Biology subjects

Grant, R. C.

Publications and source records attributed to Grant, R. C..

3 recordsLinked to original sources

bioRxiv2025

Consensus molecular subtypes define distinct evolutionary trajectories of biliary tract cancers

Introduction Biliary tract cancer (BTC) comprises a family of rare malignancies subclassified by anatomy and pathology. However, this scheme may obscure shared biology and limit patient stratification. Objectives We tested whether BTC heterogeneity can be explained by coherent latent axes and evaluated the potential to unify diverse clinical and genomic factors under a tractable biological framework Methods We performed whole-genome and transcriptome sequencing of 180 tumors enriched for tumor cells by laser capture microdissection to identify shared programs in BTC. Results Network integration across transcriptomic classes identified two consensus cancer subtypes (CCS). CCS segregated with anatomical location of primary tumor and gene expression marker analyses suggest subtypes reflect tumor cell of origin differences. CCS displayed strikingly divergent molecular landscapes, explaining more variance than anatomical location of primary tumor. CCS-B tumors were mutationally loaded with clock-like and APOBEC signatures and extrachromosomal DNA, whereas CCS-A tumors were characterized by chromosome-arm deletions. Conclusion Our approach showed that harnessing the genomic and transcriptomic diversity of BTC uncovers novel biology and improves stratification.

cancer biology↗

bioRxiv2025

The subclonal footprint of pervasive early dissemination in pancreatic cancer

Early is too late describes a central problem in pancreatic cancer referring to its relentless drive to disseminate and highlights the need to understand how this disease spreads so rapidly. In this study, we profiled 1,013 samples from 277 donors, including tissue whole genome and RNA sequencing combined with plasma whole genome sequencing at [~]25x. Strikingly, local primary tumours, including some reaching 7cm, were found to shed little to no circulating tumour DNA (ctDNA). Instead, metastatic burden in the liver but not extrahepatic sites, was a main physiologic determinant of ctDNA levels. Whole-genome duplication (WGD), high cell cycle activity, and non-glandular differentiation emerged as tumour-intrinsic features related to increased ctDNA shedding. By contrast, decreased shedding was related to extrinsic features including a reactive microenvironment and unexpectedly, humoral immunity. Analysis of tumour clonal architecture showed that in patients with low ctDNA levels, the signal disproportionately originated from subclones and this signal persisted even when the primary tumour was removed. Disseminated subclones were a significant source of ctDNA in early-stage patients. Longitudinal analysis of patients revealed that subclones seeded metastases and shed ctDNA in the blood years before detection. This first report of paired tissue and plasma whole genomes in pancreatic cancer is a unique resource and has broad implications for disease surveillance, treatment monitoring, and early detection in this disease.

cancer biology↗

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↗