A stochastic model for tumor heterogeneity

TL;DR

This paper combines experimental analysis of circulating tumor cells with a Markov model to understand tumor heterogeneity, revealing phenotype interconversion and implications for metastasis and treatment strategies.

Contribution

It introduces a Markov-based stochastic model to explain tumor cell phenotype interconversion, supported by experimental data from blood samples of colon tumor patients.

Findings

Phenotype interconversion occurs among tumor cell subpopulations.

Targeting circulating tumor cells alone may be ineffective against tumor recurrence.

Understanding phenotype transitions can improve tumor growth and metastasis insights.

Abstract

Phenotype variations define heterogeneity of biological and molecular systems, which play a crucial role in several mechanisms. Heterogeneity has been demonstrated in tumor cells. Here, samples from blood of patients affected from colon tumor were analyzed and fished with a microfluidic assay based on galactose active moieties, and incubated, for culturing, in SCID mice. Following the experimental investigation, a model based on Markov theory was implemented and discussed to explain the equilibrium existing between phenotypes of subpopulations of cells sorted using the microfluidic assay. The model in combination with the experimental results had many implications for tumor heterogeneity. It displayed interconversion of phenotypes, as observed after experiments. The interconversion generates of metastatic cells and implies that targeting the CTCs will be not an efficient method to prevent tumor recurrence. Most importantly, understanding the transitions between cell phenotypes in cell population can boost the understanding of tumor generation and growth.