Collateral sensitivity networks reveal evolutionary instability and novel treatment strategies in ALK mutated non-small cell lung cancer.

 View ORCID ProfileAndrew Dhawan, Daniel Nichol, Fumi Kinose,  View ORCID ProfileMohamed E. Abazeed,  View ORCID ProfileAndriy Marusyk,  View ORCID ProfileEric B.Haura,  View ORCID ProfileJacob G. Scott

doi: http://dx.doi.org/10.1101/075846

This article is a preprint and has not been peer-reviewed [what does this mean?].

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Abstract

Drug resistance remains an elusive problem in cancer therapy, particularly with novel targeted therapy approaches. Much work is currently focused upon the development of an increasing arsenal of targeted therapies, towards oncogenic driver genes such as ALK-EML4, to overcome the inevitable resistance that develops as therapies are continued over time. The current clinical paradigm after failure of first line ALK TKI is to administer another drug in the same class. As to which drug however, the answer is uncertain, as clinical evidence is lacking. To address this shortcoming, we evolved resistance in an ALK rearranged non-small cell lung cancer line (H3122) to a panel of 4 ALK tyrosine kinase inhibitors used in clinic, and performed a collateral sensitivity analysis to each of the other drugs. We found that all of the ALK inhibitor resistant cell lines displayed a significant cross-resistance to all other ALK inhibitors. To test for the stability of the resistance phenotypes, we evaluated the ALK-inhibitor sensitivities after drug holidays of varying length (1, 3, 7, 14, and 21 days). We found the resistance patterns to be stochastic and dynamic, with few conserved patterns. This unpredictability led us to an expanded search for treatment options for resistant cells. In this expansion, we tested a panel of 6 more anti-cancer agents for collateral sensitivity among the resistant cells, uncovering a multitude of possibilities for further treatment, including cross-sensitivity to several standard cytotoxic therapies as well as the HSP-90 inhibitors. Taken together, these results imply that resistance to targeted therapy in non-small cell lung cancer is truly a moving target; but also one where there are many opportunities to re-establish sensitivities where there was once resistance.

http://biorxiv.org/content/early/2016/09/19/075846

Cooperation between Noncanonical Ras Network Mutations in Cancer

Edward C Stites, Paul C Trampont, Lisa B Haney, Scott F Walk, Kodi S Ravichandran

doi: http://dx.doi.org/10.1101/004846

Cancer develops after the acquisition of a collection of mutations that together create the ‘cancer phenotype’. How collections of mutations work together within a cell, and whether there is selection for certain combinations of mutations, are not well understood. Using a Ras signaling network mathematical model we tested potential synergistic combinations within the Ras network. Intriguingly, our modeling, including a “computational random mutagenesis” approach, and subsequent experiments revealed that mutations of the tumor suppressor gene NF1 can amplify the effects of mutations in multiple other components of the Ras pathway, including weakly activating, noncanonical, Ras mutants. Since conventional wisdom holds that mutations within the same pathway do not co-occur, it was surprising that modeling and experiments both suggested a functional benefit for co-occurring Ras pathway mutations. Furthermore, we analyzed >3900 sequenced cancer specimens from the Cancer Cell Line Encyclopedia (CCLE) and The Cancer Genome Atlas (TCGA) and we uncovered an increased rate of co-occurrence between mutations the model predicted could display synergy. Overall, these data suggest that selective combinations of Ras pathway mutations could serve the role of cancer “driver”. More generally, this work presents a mechanism by which the context created by one mutation influences the evolutionary trajectories of cancer development, and this work suggests that mutations that result in “network instability” may promote cancer in a manner analogous to genomic instability.

Link: http://www.biorxiv.org/content/early/2014/05/06/004846

A filter-flow perspective of hematogenous metastasis offers a non-genetic paradigm for personalized cancer therapy

This is a rather short paper authored by some of us who maintain Warburg's Lens. The focus is on metastatic spread and how it can be understood from a filter-flow perspective, i.e. how the blood flow and filtration that occurs in capillary beds affects the efficiency of the process. This method builds on the work of Leonard Weiss, who was a leading figure in research into metastatic spread for many years.

Jacob G. Scott, Alexander G. Fletcher, Philip K. Maini, Alexander R. A. Anderson, Philip Gerlee

Research into mechanisms of hematogenous metastasis has largely become genetic in focus, attempting to understand the molecular basis of `seed-soil' relationships. Preceding this biological mechanism is the physical process of dissemination of circulating tumour cells (CTCs). We utilize a `filter-flow' paradigm to show that assumptions about CTC dynamics strongly affect metastatic efficiency: without data on CTC dynamics, any attempt to predict metastatic spread in individual patients is impossible.

link: http://arxiv.org/abs/1309.5078

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

David M. Gyurko, Daniel V. Veres, Dezso Modos, Katalin Lenti, Tamas Korcsmaros, Peter Csermely

(Submitted on 14 Jun 2013)

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.