Efflux pump ABCB1 single nucleotide polymorphisms and dose reductions in patients with metastatic renal cell carcinoma treated with sunitinib

Figures & data

Table IA. Analyzed SNPs linked to sunitinib pharmacokinetics.

Polymorphism	Number of patients therapy	Reasons for selection of SNPs for this project
ABCB1
rs1128503 1236C > T	88 pts Sunitinib	Better PFS (19 vs. 8 months; p = 0.027) and OS (34 vs. 21 months; p = 0.025) in the CC/CT-genotype compared to the TT-genotype in rs1128503 [9].
rs1045642 3435C > T	89 pts Sunitinib	Trend to better PFS (HR 1.42; p = 0.089) and better OS (HR 1.75; p = 0.055) in favor of the CC- and CT-genotype in rs1128503 [8].
rs2032582 2677G > T or G > A	129 pts Sunitinib	Better PFS (15.2 vs. 8.4 months; p = 0.033) and a tendency for prolonged OS (23.9 vs. 15.4 months; p = 0.078) in presence of a TCG haplotype (rs1045642 – rs1128503 – rs2032582) in ABCB1 (thus a CC-genotype in rs112503) [7].
	241 pts Pazopanib	Better OS (28 vs. 20 months, p = 0.009) in the CC-genotype compared to the TT-genotype in rs1128503 [12].
CYP3A5
rs776746 6986G > A	128 pts Sunitinib	Better PFS (not reached vs. 9.3 months) for the AA- and AG-genotypes compared to the GG-genotypes (p = 0.032) [7].
	84 pts Sunitinib	More dose-reductions (HR 3.75; p = 0.022) in the AG-genotype compared to the GG-genotype [8].
NR1/2
rs3814055 25385C > T	136 pts Sunitinib	Better PFS (10.8 vs. 6.7 months; p = 0.025) and better OS (17.1 vs. 10.2 months; p = 0.017) for the CT- and CC-genotypes compared to the TT-genotype [7].
	241 pts Pazopanib	Better OS for the CC-genotype: 29 vs. 22 vs. 23 months for the CC-, CT- and TT-variants, respectively (p = 0.03) [11].
NR1/2
rs2276707 8055C > T	136 pts Sunitinib	Better PFS (10.8 vs. 6.7 months) in the CC- and CT-genotypes compared to the TT-genotype (p = 0.025) [7].
	83 pts Sunitinib	Better PFS (18 vs. 7 months; p = 0.047) and trend for better OS (31 vs. 12 months; p = 0.08) in the GG- and GT-genotype compared to the TT-genotype [9].
NR1/3
rs4073054 7837T > G	135 pts Sunitinib	Better PFS (13.3 vs. 8.0 months) if a CAT-copy was absent in the NR1/3 haplotype composed of rs2307424, rs2307418 and rs4073054 (thus no TT-genotype in rs4073054) (p = 0.017) [7].
	87 pts Sunitinib	Better PFS (21 vs. 12 months; p = 0.025) and OS (35 vs. 22 months; p = 0.035) in the GG- and GT-genotype compared to the TT-genotype [9].

OS, overall survival; PFS, progression-free survival; Pts, patients; SNP, single nucleotide polymorphism.

Table IB. Analyzed SNPs linked to sunitinib pharmacodynamics.

Polymorphism	Number of patients therapy	Reasons for selection of SNPs for this project
VEGFR1
rs9582036 319A> C	91 pts Sunitinib	Better PFS (18 vs. 10 months; p = 0.06) and better OS (31 vs. 14 months; p = 0.008) in the AA- and AC-genotypes compared to the CC-genotype [10].
VEGFR3
rs307826 1480A> G	89 pts Sunitinib	Better PFS (13.7 vs. 3.6 months; p = 0.0079) in the AA-genotype compared to the AG-genotype [8].
	241 pts Pazopanib	OS of 26, 23 and 3.2 months for the AA-, AG- and GG-genotypes, respectively (p = 0.04) [12].
	88 pts Sunitinib	Better PFS (19 vs. 10 months; p = 0.051) and OS (31 vs. 22 months; p = 0.013) in the AA-genotype compared to the AG- and GG-genotype [9].

OS, overall survival; PFS, progression-free survival; Pts, patients; SNP, single nucleotide polymorphism.

Table II. Patient characteristics at diagnosis of mRCC and at the start of sunitinib treatment.

At initial diagnosis	Total
Male	72% (69/96)
Mean age	59 years
Ethnic origin
Caucasian	95% (91/96)
Unknown	5% (5/96)
Synchronous metastasis	51% (47/93)
Fuhrman grade
1–3	46% (43/94)
4	54% (43/94)
Clear cell histology	92% (88/96)
At the start of sunitinib
ECOG PS > 0	42% (40/96)
Neutrophils > 4.500/mm³	43% (40/94)
Platelets > 400.000/mm³	13% (12/96)
Hemoglobin low [< 11.5 g/dl (women) or < 13 g/dl (men)]	43% (41/96)
LDH > 1.5 ULN	9% (8/94)
Corrected Calcium > 10 mg/dl	8% (7/93)
Time from nephrectomy to systemic treatment < 12 months	63% (90/96)
Immunotherapy before sunitinib	25% (24/96)
Site of metastasis
Lung	79% (76/96)
Liver	20% (19/96)
Bone	39% (37/96)
Brain	7% (7/96)
IMDC prognosis
Favorable	14% (13/96)
Intermediate	59% (57/96)
Poor	27% (26/96)

ECOG PS, Eastern Cooperative Oncology Group Performance Status; IMDC, International Metastatic Renal Cell Carcinoma Database Consortium; LDH, lactate deshydrogenase; ULN, upper limit of normal.

Table III. Genotype and allele distribution of selected SNPs.

RS ID	Polymorphism	Location or functional consequence	n	Wildtype/Wildtype n (%)	Wildtype/Variant n (%)	Variant/Variant n (%)	Observed minor allele frequency (%)	Minor allele frequency in dbSNP (%)
ABCB1
rs1045642	3435C > T	I1154I	96	27 (28)	49 (51)	20 (21)	46.3	53.4
rs1128503	1236C > T	G412G	95	36 (39)	43 (45)	16 (17)	39.5	45.1
rs2032582	2677G > T or G > A	A893S	89	32 (36)	42 (47)	15 (17)	40.5	41.7
CYP3A5
rs776746	6986G > A	Affecting splicing	88	78 (89)	11 (8)	0 (0)	6.3	3.6
NR1/2
rs3814055	25385C > T	UTR-5	93	36 (39)	39 (42)	18 (19)	40.3	33.6
rs2276707	8055C > T	Intron	91	60 (66)	25 (27)	6 (7)	20.3	9.3
NR1/3
rs2307424	5719C > T	P151P	96	49 (51)	37 (39)	10 (10)	29.6	33.6
rs2307418	7738A > C	Intron	96	71 (74)	25 (26)	1 (1)	14.1	15.9
rs4073054	7837T > G	Intron	96	38 (40)	43 (45)	15 (16)	39.1	40.7
VEGFR1
rs9582036	319A > C	Intron	96	46 (48)	41 (43)	9 (9)	30.7	31.3
VEGFR3
rs307826	1480A > G	T494A	96	72 (75)	22 (23)	2 (2)	13.5	10.2

n, number of patients with successful determination of polymorphisms. Note that rs2307424 and rs4073054 in NR1/3 were analyzed because of their involvement in the CAT-haplotype [6]. rs2032582 and rs1045642 in ABCB1 were analyzed because of their involvement in the TCG-haplotype [6].

Figure 1. Impact of ABCB1 rs1128503 variants on timing of dose reductions.

Figure 2. Impact of ABCB1 rs2032582 variants on dose reductions.

Figure 3. Impact of NR1/2 rs2776707 variants on dose reductions.

Table IV. Univariate analysis: association between SNPs and time of dose reduction.

Gene (a) SNP ID	Polymorphism	No. of patients	Median TTDR (cycles)	p (UV)	HR	95% CI of HR
ABCB1
rs1128503	CT + CC	73	7	0.031	2.278	1.077–4.820
1236C > T	TT	15	19
ABCB1
rs1045642	CC	27	12	0.26	NA	NA
3435C > T	CT	49	7
	TT	20	19
	CC + CT	76	9	0.47	NA	NA
	TT	20	19
ABCB1
rs2032582	GG	32	11	0.048	NA	NA
2677G > T or G > A	GT/GA	42	5
	TT/TA	15	19
	GG + GT/GA	74	7	0.046	2.106	1.015–4.371
	TT/TA	15	19
CYP3A5
rs776746	GG	78	9	0.23	NA	NA
6986G > A	AG	10	NR
NR1/2
rs3814055	CC + CT	75	10	0.35	NA	NA
25385C > T	TT	18	5
NR1/2
rs2276707	CC + CT	85	7	0.027	2.954	1.132–7.707
8055C > T	TT	6	41.5
NR1/3
rs2307424	CC	49	11	0.90	NA	NA
5719C > T	CT + TT	47	7
NR1/3
rs2307418	AA	71	10	0.92	NA	NA
7738A > C	AC + CC	25	7
NR1/3
rs4073054	TT	38	7	0.92	NA	NA
7837T > G	TG + GG	58	9
VEGFR1
rs9582036	AA + AC	87	9	0.46	NA	NA
319A > C	CC	9	5
VEGFR3
rs307826	AA	72	9	0.85	NA	NA
1480A > G	AG + GG	24	9

p-values were calculated by a log-rank test. HR, hazard ratio; NA, not applicable; 95% CI, 95% confidence interval; TTDR, time-to-dose-reduction; UV, univariate analysis.

For ABCB1 rs1128503, we analyzed genotype TT against and the combination of genotype CC and CT, because four previous publications clearly associated the TT-variant with poor outcome. For ABCB1 rs1045642 and rs2032582, we analyzed the three genotypes separately and then combined the genotypes in function of the obtained graphs, isolating the groups that were associated to the longest TTDR. In case of CYP3A5, there were no AA-variants in our series. For NR1/2, the variants were combined as it was done in the original publications isolating the patients with TT-genotype, associated with poorer outcome. For NR1/3 rs2307424, the analysis of the three genotypes separately did not result in a significant difference in TTDR. We report the combination of the genotypes as it was done in previous publications. For NR1/3 rs2307418, there was only one patient with the CC-genotype. For NR1/3 rs4073054, we compared the TT-genotype to the TG- and GG-genotype because the TT-genotype was associated to poorer survival. For VEGFR1 rs9582036, the genotypes were pooled as it was done in the original publication. For VEGFR3 rs307826, there were only two patients with the GG-genotype: they were pooled with the GA-genotype patients.

Figure 4. Impact of ABCB1 rs1128503 variants on progression-free survival.

Figure 5. Impact of ABCB1 rs1128503 variants on overall survival.

Beuselinck B, Karadimou A, Lambrechts D, Claes B, Wolter P, Couchy G, et al. Single nucleotide polymorphisms associated with outcome in metastatic renal cell carcinoma treated with sunitinib. Br J Cancer 2013;108:887–900.

 PubMed Web of Science ®Google Scholar

Garcia-Donas J, Esteban E, Leandro-García LJ, Castellano DE, Del Alba AG, Climent MA, et al. Single nucleotide polymorphism associations with response and toxic effects in patients with advanced renal-cell carcinoma treated with first-line sunitinib: A multicentre, observational, prospective study. Lancet Oncol 2011;12:1143–50.

 PubMed Web of Science ®Google Scholar

van der Veldt AA, Eechoute K, Gelderblom H, Gietema J, Guchelaar HJ, van Erp NP, et al. Genetic polymorphisms associated with a prolonged progression-free survival in patients with metastatic renal cell cancer treated with sunitinib. Clin Cancer Res 2010;17:620–9.

 PubMed Web of Science ®Google Scholar

Xu CF, Ball HA, Bing N, Sternberg C, Xue Z, McCann L, et al. Association of genetic markers in angiogenesis- or exposure-related genes with overall survival in pazopanib-treated patients with advanced renal cell carcinoma. J Clin Oncol 2011;29(Suppl 7):abstr 303.

 Web of Science ®Google Scholar

Xu CF, Bing N, Ball H, Rajagopalan D, Sternberg C, Hutson T, et al. Pazopanib efficacy in renal cell carcinoma: Evidence for predictive genetic markers in angiogenesis- related and exposure-related genes. J Clin Oncol 2011; 29:2557–64.

 PubMed Web of Science ®Google Scholar

Beuselinck B, Karadimou A, Lambrechts D, Claes B, Wolter P, Couchy G, et al. VEGFR1 single nucleotide polymorphisms associated with outcome in patients with metastatic renal cell carcinoma treated with sunitinib – a multicentric retrospective analysis. Acta Oncol 2014;53: 103–12.

 PubMed Web of Science ®Google Scholar

Rini BI, Cohen DP, Lu DR, Chen I, Hariharan S, Gore ME, et al. Hypertension as a biomarker of efficacy in patients with metastatic renal cell carcinoma treated with sunitinib. J Natl Cancer Inst 2011;103:763–73.

 PubMed Web of Science ®Google Scholar