CRi announces study results of imaging and analysis platform for drug and molecular diagnostic development

Dec 2 2009

Cambridge Research & Instrumentation, Inc. (CRi), a leader in biomedical imaging, today announced the results of a study demonstrating for the first time the capability to detect and automatically measure key activity indicators of cancer cell signal transduction pathways in intact tissue.

The study demonstrates the potential use of CRi’s imaging and analysis platform in clinical studies to assess biomarkers for patient selection, drug response, and molecular diagnostic development. Results from a collaborative study between researchers at CRi, the Novartis Institutes for Biomedical Research, and Cell Signaling Technology (CST), was presented during the recent American Association for Cancer Research (AACR) International Conference on Molecular Targets and Cancer Therapeutics in Boston.

Detection and quantitation of multiple protein biomarkers on a single tissue section, and the ability to correlate their changes with clinical outcomes is critical to targeted drug and molecular diagnostic development. Current methods used to detect multiple pathway proteins, such as microarray analysis, lack contextual precision within cells due to destruction of tissue integrity.

In this study, researchers used CRi imaging systems to separate and quantitate overlapping signals in a single tissue section for three critical signaling proteins (phospho-Akt, -ERK, and S6 Ribosomal Protein) overcoming this significant barrier. The systems are able to distinguish the activation of these proteins that are expressed simultaneously from overlapping locations. Background autofluorescence signal was detected and subtracted using CRi’s unique autofluorescence-removal capability.

The study combines the use of multiplexed immunofluorescence staining protocols with CRi’s automated slide analysis system, Vectra^TM. This system uses multispectral imaging to isolate marker signals from one another and from autofluorescence, and CRi’s learn-by-example image analysis package, inForm^TM, for automatically segmenting images and extracting data from cells-of-interest.

inForm’s automated and reliable image analysis capabilities detect tumor cells and segment associated cellular compartments, after training on less than 10% of images. The results of the study support the application of multiplexed immunofluorescence staining protocols with Vectra and inForm in routine clinical studies. Currently, protocols and workflow procedures with these systems are being implemented for evaluation of patient samples.

“The results of this study demonstrate the power of combining CRi’s inForm and Vectra along with high quality antibodies from Cell Signaling Technology, to reveal unique, high-value information from tissue slides,” said Cliff Hoyt, a study author and chief technology officer at CRi. “The results point to a growing role for our optical imaging and analysis technologies in clinical biomarker analysis for developing targeted drug therapies and molecular diagnostics.”