Scale-free structure of cancer networks and their vulnerability to hub-directed combination therapy

BioRxiv : the Preprint Server for Biology
A. X. ChenS. Palani

Abstract

Background: The effectiveness of many targeted therapies is limited by toxicity and the rise of drug resistance. A growing appreciation of the inherent redundancies of cancer signaling has led to a rise in the number of combination therapies under development, but a better understanding of the overall cancer network topology would provide a conceptual framework for choosing effective combination partners. In this work, we explore the scale-free nature of cancer protein-protein interaction networks in 14 indications. Scale-free networks, characterized by a power-law degree distribution, are known to be resilient to random attack on their nodes, yet vulnerable to directed attacks on their hubs (their most highly connected nodes). Results: Consistent with the properties of scale-free networks, we find that lethal genes are associated with ~5-fold higher protein connectivity partners than non-lethal genes. This provides a biological rationale for a hub-centered combination attack. Our simulations show that combinations targeting hubs can efficiently disrupt 50% of network integrity by inhibiting less than 1% of the connected proteins, whereas a random attack can require inhibition of more than 30% of the connected proteins. Conclus...Continue Reading

Related Concepts

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.

Related Papers

Scientific American
Albert-László Barabási, Eric Bonabeau
BioEssays : News and Reviews in Molecular, Cellular and Developmental Biology
Vic Norris, Derek Raine
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
Tiago Pereira
© 2021 Meta ULC. All rights reserved