In silico clinical studies for optimal COVID-19 vaccination schedules in patients with cancer

This study introduces a tailored COVID-19 model for patients with cancer, incorporating viral variants and immune-response dynamics. The model aims to optimize vaccination strategies, contributing to personalized healthcare for vulnerable groups.

Cancer immunotherapy responses persist after lymph node resection

Surgical removal of lymph nodes (LNs) to prevent metastatic recurrence, including sentinel lymph node biopsy (SLNB) and completion lymph node dissection (CLND), are performed in routine practice. However, it remains controversial whether removing LNs which are critical for adaptive immune responses impairs immune checkpoint blockade (ICB) efficacy. Here, our retrospective analysis demonstrated that stage III melanoma patients retain robust response to anti-PD1 inhibition after CLND. Using orthotopic murine mammary carcinoma and melanoma models, we show that responses to ICB persist in mice after TDLN resection. Mechanistically, after TDLN resection, antigen can be re-directed to distant LNs, which extends the responsiveness to ICB. Strikingly, by evaluating head and neck cancer patients treated by neoadjuvant durvalumab and irradiation, we show that distant LNs (metastases-free) remain reactive in ICB responders after tumor and disease-related LN resection, hence, persistent anti-cancer immune reactions in distant LNs. Additionally, after TDLN dissection in murine models, ICB delivered to distant LNs generated greater survival benefit, compared to systemic administration. In complete responders, anti-tumor immune memory induced by ICB was systemic rather than confined within lymphoid organs. Based on these findings, we constructed a computational model to predict free antigen trafficking in patients that will undergo LN dissection.

Transport Barriers Influence the Activation of Anti-Tumor Immunity: A Systems Biology Analysis

Effective anti-cancer immune responses require activation of one or more naïve T cells. If the correct naïve T cell encounters its cognate antigen presented by an antigen presenting cell, then the T cell can activate and proliferate. Here, mathematical modeling is used to explore the possibility that immune activation in lymph nodes is a rate-limiting step in anti-cancer immunity and can affect response rates to immune checkpoint therapy. The model provides a mechanistic framework for optimizing cancer immunotherapy and developing testable solutions to unleash anti-tumor immune responses for more patients with cancer. The results show that antigen production rate and trafficking of naïve T cells into the lymph nodes are key parameters and that treatments designed to enhance tumor antigen production can improve immune checkpoint therapies. The model underscores the potential of radiation therapy in augmenting tumor immunogenicity and neoantigen production for improved ICB therapy, while emphasizing the need for careful consideration in cases where antigen levels are already sufficient to avoid compromising the immune response.

Computational simulations of tumor growth and treatment response: Benefits of high-frequency, low-dose drug regimens and concurrent vascular normalization

Implementation of effective cancer treatment strategies requires consideration of how the spatiotemporal heterogeneities within the tumor microenvironment (TME) influence tumor progression and treatment response. Here, we developed a multi-scale three-dimensional mathematical model of the TME to simulate tumor growth and angiogenesis and then employed the model to evaluate an array of single and combination therapy approaches. Treatments included maximum tolerated dose or metronomic (i.e., frequent low doses) scheduling of anti-cancer drugs combined with anti-angiogenic therapy. The results show that metronomic therapy normalizes the tumor vasculature to improve drug delivery, modulates cancer metabolism, decreases interstitial fluid pressure and decreases cancer cell invasion. Further, we find that combining an anti-cancer drug with anti-angiogenic treatment enhances tumor killing and reduces drug accumulation in normal tissues. We also show that combined anti-angiogenic and anti-cancer drugs can decrease cancer invasiveness and normalize the cancer metabolic microenvironment leading to reduced hypoxia and hypoglycemia. Our model simulations suggest that vessel normalization combined with metronomic cytotoxic therapy has beneficial effects by enhancing tumor killing and limiting normal tissue toxicity.

Abstract A64: Mechanistic model for booster doses effectiveness in healthy, cancer and immunosuppressed patients infected with SARS-CoV-2

Introduction: Current SARS-CoV-2 vaccines are effective at preventing COVID-19 or limiting disease severity in healthy individuals, but effectiveness is lower among patients with cancer or immunosuppression. Vaccine effectiveness wanes with time and varies by vaccine type. Moreover, current vaccines are based on the ancestral SARS-CoV-2 spike protein sequence and emerging viral variants evade vaccine induced immunity. Booster doses partially overcome these issues, but there are limited clinical data on the durability of protection afforded by boosters – especially against SARS-CoV-2 variants.Methods: Here we describe a mechanistic mathematical model for vaccination-induced immunity and use it to predict vaccine effectiveness taking into account current and possible future viral, host and vaccine characteristics. Crucially, this allows predictions over time frames currently not reported in the clinical literature. The model incorporates the infection of lung epithelium by SARS-CoV-2, the response of innate and adaptive immune cells to infection, the production of pro-and anti-inflammatory cytokines, the activation of the coagulation cascade, as well as the effects of cancer cells on the lung and on the immune response. The model further accounts for the interactions between the virus, the immune cells and the tumor cells as well as for vaccination-induced immunity.Results: Model predictions were validated with clinical data. The model predicts that for healthy individuals vaccinated and boosted with mRNA-1273, BNT-162b2a, and Ad26.COV2.S, robust immunogenicity against the ancestral and delta variant extends beyond a year. Immunogenicity is also enhanced following booster vaccination in patients with cancer on various anti-cancer therapies, including immunotherapy, and for patients without cancer on immunosuppressive agents.Conclusion: Our model predicts that ³1 booster doses will be required for these individuals to maintain protective immunity. Furthermore, for immunosuppressed individuals, simulated new SARS-CoV2 variants with enhanced ability to bind to target cells, faster replication or reduced immunogenicity could lead to breakthrough infections even after a single booster dose. Modelling data such as these may be used to anticipate and plan for future vaccination needs.

Citation Format: Chrysovalantis Voutouri, Corey C Hardin, Vivek Naranbhai, Mohammad R. Nikmaneshi, Melin J. Khandekar, Justin F Gainor, Triantafyllos Stylianopoulos, Lance L. Munn, Rakesh K. Jain. Mechanistic model for booster doses effectiveness in healthy, cancer and immunosuppressed patients infected with SARS-CoV-2 [abstract]. In: Proceedings of the AACR Special Conference: Tumor Immunology and Immunotherapy; 2022 Oct 21-24; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2022;10(12 Suppl):Abstract nr A64.

Investigation of cancer response to chemotherapy: a hybrid multi-scale mathematical and computational model of the tumor microenvironment

Tumor microenvironment (TME) is a multi-scale biological environment that can control tumor dynamics with many biomechanical and biochemical factors. Investigating the physiology of TME with a heterogeneous structure and abnormal functions not only can achieve a deeper understanding of tumor behavior but also can help develop more efficient anti-cancer strategies. In this work, we develop a hybrid multi-scale mathematical model of TME to simulate the progression of a three-dimensional tumor and elucidate its response to different chemotherapy approaches. The chemotherapy approaches include multiple low dose (MLD) of anti-cancer drug, maximum tolerated dose (MTD) of anti-cancer drug, combination therapy of MLD and anti-angiogenic drug, and combination therapy of MTD and anti-angiogenic drug. The results show that combining anti-angiogenic agent with anti-cancer drug increases the performance of cancer treatment and decreases side effects for normal tissue. Indeed, the vascular normalization caused by anti-angiogenic therapy improves anti-cancer drug delivery for both MLD and MTD approaches. The results show that anti-cancer drug administered in a lower dose than the maximum tolerated dose repetitively over a long period treats cancer with a considerable performance and fewer side effects. We also show that tumor morphology and distribution of cancer cell phenotypes can be considered as the characteristics to distinguish different chemotherapy approaches. This robust model can be applied to predict the behavior of any type of cancer and quantify cancer response to different chemotherapy approaches. The computational results of cancer response to chemotherapy are in good agreement with experimental measurements.

Placental growth factor promotes tumour desmoplasia and treatment resistance in intrahepatic cholangiocarcinoma

OBJECTIVE

Intrahepatic cholangiocarcinoma (ICC)-a rare liver malignancy with limited therapeutic options-is characterised by aggressive progression, desmoplasia and vascular abnormalities. The aim of this study was to determine the role of placental growth factor (PlGF) in ICC progression.

DESIGN

We evaluated the expression of PlGF in specimens from ICC patients and assessed the therapeutic effect of genetic or pharmacologic inhibition of PlGF in orthotopically grafted ICC mouse models. We evaluated the impact of PlGF stimulation or blockade in ICC cells and cancer-associated fibroblasts (CAFs) using in vitro 3-D coculture systems.

RESULTS

PlGF levels were elevated in human ICC stromal cells and circulating blood plasma and were associated with disease progression. Single-cell RNA sequencing showed that the major impact of PlGF blockade in mice was enrichment of quiescent CAFs, characterised by high gene transcription levels related to the Akt pathway, glycolysis and hypoxia signalling. PlGF blockade suppressed Akt phosphorylation and myofibroblast activation in ICC-derived CAFs. PlGF blockade also reduced desmoplasia and tissue stiffness, which resulted in reopening of collapsed tumour vessels and improved blood perfusion, while reducing ICC cell invasion. Moreover, PlGF blockade enhanced the efficacy of standard chemotherapy in mice-bearing ICC. Conclusion PlGF blockade leads to a reduction in intratumorous hypoxia and metastatic dissemination, enhanced chemotherapy sensitivity and increased survival in mice-bearing aggressive ICC.

Chemo-mechanistic multi-scale model of a three-dimensional tumor microenvironment to quantify the chemotherapy response of cancer

Exploring efficient chemotherapy would benefit from a deeper understanding of the tumor microenvironment (TME) and its role in tumor progression. As in vivo experimental methods are unable to isolate or control individual factors of the TME, and in vitro models often cannot include all the contributing factors, some questions are best addressed with mathematical models of systems biology. In this study, we establish a multi-scale mathematical model of the TME to simulate three-dimensional tumor growth and angiogenesis and then implement the model for an array of chemotherapy approaches to elucidate the effect of TME conditions and drug scheduling on controlling tumor progression. The hyperglycemic condition as the most common disorder for cancer patients is considered to evaluate its impact on cancer response to chemotherapy. We show that combining antiangiogenic and anticancer drugs improves the outcome of treatment and can decrease accumulation of the drug in normal tissue and enhance drug delivery to the tumor. Our results demonstrate that although both concurrent and neoadjuvant combination therapies can increase intratumoral drug exposure and therapeutic accuracy, neoadjuvant therapy surpasses this, especially against hyperglycemia. Our model provides mechanistic explanations for clinical observations of tumor progression and response to treatment and establishes a computational framework for exploring better treatment strategies.

A mechanobiological mathematical model of liver metabolism

The liver plays a complex role in metabolism and detoxification, and better tools are needed to understand its function and to develop liver-targeted therapies. In this study, we establish a mechanobiological model of liver transport and hepatocyte biology to elucidate the metabolism of urea and albumin, the production/detoxification of ammonia, and consumption of oxygen and nutrients. Since hepatocellular shear stress (SS) can influence the enzymatic activities of liver, the effect of SS on the urea and albumin synthesis are empirically modeled through the mechanotransduction mechanisms. The results demonstrate that the rheology and dynamics of the sinusoid flow can significantly affect liver metabolism. We show that perfusate rheology and blood hematocrit can affect urea and albumin production by changing hepatocyte mechanosensitive metabolism. The model can also simulate enzymatic diseases of the liver such as hyperammonemia I, hyperammonemia II, hyperarginemia, citrollinemia, and argininosuccinicaciduria, which disrupt the urea metabolism and ammonia detoxification. The model is also able to predict how aggregate cultures of hepatocytes differ from single cell cultures. We conclude that in vitro perfusable devices for the study of liver metabolism or personalized medicine should be designed with similar morphology and fluid dynamics as patient liver tissue. This robust model can be adapted to any type of hepatocyte culture to determine how hepatocyte viability, functionality, and metabolism are influenced by liver pathologies and environmental conditions.