A05 - HPB Interrogating the spatial biology of pancreatic cancer-associated fibroblasts

Abstract Background Cancer-associated fibroblasts (CAFs) are key players in the fibrotic tumour microenvironment (TME) of pancreatic cancer. Recent evidence has demonstrated the existence of multiple CAF subtypes, however there is relatively little evidence validating and corroborating these CAF subtypes in resected human pancreatic cancer. Furthermore, the spatial interactions between CAF subtypes and the epithelial and immune compartments of the pancreatic cancer TME is not well understood. Method We designed and optimised a bespoke 8-plex immunofluorescence panel for the purposes of CAF subtype profiling and elucidation of CAF spatial biology: panCK, FAP, SMA, CTGF, S100A4, IL6, LIF, PDGFR. This was applied to a cohort of n=215 resected pancreatic cancer, well characterised with highly granular clinico-pathological and transcriptomic data through the Australian Pancreatic Cancer Genome Initiative. Spatial analysis was performed with novel computational biology techniques. Results We demonstrate seven CAF subtypes which cluster to form distinct, highly prognostic “enrichment profiles” (EPs). The cold EP represents quiescent CAFs in close proximity to immune cells (multivariate HR 0.45, 95% CI 0.30-0.68, p<0.001), and the fibrotic EP represents activated CAFs in close proximity to epithelial cells (multivariate HR 2.22, 95% CI 1.48-3.35, p<0.001). We also demonstrate the prognostic power of high spatial entropy (loss of tissue architecture, correlating with the fibrotic EP) vs low spatial entropy (preservation of tissue architecture, correlating with the cold EP) (HR 2.22, 95% CI 1.47-3.35, p<0.001). Conclusion We begin to unravel the elusive spatial biology of pancreatic CAFs in a large resected human cohort. We see changes in immune cell infiltrate, modulation of cellular relationships, and greater tissue disorganisation as a result of CAF activation. These features are highly prognostic and we hypothesise they are driven by changes in crosstalk between TME compartments. Current work focuses on application of these techniques to a large resected neoadjuvantly-treated cohort, allowing further interrogation of the notorious fibrotic post-neoadjuvant pancreatic cancer TME. If accepted for presentation we look forward to presenting both cohorts simultaneously.

Authors

Institutions

Publication Details

Journal
British journal of surgery
Published
2024-11-01
DOI
https://doi.org/10.1093/bjs/znae271.005
Primary Topic
Pancreatic and Hepatic Oncology Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A05 - HPB Interrogating the spatial biology of pancreatic cancer-associated fibroblasts

David K. Chang, Stephan B. Dreyer, Adam Bryce, John Le Quesne et al.
British journal of surgery
Pancreatic and Hepatic Oncology Research
article

A05 - HPB Interrogating the spatial biology of pancreatic cancer-associated fibroblasts

David K. Chang, Stephan B. Dreyer, Adam Bryce, John Le Quesne, Fieke E. M. Froeling, Rachel Pennie, Leah Officer-Jones, Silvia Martinelli
article en

Abstract

Abstract Background Cancer-associated fibroblasts (CAFs) are key players in the fibrotic tumour microenvironment (TME) of pancreatic cancer. Recent evidence has demonstrated the existence of multiple CAF subtypes, however there is relatively little evidence validating and corroborating these CAF subtypes in resected human pancreatic cancer. Furthermore, the spatial interactions between CAF subtypes and the epithelial and immune compartments of the pancreatic cancer TME is not well understood. Method We designed and optimised a bespoke 8-plex immunofluorescence panel for the purposes of CAF subtype profiling and elucidation of CAF spatial biology: panCK, FAP, SMA, CTGF, S100A4, IL6, LIF, PDGFR. This was applied to a cohort of n=215 resected pancreatic cancer, well characterised with highly granular clinico-pathological and transcriptomic data through the Australian Pancreatic Cancer Genome Initiative. Spatial analysis was performed with novel computational biology techniques. Results We demonstrate seven CAF subtypes which cluster to form distinct, highly prognostic “enrichment profiles” (EPs). The cold EP represents quiescent CAFs in close proximity to immune cells (multivariate HR 0.45, 95% CI 0.30-0.68, p<0.001), and the fibrotic EP represents activated CAFs in close proximity to epithelial cells (multivariate HR 2.22, 95% CI 1.48-3.35, p<0.001). We also demonstrate the prognostic power of high spatial entropy (loss of tissue architecture, correlating with the fibrotic EP) vs low spatial entropy (preservation of tissue architecture, correlating with the cold EP) (HR 2.22, 95% CI 1.47-3.35, p<0.001). Conclusion We begin to unravel the elusive spatial biology of pancreatic CAFs in a large resected human cohort. We see changes in immune cell infiltrate, modulation of cellular relationships, and greater tissue disorganisation as a result of CAF activation. These features are highly prognostic and we hypothesise they are driven by changes in crosstalk between TME compartments. Current work focuses on application of these techniques to a large resected neoadjuvantly-treated cohort, allowing further interrogation of the notorious fibrotic post-neoadjuvant pancreatic cancer TME. If accepted for presentation we look forward to presenting both cohorts simultaneously.

British journal of surgeryVol. 111(Supplement_9)
Glasgow Royal Infirmary (GB), Cancer Research UK (GB), University of Glasgow (GB)
Good health and well-being
Openalex Percentile: Top 64%
Pancreatic and Hepatic Oncology Research
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.