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Mathematical modeling the order of driver gene mutations in colorectal cancer
Li, Lingling1,2; Hu, Yulu2; Xu, Yunshan3; Tang, Sanyi1
2023-06-27
Source PublicationPLoS computational biology
ISSN1553-734X
Volume19Issue:6Pages:e1011225
Abstract

Tumor heterogeneity is a large obstacle for cancer study and treatment. Different cancer patients may involve different combinations of gene mutations or the distinct regulatory pathways for inducing the progression of tumor. Investigating the pathways of gene mutations which can cause the formation of tumor can provide a basis for the personalized treatment of cancer. Studies suggested that KRAS, APC and TP53 are the most significant driver genes for colorectal cancer. However, it is still an open issue regarding the detailed mutation order of these genes in the development of colorectal cancer. For this purpose, we analyze the mathematical model considering all orders of mutations in oncogene, KRAS and tumor suppressor genes, APC and TP53, and fit it on data describing the incidence rates of colorectal cancer at different age from the Surveillance Epidemiology and End Results registry in the United States for the year 1973-2013. The specific orders that can induce the development of colorectal cancer are identified by the model fitting. The fitting results indicate that the mutation orders with KRAS → APC → TP53, APC → TP53 → KRAS and APC → KRAS → TP53 explain the age-specific risk of colorectal cancer with very well. Furthermore, eleven pathways of gene mutations can be accepted for the mutation order of genes with KRAS → APC → TP53, APC → TP53 → KRAS and APC → KRAS → TP53, and the alternation of APC acts as the initiating or promoting event in the colorectal cancer. The estimated mutation rates of cells in the different pathways demonstrate that genetic instability must exist in colorectal cancer with alterations of genes, KRAS, APC and TP53.

DOI10.1371/journal.pcbi.1011225
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaBiochemistry & Molecular Biology ; Mathematical & Computational Biology
WOS SubjectBiochemical Research Methods ; Mathematical & Computational Biology
WOS IDWOS:001016067800001
PublisherPUBLIC LIBRARY SCIENCE, 1160 BATTERY STREET, STE 100, SAN FRANCISCO, CA 94111
Scopus ID2-s2.0-85164285658
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Document TypeJournal article
CollectionDEPARTMENT OF MATHEMATICS
Corresponding AuthorTang, Sanyi
Affiliation1.School of Mathematics and Statistics, Shaanxi Normal University, Xi'an, China
2.School of Science, Xi'an Polytechnic University, Xi'an, China
3.Mathematics Department, Faculty of Science and Technology, University of Macau, Taipa, Macau, China
Recommended Citation
GB/T 7714
Li, Lingling,Hu, Yulu,Xu, Yunshan,et al. Mathematical modeling the order of driver gene mutations in colorectal cancer[J]. PLoS computational biology, 2023, 19(6), e1011225.
APA Li, Lingling., Hu, Yulu., Xu, Yunshan., & Tang, Sanyi (2023). Mathematical modeling the order of driver gene mutations in colorectal cancer. PLoS computational biology, 19(6), e1011225.
MLA Li, Lingling,et al."Mathematical modeling the order of driver gene mutations in colorectal cancer".PLoS computational biology 19.6(2023):e1011225.
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