Guardado en:
Detalles Bibliográficos
Autores principales: Harush, Uzi, Straussman, Ravid, Barzel, Baruch
Formato: Preprint
Publicado: 2025
Materias:
Acceso en línea:https://arxiv.org/abs/2501.12691
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
_version_ 1866913661112549376
author Harush, Uzi
Straussman, Ravid
Barzel, Baruch
author_facet Harush, Uzi
Straussman, Ravid
Barzel, Baruch
contents When confronted with an undesired cell population, such as bacterial infections or tumors, we seek the most effective treatment, designed to eliminate the population as rapidly as possible. A common practice is to monitor the cells short-term response to the treatment, and from that, extrapolate the eventual treatment outcome, i.e. will it eradicate the cells, and if yes at what timescales. Underlying this approach is the assumption that the cells exhibit a homogeneous response to the treatment, and hence the early response patterns can be naturally extended to later times. Recent experiments on cancer cell populations, however, indicate a significant level of cellular heterogeneity, undermining this classic assessment protocol of treatment efficacy. We, therefore, develop here a stochastic framework, to analytically predict the temporal dynamics of a heterogeneous cell population. Quite often, we find, the average cellular parameters, governing the short-term response, fail to predict the actual treatment outcome. In contrast, our analysis, which also incorporates the populations variability, helps identify the relevant statistical parameters, which in turn, enable us to predict the full trajectory of the cell population, and specifically - the likelihood and typical timescales for remission.
format Preprint
id arxiv_https___arxiv_org_abs_2501_12691
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Efficient treatment of heterogeneous malignant cell populations
Harush, Uzi
Straussman, Ravid
Barzel, Baruch
Biological Physics
Medical Physics
When confronted with an undesired cell population, such as bacterial infections or tumors, we seek the most effective treatment, designed to eliminate the population as rapidly as possible. A common practice is to monitor the cells short-term response to the treatment, and from that, extrapolate the eventual treatment outcome, i.e. will it eradicate the cells, and if yes at what timescales. Underlying this approach is the assumption that the cells exhibit a homogeneous response to the treatment, and hence the early response patterns can be naturally extended to later times. Recent experiments on cancer cell populations, however, indicate a significant level of cellular heterogeneity, undermining this classic assessment protocol of treatment efficacy. We, therefore, develop here a stochastic framework, to analytically predict the temporal dynamics of a heterogeneous cell population. Quite often, we find, the average cellular parameters, governing the short-term response, fail to predict the actual treatment outcome. In contrast, our analysis, which also incorporates the populations variability, helps identify the relevant statistical parameters, which in turn, enable us to predict the full trajectory of the cell population, and specifically - the likelihood and typical timescales for remission.
title Efficient treatment of heterogeneous malignant cell populations
topic Biological Physics
Medical Physics
url https://arxiv.org/abs/2501.12691