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Preprint WatchMildJune 11th, 2026

Receptor-structured modelling of EGFR-driven tumor initiation: from spatially resolved cell-based simulations to reduced population dynamics

Qasim, R.; BOUCHNITA, A.

A receptor-structured multiscale model predicts that EGFR overexpression and stronger receptor-ligand binding lower the EGF threshold for sustained EGFR-driven tumor initiation.

Mild contradiction

1 prior failure

One documented clinical failure (Phase 1 or 2) overlaps with the claimed mechanism.

The indexed EGFR failure on Claidex, bg-60366-egfr-cdac-nsclc-strategic-shutdown, was a sponsor decision to halt an EGFR-directed degrader in EGFR-mutant non-small cell lung cancer rather than a refutation of EGFR biology. This preprint sits adjacent to that record. It builds a receptor-structured multiscale model of EGFR-driven tumor initiation and predicts that higher EGFR abundance and stronger receptor-ligand binding lower the EGF threshold for sustained growth. The model addresses initiation dynamics calibrated to in vivo overexpression data, not the target-engagement or resistance questions that drove the clinical shutdown, so it neither confirms nor contradicts the documented failure. The match is mechanistically tangential and the indexed failure was operational, which places this flag at MILD severity.

Abstract excerpt

Alterations in epidermal growth factor receptor (EGFR) dynamics can influence tumor initiation by changing receptor abundance, ligand-dependent activation, and downstream proliferative signaling. Mathematically linking these receptor-scale processes to population-level tumor growth remains challenging because they couple molecular, cellular, and tissue-scale dynamics. Here, we develop multiscale models that explicitly captures receptor-ligand dynamics. We analyze the dynamics of a refined version of a 3D stochastic multicellular model with explicit EGFR-EGF interactions to derive a receptor-structured continuum model in which cells are organized by active receptor clusters. This model is further reduced into a population dynamics model that tracks the mean number of active receptors. It captures the main qualitative behaviours of the higher-dimensional models while enabling analytical and numerical characterization of model-derived thresholds for sustained growth. After calibration and comparison with available \textit{in vivo} tumor-growth data under EGFR overexpression, we use the model hierarchy to quantify how initiation thresholds depend on EGF availability, EGFR abundance, receptor-ligand unbinding, and genetic potential. The models predict that EGFR overexpression, stronger receptor-ligand binding, and more aggressive cell phenotypes each lower the EGF molecular counts required for sustained tumor growth. Overall, the proposed framework provides a flexible mathematical approach for connecting receptor-ligand kinetics with population-level tumor-initiation dynamics.

Matching Claidex post-mortems

1 of 1 indexed

This is an automated contradiction flag, not an editorial judgment on the preprint's quality. Flags identify where the preclinical literature and the clinical failure record diverge.