Genetic biomarkers of sorafenib response in patients with hepatocellular
carcinoma
Abstract
Purpose: The identification of biomarkers for predicting
inter-individual sorafenib response variability could allow
hepatocellular carcinoma (HCC) patients stratification. SNPs in
angiogenesis- and drug absorption, distribution, metabolism, and
excretion (ADME)-related genes were evaluated to identify new potential
predictive biomarkers of sorafenib response in HCC patients. Methods:
Five known SNPs in angiogenesis-related genes, including VEGF-A, VEGF-C,
HIF-1a, ANGPT2 and NOS3, were investigated in 34 HCC patients (9
sorafenib responders and 25 non-responders). A subgroup of 23 patients
was genotyped for SNPs in ADME genes. A machine learning classifier
method was used to discover classification rules for our dataset.
Results: We found that only VEGF-A (rs2010963) C allele and CC genotype
were significantly associated with sorafenib response. ADME-related gene
analysis identified 10 polymorphic variants in ADH1A (rs6811453), ADH6
(rs10008281), SULT1A2/CCDC101 (rs11401), CYP26A1 (rs7905939), DPYD
(rs2297595 and rs1801265), FMO2 (rs2020863) and SLC22A14 (rs149738,
rs171248 and rs183574) significantly associated with sorafenib response.
We have identified a genetic signature of predictive response which
could permit non-responder/responder patient stratification.
Angiogenesis- and ADME-related genes correlation was confirmed by
cumulative genetic risk score and network and pathway enrichment
analysis. Conclusions: Our findings provide a proof of concept that need
further validation in follow-up studies for HCC patient stratification
for sorafenib prescription.