Abstract
Intratumoral heterogeneity greatly complicates the study of molecular mechanisms driving cancer progression and our ability to predict patient outcomes. Here we have developed an automated high-throughput cell-imaging platform (htCIP) that allows us to extract high-content information about individual cells, including cell morphology, molecular content and local cell density at single-cell resolution. We further develop a comprehensive visually-aided morpho-phenotyping recognition (VAMPIRE) tool to analyze irregular cellular and nuclear shapes in both 2D and 3D microenvironments. VAMPIRE analysis of ~39,000 cells from 13 previously sequenced patient-derived pancreatic cancer samples indicate that metastasized cells present significantly lower heterogeneity than primary tumor cells. We found the same morphological signature for metastasis for a cohort of 10 breast cancer cell lines. We further decipher the relative contributions to heterogeneity from cell cycle, cell-cell contact, cell stochasticity and heritable morphological variations.
Highlights
Originated from either the primary site in the pancreas or from metastatic sites, mainly in the liver
We developed a high-throughput cell imaging platform that allowed us to extract high-content information for individual cells, including cellular and nuclear morphology, molecular content, and local multi-cellular organization
Recent studies utilizing a similar strategy of principal components analysis and unsupervised classification to identify discrete cell shapes for RNAi screen found that gene expression alterations can mediate morpho-phenotypes of cells[44,48,49]
Summary
We verified that the use of this low-magnification objective had sufficient optical resolution for measuring cellular and nuclear features by comparing results obtained using low- and high-magnification lenses (Fig. S1C). We used this assay to identify a potential morphological signature of metastasis in pancreatic ductal adenocarcinoma (PDAC) using nine previously sequenced[8], patient-derived, primary tumor (PT; five lines) and liver metastatic (LM; four lines) cell lines. Selected subsets of individual cell traces did not reveal overt morphological differences between PT and LM cells, presumably due to the irregularity of cell shapes (Fig. 1B). Morphological features, such as spreading area, shape factor, and aspect ratio, have been widely used to describe cell shape, yet, these features could not reflect the extent of cell shape variations, since even a small subset of cells displaying an extremely narrow range of values of these conventional shape descriptors appeared radically different from each other (Fig. 1C,D)
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