Evolutionary Trade-offs during tumor progression using Pareto Task Inference (ParTI) analysis

Backgrounds: Recent advances have enabled powerful methods to type tumors into diagnosisand treatment groups. Here, we applied a framework based on multi-task evolution theory, usingthe fact that tumors need to perform multiple tasks that contribute to their fitness. This approachrelies on Pareto optimality concerning multiple evolutionary tasks. It predicts that cells thatrequire performing multiple tasks have phenotypes that fall on low dimensional polytopes,phenotypes optimal for every task, known as archetypes.Materials and Methods: For each cancer type, we downloaded the gene expression data fromthe TCGA data portal. Then we downloaded the clinical data of cancers from the cBioPortal. Wefocused our analyses on adenocarcinoma of three cancers (Colorectal, Breast, and Prostate). Tofind polyhedra and archetypes in tumor cells, we used the Pareto Task Inference (ParTI) packagein MATLAB software.Results: There are trade-offs between cancer cells for proliferation and survival. In the earlystages, tumors have more of a cell division archetype for proliferation, but as the tumorprogresses to the higher stages of malignancy, their tasks change, and they have an archetypesuch as invasion to survive.Conclusion: As tumors progress from adenoma to carcinoma, their tasks change from general tospecialize because of changes in trade-offs.

کلیدواژه ها:

ParTI ، Archetype ، Multi-task evolution ، Phenotype ، Cancer