Project 2 - Single-cell, spatial and functional dissection of cancer cell states, co-evolving ecosystems, and vulnerabilities during tumor progression and metastasis

Investigators: Benjamin Izar (Project Leader), Peter Sims, Andrea Califano

The focus of Project 2 is cancer heterogeneity of brain metastases, a key molecular correlate of poor treatment response. Heterogeneity is propelled by genomic variability, adaptation, selection/expansion of drug-resistant states, signaling-mediated reprogramming/plasticity, and a complex tumor-microenvironment (TME) that modulates progressive, tumor-mediated immunosuppression and pro-tumorigenic co-operation (1). Recent multi-omics-based insights show that primary tumor and metastatic lesions comprise multiple, phenotypically distinct cell states, some of which are primed to promote disease progression or drug resistance. Malignant states and transitions are only partially explained by sequential acquisition of somatic mutations, suggesting that they result from integration of a variety of cell-intrinsic and -extrinsic molecular cues that determine their lineage attribution, establishment, and interconversion. Thus, dissecting key tumor and TME states, their transitions, and the resulting tumor ecosystems in an integrated manner, represents an increasingly critical step to the identification of more effective, rationally deployed therapies.

To date, several technical, clinical, and analytical challenges have hampered comprehensive understanding of these processes and their potential therapeutic consequences. We propose that identifying more effective, mechanism-based targets for therapeutic development in complex tumors will critically benefit from accurate and comprehensive models of the salient cellular logic governing cancer cell behavior and interactions within the TME. Furthermore, not all disease sites are created equal. Brain metastasis, for instance, is associated with reduced drug responses even when using therapies that engender beneficial extracranial responses in the same patient. Thus, resolving determinants and consequences of tumor progression and treatment responsiveness in clinically relevant disease sites, such as the brain, is an equally relevant goal and another key focus of this Project. Addressing these fundamental questions will be achieved by developing and applying cutting-edge technical and analytical frameworks designed to nominate, functionally test, and pharmacologically modulate mechanism-based targets in novel models that faithfully recapitulate the ecosystems of brain metastases. To this end, we will leverage a series of innovations by CaST investigators, including capabilities to perform multi-modal single-cell profiling from archival tissues, single-cell spatial transcriptomics, simultaneous whole-genome sequencing (lpWGS), and integrative analytical frameworks to elucidate ecosystem-wide cell states, interactions and vulnerabilities.

In Project 2, we will develop and evolve novel computational tools, including machine-learning frameworks for improved spatio-temporal assessment of biologically and chronologically sequential events, cellular interactions, master regulators and other targets that are functionally evaluated to inform future drug therapies modulating both cancer cells and the TME. These methods and analytical tools will be broadly applicable pipelines across multiple cancer contexts. Our goals are:

• To dissect and functionally model tumor progression, using integrative, single-cell resolution, spatio-temporal analyses of tumor ecosystems in primary tumor to brain metastasis progression, by elucidating functional cancer cell states and associated genomic and phenotypic variability. 
• To develop a pipeline for the systematic stratification of both malignant and immunosuppressive TME cell states in primary and metastatic brain tumors and for the systematic elucidation of their druggable dependencies, by interrogating tumor intrinsic MR proteins and ligand/receptorspecific interactions responsible for recruiting immunosuppressive subpopulations to site-specific TMEs. 
• To develop a robust pipeline for single-cell genomic and multiplexed spatial profiling of slice cultures of human tumor ecosystems to validate drugs predicted to modulate cancer cell states and mechanisms of TME subpopulation recruitment and reprogramming to immunosuppressive states.   
   

References

1. Tirosh I, Izar B, Prakadan SM, Wadsworth MH, 2nd, Treacy D, Trombetta JJ, Rotem A, Rodman C, Lian C, Murphy G, Fallahi-Sichani M, Dutton-Regester K, Lin JR, Cohen O, Shah P, Lu D, Genshaft AS, Hughes TK, Ziegler CG, Kazer SW, Gaillard A, Kolb KE, Villani AC, Johannessen CM, Andreev AY, Van Allen EM, Bertagnolli M, Sorger PK, Sullivan RJ, Flaherty KT, Frederick DT, Jane-Valbuena J, Yoon CH, Rozenblatt-Rosen O, Shalek AK, Regev A, Garraway LA. Dissecting the multicellular ecosystem of metastatic melanoma by single-cell RNA-seq. Science. 2016;352(6282):189-96. doi: 10.1126/science.aad0501. PubMed PMID: 27124452; PMCID: PMC4944528.