18 (1) (2017) 83. [2] S. Wahl, et al., Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity, Nature 541 (7635) (2017) 81–86. [3] M. Verma, et al., Genetic and epigenetic biomarkers in cancer: improving diagnosis, risk assessment, and disease stratification, Mol. Diagn. Ther. 10 (1) (2006) 1–15. [4] J.S. You, P.A. Jones, Cancer genetics and epigenetics: two sides of the same coin? Cancer Cell 22 (1) (2012) 9–20. [5] S. Costantino, et al., Epigenetics and precision medicine in cardiovascular patients: from basic concepts to the clinical arena, Eur. Heart J. 39 (47) (2018) 4150–4158. [6] X. Hong, et al., Genome-wide association study identifies peanut allergy-specific loci and evidence of epigenetic mediation in US children, Nat. Commun. 6 (2015) 6304. [7] A. Portela, M. Esteller, Epigenetic modifications and human disease, Nat. Biotechnol. 28 (10) (2010) 1057–1068. [8] H. Johansson, et al., Interactions between environmental pollutants and genetic susceptibility in asthma risk, Curr. Opin. Immunol. 60 (2019) 156–162. [9] A.E.A. Surace, C.M. Hedrich, The role of epigenetics in autoimmune/inflammatory disease, Front. Immunol. 10 (2019) 1525. [10] C. Pinel, B. Prainsack, C. McKevitt, Markers as mediators: a review and synthesis of epigenetics literature, Biosocieties 13 (1) (2019) 276–303. [11] M. Szyf, The dynamic epigenome and its implications in toxicology, Toxicol. Sci. 100 (1) (2007) 7–23. [12] L. Mirbahai, J.K. Chipman, Epigenetic memory of environmental organisms: a reflection of lifetime stressor exposures, Mutat. Res. Genet. Toxicol. Environ. Mutagen. 764-765 (2014) 10–17. [13] G. Almouzni, et al., Relationship between genome and epigenome—challenges and requirements for future research, BMC Genom. 15 (2014) 487. [14] R. Feil, M.F. Fraga, Epigenetics and the environment: emerging patterns and implications, Nat. Rev. Genet. 13 (2) (2012) 97–109. [15] A. Jangra, et al., Epigenetic modifications, alcoholic brain and potential drug targets, Ann. Neurosci. 23 (4) (2016) 246–260. [16] Z. Jin, Y. Liu, DNA methylation in human diseases, Genes Dis. 5 (1) (2018) 1–8. [17] M. Rodriguez-Paredes, M. Esteller, Cancer epigenetics reaches mainstream oncology, Nat. Med. 17 (3) (2011) 330–339. [18] D.P. Tsang, A.S. Cheng, Epigenetic regulation of signaling pathways in cancer: role of the histone methyltransferase EZH2, J. Gastroenterol. Hepatol. 26 (1) (2011) 19–27. [19] L. Gherardini, et al., Targeting cancer with epi-drugs: a precision medicine perspective, Curr. Pharm. Biotechnol. 17 (10) (2016) 856–865. [20] C.L. Miranda Furtado, et al., Epidrugs: targeting epigenetic marks in cancer treatment, Epigenetics (2019) 1–13. [21] R. Mazzone, et al., Epi-drugs in combination with immunotherapy: a new avenue to improve anticancer efficacy, Clin. Epigenetics 9 (2017) 59. [22] I. Martin-Timon, et al., Type 2 diabetes and cardiovascular disease: have all risk factors the same strength? World J. Diabetes 5 (4) (2014) 444–470.
406
Chapter 15 Challenges and prospects in epigenetic studies
[23] M. Gowshall, S.D. Taylor-Robinson, The increasing prevalence of non-communicable diseases in lowmiddle income countries: the view from Malawi, Int. J. Gen. Med. 11 (2018) 255–264. [24] B.M. Leon, T.M. Maddox, Diabetes and cardiovascular disease: epidemiology, biological mechanisms, treatment recommendations and future research, World J. Diabetes 6 (13) (2015) 1246–1258. [25] S. Sharma, A.B. Mathew, J. Chugh, miRNAs: nanomachines that micromanage the pathophysiology of diabetes mellitus, Adv. Clin. Chem. 82 (2017) 199–264. [26] P. Bhatia, et al., miRNAs: early prognostic biomarkers for Type 2 diabetes mellitus? Biomark Med. 9 (10) (2015) 1025–1040. [27] W.J. Locke, et al., Coordinated epigenetic remodelling of transcriptional networks occurs during early breast carcinogenesis, Clin. Epigenetics 7 (2015) 52. [28] M.L. Thomas, P. Marcato, Epigenetic modifications as biomarkers of tumor development, therapy response, and recurrence across the cancer care continuum, Cancers (Basel) 10 (4) (2018). [29] D.P. Potaczek, et al., Epigenetics and allergy: from basic mechanisms to clinical applications, Epigenomics 9 (4) (2017) 539–571. [30] D.E. Handy, R. Castro, J. Loscalzo, Epigenetic modifications: basic mechanisms and role in cardiovascular disease, Circulation 123 (19) (2011) 2145–2156. [31] L. Hamzehzadeh, M. Yousefi, S.H. Ghaffari, Colorectal cancer screening: a comprehensive review to recent non-invasive methods, Int. J. Hematol. Oncol. Stem Cell Res. 11 (3) (2017) 250–261. [32] R.M. Ned, S. Melillo, M. Marrone, Fecal DNA testing for colorectal cancer screening: the ColoSure test, PLoS Curr. 3 (2011) RRN1220. [33] W.D. Chen, et al., Detection in fecal DNA of colon cancer-specific methylation of the nonexpressed vimentin gene, J. Natl. Cancer Inst. 97 (15) (2005) 1124–1132. [34] J. Nian, et al., Diagnostic accuracy of methylated SEPT9 for blood-based colorectal cancer detection: a systematic review and meta-analysis, Clin. Transl. Gastroenterol. 8 (1) (2017) e216. [35] Y.W. Lu, et al., Colorectal cancer genetic heterogeneity delineated by multi-region sequencing, PLoS One 11 (3) (2016) e0152673. [36] P. Costa-Pinheiro, et al., Diagnostic and prognostic epigenetic biomarkers in cancer, Epigenomics 7 (6) (2015) 1003–1015. [37] Y. Spector, et al., Development and validation of a microRNA-based diagnostic assay for classification of renal cell carcinomas, Mol. Oncol. 7 (3) (2013) 732–738. [38] S. Gilad, et al., Classification of the four main types of lung cancer using a microRNA-based diagnostic assay, J. Mol. Diagn. 14 (5) (2012) 510–517. [39] A. Van Den Broeck, et al., Loss of histone H4K20 trimethylation occurs in preneoplasia and influences prognosis of non-small cell lung cancer, Clin. Cancer Res. 14 (22) (2008) 7237–7245. [40] D. Matthaios, et al., H2AX a promising biomarker for lung cancer: a review, Cancer Invest. 31 (9) (2013) 582–599. [41] M.M. Kronfol, et al., The role of epigenomics in personalized medicine, Expert Rev. Precis. Med. Drug Dev. 2 (1) (2017) 33–45. [42] S. Mastoraki, et al., ESR1 methylation: a liquid biopsy-based epigenetic assay for the follow-up of patients with metastatic breast cancer receiving endocrine treatment, Clin. Cancer Res. 24 (6) (2018) 1500–1510. [43] H.Y. Sung, et al., Aberrant epigenetic regulation of GABRP associates with aggressive phenotype of ovarian cancer, Exp. Mol. Med. 49 (5) (2017) e335. [44] M.D. Brooks, M.L. Burness, M.S. Wicha, Therapeutic implications of cellular heterogeneity and plasticity in breast cancer, Cell Stem Cell 17 (3) (2015) 260–271. [45] C.H. Fan, et al., O6-methylguanine DNA methyltransferase as a promising target for the treatment of temozolomide-resistant gliomas, Cell Death Dis. 4 (2013) e876. [46] N. Thon, S. Kreth, F.W. Kreth, Personalized treatment strategies in glioblastoma: MGMT promoter methylation status, Onco. Targets Ther. 6 (2013) 1363–1372.
References
407
[47] A. Luquain, et al., Analysis of MGMT methylation with the therascreen((R)) MGMT Pyro((R)) Kit (Qiagen). A method verification, Ann. Biol. Clin. (Paris) 73 (6) (2015) 665–670. [48] K. Chiam, et al., GSTP1 DNA methylation and expression status is indicative of 5-aza-2'-deoxycytidine efficacy in human prostate cancer cells, PLoS One 6 (9) (2011) e25634. [49] E. Dejeux, et al., DNA methylation profiling in doxorubicin treated primary locally advanced breast tumours identifies novel genes associated with survival and treatment response, Mol. Cancer 9 (2010) 68. [50] O.A. Stefansson, et al., BRCA1 epigenetic inactivation predicts sensitivity to platinum-based chemotherapy in breast and ovarian cancer, Epigenetics 7 (11) (2012) 1225–1229. [51] K. Visvanathan, et al., Monitoring of serum DNA methylation as an early independent marker of response and survival in metastatic breast cancer: TBCRC 005 prospective biomarker study, J. Clin. Oncol. 35 (7) (2017) 751–758. [52] B. Downs, et al., DNA methylation markers for breast cancer detection in the developing world. Clin Cancer Res. (2019) https://doi.org/10.1158/1078-0432.CCR-18-3277. [53] E. Cazaly, et al., Making sense of the epigenome using data integration approaches, Front. Pharmacol. 10 (2019) 126. [54] I. Mendizabal, et al., Cell type-specific epigenetic links to schizophrenia risk in the brain, Genome Biol. 20 (1) (2019) 135. [55] T. Zhu, et al., Cell and tissue type independent age-associated DNA methylation changes are not rare but common, Aging (Albany NY) 10 (11) (2018) 3541–3557. [56] Y. Liu, et al., Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis, Nat. Biotechnol. 31 (2) (2013) 142–147. [57] E.E. Eichler, et al., Missing heritability and strategies for finding the underlying causes of complex disease, Nat. Rev. Genet. 11 (6) (2010) 446–450. [58] S. Kriaucionis, N. Heintz, The nuclear DNA base 5-hydroxymethylcytosine is present in Purkinje neurons and the brain, Science 324 (5929) (2009) 929–930. [59] S. Kurdyukov, M. Bullock, DNA methylation analysis: choosing the right method, Biology (Basel) 5 (1) (2016). [60] R. Garzon, et al., MicroRNA-29b induces global DNA hypomethylation and tumor suppressor gene reexpression in acute myeloid leukemia by targeting directly DNMT3A and 3B and indirectly DNMT1, Blood 113 (25) (2009) 6411–6418. [61] M. Gutierrez-Arcelus, et al., Tissue-specific effects of genetic and epigenetic variation on gene regulation and splicing, PLoS Genet. 11 (1) (2015) e1004958. [62] E. Hannon, et al., Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes, Epigenetics 10 (11) (2015) 1024–1032. [63] P. Farre, et al., Concordant and discordant DNA methylation signatures of aging in human blood and brain, Epigenet. Chromatin 8 (2015) 19. [64] B.R. Joubert, et al., DNA methylation in newborns and maternal smoking in pregnancy: genome-wide consortium meta-analysis, Am. J. Hum. Genet. 98 (4) (2016) 680–696. [65] A. Kaushal, et al., Comparison of different cell type correction methods for genome-scale epigenetics studies, BMC Bioinform. 18 (1) (2017) 216. [66] A. Cardenas, et al., Validation of a DNA methylation reference panel for the estimation of nucleated cells types in cord blood, Epigenetics 11 (11) (2016) 773–779. [67] K.M. Bakulski, et al., DNA methylation of cord blood cell types: applications for mixed cell birth studies, Epigenetics 11 (5) (2016) 354–362. [68] J. Guintivano, M.J. Aryee, Z.A. Kaminsky, A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression, Epigenetics 8 (3) (2013) 290–302.
408
Chapter 15 Challenges and prospects in epigenetic studies
[69] A.E. Teschendorff, S.C. Zheng, Cell-type deconvolution in epigenome-wide association studies: a review and recommendations, Epigenomics 9 (5) (2017) 757–768. [70] W. Gai, K. Sun, Epigenetic biomarkers in cell-free DNA and applications in liquid biopsy, Genes (Basel) 10 (1) (2019). [71] C. Perez-Barrios, et al., Comparison of methods for circulating cell-free DNA isolation using blood from cancer patients: impact on biomarker testing, Transl. Lung Cancer Res. 5 (6) (2016) 665–672. [72] L. Sorber, et al., A comparison of cell-free DNA isolation kits: isolation and quantification of cell-free DNA in plasma, J. Mol. Diagn. 19 (1) (2017) 162–168. [73] C. Tiffon, The impact of nutrition and environmental epigenetics on human health and disease, Int. J. Mol. Sci. 19 (11) (2018). [74] C.J. Marsit, Influence of environmental exposure on human epigenetic regulation, J. Exp. Biol. 218 (Pt 1) (2015) 71–79. [75] B.C. Christensen, et al., Aging and environmental exposures alter tissue-specific DNA methylation dependent upon CpG island context, PLoS Genet. 5 (8) (2009) e1000602. [76] M.F. Fraga, et al., Epigenetic differences arise during the lifetime of monozygotic twins, Proc. Natl. Acad. Sci. U. S. A. 102 (30) (2005) 10604–10609. [77] N. Ahuja, J.P. Issa, Aging, methylation and cancer, Histol. Histopathol. 15 (3) (2000) 835–842. [78] A. Adaikalakoteswari, et al., Vitamin B12 insufficiency induces cholesterol biosynthesis by limiting s-adenosylmethionine and modulating the methylation of SREBF1 and LDLR genes, Clin. Epigenetics 7 (2015) 14. [79] T. Heinbockel, A.B. Csoka, Epigenetic effects of drugs of abuse, Int. J. Environ. Res. Public Health 15 (10) (2018). [80] A.B. Csoka, M. Szyf, Epigenetic side-effects of common pharmaceuticals: a potential new field in medicine and pharmacology, Med. Hypotheses 73 (5) (2009) 770–780. [81] H.M. O'Hagan, et al., Oxidative damage targets complexes containing DNA methyltransferases, SIRT1, and polycomb members to promoter CpG Islands, Cancer Cell 20 (5) (2011) 606–619. [82] A.A. Emran, et al., Commonly integrated epigenetic modifications of differentially expressed genes lead to adaptive resistance in cancer, Epigenomics 11 (7) (2019) 732–737. [83] P.A. Jones, J.P. Issa, S. Baylin, Targeting the cancer epigenome for therapy, Nat. Rev. Genet. 17 (10) (2016) 630–641. [84] T. Nieto, et al., A systematic review of epigenetic biomarkers in progression from non-dysplastic Barrett's oesophagus to oesophageal adenocarcinoma, BMJ Open 8 (6) (2018) e020427. [85] D. Zhang, et al., Genetic control of individual differences in gene-specific methylation in human brain, Am. J. Hum. Genet. 86 (3) (2010) 411–419. [86] S. Costantino, F. Paneni, F. Cosentino, Targeting chromatin remodeling to prevent cardiovascular disease in diabetes, Curr. Pharm. Biotechnol. 16 (6) (2015) 531–543. [87] A. Chase, N.C. Cross, Aberrations of EZH2 in cancer, Clin. Cancer Res. 17 (9) (2011) 2613–2618. [88] D. Rotili, A. Mai, Targeting histone demethylases: a new avenue for the fight against cancer, Genes Cancer 2 (6) (2011) 663–679. [89] C.L. Relton, G. Davey Smith, Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease, Int. J. Epidemiol. 41 (1) (2012) 161–176. [90] M.M. Mendelson, et al., Association of body mass index with DNA methylation and gene expression in blood cells and relations to cardiometabolic disease: a Mendelian randomization approach, PLoS Med. 14 (1) (2017) e1002215. [91] G. Hemani, K. Tilling, G. Davey Smith, Orienting the causal relationship between imprecisely measured traits using GWAS summary data, PLoS Genet. 13 (11) (2017) e1007081. [92] C. Luo, P. Hajkova, J.R. Ecker, Dynamic DNA methylation: in the right place at the right time, Science 361 (6409) (2018) 1336–1340.
References
409
[93] M.J. Ziller, et al., Charting a dynamic DNA methylation landscape of the human genome, Nature 500 (7463) (2013) 477–481. [94] S.O.M. Dyke, et al., Points-to-consider on the return of results in epigenetic research, Genome Med. 11 (1) (2019) 31. [95] L. Peiró-Chova, et al., Chapter 2—the importance of biobanks in epigenetic studies, in: J.L. García-Giménez (Ed.), Epigenetic Biomarkers and Diagnostics, Academic Press, Boston, 2016, pp. 19–35. [96] A.T. Lorincz, The promise and the problems of epigenetics biomarkers in cancer, Expert Opin. Med. Diagn. 5 (5) (2011) 375–379. [97] T.C. Lorenz, Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies, J. Vis. Exp. 63 (2012) e3998. [98] N. Vasiljevic, et al., Absolute quantitation of DNA methylation of 28 candidate genes in prostate cancer using pyrosequencing, Dis. Markers 30 (4) (2011) 151–161. [99] J.L. Brandsma, et al., Distinct human papillomavirus type 16 methylomes in cervical cells at different stages of premalignancy, Virology 389 (1-2) (2009) 100–107. [100] M. Li, et al., Sensitive digital quantification of DNA methylation in clinical samples, Nat. Biotechnol. 27 (9) (2009) 858–863. [101] R. Salarinia, et al., Epi-drugs and Epi-miRs: moving beyond current cancer therapies, Curr. Cancer Drug Targets 16 (9) (2016) 773–788. [102] V.M. Richon, J. Garcia-Vargas, J.S. Hardwick, Development of vorinostat: current applications and future perspectives for cancer therapy, Cancer Lett. 280 (2) (2009) 201–210. [103] E. Kaminskas, et al., FDA drug approval summary: azacitidine (5-azacytidine, Vidaza) for injectable suspension, Oncologist 10 (3) (2005) 176–182. [104] A.A. Farooqi, S. Tabassum, A. Ahmad, MicroRNA-34a: a versatile regulator of myriads of targets in different cancers, Int. J. Mol. Sci. 18 (10) (2017). [105] S. Gaur, et al., Chitosan nanoparticle-mediated delivery of miRNA-34a decreases prostate tumor growth in the bone and its expression induces non-canonical autophagy, Oncotarget 6 (30) (2015) 29161–29177. [106] H. Tazawa, et al., Tumor-suppressive miR-34a induces senescence-like growth arrest through modulation of the E2F pathway in human colon cancer cells, Proc. Natl. Acad. Sci. U. S. A. 104 (39) (2007) 15472–15477. [107] M.S. Beg, et al., Phase I study of MRX34, a liposomal miR-34a mimic, administered twice weekly in patients with advanced solid tumors, Invest. New Drugs 35 (2) (2017) 180–188. [108] R.E. Lanford, et al., Therapeutic silencing of microRNA-122 in primates with chronic hepatitis C virus infection, Science 327 (5962) (2010) 198–201. [109] H.L. Janssen, et al., Treatment of HCV infection by targeting microRNA, N. Engl. J. Med. 368 (18) (2013) 1685–1694. [110] J. Hanna, G.S. Hossain, J. Kocerha, The potential for microRNA therapeutics and clinical research, Front. Genet. 10 (2019) 478. [111] J. Liu, et al., Next generation sequencing for profiling expression of miRNAs: technical progress and applications in drug development, J. Biomed. Sci. Eng. 4 (10) (2011) 666–676.
Conclusions and perspectives: Major challenges and future prospects for prognostic epigenetics
15
Shilpy Sharma Department of Biotechnology, Savitribai Phule Pune University (Formerly University of Pune), Pune, India
1 Introduction With the advent of the human genome-sequencing era, it became clear that genetic variation alone cannot be used to predict susceptibility toward developing complex multigene disorders [1, 2]. As discussed through the length of this book, epigenetics—the study of any potentially heritable changes in gene expression or phenotype that occurs without any changes in the underlying DNA sequence—has a bigger role to play in regulating cellular pathways. Epigenetic modifications have not only shown to be associated with the onset but also with the progression and maintenance of several life-threatening and debilitating complex disorders including cancer, asthma, allergy, autoimmune diseases, cardiovascular diseases, diabetes, adiposity, etc. [2–9]. Interestingly, the epigenome, that is, the complete array of chemical modifications to DNA and histone proteins that regulate the expression of genes, is highly dynamic and can be greatly influenced by the intracellular and extracellular environment [10–13]. Epigenetic modifications may occur at the level of DNA (methylation of promoter regions resulting in gene silencing); could affect higher order of structural organization of DNA by causing posttranslational modifications in histones; mediate chromatin remodeling; or could regulate gene expression through noncoding RNAs (ncRNAs) [7, 14–16]. An accurate, yet reproducible measure of these changes could be used to reflect DNA regulation in a system. Hence, researchers and clinicians worldwide are making several attempts to develop these epigenetic marks as prognostic and/or diagnostic biomarkers for a variety diseases, given the fact that these changes can occur much earlier than when the disease actually manifests itself in the system and would thereby help in improving patient outcomes [2, 3, 7, 9, 17, 18]. In addition to this, given the reversible nature of these marks, several epi-drugs—epigenetic drugs, chemical compounds that alter the chromatin and DNA structure and could reactivate epigenetically silenced genes—are being developed to specifically target diseases [19–21].
2 Epigenetic biomarkers The prevalence of complex lifestyle associated disorders including cancer, type 2 diabetes mellitus (T2DM), cardiovascular diseases, etc., is increasing worldwide [22, 23]. This increased prevalence has Prognostic Epigenetics. https://doi.org/10.1016/B978-0-12-814259-2.00016-9 © 2019 Elsevier Inc. All rights reserved.
397
398
Chapter 15 Challenges and prospects in epigenetic studies
also been coupled with a considerable economic burden both for the patients and health-care systems. Most of these diseases, like T2DM and cardiovascular disease, are silent and go unnoticed till the disease manifests in the system [24, 25]. Part of the problem with these disorders is the lack of good diagnostic tests that could help predict the susceptibility of an individual toward developing disease [26]. These concerns together have raised the need for designing cost effective and minimally invasive tests for the screening of population for identification of individuals are at risk much before the disease develops and/or the patient becomes symptomatic. In case of cancers, for example, surveillance of high-risk patients, identified through population screening, would aid in the earlier diagnosis of cancer, much before the tumor growth and spread via metastasis. This approach would not only help in reducing the morbidity but also allow for less invasive treatment, associated with lesser side effects and complications, to the patient. In this regard, dysregulation of the epigenome has been identified as the primary event associated with many complex diseases [27]. In addition to this, as mentioned before as well, epigenetic modifications can change during the different phases of a disease, relapse, or during therapy [28–30]. Thus, measuring the epigenetic biomarkers could act as a promising tool and could greatly help advance clinical practice. A few representative examples citing the use of epigenetic biomarkers in different contexts have been described in the following subsections.
2.1 Early diagnosis, classification, and prognosis Colorectal cancer (CRC) is the third most common cause of cancer and is one of the leading causes of cancer-related mortality worldwide. CRC has been shown to develop from precancerous polyps in the colon/rectum and can be prevented and cured if diagnosed early by the removal of the polyp [31]. Therefore, a reliable screening test that can diagnose CRC before the development of the polyp or in its early precancerous stages would allow for early intervention that would greatly help in reducing the mortality and morbidity associated with the disease. The FDA has approved certain epigenetic markers for the CRC that have been launched in the market. For example, ColoSure test kit (developed by Laboratory Corporation of America) is a commercially available kit that is used for screening CRC in the United States with a specificity and sensitivity for CRC cancer as 53%–86.9% and 72.5%–83%, respectively, from fecal samples [31, 32]. This kit relies on the identification of hypermethylation of Vimentin gene, found to be hypermethylated in 53%–84% of CRC patients [33]. Likewise, ColoVantage Home is a fecal immunochemical test kit that has been used for screening purposes in Australia and New Zealand wherein methylated SPET9 gene has been used as a marker for CRC identification [34]. Likewise, Cologuard detects the methylation of NDRG4 promoter as a potential biomarker for the detection of colon cancer and large adenomas [31]. OncoGxOne Plus panel from Rosetta Genomics (http://www.rosettagenomics.com/) uses next- generation sequencing and targets 333 cancer-specific genes for detection of primary and metastatic liver cancers and intratumor heterogeneity [35]. In addition to this, miRNA-based test kits are available from Rosetta genomics that have been helpful in detecting cancer, including kidney tumors, lung, and thyroid cancer from body fluids such as urine, saliva, and serum. For kidney tumors, a panel of 24 miRNAs has been used to differentiate between four different types of kidney tumor, such as namely papillary (chromaphil) renal cell carcinoma (RCC), clear cell RCC, oncocytoma, and chromophobe RCC, and also to determine the therapy for these patients [36, 37]. Likewise, the miRNA-based Rosetta lung cancer test kit displays 93.7% sensitivity and 98% specificity for the identification of four subtypes of lung cancer [36, 38].
3 Major challenges in epigenetic studies
399
Among the different histone modifications, the lack of histone H4K20 trimethylation has also been proposed as a biomarker for early detection and therapeutic approaches to lung cancer [39]. Histone H2A variant (H2AX) has been recently proposed as a promising prognostic biomarker for lung cancer [40]. In addition to this, the presence of circulating cell-free DNA (cfDNA) has been investigated to use as a potential biomarker in breast cancer diagnosis with a sensitivity and specificity of >90% [41].
2.2 Disease progression As mentioned before, the management of diseases will be easier and more efficient if detected earlier as the severity of the disease increases with its progression through different stages. The rate of progression of different diseases, however, may vary. It has been noted that epigenetic modifications vary through the course of the disease and hence developing epigenetic markers that can predict disease progression could help in making clinical decisions. For example, ESR1 methylation detection from circulating cfDNA has been proposed for advanced breast cancer screening, metastasis, and for determining response to everolimus/exemestane treatment [42]. Aberrant epigenetic regulation of GABRP has been associated with the aggressive phenotype of ovarian cancer cells, and the methylation status of GABRP—963 CpG site has been proposed to be useful for predicting the metastatic potential in ovarian cancer patients [43].
2.3 Therapeutic response assessment and personalized medicine Due to the existence of cellular heterogeneity in diseases, existing therapies show different efficacies [44]. Therefore, information about the epigenomic state of a particular gene and/or gene cluster could help predict drug response and help determine the best combination of drugs that can be used for therapy. For example, O6-methylguaninine-DNA methyltransferase (MGMT) is a repair enzyme that repairs DNA damage caused due to DNA alkylating agents [45]. Methylation of MGMT promoter region has been associated with less DNA repair and hence, increases the sensitivity toward treatment with temozolomide—an alkylating agent, used as a first-line therapeutic agent for glioblastomas. MGMT activity has been shown to promote resistance to temozolomide; hence, MGMT promoter methylation could be used biomarker for determining personalized therapeutic options in patients with glioblastomas [46]. The therascreen MGMT Pyro kit (Qiagen) has been developed to identify methylation marks at 4 CpG sites human MGMT exon 1 from human FFPE samples [47]. Likewise, methylation of GSTP1 promoter has not only been correlated with survival in breast cancer patients, but also to determine the treatment response to Doxorubicin and DNA methyl transferase (DNMT) inhibitors [48, 49]. Hypermethylation of the BRCA1 gene promoter has been proposed to predict the sensitivity toward platinum-derived drugs as well as relapse and survival in ovarian cancer patients on cisplatin therapy [41, 50]. DNA methylation detection from serum samples has been proposed to use as an independent marker of drug response and survival in metastatic breast cancer patients [51, 52].
3 Major challenges in epigenetic studies leading to epigenetics-based biomarker development The epigenome is highly dynamic and responds quickly to intracellular and extracellular cues with the environment playing a major role [10–12]. In addition to this, the epigenetic marks are often t issue
400
Chapter 15 Challenges and prospects in epigenetic studies
and/or cell-type specific [53, 54] and can be confounded by several factors that might bias the interpretation of results obtained from such studies [55, 56]. A few of the confounding factors that limit the utility of epigenetic marks as biomarkers have been discussed in the following subsections.
3.1 Disease etiology Epigenetic markers have shown significant clinical potential for several complex disorders with multifactorial etiologies, including cancer [7, 28, 57]. However, there are certain concerns for developing epigenetic markers for such disorders which have multiple genes playing a role in the causation. For instance, different cancer types have their own cellular origin (lung, colon, ovary, etc.) and hence the epigenetic influences that have worked individually or synergistically to turn oncogenes ON might possibly be different [4, 7, 58]. Indeed, the expression of the oncogenes linked with the causation of a particular cancer can be said to be regulated by the coordinated effect of local genetic and epigenetic influences and thus would have a unique epigenetic code. For example, if attempts are being made to develop a biomarker chip that evaluates only the DNA methylation levels of a particular gene for a particular disease, the picture would be incomplete and would not reflect the global disease status. In addition to this, being complex in nature and involving multiple genes, it will be difficult to decide epigenetic marks in which gene (s) needs to be developed as biomarkers that may be used in clinical settings. To overcome this caveat, global DNA methylation status is being developed to assess global gene expression and disease phenotype [16, 59]. These tests however fail to identify the key genes and thus other epigenetic biomarkers need to be simultaneously tested. Next, there can be multiple epigenetic mechanisms operating to influence the expression of a particular gene. For instance, in addition to the DNA methylation in the promoter region, the expression of a particular gene can also be modulated by the histone modifications and the miRNA influence in that region of the genome. As an example, miR-29b has been shown to regulate the expression of DNMTs by directly targeting DNMT3a and indirectly DNMT1 [60] and these DNMTs in turn regulate the expression of the downstream genes. However, multiple testing would also lead to escalation of the time required to perform the tests and would also be associated with increased costs. In addition to this, before getting these tests in the clinical setting and prior to developing them as biomarkers, the results obtained from these analyses need to be further validated by performing molecular biology experiments (like in vitro luciferase reporter assays) along with mRNA and protein expression tests [16].
3.2 Lack of suitable tissue sample and tissue heterogeneity As has been mentioned before, epigenetic influences appear to be tissue specific [53, 54, 61]. Therefore, the epigenetic tests should ideally be designed by performing experiments on primary disease-affected tissues. However, getting a suitable sample by biopsy becomes challenging in several diseases, including neurological disorders, where tissue access is limited. In addition to this, for conducting a case-control trial with the required number of samples, obtaining tissue biopsies from healthy volunteers becomes challenging for such disorders. Hence, the use of a surrogate tissue that is easily accessible—peripheral blood, has been suggested with the assumption that few epigenetic changes in the tissues would also be reflected in the blood [16]. However, the suitability of the use of surrogate tissue is still under question [62, 63]. Moreover, the results obtained from such investigations would need to be v alidated in diseased
3 Major challenges in epigenetic studies
401
tissue as well before blood-based biomarkers are introduced into the clinical settings. This raises the need for large tissue biobanks for the validation and replication of such findings [16]. The other significant challenge working with biopsy samples is the heterogeneous nature of the cell population obtained. Even with whole blood, the scenario becomes complicated due to the presence of different cell types with distinct biological functions [55]. A mixed population of cells with varying epigenetic marks will have a dilution effect on the epigenetic marks [59]. In addition to this, the number of cell types in the heterogeneous population might be influenced by the disease status of the individual. Even though certain reference-based approaches have used to identify epigenetic signatures like DNA methylation, which are specific to a particular cell type and can be used for adjustment [55, 56], this heterogeneity could act as a potential confounder and bias the results obtained. In addition to this, the reference DNA methylation profiles are available for a few cell types, including peripheral blood mononuclear cells [6, 56, 64, 65], cord blood [66, 67], and prefrontal cortex [68]. Several referencefree algorithms such as FaST-LMM-EWASher, ReFACTOR, RefFreeEWAS, RefFreeCellMix, removing unwanted variation (RUV), and SVA have been developed to adjust for this cellular heterogeneity [16, 65]. However, the performance of these algorithms is highly dependent on the validity of model assumptions [69]. Liquid biopsies have come up as an attractive alternative in cancer diagnostics over repeated tissue biopsies simply because tumors shed DNA and cells which can be detected easily in the body fluids such as blood, urine, or saliva [70]. However, these tend to be expensive and there exists a need to develop methods that could not only prove less expensive but also would be faster, more sensitive and easier to perform with very little false discovery rate. For instance, with the current methodologies, the accurate detection of cancer in early stages does not occur as in most clinical practices the amount of blood and hence the amount of circulating cfDNA thus obtained could be limiting. Also, the amount of cfDNA could be less than 0.1% in such patients with small tumors [70]. In addition to this, cfDNA yield may be affected due to contamination from the lysed blood cells (if blood is not processed immediately after collection); the DNA isolation protocol used; and the instrument and technique used for its measurement [70–72]. Hence, gold-standard protocols need to be made and followed to implement the use of cfDNA for routine use in clinical diagnosis.
3.3 Study population heterogeneity and environmental influence The epigenome of an individual undergoes vigorous changes over the lifetime and thus can be greatly influenced by the age, sex, and ethnicity and by environmental influences including, diet, smoking status, exercise, exposure to drugs, pollutants, toxins, etc. [14, 73, 74]. Therefore, these factors need to be considered as potential confounders in an epidemiological setting while performing an epigeneticbased investigation. Indeed, the environmental influence in a particular disease setting can be rather complicated. For instance, age-associated changes in epigenetic marks including DNA methylation— referred to as epigenetic drift—have been a matter of debate for several years wherein most studies have reported them to be tissue specific [75–77]. However, a recent study by Zhu et al using matched multicell type and multi-tissue methylation profiles from the same individuals (after adjusting for celltype heterogeneity) have reported that possibly over ~70% of the epigenetic drift is shared between a significant number of different types of cell/tissues [55]. Therefore, in a clinical setting, the age of a patient needs to be considered prior to performing epigenetic testing.
402
Chapter 15 Challenges and prospects in epigenetic studies
In addition to this, additional parameters such as the definition of symptoms, treatment modalities used, duration of the disease, general health status, patient selection criteria, etc. are likely to confound the results obtained. For example, insufficiency and/or deficiency of micronutrients like Vitamin B12 (a cofactor required for nucleotide metabolism) has been known to induce cholesterol biosynthesis by limiting the S-adenosylmethionine (SAM) levels and modulating the methylation of SREBF1 and LDLR genes [78]. Therefore, to implement the correct usage of this epigenetic mark, that is, methylation of SREBF1 and LDLR genes, as biomarker for the development of metabolic syndrome, serum B12 level measurement needs to be made mandatory. Likewise, therapeutic drugs can influence the epigenetic modifications [15, 79, 80]. For instance, the antihypertensive drug—hydralazine—inhibits DNA methylation [80]. Most chemotherapeutic drugs induce DNA damage and affect DNA repair mechanisms and hence might induce changes in DNA methylation and other epigenetic modifications [81, 82]. Most cancer patients in the clinic are under the influence of these drugs. Hence, clinicians need to consider these as well when assessing the results of biomarker analysis from such patients. Most importantly, studies aiming at epigenetics-based biomarker discovery have been performed with an inadequate number of samples, lesser than those required for the validation [83, 84]. Therefore, for the successful implication of epigenetic-based markers in clinical use, large-scale epigenome-wide association studies (EWAS) studies using homogenous samples in population cohorts of different ethnicities are warranted.
3.4 Gene and environmental interactions In contrast to Mendelian disorders (wherein the phenotype is directly correlated to the phenotype) and infectious diseases (affected by the environment alone), a dynamic cross-talk exists between epigenetic modifications and genetic background in case of complex disorders. While on one hand, polymorphisms in and around genes can significantly impact the chromatin architecture, and expression and activity of epigenetic modifiers; epigenetic modifications in these genes can regulate the expression of genes [85, 86]. Mutations in several epigenetic modifiers have been reported in human cancers. For example, mutations in the histone methyltransferase—EZH2, and histone demethylase—LSD1, have been reported in breast and prostate cancer, respectively [18, 87, 88]. These mutations lead to aberrant DNA methylation, histone modifications and hence, increased genomic instability associated with cancer [4, 17]. Therefore, epigenetic marks should not be considered alone for defining precision medicine and/or biomarkers for complex diseases; rather, integration of the epigenetic and genetic maps needs to be performed while designing the same [5].
3.5 Establishment of the causal role of epigenetic changes Yet another challenge that exists for epigenetic epidemiology studies is to establish the causal role for the identified epigenetic modifications. While it has already been stated that epigenetic changes are rigorously occurring in the body and can be used as marks associated with the disease causation, these are vulnerable and can be influenced by the disease itself. This can complicate the situation and a dire need exists to separate the causal changes from those associated with the disease biology. In this regard, certain statistical approaches including causal inference test (CIT) and Mendelian randomization (MR) have been developed to distinguish between them [5, 6, 56, 89–91]. Both these methods use genetic variants as an instrument to infer the causal relationships between DNA methylation and the outcome [16].
4 Epigenetic therapy
403
In addition to this, some epigenetic marks tend to be more rigorously affected than others over time. Hence, multiple measurements overtime may be required to validate the significantly affected ones in these cases [92, 93].
3.6 Technological challenges The first and most important requirement is sample biobanks and patient registries that contain elaborate information. It should be ensured that the samples have been collected, stored, and processed as per the well-established standard operating protocols (SOPs) to eliminate any confounding effects on the results obtained [94, 95]. Secondly, even though different complementary assays have been developed for the study of epigenetic markers, there exists a great need for standardization and clinical validation. The differences in the detection levels, as well as the technological limitations associated with these assays have often led to noncomparable results being produced in different studies [96]. For instance, DNA methylation detection assays that depend on bisulfite conversion, PCR, and/or the presence of a restriction enzyme site could greatly be affected by the quality of DNA, the presence of inhibitors, primer design, and optimization [96, 97]. Hence, rigorous quality control and inclusion of appropriate controls would warrant the success of these tests to be developed in the clinical setting while keeping the false discovery rate low. While on one hand, assays including high-density DNA methylation microarrays tend to be expensive for routine testing; they are more useful for biomarker discovery on the other. In addition to this, rather than depending on nonquantitative or semiquantitative assays, recent assays are being developed that provide absolute quantitative data, like in case of DNA methylation, percentage of methylated DNA by employing PCR pyrosequencing, high-throughput whole-genome bisulfite sequencing, epiTYPER, DNA melting analysis, to name a few [98–100].
4 Epigenetic therapy The dynamic and reversible nature of epigenetic modifications make them a promising target for therapy wherein the possibility of reprogramming the epigenome and rewiring the cell landscape with the help of these drugs exists. In this regard, epi-drugs (epigenetic drugs)— compounds that alter the DNA and chromatin structure, promote disruption of transcriptional and posttranscriptional modifications and are capable of reactivating epigenetically silenced tumor suppressor and DNA repair genes—are being developed [20, 21, 101]. These drugs mostly target DNMTs and HDACs—the enzymes necessary for the maintenance and establishment of epigenetic marks. Several epigenetic therapies have been approved by the US FDA for cancer treatment and several of these compounds have been tested in preclinical as well as phase I, II, III, and IV clinical trials [20]. A few representative examples have been discussed below. The first epi-drug approved for cancer treatment—Vorinostat—is an HDAC inhibitor and has been used for the treatment of cutaneous T-cell lymphoma. It acts by enabling histone acetylation by blocking the catalytic sites of HDACs and thereby induces growth arrest and death in a wide range of transformed cells by altering the acetylation patterns [102]. The FDA approved DNMT inhibitors include cytidine analogs (azacytidine, decitabine) that act by inhibiting DNA methylation and restoration of
404
Chapter 15 Challenges and prospects in epigenetic studies
a berrantly silenced genes. These inhibitors have been successfully used for the treatment of all subtypes of myelodysplastic syndrome (MDS), other hematologic malignancies and solid tumors [20, 103]. miRNA supplementation, in diseases where they are downregulated, can potentially be used to restore the normal state. For example, miR-34—involved in regulating important cell cycle control and proliferation genes like MYC—has been reported to be silenced in several cancers [104]. Based on this observation, Synlogic Therapeutics have performed preclinical and phase I clinical trials with miR-34 (MRX34), and have found it to effectively reduce tumor size in colon cancer [105–107]. Likewise, miRNA inhibitor has been shown to be helpful in disease where they are upregulated. For example, the miR-122 repressor, miravirsen, have been successfully initiated into the clinical trial aiming at treatment of Hepatitis C infection [108, 109]. A locked nucleic acid (LNA) modified antisense oligonucleotide has been approved for phase I clinical trials of the drug MRG110 which aims at inhibiting the function of miR-92. miRagen is aiming it toward wound healing and heart failure [110].
5 Future perspectives and conclusions Epigenetic biomarkers hold a significant potential to be developed as biomarkers that can be used in the clinic. Although different epigenetic modifications—DNA methylation, histone modifications, ncRNAs—have been identified, there exists a need to learn more about the cross-links between these epigenetic processes and how they are regulated in normal as well as diseased condition. In addition to this, further improvements in the technologies that involve much-simplified sample processing steps, are high throughput and can be used to identify these modifications in a much lesser amount of time, are warranted [94]. For example, even though, next-generation technologies are being developed to study miRNA profiles [111], these tend to be expensive and difficult to apply in the clinical settings. In addition to this, a database needs to be built that is based on results obtained from EWAS studies carried out in subjects from ethnically different backgrounds. This database should also be able to categorize the epigenetic variations in the different phases of a disease (i.e., early-stage, mid-staged, and metastasis stages of a particular cancer, say breast cancer) in sex-matched age groups of patients. Information on complete epigenetic profiles throughout the different phases of the disease would aid in setting up criteria for evaluating clinical prognosis and more effective patient management. Similar information should also be available from a set of age- and sex-matched set of disease-free subjects (healthy volunteers or controls) from the same population. Along these lines, the International Human Epigenome Consortium (IHEC; http://ihec-epigenomes.org/welcome/) is being developed with the aim of providing free access to human epigenome maps (normal as well as diseased) to the research community [94]. This information would be useful in developing tools for clinical practice. Along similar lines, further exploratory research is required to understand the potential of epi-drugs that are capable of modifying aberrant epigenetic profiles in diseased cells and would promote a cell toward a healthy phenotype by stopping the progression of disease any further [19, 20].
Acknowledgments SS acknowledges the funding from Ramalingaswami fellowship (BT/RLF/Re-entry/11/2012; Department of Biotechnology—DBT, Government of India) and University Grants Commission (UGC, Government of India
References
405
F.4-5(18-FRP)(IV-Cycle)/2017(BSR)). SS lab has been generously supported by Research and Development grant and DST-Purse grant to the Department of Biotechnology, SPPU; and Board of College and University Development (BCUD) grant (SPPU) to SS; and UPE Phase II grant to SPPU.
References [1] Y. Hasin, M. Seldin, A. Lusis, Multi-omics approaches to disease, Genome Biol. 18 (1) (2017) 83. [2] S. Wahl, et al., Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity, Nature 541 (7635) (2017) 81–86. [3] M. Verma, et al., Genetic and epigenetic biomarkers in cancer: improving diagnosis, risk assessment, and disease stratification, Mol. Diagn. Ther. 10 (1) (2006) 1–15. [4] J.S. You, P.A. Jones, Cancer genetics and epigenetics: two sides of the same coin? Cancer Cell 22 (1) (2012) 9–20. [5] S. Costantino, et al., Epigenetics and precision medicine in cardiovascular patients: from basic concepts to the clinical arena, Eur. Heart J. 39 (47) (2018) 4150–4158. [6] X. Hong, et al., Genome-wide association study identifies peanut allergy-specific loci and evidence of epigenetic mediation in US children, Nat. Commun. 6 (2015) 6304. [7] A. Portela, M. Esteller, Epigenetic modifications and human disease, Nat. Biotechnol. 28 (10) (2010) 1057–1068. [8] H. Johansson, et al., Interactions between environmental pollutants and genetic susceptibility in asthma risk, Curr. Opin. Immunol. 60 (2019) 156–162. [9] A.E.A. Surace, C.M. Hedrich, The role of epigenetics in autoimmune/inflammatory disease, Front. Immunol. 10 (2019) 1525. [10] C. Pinel, B. Prainsack, C. McKevitt, Markers as mediators: a review and synthesis of epigenetics literature, Biosocieties 13 (1) (2019) 276–303. [11] M. Szyf, The dynamic epigenome and its implications in toxicology, Toxicol. Sci. 100 (1) (2007) 7–23. [12] L. Mirbahai, J.K. Chipman, Epigenetic memory of environmental organisms: a reflection of lifetime stressor exposures, Mutat. Res. Genet. Toxicol. Environ. Mutagen. 764-765 (2014) 10–17. [13] G. Almouzni, et al., Relationship between genome and epigenome—challenges and requirements for future research, BMC Genom. 15 (2014) 487. [14] R. Feil, M.F. Fraga, Epigenetics and the environment: emerging patterns and implications, Nat. Rev. Genet. 13 (2) (2012) 97–109. [15] A. Jangra, et al., Epigenetic modifications, alcoholic brain and potential drug targets, Ann. Neurosci. 23 (4) (2016) 246–260. [16] Z. Jin, Y. Liu, DNA methylation in human diseases, Genes Dis. 5 (1) (2018) 1–8. [17] M. Rodriguez-Paredes, M. Esteller, Cancer epigenetics reaches mainstream oncology, Nat. Med. 17 (3) (2011) 330–339. [18] D.P. Tsang, A.S. Cheng, Epigenetic regulation of signaling pathways in cancer: role of the histone methyltransferase EZH2, J. Gastroenterol. Hepatol. 26 (1) (2011) 19–27. [19] L. Gherardini, et al., Targeting cancer with epi-drugs: a precision medicine perspective, Curr. Pharm. Biotechnol. 17 (10) (2016) 856–865. [20] C.L. Miranda Furtado, et al., Epidrugs: targeting epigenetic marks in cancer treatment, Epigenetics (2019) 1–13. [21] R. Mazzone, et al., Epi-drugs in combination with immunotherapy: a new avenue to improve anticancer efficacy, Clin. Epigenetics 9 (2017) 59. [22] I. Martin-Timon, et al., Type 2 diabetes and cardiovascular disease: have all risk factors the same strength? World J. Diabetes 5 (4) (2014) 444–470.
406
Chapter 15 Challenges and prospects in epigenetic studies
[23] M. Gowshall, S.D. Taylor-Robinson, The increasing prevalence of non-communicable diseases in lowmiddle income countries: the view from Malawi, Int. J. Gen. Med. 11 (2018) 255–264. [24] B.M. Leon, T.M. Maddox, Diabetes and cardiovascular disease: epidemiology, biological mechanisms, treatment recommendations and future research, World J. Diabetes 6 (13) (2015) 1246–1258. [25] S. Sharma, A.B. Mathew, J. Chugh, miRNAs: nanomachines that micromanage the pathophysiology of diabetes mellitus, Adv. Clin. Chem. 82 (2017) 199–264. [26] P. Bhatia, et al., miRNAs: early prognostic biomarkers for Type 2 diabetes mellitus? Biomark Med. 9 (10) (2015) 1025–1040. [27] W.J. Locke, et al., Coordinated epigenetic remodelling of transcriptional networks occurs during early breast carcinogenesis, Clin. Epigenetics 7 (2015) 52. [28] M.L. Thomas, P. Marcato, Epigenetic modifications as biomarkers of tumor development, therapy response, and recurrence across the cancer care continuum, Cancers (Basel) 10 (4) (2018). [29] D.P. Potaczek, et al., Epigenetics and allergy: from basic mechanisms to clinical applications, Epigenomics 9 (4) (2017) 539–571. [30] D.E. Handy, R. Castro, J. Loscalzo, Epigenetic modifications: basic mechanisms and role in cardiovascular disease, Circulation 123 (19) (2011) 2145–2156. [31] L. Hamzehzadeh, M. Yousefi, S.H. Ghaffari, Colorectal cancer screening: a comprehensive review to recent non-invasive methods, Int. J. Hematol. Oncol. Stem Cell Res. 11 (3) (2017) 250–261. [32] R.M. Ned, S. Melillo, M. Marrone, Fecal DNA testing for colorectal cancer screening: the ColoSure test, PLoS Curr. 3 (2011) RRN1220. [33] W.D. Chen, et al., Detection in fecal DNA of colon cancer-specific methylation of the nonexpressed vimentin gene, J. Natl. Cancer Inst. 97 (15) (2005) 1124–1132. [34] J. Nian, et al., Diagnostic accuracy of methylated SEPT9 for blood-based colorectal cancer detection: a systematic review and meta-analysis, Clin. Transl. Gastroenterol. 8 (1) (2017) e216. [35] Y.W. Lu, et al., Colorectal cancer genetic heterogeneity delineated by multi-region sequencing, PLoS One 11 (3) (2016) e0152673. [36] P. Costa-Pinheiro, et al., Diagnostic and prognostic epigenetic biomarkers in cancer, Epigenomics 7 (6) (2015) 1003–1015. [37] Y. Spector, et al., Development and validation of a microRNA-based diagnostic assay for classification of renal cell carcinomas, Mol. Oncol. 7 (3) (2013) 732–738. [38] S. Gilad, et al., Classification of the four main types of lung cancer using a microRNA-based diagnostic assay, J. Mol. Diagn. 14 (5) (2012) 510–517. [39] A. Van Den Broeck, et al., Loss of histone H4K20 trimethylation occurs in preneoplasia and influences prognosis of non-small cell lung cancer, Clin. Cancer Res. 14 (22) (2008) 7237–7245. [40] D. Matthaios, et al., H2AX a promising biomarker for lung cancer: a review, Cancer Invest. 31 (9) (2013) 582–599. [41] M.M. Kronfol, et al., The role of epigenomics in personalized medicine, Expert Rev. Precis. Med. Drug Dev. 2 (1) (2017) 33–45. [42] S. Mastoraki, et al., ESR1 methylation: a liquid biopsy-based epigenetic assay for the follow-up of patients with metastatic breast cancer receiving endocrine treatment, Clin. Cancer Res. 24 (6) (2018) 1500–1510. [43] H.Y. Sung, et al., Aberrant epigenetic regulation of GABRP associates with aggressive phenotype of ovarian cancer, Exp. Mol. Med. 49 (5) (2017) e335. [44] M.D. Brooks, M.L. Burness, M.S. Wicha, Therapeutic implications of cellular heterogeneity and plasticity in breast cancer, Cell Stem Cell 17 (3) (2015) 260–271. [45] C.H. Fan, et al., O6-methylguanine DNA methyltransferase as a promising target for the treatment of temozolomide-resistant gliomas, Cell Death Dis. 4 (2013) e876. [46] N. Thon, S. Kreth, F.W. Kreth, Personalized treatment strategies in glioblastoma: MGMT promoter methylation status, Onco. Targets Ther. 6 (2013) 1363–1372.
References
407
[47] A. Luquain, et al., Analysis of MGMT methylation with the therascreen((R)) MGMT Pyro((R)) Kit (Qiagen). A method verification, Ann. Biol. Clin. (Paris) 73 (6) (2015) 665–670. [48] K. Chiam, et al., GSTP1 DNA methylation and expression status is indicative of 5-aza-2'-deoxycytidine efficacy in human prostate cancer cells, PLoS One 6 (9) (2011) e25634. [49] E. Dejeux, et al., DNA methylation profiling in doxorubicin treated primary locally advanced breast tumours identifies novel genes associated with survival and treatment response, Mol. Cancer 9 (2010) 68. [50] O.A. Stefansson, et al., BRCA1 epigenetic inactivation predicts sensitivity to platinum-based chemotherapy in breast and ovarian cancer, Epigenetics 7 (11) (2012) 1225–1229. [51] K. Visvanathan, et al., Monitoring of serum DNA methylation as an early independent marker of response and survival in metastatic breast cancer: TBCRC 005 prospective biomarker study, J. Clin. Oncol. 35 (7) (2017) 751–758. [52] B. Downs, et al., DNA methylation markers for breast cancer detection in the developing world. Clin Cancer Res. (2019) https://doi.org/10.1158/1078-0432.CCR-18-3277. [53] E. Cazaly, et al., Making sense of the epigenome using data integration approaches, Front. Pharmacol. 10 (2019) 126. [54] I. Mendizabal, et al., Cell type-specific epigenetic links to schizophrenia risk in the brain, Genome Biol. 20 (1) (2019) 135. [55] T. Zhu, et al., Cell and tissue type independent age-associated DNA methylation changes are not rare but common, Aging (Albany NY) 10 (11) (2018) 3541–3557. [56] Y. Liu, et al., Epigenome-wide association data implicate DNA methylation as an intermediary of genetic risk in rheumatoid arthritis, Nat. Biotechnol. 31 (2) (2013) 142–147. [57] E.E. Eichler, et al., Missing heritability and strategies for finding the underlying causes of complex disease, Nat. Rev. Genet. 11 (6) (2010) 446–450. [58] S. Kriaucionis, N. Heintz, The nuclear DNA base 5-hydroxymethylcytosine is present in Purkinje neurons and the brain, Science 324 (5929) (2009) 929–930. [59] S. Kurdyukov, M. Bullock, DNA methylation analysis: choosing the right method, Biology (Basel) 5 (1) (2016). [60] R. Garzon, et al., MicroRNA-29b induces global DNA hypomethylation and tumor suppressor gene reexpression in acute myeloid leukemia by targeting directly DNMT3A and 3B and indirectly DNMT1, Blood 113 (25) (2009) 6411–6418. [61] M. Gutierrez-Arcelus, et al., Tissue-specific effects of genetic and epigenetic variation on gene regulation and splicing, PLoS Genet. 11 (1) (2015) e1004958. [62] E. Hannon, et al., Interindividual methylomic variation across blood, cortex, and cerebellum: implications for epigenetic studies of neurological and neuropsychiatric phenotypes, Epigenetics 10 (11) (2015) 1024–1032. [63] P. Farre, et al., Concordant and discordant DNA methylation signatures of aging in human blood and brain, Epigenet. Chromatin 8 (2015) 19. [64] B.R. Joubert, et al., DNA methylation in newborns and maternal smoking in pregnancy: genome-wide consortium meta-analysis, Am. J. Hum. Genet. 98 (4) (2016) 680–696. [65] A. Kaushal, et al., Comparison of different cell type correction methods for genome-scale epigenetics studies, BMC Bioinform. 18 (1) (2017) 216. [66] A. Cardenas, et al., Validation of a DNA methylation reference panel for the estimation of nucleated cells types in cord blood, Epigenetics 11 (11) (2016) 773–779. [67] K.M. Bakulski, et al., DNA methylation of cord blood cell types: applications for mixed cell birth studies, Epigenetics 11 (5) (2016) 354–362. [68] J. Guintivano, M.J. Aryee, Z.A. Kaminsky, A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression, Epigenetics 8 (3) (2013) 290–302.
408
Chapter 15 Challenges and prospects in epigenetic studies
[69] A.E. Teschendorff, S.C. Zheng, Cell-type deconvolution in epigenome-wide association studies: a review and recommendations, Epigenomics 9 (5) (2017) 757–768. [70] W. Gai, K. Sun, Epigenetic biomarkers in cell-free DNA and applications in liquid biopsy, Genes (Basel) 10 (1) (2019). [71] C. Perez-Barrios, et al., Comparison of methods for circulating cell-free DNA isolation using blood from cancer patients: impact on biomarker testing, Transl. Lung Cancer Res. 5 (6) (2016) 665–672. [72] L. Sorber, et al., A comparison of cell-free DNA isolation kits: isolation and quantification of cell-free DNA in plasma, J. Mol. Diagn. 19 (1) (2017) 162–168. [73] C. Tiffon, The impact of nutrition and environmental epigenetics on human health and disease, Int. J. Mol. Sci. 19 (11) (2018). [74] C.J. Marsit, Influence of environmental exposure on human epigenetic regulation, J. Exp. Biol. 218 (Pt 1) (2015) 71–79. [75] B.C. Christensen, et al., Aging and environmental exposures alter tissue-specific DNA methylation dependent upon CpG island context, PLoS Genet. 5 (8) (2009) e1000602. [76] M.F. Fraga, et al., Epigenetic differences arise during the lifetime of monozygotic twins, Proc. Natl. Acad. Sci. U. S. A. 102 (30) (2005) 10604–10609. [77] N. Ahuja, J.P. Issa, Aging, methylation and cancer, Histol. Histopathol. 15 (3) (2000) 835–842. [78] A. Adaikalakoteswari, et al., Vitamin B12 insufficiency induces cholesterol biosynthesis by limiting s-adenosylmethionine and modulating the methylation of SREBF1 and LDLR genes, Clin. Epigenetics 7 (2015) 14. [79] T. Heinbockel, A.B. Csoka, Epigenetic effects of drugs of abuse, Int. J. Environ. Res. Public Health 15 (10) (2018). [80] A.B. Csoka, M. Szyf, Epigenetic side-effects of common pharmaceuticals: a potential new field in medicine and pharmacology, Med. Hypotheses 73 (5) (2009) 770–780. [81] H.M. O'Hagan, et al., Oxidative damage targets complexes containing DNA methyltransferases, SIRT1, and polycomb members to promoter CpG Islands, Cancer Cell 20 (5) (2011) 606–619. [82] A.A. Emran, et al., Commonly integrated epigenetic modifications of differentially expressed genes lead to adaptive resistance in cancer, Epigenomics 11 (7) (2019) 732–737. [83] P.A. Jones, J.P. Issa, S. Baylin, Targeting the cancer epigenome for therapy, Nat. Rev. Genet. 17 (10) (2016) 630–641. [84] T. Nieto, et al., A systematic review of epigenetic biomarkers in progression from non-dysplastic Barrett's oesophagus to oesophageal adenocarcinoma, BMJ Open 8 (6) (2018) e020427. [85] D. Zhang, et al., Genetic control of individual differences in gene-specific methylation in human brain, Am. J. Hum. Genet. 86 (3) (2010) 411–419. [86] S. Costantino, F. Paneni, F. Cosentino, Targeting chromatin remodeling to prevent cardiovascular disease in diabetes, Curr. Pharm. Biotechnol. 16 (6) (2015) 531–543. [87] A. Chase, N.C. Cross, Aberrations of EZH2 in cancer, Clin. Cancer Res. 17 (9) (2011) 2613–2618. [88] D. Rotili, A. Mai, Targeting histone demethylases: a new avenue for the fight against cancer, Genes Cancer 2 (6) (2011) 663–679. [89] C.L. Relton, G. Davey Smith, Two-step epigenetic Mendelian randomization: a strategy for establishing the causal role of epigenetic processes in pathways to disease, Int. J. Epidemiol. 41 (1) (2012) 161–176. [90] M.M. Mendelson, et al., Association of body mass index with DNA methylation and gene expression in blood cells and relations to cardiometabolic disease: a Mendelian randomization approach, PLoS Med. 14 (1) (2017) e1002215. [91] G. Hemani, K. Tilling, G. Davey Smith, Orienting the causal relationship between imprecisely measured traits using GWAS summary data, PLoS Genet. 13 (11) (2017) e1007081. [92] C. Luo, P. Hajkova, J.R. Ecker, Dynamic DNA methylation: in the right place at the right time, Science 361 (6409) (2018) 1336–1340.
References
409
[93] M.J. Ziller, et al., Charting a dynamic DNA methylation landscape of the human genome, Nature 500 (7463) (2013) 477–481. [94] S.O.M. Dyke, et al., Points-to-consider on the return of results in epigenetic research, Genome Med. 11 (1) (2019) 31. [95] L. Peiró-Chova, et al., Chapter 2—the importance of biobanks in epigenetic studies, in: J.L. García-Giménez (Ed.), Epigenetic Biomarkers and Diagnostics, Academic Press, Boston, 2016, pp. 19–35. [96] A.T. Lorincz, The promise and the problems of epigenetics biomarkers in cancer, Expert Opin. Med. Diagn. 5 (5) (2011) 375–379. [97] T.C. Lorenz, Polymerase chain reaction: basic protocol plus troubleshooting and optimization strategies, J. Vis. Exp. 63 (2012) e3998. [98] N. Vasiljevic, et al., Absolute quantitation of DNA methylation of 28 candidate genes in prostate cancer using pyrosequencing, Dis. Markers 30 (4) (2011) 151–161. [99] J.L. Brandsma, et al., Distinct human papillomavirus type 16 methylomes in cervical cells at different stages of premalignancy, Virology 389 (1-2) (2009) 100–107. [100] M. Li, et al., Sensitive digital quantification of DNA methylation in clinical samples, Nat. Biotechnol. 27 (9) (2009) 858–863. [101] R. Salarinia, et al., Epi-drugs and Epi-miRs: moving beyond current cancer therapies, Curr. Cancer Drug Targets 16 (9) (2016) 773–788. [102] V.M. Richon, J. Garcia-Vargas, J.S. Hardwick, Development of vorinostat: current applications and future perspectives for cancer therapy, Cancer Lett. 280 (2) (2009) 201–210. [103] E. Kaminskas, et al., FDA drug approval summary: azacitidine (5-azacytidine, Vidaza) for injectable suspension, Oncologist 10 (3) (2005) 176–182. [104] A.A. Farooqi, S. Tabassum, A. Ahmad, MicroRNA-34a: a versatile regulator of myriads of targets in different cancers, Int. J. Mol. Sci. 18 (10) (2017). [105] S. Gaur, et al., Chitosan nanoparticle-mediated delivery of miRNA-34a decreases prostate tumor growth in the bone and its expression induces non-canonical autophagy, Oncotarget 6 (30) (2015) 29161–29177. [106] H. Tazawa, et al., Tumor-suppressive miR-34a induces senescence-like growth arrest through modulation of the E2F pathway in human colon cancer cells, Proc. Natl. Acad. Sci. U. S. A. 104 (39) (2007) 15472–15477. [107] M.S. Beg, et al., Phase I study of MRX34, a liposomal miR-34a mimic, administered twice weekly in patients with advanced solid tumors, Invest. New Drugs 35 (2) (2017) 180–188. [108] R.E. Lanford, et al., Therapeutic silencing of microRNA-122 in primates with chronic hepatitis C virus infection, Science 327 (5962) (2010) 198–201. [109] H.L. Janssen, et al., Treatment of HCV infection by targeting microRNA, N. Engl. J. Med. 368 (18) (2013) 1685–1694. [110] J. Hanna, G.S. Hossain, J. Kocerha, The potential for microRNA therapeutics and clinical research, Front. Genet. 10 (2019) 478. [111] J. Liu, et al., Next generation sequencing for profiling expression of miRNAs: technical progress and applications in drug development, J. Biomed. Sci. Eng. 4 (10) (2011) 666–676.