Feng, Xiaodong_ Xie, Hong-Guang - Applying pharmacogenomics in therapeutics-CRC Press (2016)

78 Applying Pharmacogenomics in Therapeutics
Exons 5’
5’
RNA
AAAAAA
AAAAAA
5’ 5’
Exon baits
Exon baits
Whole genome
Whole exome (1%)
PCR amplicon
Transcriptome RNA
Exon capture transcriptome
Predominant applications:
• Gene expression
• Gene fusions
• Splice variants
Predominant applications:
• Structural variants
• Point mutations
• Copy-number variation
Predominant applications:
• Point mutations
• Copy-number variation
Predominant applications:
• Point mutations
• Deletions
Predominant applications:
• Gene expression
• Gene fusions
• Splice variants
FIGURE 4.1 Genomic profiling allows for the unbiased identification of genetic alterations
within patient samples. As outlined in the diagram below, different methodologies can be
used to detect different types of genetic alterations. Analysis of RNA samples is often desirable
for drug discovery studies because the genetic alterations that are identified are more
likely to be causative in the disease process and are therefore more likely to make good drug
targets. (Adapted from Simon R, Roychowdhury S, Nat Rev Drug Discov, 12, 358–69, 2013.)
can acquire genetic alterations while in culture that may drive disease but are not
relevant to patients. In addition, in many cases an insufficient number of cell lines
that are representative of the patient population exists. An advantage is that the cell
line–based approach is inexpensive and less time consuming compared to patient
specimen collection and analysis. Although the use of patient specimens faces challenges,
it is more likely to identify relevant drug targets. One of the biggest challenges
is obtaining a large enough sample set that is representative of the patient
population for the analyses. The size of biorepositories is often limited by the cost
associated with their maintenance and the need for patients to consent to donation
of biospecimens. 20,21 In addition, patients from minority populations are less likely
to donate biospecimens to biorepositories, meaning that the sample set may not be
representative of that patient population. 22–24 Having a large sample set is usually
important for drug target discovery because the vast majority of diseases have more
than one cause, and it is highly likely that not all patients with the disease will harbor
a particular genetic alteration; a large sample set is therefore necessary to identify
genetic alterations that are associated with disease. Working with a large sample
set also provides a good estimate of the prevalence of the genetic alteration in the
patient population, and if a large number of genes are being surveyed, working with
a large sample set helps reduce the risk of generating false positives.
Histological and/or cytological analyses have been successfully used to identify
genetic alterations and have led to the development of several “blockbuster” drugs.
However, it is challenging to use these methodologies for large-scale screenings of
samples, and for the most part histological and/or cytological studies can only be
used to identify major alterations such as chromosomal rearrangements. The development
of imatinib (Gleevec; www.gleevec.com) was made possible by cytological
analyses; cytological analyses identified a chromosomal abnormality, referred to as the
Philadelphia chromosome, in patients with chronic myelogenous leukemia (CML). 25