Embed Size (px)
DESCRIPTION
Cancer Tumor Kinetics. Gretchen A. Koch-Noble Goucher College PEER UTK 2012. Special Thanks To:. Dr. Claudia Neuhauser University of Minnesota – Rochester Author and creator of modules. Learning Objectives. After completion of this module, the student will be able to: - PowerPoint PPT Presentation
Citation preview
Cancer Tumor Kinetics
Gretchen A. Koch-NobleGoucher CollegePEER UTK 2012
Special Thanks To:Dr. Claudia Neuhauser
University of Minnesota – Rochester Author and creator of modules
Learning ObjectivesAfter completion of this module, the student will be able to:1. Build a data‐driven phenomenological model of tumor
growth with a minimal number of parameters2. Make predictions about the kinetic behavior of a tumor
based on a mathematical model3. Define growth rate and exponential growth4. Develop a differential equations describing tumor
growth5. Use WolframAlpha to solve algebraic equations and take
limits
Prerequisites1. Volume of a sphere2. Straight lines3. Natural logarithm and exponential functions4. Graphing in Excel5. Logarithmic transformation6. Fitting a straight line to data points in Excel and
displaying the equation
Knowledge Gained1. Continuous time population models2. Fitting a straight line to data3. Doubling time of an exponentially growing
population4. Growth rate and exponential growth
Concept Map
New Cases of Cancer 2011
Map from American Cancer Society. Cancer Facts & Figures 2011. Atlanta: American Cancer Society; 2011.
Cancer Tumor KineticsThe growth and spread of the cancer tumorTumor metastasis and survival rates
Table from American Cancer Society. Cancer Facts & Figures 2011. Atlanta: American Cancer Society; 2011.
Why model cancer tumor kinetics?
Case StudyPatient with breast cancer tumor and growth of
(untreated) tumor over timeDiameter (mm)
Measurement Date D1 D2 D31 06/26/69 4 4 42 11/27/69 5 4 63 11/24/70 7 8 94 07/06/71 11 12 145 08/17/73 29 33 316 09/18/73 32 36 34
D. v. Fournier, E. Weber, W. Hoeffken, M. Bauer, F. Kubli, and V. Barth. 1980. Growth rate of 147 mammary carcinoma. Cancer 8: 2198‐2207.
Questions to AnswerWhen will the patient die?
Lethal burden of tumorWhen did the cancer start?
Depends on growth rate (doubling time)
Model Assumptions1. The shape of a tumor is a sphere2. A tumor is a solid mass of tumor cells3. An individual tumor cell is a sphere with
diameter
4. 1 gram of tumor cells corresponds to 109 cells
Create the Model: Background Information
Volume of a sphere with radius, r:
Create the Model: Background Information
Volume of a sphere with radius, r:
Create the Model: Background Information
Volume of a sphere with radius, r:
Relationship between diameter, d, and radius, r:
Create the Model: Background Information
Volume of a sphere with radius, r:
Relationship between diameter, d, and radius, r:
Create the ModelVolume of a cancer tumor, VT, with diameter, D:
Volume of individual cancer tumor cell, VC, with diameter, d:
Think, Pair, Share:Create the Model
Given the two volumes, find the number of tumor cells in any given cancer tumor.
5:00
Think, Pair, Share:Create the Model
Given the two volumes, find the number of tumor cells in any given cancer tumor.
4:00
Think, Pair, Share:Create the Model
Given the two volumes, find the number of tumor cells in any given cancer tumor.
3:00
Think, Pair, Share:Create the Model
Given the two volumes, find the number of tumor cells in any given cancer tumor.
2:00
Think, Pair, Share:Create the Model
Given the two volumes, find the number of tumor cells in any given cancer tumor.
1:00
Think, Pair, Share:Create the Model
Given the two volumes, find the number of tumor cells in any given cancer tumor.
Time to Share!
Create the ModelThe number of cells in any tumor is
Create the ModelThe number of cells in any tumor is
Create the ModelSince 109 tumor cells weigh 1 gram, the weight
of the tumor is
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
10:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
9:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
8:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
7:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
6:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
5:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
4:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
3:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
2:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
1:00
Think, Pair, Share:Create the Model
1. Download the cancer data set from the Schedule webpage.
2. Under the Patient 1 tab, calculate each of the following
a. Column G: Average diameter for the tumor of the patient
b. Column H: Volume of the tumor based on the average diameter
c. Column I: Number of cells in the tumord. Column J: Weight of the tumor
Time to Share!
Create the ModelExcel Time!
Think, Pair, Share:Kinetics Model
1. Under the Patient 1 tab, calculate each of the following
a. Column C – Days between observations: Excel can calculate the number of days between observations by using simple subtraction. Set the date of the first observation to be day 0, and calculate the days between subsequent observations.
b. Plot the Number of Tumor Cells (Column I) as a function of time (Column C).
c. Determine if transforming either or both axes logarithmically gives a straight line fit.
d. What type of function should we use to fit our data?
5:00
Think, Pair, Share:Kinetics Model
1. Under the Patient 1 tab, calculate each of the following
a. Column C – Days between observations: Excel can calculate the number of days between observations by using simple subtraction. Set the date of the first observation to be day 0, and calculate the days between subsequent observations.
b. Plot the Number of Tumor Cells (Column I) as a function of time (Column C).
c. Determine if transforming either or both axes logarithmically gives a straight line fit.
d. What type of function should we use to fit our data?
4:00
Think, Pair, Share:Kinetics Model
1. Under the Patient 1 tab, calculate each of the following
a. Column C – Days between observations: Excel can calculate the number of days between observations by using simple subtraction. Set the date of the first observation to be day 0, and calculate the days between subsequent observations.
b. Plot the Number of Tumor Cells (Column I) as a function of time (Column C).
c. Determine if transforming either or both axes logarithmically gives a straight line fit.
d. What type of function should we use to fit our data?
3:00
Think, Pair, Share:Kinetics Model
1. Under the Patient 1 tab, calculate each of the following
a. Column C – Days between observations: Excel can calculate the number of days between observations by using simple subtraction. Set the date of the first observation to be day 0, and calculate the days between subsequent observations.
b. Plot the Number of Tumor Cells (Column I) as a function of time (Column C).
c. Determine if transforming either or both axes logarithmically gives a straight line fit.
d. What type of function should we use to fit our data?
2:00
Think, Pair, Share:Kinetics Model
1. Under the Patient 1 tab, calculate each of the following
a. Column C – Days between observations: Excel can calculate the number of days between observations by using simple subtraction. Set the date of the first observation to be day 0, and calculate the days between subsequent observations.
b. Plot the Number of Tumor Cells (Column I) as a function of time (Column C).
c. Determine if transforming either or both axes logarithmically gives a straight line fit.
d. What type of function should we use to fit our data?
1:00
Think, Pair, Share:Kinetics Model
1. Under the Patient 1 tab, calculate each of the following
a. Column C – Days between observations: Excel can calculate the number of days between observations by using simple subtraction. Set the date of the first observation to be day 0, and calculate the days between subsequent observations.
b. Plot the Number of Tumor Cells (Column I) as a function of time (Column C).
c. Determine if transforming either or both axes logarithmically gives a straight line fit.
d. What type of function should we use to fit our data?
Time to Share!
Kinetics ModelExcel Time!
Think, Pair, Share:Kinetics Model
1. Use the Trendline option to fit an exponential function to the data and on the graph, display the equation of the form
2. Determine and record the values of a and c.
5:00
Think, Pair, Share:Kinetics Model
1. Use the Trendline option to fit an exponential function to the data and on the graph, display the equation of the form
2. Determine and record the values of a and c.
4:00
Think, Pair, Share:Kinetics Model
1. Use the Trendline option to fit an exponential function to the data and on the graph, display the equation of the form
2. Determine and record the values of a and c.
3:00
Think, Pair, Share:Kinetics Model
1. Use the Trendline option to fit an exponential function to the data and on the graph, display the equation of the form
2. Determine and record the values of a and c.
2:00
Think, Pair, Share:Kinetics Model
1. Use the Trendline option to fit an exponential function to the data and on the graph, display the equation of the form
2. Determine and record the values of a and c.
1:00
Think, Pair, Share:Kinetics Model
1. Use the Trendline option to fit an exponential function to the data and on the graph, display the equation of the form
2. Determine and record the values of a and c.
Time to Share!
Kinetics ModelExcel Time!
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
10:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
9:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
8:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
7:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
6:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
5:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
4:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
3:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
2:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
1:00
Think, Pair, Share:Kinetics Model
1. A number of studies have shown that a primary tumor starts from a single cell. Use the model equation to predict the date when the tumor started.
2. Tumors can be detected by palpitation when their size is about 107 to 109 cells. Tumors become lethal when their size is about 1012 to 1013 cells. This size is called the lethal burden. Based on the model equation, determine when the tumor was detectable and when the tumor reached the lethal burden?
Time to Share!
Kinetics ModelExcel Time!
Doubling Time
Doubling Time
Doubling Time
Doubling Time
Doubling Time
Doubling Time
Doubling Time
Doubling TimeThen, the doubling time does not depend on the
number of cells present.
Think, Pair, Share:Doubling Time
1. Use Excel to find the doubling time for our tumor kinetics model.
3:00
Think, Pair, Share:Doubling Time
1. Use Excel to find the doubling time for our tumor kinetics model.
2:00
Think, Pair, Share:Doubling Time
1. Use Excel to find the doubling time for our tumor kinetics model.
1:00
Think, Pair, Share:Doubling Time
1. Use Excel to find the doubling time for our tumor kinetics model.
Time to Share!
Think, Pair, Share:Doubling Time
1. Excel time!
Learning ObjectivesAfter completion of this module, the student will be able
to:1. Build a data‐driven phenomenological model of tumor
growth with a minimal number of parameters2. Make predictions about the kinetic behavior of a tumor
based on a mathematical model3. Define growth rate and exponential growth4. Develop a differential equations describing tumor growth5. Use WolframAlpha to solve algebraic equations and take
limits
Putting it all together Complete the group project on page 7 of the Cancer Tumor
Kinetics pdf to find the time to lethal burden and detection time for:
Primary Cancer Doubling Time (days)
Number of Cases
Malignant Melanoma
48 10
Colon 109 10116 25
Kidney 66 5132 8
Thyroid, anaplastic
29 7
Data Source: Table III from Friberg, S. and S. Mattson. 1997. On the growth rates of human malignant tumors: Implications for medical decision making. Journal of Surgical Oncology 65: 284‐297
![Aquaporins as diagnostic and therapeutic targets in cancer ...cancer, Laryngeal cancer, Lung cancer [43], Nasopharyngeal cancer, Ovarian cancer [37] Tumor grade, prognosis, tumor angiogenesis,](https://img.dokumen.tips/doc/110x75/5ffa8fafa51a2a21db58011f/aquaporins-as-diagnostic-and-therapeutic-targets-in-cancer-cancer-laryngeal.jpg)
