Adaptation and learning of molecular networks as a description of cancer development at the systems-level: Potential use in anti-cancer therapies

TL;DR

This paper models cancer development as a two-phase process involving changes in molecular network plasticity, proposing stage-specific targeting strategies for improved anti-cancer therapies based on network dynamics.

Contribution

It introduces a systems-level, network-based model of carcinogenesis emphasizing plasticity changes and suggests tailored therapeutic strategies for different cancer stages.

Findings

Early cancer cells exhibit increased noise, entropy, and heterogeneity.

Late-stage tumors show decreased network plasticity, requiring different targeting approaches.

Cancer stem cells display variable network rigidity, impacting treatment strategies.

Abstract

There is a widening recognition that cancer cells are products of complex developmental processes. Carcinogenesis and metastasis formation are increasingly described as systems-level, network phenomena. Here we propose that malignant transformation is a two-phase process, where an initial increase of system plasticity is followed by a decrease of plasticity at late stages of carcinogenesis as a model of cellular learning. We describe the hallmarks of increased system plasticity of early, tumor initiating cells, such as increased noise, entropy, conformational and phenotypic plasticity, physical deformability, cell heterogeneity and network rearrangements. Finally, we argue that the large structural changes of molecular networks during cancer development necessitate a rather different targeting strategy in early and late phase of carcinogenesis. Plastic networks of early phase cancer development need a central hit, while rigid networks of late stage primary tumors or established metastases should be attacked by the network influence strategy, such as by edgetic, multi-target, or allo-network drugs. Cancer stem cells need special diagnosis and targeting, since their dormant and rapidly proliferating forms may have more rigid, or more plastic networks, respectively. The extremely high ability to change their rigidity/plasticity may be a key differentiating hallmark of cancer stem cells. The application of early stage-optimized anti-cancer drugs to late-stage patients may be a reason of many failures in anti-cancer therapies. Our hypotheses presented here underlie the need for patient-specific multi-target therapies applying the correct ratio of central hits and network influences -- in an optimized sequence.