This story originally ran on Dec. 1.
Cambridge Research & Instrumentation announced the results today of a study it said demonstrates for the first time the ability to "detect and automatically measure key activity indicators of cancer cell signal transduction pathways in intact tissue."
According to the Woburn, Mass.-based firm, the study suggests CRi's imaging and analysis platform may have use in clinical studies for the assessment of protein biomarkers for patient selection, drug response, and molecular diagnostic development.
The study is part of larger preclinical study and there are no plans presently to publish the results in a journal, a CRi spokeswoman said.
The study was first unveiled at the recent American Association for Cancer Research International Conference on Molecular Targets and Cancer Therapeutics. In a poster, CRi said that a common goal in drug research is to identify correlations between signaling pathway activity in intact tissue and clinical outcomes. "Correlations support target validation, trial design, patient selection, response assessment, and, if trials are
successful, the diagnostic component of theranostics," according to the poster.
However, current technologies, such as immunohistochemistry and microarrays, "provide data that are averages from volumes of tissue" and include cells that are not of interest. "These methods blur out key proteomic information that resides at the cellular level, relating to the signaling of individual cells," the researchers said.
CRi's imaging systems, however, allow researchers to separate and quantitate overlapping signals, allowing them to overcome this hurdle. In their study, use of the imaging systems resulted in the separation and measurement in a single tissue section of three key signaling proteins, phosphor-Akt, -ERK, and S6 ribosomal protein.
CRi's autofluorescence-removal capability detected autofluorescence signal and subtracted it, allowing activation of the three proteins that are expressed simultaneously from overlapping locations to be distinguished, the company said in a statement.
In the study, researchers from CRi, the Novartis Institutes for Biomedical Research, and Cell Signaling Technology combined multiplexed immunofluorescence staining protocols with CRi's automated slide analysis system, Vectra, which uses multispectral imaging to isolate biomarker signals from each other and from autofluorescence. CRi's image analysis package, inForm, for automatic segmenting of images and extraction of data from cells of interest, was also used.
According to CRi, the study "supports the application of multiplexed immunofluorescence staining protocols with Vectra and inForm in routine clinical studies."
In the company's statement, Cliff Hoyt, chief technology officer at CRi and an author of the study, said that 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."
CRi and its collaborators are presently implementing protocols and workflow procedures for real-time evaluation of patients in clinical trials.