An array of antiangiogenic biomarkers have been studied (Box 2
), including systemic measurements (for example, changes in systemic blood pressure), genotypic analyses (for example, VEGF or interleukin [IL]-8 polymorphisms), circulating markers (for example, plasma levels of VEGF), tissue markers (tumor microvessel density) and imaging parameters (for example, Ktrans
, the volume transfer constants of gadolinium between blood plasma and the extravascular extracellular space measured by MRI; ). Although promising candidates have been identified, important challenges limit their translation into practice.
Box 2 | Definitions of various types of biomarkers
- Biomarker: A distinctive biological or biologically derived indicator (as a biochemical metabolite in the body) of a process, event, or condition (as aging, disease, or exposure to a toxic substance) (Webster Medical Dictionary).
- Prognostic biomarkers: Biomarkers that provide information about the patients overall cancer outcome, regardless of therapy.16
- Predictive biomarkers: Biomarkers that can be used in advance of therapy to estimate response or survival of a specific patient on a specific treatment compared with another treatment.17
- Pharmacodynamic biomarkers: Biomarker whose changes after treatment are associated with target modulation by a specific agent.
- Surrogate marker: A biomarker intended to substitute for a clinical end point.
Advantages and challenges in measuring biomarkers of antiangiogenic therapy
The first challenge is establishing adequate criteria of response. This issue is especially problematic when using agents that target stroma, such as antiangiogenic agents. Standard lesion size (defined, by RECIST [Response Evaluation Criteria In Solid Tumors] or WHO criteria) evaluations of response might not optimally assess these agents, particularly when used as monotherapy with agents such as sunitinib or sorafenib in RCC or HCC. Anti-VEGF therapy has primarily cytostatic effects, might prune and normalize the tumor vasculature, and can have substantial systemic effects such as modulation of circulating proangiogenic and proinflammatory cytokines and cells.18–23
These effects might not shrink but rather stabilize the tumor size.24
The success in identifying a predictive biomarker for a drug will require elucidation of its mechanism of action (Supplementary Table 1
). For example, detection of over-expression or amplification of human epidermal growth factor receptor 2 (HER2/neu
) in breast cancer cells and its use as a predictive biomarker is consistent with the mechanism of action of the anti-Her2 antibody trastuzumab or the EGFR-HER2 TKI lapatinib.25,26
Unfortunately, the mechanisms of action of currently approved antiangiogenic agents are not fully understood.27,28
The anti-VEGF antibody bevacizumab has yet to show improved overall survival as monotherapy in a phase III trial. The mechanisms of action of multitargeted TKIs are even less well understood—they probably target both stromal and cancer cells. Indeed, a number of potential mechanisms by which these different agents work have been hypothesized. Of these mechanisms, ‘vascular normalization’ has the most robust clinical evidence,29
and this mechanism alone might contribute to improved survival in some cancers such as glioblastoma and/or potentially as a sensitizer to cytotoxic therapies in others (for example, rectal carcinoma)18,20,22,30
and ). Thus, the determinants of vascular normalization could serve as candidate biomarkers. Conversely, a candidate biomarker that is associated with improved benefit could provide insight into the mechanism of action or resistance of a drug.
Box 3 | Mechanisms of action of antiangiogenic therapy supported by biomarkers
- Biomarker selection has been based on tumor-specific antivascular and normalizing effects as well as systemic effects of these therapies (). We have shown that bevacizumab decreases microvascular density, increases pericyte coverage and lowers interstitial fluid pressure.22,31,32 All of these pharmacodynamic changes support the vascular normalization hypothesis. As a result of the normalized microenvironment, the proliferation rate of cancer cells remains high or increases, potentially increasing sensitivity of these tumors to chemotherapy and radiation therapy. Apoptosis of cancer cells increases in response to reduced microvascular density. In addition, reports have shown that anti-VEGF therapy might have important systemic effects: it might increase the blood pressure level, could decrease circulating progenitor cell populations, decrease or increase circulating cytokine levels, and increase tumor infiltration of immunosuppressive myeloid cells.28,33–35 Moreover, tumor vascular normalization can lead to increased accumulation in tumors of effector T lymphocytes.36
- Imaging studies have also provided pharmacodynamic evidence for both the antivascular and normalization hypotheses. A number of studies have reported decreases in perfusion and vascular permeability using a variety of imaging technologies (). It is important to note the inability to separate perfusion from permeability in the transport parameters extracted from these studies. Using a more-sophisticated MRI protocol, we found that anti-VEGF therapy can create a window of normalization that lasts at least 1 month in patients with recurrent glioblastoma, characterized by reduced permeability and vessel diameter.18,37 This effect alone might confer survival benefits in these patients.20,69
- Finally, fluorodeoxyglucose-PET studies have also shown that the fluorodeoxyglucose delivery and uptake by rectal cancers does not go down after bevacizumab monotherapy despite a decrease in microvessel density and blood flow.22,31,32 This finding provides additional evidence in support of vascular normalization by VEGF blockade.
Characteristics of biomarker selection
The second challenge results from the heterogeneous and dynamic nature of cancer. Ideally, treatment outcome would be predicted from a single measurement in the tumor biopsy sample or from the circulation before treatment initiation. Indeed, VEGF polymorphisms in tumor biopsy sample and baseline VEGF plasma levels are candidate biomarkers for bevacizumab combined with chemotherapy for patients with metastatic breast cancer.38,39
By contrast, baseline VEGF is not associated with survival outcomes for mCRC or mNSCLC.40,41
The dynamics of cancer must be recognized: not only might the biology of the primary tumor be different from its metastases, but it might also change with tumor progression and treatment. Thus, a biopsy sample before first treatment might not reflect the biology before subsequent treatment. Finally, there is regional heterogeneity: one part of a tumor may not have the same vascularity or angiogenesis as another part. Thus there is a need for spatially resolved ‘dynamic biomarkers’.
The third challenge is the inability to perform repeated biopsies (that is, before and after antiangiogenic therapy) to assess ‘dynamic biomarkers’. This challenge can be partially addressed by using novel imaging techniques, which can also provide spatial information. Such an approach has shown promise in identifying potential biomarkers for treatment outcome in patients with glioblastoma. In some cases, different types of biomarkers (for example, imaging and circulating) might need to be combined, yielding a ‘composite biomarker’, to make robust predictions.
The fourth challenge in identify biomarkers resides in the inherent design of clinical trials. Human studies are expensive and require expertise in a wide range of areas, and almost all exploratory biomarkers to date have emerged from single-arm trials.42
It is, therefore, difficult to ascertain whether the biomarker is prognostic or predictive. This is problematic for anti-VEGF therapies where VEGF levels in the circulation or tumor biopsy samples have been shown to be prognostic in a number of cancer types.43,44
Even markers identified from randomized trials have emerged from secondary analyses, and require independent validation.
A fifth challenge is the unpredictability of response or toxicity, and resistance by activation of tumor VEGF-independent angiogenic pathways. Thus, biological (mechanism-driven) marker (biomarker) discovery has become a priority for these costly therapies that can be associated with rare but serious adverse effects.
A sixth challenge is to optimize and standardize various biomarkers assays. For example, different approaches are being used to measure vascular imaging parameters or circulating proteins and cells. Each approach gives a different result, which makes it difficult to compare trial results. This is further confounded by the inability of widely used imaging techniques to distinguish antivascular effects from antitumor effects of antiangiogenic agents.45
Thus, overall response rate and/or progression-free survival outcomes on the basis of contrast-enhanced imaging might not reflect a true antitumor response.
When a biomarker has been identified and validated the question for their clinical implementation will arise. Will they be generic for any anti-VEGF drug, any tumor type or stage or combination regimen? Despite these limitations, a number of candidate biomarkers are emerging for antiangiogenic therapy of cancer. Some of these findings are provocative and raise new questions about the efficacy, safety and cost–benefit ratios of these therapies. We discuss the current understanding and the future directions in establishing candidate ‘predictive biomarkers’, ‘toxicity biomarkers’ and ‘VEGF-resistance biomarkers’, and the steps necessary for their future validation.