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Summary: Lineage switching can induce therapy resistance in cancer. Yet, how lineage fidelity is maintained and how it can be lost remain poorly understood. Here, we have used CRISPR-Cas9-based genetic screening to demonstrate that loss of SMARCB1, a member of the SWI/SNF chromatin remodeling complex, can confer an advantage to clear cell renal cell carcinoma (ccRCC) cells upon inhibition of the renal lineage factor PAX8. Lineage factor inhibition-resistant ccRCC cells formed tumors with morphological features, but not molecular markers, of neuroendocrine differentiation. SMARCB1 inactivation led to large-scale loss of kidney-specific epigenetic programs and restoration of proliferative capacity through the adoption of new dependencies on factors that represent rare essential genes across different cancers. We further developed an analytical approach to systematically characterize lineage fidelity using large-scale CRISPR-Cas9 data. An understanding of the rules that govern lineage switching could aid the development of more durable lineage factor-targeted and other cancer therapies.

Summary: Intra-tumor heterogeneity is frequently observed in cancer patients, and it is associated with therapeutic resistance and disease relapse. However, its systematic assessment is still limited and often unfeasible. Here, we use a mathematical model of tumor progression to decipher how multiple clones emerge and organize into complex architectures. We found a trade-off between cancer cell alteration and proliferation rates that defines a transition between low and high heterogeneity, the latter characterized by branching tumor phylogenies. We predict the existence of observed and hidden intra-tumor heterogeneity, which challenges the correct estimation of intrinsic tumor complexity. Although the numbers of observed and hidden clones do not always correlate, we demonstrate that population frequencies of observed clones can be used to estimate the extent of hidden heterogeneity in both simulated and human tumors. The characterization of complex clonal architectures is a critical first step toward understanding their organizing principles and predicting their emergence. : Bioinformatics; Cancer; Cancer Systems Biology; Mathematical Biosciences; Systems Biology Subject Areas: Bioinformatics, Cancer, Cancer Systems Biology, Mathematical Biosciences, Systems Biology

Summary: Cancer cells acquire genotypic and phenotypic changes over the course of the disease. A minority of these changes enhance cell fitness, allowing a tumor to evolve and overcome environmental constraints and treatment. Cancer evolution is driven by diverse processes governed by different rules, such as discrete and irreversible genetic variants and continuous and reversible plastic reprogramming. In this perspective, we explore the role of cell plasticity in tumor evolution through specific examples. We discuss epigenetic and transcriptional reprogramming in “disease progression” of solid tumors, through the lens of the epithelial-to-mesenchymal transition, and “treatment resistance”, in the context endocrine therapy in hormone-driven cancers. These examples offer a paradigm of the features and challenges of cell plastic evolution, and we investigate how recent technological advances can address these challenges. Cancer evolution is a multi-faceted process, whose understanding and harnessing will require an equally diverse prism of perspectives and approaches.