How to schedule VEGF and PD-1 inhibitors in combination cancer therapy?

Towards Targeting Endothelial Rap1B to Overcome Vascular Immunosuppression in Cancer

The vascular endothelium, a specialized monolayer of endothelial cells (ECs), is crucial for maintaining vascular homeostasis by controlling the passage of substances and cells. In the tumor microenvironment, Vascular Endothelial Growth Factor A (VEGF-A) drives tumor angiogenesis, leading to endothelial anergy and vascular immunosuppression-a state where ECs resist cytotoxic CD8+ T cell infiltration, hindering immune surveillance. Immunotherapies have shown clinical promise. However, their effectiveness is significantly reduced by tumor EC anergy. Anti-angiogenic treatments aim to normalize tumor vessels and improve immune cell infiltration. Despite their potential, these therapies often cause significant systemic toxicities, necessitating new treatments. The small GTPase Rap1B emerges as a critical regulator of Vascular Endothelial Growth Factor Receptor 2 (VEGFR2) signaling in ECs. Our studies using EC-specific Rap1B knockout mice show that the absence of Rap1B impairs tumor growth, alters vessel morphology, and increases CD8+ T cell infiltration and activation. This indicates that Rap1B mediates VEGF-A's immunosuppressive effects, making it a promising target for overcoming vascular immunosuppression in cancer. Rap1B shares structural and functional similarities with RAS oncogenes. We propose that targeting Rap1B could enhance therapies' efficacy while minimizing adverse effects by reversing endothelial anergy. We briefly discuss strategies successfully developed for targeting RAS as a model for developing anti-Rap1 therapies.

Antiangiogenic-immune-checkpoint inhibitor combinations: lessons from phase III clinical trials

Antiangiogenic agents, generally antibodies or tyrosine-kinase inhibitors that target the VEGF-VEGFR pathway, are currently among the few combination partners clinically proven to improve the efficacy of immune-checkpoint inhibitors (ICIs). This benefit has been demonstrated in pivotal phase III trials across different cancer types, some with practice-changing results; however, numerous phase III trials have also had negative results. The rationale for using antiangiogenic drugs as partners for ICIs relies primarily on blocking the multiple immunosuppressive effects of VEGF and inducing several different vascular-modulating effects that can stimulate immunity, such as vascular normalization leading to increased intratumoural blood perfusion and flow, and inhibition of pro-apoptotic effects of endothelial cells on T cells, among others. Conversely, VEGF blockade can also cause changes that suppress antitumour immunity, such as increased tumour hypoxia, and reduced intratumoural ingress of co-administered ICIs. As a result, the net clinical benefits from antiangiogenic-ICI combinations will be determined by the balance between the opposing effects of VEGF signalling and its inhibition on the antitumour immune response. In this Perspective, we summarize the results from the currently completed phase III trials evaluating antiangiogenic agent-ICI combinations. We also discuss strategies to improve the efficacy of these combinations, focusing on aspects that include the deleterious functions of VEGF-VEGFR inhibition on antitumour immunity, vessel co-option as a driver of non-angiogenic tumour growth, clinical trial design, or the rationale for drug selection, dosing and scheduling.

IL-27 in combination with anti-PD-1 can be anti-cancer or pro-cancer

Interleukin-27 (IL-27) is known to play opposing roles in immunology. The present paper considers, specifically, the role IL-27 plays in cancer immunotherapy when combined with immune checkpoint inhibitor anti-PD-1. We first develop a mathematical model for this combination therapy, by a system of Partial Differential Equations, and show agreement with experimental results in mice injected with melanoma cells. We then proceed to simulate tumor volume with IL-27 injection at a variable dose F and anti-PD-1 at a variable dose g. We show that in some range of "small" values of g, as f increases tumor volume decreases as long as fFc(g), where Fc(g) is a monotone increasing function of g. This demonstrates that IL-27 can be both anti-cancer and pro-cancer, depending on the ranges of both anti-PD-1 and IL-27.

Engineered IL-7 synergizes with IL-12 immunotherapy to prevent T cell exhaustion and promote memory without exacerbating toxicity

Cancer immunotherapy is moving toward combination regimens with agents of complementary mechanisms of action to achieve more frequent and robust efficacy. However, compared with single-agent therapies, combination immunotherapies are associated with increased overall toxicity because the very same mechanisms also work in concert to enhance systemic inflammation and promote off-tumor toxicity. Therefore, rational design of combination regimens that achieve improved antitumor control without exacerbated toxicity is a main objective in combination immunotherapy. Here, we show that the combination of engineered, tumor matrix-binding interleukin-7 (IL-7) and IL-12 achieves remarkable anticancer effects by activating complementary pathways without inducing any additive immunotoxicity. Mechanistically, engineered IL-12 provided effector properties to T cells, while IL-7 prevented their exhaustion and boosted memory formation as assessed by tumor rechallenge experiments. The dual combination also rendered checkpoint inhibitor (CPI)-resistant genetically engineered melanoma model responsive to CPI. Thus, our approach provides a framework of evaluation of rationally designed combinations in immuno-oncology and yields a promising therapy.

PB101, a VEGF- and PlGF-targeting decoy protein, enhances antitumor immunity and suppresses tumor progression and metastasis

Antiangiogenic therapy is a recognized method for countering the immunosuppressive tumor microenvironment (TME) and improving anti-tumor immunity. PB101 is a glycosylated decoy receptor that binds to VEGF-A and PlGF with high affinity, based on the VEGFR1 backbone. Here, we elucidated PB101-induced remodeling of tumor angiogenesis and immunity, which enhances anti-PD-L1 immune checkpoint blockade. PB101 inhibited tumor growth by suppressing angiogenesis and enhancing CD8+ T cell infiltration into the tumors. PB101 induced robust reprogramming of antitumor immunity and activates intratumoral CD8+ T cells. Anti-tumor efficacy of PB101 is mostly dependent on CD8+ T cells and IFN-γ. PB101 reprograms tumor immunity in a manner distinct from that of the conventional VEGF decoy receptor, VEGF-trap. With its potent immune-modulating capability, PB101 synergizes with an anti-PD-L1, triggering strengthened antitumor immunity. Combining PB101 and anti-PD-L1 could establish durable protective immunity against tumor recurrence and metastasis. The findings of this study offer scientific rationales for further clinical development of PB101, particularly when used in combination with immune checkpoint inhibitors, as a potential treatment for advanced cancers.

Immune-checkpoint inhibitor therapy response evaluation using oncophysics-based mathematical models

The field of oncology has transformed with the advent of immunotherapies. The standard of care for multiple cancers now includes novel drugs that target key checkpoints that function to modulate immune responses, enabling the patient's immune system to elicit an effective anti-tumor response. While these immune-based approaches can have dramatic effects in terms of significantly reducing tumor burden and prolonging survival for patients, the therapeutic approach remains active only in a minority of patients and is often not durable. Multiple biological investigations have identified key markers that predict response to the most common form of immunotherapy-immune checkpoint inhibitors (ICI). These biomarkers help enrich patients for ICI but are not 100% predictive. Understanding the complex interactions of these biomarkers with other pathways and factors that lead to ICI resistance remains a major goal. Principles of oncophysics-the idea that cancer can be described as a multiscale physical aberration-have shown promise in recent years in terms of capturing the essence of the complexities of ICI interactions. Here, we review the biological knowledge of mechanisms of ICI action and how these are incorporated into modern oncophysics-based mathematical models. Building on the success of oncophysics-based mathematical models may help to discover new, rational methods to engineer immunotherapy for patients in the future. This article is categorized under: Therapeutic Approaches and Drug Discovery > Nanomedicine for Oncologic Disease.

Mathematical modeling of cancer immunotherapy for personalized clinical translation

Encouraging advances are being made in cancer immunotherapy modeling, especially in the key areas of developing personalized treatment strategies based on individual patient parameters, predicting treatment outcomes and optimizing immunotherapy synergy when used in combination with other treatment approaches. Here we present a focused review of the most recent mathematical modeling work on cancer immunotherapy with a focus on clinical translatability. It can be seen that this field is transitioning from pure basic science to applications that can make impactful differences in patients' lives. We discuss how researchers are integrating experimental and clinical data to fully inform models so that they can be applied for clinical predictions, and present the challenges that remain to be overcome if widespread clinical adaptation is to be realized. Lastly, we discuss the most promising future applications and areas that are expected to be the focus of extensive upcoming modeling studies.

Pivotal role of PD-1/PD-L1 immune checkpoints in immune escape and cancer progression: Their interplay with platelets and FOXP3+Tregs related molecules, clinical implications and combinational potential with phytochemicals

Immune checkpoint proteins including programmed cell death protein 1 (PD-1), its ligand PD-L1 and cytotoxic T lymphocyte-associated antigen-4 (CTLA-4) are involved in proliferation, angiogenesis, metastasis, chemoresistance via immune escape and immune tolerance by disturbing cytotoxic T cell activation. Though many clinical trials have been completed in several cancers by using immune checkpoint inhibitors alone or in combination with other agents to date, recently multi-target therapy is considered more attractive than monotherapy, since immune checkpoint proteins work with other components such as surrounding blood vessels, dendritic cells, fibroblasts, macrophages, platelets and extracellular matrix within tumor microenvironment. Thus, in the current review, we look back on research history of immune checkpoint proteins and discuss their associations with platelets or tumor cell induced platelet aggregation (TCIPA) and FOXP3+ regulatory T cells (Tregs) related molecules involved in immune evasion and tumor progression, clinical implications of completed trial results and signaling networks by phytochemicals for combination therapy with immune checkpoint inhibitors and suggest future research perspectives.

A cancer model with nonlocal free boundary dynamics

Cancer cells at the tumor boundary move in the direction of the oxygen gradient, while cancer cells far within the tumor are in a necrotic state. This paper introduces a simple mathematical model that accounts for these facts. The model consists of cancer cells, cytotoxic T cells, and oxygen satisfying a system of partial differential equations. Some of the model parameters represent the effect of anti-cancer drugs. The tumor boundary is a free boundary whose dynamics is determined by the movement of cancer cells at the boundary. The model is simulated for radially symmetric and axially symmetric tumors, and it is shown that the tumor may increase or decrease in size, depending on the "strength" of the drugs. Existence theorems are proved, global in-time in the radially symmetric case, and local in-time for any shape of tumor. In the radially symmetric case, it is proved, under different conditions, that the tumor may shrink monotonically, or expand monotonically.

Modeling the effect of gut microbiome on therapeutic efficacy of immune checkpoint inhibitors against cancer

Immune checkpoint inhibitors have been shown to be highly successful against some solid metastatic malignancies, but only for a subset of patients who show durable clinical responses. The overall patient response rate is limited due to the interpatient heterogeneity. Preclinical and clinical studies have recently shown that the therapeutic responses can be improved through the modulation of gut microbiome. However, the underlying mechanisms are not fully understood. In this paper, we explored the effect of favorable and unfavorable gut bacteria on the therapeutic efficacy of anti-PD-1 against cancer by modeling the tumor-immune-gut microbiome interactions, and further examined the predictive markers of responders and non-responders to anti-PD-1. The dynamics of the gut bacteria was fitted to the clinical data of melanoma patients, and virtual patients data were generated based on the clinical patient survival data. Our simulation results show that low initial growth rate and low level of favorable bacteria at the initiation of anti-PD-1 therapy are predictive of non-responders, while high level of favorable bacteria at the initiation of anti-PD-1 therapy is predictive of responders. Simulation results also confirmed that it is possible to promote patients' response rate to anti-PD-1 by manipulating the gut bacteria composition of non-responders, whereby achieving long-term progression-free survival.

Interlocked feedback loops balance the adaptive immune response

Adaptive immune responses can be activated by harmful stimuli. Upon activation, a cascade of biochemical events ensues the proliferation and the differentiation of T cells, which can remove the stimuli and undergo cell death to maintain immune cell homeostasis. However, normal immune processes can be disrupted by certain dysregulations, leading to pathological responses, such as cytokine storms and immune escape. In this paper, a qualitative mathematical model, composed of key feedback loops within the immune system, was developed to study the dynamics of various response behaviors. First, simulation results of the model well reproduce the results of several immune response processes, particularly pathological immune responses. Next, we demonstrated how the interaction of positive and negative feedback loops leads to irreversible bistable, reversible bistable and monostable, which characterize different immune response processes: cytokine storm, normal immune response, immune escape. The stability analyses suggest that the switch-like behavior is the basis of rapid activation of the immune system, and a balance between positive and negative regulation loops is necessary to prevent pathological responses. Furthermore, we have shown how the treatment moves the system back to a healthy state from the pathological immune response. The bistable mechanism that revealed in this work is helpful to understand the dynamics of different immune response processes.

Intratumoral VEGF nanotrapper reduces gliobastoma vascularization and tumor cell mass

Glioblastoma multiforme (GBM) is the most aggressive and invasive malignant brain cancer. GBM is characterized by a dramatic metabolic imbalance leading to increased secretion of the pro-angiogenic factor VEGF and subsequent abnormal tumor vascularization. In 2009, FDA approved the intravenous administration of bevacizumab, an anti-VEGF monoclonal antibody, as a therapeutic agent for patients with GBM. However, the number of systemic side effects and reduced accessibility of bevacizumab to the central nervous system and consequently to the GBM tumor mass limited its effectiveness in improving patient survival. In this study, we combined experimental and computational modelling to quantitatively characterize the dynamics of VEGF secretion and turnover in GBM and in normal brain cells and simultaneous monitoring of vessel growth. We showed that sequestration of VEGF inside GBM cells, can be used as a novel target for improved bevacizumab-based therapy. We have engineered the VEGF nanotrapper, a cargo system that allows cellular uptake of bevacizumab and inhibits VEGF secretion required for angiogenesis activation and development. Here, we show the therapeutic efficacy of this nanocargo in reducing vascularization and tumor cell mass of GBM in vitro and in vivo cancer models.

Computational modelling of modern cancer immunotherapy

Modern cancer immunotherapy has revolutionised oncology and carries the potential to radically change the approach to cancer treatment. However, numerous questions remain to be answered to understand immunotherapy response better and further improve the benefit for future cancer patients. Computational models are promising tools that can contribute to accelerated immunotherapy research by providing new clues and hypotheses that could be tested in future trials, based on preceding simulations in addition to the empirical rationale. In this topical review, we briefly summarise the history of cancer immunotherapy, including computational modelling of traditional cancer immunotherapy, and comprehensively review computational models of modern cancer immunotherapy, such as immune checkpoint inhibitors (as monotherapy and combination treatment), co-stimulatory agonistic antibodies, bispecific antibodies, and chimeric antigen receptor T cells. The modelling approaches are classified into one of the following categories: data-driven top-down vs mechanistic bottom-up, simplistic vs detailed, continuous vs discrete, and hybrid. Several common modelling approaches are summarised, such as pharmacokinetic/pharmacodynamic models, Lotka-Volterra models, evolutionary game theory models, quantitative systems pharmacology models, spatio-temporal models, agent-based models, and logic-based models. Pros and cons of each modelling approach are critically discussed, particularly with the focus on the potential for successful translation into immuno-oncology research and routine clinical practice. Specific attention is paid to calibration and validation of each model, which is a necessary prerequisite for any successful model, and at the same time, one of the main obstacles. Lastly, we provide guidelines and suggestions for the future development of the field.

Implications of immune-mediated metastatic growth on metastatic dormancy, blow-up, early detection, and treatment

Metastatic seeding of distant organs can occur in the very early stages of primary tumor development. Once seeded, these micrometastases may enter a dormant phase that can last decades. Curiously, the surgical removal of the primary tumor can stimulate the accelerated growth of distant metastases, a phenomenon known as metastatic blow-up. Recent clinical evidence has shown that the immune response can have strong tumor promoting effects. In this work, we investigate if the pro-tumor effects of the immune response can have a significant contribution to metastatic dormancy and metastatic blow-up. We develop an ordinary differential equation model of the immune-mediated theory of metastasis. We include both anti- and pro-tumor immune effects, in addition to the experimentally observed phenomenon of tumor-induced immune cell phenotypic plasticity. Using geometric singular perturbation analysis, we derive a rather simple model that captures the main processes and, at the same time, can be fully analyzed. Literature-derived parameter estimates are obtained, and model robustness is demonstrated through a time dependent sensitivity analysis. We determine conditions under which the parameterized model can successfully explain both metastatic dormancy and blow-up. The results confirm the significant active role of the immune system in the metastatic process. Numerical simulations suggest a novel measure to predict the occurrence of future metastatic blow-up in addition to new potential avenues for treatment of clinically undetectable micrometastases.