After assessing the ABM's ability to capture the complexity, heterogeneity, and dynamic processes of liver regeneration, as well as HCC recurrence and growth, the next step was to focus on eliminating the tumour. In close collaboration with Dr. Enrique Rodriguez-Lomba, an MD, we studied dosimetry strategies for CAR T-cell immunotherapy.

What Is CAR T-Cell Immunotherapy?

CAR T-cell immunotherapy (Chimeric Antigen Receptor T-cell therapy) is a revolutionary type of cancer treatment that uses a patient's own immune cells (T-cells) to specifically target and destroy cancer cells. It is a form of personalized immunotherapy designed to reprogram the immune system to recognize and attack tumours.

How Does CAR T-Cell Therapy Work?

The process involves several key steps:

• T-Cell Collection: A sample of the patient’s blood is drawn through a process called leukapheresis, which separates T-cells (a type of white blood cell) from the rest of the blood. The remaining blood components are returned to the patient.
• Genetic Modification: T-cells are genetically modified in the laboratory to express a special receptor on their surface called a Chimeric Antigen Receptor (CAR). The CAR is designed to recognize specific proteins (antigens) expressed on the surface of cancer cells. 
• Multiplication: The genetically modified CAR T-cells are then grown and multiplied in the lab to produce millions of cells. This ensures there are enough modified cells to fight the cancer effectively.

Image taken from: https://solvingkidscancer.org/blog/latest-in-car-t-cell-therapy/

• Conditioning Therapy: Before reintroducing the CAR T-cells, the patient undergoes lymphodepletion chemotherapy. This reduces the number of existing immune cells, creating space for the CAR T-cells to thrive and function optimally.
• Injection: The engineered CAR T-cells are infused back into the patient’s bloodstream. These cells circulate in the body, seeking out and binding to cancer cells that express the targeted antigen.
• Immune Response and Cancer Cell Killing: Once a CAR T-cell binds to a cancer cell, it becomes activated and releases cytotoxic molecules that destroy the cancer cell. The CAR T-cells also replicate in the body, creating a lasting immune defence against cancer recurrence.

Advantages of CAR T-Cell Therapy

• Precision Targeting: CAR T-cells specifically attack cancer cells expressing the target antigen, minimizing damage to healthy tissues.
• Durability: CAR T-cells can persist in the body, offering long-term surveillance against cancer recurrence.
• Effectiveness: It has shown remarkable success, particularly in blood cancers like leukaemia, lymphoma, and multiple myeloma.

Challenges and Side Effects

• Cytokine Release Syndrome (CRS): An overactive immune response that causes fever, low blood pressure, and organ dysfunction. It is treatable in most cases.
• Neurotoxicity: Some patients may experience temporary neurological side effects, such as confusion or difficulty speaking.
• Antigen Escape: Cancer cells may lose or downregulate the targeted antigen, allowing them to evade CAR T-cells.
• Limited Efficacy in Solid Tumours: CAR T-cell therapy has been more successful in blood cancers than in solid tumours, where challenges like the tumour microenvironment and antigen heterogeneity exist.

In-silico study of CAR T-cells immunotherapy

One of the barriers to the development of effective cellular therapies, specifically for CAR T-cells, is target antigen heterogeneity. It is thought that intratumour heterogeneity is one of the leading determinants of therapeutic resistance and treatment failure. While understanding antigen heterogeneity is important for effective therapeutics, a good therapy strategy could enhance the therapy efficiency.
Within this broad context, the aim of our work is to use our agent-based model to rationalise the potential outcomes of CAR T-cell therapies over patient derived heterogeneous tumour organoids, using a computational approach. The importance of computational models lies at its ability to predict non-intuitive results. Here, we show that using an ABM model, we are able to analyse the results of different treatments characterised by different schedules and dosages, without wrecking the organoid with therapies that are not likely to produce any significant outcome.

Main reuslts

• Our model suggests that increasing the CAR T-cell number does not necessarily increase the killing ratio. Higher ratios reduce the mutational load of the tumour making it less prolific, but by the end of the simulation, the amount of free CAR T-cells increases as we increase the dosage, and so does the risk of side effects. 
• We increased the CAR T-cells persistence to prevent exhaustion. We found that enhancing the persistence of the CAR T-cells will not necessarily improve the therapy outcomes, but it can be associated with increasing levels of T-cell hypofunction. 
• We provided multiple doses of highly active CAR T-cells to replace those that have become hypofunctional. A second dose was applied at different days, for different dosage ratios. The tumour size was reduced as well as the tumour growth rate. Our model suggests that a second dose of Cancer:CAR T-cell ratio = 1.00 shows a significant reduction compared to the application of only one dose, particularly when applied between days 4 and 8, i.e. not very late but also not very soon.
• One emergent phenomenon that came out of the simulations, and might be another reason for therapy inefficiency in solid tumours, is the formation of a shield-like structure of cells with low oncoprotein expression and reduced proliferation rate, that protected cells with high oncoprotein expression.​

• In order to overcome antigen escape and heterogeneity, we studied another approach of therapy, based in the syn-Notch receptor. In this context T-cells can target every cancer cell, regardless of its oncoprotein expression value. It has been found that doses of ratio larger than 1.50, will successfully eliminate the organoid. Since one of the milestones of this type of therapies is their capacity to target cancer cells not only in the primary tumour but in the whole body, this result is very promising if one considers this large ratio as an early stage metastasis—CAR T-cell ratio. In other words, If we apply a dose of a small ratio compared to the primary tumour, but the patient developed an early stage metastasis, i.e. a smaller tumour, the normal ratio will become a large ratio compared to the metastasis and will successfully eliminate it.

Even though our model is not a 1 : 1 in silico copy of the organoid and, therefore, it can not accurately describe in full detail the complex biological processes, it could serve as a tool to test different hypotheses, as well as for testing and analysing possible outcomes using multiple plausible parameter combinations. We are confident that once the goal of implementing patient specific factors is reached and the model undergoes rigorous calibration and validation, it could be used as a platform for in silico conducting virtual clinical trials.

Liver & HCC

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