A model for immunotherapies against small, solid and motile tumors
(2014) FYSM31 20132Department of Physics
Computational Biology and Biological Physics - Undergoing reorganization
- Abstract (Swedish)
- Most of all deaths from cancer are due to tumor metastasis, specifically 9 out of 10. Metastasis is associated with a number of factors, including cancer cell motility, tumor adhesive property and cancer shape. As a result, the dynamics, development and consequent prognosis of tumors are still not well characterized.
The development of immunotherapies for cancer has been a focus for research in recent years and a number of studies show that it has great potential as a possible cure against cancer. In simple terms, immunotherapies elicit a specific body's immune response enabling it to prevent diseases. Results indicate that vaccination of 3-5\% of cytotoxic T cells in lymph nodes can result in an effective counteraction against cancer... (More) - Most of all deaths from cancer are due to tumor metastasis, specifically 9 out of 10. Metastasis is associated with a number of factors, including cancer cell motility, tumor adhesive property and cancer shape. As a result, the dynamics, development and consequent prognosis of tumors are still not well characterized.
The development of immunotherapies for cancer has been a focus for research in recent years and a number of studies show that it has great potential as a possible cure against cancer. In simple terms, immunotherapies elicit a specific body's immune response enabling it to prevent diseases. Results indicate that vaccination of 3-5\% of cytotoxic T cells in lymph nodes can result in an effective counteraction against cancer development. Also, clinical trials have shown encouraging outcomes, although there are still many factors in the interaction between the immune response and cancer that are not understood.
We present a three dimensional model simulating the interaction between an immune response and motile cancers after a preventative vaccine. Tumor movement is modeled using effective physical forces, with a specific focus on cell-to-cell adhesion properties and tumor cells velocity, thus taking into account the availability of cancer cells to spread and metastasize. Previous studies have pointed out that immunotherapies can be effective against small, solid tumors, but did not consider the possibility of cancer cells detaching from each other and spread. We also investigate the model dependence on the shape, density and distribution of the tumor. This shows some predictive power in determining the outcome of an immune response against solid, small (less than 10 000 cells) tumors. Our results indicate that low tumor velocity is a good indicator for a successful eradication before relapse, whilst metastasis and high velocity leads, almost invariably, to relapse and tumor escape. The effect of cell-to-cell adhesion on prognosis is itself also velocity dependent. Shape measurements have shown to be strongly related to cell distribution in different sized clusters and the probability of a successful eradication of the tumor.
In conclusion, our results generally indicate that some of the measurement techniques available to clinicians for the classification of tumors can bear some predictive power in immunotherapy. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/4285666
- author
- Flood, Emelie LU
- supervisor
- organization
- course
- FYSM31 20132
- year
- 2014
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Cancer, tumor, agent based model, delay differential equation, immunotherapy, Matlab, computations, CTL, cell motility, adhesion, repulsion, Metropolis algorithm.
- language
- English
- id
- 4285666
- date added to LUP
- 2014-03-10 11:08:44
- date last changed
- 2014-10-22 10:18:39
@misc{4285666,
abstract = {{Most of all deaths from cancer are due to tumor metastasis, specifically 9 out of 10. Metastasis is associated with a number of factors, including cancer cell motility, tumor adhesive property and cancer shape. As a result, the dynamics, development and consequent prognosis of tumors are still not well characterized.
The development of immunotherapies for cancer has been a focus for research in recent years and a number of studies show that it has great potential as a possible cure against cancer. In simple terms, immunotherapies elicit a specific body's immune response enabling it to prevent diseases. Results indicate that vaccination of 3-5\% of cytotoxic T cells in lymph nodes can result in an effective counteraction against cancer development. Also, clinical trials have shown encouraging outcomes, although there are still many factors in the interaction between the immune response and cancer that are not understood.
We present a three dimensional model simulating the interaction between an immune response and motile cancers after a preventative vaccine. Tumor movement is modeled using effective physical forces, with a specific focus on cell-to-cell adhesion properties and tumor cells velocity, thus taking into account the availability of cancer cells to spread and metastasize. Previous studies have pointed out that immunotherapies can be effective against small, solid tumors, but did not consider the possibility of cancer cells detaching from each other and spread. We also investigate the model dependence on the shape, density and distribution of the tumor. This shows some predictive power in determining the outcome of an immune response against solid, small (less than 10 000 cells) tumors. Our results indicate that low tumor velocity is a good indicator for a successful eradication before relapse, whilst metastasis and high velocity leads, almost invariably, to relapse and tumor escape. The effect of cell-to-cell adhesion on prognosis is itself also velocity dependent. Shape measurements have shown to be strongly related to cell distribution in different sized clusters and the probability of a successful eradication of the tumor.
In conclusion, our results generally indicate that some of the measurement techniques available to clinicians for the classification of tumors can bear some predictive power in immunotherapy.}},
author = {{Flood, Emelie}},
language = {{eng}},
note = {{Student Paper}},
title = {{A model for immunotherapies against small, solid and motile tumors}},
year = {{2014}},
}