Since the National Human Genome Research Institute (NHGRI) initiated a program in 2004 to advance sequencing technology development, the resulting next generation sequencing technology (also called massively parallel sequencing) was initially restricted to being used for research purposes. With increasing availability of commercial sequencing platforms, these technologies are entering the clinic along with the means to analyze the metabolome, proteome and microbiome and may soon form the cornerstone of diagnostics and therapeutics. Dr Sandeep Pingle, Roundtable blog editor finishes his blog series by summarizing the clinical applications of next generation sequencing.
Currently, the most common use of genome sequencing is in cancer patients. Cancer may be associated with somatic mutations, ranging from single-nucleotide polymorphisms to large genomic alterations. Next generation sequencing is a highly versatile tool to detect these genetic variations in cancer patients. In combination with other tools for proteomics and metabolomics, next generation sequencing can provide vast amounts of data that will enable development of strategies for personalized cancer therapy.
In addition, though it is known for a long time that very rare genetic mutations underlie common diseases such as diabetes, hypertension, schizophrenia and even cancers, elucidating an exact role of such genetic mutations has proved elusive. However, recent advances and development of massive parallel sequencing makes detecting such mutations a reality. Two recent studies, using exome sequencing identified abundant “rare” variants that may be associated with increased incidence of a specific disease in humans [2, 3]. Analyses of these genetic variants will provide a unique insight, making it possible to identify disease risk for individuals and later, stratify them for personalized therapy. The importance of these findings prompted Wired magazine to list this research as one of top 10 scientific discoveries of 2012 .
Sequencing the whole genome of an individual (personalized genome) using next generation sequencing can identify sequences that are potentially associated with disease. This information is useful to assess risk of chronic diseases and inherited disorders. In addition, genome sequencing can be used to shed light on the status of drug metabolizing enzymes and transporters in individuals. These are proteins present in the body that drive absorption and distribution of a drug in the body and its metabolism. These data can be used to predict drug responses and toxicities in an individual and help personalize drug therapy.
Another application based on next-generation sequencing that featured prominently in Wired magazine was the noninvasive whole-genome sequencing of a human fetus  that has major implications for prenatal genetic diagnostics. Finally, next generation sequencing finds application in studies identifying genetic variations that occurred during the past thousands of years by studying Neanderthal and other archaic human DNA. Though not directly translational, this use of next generation sequencing will help understand evolutionary changes in humans.
Though we have come a long way from the early days of sequencing, further advances are required to improve efficiency, data analyses and interpretation. Application of next generation sequencing arguably represents one of the most rapid translations of a technology from bench-to-bedside and has the potential to accelerate biomedical research and improve patient care.
- Sandeep Pingle is the San Diego Editor for the blog “Roundtable Review” by Oxbridge Biotech Roundtable
- Evolution and Functional Impact of Rare Coding Variation from Deep Sequencing of Human Exomes: Science (2012) DOI: 10.1126/science.1219240
- An Abundance of Rare Functional Variants in 202 Drug Target Genes Sequenced in 14,002 People: Science (2012) DOI: 10.1126/science.1217876
- Top Scientific Discoveries of 2012: Wired Science
- Noninvasive Whole-Genome Sequencing of a Human Fetus: Science Translational Medicine (2012) DOI: 10.1126/scitranslmed.3004323