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Power-law growth models explain incidences and sizes of pancreatic cancer precursor lesions and confirm spatial genomic findings.
- Source :
-
Science advances [Sci Adv] 2024 Jul 26; Vol. 10 (30), pp. eado5103. Date of Electronic Publication: 2024 Jul 26. - Publication Year :
- 2024
-
Abstract
- Pancreatic ductal adenocarcinoma is a rare but lethal cancer. Recent evidence suggests that pancreatic intraepithelial neoplasia (PanIN), a microscopic precursor lesion that gives rise to pancreatic cancer, is larger and more prevalent than previously believed. Better understanding of the growth-law dynamics of PanINs may improve our ability to understand how a miniscule fraction makes the transition to invasive cancer. Here, using three-dimensional tissue mapping, we analyzed >1000 PanINs and found that lesion size is distributed according to a power law. Our data suggest that in bulk, PanIN size can be predicted by general growth behavior without consideration for the heterogeneity of the pancreatic microenvironment or an individual's age, history, or lifestyle. Our models suggest that intraductal spread and fusing of lesions drive our observed size distribution. This analysis lays the groundwork for future mathematical modeling efforts integrating PanIN incidence, morphology, and molecular features to understand tumorigenesis and demonstrates the utility of combining experimental measurement with dynamic modeling in understanding tumorigenesis.
- Subjects :
- Humans
Incidence
Genomics methods
Carcinoma in Situ genetics
Carcinoma in Situ pathology
Carcinoma in Situ epidemiology
Carcinoma, Pancreatic Ductal genetics
Carcinoma, Pancreatic Ductal pathology
Models, Theoretical
Pancreatic Neoplasms genetics
Pancreatic Neoplasms pathology
Pancreatic Neoplasms epidemiology
Precancerous Conditions genetics
Precancerous Conditions pathology
Subjects
Details
- Language :
- English
- ISSN :
- 2375-2548
- Volume :
- 10
- Issue :
- 30
- Database :
- MEDLINE
- Journal :
- Science advances
- Publication Type :
- Academic Journal
- Accession number :
- 39058773
- Full Text :
- https://doi.org/10.1126/sciadv.ado5103