Figures & data
Table 1. Reported SNP associations (P ≤ 0.05) with TKI treatment outcome in mRCC from 2009 to 2015.
Figure 1. Flowchart of study selection process. Our original search on the 14th of January 2015 resulted in a total of 968 articles (Supplementary document 2). For the first selection by title, there was a disagreement between the two independent reviewers on a number of 114 titles (12%). After consensus was reached with the last review author (HJG), this resulted in a number of 104 articles which was complemented with 33 additional articles of the search from January 14 to May 31, 2015. A total of 134 articles was available for the second selection step based on abstract reading. Consensus had to be reached for 20 of the 134 abstracts (15%) and resulted in exclusion of 67 articles. Consequently, a number of 67 articles underwent full text review and data extraction. Finally, 15 articles were excluded for data extraction because no treatment was evaluated (n = 8), prognostic biomarkers were investigated (n = 5) or these were no original articles but commentaries (n = 2) and using cross-references, we included two additional studies [Citation37, Citation69]. Ultimately, a total of 54 articles was included in our systematic review.
![Figure 1. Flowchart of study selection process. Our original search on the 14th of January 2015 resulted in a total of 968 articles (Supplementary document 2). For the first selection by title, there was a disagreement between the two independent reviewers on a number of 114 titles (12%). After consensus was reached with the last review author (HJG), this resulted in a number of 104 articles which was complemented with 33 additional articles of the search from January 14 to May 31, 2015. A total of 134 articles was available for the second selection step based on abstract reading. Consensus had to be reached for 20 of the 134 abstracts (15%) and resulted in exclusion of 67 articles. Consequently, a number of 67 articles underwent full text review and data extraction. Finally, 15 articles were excluded for data extraction because no treatment was evaluated (n = 8), prognostic biomarkers were investigated (n = 5) or these were no original articles but commentaries (n = 2) and using cross-references, we included two additional studies [Citation37, Citation69]. Ultimately, a total of 54 articles was included in our systematic review.](/cms/asset/0e0afe3b-1dfa-4fd5-96f8-501bd37b47e5/iero_a_1148601_f0001_b.gif)
Figure 2. Main results on associations of SNPs involved in pharmacokinetics or pharmacodynamics of TKIs with clinical treatment outcome in mRCC.
An increased risk for common sunitinib toxicities was seen for SNPs in CYP1A1, NR1I3, ABCB1 and ABCG2. Furthermore, CYP3A5*1 was associated with dose reductions due to toxicity and an increased time-to-dose-reduction (TTDR) was seen for ABCB1 SNPs. Associations with the clearance of sunitinib and/or SU12662 were observed for SNPs in CYP3A5, ABCB1 and CYP3A4. A higher exposure to sunitinib and progressive disease was reported for rs1045642 in ABCB1 in Chinese patients. For efficacy, CYP3A5*1 and SNPs in ABCB1, NR1I2 and NR1I3 were associated with PFS. Associations of CYP3A5*1 with the need for dose reductions and of the ABCB1 haplotype with PFS were confirmed in a larger study [Citation30]. Regarding pharmacodynamics, SNPs in VEGFR2, FLT3, VEGF-A and eNOS were associated with sunitinib toxicities and with hypertension in particular. Associations with either response rate, PFS and/or OS were observed for SNPs in VEGF-A, VEGF-R1, VEGF-R3 and FGF-R2 [Citation19-Citation44]. For pazopanib, only articles from the group of Xu et al. were included in our search. The main findings were that UGT1A1*28, UGT1A1*60 and CYP1A2 (rs762551) were associated with bilirubin levels and SNPs in HFE were associated with increased ALT levels. Additionally, SNPs in IL8, HIF1A, NR1I2 and VEGFA were associated with either PFS or response rate. For patients using either sunitinib or pazopanib, UGT1A1 SNP genotypes *28, *37 and *6 showed an increased risk for hyperbilirubinemia and rs1126647 in IL8 was associated with OS. Only two pharmacogenetic studies on sorafenib were found in which genetic polymorphisms in ABCC2 and HLA-A were associated with high-grade skin rash and rs2071559 in VEGF-R2 was associated with PFS and OS. For axitinib, no associations were reported [Citation40-Citation44].
![Figure 2. Main results on associations of SNPs involved in pharmacokinetics or pharmacodynamics of TKIs with clinical treatment outcome in mRCC.An increased risk for common sunitinib toxicities was seen for SNPs in CYP1A1, NR1I3, ABCB1 and ABCG2. Furthermore, CYP3A5*1 was associated with dose reductions due to toxicity and an increased time-to-dose-reduction (TTDR) was seen for ABCB1 SNPs. Associations with the clearance of sunitinib and/or SU12662 were observed for SNPs in CYP3A5, ABCB1 and CYP3A4. A higher exposure to sunitinib and progressive disease was reported for rs1045642 in ABCB1 in Chinese patients. For efficacy, CYP3A5*1 and SNPs in ABCB1, NR1I2 and NR1I3 were associated with PFS. Associations of CYP3A5*1 with the need for dose reductions and of the ABCB1 haplotype with PFS were confirmed in a larger study [Citation30]. Regarding pharmacodynamics, SNPs in VEGFR2, FLT3, VEGF-A and eNOS were associated with sunitinib toxicities and with hypertension in particular. Associations with either response rate, PFS and/or OS were observed for SNPs in VEGF-A, VEGF-R1, VEGF-R3 and FGF-R2 [Citation19-Citation44]. For pazopanib, only articles from the group of Xu et al. were included in our search. The main findings were that UGT1A1*28, UGT1A1*60 and CYP1A2 (rs762551) were associated with bilirubin levels and SNPs in HFE were associated with increased ALT levels. Additionally, SNPs in IL8, HIF1A, NR1I2 and VEGFA were associated with either PFS or response rate. For patients using either sunitinib or pazopanib, UGT1A1 SNP genotypes *28, *37 and *6 showed an increased risk for hyperbilirubinemia and rs1126647 in IL8 was associated with OS. Only two pharmacogenetic studies on sorafenib were found in which genetic polymorphisms in ABCC2 and HLA-A were associated with high-grade skin rash and rs2071559 in VEGF-R2 was associated with PFS and OS. For axitinib, no associations were reported [Citation40-Citation44].](/cms/asset/0c010193-22af-4194-adfa-b8ccbb611037/iero_a_1148601_f0002_oc.jpg)