A computational model for the cancer field effect
IntroductionThe Cancer Field Effect describes an area of pre-cancerous cells that results from continued exposure to carcinogens. Cells in the cancer field can easily develop into cancer. Removal of the main tumor mass might leave the cancer field behind, increasing risk of recurrence.MethodsThe mod...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2023-07-01
|
| Series: | Frontiers in Artificial Intelligence |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frai.2023.1060879/full |
| _version_ | 1797788058232291328 |
|---|---|
| author | Karl Deutscher Thomas Hillen Jay Newby |
| author_facet | Karl Deutscher Thomas Hillen Jay Newby |
| author_sort | Karl Deutscher |
| collection | DOAJ |
| description | IntroductionThe Cancer Field Effect describes an area of pre-cancerous cells that results from continued exposure to carcinogens. Cells in the cancer field can easily develop into cancer. Removal of the main tumor mass might leave the cancer field behind, increasing risk of recurrence.MethodsThe model we propose for the cancer field effect is a hybrid cellular automaton (CA), which includes a multi-layer perceptron (MLP) to compute the effects of the carcinogens on the gene expression of the genes related to cancer development. We use carcinogen interactions that are typically associated with smoking and alcohol consumption and their effect on cancer fields of the tongue.ResultsUsing simulations we support the understanding that tobacco smoking is a potent carcinogen, which can be reinforced by alcohol consumption. The effect of alcohol alone is significantly less than the effect of tobacco. We further observe that pairing tumor excision with field removal delays recurrence compared to tumor excision alone. We track cell lineages and find that, in most cases, a polyclonal field develops, where the number of distinct cell lineages decreases over time as some lineages become dominant over others. Finally, we find tumor masses rarely form via monoclonal origin. |
| first_indexed | 2024-03-13T01:30:12Z |
| format | Article |
| id | doaj.art-91daa4c2eb1445d1b8b10c5a56b0b8c4 |
| institution | Directory Open Access Journal |
| issn | 2624-8212 |
| language | English |
| last_indexed | 2024-03-13T01:30:12Z |
| publishDate | 2023-07-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Artificial Intelligence |
| spelling | doaj.art-91daa4c2eb1445d1b8b10c5a56b0b8c42023-07-04T08:18:48ZengFrontiers Media S.A.Frontiers in Artificial Intelligence2624-82122023-07-01610.3389/frai.2023.10608791060879A computational model for the cancer field effectKarl DeutscherThomas HillenJay NewbyIntroductionThe Cancer Field Effect describes an area of pre-cancerous cells that results from continued exposure to carcinogens. Cells in the cancer field can easily develop into cancer. Removal of the main tumor mass might leave the cancer field behind, increasing risk of recurrence.MethodsThe model we propose for the cancer field effect is a hybrid cellular automaton (CA), which includes a multi-layer perceptron (MLP) to compute the effects of the carcinogens on the gene expression of the genes related to cancer development. We use carcinogen interactions that are typically associated with smoking and alcohol consumption and their effect on cancer fields of the tongue.ResultsUsing simulations we support the understanding that tobacco smoking is a potent carcinogen, which can be reinforced by alcohol consumption. The effect of alcohol alone is significantly less than the effect of tobacco. We further observe that pairing tumor excision with field removal delays recurrence compared to tumor excision alone. We track cell lineages and find that, in most cases, a polyclonal field develops, where the number of distinct cell lineages decreases over time as some lineages become dominant over others. Finally, we find tumor masses rarely form via monoclonal origin.https://www.frontiersin.org/articles/10.3389/frai.2023.1060879/fullcancer field effectfield cancerizationcarcinogenesishead and neck squamous cell carcinomacomputational modelinghybrid cellular automaton |
| spellingShingle | Karl Deutscher Thomas Hillen Jay Newby A computational model for the cancer field effect Frontiers in Artificial Intelligence cancer field effect field cancerization carcinogenesis head and neck squamous cell carcinoma computational modeling hybrid cellular automaton |
| title | A computational model for the cancer field effect |
| title_full | A computational model for the cancer field effect |
| title_fullStr | A computational model for the cancer field effect |
| title_full_unstemmed | A computational model for the cancer field effect |
| title_short | A computational model for the cancer field effect |
| title_sort | computational model for the cancer field effect |
| topic | cancer field effect field cancerization carcinogenesis head and neck squamous cell carcinoma computational modeling hybrid cellular automaton |
| url | https://www.frontiersin.org/articles/10.3389/frai.2023.1060879/full |
| work_keys_str_mv | AT karldeutscher acomputationalmodelforthecancerfieldeffect AT thomashillen acomputationalmodelforthecancerfieldeffect AT jaynewby acomputationalmodelforthecancerfieldeffect AT karldeutscher computationalmodelforthecancerfieldeffect AT thomashillen computationalmodelforthecancerfieldeffect AT jaynewby computationalmodelforthecancerfieldeffect |