Biology subjects

McLean, I. C.

Publications and source records attributed to McLean, I. C..

4 recordsLinked to original sources

bioRxiv2025

Oncostatin M orchestrates collective epithelial migration via HIF1A activation

Extracellular signals strongly influence cell behavior, yet the mechanisms by which specific ligands mediate changes in phenotype remain unclear. The cytokine Oncostatin M (OSM) regulates homeostasis, wound healing, inflammation, and cancer progression. We previously found that OSM induces collective cell migration (CCM), a process where cells move as cohesive units while retaining cell-cell contacts, in MCF10A mammary epithelial cells. Here, we investigated how OSM drives CCM by comparing its effects with those elicited by epidermal growth factor (EGF) and interferon gamma (IFNG), defining ligand-specific phenotypes and molecular networks. Integrative transcriptomic and proteomic analyses identified hypoxia-inducible factor-1 (HIF1A) and signal transducer and activator of transcription 3 (STAT3) as central regulators of OSM responses. Functional validation revealed that HIF1A drives transcriptional programs associated with hypoxia, metabolic reprogramming, and immune pathways. Complement signaling emerged as a downstream effector of HIF1A, and its inhibition disrupted OSM-induced clustering and CCM. These findings establish a mechanistic link between OSM signaling, HIF1A activation, and CCM, demonstrating how cytokine-driven transcriptional reprogramming coordinates epithelial migration. Analysis of public breast cancer data suggests this pathway is active in human tumors and may contribute to tissue remodeling, repair, and metastasis.

cell biology↗

bioRxiv2025

Integrative Analysis of EGF, OSM, and TGFB Signaling Pathways Reveals Synergistic Mechanisms Driving Cell Motility Through CXCR2 Chemotactic Signaling and CREB Activation

The microenvironment surrounding cells plays a critical role in determining cellular phenotype. Key components of the microenvironment include the diverse milieu of ligands and cytokines bind cell surface receptors to initiate changes in molecular programs. While the responses to extracellular signals have been extensively studied in isolation, little is known about the effects of combinations of signals on phenotypic and transcriptional responses. In this study, we used a coordinated approach to systematically investigate the combinatorial effects of the cytokines Oncostatin M (OSM) and Transforming Growth Factor Beta 1 (TGFB), and the growth factor Epidermal Growth Factor (EGF) on MCF10A mammary epithelial cells. Quantitative analysis of live-cell imaging data revealed a complex array of phenotypic responses after ligand treatment, including changes in proliferation, motility, cell clustering, and cytoplasmic size. We observed that all ligand combinations produce emergent phenotypic responses distinct from the maximal effects of individual ligands, indicating induction of new molecular programs. Companion RNA sequencing studies revealed a synergistic upregulation of a small but specific transcriptional program, including genes involved in cell migration, epithelial differentiation, and chemotactic signaling. Notably, these included chemokines such as CXCL3, CXCL5, and PPBP, which are known drivers of epithelial proliferation and migration. Additionally, transcription factor enrichment analyses and Reverse Phase Protein Array (RPPA) studies highlighted distinct changes in pathway utilization and transcription factor activity following combination treatment, including enhanced activation of MAP kinase and CREB signaling, compared to treatment with either agent alone. Using partial least squares regression, we identified robust transcriptional signatures associated with quantitative cellular phenotypes. We validated these signatures in independent datasets, confirming that they generalize across cellular contexts. Finally, an in-depth functional analysis of cell motility with RNA interference and pathway inhibition revealed that synergistic upregulation of CXCR2 signaling, mediated by CREB transcription factor activation, contributes to increases in cell motility across ligand conditions. These findings underscore the importance of combinatorial signaling in reprogramming epithelial phenotypes and reveal potential therapeutic targets for disrupting synergistic pathways in disease contexts such as cancer progression. Together, this study provides a framework for understanding how complex ligand interactions shape phenotypic and molecular landscapes.

cell biology↗

bioRxiv2025

Neoplastic immune mimicry is a generalizable phenomenon in breast cancer and epithelial CD69 enables early tumor progression

Dedifferentiation programs are commonly enacted during breast cancer progression to enhance tumor cell fitness. Increased cellular plasticity within the neoplastic compartment of tumors correlates with disease aggressiveness, often culminating in greater resistance to cytotoxic therapies or augmented metastatic potential. Here we report that subpopulations of dedifferentiated neoplastic breast epithelial cells express canonical leukocyte cell surface receptor proteins and have thus named this cellular program "immune mimicry." We document neoplastic cells engaging in immune mimicry within public human breast tumor single-cell RNA-seq datasets, histopathological breast tumor specimens, breast cancer cell lines, as well as in murine transgenic and cell line-derived mammary cancer models. Immune-mimicked neoplastic cells harbor hallmarks of dedifferentiation and are enriched in treatment-resistant and high-grade breast tumors. We corroborated these observations in aggressive breast cancer cell lines where anti-proliferative cytotoxic chemotherapies drove epithelial cells toward immune mimicry. Moreover, in subsequent proof-of-concept studies, we demonstrate that expression of the CD69 leukocyte activation protein by neoplastic cells confers a proliferative advantage that facilitates early tumor growth and therefore conclude that neoplastic breast epithelial cells upregulating leukocyte surface receptors potentiate malignancy. Moving forward, neoplastic immune mimicry should be evaluated for prognostic utility in additional breast cancer cohorts to determine its potential for patient stratification. Future research should evaluate correlates with distal metastases, progression-free survival, overall survival, and therapeutic response/resistance. Statement of SignificanceNeoplastic breast epithelial cells express surface receptors canonically attributed to leukocytes and are associated with therapy resistance and aggressive tumor behavior.

cancer biology↗

bioRxiv2024

Single-cell morphodynamical trajectories enable prediction of gene expression accompanying cell state change

Extracellular signals induce changes to molecular programs that modulate multiple cellular phenotypes, including proliferation, motility, and differentiation status. The connection between dynamically adapting phenotypic states and the molecular programs that define them is not well understood. Here we develop data-driven models of single-cell phenotypic responses to extracellular stimuli by linking gene transcription levels to "morphodynamics" - changes in cell morphology and motility observable in time-lapse image data. We adopt a dynamics-first view of cell state by grouping single-cell trajectories into states with shared morphodynamic responses. The single-cell trajectories enable development of a first-of-its-kind computational approach to map live-cell dynamics to snapshot gene transcript levels, which we term MMIST, Molecular and Morphodynamics-Integrated Single-cell Trajectories. The key conceptual advance of MMIST is that cell behavior can be quantified based on dynamically defined states and that extracellular signals change the overall distribution of cell states by altering rates of switching between states. We find a cell state landscape that is bound by epithelial and mesenchymal endpoints, with distinct sequences of epithelial to mesenchymal transition (EMT) and mesenchymal to epithelial transition (MET) intermediates. The analysis yields predictions for gene expression changes consistent with curated EMT gene sets and predicts expression of thousands of RNA transcripts through extracellular signal-induced EMT and MET with near-continuous time resolution. The MMIST framework leverages true single-cell dynamical behavior to generate molecular-level omics inferences and is broadly applicable to other biological domains, time-lapse imaging approaches and molecular snapshot data. SummaryIn normal homeostatic tissues, extracellular signals induce changes in the behavior and state of epithelial cells, and aberrant responses to such signals are associated with diseases. To decode and potentially steer these responses, it is essential to link live-cell behavior to molecular programs; however, high-throughput molecular techniques are destructive or require fixation. Here we present a novel computational approach to connect single-cell measures of cell phenotype and behavior to bulk molecular readouts, enabling prediction of dynamic changes in gene expression programs. This reveals molecular programs associated with distinct cell states and identifies drivers that may be manipulated to control cell state change.

cell biology↗