Immunotherapy—in which a boost to a patient’s immune cells is intended to strengthen the innate immune system—is showing promising results fighting different kinds of cancers. For example, in adoptive T-cell immunotherapy, T cells are removed from a patient, engineered to better equip them to fight cancer cells, and then returned to the patient. Other approaches, such as blocking the checkpoint inhibitor pathway, are also showing promise. An interaction between two proteins (PD-1 and PD-L1) is thought to form a shield that protects cancer cells from the patient’s immune cell attacks. Disrupting this pathway—and hence snatching away the cancer cells’ shield—is thought to allow the immune system to function more effectively. PD-1 is also known as a checkpoint protein, so the disrupting the pathway is also called checkpoint inhibitor therapy.
Yet these promising new approaches sometimes fail, indicating that researchers still have a long way to go. Here are some examples of issues facing immunotherapy researchers and clinicians today, along with new tools and technologies built for the task.
Identifying likely responders using biomarkers
While some patients benefit from immunotherapies that target the PD-1/PD-L1 interaction, others do not. Many research groups are searching for methods to identify patients likely to respond to treatment prior to initiating therapy, for example by the presence of biomarkers in a patient biopsy. Akoya focuses on tissue architecture, disease pathology, and how these influence the effectiveness of immunotherapy. They offer the CODEX system for multiplexing biomarker discovery, and the quantitative pathology system Phenoptics for translational and clinical research.
The CODEX platform provides high-dimensional spatial analysis of over 40 immune markers in situ. Understanding tissue architecture is important because the effectiveness of immunotherapy can be influenced by spatial relationships and interactions among cells in tumors. “Our technology uses tissue imaging to characterize the complexities of the tumor microenvironment, and better understand the role of spatial relationships between infiltrating immune cells and the remodel of the cellular matrix,” says Chris Streck, VP of marketing at Akoya. “The CODEX system converts existing fluorescent microscopes into high dimensional imaging systems capable of providing in situ analysis at cellular and subcellular scales.”
Akoya’s Phenoptics platform lets researchers visualize and measure tumor cells and multiple immune-cell phenotypes simultaneously in formalin-fixed paraffin-embedded (FFPE) tissue. “Phenoptics integrates multiplexed immunohistochemistry and imaging to quantitatively capture systems biology data with cellular detail,” says Streck. “It helps researchers better understand the integrations between tumor cells and the immune system within the tumor environment.” A recent 
in JAMA Oncology found that multiplexed immuno-oncology biomarker testing using Akoya’s technology was more effective than other methods for predicting patient response to treatments targeting PD-1/PD-L1.
Biomarker expression mapping is also supported by Cytiva’s Cell DIVE, an imaging system (using HALO software from Indica Labs) that spatially maps biomarker expression in patient tumor tissue at the single-cell level for over 60 biomarkers. “Immunotherapy feels like a miracle cure for some people, and absolutely cruel dashed hopes for others,” says Prachi Bogetto, diagnostics segment leader for cell analysis at Cytiva (formerly GE Healthcare Life Sciences). “The key to discerning which side of that line a patient might fall on is understanding their particular immune profile for their particular cancer.”
Bogetto believes that one of the current challenges in immunotherapy is the heterogeneity of response from patient to patient, and even within a patient. “There are clearly documented cases of evaluating different tumors within a patient of the same cancer modality but located in different organs that respond differently to the same treatment,” she says. A recent PLOS ONE on stage 3 metastatic melanoma showed that Cell DIVE was able to find patterns of homogeneity in immune cell expression, starting with a patient cohort that initially appeared heterogeneous. By grouping patients into cohorts based on a pattern of immune cell expression, it may be possible to identify good candidates for specific drugs.
The side effects of cancer immunotherapy can be devastating, but the additional tragedy is that a physician may only get one shot at choosing it. “If you get it wrong, your patient has run out of chances to have any kind of meaningful extension of lifespan,” says Bogetto, who believes that the greater information contributed by Cytiva’s Cell DIVE and other systems can help to improve clinical outcomes for cancer patients undergoing immunotherapy.
Identifying responders using genomics
Similar efforts to predict likely responders to immunotherapy are also being explored in the genomic realm. Bio-Rad’s droplet digital PCR (ddPCR) technology, combined with their Microsatellite Instability (MSI) Assay, can help to choose appropriate checkpoint inhibitor therapies by identifying mutations at 5 loci relevant to MSI status using plasma or FFPE samples. Bio-Rad’s ddPCR and single-cell NGS applications are also being used to understand the roles that different cells play in tumor microenvironments, in an effort to identify larger populations of immunotherapy responders, says Dawne Shelton, associate director for ddPCR IVD at Bio-Rad Laboratories Digital Biology Group.
According to Shelton, at most only 10% of patients have ideal responses to checkpoint inhibitor drugs. “Clinicians are looking for indications of a high mutational rate and a lot of neoantigens per tumor that the immune system can latch onto and kill,” she says. “However, tumor cells are ideally selected for their ability to hide from the immune system.” Identifying the means by which cells “hide” from the immune system will help researchers force them to become visible — and therefore vulnerable — to immunotherapy. “Both ddPCR and single-cell NGS are being used to identify these mechanisms, measure tumor infiltrating lymphocytes, and identify good candidates for therapy using MSI-high detection,” says Shelton.
Developing robust living products
Even as immunotherapy is changing the way cancer is treated today, challenges remain when it comes to delivering an effective and persistent immune response. Luke Dimasi, manager of global product marketing for Agilent Technologies’ Cell Analysis Division, believes that this is due in part to the in vitro assay tools available to cancer researchers today, which aren’t typically built to develop a living biological product like immune cells. “Delivery of a safe, potent, and persistent immune cell product requires a comprehensive understanding of the drivers for immune cell function,” he says. “The success of next-generation adoptive immune cell therapies will, therefore, be dependent on a deeper understanding of efficacy and potency delivered by real-time, functional cell assays, that can better predict in vivo immune response.”
Agilent’s tools for real-time live cell analysis are helping researchers to understand what drives immune cells to effect the right response at the right place and time. Agilent’s Seahorse XF HS Mini, a live cell metabolism platform designed for immunotherapy development, “enables researchers to probe the metabolic state of increasingly rare primary isolated or sorted immune cell types, and identify metabolic drivers that improve the fitness and persistence of immune cells in the suppressive tumor microenvironment,” says Dimasi. In addition, Agilent’s xCELLigence RTCA eSight assesses immune cell-mediated tumor cell killing and cytotoxic potency using real-time label-free impedance measurements. It can also assess immune effector cell activation and proliferation. “These two new platforms provide immunotherapy developers fit-for-purpose, in vitro tools capable of assessing therapeutic potential,” says Dimasi.
With biomarker and immune cell tools to help identify which patients are more likely respond to which immunotherapy, clinicians are armed with increasing amounts of information on which to base treatment recommendations. As technologies in this area continue advancing, more patients are likely to benefit from immunotherapy treatments.