Emergence of hybrid states of stem-like cancer cells correlates with poor prognosis in oral cancer

Vipparthi, Kavya; Hari, Kishore; Chakraborty, Priyanka; Ghosh, Subhashis; Patel, Ankit Kumar; Ghosh, Arnab; Biswas, Nidhan K.; Sharan, Rajeev; Arun, Pattatheyil; Jolly, Mohit Kumar; Singh, Sandeep

doi:10.1016/j.isci.2022.104317

Cited by 25 publications

(23 citation statements)

References 65 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…For instance, Cancer Stem Cells (CSCs) -a subpopulation of tumor cells that can self-renew and differentiate into other phenotypes -were earlier thought to seated at the apex in the hierarchy of cellular differentiation (16). However, recent evidence across cancer types has shown that a) non-CSCs can acquire the traits of CSCs stochastically (17,18), and b) CSCs include many subpopulations that may reversibly switch among one another (19,20). The transition rates among different cellular phenotypes can, of course, be influenced by external conditions such as drug treatment (20,21).…”

Section: Fig 1 Sources Of Non-genetic Heterogeneity Cells With Distin...mentioning

confidence: 99%

“…However, recent evidence across cancer types has shown that a) non-CSCs can acquire the traits of CSCs stochastically (17,18), and b) CSCs include many subpopulations that may reversibly switch among one another (19,20). The transition rates among different cellular phenotypes can, of course, be influenced by external conditions such as drug treatment (20,21). Thus, combinatorial and/or sequential strategies that can overcome the adaptive strategies of cancer cell subpopulations by specifically targeting the vulnerabilities of a drug-induced transition are gaining increasing attention (22,23).…”

Section: Fig 1 Sources Of Non-genetic Heterogeneity Cells With Distin...mentioning

confidence: 99%

“…Several above-mentioned studies have incorporated a mathematical modelling approach to better understand the dynamics of cell-state transitions at individual cell as well as at population levels. These models have been instrumental to quantify cell-state transition rates from one subpopulation to another (17,20), explain population dynamics behavior in the absence and presence of drug (10,42,51), and to predict sequential therapies that can be helpful in overcoming the drug-induced plasticity in a cell population (23).…”

Section: Mathematical Models As a Tool To Understand Cell-state Trans...mentioning

confidence: 99%

“…At a cell population level, Markov Chain (MC) model is an extensively employed approach to study spontaneous/drug induced cell-state transitions (17,20,41). Using the population fraction of cellular states over time, MC model can determines the transition probabilities between each pair of states (Fig 4A).…”

Section: Mathematical Models As a Tool To Understand Cell-state Trans...mentioning

confidence: 99%

“…While the CD24 high sub-populations could not generate CD24 low cells, ALDH high and ALDH low ones could interconvert, highlighting a possible hierarchy within the diverse CSCs. Drug treatment can alter the transition rates between ALDH high and ALDH low to drive enrichment of ALDH high cells (20). Further, MC models can be modified to include additional factors such as cell growth (21) or differential viabilities of cell populations to specific drugs.…”

Section: Mathematical Models As a Tool To Understand Cell-state Trans...mentioning

confidence: 99%

See 4 more Smart Citations

Stochastic Population Dynamics of Cancer Stemness and Adaptive Response to Therapies

Jain¹,

Duddu²,

Jolly³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

Intratumoral heterogeneity can exist along multiple axes: Cancer Stem Cells (CSCs)/non-CSCs, drug-sensitive/drug-tolerant states and a spectrum of epithelial-hybrid-mesenchymal phenotypes. Further, these diverse cell-states can switch reversibly among one another, thereby posing a major challenge to therapeutic efficacy. Therefore, understanding the origins of phenotypic plasticity and heterogeneity remains an active area of investigation. While genomic components (mutations, chromosomal instability) driving heterogeneity have been well-studied, recent reports highlight the role of non-genetic mechanisms in enabling both phenotypic plasticity and heterogeneity. Here, we discuss various processes underlying phenotypic plasticity such as stochastic gene expression, chromatin reprogramming, asymmetric cell division and the presence of multiple “attractors”. These processes can facilitate a dynamically evolving cell population such that a subpopulation of (drug-tolerant) cells can survive lethal drug exposure and recapitulate population heterogeneity on drug withdrawal, leading to relapse. These drug-tolerant cells can be both pre-existing and also induced by the drug itself through cell-state reprogramming. The dynamics of cell-state transitions both in absence and presence of the drug can be quantified through mathematical models. Such a dynamical systems approach to elucidating patterns of intratumoral heterogeneity by integrating longitudinal experimental data with mathematical models can help design effective combinatorial and/or sequential therapies for better clinical outcomes.

show abstract

Section: Fig 1 Sources Of Non-genetic Heterogeneity Cells With Distin...mentioning

confidence: 99%

Section: Fig 1 Sources Of Non-genetic Heterogeneity Cells With Distin...mentioning

confidence: 99%

Section: Mathematical Models As a Tool To Understand Cell-state Trans...mentioning

confidence: 99%

Section: Mathematical Models As a Tool To Understand Cell-state Trans...mentioning

confidence: 99%

Section: Mathematical Models As a Tool To Understand Cell-state Trans...mentioning

confidence: 99%

See 3 more Smart Citations

Stochastic Population Dynamics of Cancer Stemness and Adaptive Response to Therapies

Jain¹,

Duddu²,

Jolly³

2022

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Targeting cancer stem cells as a strategy for reducing chemotherapy resistance in head and neck cancers

Dorna

Paluszczak

2023

J Cancer Res Clin Oncol

View full text Add to dashboard Cite

Purpose Resistance to chemotherapy and radiotherapy is the primary cause of a poor prognosis in oncological patients. Researchers identified many possible mechanisms involved in gaining a therapy-resistant phenotype by cancer cells, including alterations in intracellular drug accumulation, detoxification, and enhanced DNA damage repair. All these features are characteristic of stem cells, making them the major culprit of chemoresistance. This paper reviews the most recent evidence regarding the association between the stemness phenotype and chemoresistance in head and neck cancers. It also investigates the impact of pharmacologically targeting cancer stem cell populations in this subset of malignancies. Methods This narrative review was prepared based on the search of the PubMed database for relevant papers. Results Head and neck cancer cells belonging to the stem cell population are distinguished by the high expression of certain surface proteins (e.g., CD10, CD44, CD133), pluripotency-related transcription factors (SOX2, OCT4, NANOG), and increased activity of aldehyde dehydrogenase (ALDH). Chemotherapy itself increases the percentage of stem-like cells. Importantly, the intratumor heterogeneity of stem cell subpopulations reflects cell plasticity which has great importance for chemoresistance induction. Conclusions Evidence points to the advantage of combining classical chemotherapeutics with stemness modulators thanks to the joint targeting of the bulk of proliferating tumor cells and chemoresistant cancer stem cells, which could cause recurrence.

show abstract

Epigenetic modulation of cancer stem cells in vitro 3D models

Kumar Das,

Stella,

Saunders

et al. 2024

Cancer Stem Cells and Signaling Pathways

View full text Add to dashboard Cite

Emergence of hybrid states of stem-like cancer cells correlates with poor prognosis in oral cancer

Cited by 25 publications

References 65 publications

Stochastic Population Dynamics of Cancer Stemness and Adaptive Response to Therapies

Stochastic Population Dynamics of Cancer Stemness and Adaptive Response to Therapies

Targeting cancer stem cells as a strategy for reducing chemotherapy resistance in head and neck cancers

Epigenetic modulation of cancer stem cells in vitro 3D models

Contact Info

Product

Resources

About