Abstract
BackgroundThree-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. In this study, we present an automated image analysis protocol for detailed morphological protein marker profiling of tumoroid cross section images.MethodsHistologic cross sections of breast tumoroids developed in co-culture suspensions of breast cancer cell lines, stained for E-cadherin and progesterone receptor, were digitized and pixels in these images were classified into five categories using k-means clustering. Automated segmentation was used to identify image regions composed of cells expressing a given biomarker. Synthesized images were created to check the accuracy of the image processing system.ResultsAccuracy of automated segmentation was over 95% in identifying regions of interest in synthesized images. Image analysis of adjacent histology slides stained, respectively, for Ecad and PR, accurately predicted regions of different cell phenotypes. Image analysis of tumoroid cross sections from different tumoroids obtained under the same co-culture conditions indicated the variation of cellular composition from one tumoroid to another. Variations in the compositions of cross sections obtained from the same tumoroid were established by parallel analysis of Ecad and PR-stained cross section images.ConclusionProposed image analysis methods offer standardized high throughput profiling of molecular anatomy of tumoroids based on both membrane and nuclei markers that is suitable to rapid large scale investigations of anti-cancer compounds for drug development.
Highlights
Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo
We have studied the anatomy of co-cultures of poorly invasive and highly invasive breast cancer cell lines using digitized cross section images immunohistochemically stained for E-cadherin (Ecad) and progesterone receptor (PR) by automated image analysis methods
The automated methods for image processing were first tested on synthetic images computationally simulating the biomarker decorated images of the tumoroid cross sections (Figure 2)
Summary
Three-dimensional in vitro culture of cancer cells are used to predict the effects of prospective anti-cancer drugs in vivo. Cell lines derived from cancer tissues are used extensively to model in vivo drug response as they can be transferred, reproduced, and analyzed in standardized assays [1,2]. Effects of therapeutic compounds have been studied widely on cell lines isolated from breast, skin, colon, prostate, lung, brain, and the bone marrow [3,4,5,6,7,8,9]. The limitations of two-dimensional assays of cancer cell cultures in representing in vivo tissue conditions may be due to the lack of cell to cell and cell to extracellular matrix interactions [11]. Three dimensional cell cultures promote cell to cell interaction in a more realistic (page number not for citation purposes)
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