Bridging Sunitinib Exposure to Time-to-Tumor Progression in Hepatocellular Carcinoma Patients With Mathematical Modeling of an Angiogenic Biomarker

A PK-PD model linking biomarker dynamics to progression-free survival in patients treated with everolimus and sorafenib combination therapy, EVESOR phase I trial

PURPOSE

The objective was to develop a pharmacokinetic-pharmacodynamic (PK-PD) model linking everolimus and sorafenib exposure with biomarker dynamics and progression-free survival (PFS) based on data from EVESOR trial in patients with solid tumors treated with everolimus and sorafenib combination therapy and to simulate alternative dosing schedules for sorafenib.

PATIENTS AND METHODS

Everolimus (5-10 mg once daily, qd) and sorafenib (200-400 mg twice daily, bid) were administered according to four different dosing schedules in 43 solid tumor patients. Rich PK and PD sampling for serum angiogenesis biomarkers was performed. Baseline activation of RAS/RAF/ERK (MAPK) pathway was assessed by quantification of mRNA specific gene panel in tumor biopsies. The PK-PD modeling was performed using NONMEM^® software.

RESULTS

An indirect response PK-PD model linking sorafenib plasma exposure with soluble vascular endothelial growth factor receptor 2 (sVEGFR2) dynamics was developed. Progression-free survival (PFS) was described by a parametric time-to-event model. Higher decreases in sVEGFR2 at day 21 and higher baseline activation of MAPK pathway were associated with longer PFS (p = 0.002 and p = 0.007, respectively). The simulated schedule sorafenib 200 mg bid 5 days-on/2 days-off + continuous everolimus 5 mg qd was associated with median PFS of 4.3 months (95% CI 1.6-14.4), whereas the median PFS in the EVESOR trial was 3.6 months (95% CI 2.7-4.2, n = 43).

CONCLUSION

Sorafenib 200 mg bid 5 days-on/2 days-off + everolimus 5 mg qd continuous was selected for an additional arm of EVESOR trial to evaluate whether this simulated schedule is associated with higher clinical benefit.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT01932177.

Modeling Hepatocellular Carcinoma Cells Dynamics by Serological and Imaging Biomarkers to Explain the Different Responses to Sorafenib and Regorafenib

Simple Summary

Systemic therapy in advanced hepatocellular-carcinomas (HCC) has limited benefits, but some patients show partial responses (PR) and a few even a complete response (CR). Understanding the biological mechanisms could help clinicians in decision-making. Aim of this study was to develop a physic-mathematical model to investigate tumor dynamics using α-fetoprotein (AFP) and protein induced by vitamin K absence-II (PIVKA-II) measures combined with digital imaging. The model was set-up in three prototype patients with CR/PR to sorafenib and PR to regorafenib, and then applied in seven patients with different types of response. Overall, the rate constant of cancer cells production ranged between 0.250–0.372 C × day⁻¹. During therapy, neo-angiogenesis reduction was higher in four CR than in four PR or stable disease (SD) and in two non-responders (median: 83.2% vs. 29.4% vs. 2.0%). Tumor vasculature decay appeared accelerated in CR. We conclude that modeling serological and imaging biomarkers could help personalization of systemic therapy.

Abstract

In advanced HCC, tyrosine-kinase inhibitors obtain partial responses (PR) in some patients and complete responses (CR) in a few. Better understanding of the mechanism of response could be achieved by the radiomic approach combining digital imaging and serological biomarkers (α-fetoprotein, AFP and protein induced by vitamin K absence-II, PIVKA-II) kinetics. A physic-mathematical model was developed to investigate cancer cells and vasculature dynamics in three prototype patients receiving sorafenib and/or regorafenib and applied in seven others for validation. Overall four patients showed CR, two PR, two stable-disease (SD) and two progressive-disease (PD). The rate constant of cancer cells production was higher in PD than in PR-SD and CR (median: 0.398 vs. 0.325 vs. 0.316 C × day⁻¹). Therapy induced reduction of neo-angiogenesis was greater in CR than in PR-SD and PD (median: 83.2% vs. 29.4% and 2.0%), as the reduction of cell-proliferation (55.2% vs. 7.6% and 0.7%). An additional dose-dependent acceleration of tumor vasculature decay was also observed in CR. AFP and cancer cells followed the same kinetics, whereas PIVKA-II time/dose dependent fluctuations were influenced also by tissue ischemia. In conclusion, pending confirmation in a larger HCC cohort, modeling serological and imaging biomarkers could be a new tool for systemic therapy personalization.

A multicentre phase 1b/2 study of tivozanib in patients with advanced inoperable hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a major cause of cancer-related death. It is a highly vascular tumour with multiple angiogenic factors, most importantly vascular endothelial growth factor (VEGF), involved in HCC progression. Tivozanib is an oral inhibitor of VEGFR-1/2/3 with promising activity against HCC in vivo.

Methods

We conducted a phase 1b/2 study of tivozanib in patients with advanced HCC. The safety, dosing, pharmacokinetics, pharmacodynamics, and preliminary antineoplastic efficacy of tivozanib were evaluated.

Results

Twenty-seven patients received at least one dose of tivozanib. Using a 3+3 design, the recommended phase 2 dose (RP2D) of tivozanib was determined to be 1 mg per os once daily, 21 days on–7 days off. The median progression-free and overall survival were 24 weeks and 9 months, respectively, for patients treated at RP2D. The overall response rate was 21%. Treatment was well tolerated. A significant decrease in soluble plasma VEGFR-2 was noted, assuring adequate target engagement.

Conclusions

Although this study did not proceed to stage 2, there was an early efficacy signal with a very favourable toxicity profile. A phase 1/2 trial of tivozanib in combination with durvalumab is currently underway.

Trial registration

ClinicalTrials.gov NCT01835223, registered on 15 April 2013.

Progress and Opportunities to Advance Clinical Cancer Therapeutics Using Tumor Dynamic Models

There is a need for new approaches and endpoints in oncology drug development, particularly with the advent of immunotherapies and the multiple drug combinations under investigation. Tumor dynamics modeling, a key component to oncology "model-informed drug development," has shown a growing number of applications and a broader adoption by drug developers and regulatory agencies in the past years to support drug development and approval in a variety of ways. Tumor dynamics modeling is also being investigated in personalized cancer therapy approaches. These models and applications are reviewed and discussed, as well as the limitations and issues open for further investigations. A close collaboration between stakeholders like clinical investigators, statisticians, and pharmacometricians is warranted to advance clinical cancer therapeutics.

Multiscale systems pharmacological analysis of everolimus action in hepatocellular carcinoma

Dysregulation of mTOR pathway is common in hepatocellular carcinoma (HCC). A translational quantitative systems pharmacology (QSP), pharmacokinetic (PK), and pharmacodynamic (PD) model dissecting the circuitry of this pathway was developed to predict HCC patients' response to everolimus, an mTOR inhibitor. The time course of key signaling proteins in the mTOR pathway, HCC cells viability, tumor volume (TV) and everolimus plasma and tumor concentrations in xenograft mice, clinical PK of everolimus and progression free survival (PFS) in placebo and everolimus-treated patients were extracted from literature. A comprehensive and multiscale QSP/PK/PD model was developed, qualified, and translated to clinical settings. Model fittings and simulations were performed using Monolix software. The S6-kinase protein was identified as critical in the mTOR signaling pathway for describing everolimus lack of efficacy in HCC patients. The net growth rate constant (kg) of HCC cells was estimated at 0.02 h^-1 (2.88%RSE). The partition coefficient of everolimus into the tumor (kp) was determined at 0.06 (12.98%RSE). The kg in patients was calculated from the doubling time of TV in naturally progressing HCC patients, and was determined at 0.004 day^-1. Model-predicted and observed PFS were in good agreement for placebo and everolimus-treated patients. In conclusion, a multiscale QSP/PK/PD model elucidating everolimus lack of efficacy in HCC patients was successfully developed and predicted PFS reasonably well compared to observed clinical findings. This model may provide insights into clinical response to everolimus-based therapy and serve as a valuable tool for the clinical translation of efficacy for novel mTOR inhibitors.

Population Modeling Integrating Pharmacokinetics, Pharmacodynamics, Pharmacogenetics, and Clinical Outcome in Patients With Sunitinib-Treated Cancer

The tyrosine kinase inhibitor sunitinib is used as first‐line therapy in patients with metastasized renal cell carcinoma (mRCC), given in fixed‐dose regimens despite its high variability in pharmacokinetics (PKs). Interindividual variability of drug exposure may be responsible for differences in response. Therefore, dosing strategies based on pharmacokinetic/pharmacodynamic (PK/PD) models may be useful to optimize treatment. Plasma concentrations of sunitinib, its active metabolite SU12662, and the soluble vascular endothelial growth factor receptors sVEGFR‐2 and sVEGFR‐3, were measured in 26 patients with mRCC within the EuroTARGET project and 21 patients with metastasized colorectal cancer (mCRC) from the C‐II‐005 study. Based on these observations, PK/PD models with potential influence of genetic predictors were developed and linked to time‐to‐event (TTE) models. Baseline sVEGFR‐2 levels were associated with clinical outcome in patients with mRCC, whereas active drug PKs seemed to be more predictive in patients with mCRC. The models provide the basis of PK/PD‐guided strategies for the individualization of anti‐angiogenic therapies.

A Pharmacometric Framework for Axitinib Exposure, Efficacy, and Safety in Metastatic Renal Cell Carcinoma Patients

The relationships between exposure, biomarkers (vascular endothelial growth factor (VEGF), soluble VEGF receptors (sVEGFR)-1, -2, -3, and soluble stem cell factor receptor (sKIT)), tumor sum of longest diameters (SLD), diastolic blood pressure (dBP), and overall survival (OS) were investigated in a modeling framework. The dataset included 64 metastatic renal cell carcinoma patients (mRCC) treated with oral axitinib. Biomarker timecourses were described by indirect response (IDR) models where axitinib inhibits sVEGFR-1, -2, and -3 production, and VEGF degradation. No effect was identified on sKIT. A tumor model using sVEGFR-3 dynamics as driver predicted SLD data well. An IDR model, with axitinib exposure stimulating the response, characterized dBP increase. In a time-to-event model the SLD timecourse predicted OS better than exposure, biomarker- or dBP-related metrics. This type of framework can be used to relate pharmacokinetics, efficacy, and safety to long-term clinical outcome in mRCC patients treated with VEGFR inhibitors. (ClinicalTrial.gov identifier NCT00569946.).