Sun2018 - Instantaneous mutation rate in cancer initiation and progression

Model Identifier
BIOMD0000000915
Short description
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<p>Background
Cancer is one of the leading causes for the morbidity and mortality worldwide. Although substantial studies have been conducted theoretically and experimentally in recent years, it is still a challenge to explore the mechanisms of cancer initiation and progression. The investigation for these problems is very important for the diagnosis of cancer diseases and development of treatment schemes.
Results
To accurately describe the process of cancer initiation, we propose a new concept of gene initial mutation rate based on our recently designed mathematical model using the non-constant mutation rate. Unlike the widely-used average gene mutation rate that depends on the number of mutations, the gene initial mutation rate can be used to describe the initiation process of a single patient. In addition, we propose the instantaneous tumour doubling time that is a continuous function of time based on the non-constant mutation rate. Our proposed concepts are supported by the clinic data of seven patients with advanced pancreatic cancer. The regression results suggest that, compared with the average mutation rate, the estimated initial mutation rate has a larger value of correlation coefficient with the patient survival time. We also provide the estimated tumour size of these seven patients over time.
Conclusions
The proposed concepts can be used to describe the cancer initiation and progression for different patients more accurately. Since a quantitative understanding of cancer progression is important for clinical treatment, our proposed model and calculated results may provide insights into the development of treatment schemes and also have other clinic implications.</p>
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Format
SBML
(L2V4)
Related Publication
-
Instantaneous mutation rate in cancer initiation and progression.
- Sun S, Klebaner F, Zhang X, Tian T
- BMC systems biology , 11/ 2018 , Volume 12 , Issue Suppl 6 , pages: 110 , PubMed ID: 30463617
- School of Mathematical Sciences, Monash University, Melbourne, 3800, VIC, Australia.
- BACKGROUND:Cancer is one of the leading causes for the morbidity and mortality worldwide. Although substantial studies have been conducted theoretically and experimentally in recent years, it is still a challenge to explore the mechanisms of cancer initiation and progression. The investigation for these problems is very important for the diagnosis of cancer diseases and development of treatment schemes. RESULTS:To accurately describe the process of cancer initiation, we propose a new concept of gene initial mutation rate based on our recently designed mathematical model using the non-constant mutation rate. Unlike the widely-used average gene mutation rate that depends on the number of mutations, the gene initial mutation rate can be used to describe the initiation process of a single patient. In addition, we propose the instantaneous tumour doubling time that is a continuous function of time based on the non-constant mutation rate. Our proposed concepts are supported by the clinic data of seven patients with advanced pancreatic cancer. The regression results suggest that, compared with the average mutation rate, the estimated initial mutation rate has a larger value of correlation coefficient with the patient survival time. We also provide the estimated tumour size of these seven patients over time. CONCLUSIONS:The proposed concepts can be used to describe the cancer initiation and progression for different patients more accurately. Since a quantitative understanding of cancer progression is important for clinical treatment, our proposed model and calculated results may provide insights into the development of treatment schemes and also have other clinic implications.
Contributors
Submitter of the first revision: Szeyi Ng
Submitter of this revision: Ahmad Zyoud
Modellers: Szeyi Ng, Ahmad Zyoud
Submitter of this revision: Ahmad Zyoud
Modellers: Szeyi Ng, Ahmad Zyoud
Metadata information
is (3 statements)
isDescribedBy (2 statements)
hasTaxon (1 statement)
isDerivedFrom (9 statements)
occursIn (1 statement)
hasProperty (5 statements)
BioModels Database
MODEL1909300002
BioModels Database MODEL1909300002
BioModels Database BIOMD0000000915
BioModels Database MODEL1909300002
BioModels Database BIOMD0000000915
isDescribedBy (2 statements)
hasTaxon (1 statement)
isDerivedFrom (9 statements)
Experimental Factor Ontology
pancreatic carcinoma
VariO mutation
Mathematical Modelling Ontology Ordinary differential equation model
BioModels Database MODEL1909300002
Experimental Factor Ontology cancer
VariO mutation
Mathematical Modelling Ontology Ordinary differential equation model
BioModels Database MODEL1909300002
Experimental Factor Ontology cancer
occursIn (1 statement)
hasProperty (5 statements)
VariO
mutation
Experimental Factor Ontology pancreatic carcinoma
Experimental Factor Ontology cancer
Mathematical Modelling Ontology Ordinary differential equation model
NCIt Doubling Time
Experimental Factor Ontology pancreatic carcinoma
Experimental Factor Ontology cancer
Mathematical Modelling Ontology Ordinary differential equation model
NCIt Doubling Time
Curation status
Curated
Modelling approach(es)
Tags
Connected external resources
Name | Description | Size | Actions |
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Model files |
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Sun2018.xml | SBML L2V4 file for the model_Curated | 75.95 KB | Preview | Download |
Additional files |
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Sun2018 - Instantaneous mutation rate in cancer initiation and progression.cps | COPASI 4.24 (Build 197) file for the model | 60.12 KB | Preview | Download |
Sun2018 - Instantaneous mutation rate in cancer initiation and progression.xml | SBML L2V4 file for the model_Original File | 34.41 KB | Preview | Download |
Sun2018.cps | COPASI version 4.27 (Build 217) | 116.53 KB | Preview | Download |
Sun2018.sedml | sed-ml L1V2 | 10.48 KB | Preview | Download |
- Model originally submitted by : Szeyi Ng
- Submitted: Sep 30, 2019 10:23:51 AM
- Last Modified: Feb 28, 2020 2:17:30 PM
Revisions
-
Version: 5
- Submitted on: Feb 28, 2020 2:17:30 PM
- Submitted by: Ahmad Zyoud
- With comment: Automatically added model identifier BIOMD0000000915
-
Version: 2
- Submitted on: Sep 30, 2019 10:23:51 AM
- Submitted by: Szeyi Ng
- With comment: Edited model metadata online.
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revisions as only public revisions are displayed here. Any private revisions
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Legends
: Variable used inside SBML models
: Variable used inside SBML models
Species
Species | Initial Concentration/Amount |
---|---|
p 2 C19700 ; pancreatic carcinoma |
0.0 mmol |
p 8 C19700 ; pancreatic carcinoma |
0.0 mmol |
p 3 C19700 ; pancreatic carcinoma |
0.0 mmol |
p 1 pancreatic carcinoma ; C19700 |
0.0 mmol |
p 7 C19700 ; pancreatic carcinoma |
0.0 mmol |
p 4 C19700 ; pancreatic carcinoma |
0.0 mmol |
Reactions
Reactions | Rate | Parameters |
---|---|---|
p_2 => p_3 | compartment*myu*p_2 | myu = 0.001 |
p_7 => p_8 | compartment*myu*p_7 | myu = 0.001 |
p_0 => p_1 | compartment*myu*p_0 | myu = 0.001 |
p_3 => p_4 | compartment*myu*p_3 | myu = 0.001 |
p_1 => p_2 | compartment*myu*p_1 | myu = 0.001 |
p_4 => p_5 | compartment*myu*p_4 | myu = 0.001 |
p_6 => p_7 | compartment*myu*p_6 | myu = 0.001 |
Curator's comment:
(added: 28 Feb 2020, 14:15:46, updated: 28 Feb 2020, 14:15:46)
(added: 28 Feb 2020, 14:15:46, updated: 28 Feb 2020, 14:15:46)
The figures that have been reproduced from the curated model
we had to change the parameter ( a ) from 0.000001 into 0.001 to be able to reproduce the figures.
Figure 1 represent patients 2 and 8 in a constant ( b=0) and non-constant rate parameter ( b = 0.00003)
Figure 3 represent the Tumour Doubling time of the model ( DB) and the Tumour doubling time for each patient ( DT_P(1-7))