Abstract C010: Single-cell profiling unleashes KRAS-driven redrafting of the tumor microenvironment before cancer onset

Abstract Pancreatic cancer is a highly lethal and aggressive disease, commonly characterized by a unique tumor microenvironment, where mutant KRAS signaling plays a pivotal role in its pathophysiology. To deepen our understanding of KRAS-dependent signaling in earliest tumor development, oncogenic KRAS (KRASG12D) expression was induced in human stem cell-derived pancreatic ductal-like organoids (PDLOs), followed by time-resolved single-cell RNA and bulk ATAC sequencing. This unique precancerous state model facilitated a comprehensive characterization of early oncogenic events at cellular resolution. Furthermore, a machine learning approach was applied to accurately predict KRAS-dependent cell identities. Within seven days, mutated KRAS triggers distinct gene signature programs related to extracellular matrix remodeling and inflammation. Although derived from dysplastic yet non-cancerous states, these gene signatures negatively correlated with overall survival in PDAC (pancreatic ductal adenocarcinoma) patients. The KRAS-dependent signatures retrieved with the machine learning approach allowed the grouping of 24 published PDAC cases, showing differences in niche composition and communication patterns. Various co-culture systems demonstrated that KRASG12D-expressing PDLOs could activate pancreatic stellate cells, inducing a cancer- associated fibroblast (CAF)-like state. Simultaneously, these KRAS-activated organoids were protected from T cell infiltration in vitro. Furthermore, in silico approaches were employed to reconstruct a virtual pancreatic cancer space, demonstrating that our PDLOs transcriptionally bridge healthy and malignant ductal states. This also revealed potential KRAS-driven pathways mediating CAF activation and T cell shielding preceding cancer onset. In summary, our human PDLO model enables us to explore the transition from normal to cancerous states, addressing gaps in our understanding of tumor development and tumor niche preparation. Citation Format: Chantal Allgoewer, Markus Breunig, Meike Hohwieler, Medhanie Mulaw, Alexander Kleger. Single-cell profiling unleashes KRAS-driven redrafting of the tumor microenvironment before cancer onset [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C010.

Authors

Institutions

Publication Details

Journal
Cancer Research
Published
2024-09-15
DOI
https://doi.org/10.1158/1538-7445.pancreatic24-c010
Primary Topic
Cell Adhesion Molecules Research
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract C010: Single-cell profiling unleashes KRAS-driven redrafting of the tumor microenvironment before cancer onset

Markus Breunig, Medhanie Mulaw, Meike Hohwieler, Alexander Kleger et al.
Cancer Research
Cell Adhesion Molecules Research
article

Abstract C010: Single-cell profiling unleashes KRAS-driven redrafting of the tumor microenvironment before cancer onset

Markus Breunig, Medhanie Mulaw, Meike Hohwieler, Alexander Kleger, Chantal Allgoewer
article en

Abstract

Abstract Pancreatic cancer is a highly lethal and aggressive disease, commonly characterized by a unique tumor microenvironment, where mutant KRAS signaling plays a pivotal role in its pathophysiology. To deepen our understanding of KRAS-dependent signaling in earliest tumor development, oncogenic KRAS (KRASG12D) expression was induced in human stem cell-derived pancreatic ductal-like organoids (PDLOs), followed by time-resolved single-cell RNA and bulk ATAC sequencing. This unique precancerous state model facilitated a comprehensive characterization of early oncogenic events at cellular resolution. Furthermore, a machine learning approach was applied to accurately predict KRAS-dependent cell identities. Within seven days, mutated KRAS triggers distinct gene signature programs related to extracellular matrix remodeling and inflammation. Although derived from dysplastic yet non-cancerous states, these gene signatures negatively correlated with overall survival in PDAC (pancreatic ductal adenocarcinoma) patients. The KRAS-dependent signatures retrieved with the machine learning approach allowed the grouping of 24 published PDAC cases, showing differences in niche composition and communication patterns. Various co-culture systems demonstrated that KRASG12D-expressing PDLOs could activate pancreatic stellate cells, inducing a cancer- associated fibroblast (CAF)-like state. Simultaneously, these KRAS-activated organoids were protected from T cell infiltration in vitro. Furthermore, in silico approaches were employed to reconstruct a virtual pancreatic cancer space, demonstrating that our PDLOs transcriptionally bridge healthy and malignant ductal states. This also revealed potential KRAS-driven pathways mediating CAF activation and T cell shielding preceding cancer onset. In summary, our human PDLO model enables us to explore the transition from normal to cancerous states, addressing gaps in our understanding of tumor development and tumor niche preparation. Citation Format: Chantal Allgoewer, Markus Breunig, Meike Hohwieler, Medhanie Mulaw, Alexander Kleger. Single-cell profiling unleashes KRAS-driven redrafting of the tumor microenvironment before cancer onset [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pancreatic Cancer Research; 2024 Sep 15-18; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl_2):Abstract nr C010.

Cancer ResearchVol. 84(17_Supplement_2)
Universität Ulm (DE), University Hospital Ulm (DE)
Openalex Percentile: Top 77%
Cell Adhesion Molecules 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.