Robinson, T. L. | bioRxiv Science

bioRxiv2023

Analysis of uveal melanoma scRNA sequencing data identifies neoplastic-immune hybrid cells that exhibit metastatic potential

Uveal melanoma (UM) is the most common non-cutaneous melanoma and is an intraocular malignancy that affects nearly 7,000 individuals per year worldwide. Of these, nearly 50% will progress to metastatic disease for which there are currently no effective therapies. Despite advances in the molecular profiling and metastatic stratification of class 1 and 2 UM tumors, little is known regarding the underlying biology of UM metastasis. Our group has identified a disseminated tumor cell population characterized by co-expression of immune and melanoma proteins, (circulating hybrid cells (CHCs), in patients with UM. Compared to circulating tumor cells, CHCs are detected at an increased prevalence in peripheral blood and can be used as a non-invasive biomarker to predict metastatic progression. To identify mechanisms underlying enhanced hybrid cell dissemination we sought to identify hybrid cells within a primary UM single cell RNA-seq dataset. Using rigorous doublet discrimination approaches, we identified UM hybrids and evaluated their gene expression, predicted ligand-receptor status, and cell-cell communication state in relation to other melanoma and immune cells within the primary tumor. We identified several genes and pathways upregulated in hybrid cells, including those involved in enhancing cell motility and cytoskeleton rearrangement, evading immune detection, and altering cellular metabolism. In addition, we identified that hybrid cells express ligand-receptor signaling pathways implicated in promoting cancer metastasis including IGF1-IGFR1, GAS6-AXL, LGALS9-P4HB, APP-CD74 and CXCL12-CXCR4. These results contribute to our understanding of tumor progression and interactions between tumor cells and immune cells in the UM microenvironment that may promote metastasis.

cancer biology↗

bioRxiv2021

A minimal robophysical model of quadriflagellate self-propulsion

Locomotion at the microscale is remarkably sophisticated. Microorganisms have evolved diverse strategies to move within highly viscous environments, using deformable, propulsion-generating appendages such as cilia and flagella to drive helical or undulatory motion. In single-celled algae, these appendages can be arranged in different ways around an approximately 10 {micro}m cell body, and coordinated in distinct temporal patterns. Inspired by the observation that some quadriflagellates (bearing four flagella) have an outwardly similar morphology and flagellar beat pattern, yet swim at different speeds, this study seeks to determine whether variations in swimming performance could arise solely from differences in swimming gait. Robotics approaches are particularly suited to such investigations, where the phase relationships between appendages can be readily manipulated. Here, we developed autonomous, algae-inspired robophysical models that can self-propel in a viscous fluid. These macroscopic robots (length and width = 8.5 cm, height = 2 cm) have four independently actuated flagella that oscillate back and forth under low-Reynolds number conditions (Re[~] [O] (10-1)). We tested the swimming performance of these robot models with appendages arranged in one of two distinct configurations, and coordinated in one of three distinct gaits. The gaits, namely the pronk, the trot, and the gallop, correspond to gaits adopted by distinct microalgal species. When the appendages are inserted perpendicularly around a central body, the robot achieved a net performance of 0.15 - 0.63 body lengths per cycle, with the trot gait being the fastest. Robotic swimming performance was found to be comparable to that of the algal microswimmers across all gaits. By creating a minimal robot that can successfully reproduce cilia-inspired drag-based swimming, our work paves the way for the design of next-generation devices that have the capacity to autonomously navigate aqueous environments.

biophysics↗