Cell-state transitions and frequency-dependent interactions among subpopulations together explain the dynamics of spontaneous epithelial-mesenchymal heterogeneity in breast cancer DOI Creative Commons
Paras Jain, Ramanarayanan Kizhuttil, M Nair

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 8, 2023

Abstract Individual cells in a tumour can be distributed among Epithelial (E) and Mesenchymal (M) cell-states, as characterised by the levels of canonical E M markers. Even after (E-M) subpopulations are isolated then cultured independently, E-M heterogeneity re-equilibrate each population over time, sometimes regaining initial distribution parental cell population. However, it remains unclear which population-level processes give rise to dynamical changes observed experimentally, including 1) differential growth, 2) cell-state switching, 3) frequency-dependent growth or state-transition rates. Here, we analyse necessity these three explaining dynamics distributions PMC42-LA HCC38 breast cancer cells. We find that differences subpopulations, with without any interactions (cooperation suppression) sub-populations, insufficient explain dynamics. This insufficiency is ameliorated transitions, albeit at slow rates, both data. Further, our models predict treatment TGFβ signalling JAK2/3 inhibitors could significantly enhance transition rates from state state, but does not prevent transitions M. Finally, devise selection criterion identify next most informative time points for future experimental data optimally improve identifiability estimated best fit model parameters. Overall, study identifies necessary shaping

Language: Английский

Epithelial–mesenchymal plasticity in cancer: signaling pathways and therapeutic targets DOI Creative Commons
Xiangpeng Wang,

Xiaoxia Xue,

Mingshi Pang

et al.

MedComm, Journal Year: 2024, Volume and Issue: 5(8)

Published: Aug. 1, 2024

Abstract Currently, cancer is still a leading cause of human death globally. Tumor deterioration comprises multiple events including metastasis, therapeutic resistance and immune evasion, all which are tightly related to the phenotypic plasticity especially epithelial–mesenchymal (EMP). cells with EMP manifest in three states as transition (EMT), partial EMT, mesenchymal–epithelial transition, orchestrate switch heterogeneity tumor via transcriptional regulation series signaling pathways, transforming growth factor‐β, Wnt/β‐catenin, Notch. However, due complicated nature EMP, diverse process not fully understood. In this review, we systematically conclude biological background, regulating mechanisms well role therapy response. We also summarize range small molecule inhibitors, immune‐related approaches, combination therapies that have been developed target for outstanding EMP‐driven deterioration. Additionally, explore potential technique EMP‐based mechanistic investigation research, may burst vigorous prospects. Overall, elucidate multifaceted aspects progression suggest promising direction treatment based on targeting EMP.

Language: Английский

Citations

4
Factors Determining Epithelial-Mesenchymal Transition in Cancer Progression DOI Open Access

Paulina Tomecka,

Dominika Kunachowicz, Julia Górczyńska

et al.

International Journal of Molecular Sciences, Journal Year: 2024, Volume and Issue: 25(16), P. 8972 - 8972

Published: Aug. 17, 2024

Epithelial-mesenchymal transition (EMT) is a process in which an epithelial cell undergoes multiple modifications, acquiring both morphological and functional characteristics of mesenchymal cell. This dynamic initiated by various inducing signals that activate numerous signaling pathways, leading to the stimulation transcription factors. EMT plays significant role cancer progression, such as metastasis tumor heterogeneity, well drug resistance. In this article, we studied molecular mechanisms, epigenetic regulation, cellular plasticity EMT, microenvironmental factors influencing process. We included vivo vitro models investigation clinical implications use curing oncological patients targeting its therapies. Additionally, review concludes with future directions challenges wide field EMT.

Language: Английский

Citations

4
Negligible Long-Term Impact of Nonlinear Growth Dynamics on Heterogeneity in Models of Cancer Cell Populations DOI Creative Commons
Stefano Giaimo, Saumil Shah, Michael Raatz

et al.

Bulletin of Mathematical Biology, Journal Year: 2025, Volume and Issue: 87(2)

Published: Jan. 3, 2025

Abstract Linear compartmental models are often employed to capture the change in cell type composition of cancer populations. Yet, these populations usually grow a nonlinear fashion. This begs question how linear can successfully describe dynamics types. Here, we propose general modeling framework with part capturing growth and transitions. We prove that this model asymptotically equivalent those governed only by its under wide range assumptions for growth.

Language: Английский

Citations

0
Molecular mechanism underlying epithelial‐mesenchymal transformation and cisplatin resistance in esophageal squamous cell carcinoma DOI Creative Commons

Kewei Song,

Chenhui Ma,

Baohong Gu

et al.

Thoracic Cancer, Journal Year: 2023, Volume and Issue: 14(31), P. 3069 - 3079

Published: Sept. 17, 2023

Abstract Esophageal cancer (EC) occupies the seventh spot of most prevalent malignancy ailments worldwide and sixth leading cause cancer‐related death. squamous cell carcinoma (ESCC) is also predominant histological subtype EC, cisplatin (DDP) commonly used as a first‐line chemotherapeutic drug for late advanced stages disease. However, emergence resistance during clinical treatment possesses significant challenge to therapeutic success patient outcomes. Collectively, epithelial‐mesenchymal transformation (EMT) process in which transcription factors are induced regulate expression epithelial stromal markers promote differentiation cells into cells. Recent studies have demonstrated close association between EMT chemotherapy tumor cells, with concrete evidence reciprocal reinforcement. Therefore, this review, we elucidate molecular mechanism underlying ESCC, shed light on mechanisms driving DDP resistance, provide insights intricate interplay ESCC. We aimed some new hypotheses perspectives that may address‐inform future strategies ESCC treatment.

Language: Английский

Citations

4
Protocol for inferring epithelial-to-mesenchymal transition trajectories from single-cell RNA sequencing data using R DOI Creative Commons
Annice Najafi, Mohit Kumar Jolly, Jason T. George

et al.

STAR Protocols, Journal Year: 2024, Volume and Issue: 5(1), P. 102819 - 102819

Published: Jan. 5, 2024

The epithelial-to-mesenchymal transition (EMT) provides crucial insights into the metastatic process and possesses prognostic value within cancer context. Here, we present COMET, an R package for inferring EMT trajectories inter-state rates from single-cell RNA sequencing data. We describe steps finding optimal number of genes a specific context, estimating EMT-related trajectories, fitting continuous-time Markov chain to inferred rates.

Language: Английский

Citations

0
Cell-state transitions and frequency-dependent interactions among subpopulations together explain the dynamics of spontaneous epithelial-mesenchymal heterogeneity in breast cancer DOI Creative Commons
Paras Jain, Ramanarayanan Kizhuttil, M Nair

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Dec. 8, 2023

Abstract Individual cells in a tumour can be distributed among Epithelial (E) and Mesenchymal (M) cell-states, as characterised by the levels of canonical E M markers. Even after (E-M) subpopulations are isolated then cultured independently, E-M heterogeneity re-equilibrate each population over time, sometimes regaining initial distribution parental cell population. However, it remains unclear which population-level processes give rise to dynamical changes observed experimentally, including 1) differential growth, 2) cell-state switching, 3) frequency-dependent growth or state-transition rates. Here, we analyse necessity these three explaining dynamics distributions PMC42-LA HCC38 breast cancer cells. We find that differences subpopulations, with without any interactions (cooperation suppression) sub-populations, insufficient explain dynamics. This insufficiency is ameliorated transitions, albeit at slow rates, both data. Further, our models predict treatment TGFβ signalling JAK2/3 inhibitors could significantly enhance transition rates from state state, but does not prevent transitions M. Finally, devise selection criterion identify next most informative time points for future experimental data optimally improve identifiability estimated best fit model parameters. Overall, study identifies necessary shaping

Language: Английский

Citations

0