Next-generation sequencing and epigenome technologies: potential medical applications

Keywords::

• cancer genome
• epigenome
• genetic tests
• human genome
• innovation
• medical implications
• NGS technology
• validity

The latest genomic technology, with faster, cheaper and more accurate complete sequencing of the human genome and specimens, has revolutionized biomedical research. Despite this technology explosion, the diversity of life and disease is a challenge to unravel. Individuals or patients with similar genome sequences have different phenotypes, including risks of disease development and response to the same therapy, respectively. Current innovation technology aims to achieve simultaneous reading of both genome sequencing and the epigenome. The epigenome concept – a set of chemical modifications of DNA (epigenetics), that regulate gene expression – can contribute to a deeper understanding of epigenetic coding, biodiversity and disease heterogeneity, particularly for intractable diseases such as cancer. How could this genomic and epigenomic technology change medical practice, and what are the challenges to reach genomic and epigenomic medicine?

Genome sequencing technology explosion

10 years after the first complete draft of a human genome sequence, advances in genomic technologies have revolutionized biomedical research [1–3]. How can this rapid progress in sequencing technology be explained? High-throughput technology with an unprecedented ability of massively parallel genome sequencing technology permits the simultaneous analysis of millions of variants across the genome. This genome-wide map permits the identification of most, or even all, causal mutations underlying common human disorders. Therefore, this in-depth assessment opens new ways in understanding disease pathogenesis and progression, disorder risk prediction, prevention and treatment. This huge potential of genomics to revolutionize medicine and improve healthcare reliably attracts much interest from the biotechnology and pharmaceutical industries, biomedical sciences, and academia. However, multiple challenges and problems should be resolved.

Next-generation sequencing technology

The ability of next-generation sequencing (NGS) technology [4] for complete sequencing of human genomes, including both protein-coding and noncoding DNA, can lead to the completion of a mutations catalog for many major diseases, such as cancer. Although most efforts have focused on protein-encoding genes that account for a very small proportion of the human genome, the noncoding DNA – what used to be called ‘junk’ DNA – may have a crucial role in the fundamentals of gene regulation. An international collaborative project called the Encyclopedia of DNA Elements (ENCODE) demonstrated that in a selected portion of the genome containing just a few percent of protein-coding sequence, between 74 and 93% of DNA was transcribed into RNA [5]. Much noncoding DNA has a regulatory role; small RNAs of different varieties seem to control gene expression at the level of both DNA and RNA transcripts in ways that are still only beginning to become clear [6].

The rapidly dropping costs have led to the publication of at least two dozen complete human genome sequences, and an additional 200 full-genome sequencing works are due to be published [7]. Several international consortiums have been launched, including the ‘1000 Genome Project’, while the ‘10,000 Genomes’ project is going to be started [8]. Moreover, for major diseases, such as cancer, the International Cancer Genome Consortium (ICGC) [9] will reveal the repertoire of driver mutations. Three fully sequenced cancer genomes, including breast, lung and melanoma cancer, have been published [10–13] and, along with other recent systematic studies of cancer genomes, reveal that cancer is much more heterogeneous and complicated than initially thought [13,14].

This high complexity and heterogeneity of complex common disorders such as cancer, cardiovascular disease, diabetes, schizophrenia and others, explains the limitations and hurdles in both the prevention and treatment setting. A huge number of mutations in key genes is involved in these diseases. These DNA changes, for example in cancer, include not only point mutations, such as single-nucleotide polymorphisms, but also genomic rearrangements and copy-number changes [14]. These mutated genes dysregulate several signaling pathways that vary widely, even among patients with the same cancer type, tumor stage and clinicopathologic features. Therefore, it is not surprising that currently used targeting agents targeting a single gene or a single signaling pathway, such as EGF receptor, HER2 or VEGF, are noneffective for most patients [15,16].

The major investments by the biotechnology and pharmaceutical industries in the present generation of biologic agents have modestly met the expectations. However, there has been an isolated clinical success with trastuzumab – an anti-HER2 signaling pathway inhibitor – which has been added to chemotherapy in the treatment of breast cancer and gastric cancer [17–25]. However, the applications of most other targeted agents for various cancer types are limited to small subsets of patients only [15–17,26,27].

Business & direct-to-consumer genetic tests

Current NGS-based platforms permit systematic studies for complete human genome sequencing, which reveal the high complexity of major common complex diseases such as cancer. However, the uncritical rapid development and availablity to the population of direct-to-consumer (DTC) medical tests for personalized risks estimates, before their validity is known, may cause more harm than provide benefit to the general population. Several companies, based on partial genome sequencing and preliminary data from genome-wide association studies [28,29], developed DTC genetics tests for predicting risks of various common diseases. These DTC tests have been commercialized extremely rapidly and are promoted for their ability to predict development risks.

Can we trust these genetic tests?

These DTC genetic tests were based on an incomplete number of single-nucleotide polymorphisms and, although largely unregulated, are used increasingly to diagnose conditions, map ancestry or predict disease risk [30]. However, in an absence of clinical validity, including clinical sensitivity, specificity and utility (the balance between the health-related benefits and the harm caused to the patient), caution is suggested for the clinical use of these DTC genetic tests [31,32]. Expressing its valid concerns in an effort to protect the public from potential harms, the US FDA sent a letter informing Pathway Genomics and 19 other companies that their DNA testing and interpretation service “appears to meet the definition of a device”, and may therefore require FDA approval [101].

Potential & challenges of NGS

With improved quality for data analysis and rapidly dropping costs, NGS platforms shape a rational strategy towards completion of a mutations catalog for common diseases. This assessment of genetic alterations underlying major disorders, such as cancer, represents the basis for pathogenesis-based development of genetic tests. These tests predicting disease risks might be used in both individuals’ risk prediction and stratification of people in the general population into high-risk and low-risk, which implies genetic screening [33].

However, in order to reach such major healthcare advances, including novel medical test-based general population screening and primary prevention from major diseases, a lot of challenges have to be overcome [34]. For example, an accurate method to distinguish driver (causal) mutations from passenger (noncausal) mutations has to be standardized. Moreover, it is yet unknown whether the major funding required for sequencing of the noncoding region of the human genome and the exploration of its potential functional role will have cost–effectiveness clinical implications in the biomarkers and drugs development research arena [35]. Two other major problems await solution. How can we explain life diversity among populations with identical whole-genome sequencing but with different phenotypes and different susceptibilities to a disease? How would we able to predict the inference of complex dynamic systems such as biological and environmental systems [27]?

Epigenetics & epigenome

Genetic variants identified by genome sequencing can explain life diversity. However, some individuals or patients with similar genomes present different phenotypes. For example, monozygotic twins can have different phenotypes and different susceptibilities to a disease despite their identical DNA sequences [36].

The complexity of genetic regulation is one of the great wonders of nature, but it represents a daunting challenge to unravel. Research on epigenetics, those changes to gene expression caused by chemical modification of DNA and its associated proteins, may contribute to understanding the functional role of genes [37]. These epigenetic DNA modifications affect the expression of genes rather than the genes themselves, and cannot be explored even with the NGS technology.

DNA methylation – the addition of methyl groups to individual bases – is the best-studied epigenetic modification among many epigenetic markers. DNA methylation, which reduces gene expression, is linked to key developmental events, as well as many types of cancer. The gold-standard method for detecting DNA methylation is bisulfite sequencing. Sequencing the converted DNA allows a reconstruction of a genome-wide methylation map. However, the technique has several drawbacks. Not only is it expensive and time consuming, it also damages DNA, reducing the map’s accuracy [38].

Innovative sequencing technology

Companies with expertise in innovative sequencing technologies try to achieve the ideal: the simultaneous reads of both genome sequencing and epigenetic changes. Sequencing company Pacific Biosciences, based in Menlo Park, CA, USA, has now developed an integrated system that simultaneously reads a genome sequence and detects DNA methylation. This method is a small step, but it’s an important step forward [39].

This company foresees, with this technology, that in the future there will be a unification of the fields of epigenomics and with the latest technique, the cost of a full-genome methylation map would drop from US$100,000 using bisulfite sequencing for a single human genome to US$100–1000 [39]. With such rapidly dropping expenses, the concept of the epigenome now appears realistic.

Exploring the epigenome – a genome-wide map of epigenetic modifications – undoubtedly represents an important step forward in understanding one of the great wonders of nature, but the genetic regulation is a daunting challenge to unravel. To arrive at this goal, the International Human Epigenome Consortium (IHEC) was launched early this year. In an economic crisis period, is now the time for such an expensive project? In a recent editorial in Nature[37], it has been emphasized that despite the clichéd debate on big science versus small science, the Human Epigenome Project is a challenge whose time has come. The IHEC will deliver information regarding health and disease as it progresses, particularly regarding intractable diseases such as cancer.

Nonlinear systems

Another big challenge with a major contribution in understanding the complex genetic and epigenetic coding and biodiversity, is how to predict the inference of complex dynamic interactions between biological and environmental systems [27,35,40,41]. Indeed, emerging strong evidence indicates that cancer, and the development and evolution of other common diseases, are driven by gene–gene and gene–environment interactions rather than a simple accumulation of causal genetic variants over a cut-off value [27,33]. However, no standard statistical or computational method has been developed to predict such complex networks. Such chaotic or near-chaotic systems are almost invariably driven by endogenous dynamic processes plus demographic and environmental process noise, and are only observable with error [41,42]. Exciting research is underway to overcome these challenges. For example, a new method is proposed that requires only the ability to simulate the observed data on a system from the dynamic model regarding which inferences are required [43].

To achieve clinical success in the biomarkers and drugs research arena without considering clinical data is elusive. Even the most perfect sequencing technology will be unable to link these genotyping data with phenotype without the consideration of clinical data. Craig Venter notes that because of the huge volume of phenotypic data, we will need supercomputers, which would run 1000-times faster than today’s fastest computers, in order to compare even thousands of genotypes and phenotypes with each other [3]. The necessity of clinical data is now increasingly being recognized, and a novel clinico-genome model integrating both clinical and genotyping data towards personalized medicine has been published [44]. Personalizing decision making in the prevention and treatment setting through genome sequencing and network modeling can revolutionize clinical medicine [2,26].

Conclusion

In the postgenomic era, systematic genomic studies provide clues on the complexity and heterogeneity of major diseases killing millions of patients each year worldwide. To reverse this status, innovation is the key value driver for improving health. Beyond next-generation human genome sequencing technology and exploration of the epigenome, scientific intellect with international cooperations now shape the basis of genomic and epigenomic medicine.

Financial & competing interests disclosure

The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.