A new hypothesis: some metastases are the result of inflammatory processes by adapted cells, especially adapted immune cells at sites of inflammation

Modeling and simulation of genotypic Tumor Mutational Burden and Phenotypic Immunogenicity biomarkers in cancer immunoediting with Ising-Hamiltonian characterization

BACKGROUND AND OBJECTIVE

In the Tumor Micro-Environment, cancer progression and its relationship with the Immune System (IS) are described in terms of cancer immunoediting (CI) phases, each of which is characterized by different types and levels of interaction between the tumor cells and elements of the IS, such as CD8+T cells. Said interactions are governed by genotypical (Tumor Mutational Burden, TMB) and phenotypical aspects pertaining to the tumor, as well as by the strength of the IS. In this work, a computational model of CI is presented that incorporates the TMB and the biomarker Tumor Immunogenic Phenotype (TIP) as its control parameters, and which employs the Ising-model Hamiltonian to characterize the system with respect to the CI phases.

METHODS

Our model is a probabilistic multi-agent system with agents for tumor cells and for the IS. The computer implementation includes the parametrization of the TMB and the TIP, which is useful for identifying whether a tumor is hot or cold based on tumor immunogenicity and inflammation. For modeling the interactions between tumor and immune cells, the relevant elements are integrated under a Michaelis-Menten equation that regulates the recruitment rate of CD8+T cells and other IS elements. This novel quantification of immune cell recruitment encompasses the growth of neoantigen production, which in turn triggers the growth of CD8+T cells.

RESULTS

Our model reliably captures the Elimination, Equilibrium, and Escape phases of tumor-immune cell interactions, modulating the observed behaviors through the introduced parametrization of TMB and TIP biomarkers. Notably, these results align well with the combination of genotypical and phenotypical biomarkers analyzed in recent literature. A remarkable instance is the appreciable inhibition of the tumor activity during the Escape phase, observed for phenotypically hot tumors with relatively high TMB, and pointing towards improved efficacy of the IS against such tumors. The Ising-Hamiltonian provides precise quantification of diverse tumor-immune interactions across different TMB and TIP value combinations.

CONCLUSIONS

The presented model, formed by relatively simple agents, generates emergent behaviors through which the phases of CI are identified. The flexible choice of control parameters is robust enough and provides a plausible explanation for the mechanisms through which tumors with high TMB and high immunogenicity (i.e., hot tumors) exhibit a higher probability of responding to immunotherapy treatment. Characterization via the Ising-model Hamiltonian supports this explanation by summarizing the system's dynamics, which, in turn, facilitates its analysis and methodical improvements. The complex interplay of TMB, TIP, and individual physiology is finely captured.

Sialendoscopic removal of metastatic adenocarcinoma in a mucous plug from Stensen's duct

Sialendoscopy is a minimally invasive technique used mainly in the diagnosis and treatment of obstructive salivary gland disorders. There has yet to be a report on its use in the diagnosis of metastatic disease. While metastatic cancer has been described in numerous head and neck anatomic subsites, it has not been reported to be found in a mucous plug in Stensen's duct. Sialendoscopy was performed in a 68-year-old female patient who presented with symptoms of ductal obstruction. Basket removal of a mucous plug was done and histopathological analysis of this specimen found adenocarcinoma. The overall clinical picture, imaging, and final histopathological results suggested that this patient had metastatic breast carcinoma to a mucous plug in Stensen's duct, the diagnosis of which was made with the aid of interventional sialendoscopy. This is the first report in which metastatic cancer was identified in a mucous plug in Stensen's duct. Sialendoscopy can be a useful tool to aid in the diagnosis of metastatic diseases in rare and unusual clinical situations.

Diminutive Colon Metastasis From Breast Cancer: An Unexpected Finding in a Patient Undergoing Ulcerative Colitis Surveillance

Metastatic lesions to the colon are far less common than primary tumors. Breast cancer metastasis to the colon is rarely reported, and it is often atypical in presentation and difficult to diagnose. We present a case of a diminutive asymptomatic breast cancer metastasis to the colon found during surveillance colonoscopy in a patient with long-lasting ulcerative colitis, which was initially regarded as a colitis-associated dysplastic lesion. Because early detection of metastatic disease plays a key role in the treatment of patients with breast cancer, a high index of suspicion must be maintained for atypical metastatic presentations to the gastrointestinal tract.

Modeling cancer immunoediting in tumor microenvironment with system characterization through the ising-model Hamiltonian

Background and objective

Cancer Immunoediting (CI) describes the cellular-level interaction between tumor cells and the Immune System (IS) that takes place in the Tumor Micro-Environment (TME). CI is a highly dynamic and complex process comprising three distinct phases (Elimination, Equilibrium and Escape) wherein the IS can both protect against cancer development as well as, over time, promote the appearance of tumors with reduced immunogenicity. Herein we present an agent-based model for the simulation of CI in the TME, with the objective of promoting the understanding of this process.

Methods

Our model includes agents for tumor cells and for elements of the IS. The actions of these agents are governed by probabilistic rules, and agent recruitment (including cancer growth) is modeled via logistic functions. The system is formalized as an analogue of the Ising model from statistical mechanics to facilitate its analysis. The model was implemented in the Netlogo modeling environment and simulations were performed to verify, illustrate and characterize its operation.

Results

A main result from our simulations is the generation of emergent behavior in silico that is very difficult to observe directly in vivo or even in vitro. Our model is capable of generating the three phases of CI; it requires only a couple of control parameters and is robust to these. We demonstrate how our simulated system can be characterized through the Ising-model energy function, or Hamiltonian, which captures the “energy” involved in the interaction between agents and presents it in clear and distinct patterns for the different phases of CI.

Conclusions

The presented model is very flexible and robust, captures well the behaviors of the target system and can be easily extended to incorporate more variables such as those pertaining to different anti-cancer therapies. System characterization via the Ising-model Hamiltonian is a novel and powerful tool for a better understanding of CI and the development of more effective treatments. Since data of CI at the cellular level is very hard to procure, our hope is that tools such as this may be adopted to shed light on CI and related developing theories.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04731-w.

A mathematical model for the immune-mediated theory of metastasis

Accumulating experimental and clinical evidence suggest that the immune response to cancer is not exclusively anti-tumor. Indeed, the pro-tumor roles of the immune system  -  as suppliers of growth and pro-angiogenic factors or defenses against cytotoxic immune attacks, for example  -  have been long appreciated, but relatively few theoretical works have considered their effects. Inspired by the recently proposed "immune-mediated" theory of metastasis, we develop a mathematical model for tumor-immune interactions at two anatomically distant sites, which includes both anti- and pro-tumor immune effects, and the experimentally observed tumor-induced phenotypic plasticity of immune cells (tumor "education" of the immune cells). Upon confrontation of our model to experimental data, we use it to evaluate the implications of the immune-mediated theory of metastasis. We find that tumor education of immune cells may explain the relatively poor performance of immunotherapies, and that many metastatic phenomena, including metastatic blow-up, dormancy, and metastasis to sites of injury, can be explained by the immune-mediated theory of metastasis. Our results suggest that further work is warranted to fully elucidate the pro-tumor effects of the immune system in metastatic cancer.

Cell dynamics in tumour environment after treatments

Most cancer treatments cause necrotic cell deaths in the tumour microenvironment. Necrotic cells send signals to immune cells to start the wound healing process in the tissue. Therefore, we assume after stopping treatments there is a wound that needs to be healed. We develop a simple computational model to investigate cell dynamics during the wound healing process after treatments. The model predicts that the involvement of high-fitness cancer cells in the wound healing leads to fast relapse, and cancer cells outside of the wound can cause a slow recurrence of the tumour. Therefore, the absence of relapse after treatments may imply a slow-developing tumour that might not reach an observable size in the patients' lifetime. Additionally, the model indicates that the location of remaining cancer cells after treatments is an important factor in the recurrence time. The fastest recurrence happens when high-fitness cancer cells remain inside of the wound. However, the longest time to recurrence corresponds to cancer cells located outside of the wound. Note that this model is the first attempt to study cell dynamics in the wound healing process after cancer treatments, and it has some limitations that might influence the results. Experiments are needed to validate the results.