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Bioinformatics, Computational and Systems Biology

Bioinformatics, Computational and Systems Biology - Poster Session E

Poster M5 - STAT1 multiplexes pro- and anti-cancer signaling through a temporally controlled pulse of phosphorylation

Saturday, October 26, 2024

10:00 AM - 11:00 AM EST

Location: Exhibit Hall E, F & G

Presenting Author(s)

Ranya K. A. Virk, PhD (she/her/hers)

Postdoctoral Scholar
University of California, San Francisco
San Francisco, California, United States

Co-Author(s)

XS

Xiaoxiao Sun

Research Scientist
University of California, San Francisco, United States
SA

Sigurd Angenent

Professor
University of Wisconsin, Madison, United States
LW

Lani Wu

Professor
University of California, San Francisco, United States

Last Author(s)

SA

Steven Altschuler

Professor
University of California, San Francisco, United States

Introduction: A critical limitation of targeted therapy is incomplete eradication of cancer cell populations and subsequent tumor recurrence. Targeted therapies are designed to block specific oncogene-driven pro-survival signaling pathways in cancer cells. Yet, even within a clonal population, cancer cells exhibit a range of oncogene dependencies. As a result, current treatments target the bulk population of tumor cells but fail to eliminate a distinct subpopulation of cells that persist in presumed lethal drug concentrations. These “persister” cells serve as a reservoir for the emergence of mutations that ultimately drive resistance.

The relatively new field of cancer persistence has focused on identifying molecular targets against persistence. However, a major unaddressed challenge is understanding how cancer hijacks dynamical cell signaling circuits to steer cell fate towards persistence. Recently, we discovered that the IFNg/STAT1 signaling circuit can paradoxically transmit both anti- and pro-persistence signals in EGFR-mutant non-small cell lung cancer (NSCLC) treated with targeted therapy. Specifically, STAT1 signaling increases cancer cell survival at low IFNg stimulation yet reduces survival at high stimulation. Here, we investigate a new role for the well-studied IFNg/STAT1 signal transduction circuit in cancer persistence. This provides the opportunity to dissect how patterns of opposing survival signals are weighed to dictate a cell-fate outcomes days after drug treatment; and how this circuit is hijacked by cancer to promote persistence.

Materials and

Methods: To understand how final persistence outcomes are encoded by STAT1 dynamics, we developed a phenomenological model driven by time-relevant experimental data. Based on preliminary data, we hypothesized that IFNg stimulation impacts persistence by modulating the levels of phosphorylated STAT1 (P-STAT1: anti-persistence) and unphosphorylated STAT1 (U-STAT1: pro-persistence), both of which function as transcription factors. Hinging on this hypothesis, the model consists of a system of coupled differential equations to capture temporal dynamics of key signaling components, with terms modeling interactions, synthesis, and decay. The model was fit to our experimental dataset, comprised of immunofluorescence (IF) measurements of total STAT1 (T-STAT1) and phosphorylated P-STAT1 (where T-STAT1 = P-STAT1 + U-STAT1) along with corresponding persister assays measuring cell viability after 6 days of targeted drug treatment. IFNg was administered at a wide range of doses to elicit both pro-persistence (low IFNg) and anti-persistence (high IFNg) outcomes. Our integrated approach allowed us to: 1) Impute U-STAT1 levels, which cannot be measured experimentally, from IF measurements of T-STAT1 and P-STAT1 levels. 2) Connect signaling dynamics across relevant timescales. Dynamically tracking P-STAT1 is experimentally unfeasible. Our model connects the earliest activation of P-STAT1 signaling (minutes to hours), to intermediate U-STAT1 signaling (~2-3 days), and finally to cell-fate decisions only observable many days after targeted treatment. 3) Mathematical modeling allowed us to disentangle multiple layers of feedback that regulate the strength and dynamics of IFNg/STAT1 signaling.

Results, Conclusions, and Discussions: Using our data-driven model, we discovered that positive feedback is required to encode both pro- and anti-persistence signals within the same circuit. Positive feedback occurs through transcription of STAT1 by phosphorylated STAT1. Upon IFNg stimulation, an early pulse of P-STAT1 signaling (minutes to hours) activates opposing persistence signals. For low IFNg, positive feedback drives U-STAT1 accumulation, increasing persistence. Conversely, for high IFNg, positive feedback drives a prolonged P-STAT1 pulse (hours to ~1 day), decreasing persistence. These model predictions were validated via temporally controllable JAK inhibition to determine how perturbing distinct phases of the P-STAT1 signal modulate persistence outcomes. Altogether, we demonstrate that persistence/death decisions are encoded in a temporally controlled pulse of IFNg-dependent STAT1 phosphorylation. Our study identifies two potential mechanisms to increase the efficacy of targeted drugs by rewiring the IFNg/STAT1 persister circuit: 1) eliminate positive feedback to remove pro-persistence U-STAT1 accumulation or 2) increase prolonged P-STAT1 signaling (e.g., by decreasing negative feedback or inhibiting phosphatase activity) to boost anti-persistence signaling. Notably, this is the first phenomenological model of a persister circuit capable of predicting life/death decisions from circuit perturbations. It is our hope that this study will provide a template for other studies of persister circuits and how they can be disrupted.

Acknowledgements (Optional): This work was supported by the NIH T32 Molecular and Cellular Mechanisms in Cancer postdoctoral fellowship (T32CA108462).