Affiliations: Section of Cancer Genomics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA | Institute for Pathology, Paracelsus Medical University, Salzburg, Austria | MetaSystems, Waltham, MA, USA
Note: [] Corresponding author: Thomas Ried, Section of Cancer Genomics, National Institutes of Health, Building 50, Room 1408, 50 South Drive, Bethesda, MD 20892, USA. Tel.: +1 301 594 3118; Fax: +1 301 402 1204; E-mail: riedt@mail.nih.gov.
Abstract: Background: The simultaneous detection of protein expression and gene copy number changes in patient samples, like paraffin-embedded tissue sections, is challenging since the procedures of immunohistochemistry (IHC) and Fluorescence in situ Hybridization (FISH) negatively influence each other which often results in suboptimal staining. Therefore, we developed a novel automated algorithm based on relocation which allows subsequent detection of protein content and gene copy number changes within the same cell. Methods: Paraffin-embedded tissue sections of colorectal cancers were stained for CD133 expression. IHC images were acquired and image coordinates recorded. Slides were subsequently hybridized with fluorescently labeled DNA probes. FISH images were taken at the previously recorded positions allowing for direct comparison of protein expression and gene copy number signals within the same cells/tissue areas. Relocation, acquisition of the IHC and FISH images, and enumeration of FISH signals in the immunophenotyped tumour areas were done in an automated fashion. Results: Automated FISH analysis was performed on 13 different colon cancer samples that had been stained for CD133; each sample was scored for MYC, ZNF217 and Chromosome 6 in CD133 positive and negative glands. From the 13 cases four (31%) showed amplification for the MYC oncogene and seven of 13 (54%) cases were amplified for ZNF217. There was no significant difference between CD133 positive tumour and CD133 negative tumour cells. Conclusion: The technique and algorithm presented here enables an easy and reproducible combination of IHC and FISH based on a novel automated algorithm using relocation and automated spot counting.
