Cancer claims more than half a million lives each year in the United States alone. Understanding the biology of cancer and developing treatment options is an ongoing challenge due to lack of a whole picture of cancerous cell growth and survival mechanisms. In recent years, immunotherapy, a type of therapy that is administrated in order to stimulate or suppress the immune system to help the body fight cancer, has shown impressive results in a subset of patients. Understanding the mechanisms of action of specific immunotherapies requires identifying different immune cells and their interaction with the tumor microenvironment.
MultiOmyx is a well-established multiplexed immunofluorescence technology that enables visualization and characterization of multiple biomarkers on a single 4μm tissue section. The technology visualizes the immune cells in and around the tumor region and this equips our clients with the knowledge they need for developing personalized cancer treatments. Furthermore, the final MultiOmyx report summarizes all the tumor-immune cell interaction data, quantitatively cellular level. Even for a small tissue sample, clients receive millions of data points. This is critical because clinical samples are precious and numbers of serial sections are limited.
MultiOmyx is a part of the Pharma Services division at NeoGenomics. The MultiOmyx operations team consists of Ph.D. scientists with expertise in Oncology, Clinical Lab Scientists with 10+ years of experience, innovative Bioinformaticians, and dedicated Systems Engineers. After receiving FFPE samples or slides from our clients, an H&E is generated and a pathologist evaluates the quality of the tissue. The MultiOmyx Lab Scientists then proceed to stain the sample for two biomarkers at a time where after each round of staining is imaged. The dye is then inactivated by the use of a MultiOmyx proprietary dye inactivation chemistry, enabling repeated rounds of staining and deactivation. The number of biomarkers can be as high as 60 on the same sample. High quality images are the core of this assay. The Bioinformatics team have developed numerous computer algorithms that can identify each cell in the images as immune cells or any other type of cell. These algorithms use complex functions and routines that can zoom into a cell and identify features and measure biomarker expression. The scientists work closely with the Bioinformatics team and make in depth investigation and interpretation of the results as it applies to the human body. This is an intense process that can take several weeks to analyze millions of cells.
Due to the significant increase in demand for MultiOmyx services and data, the Bioinformatics group have developed an in-house deep algorithm toolbox utilizing deep learning techniques. Deep learning is a subcategory of artificial intelligence and machine learning. In MultiOmyx, deep learning algorithms makes it possible to automatically and accurately detect proteins in an image at “machine speed”, this can dramatically decrease TAT and enhance our volume growth.
Over the last 8 years at NeoGenomics, MultiOmyx has proven its significant potential for facilitating cancer research. For a multi-modal approach the technology can be integrated with RNAScope on the same section with co-detection of RNA and protein greatly expanding the data output from a single specimen, providing critical information such as the source of secreted proteins (e.g. cytokines) or cell type specific transcript levels. MultiOmyx has a huge growth potential in the coming years as its utility in immunotherapy trials becomes more pronounced, as well as outside the field of cancer in studies for infectious diseases such as HBV and in autoimmune disorders such as Celiac disease.
