Command Palette

Search for a command to run...

Preprint WatchMildJuly 30th, 2026

Hypergraph geometry localizes mutation-associated dependency vulnerabilities in cancer.

Lee, J.; Lee, J.

A hypergraph geometry framework localizes reproducible synthetic lethal dependencies to negatively curved network regions, and the BRAF and MAP2K1 dependency family shows strong selective sensitivity to downstream MAPK pathway inhibition in PRISM dose-response data.

Mild contradiction

1 prior failure

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

Claidex holds one BRAF failure, brimarafenib with mirdametinib in BRAF and NRAS mutant melanoma, terminated on tolerability and recorded as a safety signal (brimarafenib-mirdametinib-braf-melanoma-phase1-2-tolerability-termination). This preprint reports that the BRAF and MAP2K1 pair is selectively sensitive to downstream MAPK inhibition, which is computational support for exactly the vertical combination strategy that the Claidex entry shows failing on tolerability rather than on activity. The distinction matters: the preprint speaks to whether the combination should work, and the recorded failure speaks to whether patients can take it. Its authors also report that the geometric separation is statistically fragile, reaching only nominal significance at p equal to 0.031 and sensitive to removal of single families, so the computational claim is weak evidence on its own.

Abstract excerpt

Mutation-specific therapeutic vulnerabilities remain difficult to identify in precision oncology because lineage effects and network topology can obscure true synthetic lethal relationships. Here, we present a computational framework that maps genomic mutational profiles and genome-wide CRISPR-Cas9 screens onto multi-scale hypergraphs constructed from macromolecular complexes (CORUM), protein interaction modules (STRING), and transcriptional regulons (TRRUST). Using strict reproducibility criteria across lineage-split cohorts, we identify cross-topology overlap families of dependencies that recur across independent biological organizational layers. We then characterize these candidates with discrete hypergraph geometry, including Hypergraph Fractional Ricci Curvature (HFRC) and Hypergraph Local Ricci Curvature (HLRC), and evaluate them against multidimensional matched-null distributions and degree-preserving shuffles to control for network density and node degree bias. We evaluate the 8 core cross-topology families for clinical prognostic value. Separately, to validate the pharmacological actionability of the hypergraph framework, we project our prioritized candidates onto PRISM dose-response profiles, confirming that the geometrically constrained BRAF:MAP2K1 family exhibits strong, selective drug sensitivity to downstream MAPK pathway inhibition. The strongest face-validity result is SMARCA2:SMARCA4, a clinically validated paralog synthetic lethal pair in chromatin remodeling that our pipeline recovered purely through unsupervised geometric constraints. While across the prioritized overlap families this specific class of reproducible dependencies localizes to highly integrated, negatively curved hypergraph regions, this topological separation is statistically fragile; it achieves nominal significance (p = 0.031) as a primary endpoint and is sensitive to the removal of single families. Nonetheless, this pattern persists across independent screening platforms, including Sanger and DepMap 25Q3, suggesting a potential, albeit statistically sensitive, geometric framework for prioritizing actionable targets in precision oncology.

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.