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Abstract

A quantitative bio-imaging platform is developed for analysis of human cancer dissemination in a short-term vertebrate xenotransplantation assay. Six days after implantation of cancer cells in zebrafish embryos, automated imaging in 96 well plates coupled to image analysis algorithms quantifies spreading throughout the host. Findings in this model correlate with behavior in long-term rodent xenograft models for panels of poorly- versus highly malignant cell lines derived from breast, colorectal, and prostate cancer. In addition, cancer cells with scattered mesenchymal characteristics show higher dissemination capacity than cell types with epithelial appearance. Moreover, RNA interference establishes the metastasis-suppressor role for E-cadherin in this model. This automated quantitative whole animal bio-imaging assay can serve as a first-line in vivo screening step in the anti-cancer drug target discovery pipeline.

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Citation: Ghotra VPS, He S, de Bont H, van der Ent W, Spaink HP, et al. (2012) Automated Whole Animal Bio-Imaging Assay for Human Cancer Dissemination. PLoS ONE 7(2): e31281. doi:10.1371/journal.pone.0031281

Editor: Laurent Rénia, Agency for Science, Technology and Research - Singapore Immunology Network, Singapore

Received: August 2, 2011; Accepted: January 4, 2012; Published: February 8, 2012

Copyright: © 2012 Ghotra et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Funding: This work was supported by the Dutch Cancer Society (UL-2010-4670) and EU FP7 ZF Cancer project (HEALTH-F2-2008-201439). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Traditional anti-cancer drug screens are performed using cell lines grown in 2D culture or using in vitro protein binding assays. Cancer progression, however, is a complex process of dynamic interactions between cancer cells and the organism that involves genetic alterations leading to deregulated survival and proliferation, angiogenesis, invasion, and metastasis [1]. Ideally, genes that play a role in this process are identified by in vivo ablation or silencing. Although genetic mouse models for cancer and human tumor cell xenotransplantation models in rodents remain essential, such systems are costly, slow, and less amenable to high-throughput assays for cancer drug target discovery. There is a clear need to develop fast, semi-automated in vivo systems for medium to high-throughput screening applications in preclinical target discovery and lead compound identification.

In this respect, zebrafish (ZF) offer a number of unique advantages for investigating the mechanisms that drive cancer formation and progression. ZF are vertebrates that can be raised in large numbers in a cost-effective manner. An almost complete genome sequence reveals that most cancer genes and tumor suppressor genes are highly conserved between ZF and humans (http://www.ncbi.nlm.nih.gov/genome/guide/zebrafish) and ZF form spontaneous tumors with similar histopathological and gene expression profiles as human tumors [2]–[4]. Importantly, xenotransplantation with human cancer cells is possible [5], [6]. ZF embryos that are used for this purpose lack an adaptive immune system, which increases the success of xenotransplantation while they provide a microenvironment where human tumor cells proliferate, migrate, form tumor masses, and stimulate angiogenesis [5]–[8].

ZF embryos are particularly useful for semi high-throughput microscopic analysis platforms as they are translucent, and can be maintained in 96 well plates. The optical transparency of ZF offers exciting research opportunities allowing visualization of the metastatic process at high resolution [8], [9]. Recent findings indicate that a wide range of pharmaceutically active compounds illicit physiological responses in ZF embryos and inhibit disease development similar to effects in mammalian systems [10]–[12]. These findings underscore the potential for a ZF embryo xenotransplantation model to be used in the anti-cancer drug discovery process. However, at this time, using ZF to screen for cancer relevant drug - and gene targets is limited by the lack of comprehensive automated bioassays. Here, we applied automated imaging and image analysis procedures to a ZF xenotransplantation model to develop the first semi-automated whole-organism quantitative bio-imaging assay for analyzing cancer dissemination in a vertebrate.

Results

We developed a noninvasive, quantitative whole animal bioimaging method for dissemination of xenotransplanted human cancer cells in ZF embryos in 96-well format. All the steps are briefly outlined in Figure 1.

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Figure 1. Schematic overview of the procedure.

(A) Yolk sac implantation of CM-DiI labeled tumor cells into Tg (Fli:EGFP) ZF embryos 2 days post-fertilization. (B) Formaldehyde fixed 6 dpi embryos arrayed in 96 well plates. (C) Automated image acquisition using CLSM platform equipped with movable stage captures multiple Z stacks per embryo using 488 and 561 nm laser lines. (D and E) Automated creation of extended depth composite images. (F) Multiple extended depth images depicting embryos lying in different lateral orientations. (G) Automated uniform reorientation of images. (H) Scatter plot representing tumor foci burden in multiple embryos belonging to one experimental condition.

doi:10.1371/journal.pone.0031281.g001

Automated image capturing and pre-processing

CMDiI-labeled tumor cells were injected in the yolk sac of 2-day-old fli-EGFP embryos [13] and fixed 6 days post-implantation (dpi) (Figure 1A). Fixed embryos were arrayed in 96 well glass bottom plates for automated imaging (<5 minutes per plate) (Figure 1B). Epi-fluorescence microscopy failed to detect disseminated tumor cells due to excessive background from the primary tumor mass. Therefore, using a confocal laser-scanning microscope (CLSM) combined with an automated stage; multiple z stacks per embryo were captured for each well in a fully automated procedure (Figure 1C, 1D and Video S1). Confocal images were automatically converted into extended depth composite images (Figure 1E) that were rearranged to a uniform orientation (Figure 1F and G) to allow for automated quantitative image analysis (Figure 1H).

Automated multiparametric analysis of cancer cell dissemination

Having established conditions for automated imaging and image pre-processing of tumor cell implanted ZF embryos; we subsequently developed an algorithm for automated analysis of tumor foci burden in the post-processed ZF images. For this, Image-Pro based software was developed, which performed essentially three major functions (see materials and methods section for detailed information on the macro's). 1) Reorientation of the images (Figure 2): all embryos were automatically reoriented to a horizontal orientation, with the head towards the right and the yolk sac towards the bottom. 2) Determination of the injection position of labeled tumor cells (Figure 3A–C): the injection position was calculated from the images based on the segmented GFP channel (and confirmed by visual inspection using the red channel). 3) Detection of tumor foci (Figure 3D and E): The red channel was segmented using an intensity threshold and minimum and maximum area filters

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