Sanja Karovic

Sorafenib dose escalation is not uniformly associated with blood pressure elevations in normotensive patients with advanced malignancies.

Hypertension after treatment with vascular endothelial growth factor (VEGF) receptor inhibitors is associated with superior treatment outcomes for advanced cancer patients. To determine whether increased sorafenib doses cause incremental increases in blood pressure (BP), we measured 12‐h ambulatory BP in 41 normotensive advanced solid tumor patients in a randomized dose‐escalation study. After 7 days’ treatment (400 mg b.i.d.), mean diastolic BP (DBP) increased in both study groups. After dose escalation, group A (400 mg t.i.d.) had marginally significant further increase in 12‐h mean DBP (P = 0.053), but group B (600 mg b.i.d.) did not achieve statistically significant increases (P = 0.25). Within groups, individuals varied in BP response to sorafenib dose escalation, but these differences did not correlate with changes in steady‐state plasma sorafenib concentrations. These findings in normotensive patients suggest BP is a complex pharmacodynamic biomarker of VEGF inhibition. Patients have intrinsic differences in sensitivity to sorafenibs BP‐elevating effects.

Predicting Response to Histone Deacetylase Inhibitors Using High-Throughput Genomics

BACKGROUND Many disparate biomarkers have been proposed as predictors of response to histone deacetylase inhibitors (HDI); however, all have failed when applied clinically. Rather than this being entirely an issue of reproducibility, response to the HDI vorinostat may be determined by the additive effect of multiple molecular factors, many of which have previously been demonstrated. METHODS We conducted a large-scale gene expression analysis using the Cancer Genome Project for discovery and generated another large independent cancer cell line dataset across different cancers for validation. We compared different approaches in terms of how accurately vorinostat response can be predicted on an independent out-of-batch set of samples and applied the polygenic marker prediction principles in a clinical trial. RESULTS Using machine learning, the small effects that aggregate, resulting in sensitivity or resistance, can be recovered from gene expression data in a large panel of cancer cell lines.This approach can predict vorinostat response accurately, whereas single gene or pathway markers cannot. Our analyses recapitulated and contextualized many previous findings and suggest an important role for processes such as chromatin remodeling, autophagy, and apoptosis. As a proof of concept, we also discovered a novel causative role for CHD4, a helicase involved in the histone deacetylase complex that is associated with poor clinical outcome. As a clinical validation, we demonstrated that a common dose-limiting toxicity of vorinostat, thrombocytopenia, can be predicted (r = 0.55, P = .004) several days before it is detected clinically. CONCLUSION Our work suggests a paradigm shift from single-gene/pathway evaluation to simultaneously evaluating multiple independent high-throughput gene expression datasets, which can be easily extended to other investigational compounds where similar issues are hampering clinical adoption.

Technical considerations in the development of circulating peptides as pharmacodynamic biomarkers for angiogenesis inhibitors

To determine the biological reproducibility and estimate relevant covariates for candidate circulating biomarkers of angiogenesis, we conducted 3 sub‐studies with ≤15 subjects each. In study 1, 6 healthy subjects provided 13 blood samples across 14–24 days. In study 2, 15 advanced solid tumor patients provided single blood samples before, and approximately 8 and 40 days after sorafenib treatment. In study 3, 4 healthy subjects provided blood samples on 3 occasions over 14 days, processed simultaneously in 2 different laboratories at a single institution. Vascular endothelial growth factor (VEGFA), soluble VEGF receptor‐2 (sVEGFR2), and angiopoietin‐2 (Ang2) concentrations in plasma and serum were determined by standard immunoassays. Ang2 and sVEGFR2 demonstrated low variance within and high variance across individuals reflected by the high intraclass correlation coefficient (for Ang2: 0.86 for plasma, 0.89 for serum; for sVEGFR2: 0.91 for plasma, 0.87 for serum). Repeated measures linear modeling from 15 patients demonstrated increased Ang2 (P ≤ 0.05) and decreased sVEGFR2 (P ≤ 0.05) after exposure to sorafenib. VEGFA had high intraindividual variance, and study 3 demonstrated the laboratory to have significant effects on plasma measurements (P ≤ 0.05). The biological reproducibility of sVEGFR2 and Ang2 support further use of these markers in studies of vasculature‐targeted therapeutics.

Comparative Effects of CT Imaging Measurement on RECIST End Points and Tumor Growth Kinetics Modeling.

Quantitative assessments of tumor burden and modeling of longitudinal growth could improve phase II oncology trials. To identify obstacles to wider use of quantitative measures we obtained recorded linear tumor measurements from three published lung cancer trials. Model‐based parameters of tumor burden change were estimated and compared with similarly sized samples from separate trials. Time‐to‐tumor growth (TTG) was computed from measurements recorded on case report forms and a second radiologist blinded to the form data. Response Evaluation Criteria in Solid Tumors (RECIST)‐based progression‐free survival (PFS) measures were perfectly concordant between the original forms data and the blinded radiologist re‐evaluation (intraclass correlation coefficient = 1), but these routine interrater differences in the identification and measurement of target lesions were associated with an average 18‐week delay (range, −20 to 55 weeks) in TTG (intraclass correlation coefficient = 0.32). To exploit computational metrics for improving statistical power in small clinical trials will require increased precision of tumor burden assessments.

Clinical pharmacodynamic/exposure characterisation of the multikinase inhibitor ilorasertib (ABT-348) in a phase 1 dose-escalation trial

BackgroundIlorasertib (ABT-348) inhibits Aurora and VEGF receptor (VEGFR) kinases. Patients with advanced solid tumours participated in a phase 1 dose-escalation trial to profile the safety, tolerability, and pharmacokinetics of ilorasertib.MethodsIlorasertib monotherapy was administered at 10–180 mg orally once daily (Arm I, n = 23), 40–340 mg orally twice daily (Arm II, n = 28), or 8–32 mg intravenously once daily (Arm III, n = 7), on days 1, 8, and 15 of each 28-day cycle.ResultsDose-limiting toxicities were predominantly related to VEGFR inhibition. The most frequent treatment-emergent adverse events ( > 30%) were: fatigue (48%), anorexia (34%), and hypertension (34%). Pharmacodynamic markers suggested that ilorasertib engaged VEGFR2 and Aurora B kinase, with the VEGFR2 effects reached at lower doses and exposures than Aurora inhibition effects. In Arm II, one basal cell carcinoma patient (40 mg twice daily (BID)) and one patient with adenocarcinoma of unknown primary site (230 mg BID) had partial responses.ConclusionsIn patients with advanced solid tumours, ilorasertib treatment resulted in evidence of engagement of the intended targets and antitumour activity, but with maximum inhibition of VEGFR family kinases occurring at lower exposures than typically required for inhibition of Aurora B in tissue.Clinical Trial Registration: NCT01110486

Serum C-Telopeptide Collagen Crosslinks and Plasma Soluble VEGFR2 as Pharmacodynamic Biomarkers in a Trial of Sequentially Administered Sunitinib and Cilengitide

Purpose: Fit-for-purpose pharmacodynamic biomarkers could expedite development of combination antiangiogenic regimens. Plasma sVEGFR2 concentrations ([sVEGFR2]) mark sunitinib effects on the systemic vasculature. We hypothesized that cilengitide would impair microvasculature recovery during sunitinib withdrawal and could be detected through changes in [sVEGFR2]. Experimental Design: Advanced solid tumor patients received 50 mg sunitinib daily for 14 days. For the next 14 days, patients were randomized to arm A (cilengitide 2,000 mg administered intravenously twice weekly) or arm B (no treatment). The primary endpoint was change in [sVEGFR2] between days 14 and 28. A candidate pharmacodynamic biomarker of cilengitide inhibition of integrin αvβ3, serum c-telopeptide collagen crosslinks (CTx), was also measured. Results: Of 21 patients, 14 (7 per arm) received all treatments without interruption and had all blood samples available for analysis. The mean change and SD of [sVEGFR2] for all sunitinib-treated patients was consistent with previous data. There was no significant difference in the mean change in [sVEGFR2] from days 14 to 28 between the arms [arm A: 2.8 ng/mL; 95% confidence interval (CI), 2.1–3.6 vs. arm B: 2.0 ng/mL; 95% CI, 0.72–3.4; P = 0.22, 2-sample t test]. Additional analyses suggested (i) prior bevacizumab therapy to be associated with unusually low baseline [sVEGFR2] and (ii) sunitinib causes measurable changes in CTx. Conclusions: Cilengitide had no measurable effects on any circulating biomarkers. Sunitinib caused measurable declines in serum CTx. The properties of [sVEGFR2] and CTx observed in this study inform the design of future combination antiangiogenic therapy trials. Clin Cancer Res; 21(22); 5092–9. ©2015 AACR.

Vol-PACT: A Foundation for the NIH Public-Private Partnership That Supports Sharing of Clinical Trial Data for the Development of Improved Imaging Biomarkers in Oncology

PURPOSE To develop a public-private partnership to study the feasibility of a new approach in collecting and analyzing clinically annotated imaging data from landmark phase III trials in advanced solid tumors. PATIENTS AND METHODS The collection of clinical trials fulfilled the following inclusion criteria: completed randomized trials of > 300 patients, highly measurable solid tumors (non-small-cell lung cancer, colorectal cancer, renal cell cancer, and melanoma), and required sponsor and institutional review board sign-offs. The new approach in analyzing computed tomography scans was to transfer to an academic image analysis laboratory, draw contours semi-automatically by using in-house-developed algorithms integrated into the open source imaging platform Weasis, and perform serial volumetric measurement. RESULTS The median duration of contracting with five sponsors was 12 months. Ten trials in 7,085 patients that covered 12 treatment regimens across 20 trial arms were collected. To date, four trials in 3,954 patients were analyzed. Source imaging data were transferred to the academic core from 97% of trial patients (n = 3,837). Tumor imaging measurements were extracted from 82% of transferred computed tomography scans (n = 3,162). Causes of extraction failure were nonmeasurable disease (n = 392), single imaging time point (n = 224), and secondary captured images (n = 59). Overall, clinically annotated imaging data were extracted in 79% of patients (n = 3,055), and the primary trial end point analysis in each trial remained representative of each original trial end point. CONCLUSION The sharing and analysis of source imaging data from large randomized trials is feasible and offer a rich and reusable, but largely untapped, resource for future research on novel trial-level response and progression imaging metrics.

Comparison of tumor size assessments in tumor growth inhibition-overall survival models with second-line colorectal cancer data from the VELOUR study

PurposeTo compare lesion-level and volumetric measures of tumor burden with sum of the longest dimensions (SLD) of target lesions on overall survival (OS) predictions using time-to-growth (TTG) as predictor.MethodsTumor burden and OS data from a phase 3 randomized study of second-line FOLFIRI ± aflibercept in metastatic colorectal cancer were available for 918 patients out of 1216 treated (75%). A TGI model that estimates TTG was fit to the longitudinal tumor size data (nonlinear mixed effect modeling) to estimate TTG with: SLD, sum of the measured lesion volumes (SV), individual lesion diameters (ILD), or individual lesion volumes (ILV). A parametric OS model was built with TTG estimates and assessed for prediction of the hazard ratio (HR) for survival.ResultsIndividual lesions had consistent dynamics within individuals. Between-lesion variability in rate constants was lower (typically < 27% CV) than inter-patient variability (typically > 50% CV). Estimates of TTG were consistent (around 12 weeks) across tumor size assessments. TTG was highly significant in a log-logistic parametric model of OS (median over 12 months). When individual lesions were considered, TTG of the fastest progressing lesions best predicted OS. TTG obtained from the lesion-level analyses were slightly better predictors of OS than estimates from the sums, with ILV marginally better than ILD. All models predicted VELOUR HR equally well and all predicted study success.ConclusionThis analysis revealed consistent TGI profiles across all tumor size assessments considered. TTG predicted VELOUR HR when based on any of the tumor size measures.