Cancer-associated fibroblasts (CAFs) play a major role in the progression and drug resistance of pancreatic cancer. Recent studies suggest that CAFs exhibit functional heterogeneity and distinct transcriptomic signatures in pancreatic cancer. Pancreatic fibroblasts also form an integral component in pancreatic diseases such as chronic pancreatitis named disease-associated fibroblasts (DAFs). However, intra-tumoral heterogeneity of CAFs in pancreatic cancer patients and their pivotal role in cancer-related mechanisms have not been fully elucidated. Further, it has not been elucidated whether CAF subtypes identified in pancreatic cancer also exist in chronic pancreatitis. In this study, we used primary isolated fibroblasts from pancreatic cancer and chronic pancreatitis patients using the outgrowth method. Single-cell RNA sequencing (scRNA-seq) was performed, and bioinformatics analysis identified highly variable genes, including factors associated with overall survival of pancreatic cancer patients. The majority of highly variable genes are involved in the cell cycle. Instead of previously classified myofibroblastic (myCAFs), inflammatory (iCAFs), and antigen-presenting (ap) CAFs, we identified a myCAFs-like subtype in all cases. Most interestingly, after cell cycle regression, we observed 135 highly variable genes commonly identified in chronic pancreatitis and pancreatic cancer patients. This study is the first to conduct scRNAseq and bioinformatics analyses to compare CAFs/DAFs from both chronic pancreatitis and pancreatic cancer patients. Further studies are required to select and identify stromal factors in DAFs from chronic pancreatitis cases, which are commonly expressed also in CAFs potentially contributing to pancreatic cancer development.
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http://dx.doi.org/10.3390/cells11162583 | DOI Listing |
Ann Surg Oncol
January 2025
Hepato-Pancreato-Biliary Service, Department of Surgery, Memorial Sloan Kettering Cancer Center, New York, NY, USA.
Discov Oncol
January 2025
Department of Laboratory, the Second Hospital of Shanxi Medical University, No. 382, Wuyi Road, Taiyuan, 030001, Shanxi, People's Republic of China.
Background: Pancreatic cancer (PAC) has a complex tumor immune microenvironment, and currently, there is a lack of accurate personalized treatment. Establishing a novel consensus machine learning driven signature (CMLS) that offers a unique predictive model and possible treatment targets for this condition was the goal of this study.
Methods: This study integrated multiple omics data of PAC patients, applied ten clustering techniques and ten machine learning approaches to construct molecular subtypes for PAC, and created a new CMLS.
mSphere
January 2025
State Key Laboratory of Systems Medicine for Cancer, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Ningning Liu works in the field of fungal infection and cancer progression, with a particular focus on the mechanism of host-pathogen interaction. In this mSphere of influence article, he reflects on how papers entitled "The fungal mycobiome promotes pancreatic oncogenesis via activation of MBL," by B. Aykut, S.
View Article and Find Full Text PDFJ Hepatobiliary Pancreat Sci
January 2025
Department of Gastroenterology, Shizuoka General Hospital, Shizuoka, Japan.
Cureus
January 2025
Hepato-Pancreato-Biliary (HPB) Unit, University Hospital Southampton NHS Foundation Trust, Southampton, GBR.
Background The relationship between physical activity and incident pancreatic cancer is poorly defined, and the evidence to date is inconsistent, largely due to small sample sizes and insufficient incident outcomes. Using the UK Biobank cohort dataset, the association between physical activity levels at recruitment and incident pancreatic ductal adenocarcinoma (PDAC) at follow-up was analysed. Method Physical activity, the key exposure, was quantified using Metabolic Equivalent Task (MET) values and categorised into walking, moderate, and vigorous activity.
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