Hypoxia as a driver of morphological and molecular microevolution of pancreatic ductal adenocarcinoma cells and spheroids - replication data

The dataset was generated to investigate the phenotypic evolution and tumorigenic potential of pancreatic ductal adenocarcinoma (PDAC) cells under normoxic and hypoxic conditions. By integrating machine learning-assisted image analysis, the study aimed to quantify morphometric changes in 2D cultures and assess molecular and cellular adaptations, with a focus on epithelial-mesenchymal transition (EMT) and tumor microevolution.
The dataset includes: (A) quantitative morphometric data of 2D and 3D cells in normoxia and hypoxia (e.g., spheroid size, shape, density, and circularity); (B) molecular marker expression levels associated with hypoxia response (VHL), fibrosis (Col1, elastin), and EMT (vimentin, β-catenin, N-cadherin); (C) kinetics of tumor in murine model highlighting their tumorigenic potential.
The dataset provides comprehensive insights into hypoxia-driven adaptations in PDAC cells, covering: (A) cellular and spheroid-level responses to oxygen deprivation; (B) lineage-specific differences in hypoxia adaptation between PAN_02 and PANC-1 cells; (C) machine learning-assisted multi-parametric quantification of PDAC plasticity and microevolution.