Up to 65 cellular events on a single slide
ALISO VIEJO, Calif.—Clarient, a GE Healthcare company, has introduced MultiOmyx technology, which company officials describe as the first lab-developed test to assess multiple proteins at single-cell level. Designed to aid in the pathologist's diagnosis of certain difficult lymphoma cases by doing more with less tissue, the technology may provide a more complete picture of a patient's cancer and help explain tumor behavior and growth.
"As pathologists, we have to establish a diagnosis with a single piece of tissue," explains Dr. Steve Bloom, Clarient's chief medical officer. "As we look for more specific cancers and subtypes, we have to answer more questions with less tissue, sometimes as little as 5 microns."
Sometimes the piece of tissue is too small to address all of the therapy questions, according to Bloom. There have to be many stains on the same piece of tissue, and not every slice is adept at giving the right answers. He makes the analogy of a cherry pie where some slices have the cherries and others only the sauce.
"We're looking for specific cells," he says. "Sometimes we exhaust the tissue trying to answer all of the questions, but we still want to keep residual tissue for future research or to go back and look at it again."
He adds, "MultiOmyx addresses the right cells and allows for retention for the future. Its advantages include cost savings from not having to do multiple biopsies, preventing the discomfort of doing additional biopsies, preserving residual tissue and obtaining more consistent results."
The technology was created out of the GE Global Research Center to do multiple stains on a single slide. When GE acquired Clarient, Bloom was involved in the technology transfer, taking a fairly complex procedure and enabling pathologists to do it.
"We want to allow precision medicine to become even more precise," Bloom says. "Eventually, we want to be able to profile what is unique about each person's tumor and customize therapy specific to that person's cancer."
Additionally, he says clinicians want to understand all of the interactions on one cell—how all complex proteins interact with each other. After analyzing the proteins, clinicians need bioinformatics software to "dissect complex interactions and turn them into insights, to put them into a profile to tell doctors how to best treat patients," Bloom explains.
MultiOmyx uses fluorescence to provide quantitative analysis of antibodies and allows for as many as 65 proteins to be examined on a single tissue sample. It creates a "digital map" of the tumor, giving each cell an "address" and enabling a clear graphic representation of protein expression. Matching this map to known biosignatures gives researchers a more accurate representation of the exact characteristics of the tumor and may provide clinicians with a clearer view to aid the diagnosis. Additionally, it enables them to identify patterns in the tissue by analyzing each cell and biomarker individually, or as a cluster, and thus get a level of understanding of the biological process that could not be achieved via traditional methods, according to the company.
The Hodgkin Lymphoma (HL) Profile by MultiOmyx helps to assess nine unique antibodies on a single formalin-fixed paraffin-embedded tissue section to aid in differential diagnosis of Classical HL. In clinical validation, this single-slide assay demonstrated high levels of accuracy, diagnostic reproducibility and repeatability and high sensitivity of all immunofluorescent stains in comparison to traditional immunohistochemistry performed on the same samples. The correlation study identified unique cases where MultiOmyx demonstrated improved performance.
A clinical paper written by a team of scientists from GE Global Research and published in Proceedings of the National Academy of Sciences (PNAS) described the relevance of the MultiOmyx technology. The paper detailed the different ways GE is using image data to visualize cancer and the relationship between different biomarkers and the tumor environment and suggests that the technology could be broadly applicable to problems in basic biological research, drug discovery and development and companion and clinical diagnostics.
"Now we can look at huge databases of raw data and ask complex questions," Bloom says. "It's an entire facet of analytical capability that didn't exist before."