S. K. Anderson1, J. M. Lafky1, X. W. Carrero1, T. K. Kimlinger1, T. M. Halling1, S. Kumar1, P. J. Flynn2, H. M. Gross3, K. A. Jaeckle4, J. C. Buckner1, E. Galanis1

(1Mayo Clinic, Rochester, MN; 2Metro Minnesota CCOP, St. Louis Park, MN; 3Hematology and Oncology of Dayton, Dayton, OH; 4Mayo Clinic in Florida, Jacksonville, FL)

Abstract ID: 2019

Single nucleotide polymorphisms (SNPs) and circulating endothelial cells (CECs) as outcome predictors in recurrent glioblastoma (rGBM) patients (pts) treated with bevacizumab (BEV) and sorafenib (SOR)

Abstract (Updated)Background: There is a lack of biomarkers to predict outcome or monitor antiangiogenesis therapies. We investigated whether SNPs or CECs could predict treatment efficacy/toxicity in rGBM pts treated with bevacizumab and sorafenib.

Methods: Blood was obtained for SNP and CEC analyses from rGBM pts enrolled in the Phase II trial N0776 (Galanis et al., ASCO. 2010). VEGF, VEGFR2, and HIF-1alpha SNPs were analyzed by TaqMan® or direct sequencing. Blood for CECs was collected at baseline, cycle 1 day 3, prior to treatment cycles 2, 3, 5, 7, 9, 11, 13, and at the time the pt went off study. CECs were enumerated by flow cytometry. Unequal variance two-sample and paired t-tests were performed to compare values between pt outcome groups and serial measurements within a pt, respectively.

Results: All 54 enrolled pts had DNA available for SNP analyses. Significant differences (Fisher’s Exact, p<0.05) were observed between genotypes and either progression free survival at 6 months (PFS6) (VEGF rs1005230, rs1570360, rs699947, rs833061, VEGFR2 rs2071559) or grade 3+ adverse events (AEs) fatigue (VEGF rs10434, rs1005230, rs699947, rs833061) or hypertension (rs1005230, rs699947, rs833061). The false discovery rate was 11% after correcting for multiple comparisons (method of Benjamini & Hochberg). Kaplan-Meier and Cox proportional hazard models demonstrated that only SNPs in the VEGF promoter were associated with PFS. None of the SNPs examined were associated with overall survival (OS). CEC analysis was performed on 49 of 54 pts. Median baseline CECs (bCEC) were 83.3 (mean: 136; range: 6.5-594) cells/mL; there was no correlation between bCEC values and PFS6 (p=0.19). Absolute differences between bCECs and other time points were not significant; yet, the CEC log2-fold change (FC) from bCECs decreased during treatment and reached significance at cycles 2, 7, 9, and 11 (0.03, 0.047, 0.004, and 0.005, respectively). Differences in log2-FC from bCECs to off study CECs (≤ 14 days) for pts off study for progression was higher compared to pts off study for other reasons (p=0.02, t-test).

Conclusions: Based upon this 54 pt cohort, further biomarker studies examining the utility of SNPs for predicting PFS and AEs and use of CEC monitoring for predicting pt progression in rGBM pts treated with BEV/SOR appear warranted.

Background

• GBM is characterized by intense angiogenesis (Jain et al, 2007).

• N0776 was designed to test the hypothesis of a complete blockage of the VEGF signaling pathway by combining an anti-ligand (bevacizumab) with a multi-targeted receptor kinase inhibitor (sorafenib) approach could result in synergistic inhibitory effects of tumor angiogenesis.

• SNPs involved in the VEGF/VEGFR2 pathway may relate to antiangiogenesis treatment efficacy and toxicity.

• Previous studies have demonstrated that CEC increase is associated with progression on treatment in GBM pts treated with an anti-VEGFR tyrosine kinase inhibitor (Batchelor, 2007).

SNP (n=54)6 month PFS

(p value*)Fatigue

(p value*)Hypertension

(p value*)Skin reaction

(p value*)

rs699947 0.011 0.022 0.006 0.085

rs1005230 0.011 0.022 0.006 0.085

rs833061 0.013 0.014 0.010 0.071

rs1570360 0.004 0.072 0.153 0.227

rs2010963 0.055 0.114 0.233 0.084

rs25648 0.145 0.065 0.154 0.103

rs3025039 0.324 0.286 0.322 0.215

rs10434 0.100 0.025 0.123 0.166

rs2305948 0.324 0.286 0.341 0.429

rs2071559 0.025 0.052 0.085 0.168

rs1870377 0.098 0.093 0.152 0.055

rs2219471 0.107 0.082 0.188 0.268

rs11549465 0.157 0.438 0.516 0.670

ConclusionsIn rGBM pts treated with BEV/SOR, there appears to be a trend for:

• Increased PFS6 successes in rGBM pts with mutant alleles in the VEGF promoter (rs699947 and rs833061) and VEGFR2 promoter (rs2071559). These pts, therefore, may benefit from combined treatment with BEV/SOR.

• Fewer PFS6 successes in rGBM pts with the mutant allele in the rs1005230 and rs1570360 VEGF promoter. These pts, therefore, may not benefit from combined treatment with BEV/SOR.

• Increased grade 3+ fatigue and hypertension in rGBM pts with heterozygous alleles in the VEGF promoter (rs1005230, rs699947, and rs833061).

• Increased grade 3+ fatigue in rGBM pts with heterozygous alleles in the VEGF 3’UTR (rs10434).

Although there was no correlation between bCEC values and PFS6 (p=0.19) in rGBM pts treated with BEV/SOR, monitoring the differences in CEC log2-FC from baseline during this treatment combination may predict progression.

The relationship between the promoter SNPs and VEGF/VEGFR2 transcription and protein levels, as well as the association between these promoter SNPs and PFS6 and grade 3+ fatigue and hypertension in rGBM pts treated with BEV/SOR needs to be further elucidated. In addition, further prospective validation of the monitoring of CECs in rGBM pts treated with this combination is warranted.

*Fisher’s Exact Test p-value

Table 2SNP Relationships

MethodsN0776 Specific Characteristics:• Eligibility criteria included: histological confirmation of GBM as

determined by central pathology review, evidence of tumor progression following RT, < 1 regimen for recurrent disease, and ECOG performance status 0, 1, or 2.

• Exclusion criteria included: poorly controlled hypertension, bleeding diathesis, anticoagulation, and prior antiangiogenic therapy.

• Patients were treated with sorafenib (200 mg orally BID, days 1-14) and BEV (5 mg/kg IV) every 14 days. Due to high incidence of toxicity, sorafenib dose after the first 19 pts was modified to 200 mg qd.

• Primary endpoints: PFS rate at 6 months and safety.Secondary endpoints: time to progression and overall survival.

Statistical design:• All evaluable N0776 pts provided peripheral blood for germline

DNA extraction and subsequent SNP genotyping (Table 1); Genotyping was performed in the Genotyping Shared Resource, Mayo Clinic, Rochester, MN, using TaqMan® Drug Metabolism Genotyping Assays (Applied Biosystems, Foster City, CA) or direct sequencing.

• Fisher’s exact tests were used to determine if genotype was associated with the response of interest (PFS6, or the most common 3+ adverse events, i.e., fatigue [24%], hypertension [15%], and skin reaction-hand/foot [9%]).

• Kaplan-Meier and Cox proportional hazard models were used to compare PFS and OS between genotype subgroups.

• 49 of 54 pts provided EDTA whole blood for CEC analysis. CECs were enumerated by flow cytometry. Unequal variance two-sample and paired t-tests were performed to compare values between pt outcome groups and serial measurements within a pt, respectively.

Results• 54 rGBM pts were enrolled. Mean age was 54.4 years (range:

25-76). Median PFS was 2.9 months (95% CI: 2.3-3.6) and median OS was 5.6 months (95% CI: 4.7-8.2). Fifty-two pts are off study. Thirty-nine (72 %) and 6 (11 %) pts experienced treatment-related grade 3 or 4 AE and grade 4 AE, respectively.

• Mutant alleles in the VEGF promoter and in the VEGFR2 promoter were associated with PFS6; heterozygous alleles in the VEGF promoter and VEGFR2 promoter were associated with an increase in grade 3+ fatigue and hypertension; heterozygous alleles in the VEGF 3’UTR were associated with an increase in grade 3+ fatigue (Table 2); no differences were observed between the genotype subgroups and either PFS6 or the most common grade 3+ AEs for the remaining SNPs analyzed.

• Mutant alleles in the VEGF promoter were associated with PFS (Fig. 1), but not OS. No associations were observed between the other SNPs examined and PFS or OS.

• There was no correlation between bCEC values and PFS6 (p=0.19; DNS); there were no differences between absolute bCECs and other time points; however, the CEC log2-FC from bCECs decreased during treatment and reached significance at cycles 2, 7, 9, and 11 (Fig. 2A); and differences in log2-FC from bCECs to off study CECs (≤ 14 days) for pts off study for progression was higher compared to pts off study for other reasons (Fig. 2B).

AA(0, 0%)

GA(0, 0%)

GG(54, 100%)

C_34492744_10Exon 12(Ala588Thr)

1762G>Aa 2166G>Ab

rs11549467

TT(0, 0%)

CT(4, 7.4%)

CC(50, 92.6%)

C_25473074_10Exon 12(Pro582Ser)

1744C>Ta 2148C>Tb

rs11549465HIF1-NM_001530.3

GG(3, 5.6%)

AG(19, 35.2%)

AA(32, 59.3%)

C_1673874_1_Intron 202818-37A>Gars2219471

AA(4, 7.4%)

TA(21, 38.9%)

TT(29, 53.7%)

C_11895315_20Exon 11(Gln472His)

1416T>Aa

1718T>Abrs1870377

TT(0, 0%)

CT(11, 20.4%)

CC(43, 79.6%)

C_22271999_20Exon 7(Val297Ile)

889C>Ta 1191C>Tbrs2305948

CC(14, 25.9%)

TC(27, 50.0%)

TT(13, 24.1%)

C_15869271_10Promoter906T>Ca 604T>Cbrs2071559

VEGFR2NM_002253.2

AA(9, 16.7%)

GA(29, 53.7%)

GG(16, 29.6%)

C_1647360_203’-UTR1612G>Aa

2650G>Abrs10434

TT(0, 0%)

CT(11, 20.4%)

CC(43, 79.6%)

C_16198794_103’-UTR936C>Ta

1974C>Tbrs3025039

TT(1, 1.9%)

CT(18, 33.3%)

CC(35, 64.8%)

C_791476_105’-UTR-7C>Ta

1032C>Tbrs25648

CC(1, 1.9%)

GC(23, 42.6%)

GG(30, 55.6%)

C_8311614_105’-UTR-634G>Ca

405G>Cbrs2010963

AA(4, 7.4%)

GA(26, 48.2%)

GG(24, 44.4%)

C_1647379_10Promoter-1154G>Aa

-116G>Abrs1570360

TT(10, 18.5%)

CT(32, 59.3%)

CC(12, 22.2%)

C_1647381_10Promoter-1498C>Ta

-460C>Tbrs833061

TT(12, 22.2%)

CT(30, 55.6%)

CC(12, 22.2%)

C_8311612_10Promoter-2489C>Ta

-1451C>Tbrs1005230

CC(12, 22.2%)

AC(30, 55.6%)

AA(12, 22.2%)

C_8311602_10Promoter-2578A>Ca

-1540A>Cbrs699947

VEGFNM_001171623.1

MutantHeterozygous Wild-type

Genotype(frequency, percentage)

ABI Assay IDGene structure location

Gene position of SNPSNP (n=54)Gene

Table 1SNPs Analyzed and Genotype Frequencies

a Position relative to translation start site. b Position relative to transcription initiation site.

Figure 2 CEC Changes

A.

B.

Figure 1 PFS by VEGF Promoter SNP

A. rs699947 B. rs1005230

C. rs833061 D. rs1570360

False Discovery Rate for the 12 p-values < 0.05 is 11%