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arXiv · 2607.04938

Parenclitic hypergraphs and their application in personalized cancer therapy

K. K. H. Manjunatha·D. Aleja·F. Liu·M. Zhang·Y. Qi·L. Minati·G. -Q. Sun·S. Zhuang·C. Cai·J. Li·R. Criado·M. Romance del Rio·D. Papo·Y. -J. Ma·F. Fang·C. I. del Genio·Z. Zhao·H. Gao·S. Boccaletti
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Abstract

Understanding the differences between individual instances of the same complex system remains a central challenge, particularly in biological contexts. Parenclitic networks constitute a suitable means to detect deviations in correlations with respect to reference populations. Here, we introduce parenclitic hypergraphs, a general framework for identifying anomalies in higher-order correlations across arbitrary interaction orders. After validating the method on synthetic datasets and benchmark ones, we apply it to patient-derived cancer organoids, capturing temporal changes in gene expression between healthy and cancerous tissues as the disease progresses. Our approach not only reproduces known oncogenic signatures, but also reveals a previously unrecognized candidate therapeutic target. Since organoids are generated from individual patients, our method provides, for the first time, a viable protocol for personalized cancer therapy based on higher-order correlation patterns. These findings offer a novel, systems-level strategy for precision oncology grounded in complex systems theory.

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K. K. H. Manjunatha, D. Aleja, F. Liu, M. Zhang, Y. Qi, L. Minati, G. -Q. Sun, S. Zhuang, C. Cai, J. Li, R. Criado, M. Romance del Rio, D. Papo, Y. -J. Ma, F. Fang, C. I. del Genio, Z. Zhao, H. Gao, S. Boccaletti. 2026-07-06. Parenclitic hypergraphs and their application in personalized cancer therapy. https://arxiv.org/abs/2607.04938

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