THANK YOU FOR SUBSCRIBING
The biomarker and immune cell tools help to recognize the patients that will respond to immunotherapy.
FREMONT, CA: Immunotherapy shows promising results against various forms of cancers, as it boosts the immune cells of a patient to increase the innate immune system's strength. For example, during adoptive T-cell immunotherapy, the T cells are removed from a patient to be prepared to battle against cancer cells and then returned to the patient. Other methods are also showing promise, like blocking the pathway of the checkpoint inhibitor.
It is presumed that a connection between two proteins (PD-1 and PD-L1) forms a defense that safeguard cancer cells from the patient's immune cell attacks. It is assumed that disrupting this pathway and thus snatching away the shield of cancer cells would enable the immune system to operate more efficiently. PD-1 is even recognized as a checkpoint protein, so the disrupting process is also known as checkpoint inhibitor therapy.
Identifying likely responders using biomarkers
Although some patients benefit from immunotherapies that target the interaction between PD-1/PD-L1, others may not. Several research groups are looking for ways to classify patients who are likely to respond to the medication before starting therapy, such as biomarkers in a biopsy of patients.
Akoya emphasizes the tissue's infrastructure, disease pathology, and how these impact immunotherapy's efficacy. They deliver the CODEX method for multiplexing biomarker discovery and the quantitative pathology system Phenoptics for a translational and clinical study.
The CODEX platform gives a High-dimensional spatial analysis of over 40 immune markers in situ. Recognizing tissue architecture is essential because spatial relationships and interactions between cells in tumors can affect immunotherapy efficacy.
The Biomarker expression mapping is helped by Cytiva's Cell DIVE, an imaging device (utilizing HALO software from Indica Labs) that temporarily maps biomarker expression for over 60 biomarkers in patients tumor tissue at the single-cell stage.
Identifying responders using genomics
Same efforts are also being pursued in the genomic domain to predict possible responses to immunotherapy. Integrated with the Microsatellite Instability (MSI) Assay, Bio-droplet Rad's digital PCR (ddPCR) technology will help select suitable checkpoint inhibitor therapies using plasma FFPE samples to recognize mutations at 5 loci related to MSI status.
Bio-ddPCR Rad's and single-cell NGS applications are used to identify the functions that various cells perform in tumor microenvironments to classify larger populations of immunotherapy responders.