Genomics and Drug Discovery

A major development occurred in the 1990s when automation technology and combinatorial compound libraries allowed parallel screening of a much higher number of compounds than was previously possible. Additional improvement in the drug-screening process was achieved through early introduction of toxicity and pharmacokinetics evaluations. In parallel, structural biology has provided new means of engineering ‘tailor-made’ drugs. During the last decade, much attention has been paid to the potential effect genomics research might have on the drug-discovery process. It is, therefore, appropriate to take a closer look at the various ways genomics can support drug discovery today and the prominent influence genomics will potentially present in the future and, especially, in the area of personalized medicines.

A draft of the sequence of the human genome was first presented in 2000. Just 3 years later, the first complete genome version was published, which immediately received plenty of attention as a promising future approach for genomics-based drug discovery. Now, a decade later, a number of applications of genomics have been realized and the field has obtained a more established position within novel drug discovery. More efficient use of genomics information has mainly become possible due to one of the most important technology developments, the high-throughput next-generation sequencing. High-throughput next-generation sequencing can generate over 100-times more data compared with earlier methods, which has also permitted a significant reduction in sequencing costs. In comparison to the price tag of US$25 million and 5 years of work for the first complete sequencing of the human genome, the commercial cost has dropped in 2011 to $4000, and the time required for full genome sequence has been reduced to only approximately a month. In parallel, major developments in bioinformatics methodology has significantly strengthened the analysis capacity of generated data. In this context, new methods for the following four areas have been introduced: processing of large-scale robust genomic data; introduction of the functional effect and the impact of genome variation; integration of systems data to relate complex genetic interactions with phenotypes; and translation of discoveries into medical practice.

Genomics information can support modern drug discovery in various ways. The human genome as such provides valuable insight into the identification of novel drug targets. Furthermore, individual variations in the human genome present additional opportunities for drug discovery. It can reveal the information of hereditary diseases, susceptibility to maladies and even the cause of disease in discovery of mutations, deletions and reorganizations in patients. In addition, sequence information on target genomes might present new drug-discovery opportunities. In this latter context, plants possessing some advantages as the source of novel compounds compared with synthetic chemistry could be targets if appropriate sequence information became available. Natural products genomics has therefore become the way to access the plants own genomic capacity and to modify complex bioactive metabolites. For this purpose, natural products genomics has been applied for Nicotiana tabacum and Catharanthis roseus. A combination of gain of function mutagenesis and selection allowed the mimicking of the evolution of novel compounds in plants and permitted an increase in yields of known bioactive metabolites in a rapid screening project of large populations of mutants at cell culture level. Another target genome-sequencing approach has been to analyze new antimalarial chemotypes. Five Plasmodium falciparum parasite lines of distinct geographic origin were studied from arrayed libraries in a high-throughput screening assay. The study revealed three compound classes that demonstrated either differential or comprehensive antimalarial activity. Moreover, the nascent structure–activity relationship allowed further optimization of these chemotypes.

Numerous approaches have targeted the human genome itself but it is only possible to highlight a few of them in this article. In attempts to accelerate the development of next-generation drugs for the treatment of multiple myeloma, the Multiple Myeloma Research Foundation has focused its research investments on genomics and epigenetics. The goal has been to enhance the understanding of the basic biology of multiple myeloma, support clinical development of new treatments and through genomics information link the right treatment to the right patient. Likewise, extensive genome information will provide new opportunities for the development of CNS drugs. Accumulated genetic information of psychiatric illnesses will result in better understanding of the patho-physiological and patho-etiological perspectives and will aid in the development of more targeted treatment of, for instance, Alzheimer’s disease. As molecular genetic alterations are the basis for human cancer, the human genome project has provided new tools for the discovery of novel cancer-associated genes. In this context, digital karyotyping and array-based techniques have been developed to investigate the human cancer landscape. Combined with gene-expression profiling and high-throughput mutational analysis, these technologies will aid the discovery of potential novel oncogenes and tumor suppressors.

Recently, much attention has been given to the observed variations in individual drug responses due to genetic variations in drug metabolism, drug transport and disease susceptibility. These findings resulted in the establishment of pharmacogenomics and provided the means to develop personalized or individualized medicine. The application of gene mapping and deciphering pathogenic mutations have unraveled novel mechanisms and have aided drug discovery, making targeted pharmacotherapy possible. For instance, rapamycin suppressed the mTOR pathway-associated hamartomas in dominantly inherited cancer family syndromes and angiotensin-converting enzyme receptor blockers in preventing aortic dilatation in Marfan syndrome arteriopathies. Pharmacogenomics has proven useful for establishing the basis for antidepressant treatment and the knowledge obtained will strongly support the design of future therapeutics. One of the issues addressed by personalized medicine is the individual drug sensitivity. In efforts to identify the best drug for each cancer patient, merging genomic and pharmacologic analysis of therapy choice (MATCH), an approach to use public genomic resources and drug testing of fresh tumor samples, has been applied to link drugs to patients. MATCH demonstrated that aggressive breast tumor subtypes are most likely to be sensitive to valproic acid and provided useful information to select optimal drug regimens before initiation of clinical trials. Due to the narrow therapeutic index and life-threatening drug toxicity dictated by administration of maximally tolerated doses, up to one-third of the patients may develop unacceptable toxicity. This could be adjusted by thorough genomics screening of patient–drug responsiveness prior to treatment. Whole-exome sequencing identified a potential novel genetic risk factor in a child with VACTERL (vertebral anomalies) association, a heterozygous mutation in carbamoyl phosphate synthetase I, which allowed targeted preventive measures in this patient and relatives with the same mutation. In the context of genomics-based drug development, systems medicine has been proposed for major noncommunicable diseases including cardiovascular, chronic respiratory, metabolic, rheumatologic and neurologic disorders and cancers. In this approach, each disease will not be studied individually. Instead, their intertwined gene environment and socio-economic interactions will be taken into account to build a road map for the so-called P4 medicine approach, including predictive, preventive, personalized and participatory aspects. Moreover, immunogenetics and immunogenomics have been integrated with systems biology by applying cutting-edge, high-dimensional assays combined with novel bioinformatics to develop vaccionomics. These next-generation vaccines will expand the capabilities to generate individualized medicine. An interesting approach to apply genomics has been to initiate the ClinSeq pilot project, where whole-genome sequencing provided large amounts of DNA sequence data from individuals for clinical research. In the initial phase, approximately 1000 participants were enrolled to explore the genetic architecture of disease, implement genomic technology, inform consent, disclose genetic information, and archive, analyze and display sequence data. Several genes that served as positive controls for the project were identified from the initial 826 Mb of sequence data and illustrated how large-scale medical sequencing can be a practical, productive, and a critical component of research in genomic medicine.

An area of drug discovery that has seen a much slower development than originally anticipated in the early 1990s is gene therapy. Lack of sufficient knowledge and some badly planned clinical trials threw gene therapy into despair and resulted in both investors and key industrial players abandoning the field. Fortunately, recent breakthroughs will, hopefully, lead to a serious rethinking and renewed support. In this context, lentivirus vectors provided ongoing remission 10 months after the treatment of leukemia patients. A clearly personalized genomics approach was taken by engineering lentivirus vectors expressing a chimeric antigen receptor with specificity for the B-cell antigen CD19 coupled with the co-stimulatory CD137 T-cell receptor. Lentivirus-transduced T cells were re-infused into patients with refractory chronic lymphocytic leukemia, which resulted in complete remission. The engineered cells persisted for 6 months in the blood and bone marrow and continued to express the chimeric antigen receptor. This example clearly demonstrates how genomics information has been successfully implemented in drug discovery for a personalized gene-therapy medicine.

With all these novel approaches in drug discovery applying genomics, individualized medicine and gene therapy, what will the future hold? The accelerated gene-sequencing techniques will provide access to increasing amounts of genomic data. The imminent risk is that the scientific community will produce more data than can be efficiently handled. It is, therefore, essential to properly develop the technology that will allow us to analyze and understand the generated data. It includes the functional effect of generated sequences, the impact of genetic variation, understanding of complex genetic interactions and the translational novel medicine. The other aspects of future drug discovery are the low success rate and increasing costs of bringing new drugs to the market. Have we run out of novel drug targets? Definitely not! The relatively recent discovery of gene silencing and microRNAs, and their involvement in gene regulation represents numerous interesting novel targets for drug discovery. Due to their nucleotide-based nature, genomics will play a crucial role in the development of these new drugs. However, as with other gene-based drugs, efficient delivery is still a major issue, which needs to be addressed to improve efficacy. In addition, novel pathways discovered for G-protein-coupled receptors and their dimerization provides further possibilities for the development of drugs based on the largest class of current drug targets. As mentioned previously, more sequence data generated from genome sequencing will certainly provide novel central nervous system and cancer drug targets. Obviously, the application of genomics leading to personalized medicine with appropriate information about drug sensitivity and responsiveness might provide better drugs in a shorter time. How to reduce the costs for drug discovery and healthcare in general is another issue. Some reflections will now be presented.

It is tempting to bring up the importance of nutrigenomics in this editorial. Although it is a side step from the mainstream of genomics, its importance should not be underestimated. Independent of success in development of more-efficient drugs, preventive medicine is of utmost importance. It has, already, been demonstrated that dietary changes in prostate cancer patients led to significant modulation of gene expression, which has critical roles in tumorigenesis and protein phosphorylation. It seems that the nutrition affects our gene expression dramatically and changes in diet can repress the expression of ‘bad’ genes and enhance the activity levels of ‘good’ genes after only a few months. Nutrigenomics will, obviously, have a tremendous effect on preventive medicine and, thereby, enormous socio-economic consequences. The increasing costs in drug development and healthcare will certainly put an ever stronger pressure on investing substantial resources in not only treating disease but to allocate efforts to eradicate the causes of disease. Clearly, treatment of disease can be compared with the tip of the iceberg, whereas the preventive medicine approach allows targeting the whole iceberg. Therefore, it is evident that nutrigenomics will play a significant role in preventive medicine. However, we are far from the end of exploring the opportunities of generating novel and innovative drugs with existing and future technology. It is certainly out of the question that genomics would not play a major role in this process. In particular, the field of personalized medicine will profit significantly from strong genomics research.