Biology subjects

Redmond, K.

Publications and source records attributed to Redmond, K..

4 recordsLinked to original sources

bioRxiv2024

Viral mimicry redirects immunosuppressed colorectal tumour landscapes towards a proinflammatory and CMS1-like regenerative state

In colorectal cancer (CRC), tumours classifier as consensus molecular subtype 4 (CMS4) have the worst prognosis and derive negligible benefit from chemotherapy. We previously described how repressed interferon-related signalling is associated with increased relapse in CMS4 tumours. Although the viral mimetic poly(I:C) can reduce liver metastasis in vivo, the initial phenotypic changes that underpin its anti-metastatic response remain poorly described, particularly in the immunosuppressed CMS4 tumour microenvironment. Here we characterise lineage-specific anti-metastatic responses induced by poly(I:C), including acute macrophage polarisation and a novel CMS1-like regenerative stem cell state, which drive pro-inflammatory microenvironmental changes in CRC. These insights enabled the development of tractable biomarkers that identify an "immune-warm" patient subset most likely to respond to poly(I:C), enriched for mismatch-repair proficient (pMMR), anti-inflammatory macrophages and CMS4-like features. The viral mimetic poly(I:C) offers a tailored treatment option for CMS4 tumours, by reprogramming stem cell states and activation of an innate-adaptive anti-metastatic response.

cancer biology↗

bioRxiv2022

Biological misinterpretation of transcriptional signatures in tumour samples can unknowingly undermine mechanistic understanding and faithful alignment with preclinical data

Precise mechanism-based gene expression signatures (GESs) have been developed in appropriate in vitro and in vivo model systems, to identify important cancer-related signalling processes. However, some GESs originally developed to represent specific disease processes, primarily with an epithelial cell focus, are being applied to heterogeneous tumour samples where the expression of the genes in the signature may no longer be epithelial-specific. Therefore, unknowingly, even small changes in tumour stroma percentage can directly influence GESs, undermining the intended mechanistic signalling. Using colorectal cancer as an exemplar, we deployed numerous orthogonal profiling methodologies, including laser capture microdissection, flow cytometry, bulk and multiregional biopsy clinical samples, single cell RNAseq and finally spatial transcriptomics, to perform a comprehensive assessment of the potential for the most widely-used GESs to be influenced, or confounded, by stromal content in tumour tissue. To complement this work, we generated a freely-available resource, ConfoundR; https://confoundr.qub.ac.uk/, that enables users to test the extent of stromal influence on an unlimited number of the genes/signatures simultaneously across colorectal, breast, pancreatic, ovarian and prostate cancer datasets. Findings presented here demonstrate the clear potential for misinterpretation of the meaning of GESs, due to widespread stromal influences, which in-turn can undermine faithful alignment between clinical samples and preclinical data/models, particularly cell lines and organoids, or tumour models not fully recapitulating the stromal and immune microenvironment. As such, efforts to faithfully align preclinical models of disease using phenotypically-designed GESs must ensure that the signatures themselves remain representative of the same biology when applied to clinical samples.

cancer biology↗

bioRxiv2021

The Molecular Subtyping Resource (MouSR): a user-friendly tool for rapid biological discovery from human or mouse transcriptional data

Generation of transcriptional data has dramatically increased in the last decade, driving the development of analytical algorithms that enable interrogation of the biology underpinning the profiled samples. However, these resources require users to have expertise in data wrangling and analytics, reducing opportunities for biological discovery by "wet-lab" users with a limited programming skillset. Although commercial solutions exist, costs for software access can be prohibitive for academic research groups. To address these challenges, we have developed an open source and user-friendly data analysis platform for on-the-fly bioinformatic interrogation of transcriptional data derived from human or mouse tissue, called "MouSR". This internet-accessible analytical tool, https://mousr.qub.ac.uk/, enables users to easily interrogate their data using an intuitive "point and click" interface, which includes a suite of molecular characterisation options including QC, differential gene expression, gene set enrichment and microenvironmental cell population analyses from RNA-Seq. Users are provided with adjustable options for analysis parameters to generate results that can be saved as publication-quality images. To highlight its ability to perform high quality data analysis, we utilise the MouSR tool to interrogate our recently published tumour dataset, derived from genetically engineered mouse models and matched organoids, where we rapidly reproduced the key transcriptional findings. The MouSR online tool provides a unique freely-available option for users to perform rapid transcriptomic analyses and comprehensive interrogation of the signalling underpinning transcriptional datasets, which alleviates a major bottleneck for biological discovery.

bioinformatics↗

bioRxiv2021

Stromal cell sialylation suppresses T cells in inflammatory tumour microenvironments: A new tumour stromal cell immune checkpoint?

Immunosuppressive tumour microenvironments (TME) reduce the effectiveness of immune responses in cancer. Non-haematopoietic mesenchymal stromal cells (MSC), the precursor to cancer associated fibroblasts (CAFs), dictate tumour progression by enhancing immune cell suppression. Hyper-sialylation of glycans promotes immune evasion in cancer, but the role of sialyation in stromal cell-mediated immunosuppression is unknown. Here we study changes in sialyltransferase (ST) enzymes and associated surface expressed sialic acid in stromal cells following inflammatory and tumour secretome conditioning. We show that tumour conditioned stromal cells have increased levels of sialyltransferases, 2,3/6 linked sialic acid and siglec ligands. In tumour models of solid (colorectal cancer) and haematological (multiple myeloma) stromal rich tumours, stromal cell sialylation is associated with enhanced immunosuppression. Using datasets and patient samples, we confirm that targeting sialylation in tumour stromal cells reverses immune cell exhaustion. Targeting stromal cell sialylation may represent a novel immune checkpoint to reactivate anti-tumour immunity.

immunology↗