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Reese, T. C.

Publications and source records attributed to Reese, T. C..

2 recordsLinked to original sources

Temporal Clonal Tracing and Functional Perturbation Reveal Niche-Adaptive and Tumor-Intrinsic IFNγ Dependencies Driving Ovarian Cancer Metastasis

Metastasis is an emergent continuum driven by evolving reciprocal adaptations between disseminating tumor cells (DTCs) and specialized niches of different organs. The interplay between intrinsic and niche-driven mechanisms that enable DTCs to survive and home to distant organs in peritoneal ovarian cancer metastasis remains incompletely understood. Here, we present MetTag, a single-cell barcoding and transcriptome profiling approach with single cell clonality barcodes and time-stamped batch identifiers (BC.IDs) to resolve metastasis clonality and temporal dynamics of DTC colonization. Deep sequencing of MetTag barcodes revealed enrichment of early-disseminated clones across metastatic sites, and targeted depletion of pioneer DTCs diminished the outgrowth of subsequent arriving DTCs. Subsequent MetTag-coupled single cell RNA sequencing (scRNA-seq) on ascites and metastasis-bearing omenta revealed a distinct interferon-gamma (IFN{gamma})-centric transcriptional trajectory selectively enriched among pioneer clones. In vivo CRISPR/Cas9 screening of niche-specific signatures demonstrated that the tumor-intrinsic IFN{gamma} response is functionally required for peritoneal metastasis. Knockout of the IFN{gamma} receptor 1 (Ifngr1) in the initial pioneer DTCs significantly reduced total metastatic burden, revealing a critical window of time in which IFN{gamma} signaling shapes the post-seeding metastatic niche (PSMN) and subsequent metastatic evolution. Mechanistically, the tumor-intrinsic IFN{gamma} response induced Poly(ADP-Ribose) polymerase family member 14 (Parp14) and peritoneal macrophages cooperatively shield DTCs from anoikis by promoting pro-survival signaling. Our study defines the temporal clonal architecture of peritoneal niches and reveals a "first come, first served" adaptation principle, where pioneer colonizer fitness determines the success of subsequent colonizers.

cancer biology↗

Omics-Based Interaction Framework - a systems model to reveal molecular drivers of synergy

Bioactive molecule library screening strategies may empirically identify effective combination therapies. However, without a systems theory to interrogate synergistic responses, the molecular mechanisms underlying favorable drug-drug interactions remain unclear, precluding rational design of combination therapies. Here, we introduce Omics-Based Interaction Framework (OBIF) to reveal molecular drivers of synergy through integration of statistical and biological interactions in supra-additive biological responses. OBIF performs full factorial analysis of feature expression data from single vs. dual factor exposures to identify molecular clusters that reveal synergy-mediating pathways, functions and regulators. As a practical demonstration, OBIF analyzed a therapeutic dyad of immunostimulatory small molecules that induces synergistic protection against influenza A pneumonia. OBIF analysis of transcriptomic and proteomic data identified biologically relevant, unanticipated cooperation between RelA and cJun that we subsequently confirmed to be required for the synergistic antiviral protection. To demonstrate generalizability, OBIF was applied to data from a diverse array of Omics platforms and experimental conditions, successfully identifying the molecular clusters driving their synergistic responses. Hence, OBIF is a phenotype-driven systems model that supports multiplatform exploration of synergy mechanisms.

systems biology↗