ReviewFrontiers in network physiology2023
Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics.
Review in Frontiers in network physiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed, 8 citations in OpenAlex.
- YAP1 Defines an Emergent, Plastic Population of Relapsed SCLC.Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer · 2026Article
- Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer.Molecular oncology · 2026Article
- Decrypting cancer's spatial code: from single cells to tissue niches.Molecular oncology · 2025Review
- YAP1 defines an emergent, plastic population of relapsed small cell lung cancer.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
Phenotypic plasticity of cancer cells can lead to complex cell state dynamics during tumor progression and acquired resistance. Highly plastic stem-like states may be inherently drug-resistant. Moreover, cell state dynamics in response to therapy allow a tumor to evade treatment. In both scenarios, quantifying plasticity is essential for identifying high-plasticity states or elucidating transition paths between states. Currently, methods to quantify plasticity tend to focus on 1) quantification of quasi-potential based on the underlying gene regulatory network dynamics of the system; or 2) inference of cell potency based on trajectory inference or lineage tracing in single-cell dynamics. Here, we explore both of these approaches and associated computational tools. We then discuss implications of each approach to plasticity metrics, and relevance to cancer treatment strategies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.