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

64 Applying Pharmacogenomics in Therapeutics
SLCO1B1 (encoding solute carrier organic anion transporter family, member 1B1).
For example, three SNPs, rs1128503 (synonymous), rs2032582 (missense), and
rs1045642 (synonymous) located in ABCB1, have been demonstrated to influence
directly on statin pharmacokinetics and indirectly on statin pharmacodynamics,
considering the important role of ABCB1 in transporting statins and metabolites; 108
SNPs rs5883 (synonymous) and rs9930761 (intronic) in CETP gene, the protein
product of which shuttles cholesterol esters from high-density lipoprotein (HDL)
particles to low-density lipoproteins (LDL), have been associated with HDL levels,
risk for coronary artery disease, and response to statin therapy. 109 SNPs rs5908
( missense) and rs12916 (3′-UTR) in HMGCR gene, which encodes an enzyme catalyzing
a rate-limiting step in cholesterol biosynthesis, were found to be significantly
associated with attenuated LDL cholesterol reduction as well as racial differences in
statin therapy; 110 and SNP rs4149056 (missense) in SLCO1B1 gene, which encodes
a transporter that transports certain hormones, toxins, and drugs into the liver for
removal from the body, was found to be associated with simvastatin-induced myopathy
in patients, while the effect of rs4149056 on statin pharmacokinetics was shown
to vary with statin type. 111 In addition, a multiple-loci interaction model that combines
polymorphisms from different candidate genes was shown to be a better predictor
for LDL cholesterol-lowering effects. 112
Cancers
During the past decade, cancer research has witnessed extensive utilization of novel
high-throughput profiling technologies. Large cancer-focused projects, such as
the Cancer Genome Atlas (TCGA) Project sponsored by the National Institutes of
Health, have begun to significantly enhance our current knowledge of cancer pathogenesis
and responses to therapeutics. Pharmacogenomic biomarker discovery for
anticancer drugs has benefited from these technological advances, with novel biomarkers
being identified for better prediction of sensitivity to cancer therapies. We
showcase here some novel biomarkers recently proposed or developed for anticancer
drug responses, particularly using hematological malignancies as an example.
For example, Ph+/Ph− status for the Philadelphia chromosome has been proposed
to be a “chromosomal” biomarker that may predict survival response to TKIs, including
imatinib and nilotinib, used to treat chronic myeloid leukemia (CML). Previous
studies suggested that treatment with these TKIs significantly improves survival
compared with survival rates in the pre-TKI era in patients with Ph+ CML. 113–115
With the availability of these TKIs, a molecular biomarker, BCR-ABL gene fusion,
which represents the product of Ph+ status, could enable us to measure the molecular
response to the TKIs, thus helping determine treatment efficacy and guide further
clinical decision. A recent study showed that assessment of BCR-ABL1 transcript
levels at three months was the only requirement for predicting outcome for patients
with CML treated with TKIs. 116 However, this molecular biomarker has not yet been
validated sufficiently to be cleared by the US FDA for clinical use.
Another example of recently implicated novel biomarkers for anticancer drug
response is the mutation status of JAK2 gene (which encodes Janus kinase 2) in
treating acute myeloid leukemia (AML). Previous studies showed that although