ArticleiScience2021
Systems-level network modeling deciphers the master regulators of phenotypic plasticity and heterogeneity in melanoma.
Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 40 citations in OpenAlex.
- Modulation of Network Plasticity Opens Novel Therapeutic Possibilities in Cancer, Diabetes, and Neurodegeneration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Genetic Insight into Expression-Defined Melanoma Subtypes and Network Mechanisms: An in Silico Study.Genes · 2025Article
- SOX10, MITF, and microRNAs: Decoding their interplay in regulating melanoma plasticity.International journal of cancer · 2025Review
- Intercellular signaling reinforces single-cell level phenotypic transitions and facilitates robust re-equilibrium of heterogeneous cancer cell populations.Cell communication and signaling : CCS · 2025Article
- Low dimensionality of phenotypic space as an emergent property of coordinated teams in biological regulatory networks.iScience · 2025Article
- Mutually exclusive teams-like patterns of gene regulation characterize phenotypic heterogeneity along the noradrenergic-mesenchymal axis in neuroblastoma.Cancer biology & therapy · 2024Article
- Proneural-mesenchymal antagonism dominates the patterns of phenotypic heterogeneity in glioblastoma.iScience · 2024Article
- LncRNAs in melanoma phenotypic plasticity: emerging targets for promising therapies.RNA biology · 2024Review
- Single cell multi-omics reveal intra-cell-line heterogeneity across human cancer cell lines.Nature communications · 2023Article
- Cellular barcoding tracks heterogeneous clones through selective pressures and phenotypic transitions.Trends in cancer · 2023Review
- Toward a systems-level probing of tumor clonality.iScience · 2023Review
- Dynamics of Epithelial-Mesenchymal Plasticity: What Have Single-Cell Investigations Elucidated So Far?ACS omega · 2023Review
- Article
- Epigenetic memory acquired during long-term EMT induction governs the recovery to the epithelial state.Journal of the Royal Society, Interface · 2023Article
- Emergent dynamics of underlying regulatory network links EMT and androgen receptor-dependent resistance in prostate cancer.Computational and structural biotechnology journal · 2023Article
- Quantitative landscapes reveal trajectories of cell-state transitions associated with drug resistance in melanoma.iScience · 2022Article
- Article
- Emergent dynamics of a three-node regulatory network explain phenotypic switching and heterogeneity: a case study of Th1/Th2/Th17 cell differentiation.Molecular biology of the cell · 2022Article
- Interconnected high-dimensional landscapes of epithelial-mesenchymal plasticity and stemness in cancer.Clinical & experimental metastasis · 2022Review
- Mapping phenotypic heterogeneity in melanoma onto the epithelial-hybrid-mesenchymal axis.Frontiers in oncology · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Phenotypic (i.e. non-genetic) heterogeneity in melanoma drives dedifferentiation, recalcitrance to targeted therapy and immunotherapy, and consequent tumor relapse and metastasis. Various markers or regulators associated with distinct phenotypes in melanoma have been identified, but, how does a network of interactions among these regulators give rise to multiple "attractor" states and phenotypic switching remains elusive. Here, we inferred a network of transcription factors (TFs) that act as master regulators for gene signatures of diverse cell-states in melanoma. Dynamical simulations of this network predicted how this network can settle into different "attractors" (TF expression patterns), suggesting that TF network dynamics drives the emergence of phenotypic heterogeneity. These simulations can recapitulate major phenotypes observed in melanoma and explain de-differentiation trajectory observed upon BRAF inhibition. Our systems-level modeling framework offers a platform to understand trajectories of phenotypic transitions in the landscape of a regulatory TF network and identify novel therapeutic strategies targeting melanoma plasticity.
Indexed as
Identifiers
What OpenQuestion holds
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.