Targeting neuropilin-1 to inhibit VEGF signaling in cancer: Comparison of therapeutic approaches

Abstract

Angiogenesis (neovascularization) plays a crucial role in a variety of physiological and pathological conditions including cancer, cardiovascular disease, and wound healing. Vascular endothelial growth factor (VEGF) is a critical regulator of angiogenesis. Multiple VEGF receptors are expressed on endothelial cells, including signaling receptor tyrosine kinases (VEGFR1 and VEGFR2) and the nonsignaling co-receptor Neuropilin-1. Neuropilin-1 binds only the isoform of VEGF responsible for pathological angiogenesis (VEGF165), and is thus a potential target for inhibiting VEGF signaling. Using the first molecularly detailed computational model of VEGF and its receptors, we have shown previously that the VEGFR-Neuropilin interactions explain the observed differential effects of VEGF isoforms on VEGF signaling in vitro, and demonstrated potent VEGF inhibition by an antibody to Neuropilin-1 that does not block ligand binding but blocks subsequent receptor coupling. In the present study, we extend that computational model to simulation of in vivo VEGF transport and binding, and predict the in vivo efficacy of several Neuropilin-targeted therapies in inhibiting VEGF signaling: (a) blocking Neuropilin-1 expression; (b) blocking VEGF binding to Neuropilin-1; (c) blocking Neuropilin-VEGFR coupling. The model predicts that blockade of Neuropilin-VEGFR coupling is significantly more effective than other approaches in decreasing VEGF-VEGFR2 signaling. In addition, tumor types with different receptor expression levels respond differently to each of these treatments. In designing human therapeutics, the mechanism of attacking the target plays a significant role in the outcome: of the strategies tested here, drugs with similar properties to the Neuropilin-1 antibody are predicted to be most effective. The tumor type and the microenvironment of the target tissue are also significant in determining therapeutic efficacy of each of the treatments studied.

Figure 1. Schematics of VEGF Transport in Tumors, VEGF Receptor Binding, and Therapeutic Strategies

(A) Schematic of the in vivo model. Parenchymal cells secrete VEGF; VEGF₁₂₁ is freely diffusible, but VEGF₁₆₅ can be sequestered by proteoglycans in the ECM (light gray) and the basement membranes (dark gray). The isoforms bind to VEGF receptors on the endothelial cells. (B) VEGF isoforms bind to VEGFR2 that transduces the angiogenic signal intracellularly. VEGF₁₂₁ does not bind Neuropilin-1; VEGF₁₆₅ may bind both VEGFR2 and Neuropilin-1 simultaneously. Thus there are two pathways for the binding of VEGF₁₆₅ to the signaling VEGFR2 receptor: first by binding directly, and second by binding Neuropilin-1 and then diffusing laterally on the cell surface to couple to VEGFR2. VEGFR1, which modulates the signaling of VEGFR2, binds both isoforms of VEGF. VEGFR1 also binds directly to Neuropilin-1. This complex is permissive for VEGF₁₂₁–VEGFR1 binding but not VEGF₁₆₅–VEGFR1; thus, high levels of Neuropilin-1 displace VEGF₁₆₅ from VEGFR1, making it available for VEGFR2 binding. Only VEGF₁₆₅ binds directly to the ECM binding site (represented by GAG chains). (C) By targeting Neuropilin-1, we can target specifically VEGF₁₆₅-induced signaling. Three methods for targeting Neuropilin-1 are analyzed here: blockade of Neuropilin-1 expression (e.g., using siRNA); blockade of VEGF–Neuropilin binding (e.g., using a fragment of placental growth factor to occupy the binding site); and blockade of VEGFR–Neuropilin coupling (e.g., using an antibody for Neuropilin-1 that does not interfere with VEGF–Neuropilin binding).

Figure 2. Interactions between VEGF₁₂₁, VEGF₁₆₅, and Their Cell Surface Receptors VEGFR1, VEGFR2, and Neuropilin-1, and Interstitial GAG Binding Sites

(A) VEGF₁₂₁ binds to VEGFR2 but not Neuropilin-1. VEGF₁₆₅ binds both receptors as well as GAG chains in the interstitial space. VEGF₁₆₅ bound to Neuropilin-1 can diffuse laterally on the cell membrane and bind VEGFR2 (and vice versa), coupling these receptors together, even though the receptors themselves do not interact. (B) VEGF₁₂₁ and VEGF₁₆₅ both bind VEGFR1. Neuropilin-1 and VEGFR1 interact directly, forming a complex that is permissive for VEGF₁₂₁ binding but not VEGF₁₆₅. (C) Inhibition of Neuropilin-1 expression results in a decrease in the insertion rate of Neuropilin receptors into the cell membrane (s_N). (D) PlGF_2Δ, a fragment of placental growth factor, competes with VEGF₁₆₅ for the binding site on Neuropilin-1. (E) An antibody to Neuropilin-1 that does not interfere with VEGF₁₆₅ binding can block the coupling of VEGF₁₆₅–Neuropilin to VEGFR2, resulting in sequestration of VEGF on nonsignaling Neuropilin.

Figure 3. VEGF Binding to VEGFR2 In Vivo Is Inhibited by Targeting Neuropilin-1

(A–C) The time course of VEGF–VEGFR2 complex formation on the endothelial cells following each of the three treatments. For blocking VEGF–Neuropilin-1 binding (B) and VEGFR–Neuropilin-1 coupling (C), this figure represents bolus intratissue protein delivery at time 0. For Neuropilin-1 expression blockade, insertion of Neuropilin-1 into the membrane decreases to the indicated level at time 0. The VEGF₁₂₁–VEGFR2 binding curve is indistinguishable from the no-treatment line in each case. The tumor modeled here expresses 10,000 VEGFR2 and 100,000 Neuropilin per endothelial cell. (D–F) Free (unbound) VEGF concentration in the interstitial space. *VEGF₁₂₁ secreted at the same rate as VEGF₁₆₅. (G–I) The concentration of VEGF inhibitor in the interstitial space, or density of Neuropilin, on the blood vessel endothelial cell surface.

Figure 4. Average VEGF–VEGFR2 Signaling Inhibition

The average inhibition of VEGF–VEGFR2 complex formation over the 48 hours following blockade of Neuropilin-1 expression (A), or bolus intratissue protein delivery (B) of competitive binding inhibitor or VEGFR–Neuropilin-1 coupling blocker. Endothelial cells expressing 10,000 VEGFR2 and 100,000 Neuropilin-1.

Figure 5. Tissue Expressing High VEGFR1 Levels Responds Differently to Treatment

(A–C) Formation of VEGF–VEGFR2 complexes over time following anti-Neuropilin treatment, for a tumor expressing 10,000 VEGFR1 per endothelial cell in addition to the VEGFR2 and Neuropilin-1 expression of Figures 3 and 4. (D–F) VEGF–VEGFR1 complex formation. (G–I) Free (unbound) interstitial VEGF concentration. *VEGF₁₂₁ secreted at the same rate as VEGF₁₆₅.

Figure 6. Average VEGF–VEGFR2 Signaling Inhibition over the 48 Hours Following Treatment

Endothelial cells expressing 10,000 VEGFR1, 10,000 VEGFR2, and 100,000 Neuropilin-1.

Figure 7. Tissue Specificity of Neuropilin-Targeted Inhibition of VEGF Signaling

Tissues that express low levels of Neuropilin-1 are insensitive to all Neuropilin-targeting treatments. The inhibition of VEGF–VEGFR2 signaling is directly proportional to Neuropilin-1 density (A–C), except at very high Neuropilin levels, which can overcome the inhibition. Tissues that express intermediate and high levels of Neuropilin-1 are further distinguished by the level of expression of VEGFR1. Blocking VEGFR–Neuropilin coupling is the most effective treatment to reduce VEGF–VEGFR2 signaling for tissues with any VEGFR1 expression level. However, in high VEGFR1 tissues, the other treatments are also quite effective. All three treatments significantly induce VEGF–VEGFR1 complex formation (D–F). The circles in each figure denote the conditions for Figures 3 and 4 (left, VEGFR1 actually zero in simulations) and Figures 5 and 6 (right) to compare the efficacy of the treatments for different tumors. The results shown are for a Neuropilin-1 expression knockdown to 1%, for 1 μM PlGF_2Δ, and 1 μM Ab_NRP.

Figure 8. VEGF Signaling Inhibition Is Effective for a Shorter Period of Time for a Tissue with a Higher Microvascular Density

(A–C) VEGF–VEGFR2 complex formation on the endothelial cells following each of the three treatments. The tumor modeled here expresses 10,000 VEGFR2 and 100,000 Neuropilin per endothelial cell. Gray lines represent the case of 2% vascular volume, as depicted in Figure 3; the black lines represent 4.2% vascular volume. Note that while the 10³/cell, pM, and nM scales apply to both the gray and black lines, the pmol/L tissue scales apply only to the black lines; the normalization is different for the gray lines (see Figure 3 for the correct scales). (D–F) Free (unbound) VEGF concentration in the interstitial space. *VEGF₁₂₁ secreted at the same rate as VEGF₁₆₅. (G–I) The concentration of VEGF inhibitor in the interstitial space, or density of Neuropilin on the blood vessel endothelial cell surface.

Figure 9. Average VEGF Signaling for the 48 Hours Following Treatment Inhibition Is Decreased at Higher Microvascular Density

The gray lines represent the case of 2% vascular volume (as depicted in Figure 4); the colored lines represent a 4.2% vascular volume. The peak inhibition due to the blockade of VEGFR–Neuropilin coupling is the same for both vascular densities; however, the peak for the other two treatments is lower. Endothelial cells expressing 10,000 VEGFR2 and 100,000 Neuropilin-1.