James P B O'Connor

DCE-MRI biomarkers in the clinical evaluation of antiangiogenic and vascular disrupting agents

Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is now frequently used in early clinical trial assessment of antiangiogenic and vascular disrupting compounds. Evidence of drug efficacy and dose-dependent response has been demonstrated with some angiogenesis inhibitors. This review highlights the critical issues that influence T1-weighted DCE-MRI data acquisition and analysis, identifies important areas for future development and reviews the clinical trial findings to date.

Imaging tumor vascular heterogeneity and angiogenesis using dynamic contrast-enhanced magnetic resonance imaging.

This article reviews the application of dynamic contrast-enhanced magnetic resonance imaging in both clinical studies and early-phase trials of angiogenesis inhibitors. Emphasis is placed on how variation in image acquisition and analysis affects the meaning and use of derived variables. We then review the potential for future developments, with particular reference to the application of dynamic contrast-enhanced magnetic resonance imaging to evaluate the heterogeneity of tumor tissues.

Dynamic contrast-enhanced MRI in clinical trials of antivascular therapies

About 100 early-phase clinical trials and investigator-led studies of targeted antivascular therapies—both anti-angiogenic and vascular-targeting agents—have reported data derived from T1-weighted dynamic contrast-enhanced (DCE)-MRI. However, the role of DCE-MRI for decision making during the drug-development process remains controversial. Despite well-documented guidelines on image acquisition and analysis, several key questions concerning the role of this technique in early-phase trial design remain unanswered. This Review describes studies of single-agent antivascular therapies, in which DCE-MRI parameters are incorporated as pharmacodynamic biomarkers. We discuss whether these parameters, such as volume transfer constant (Ktrans), are reproducible and reliable biomarkers of both drug efficacy and proof of concept, and whether they assist in dose selection and drug scheduling for subsequent phase II trials. Emerging evidence indicates that multiparametric analysis of DCE-MRI data offers greater insight into the mechanism of drug action than studies measuring a single parameter, such as Ktrans. We also provide an overview of current data and appraise the future directions of this technique in oncology trials. Finally, major hurdles in imaging biomarker development, validation and qualification that hinder a wide application of DCE-MRI techniques in clinical trials are addressed.

Critical research gaps and translational priorities for the successful prevention and treatment of breast cancer

IntroductionBreast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice.MethodsMore than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer ‘stem’ cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account.ResultsThe 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working.ConclusionsWith resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years.

Imaging Intratumor Heterogeneity: Role in Therapy Response, Resistance, and Clinical Outcome

Tumors exhibit genomic and phenotypic heterogeneity, which has prognostic significance and may influence response to therapy. Imaging can quantify the spatial variation in architecture and function of individual tumors through quantifying basic biophysical parameters such as CT density or MRI signal relaxation rate; through measurements of blood flow, hypoxia, metabolism, cell death, and other phenotypic features; and through mapping the spatial distribution of biochemical pathways and cell signaling networks using PET, MRI, and other emerging molecular imaging techniques. These methods can establish whether one tumor is more or less heterogeneous than another and can identify subregions with differing biology. In this article, we review the image analysis methods currently used to quantify spatial heterogeneity within tumors. We discuss how analysis of intratumor heterogeneity can provide benefit over more simple biomarkers such as tumor size and average function. We consider how imaging methods can be integrated with genomic and pathology data, instead of being developed in isolation. Finally, we identify the challenges that must be overcome before measurements of intratumoral heterogeneity can be used routinely to guide patient care. Clin Cancer Res; 21(2); 249–57. ©2014 AACR.

Quantitative imaging biomarkers in the clinical development of targeted therapeutics: current and future perspectives.

Targeted therapeutics have challenged how imaging techniques assess tumour response to treatment because many new agents are thought to cause cytostasis rather than cytotoxicity. Advanced tracer development, image acquisition, and image analysis have been used to produce quantitative biomarkers of pathophysiology, with particular focus on measurement of tumour vascular characteristics. Here, we critically appraise strategies available to generate imaging biomarkers for use in development of targeted therapeutics. We consider important practical and technical features of data acquisition and analysis because these factors determine the precise physiological meaning of every biomarker. We discuss the merits of volume-based and other size-based metrics for assessment of targeted therapeutics, and we examine the strengths and weaknesses of CT, MRI, and PET biomarkers derived from conventional clinical data. We review imaging biomarkers of tumour microvasculature and discuss imaging strategies that probe other physiological processes including cell proliferation, apoptosis, and tumour invasion. We conclude on the need to develop comprehensive compound-specific imaging biomarkers that are appropriate for every class of targeted therapeutics, and to investigate the complementary information given in multimodality imaging studies of targeted therapeutics.

Quantifying Antivascular Effects of Monoclonal Antibodies to Vascular Endothelial Growth Factor: Insights from Imaging

Purpose: Little is known concerning the onset, duration, and magnitude of direct therapeutic effects of anti–vascular endothelial growth factor (VEGF) therapies. Such knowledge would help guide the rational development of targeted therapeutics from bench to bedside and optimize use of imaging technologies that quantify tumor function in early-phase clinical trials. Experimental Design: Preclinical studies were done using ex vivo microcomputed tomography and in vivo ultrasound imaging to characterize tumor vasculature in a human HM-7 colorectal xenograft model treated with the anti-VEGF antibody G6-31. Clinical evaluation was by quantitative magnetic resonance imaging in 10 patients with metastatic colorectal cancer treated with bevacizumab. Results: Microcomputed tomography experiments showed reduction in perfused vessels within 24 to 48 h of G6-31 drug administration (P ≤ 0.005). Ultrasound imaging confirmed reduced tumor blood volume within the same time frame (P = 0.048). Consistent with the preclinical results, reductions in enhancing fraction and fractional plasma volume were detected in patient colorectal cancer metastases within 48 h after a single dose of bevacizumab that persisted throughout one cycle of therapy. These effects were followed by resolution of edema (P = 0.0023) and tumor shrinkage in 9 of 26 tumors at day 12. Conclusion: These data suggest that VEGF-specific inhibition induces rapid structural and functional effects with downstream significant antitumor activity within one cycle of therapy. This finding has important implications for the design of early-phase clinical trials that incorporate physiologic imaging. The study shows how animal data help interpret clinical imaging data, an important step toward the validation of image biomarkers of tumor structure and function. (Clin Cancer Res 2009;15(21):6674–82)Purpose Little is known concerning the onset, duration and magnitude of direct therapeutic effects of anti-VEGF therapies. Such knowledge would help guide the rational development of targeted therapeutics from bench to bedside and optimize use of imaging technologies that quantify tumor function in early phase clinical trials.

DCE-MRI biomarkers of tumour heterogeneity predict CRC liver metastasis shrinkage following bevacizumab and FOLFOX-6

Background:There is limited evidence that imaging biomarkers can predict subsequent response to therapy. Such prognostic and/or predictive biomarkers would facilitate development of personalised medicine. We hypothesised that pre-treatment measurement of the heterogeneity of tumour vascular enhancement could predict clinical outcome following combination anti-angiogenic and cytotoxic chemotherapy in colorectal cancer (CRC) liver metastases.Methods:Ten patients with 26 CRC liver metastases had two dynamic contrast-enhanced MRI (DCE-MRI) examinations before starting first-line bevacizumab and FOLFOX-6. Pre-treatment biomarkers of tumour microvasculature were computed and a regression analysis was performed against the post-treatment change in tumour volume after five cycles of therapy. The ability of the resulting linear model to predict tumour shrinkage was evaluated using leave-one-out validation. Robustness to inter-visit variation was investigated using data from a second baseline scan.Results:In all, 86% of the variance in post-treatment tumour shrinkage was explained by the median extravascular extracellular volume (ve), tumour enhancing fraction (EF), and microvascular uniformity (assessed with the fractal measure box dimension, d0) (R2=0.86, P<0.00005). Other variables, including baseline volume were not statistically significant. Median prediction error was 12%. Equivalent results were obtained from the second scan.Conclusion:Traditional image analyses may over-simplify tumour biology. Measuring microvascular heterogeneity may yield important prognostic and/or predictive biomarkers.

Quantifying spatial heterogeneity in dynamic contrast-enhanced MRI parameter maps.

Dynamic contrast‐enhanced MRI is becoming a standard tool for imaging‐based trials of anti‐vascular/angiogenic agents in cancer. So far, however, biomarkers derived from DCE‐MRI parameter maps have largely neglected the fact that the maps have spatial structure and instead focussed on distributional summary statistics. Such statistics—e.g., biomarkers based on median values—neglect the spatial arrangement of parameters, which may carry important diagnostic and prognostic information. This article describes two types of heterogeneity biomarker that are sensitive to both parameter values and their spatial arrangement. Methods based on Rényi fractal dimensions and geometrical properties are developed, both of which attempt to describe the complexity of DCE‐MRI parameter maps. Experiments using simulated data show that the proposed biomarkers are sensitive to changes that distribution‐based summary statistics cannot detect and demonstrate that heterogeneity biomarkers could be applied in the drug trial setting. An experiment using 23 DCE‐MRI parameter maps of gliomas—a class of tumour that is graded on the basis of heterogeneity—shows that the proposed heterogeneity biomarkers are able to differentiate between low‐ and high‐grade tumours. Magn Reson Med, 2009.

Quantifying heterogeneity in human tumours using MRI and PET

Most tumours, even those of the same histological type and grade, demonstrate considerable biological heterogeneity. Variations in genomic subtype, growth factor expression and local microenvironmental factors can result in regional variations within individual tumours. For example, localised variations in tumour cell proliferation, cell death, metabolic activity and vascular structure will be accompanied by variations in oxygenation status, pH and drug delivery that may directly affect therapeutic response. Documenting and quantifying regional heterogeneity within the tumour requires histological or imaging techniques. There is increasing evidence that quantitative imaging biomarkers can be used in vivo to provide important, reproducible and repeatable estimates of tumoural heterogeneity. In this article we review the imaging methods available to provide appropriate biomarkers of tumour structure and function. We also discuss the significant technical issues involved in the quantitative estimation of heterogeneity and the range of descriptive metrics that can be derived. Finally, we have reviewed the existing clinical evidence that heterogeneity metrics provide additional useful information in drug discovery and development and in clinical practice.