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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Abstract

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

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Recasting the cancer stem cell hypothesis: unification using a continuum model of microenvironmental forces

Jacob G. Scott,  View ORCID ProfileAndrew Dhawan,  View ORCID ProfileAnita Hjelmeland,  View ORCID ProfileJustin Lathia,  View ORCID ProfileMasahiro Hitomi,  View ORCID ProfileAlexander G. Fletcher, Philip K. Maini, Alexander R. A. Anderson

doi: https://doi.org/10.1101/169615

This article is a preprint and has not been peer-reviewed [what does this mean?].

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Abstract

Since the first evidence for cancer stem cells in leukemia, experimentalists have sought to identify tumorigenic subpopulations in solid tumors. In parallel, scientists have argued over the implications of the existence of this subpopulation. On one side, the cancer stem cell hypothesis posits that a small subset of cells within a tumor are responsible for tumorigenesis and are capable of recapitulating the entire tumor on their own. Under this hypothesis, a tumor may be conceptualized as a series of coupled compartments, representing populations of progressively differentiated cell types, starting from stem cells. The allure of this model is that it elegantly explains our therapeutic failures: we have been targeting the wrong cells. Alternatively, the stochastic model states that all cells in a tumor can have stem-like properties, and have an equally small capability of forming a tumor. As tumors are, by nature, heterogeneous, there is ample evidence to support both hypotheses. We propose a mechanistic mathematical description that integrates these two theories, settling the dissonance between the schools of thought and providing a road map for integrating disparate experimental results into a single theoretical framework. We present experimental results from clonogenic assays that demonstrate the importance of defining this novel formulation, and the clarity that is provided when interpreting these results through the lens of this formulation.

http://www.biorxiv.org/content/early/2017/07/28/169615

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The effects of mutational process and selection on driver mutations across cancer types

 View ORCID ProfileDaniel Temko, Ian Tomlinson, Simone Severini, Benjamin Schuster-Boeckler, Trevor Graham

doi: https://doi.org/10.1101/149096

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

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Epidemiological evidence has long associated environmental mutagens with increased cancer risk. However, links between specific mutation-causing processes and the acquisition of individual driver mutations have remained obscure. Here we have used public cancer sequencing data to infer the independent effects of mutation and selection on driver mutation complement. First, we detect associations between a range of mutational processes, including those linked to smoking, ageing, APOBEC and DNA mismatch repair (MMR) and the presence of key driver mutations across cancer types. Second, we quantify differential selection between well-known alternative driver mutations, including differences in selection between distinct mutant residues in the same gene. These results show that while mutational processes play a large role in determining which driver mutations are present in a cancer, the role of selection frequently dominates.

http://www.biorxiv.org/content/early/2017/06/12/149096