Biology subjects

Wood, C. S.

Publications and source records attributed to Wood, C. S..

4 recordsLinked to original sources

bioRxiv2026

PerturbLDM: conditional latent diffusion for modelling single-cell perturbation responses

Single-cell perturbation profiling maps intervention-induced phenotypes, yet experiments measure only a fraction of the perturbation-context space. Learning context-dependent perturbation effects could enable response prediction beyond measured conditions. Here we introduce PerturbLDM, a latent-diffusion framework for conditional generation of single-cell transcriptional responses. Following Tahoe-100M pretraining, it predicted 13,942 held-out combinations of observed drugs, doses and cell lines more accurately than existing methods, with higher matched-control effect correlation than an additive marginal baseline in 95.2% of conditions. The Tahoe-100M-pretrained model was further used to rank PANACEA compounds by pathway similarity, placing shared-mechanism pairs among nearest neighbours. In smaller datasets, Per-turbLDM generated a mid-gestational fetal-colon state with 67% lower gene-wise error than Squidiff, retaining the balance between absorptive and BEST4/OTOP2-like epithelial programmes. In PBMCs, it captured six of seven interferon and antiviral programmes and the interferon-associated FAO-OXPHOS programme more accurately than scGen. Together, these results support conditional response generation across data scales and biological settings.

bioinformatics↗

bioRxiv2025

Increased mRNA translation delays lung adenocarcinoma initiation and exposes a therapeutic vulnerability to MEK inhibitors

Although protein synthesis inhibitors are being evaluated as anti-cancer agents, the dynamics of mRNA translation in early tumorigenesis are still poorly understood. We report that deletion of the mRNA-translation repressor, eIF4A2 in early KRAS-driven lung adenocarcinoma leads to a dysregulated protein synthesis landscape characterised by a strongly upregulated secretome, enlarged secretory compartments, increased oxidative metabolism and acquisition of senescence-like characteristics. Paradoxically, this overdriven protein synthesis landscape delays tumorigenesis and leads to appearance of clusters of non-proliferative, p21-positive KRAS-expressing cells in the lung. Administration of rapamycin to reduce mRNA translation suppresses senescence and restores tumorigenesis following eIF4A2 deletion. Importantly, some eIF4A2 knockout cells overcome senescence to form tumours that exhibit enhanced MAP-kinase signalling and, in contrast to eIF4A2+/+ lesions, these may be eradicated by administration of a MEK inhibitor. Thus, dysregulated mRNA translation exposes a potential therapeutic vulnerability in KRAS-driven lung adenocarcinoma by forcing cancer cells to rely on MEK signalling. Statement of significanceThe requirement for anabolism in cancers has led to the search for inhibitors of mRNA translation as anti-cancer agents. However, we report that increased rates of mRNA translation promote a senescence-like phenotype in KRAS-driven lung cancer which delays tumorigenesis and renders the resulting tumours sensitive to MEK inhibition.

cancer biology↗

bioRxiv2024

Spatial resolution of transcriptomic plasticity states underpinning lethal morphologies in lung adenocarcinoma

Adenocarcinoma of the lung (LUAD) is a common and highly lethal disease. Clinical grading of disease strongly predicts recurrence and survival after surgery and is determined by morphological assessment of histological growth patterns in resected tumours. The molecular basis of growth pattern is poorly understood at present, as are the mechanisms linking growth pattern to recurrence and death. Interestingly, the two archetypal lethal morphologies, solid and micropapillary patterns, are characterised by their biphasic appearance. Both have an epithelial fraction which is in direct stromal contact, and a fraction which is not. This morphological variance seems likely to represent plasticity, and to be causally linked to mechanisms of virulence. To investigate the gene expression changes related to growth pattern both intra- and intertumoral, we applied spatial transcriptomics (Nanostring GeoMx DSP) to tissue microarray specimens of primary resected human lung adenocarcinoma. Using a variety of region-of-interest (ROI) selection strategies, we sampled 160 pure epithelial ROIs across 7 distinct morphological features of LUAD from 51 patients. Analyses of gene expression reveal fundamental trajectories connecting growth patterns, and crucial modes of plasticity which underly high-risk morphologies. These modes suggest mechanisms for the origins of growth pattern and mechanisms of virulence. Our work highlights dramatic divergence in gene expression programmes between highly lethal but morphologically diverse modes of tumour growth. Furthermore, it provides an explanation for how microscopically localised hypoxia in the primary tumour helps to establish and maintain survival strategies which ultimately determine morphology-specific mechanisms of tumour metastasis, suggesting new therapeutic vulnerabilities.

cancer biology↗

bioRxiv2022

Spatially Resolved Transcriptomics Deconvolutes Histological Prognostic Subgroups in Patients with Colorectal Cancer and Synchronous Liver Metastases

BackgroundPatients demonstrating strong immune responses to primary colorectal cancer (CRC) have a survival benefit following surgery, while those with predominantly stromal microenvironments do poorly. Biomarkers to identify patients with colorectal cancer liver metastases (CRLM) who have good prognosis following surgery for oligometastatic disease remain elusive. The aim of this study was to determine the practical application of a simple histological assessment of immune cell infiltration and stromal content in predicting outcome following synchronous resection of primary CRC and CRLM, and to interrogate the underlying functional biology that drives disease progression. MethodsPatients undergoing synchronous resection of primary CRC and CRLM underwent detailed histological assessment, panel genomic and bulk transcriptomic assessment, immunohistochemistry (IHC) and GeoMx Spatial Transcriptomics (ST) analysis. Integration with genomic features, pathway enrichment analysis and immune deconvolution were performed. ResultsHigh-immune metastases were associated with improved cancer specific survival (HR, 0.36, P=0.01). Bulk transcriptomic analysis was confounded by stromal content but ST demonstrated that the invasive edge of the metastases of long-term survivors was characterized by adaptive immune cell populations enriched for Type II Interferon signalling (NES=-2.05 P.Adj<0.005) and MHC-Class II Antigen Presentation (NES=-2.09 P.Adj<0.005). In contrast, patients with poor prognosis demonstrated increased abundance of regulatory T-cells and neutrophils with enrichment of Notch (NES=2.2 P.Adj=0.022) and TGF-{beta} (NES=2.2 P.Adj=0.02) signalling pathways at the metastatic tumor centre. ConclusionsHistological assessment stratifies outcome in patients undergoing synchronous resection of CRLM. ST analysis reveals significant intra-tumoral and inter-lesional heterogeneity with underlying transcriptomic programmes identified in driving each phenotype. TRANSLATIONAL RELEVANCEThe current study demonstrates that accurate histological assessment of immune cell infiltration and stromal content can define survival in patients following resection of oligometastatic liver disease when presenting synchronously with primary colorectal cancer. A spatial transcriptomic approach has demonstrated heterogeneity between patients, between matched lesions in the same patient and within individual lesions. Patients with high immune infiltrates at the invasive margin demonstrated lymphocytic infiltration and associated upregulated adaptive immune pathways in long term survivors. In specimens with low immune infiltrate at the tumor edge a significant reduction in survival was observed, this was determined by upregulated immunosuppressive pathways and a predominance of innate immune cells surrounding metastases. Spatial transcriptomics can be used to examine drivers of metastatic progression in CRC and identifies patients with reactive and suppressed immune microenvironments. Application across a larger cohort will build the cartography of CRLM, while in future, studies may assess application of this technology to pre and post treatment biopsy samples with the aim of predicting individual therapeutic responses. The current study has highlighted discrepancies between bulk and ST derived data whilst demonstrating accuracy of deconvoluted transcriptome to determine immune profiling. Now that ST strategies are becoming more achievable at scale, this has implications for the interpretation of the bulk transcriptomic signatures both of primary and metastatic CRC.

cancer biology↗