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Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

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Page 1: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Metastatic Breast Cancer in the Lungs

(breast cancer)

Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Page 2: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Brief overview of Metastatic Breast cancer

Type of breast cancer that spreads to other organs

A complication of primary breast cancer

Process of cancer spreading is called metastasis

Same type of cancer cells as normal cancer

Page 3: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

**The table presents the weight of the tumor (p) in mg at time (t) (days)with the growth rate given by g(p) in mg/day.

Data table for graphs

Page 4: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Percent mass change of the tumor per day:

Page 5: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Tumor Growth Model: Density of tumor (mg) per day

Page 6: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Tumor Growth Model for “fitted” graph:

Page 7: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Tumor Regression Code

Page 8: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Tumor Kuznetsov Model Code

Page 9: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Tumor Kuznetsov Model Code (cont.)

Page 10: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Tumor Fit Data Code

Page 11: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Tumor Fit Data Code (cont.)

Page 12: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

MethodologyTo model the tumor growth and interaction with

the immune system we used the Kuznetsov version of a predator‐prey model:

which is

Page 13: Metastatic Breast Cancer in the Lungs (breast cancer) Project completed by: Brad Davis, Scott Feldhaus, Patrick Dolan, Haley Santilli

Methodology Taking x(t) as the population of tumor cells and y(t) as the population

of immune cells, we generated a linear regression of x’/x to find the parameters a and b in the Kuznetsov model.

For the other parameters, we used those given in panel (a) on page 10 of “Interactions Between the Immune System and Cancer: A Brief Review of Non‐spatial Mathematical Models” by R. Eftimie, et al. These parameters, however, did not generate an appropriate curve, because all the Kuznetsov models in the Eftimie paper yielded either decreasing, logistic, or periodic changes in the tumor cell population, while our data appeared to have an exponential growth rate.

To improve the model, we altered the parameter n to reduce the effect of the immune cells on the cancer population, and achieved an exponential growth curve closer to an unbounded Gompertz model, which fit the tumor data rather nicely.

This affected the immune cells causing a rapid collapse in the effector cell population. We then used the Python optimization code to generate a tumor growth curve with a better fit.