Emergent dynamics of underlying regulatory network links EMT and androgen receptor-dependent resistance in prostate cancer DOI Creative Commons
Rashi Jindal, Abheepsa Nanda, Maalavika Pillai

и другие.

Computational and Structural Biotechnology Journal, Год журнала: 2023, Номер 21, С. 1498 - 1509

Опубликована: Янв. 1, 2023

Advanced prostate cancer patients initially respond to hormone therapy, be it in the form of androgen deprivation therapy or second-generation therapies, such as abiraterone acetate enzalutamide. However, most men with eventually develop resistance. This resistance can arise through multiple mechanisms, genetic mutations, epigenetic non-genetic pathways, lineage plasticity along epithelial-mesenchymal neuroendocrine-like axes. These mechanisms often co-exist within a single patient's tumor and overlap cell. There exists growing need better understand how phenotypic heterogeneity results from emergent dynamics regulatory networks governing independence. Here, we investigated network connecting drivers receptor (AR) splice variant-mediated independence those transition. Model simulations for this revealed four possible phenotypes: epithelial-sensitive (ES), epithelial-resistant (ER), mesenchymal-resistant (MR) mesenchymal-sensitive (MS), latter phenotype occurring rarely. We observed that well-coordinated "teams" regulators working antagonistically enable these phenotypes. model predictions are supported by transcriptomic datasets both at single-cell bulk levels, including vitro EMT induction models clinical samples. Further, our reveal spontaneous stochastic switching between ES MR states. Addition immune checkpoint molecule, PD-L1, was able capture interactions AR, mesenchymal marker SNAIL, which also confirmed quantitative experiments. systems-level understanding driver could aid transitions progression cancers help identifying novel therapeutic strategies targets.

Язык: Английский

Mathematical modelling of cancer invasion: Phenotypic transitioning provides insight into multifocal foci formation DOI Creative Commons
Zuzanna Szymańska, Mirosław Lachowicz, Nikolaos Sfakianakis

и другие.

Journal of Computational Science, Год журнала: 2023, Номер 75, С. 102175 - 102175

Опубликована: Ноя. 20, 2023

The transition from the epithelial to mesenchymal phenotype and its reverse (from epithelial) are crucial processes necessary for progression spread of cancer. In this paper, we investigate how phenotypic switching at cancer cell level impacts behaviour tissue level, specifically on emergence isolated foci invading solid tumour mass leading a multifocal tumour. To end, propose new mathematical model invasion that includes influence rate metastasis. implications explored through numerical simulations revealing plasticity phenotypes appears be disease local invasive spread. computational show primary reminiscent in vivo breast carcinomas, where multiple, synchronous, ipsilateral neoplastic frequently observed associated with poorer patient prognosis.

Язык: Английский

Процитировано

8
Low dimensionality of phenotypic space as an emergent property of coordinated teams in biological regulatory networks DOI Creative Commons
Kishore Hari, Pradyumna Harlapur,

Aashna Saxena

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2023, Номер unknown

Опубликована: Фев. 3, 2023

Abstract Biological networks driving cell-fate decisions involve complex interactions, but they often give rise to only a few phenotypes, thus exhibiting low-dimensional dynamics. The network design principles that govern such canalization remain unclear. Here, we investigate across diverse biological contexts– Epithelial-Mesenchymal Transition, Small Cell Lung Cancer, and Gonadal determination – reveal the presence of two mutually antagonistic, well-coordinated teams nodes leads phenotypic space first principal component (PC1) axis can capture most variance. Further analysis artificial team-based random counterparts reveals decomposition is determined by team strength within these networks, demonstrating how underlying structure governs PC1 low dimensionality in corresponding transcriptomic data confirms applicability our observations. We propose topology are critical for generating landscape.

Язык: Английский

Процитировано

7
Theoretical and computational tools to model multistable gene regulatory networks DOI
Federico Bocci, Dongya Jia, Qing Nie

и другие.

Reports on Progress in Physics, Год журнала: 2023, Номер 86(10), С. 106601 - 106601

Опубликована: Авг. 2, 2023

The last decade has witnessed a surge of theoretical and computational models to describe the dynamics complex gene regulatory networks, how these interactions can give rise multistable heterogeneous cell populations. As use modeling genetic biochemical circuits becomes more widespread, theoreticians with mathematical physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, network theory biological systems. This review aims at providing clear overview most important methodologies applied in field while highlighting current future challenges. It also includes hands-on tutorials solve simulate some archetypical system used field. Furthermore, we provide concrete examples existing literature for that wish explore this fast-developing Whenever possible, highlight similarities differences between networks 'classical' systems typically studied non-equilibrium quantum mechanics.

Язык: Английский

Процитировано

7
Dynamical hallmarks of cancer: Phenotypic switching in melanoma and epithelial-mesenchymal plasticity DOI
Paras Jain, Maalavika Pillai, Atchuta Srinivas Duddu

и другие.

Seminars in Cancer Biology, Год журнала: 2023, Номер 96, С. 48 - 63

Опубликована: Окт. 1, 2023

Язык: Английский

Процитировано

7
Emergent dynamics of underlying regulatory network links EMT and androgen receptor-dependent resistance in prostate cancer DOI Creative Commons
Rashi Jindal, Abheepsa Nanda, Maalavika Pillai

и другие.

Computational and Structural Biotechnology Journal, Год журнала: 2023, Номер 21, С. 1498 - 1509

Опубликована: Янв. 1, 2023

Advanced prostate cancer patients initially respond to hormone therapy, be it in the form of androgen deprivation therapy or second-generation therapies, such as abiraterone acetate enzalutamide. However, most men with eventually develop resistance. This resistance can arise through multiple mechanisms, genetic mutations, epigenetic non-genetic pathways, lineage plasticity along epithelial-mesenchymal neuroendocrine-like axes. These mechanisms often co-exist within a single patient's tumor and overlap cell. There exists growing need better understand how phenotypic heterogeneity results from emergent dynamics regulatory networks governing independence. Here, we investigated network connecting drivers receptor (AR) splice variant-mediated independence those transition. Model simulations for this revealed four possible phenotypes: epithelial-sensitive (ES), epithelial-resistant (ER), mesenchymal-resistant (MR) mesenchymal-sensitive (MS), latter phenotype occurring rarely. We observed that well-coordinated "teams" regulators working antagonistically enable these phenotypes. model predictions are supported by transcriptomic datasets both at single-cell bulk levels, including vitro EMT induction models clinical samples. Further, our reveal spontaneous stochastic switching between ES MR states. Addition immune checkpoint molecule, PD-L1, was able capture interactions AR, mesenchymal marker SNAIL, which also confirmed quantitative experiments. systems-level understanding driver could aid transitions progression cancers help identifying novel therapeutic strategies targets.

Язык: Английский

Процитировано

6