Biology subjects

Cannell, I. G.

Publications and source records attributed to Cannell, I. G..

4 recordsLinked to original sources

bioRxiv2026

A three-dimensional imaging pipeline for the detection of vasculogenic mimicry in mouse tumor models

Vasculogenic mimicry (VM) describes the ability for tumor cells to mimic endothelial cells and form tumor-lined blood vessels. Although VM is associated with poor prognosis, resistance to therapeutics and metastasis, its presence, relevance and functionality have been debated, largely due to the techniques employed to determine its presence. Dual CD31 and periodic acid-Schiff (PAS) histological staining, the method widely used to detect VM within tumor tissue, is hampered by issues with artifacts of 2D sections and does not assess active blood flow through vessels and hence cannot confirm vessel functionality. Here, we present a 3D imaging pipeline to detect functionally perfused VM and host vessels within mouse tumor models. Mice tumor models are intravenously injected with fluorescently-labelled tomato lectin which binds to the lumen of functional blood vessels. These tumors are thickly sliced, optically-cleared, stained with endothelial markers and imaged using light-sheet microscopy. We apply this imaging modality to image tumors from six breast cancer patient-derived tissue xenograft models, an orthotopic mammary cancer model and two small cell lung cancer circulating-tumor cell explant models, where VM vessels, mosaic vessels and host-VM vessel junctions can be detected. To our knowledge, this is the largest collection of 3D VM vessel images to date, providing convincing evidence of the presence and functionality of VM within tumors and defining the level of evidence necessary to detect VM in vivo.

cancer biology↗

bioRxiv2025

Unravelling the in vivo traits of vasculogenic mimicry

Vasculogenic mimicry (VM) describes the ability of cancer cells to acquire endothelial properties and form vessel-like channels that facilitate tumour blood supply. While the molecular drivers of VM have been well-explored in cell cultures and biopsies, an in vivo description remains elusive. Here, we used graph theory to define VM biomarkers and elucidate the spatiotemporal dynamics of VM using in vitro and in vivo breast cancer models with and without anti-angiogenic treatment. Optical microscopy was used to assess pseudo-vascular networks in vitro while photoacoustic imaging across scales was applied in vivo to identify and locate haemoglobin contrast-derived blood vessel morphology and functionality. VM was associated with greater oxygenation heterogeneity and poorer anti-angiogenic response, reflected as stable meshed networks in vitro and blood-containing circular structures in vivo. We demonstrate for the first time a multi-scale approach bridging the in vitro-in vivo translational gap to assess anti-vascular treatment resistance and the therapeutic potential in vasculogenic mimicry-rich tumours, exploring novel avenues in preclinical drug screening and systemic drug delivery.

cancer biology↗

bioRxiv2021

WILD-seq: Clonal deconvolution of transcriptomic signatures of sensitivity and resistance to cancer therapeutics in vivo.

Tumor heterogeneity is thought to be a major barrier to successful cancer treatment due to the presence of drug resistant clonal lineages. However, identifying the characteristics of such lineages that underpin resistance to therapy has remained challenging. Here we utilize clonal transcriptomics with WILD-seq; Wholistic Interrogation of Lineage Dynamics by sequencing, in mouse models of triple-negative breast cancer (TNBC) to understand response and resistance to therapy, including BET bromodomain inhibition and taxane-based chemotherapy. This analysis revealed oxidative stress protection by NRF2 as a major mechanism of taxane resistance and led to the discovery that our tumor models are collaterally sensitive to asparagine deprivation therapy using the clinical stage drug L-asparaginase after frontline treatment with docetaxel. In summary, clonal transcriptomics with WILD-seq identifies mechanisms of resistance to chemotherapy that are also operative in patients and pin points asparagine bioavailability as a druggable vulnerability of taxane resistant lineages.

cancer biology↗

bioRxiv2018

Transite: A computational motif-based analysis platform that identifies RNA-binding proteins modulating changes in gene expression

RNA-binding proteins (RBPs) play critical roles in regulating gene expression by modulating splicing, RNA stability, and protein translation. In response to various stimuli, alterations in RBP function contribute to global changes in gene expression, but identifying which specific RBPs are responsible for the observed changes in gene expression patterns remains an unmet need. Here, we present Transite a multi-pronged computational approach that systematically infers RBPs influencing gene expression changes through alterations in RNA stability and degradation. As a proof of principle, we applied Transite to public RNA expression data from human patients with non-small cell lung cancer whose tumors were sampled at diagnosis, or after recurrence following treatment with platinum-based chemotherapy. Transite implicated known RBP regulators of the DNA damage response and identified hnRNPC as a new modulator of chemotherapeutic resistance, which we subsequently validated experimentally. Transite serves as a generalizable framework for the identification of RBPs responsible for gene expression changes that drive cell-state transitions and adds additional value to the vast wealth of publicly-available gene expression data.

bioinformatics↗