Dynamical modelling of proliferative-invasive plasticity and IFNγ signaling in melanoma reveals mechanisms of PD-L1 expression heterogeneity

Abstract

Phenotypic heterogeneity of melanoma cells contributes to drug tolerance, increased metastasis, and immune evasion in patients with progressive disease. Diverse mechanisms have been individually reported to shape extensive intra- and inter- tumoral phenotypic heterogeneity, such as IFN-gamma signaling and proliferative-invasive transition, but how their crosstalk impacts tumor progression remains largely elusive. Here, using dynamical systems modeling and analysis of publicly available transcriptomic data at both bulk and single-cell levels, we demonstrate that the emergent dynamics of a regulatory network comprising MITF, SOX10, SOX9, JUN and ZEB1 can recapitulate experimental observations about the co-existence of diverse phenotypes (proliferative, neural crest-like, invasive) and reversible cell-state transitions among them. These phenotypes have varied levels of PD-L1, thus driving variability in immunosuppression. We elucidate how this heterogeneity in PD-L1 levels can be aggravated by combinatorial dynamics of these regulators with IFN-gamma signaling. Our model predictions are corroborated by analysis of PD-L1 levels in pre- and post-treatment scenarios both in vitro and in vivo. Our calibrated dynamical model offers a platform to test combinatorial therapies and provide rational avenues for clinical management of metastatic melanoma.

Proneural – Mesenchymal antagonism dominates the patterns of phenotypic heterogeneity in Glioblastoma

“…Additionally, GBM cells exhibit a remarkable degree of plasticity, allowing them to adapt and evolve rapidly in response to diverse treatments (Yabo et al, 2022). Similar to observations in breast cancer, lung cancer and melanoma (Goyal et al, 2023;Oren et al, 2021;Ramirez et al, 2016;Sahoo et al, 2021b;Su et al, 2017;Subhadarshini et al, 2023), GBM subpopulations can also undergo genetic and/or non-genetic (reversible) cell-state transitions (Goyal et al, 2023;Stepanenko et al, 2016;L. Wang et al, 2022), often driving drug resistance and eventual GBM recurrence.…”