# Cell-State-Specific Drug Responses are Associated With Differences in Signaling Network Wiring

**Authors:** Niels Krämer, Roderick van Eijl, Tim Stohn, Sabine Tanis, Lodewyk FA. Wessels, Evert Bosdriesz, Klaas W. Mulder

PMC · DOI: 10.1016/j.mcpro.2026.101529 · 2026-02-16

## TL;DR

This study shows how drug responses in individual cells depend on their internal state and how signals flow through their networks.

## Contribution

The study reveals that cell-state differences affect drug responses and signaling network wiring in single human epidermal stem cells.

## Key findings

- Drug treatment effects propagate through the EGF-signaling pathway to other parts of the signaling network.
- Nine distinct cell-states show state-dependent drug responses for many (phospho-)proteins.
- Computational modeling reveals cell-state-specific differences in signaling network interactions.

## Abstract

Intracellular signaling pathways form networks through which information is transmitted, often in the form of kinase-mediated phosphorylation events, to interpret extracellular signals and elicit appropriate cellular responses. Yet, even isogenic cells in a homogenous environment show heterogeneity in their intracellular “cell-state”, as well as their response to extracellular signals. Here, we aimed to better understand this relation between these phenomena by investigating how information flows through the EGF-receptor centered network upon targeted drug treatment, and how this is affected by cell-to-cell-state differences. Using single-cell ID-seq, we profiled the cell-state and signaling activity in primary human epidermal stem cells by measuring 69 (phospho-)proteins upon inhibition of the Erk/MAPK (p90RSK) and Akt/mTOR (p70S6K) routes downstream of the EGF pathway. We found that the effects of drug treatment propagated from the EGF-signaling pathway to other connected parts of the cellular signaling network, indicating altered signaling flow. We identified nine distinct cell-states that show pervasive state-dependent drug-responses for many (phospho-)proteins. Computational modeling of the signaling network using single-cell Comparative Network Reconstruction showed that many interactions between phospho-proteins (i.e. network wiring) were quantitatively different between cell-states. Furthermore, (phospho-)proteins with a cell-state dependent drug response, were more likely to be involved in interactions that showed a cell-state dependent strength. Overall, our results indicate that drug treatment response and signaling interactions between proteins are closely related and modulated by cell-state.

•We study signaling response to drug treatment in individual cells using scID-seq.•Inhibition of downstream effectors results in redirection of signaling flow.•The state of the cell influences the response to inhibitor treatment.•Computational reconstruction indicates cell-state-specific signaling network wiring.

We study signaling response to drug treatment in individual cells using scID-seq.

Inhibition of downstream effectors results in redirection of signaling flow.

The state of the cell influences the response to inhibitor treatment.

Computational reconstruction indicates cell-state-specific signaling network wiring.

Not all cells in a population respond the same to external signals or drug treatment, suggesting cell-to-cell differences in signal processing. These cellular responses depend on how the signal flows through the intracellular biochemical networks to eventually regulate transcription factors. Using (phospho-)protein measurements from individual cells and computational modelling, we found that targeting downstream effectors of the EGFR pathway results in redirected signaling flow and that the paths available in the signaling network depend on the underlying state of the cell.

## Linked entities

- **Proteins:** EGF (epidermal growth factor), rl (Mitogen-activated protein kinase rl), RPS6KA1 (ribosomal protein S6 kinase A1), RPS6KB1 (ribosomal protein S6 kinase B1)
- **Species:** Homo sapiens (taxon 9606)

## Full-text entities

- **Genes:** EGFR (epidermal growth factor receptor) [NCBI Gene 1956] {aka ERBB, ERBB1, ERRP, HER1, NISBD2, NNCIS}, MTOR (mechanistic target of rapamycin kinase) [NCBI Gene 2475] {aka FRAP, FRAP1, FRAP2, RAFT1, RAPT1, SKS}, MAPK1 (mitogen-activated protein kinase 1) [NCBI Gene 5594] {aka ERK, ERK-2, ERK2, ERT1, MAPK2, NS13}, RPS6KB1 (ribosomal protein S6 kinase B1) [NCBI Gene 6198] {aka PS6K, S6K, S6K-beta-1, S6K1, STK14A, p70 S6KA}, RPS6KA1 (ribosomal protein S6 kinase A1) [NCBI Gene 6195] {aka HU-1, MAPKAPK1, MAPKAPK1A, RSK, RSK1, p90Rsk}, EGF (epidermal growth factor) [NCBI Gene 1950] {aka HOMG4, URG}, AKT1 (AKT serine/threonine kinase 1) [NCBI Gene 207] {aka AKT, PKB, PKB-ALPHA, PRKBA, RAC, RAC-ALPHA}
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Figures

14 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13014938/full.md

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Source: https://tomesphere.com/paper/PMC13014938