Philip D. Dunne

This study identifies mitochondrial metabolism as a key factor in 5-fluorouracil resistance in colorectal cancer and shows that targeting mitochondrial Complex I can enhance chemotherapy effectiveness.

This study identifies stromal prostaglandin E2 as a key regulator of cell-fate plasticity in colorectal cancer, showing it converts chemosensitive stem cells into chemorefractory, prometastatic cells.

This study shows that poly(I:C) treatment in CMS4 colorectal tumors induces a pro-inflammatory, CMS1-like regenerative state and identifies biomarkers for predicting therapeutic response.

This study shows that Runx1 and Runx2 suppress Wnt/β-catenin-driven mammary tumourigenesis, with combined loss leading to increased tumour development and oncogenic pathway activation.

The paper identifies high MYC activity as a targetable feature in lung adenocarcinoma using phenotype-based subtyping and shows sensitivity to a dual inhibitor of MYC co-factors.

This study shows stromal cell sialylation via the Sialic acid/Siglec axis suppresses innate immune cell function in CRC, and targeting this pathway restores immune activity.

The paper identifies a BMP-dependent endocytosis pathway for GREM1 in epithelial cells, showing BMP binding is required for GREM1 uptake and antagonism of BMP signaling.

This study identifies TNF- and TGF-β signaling as drivers of tumour budding in CRC, linked to poor prognosis and an immunosuppressive microenvironment.

This study identifies a druggable PREX2/RAC1/PI3Kβ signalling axis in BRAF-mutant melanoma that confers resistance to therapies and can be targeted to improve treatment outcomes.

This study compares GSEA tools and finds single sample approaches better capture biological distinctions than pairwise methods in cancer recurrence analysis.

The paper identifies that reduced transcriptome panels in spatial transcriptomics can lead to inaccurate subtyping and phenotyping due to library size biases.

MouSR is an open-source tool for rapid transcriptomic analysis of human or mouse data, enabling biological discovery without programming expertise.

ACE identifies correlations between clinical and genomic data in TCGA using an evolutionary algorithm for efficient analysis.

Open-source QuPath combines tile-based whole slide viewing, object hierarchies and trainable classifiers; it automated CD3, CD8, p53, PD-L1 and stromal scoring that stratified colon cancer survival.