September 28, 2010 | Insights Outlook | One of the really big questions facing genomics practitioners today is whether they can in fact identify key genetic variants related to serious common diseases, and if so, whether this knowledge will lead either immediately or indirectly to new medical treatments. With DNA-centrism so prevalent today, it’s easy to lose perspective on the incredible complexity of the human organism at levels ranging from the subatomic through the atomic, molecular, supra-molecular, organelle, and cell levels, each with its own network of interacting players, and each communicating with adjacent layers and generating emergent properties not predicted at lower levels.
Eric Schadt, CSO at Pacific Biosciences, told Insight Pharma Reports: “I think that with some of the earlier work we did on predictive models of disease and how that drove a lot of the drug discovery, I felt that we were glimpsing maybe in the most optimistic of cases 1% of the biology. With the new technologies that are emerging today… our ability to glimpse an order of magnitude or so more of the biology is possible. It may be 10% or even more.”
Indeed, diagnostic companies and clinical laboratories are already starting to offer NGS services devoted to less common, often rare Mendelian diseases, in which genetic variations in single genes are largely responsible for disease onset. In total, these illnesses represent an estimated 10% of all serious disease cases, and we can likely expect screening for hundreds of them to become available in the next year or two. Yet many of these diseases are proving to be a bit more complex than represented by the paradigm in which a genetic variant leads to a defective protein, which causes the disease symptoms. Even sickle cell anemia and cystic fibrosis have both proved to be more complex biologically than originally conceived.
Nor can one doubt that deeper understandings of cancer in its many guises are going to emerge in the next decade and that these will lead to further progress in improving both the quality and extent of life for cancer patients. Cancer appears to be a poster child for the kinds of complexity that drug discoverers will face in this next era of plying their trade. Multiple biological pathways contributing to uncontrolled cell proliferation and metastasis are going to be identified, and in most cases it will not be sufficient to attack any one or even two pathways.
On the one hand, it’s not yet clear where all this NGS-stimulated genomic research is headed. Yet there is cause for great optimism. Given the incredible scope of NGS-based genomic studies now in progress, knowledge gained will no doubt stimulate downstream functional studies. These in turn will undoubtedly negate or alter large segments of current received wisdom and open the doors to new hypotheses and approaches that will revolutionize biology and medicine in ways we cannot presently envision.
Also on the bright side, it is not yet time to abandon the one-target/one-drug paradigm even with its already-obvious limitations. Pre-NGS -omics research had already led to some interesting new target possibilities. A number of companies currently have drugs directed against novel targets in the pipeline that may in fact make it through to market and prove highly beneficial.
Below are some observations and conclusions taken from Insight Pharma Reports’ recently completed survey on NGS adoption and applications. In our survey population, basic genomic research was by far the greatest preoccupation for all respondents, with biomarker discovery a distant second. Capillary electrophoresis sequencing is alive and well in both commercial and academic settings, but around half of those possessing such instruments also have NGS systems. Of those with no NGS systems, one-third plan to have them before the end of 2011, and more than half intend to acquire them by 2015. Furthermore, more than half of respondents’ organizations outsource NGS, and half of those who don’t now, plan to start in 2011.
Among factors inhibiting uptake of NGS, difficulties in data interpretation, preference for microarrays, and cost of data storage were dominant. Reagent and data interpretation cost were lesser concerns, as were concerns over data quality. Whole genome sequencing, RNA-seq, exome sequencing, and resequencing are all much more prevalent at this time than ChIP-seq, Methyl-seq, and GWAS. Cancer research via NGS is much more prevalent than cardiologic and neurologic disease research. Microbial-related sequencing (e.g., microbiome and metagenomics) also ranks high among application areas. Pharmacogenomics ranks considerably higher in the commercial sectors than for the non-profits.