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Chutoe, C.

Publications and source records attributed to Chutoe, C..

2 recordsLinked to original sources

USP18 Inhibition Enhances Type I Interferon Signalling and Immune Activation in the Tumour Microenvironment of Triple-Negative Breast Cancer

Triple-negative breast cancer (TNBC) is one of the most aggressive and treatment-resistant breast cancers. Although immunotherapy has emerged as a promising treatment option, clinical benefit is limited, with only around half of patients responding, even when combined with standard chemotherapeutic agents. This limited efficacy is often attributed to immunologically "cold" tumour microenvironments (TME), which are resistant to current immunotherapies. Addressing this challenge requires approaches that can reprogram "cold" TMEs into "hot" immune-responsive states. USP18, a negative regulator of type I interferon (IFN) signalling, suppresses immune activation by removing ISG15 from target proteins and disrupting IFNAR-STAT2 interactions. Here, we show that both genetic ablation and catalytic inactivation of USP18 enhance type I IFN signalling in TNBC cells, leading to sustained STAT1/STAT2 phosphorylation. This increased IFN responsiveness promotes antigen presentation via MHC-I upregulation and increases expression of pro-apoptotic ligands such as FAS. Proteomic profiling and immunophenotyping revealed that USP18 inhibition in vivo reduces tumour growth and increases immunogenicity, accompanied by cancer-immune infiltration modulation including CD8 T cells, Th1 cells, NK cells, cDC1, and pro-inflammatory M1-like macrophages. These changes reflect a shift in the TME from an immunosuppressive to an immunostimulatory state, driven by heightened and prolonged type I IFN signalling. Our findings highlight the therapeutic potential of USP18 inhibition to convert immunologically "cold" tumours into "hot" tumours, by enhancing IFN-driven immune activation and improving the efficacy of immunotherapy in TNBCs.

cancer biology↗

DIRT/μ - Automated extraction of root hair traits using combinatorial optimization

Similar to any microscopic appendages, such as cilia or antennae, phenotyping of root hairs has been a challenge due to their complex intersecting arrangements in two-dimensional (2D) images and the technical limitations of automated measurements. Digital Imaging of Root Traits at Microscale (DIRT/) addresses this issue by computationally resolving intersections and extracting individual root hairs from 2D microscopy images. This solution enables automatic and precise trait measurements of individual root hairs. DIRT/ rigorously defines a set of rules to resolve intersecting root hairs and minimizes a newly designed cost function to combinatorically identify each root hair in the microscopy image. As a result, DIRT/ accurately measures traits such as root hair length (RHL) distribution and root hair density (RHD), which are impractical for manual assessment. We tested DIRT/ on three datasets to validate its performance and showcase potential applications. By measuring root hair traits in a fraction of the time manual methods require, DIRT/ eliminates subjective biases from manual measurements. Automating individual root hair extraction accelerates phenotyping and quantifies trait variability within and among plants, creating new possibilities to characterize root hair function and their underlying genetics.

plant biology↗