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We’ve hosted a two-part webinar series in collaboration with Science on the theme of the changing landscape of diagnostic biomarkers in oncology. In the first part of this series, we heard from the following experts in the field:
Sacha Gnjatic – Icahn School of Medicine at Mount Sinai, New York, NY
David Rimm – Yale University School of Medicine, New Haven, CT
Houssein Abdul Sater – NIH NCI Center for Cancer Research, Bethesda, MD
The first webinar is still available to watch here. In case you don’t have time to watch the full video, we’ve summarized some of the key discussion areas below.
The discussion started by outlining a significant shift in approach for immunotherapy biomarkers compared to conventional biomarkers. With this approach, the tumor is no longer the sole target and the immune system is primed to recognize cancer cells. Individual tumor biomarkers are not enough; it is critical to consider the entire, complex immune cell network. This network is key to fully understanding which biomarkers might accurately predict which patients will respond to treatments. A single biomarker such as PD-L1 expression is insufficient alone to capture disease-relevant immune signatures and the interactions between important cell types. For example, some patients showing high PD-L1 expression do not respond to immunotherapy, while conversely, some patients showing low PD-L1 expression respond well to immunotherapy.
Understanding the mechanisms underlying different immune signatures is important for the development of innovative and integrated assays that accurately predict responses to treatments. Previously identified immunotherapy biomarkers include immune cell infiltrate, tumor mutational burden (TMB), and microsatellite instability, which can be used to predict the effectiveness of therapies in different patient groups. The panel discussed how immunotherapy research is uncovering promising new biomarkers to guide immunotherapy. Gut microbiota, blood analytes, stromal markers, and circulating DNA were highlighted as having potential for novel biomarker discovery. Large-scale patient studies, big-data analysis, and modern technology platforms are accelerating biomarker discovery and implementation in diagnostic tests.
Accelerating the adoption of multiple immunotherapy biomarkers is dependent on a better way to generate, integrate, and monitor patient biomarker data on a larger scale. The Cancer Immune Monitoring and Analysis Centers and Cancer Immunologic Data Commons (CIMAC-CIDC) is a new initiative with a mission to enhance clinical trials in cancer immune therapies by applying new technologies and extensive data analysis expertise to produce a network of functional immunotherapy biomarker data. A suite of technologies including multiplex IHC, mass cytometry, RNA sequencing, whole exome sequencing, and serum cytokine analysis will be used across four main centers. This network will serve as a resource to support immunotherapy research and early-phase clinical trials.
Mass cytometry is a high-throughput protein analysis technique which involves labeling the targets within a sample with heavy metal–conjugated “carrier-free” antibodies, ie antibodies stored in PBS rather than buffers containing preservatives such as sodium azide. This technology currently enables the analysis of up to 50 markers simultaneously from a single cell.
Challenges facing the adoption of multiple biomarkers were discussed, including harmonization, integration, reimbursement, and commercial viability. A lack of full concordance between different tests for the same target was highlighted for PD-L1 where tests differ in their scoring criteria and interpretation. This variation will increase further when integrating multiple tests to different biomarkers together, as different labs, equipment and conditions can all contribute to variations in results. These variables need to be better standardized to achieve a robust and reproducible diagnostic test.
The members of the panel shared their perspectives around the best combination of markers that would give an accurate prediction of tumor response. The future potential of measuring tumor mutation burden (TMB) was viewed differently by the panel, given the low percentage of patients with a high TMB. A combination of a small number of cell type markers and immune checkpoints were also considered a promising combination to predict response to immunotherapies. Predictive data combined with cost/benefit considerations would be helpful when deciding how and when different assays should be used, for example, sequentially versus at the same time.
Click here to view the next webinar in the series “The changing landscape of diagnostic biomarkers: Revealing the future of diagnostics, from singleplex to multiplex.”
To push the boundaries of what we can achieve for future diagnostic tests, researchers need access to a diverse range of reliable research tools and expertise. At Abcam, we have a strong immuno-oncology focus, and we are frequently developing new recombinant monoclonal products for IO targets. Carrier-free antibodies give flexibility across different platforms and multiplex technologies including mass cytometry. Abcam has a broad range of carrier-free recombinant monoclonal antibodies that are suitable for metal-conjugation and multiplexing, including targets such as PD-L1, PD-1, CD68, CD163, CD4, CD8, and FOXP3. We’re happy to help you with the tools or support you need to accelerate your research, antibody discovery, and/or companion diagnostic development.