Processes 2019, 7,37
studied in the context of infectious diseases and cancer. Kim and Lee used a hybrid model to study the
efficacy of preventative cancer vaccines. The model comprised two compartments for interactions of
tumor and immune cells at the tissue site and in the draining lymph nodes [115]. Jacob et al. developed
a three-compartment ABM that includes lymph nodes, blood vessels, and organ/tissue. The model was
used to study immune response against viruses in these compartments [116]. Marino et al. developed
a hybrid model where the lymph node and blood compartment were simulated using ordinary
differential equations and the lung compartment was simulated using agents. They focused on the
formation of granulomas in the lung, which are organized structures of immune cells in the lung,
and are a hallmark of infection. The model focused on the recruitment of APCs in the lymph node
from the lung for Mycobacterium tuberculosis (Mtb, the causative bacterium of TB) infection [117]. In
another study, they investigated the role of DC in Mtb infection [118]. The growth and dissemination
of bacteria were highly affected by CD8+ and CD4+ T-cell proliferation rates and DC migration. Such
multiscale models allow the study of tissue level dynamics during adaptive immune response [118],
and although they focus on infectious disease, many of the components and processes involved in
anti-cancer immunity and adaptive immunity against infection are shared. For example, T-cells specific
to tumor antigens are primed and expanded in a similar fashion to that in which T-cells specific to
foreign antigens are during their response to infection; the immune suppressive mechanisms that
cancer cells hijack to evade immune surveillance are also deployed during an immune response against
infection to prevent excessive tissue damage. Since the body reacts similarly in response to an infection
as it does in response to cancer (e.g., activation of similar signaling pathways), cancer models can
heavily borrow from this literature.
3.4. Models Focusing on Tumor Immunotherapy
A variety of cancer immunotherapy strategies exist that range from boosting the overall immune
response to specifically targeting cancer immunity. Some examples of immunotherapies are treatment
vaccines, adoptive cell transfer, and immune checkpoint inhibitor treatments. Agent-based and
hybrid models are developed to help understand these therapies when applied separately or in
combination with other cancer treatments. One type of therapy that has been explored is cancer
vaccines. Therapeutic cancer vaccines treat existing cancers by delivering immunogenic and tumor
specific antigens to the patient to induce cellular and/or humoral anti-tumor immunity. Pennisi et al.
have developed several hybrid models investigating the immune system effects on tumors. They
developed a hybrid model to study the development of lung metastases from mammary carcinoma [75].
Pennisi et al. also developed a hybrid model MetastaSim to simulate the protection against lung
metastases in mouse using Triplex cell vaccine [73]. In this simulation, macrophages could capture
tumor-associated antigen and immunocomplexes, breaking them down and eliminating them from
the system. This vaccine elicited a combination of three stimuli: the p185neu antigen expressed by
the HER2/neu gene, allogeneic major histocompatibility complex (MHC) molecules, and IL-12 which
enhances antigen presentation. Using this model, after calibration and validation, the authors were
able to evaluate different protocols of vaccine administration. The simulation results suggested that in
order to maximize protection while reducing the number of administrations, the vaccination strategy
should include a significant dosage early on and a few recalls afterwards.
Dreau et al. developed an ABM model of solid tumor progression to understand the interplay
between solid tumor growth, tumor vascular growth, and the host’s immune system [119]. The
model includes tumor and immune cells, vasculature, tumor cell proliferation, and immune system
response. Their model supported immunotherapy as an effective cancer treatment in individuals with
functioning immune systems. They concluded that a strong immune response limits tumor growth in
a way that cannot be achieved under a weaker immune response. Another study focused on the role of
T-cells in the effectiveness of response to immunotherapy in B-16 melanoma [120]. The model includes
macrophages, DC, tumor vasculature, and interactions between these components. It was found that
48
studied in the context of infectious diseases and cancer. Kim and Lee used a hybrid model to study the
efficacy of preventative cancer vaccines. The model comprised two compartments for interactions of
tumor and immune cells at the tissue site and in the draining lymph nodes [115]. Jacob et al. developed
a three-compartment ABM that includes lymph nodes, blood vessels, and organ/tissue. The model was
used to study immune response against viruses in these compartments [116]. Marino et al. developed
a hybrid model where the lymph node and blood compartment were simulated using ordinary
differential equations and the lung compartment was simulated using agents. They focused on the
formation of granulomas in the lung, which are organized structures of immune cells in the lung,
and are a hallmark of infection. The model focused on the recruitment of APCs in the lymph node
from the lung for Mycobacterium tuberculosis (Mtb, the causative bacterium of TB) infection [117]. In
another study, they investigated the role of DC in Mtb infection [118]. The growth and dissemination
of bacteria were highly affected by CD8+ and CD4+ T-cell proliferation rates and DC migration. Such
multiscale models allow the study of tissue level dynamics during adaptive immune response [118],
and although they focus on infectious disease, many of the components and processes involved in
anti-cancer immunity and adaptive immunity against infection are shared. For example, T-cells specific
to tumor antigens are primed and expanded in a similar fashion to that in which T-cells specific to
foreign antigens are during their response to infection; the immune suppressive mechanisms that
cancer cells hijack to evade immune surveillance are also deployed during an immune response against
infection to prevent excessive tissue damage. Since the body reacts similarly in response to an infection
as it does in response to cancer (e.g., activation of similar signaling pathways), cancer models can
heavily borrow from this literature.
3.4. Models Focusing on Tumor Immunotherapy
A variety of cancer immunotherapy strategies exist that range from boosting the overall immune
response to specifically targeting cancer immunity. Some examples of immunotherapies are treatment
vaccines, adoptive cell transfer, and immune checkpoint inhibitor treatments. Agent-based and
hybrid models are developed to help understand these therapies when applied separately or in
combination with other cancer treatments. One type of therapy that has been explored is cancer
vaccines. Therapeutic cancer vaccines treat existing cancers by delivering immunogenic and tumor
specific antigens to the patient to induce cellular and/or humoral anti-tumor immunity. Pennisi et al.
have developed several hybrid models investigating the immune system effects on tumors. They
developed a hybrid model to study the development of lung metastases from mammary carcinoma [75].
Pennisi et al. also developed a hybrid model MetastaSim to simulate the protection against lung
metastases in mouse using Triplex cell vaccine [73]. In this simulation, macrophages could capture
tumor-associated antigen and immunocomplexes, breaking them down and eliminating them from
the system. This vaccine elicited a combination of three stimuli: the p185neu antigen expressed by
the HER2/neu gene, allogeneic major histocompatibility complex (MHC) molecules, and IL-12 which
enhances antigen presentation. Using this model, after calibration and validation, the authors were
able to evaluate different protocols of vaccine administration. The simulation results suggested that in
order to maximize protection while reducing the number of administrations, the vaccination strategy
should include a significant dosage early on and a few recalls afterwards.
Dreau et al. developed an ABM model of solid tumor progression to understand the interplay
between solid tumor growth, tumor vascular growth, and the host’s immune system [119]. The
model includes tumor and immune cells, vasculature, tumor cell proliferation, and immune system
response. Their model supported immunotherapy as an effective cancer treatment in individuals with
functioning immune systems. They concluded that a strong immune response limits tumor growth in
a way that cannot be achieved under a weaker immune response. Another study focused on the role of
T-cells in the effectiveness of response to immunotherapy in B-16 melanoma [120]. The model includes
macrophages, DC, tumor vasculature, and interactions between these components. It was found that
48