Collateral sensitivity is contingent on the repeatability of evolution

 View ORCID ProfileDaniel Nichol, Joseph Rutter, Christopher Bryant, Peter Jeavons,  View ORCID ProfileAlexander Anderson, Robert Bonomo, Jacob Scott

doi: https://doi.org/10.1101/185892

This article is a preprint and has not been peer-reviewed [what does this mean?].

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Antibiotic resistance represents a growing health crisis that necessitates the immediate discovery of novel treatment strategies. One such strategy is the identification of sequences of drugs exhibiting collateral sensitivity, wherein the evolution of resistance to a first drug renders a population more susceptible to a second. Here, we demonstrate that sequential multi-drug therapies derived from in vitro evolution experiments can have overstated therapeutic benefit - potentially suggesting a collaterally sensitive response where cross resistance ultimately occurs. The evolution of drug resistance need not be genetically or phenotypically convergent, and where resistance arises through divergent mechanisms, the efficacy of a second drug can vary substantially. We first quantify the likelihood of this occurring by use of a mathematical model parametrised by a set of small combinatorially complete fitness landscapes for Escherichia coli. We then verify, through in vitro experimental evolution, that a second-line drug can indeed stochastically exhibit either increased susceptibility or increased resistance when following a first. Genetic divergence is confirmed as the driver of this differential response through targeted sequencing. These results indicate that the present methodology of designing drug regimens through experimental collateral sensitivity analysis may be flawed under certain ecological conditions. Further, these results suggest the need for a more rigorous probabilistic understanding of the contingencies that can arise during the evolution of drug resistance.

http://www.biorxiv.org/content/early/2017/09/07/185892

Stromal Reactivity Differentially Drives Tumor Cell Evolution and Prostate Cancer Progression

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Ziv Frankenstein,  View ORCID ProfileDavid Basanta, Omar E. Franco, Yan Gao, Rodrigo A. Javier, Douglas W. Strand, MinJae Lee,  View ORCID ProfileSimon W. Hayward, Gustavo Ayala,  View ORCID ProfileAlexander R. A. Anderson

doi: https://doi.org/10.1101/159616 

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We implemented a hybrid multiscale model of carcinogenesis that merges data from biology and pathology on the microenvironmental regulation of prostate cancer (PCa) cell behavior. It recapitulates the biology of stromal influence in prostate cancer progression. Our data indicate that the interactions between the tumor cells and reactive stroma shape the evolutionary dynamics of PCa cells and explain overall tumor aggressiveness. We show that the degree of stromal reactivity, when coupled with the current clinical biomarkers, significantly improves PCa prognostication, both for death and recurrence, that may alter treatment decisions. We also show that stromal reactivity correlates directly with tumor growth but inversely modulates tumor evolution. This suggests that the aggressive stromal independent PCa may be an inevitable evolutionary result of poor stromal reactivity. It also suggests that purely tumor centric metrics of aggressiveness may be misleading in terms on clinical outcome.

http://www.biorxiv.org/content/early/2017/08/21/159616

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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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