Biology subjects

Gorman, J. L.

Publications and source records attributed to Gorman, J. L..

4 recordsLinked to original sources

bioRxiv2026

Multimodal cell communication networks nominate immunotherapies for RCC subgroups with discrete T cell recruitment or expansion

Renal cell carcinoma (RCC) is amongst the most immune-infiltrated solid tumours, but only a small subset of patients achieves durable response to immune checkpoint blockade therapy. Efforts to characterize the immune microenvironment and molecular regulators responsible for treatment responses have explored numerous facets of disease biology using compartmentalized genomics, transcriptomics, and proteomics datasets, yielding many important yet context and data specific insights. Therefore, to provide a more integrated approach to informing future precision medicine strategies, we combined the complementary strengths of multiple technological platforms to profile multi-regional, spatially annotated surgical biospecimens from 65 RCC patients by single-cell RNA sequencing with paired TCR and BCR repertoire analysis, imaging mass cytometry, suspension mass cytometry, spatial transcriptomics and deconvolved bulk RNA sequencing. With this resource dataset, we explored patient subgroups and precision immunotherapy strategies using an integrated analysis of transcripts and proteins across single cell and spatial modalities. Proximal cell interactions and distinct receptor-ligand pairings identified 7 recurrent cellular communication networks. Robustly mapping reproducible gene signatures across technologies and to a variety of publicly available datasets, we show these highly refined immune subgroups stratify patients with tumour microenvironments associated with prognosis and immunotherapy response. Notably, this reveals that highly infiltrated environments with the potential for immunotherapy response may in fact comprise two distinct communication networks, with differing modes of T cell clonal expansion and immune evasion axes associated with T cell exhaustion or myeloid and NK reprogramming, which could inform targeted combination therapeutic strategies to improve outcomes. Overall, we provide a high-dimensional multi-modal resource dataset that enables cross-platform integration, links stages of T cell clonal expansion with enabling or suppressive RCC immune cell communication networks and nominates rational strategies for combinatorial precision immunotherapy. (Funded by University Health Network, Toronto; REMEDY ClinicalTrials.gov number, NCT04005183.)

cancer biology↗

bioRxiv2025

Rakaia: interactive discovery of spatial biology at scale

Spatial biology data throughput currently outpaces interpretable analysis, limiting large-scale discovery and translation. Here we present Rakaia, a browser-based platform for multiplexed imaging and spatial transcriptomics, empowering code-free interactive exploration and evaluation. Rakaia enables visualization, annotation, and feature-based querying with prioritization across thousands of images. We use Rakaia to identify cell types of interest in >200 highly multiplexed images from non-malignant human breast tissue. Rakaia is available at: https://rakaia.io/

bioinformatics↗

bioRxiv2025

Integrated spatial proteomics of human PDAC uncovers an expanded tumour-immune-stroma spectrum with genomic associations

Distinctively, pancreatic ductal adenocarcinoma (PDAC) consists of sparse tumour lesions intertwined with extensive desmoplastic stroma. The complexity of tumour-microenvironment interactions within this desmoplasia poses a challenge for accurate tumour profiling and patient stratification, and characterizes a profoundly chemoresistant tumour. Here we mapped the spatial relationships between tumour, stroma, and immune cell compartments delineating tumour and microenvironment types that expand the classical to basal spectrum of human PDAC. We used imaging mass cytometry to profile the in situ multi-cellular organization of 81 cell types in resected cases with paired whole genome sequencing. Cell types, functions, and pathway activation were distributed as highly reproducible environments in discrete locations throughout these tumours, which we deep-profiled using laser-capture mass spectrometry. We show that the connections between tumour phenotypes, vascularization, immune response, and stromal biophysical state are reinforced by genomic aberrations, altered by treatment, and associated with patient outcome. Predictive machine-learning models showed that spatial single cell data outperformed genomic or clinical features but integrated multi-omics models provide the best prediction of patient survival with compressed models requiring only 10 non-redundant robust molecular measures associated with the phenotypic spectrum of PDAC. Together, these findings define a phenotypic and molecular framework of PDAC that captures tumour-microenvironment co-dependencies and offers a refined basis for patient stratification and therapeutic targeting.

cancer biology↗

bioRxiv2019

Development of a drug repressible β-catenin mutant mouse to examine effect of activated β-catenin signaling on long-term maintenance of mammary tumor growth

Stabilized {beta}-catenin expression is a well described initiator of mammary tumorigenesis in the mouse and elevated nuclear expression of this protein has been observed in human triple-negative tumor samples. However, the importance of stabilized {beta}-catenin to continued tumor growth after initiation, and in the context of other driver mutations, has yet to be elucidated. To ascertain the importance of stabilized {beta}-catenin after tumor initiation, we generated a novel transgenic mouse model, utilizing the tet-off system, to control expression of a stabilized mutant of {beta}-catenin. Pups from early litters carrying one allele of regulatable stabilized {beta}-catenin at the Rosa26 locus, but not targeted by Cre, were smaller in size compared with wildtype littermates and also developed skin lesions, requiring euthanasia. Maintenance of breeding cages on doxycycline chow allowed for healthy transgenic pups to survive past 3 weeks of age and 6 animal cohorts were established. We used two different mammary Cre strains, WAP-Cre and MMTV-NLST-Cre, crossed with regulatable, stabilized {beta}-catenin (bcatFL) animals, as well as animals expressing mutated p53-R270H. While mammary tumors developed in animals expressing Cre-targeted regulatable bcatFL, the penetrance and growth kinetics were lower than observed with other mammary mouse models expressing stabilized {beta}-catenin. Since fewer animals developed tumors, we focused analysis on the effect of turning off stabilized {beta}-catenin expression following tumor initiation. In the animals examined, a delay in tumor growth, but not regression, was observed in animals expressing Cretargeted bcatFL as well as those expressing both bcatFL and p53-R270H. These results indicate that in a less aggressive {beta}-catenin model, additional mutations likely provide independence from the initiating event.

cancer biology↗