Biology subjects

Hanley, C. J.

Publications and source records attributed to Hanley, C. J..

3 recordsLinked to original sources

bioRxiv2026

Histopathology-inferred spatial transcriptomics characterizes the tumor microenvironment in 1,500 head and neck tumors and predicts clinical outcomes

Head and neck squamous cell carcinoma (HNSC) is a prevalent malignancy associated with poor prognosis despite recent therapeutic advances. We hypothesized that a comprehensive understanding of the spatial heterogeneity and organization of the tumor microenvironment (TME) can substantially improve risk stratification and prediction of treatment response in HNSC. As spatial transcriptomics (ST) remains labor-intensive and costly, we developed HEiST (H&E-Inferred Spatial Transcriptomics), a deep learning framework that predicts spatially resolved gene expression profiles directly from routine hematoxylin and eosin (H&E)-stained histology slides. After rigorous validation across two independent external ST cohorts, we applied HEiST to infer spatial transcriptomes across 1,500 HNSC patient tumors spanning two publicly available datasets and two newly generated cohorts, one treated with concurrent chemoradiotherapy (CCRT) and one with immunotherapy. This large-scale analysis uncovered reproducible spatial clusters characterizing the HNSC TME, defining two distinct prognostic Spatiotypes, Immune-Exhausted and Immune-Activated, with significantly distinct survival outcomes. Critically, spatial cluster composition accurately predicts HPV status and yields treatment response predictors for both CCRT/radiotherapy and immunotherapy that outperform costly gene-expression and direct image-based approaches. Notably, the ST cluster-based predictor of immunotherapy response markedly surpasses the performance of commonly used FDA-approved biomarkers, including CPS, TPS, and their combination. To the best of our knowledge, this represents the first virtual spatial profiling effort and the most comprehensive large-scale spatial TME analysis in HNSC to date. HEiST thus introduces a scalable, low-cost, and spatially grounded biomarker discovery for precision oncology in HNSC.

cancer biology↗

bioRxiv2024

Developmental programmes drive cellular plasticity, disease progression and therapy resistance in lung adenocarcinoma

BackgroundCellular plasticity, involving loss of lineage determination and emergence of hybrid cell states, plays a pivotal role in non-small cell lung cancer (NSCLC) disease progression and therapy resistance. However, the full spectrum of atypical states generated in human NSCLC and the pathways that regulate them are yet to be fully elucidated. Here we examine the role of developmental programmes, alveogenesis and branching morphogenesis (BM), in regulating phenotypic diversity in NSCLC. MethodsTranscriptomic analysis of epithelial cells isolated from murine lungs at different stages of organogenesis were used to derive gene signatures for developmental programmes. Bulk tissue transcriptomic datasets from human NSCLC and non-neoplastic control samples were used to identify whether developmental programmes were associated with molecular, morphological, and clinical parameters. Single-cell RNA-sequencing was used to identify malignant cell states in human NSCLC (n = 16,621 epithelial cells from 72 samples) and protein level validation of these states was carried out using multiplexed immunohistochemistry (n = 40). ResultsMutually antagonistic regulation of alveogenesis and BM was found to account for a significant proportion of transcriptomic variance in human NSCLC bulk tissue datasets. BM activation was associated with poor overall survival rates in five independent lung adenocarcinoma (LUAD) cohorts (p=2.04e-13); and was significantly prognostic for resistance to tyrosine kinase inhibitors (TKIs; p=0.003) and immune checkpoint blockade (ICBs; p=0.014), in pre-treatment biopsies. Single-cell RNA-sequencing analysis revealed that malignant LUAD cells with loss of alveolar lineage fidelity predominantly acquired inflamed or basal-like cellular states, which were variably persistent in samples from TKI and ICB recurrence. ConclusionsOur results show LUAD tumours undergo reversion from an alveogenic to branching morphogenic phenotype during disease progression, generating inflamed or basal-like cell states that are variably persistent following TKI or ICB treatments. These findings identify prognostic biomarkers for therapy response and underscore the role of different cell states in resistance to multiple treatment modalities.

cancer biology↗

bioRxiv2020

Spatially discrete signalling niches regulate fibroblast heterogeneity in human lung cancer

Fibroblasts are functionally heterogeneous cells, capable of promoting and suppressing tumour progression. Across cancer types, the extent and cause of this phenotypic diversity remains unknown. We used single-cell RNA sequencing and multiplexed immunohistochemistry to examine fibroblast heterogeneity in human lung and non-small cell lung cancer (NSCLC) samples. This identified seven fibroblast subpopulations: including inflammatory fibroblasts and myofibroblasts (representing terminal differentiation states), quiescent fibroblasts, proto-myofibroblasts (x2) and proto-inflammatory fibroblasts (x2). Fibroblast subpopulations were variably distributed throughout tissues but accumulated at discrete niches associated with differentiation status. Bioinformatics analyses suggested TGF-{beta}1 and IL-1 as key regulators of myofibroblastic and inflammatory differentiation respectively. However, in vitro analyses showed that whilst TGF-{beta}1 stimulation in combination with increased tissue tension could induce myofibroblast marker expression, it failed to fully re-capitulate ex-vivo phenotypes. Similarly, IL-1{beta} treatment only induced upregulation of a subset of inflammatory fibroblast marker genes. In silico modelling of ligand-receptor signalling identified additional pathways and cell interactions likely to be involved in fibroblast activation, which can be examined using publicly available R shiny applications (at the following links: myofibroblast activation and inflammatory fibroblast activation). This highlighted a potential role for IL-11 and IL-6 (among other ligands) in myofibroblast and inflammatory fibroblast activation respectively. This analysis provides valuable insight into fibroblast subtypes and differentiation mechanisms in NSCLC.

cancer biology↗