Individual risk assessment: The use of toxicogenomics to predict adverse drug responses E. Jongedijk(a), R. Neft(b), K. Schmeiser(a), P. Alen(a) and S. Farr (b) (a) Phase-1 BioResearch, Technologiepark 4, 9052 Zwijnaarde (Gent), Belgium (b) Phase-1 Molecular Toxicology, 2904 Rodeo Park Drive East, Santa Fe (NM) 87505, USA Introduction It has long been known that people, when given the same therapeutic drug, can react quite differently. Phase-1 has developed a technology to identify, in advance, which patient will develop an adverse drug reaction (ADR). This knowledge will not only be beneficial to the sub-population of patients with certain ADRs but will also help to keep good drugs on the market and reduce the liability for drug manufacturers. Phase-1’s approach to determine gene expression profiles predictive of ADR involves three steps. Firstly, using transcriptome fingerprinting , all differentially expressed genes indicative for the treatment are identified. This open-ended technique is based on mRNA differential display. The second step is to use a higher throughput technique, such as microarrays, to screen a population of sensitive and non-sensitive individuals using the identified gene set. Finally; the third step is to move the predictive genes only to a clinical-applicable platform, such as RT-PCR based “Risk Cards”, co-developed with Applied Biosystems. Experimental design Figure 1: Culturing cells for transcriptome fingerprinting. To perform a proof-of-principle study the well-characterized drug
Lymphocytes from 3 penicillin sensitive and 3 penicillin non-sensitive individuals were treated with penicillin before isolating the RNA for transcriptome fingerprinting. penicillin. The incidence of penicillin sensitivity is estimated to be as high as 10% in the general population and the adverse reactions to penicillin range from mild skin rashes to severe exfoliative dermatitis. Cultured lymphocytes in the presence of PHA for 24 hours Because white blood cells, the target cells for allergies, are easily Whole blood Isolated lymphocytes accessed and because many penicillin sensitive people are available in the general population, this is an excellent candidate for a gene Transcriptome Fingerprinting expression study. Wash cells with PBS and culture for additional 24 hours without PHA 1) Transcriptome fingerprinting An open-ended technique, termed transcriptome fingerprinting, has Untreated been used to identify all differentially expressed genes in lymphocytes RNA isolation Divide cells equally and stimulate with penicillin for 24 hrs following Penicillin G treatment. Lymphocytes from sensitive and non- sensitive individuals were cultured in vitro and treated with penicillin G. 1 2 3 4 1 2 3 4 1 2 3 4 1 2 3 4 Untreated cells from each individual were used as negative controls. The 1 2 3 41 2 3 4 1 2 3 4 1 2 3 4 total RNA was isolated from treated and untreated lymphocytes and Figure 2: Transcriptome fingerprinting in lymphocytes from two individuals. applied to transcriptome profiling (Figure 1). 30 arbitrary primers were
Each group of four lanes represents a single primer combination. The gel shows
used to perform 90 reactions, covering approximately 71% of the total
samples using untreated (lanes 1 and 3) and treated (lanes 2 and 4) lymphocytes
transcriptome (Figure 2).
from penicillin sensitive (lanes 1 and 2) and non-sensitive (lanes 3 and 4) individuals. The red arrows point at differentially expressed genes indicating a
response in the penicillin sensitive individual (up-regulation after the treatment), whereas the green arrow points at an up-regulated gene indicating a response in
Once all differentially expressed gene between sensitive and non-
the non-sensitive person only. The blue arrow highlights a basal difference
sensitive peoples were identified they were excised from the gel, amplified, cloned, sequenced and used as targets on a customized microarray. RNA samples provided from 8 sensitive and 8 non-sensitive individuals Figure 3: Transfer of the marker genes from the were processed using the customized microarray. Gene expression customized microarray (a) onto a high-throughput profiles from the two populations were analyzed to select a small platform (b). number of “discriminator genes” that were most differentially expressed
Independent-samples T-tests were performed to suggest
between sensitive and non-sensitive people (Figure 3).
which genes discriminate best between the sensitive and
non-sensitive people. Twenty-one genes (p ≤ 0.005) were identified and transferred onto a clinically available
platform (TaqMan technology based risk-cards).
The “discriminator genes” were moved onto 96-well format ‘Risk-Cards’, allowing a fast, sensitive and semi-quantitative parallel measurement of the 21 genes in quadruplicate. As little as 60-800ng of RNA is required Figure 4: Correlation matrix using Phase1’s for this card-based assay allowing the use of small blood or biopsy Non-sensitive Sensitive 1 2 3 4 5 6 1 2 3 4 5 6 7 8 9 software. samples. Non-sensitive
The 21 identified “discriminator” genes were used to
Non-sensitive It has been verified that both platforms, single-stranded cDNA Non-sensitive
calculate a correlation matrix. Bright colors indicate a high
Non-sensitive microarrays (using Phase-1’s technology) and risk-cards (using the Non-sensitive
correlation between individuals whereas dark colors
indicate low correlation between individuals. It is
TaqMan technology), result in the same gene expression profile (data Sensitive Sensitive
interesting to note that sensitive individuals more highly
not shown). Sensitive Sensitive
resemble each other (red box). The non-sensitive
individual #2, however, continues to resemble the
sensitive individuals indicating a sensitivity to penicillin, which was confirmed by an allergist.
Conclusions The combination of the three steps described above allows the identification and validation of gene patterns predicting individuals at risk for developing adverse drug hypersensitivity. Both, patients and healthcare industry, can benefit from this powerful genomic tool. Potential compounds for the application of Phase-1’s individual risk assessment are drugs that a) have been withdrawn from the market, b) that are restricted in use or c) that require frequent patient monitoring because of adverse responses in a subset of the population.
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