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Decoding Plasticity Regulators and Transition Trajectories in Glioblastoma with Single-cell Multiomics
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Decoding Plasticity Regulators and Transition Trajectories in Glioblastoma with Single-cell Multiomics

Manu Saraswat, Laura Rueda-Gensini, Elisa Heinzelmann +20 more
May 2025
 ·
bioRxiv
 ·
DOI 
10.1101/2025.05.13.653733
94
%
Reproducible
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This paper passed independent validation.
QED's automated review checked the evidence supporting each claim, the statistical methods, and whether the results are reproducible from the data provided.

It ranks in the top 1% of preprints assessed in Cancer Biology this quarter.
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Why this is interesting

This work overturns the assumption that glioblastoma plasticity is simply permissive, revealing a hierarchy of state transitions actively enforced by repressors—and demonstrating that MYT1L, a safeguard repressor, restricts invasion and prolongs survival in vivo.

Author perspective

What is the most important insight, discovery, or finding from your paper that you would like other scientists to know?
“

Many cancers resist therapy not through new mutations but by switching cell states — yet whether this plasticity is random or follows a predictable regulatory logic has remained unresolved. Combining deep-learning models of gene regulation with perturbation screens in glioblastoma, we find that the stability of its cell states rests on an asymmetric interplay of activators and repressors, wherein even low-plasticity states are not stable endpoints but configurations actively maintained by safeguard repressors. Chief among these is MYT1L, which silences the master regulators of every alternative state; its loss reactivates plasticity, whereas its overexpression suppresses tumor growth in vivo. More broadly, this study provides a data-driven blueprint for dissecting and manipulating cellular plasticity in cancer, exposing safeguard repressors as a therapeutic target class distinct from differentiation factors.

”
Moritz Mall

QED claims analysis

Summary

Glioblastoma cell states exhibit a structured hierarchy of epigenetic plasticity governed by distinct enhancer-driven gene regulatory networks, wherein neuronal-like cells deploy the transcriptional repressor MYT1L to actively silence master regulators of alternate states, thereby constraining plasticity and tumor progression—a mechanism that can be therapeutically exploited to restrict malignant state transitions and improve survival outcomes.

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Main Claim 1 –

Neuronal-like GB cells show lowest epigenetic plasticity

Supporting evidence

  • scDORI infers continuous enhancer-driven GRNs from single-cell multiomics
Main Claim 2 –

State-specific regulatory programs govern GB transition potentials

Supporting evidence

  • Transition potential predicts spatial proximity of GB states in tumors
  • Neuronal-like transitions require pseudotemporal shutdown of plasticity repressors
Main Claim 3 –

Neuronal-like GB cells repress alternate states to limit plasticity

Supporting evidence

  • MYT1L is neuronal-like specific and broadly represses alternate states
Main Claim 4 –

MYT1L binds and silences alternate-state TFs to restrict plasticity

Supporting evidence

  • CUT&RUN validates MYT1L repression of alternate-state transcription factors
  • MYT1L shifts transcription toward neuronal-like identity and suppresses alternatives
  • MYT1L induces neuronal-like morphology and reduces tumor microtube connectivity

Abstract

Glioblastoma (GB) is one of the most lethal human cancers, marked by profound intratumoral heterogeneity and near-universal treatment resistance. Cellular plasticity, the capacity of cancer cells to transition between phenotypic states, drives GB progression and resistance. However, the regulatory logic that permits or restricts specific state transitions remains poorly understood. Here, we integrated single-nucleus RNA and chromatin accessibility multi-ome profiles from over one million cells across primary IDH-wildtype GBs and developed scDORI, a scalable deep-learning framework to infer enhancer-driven gene regulatory networks (eGRNs) at single-cell resolution. Our analysis revealed a structured hierarchy of GB cell states governed by distinct regulatory programs, with marked variability in epigenetic plasticity that enables or constrains transitions. Neuronal-like tumor cells emerge as a low plasticity state that deploys active repression, in contrast to more permissive progenitor-like and astrocytic states. We identified the neuronal-like state-specific repressor MYT1L as a key regulator that silences master transcription factors of alternative states. MYT1L gain-of-function in patient-derived GB cells reduced chromatin accessibility, induced neuronal-like identity, and restricted proliferation and invasion in vivo, whereas loss-of-function reactivated plasticity and accelerated malignant features. Our findings delineate the epigenetic architecture and associated transcriptional master regulators that shape GB state trajectories, and establish safeguard repressors such as MYT1L as potential therapeutic targets to constrain malignant plasticity.

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