Author: Gavin Gordon, PhD., Vice President, Clinical Market Development
We recently announced a partnership with Agilent to develop multiplex diagnostic solutions for tissue analysis and to commercialize workflow solutions for these assays in the clinical research market. I’m thrilled that our organizations are collaborating to develop chromogenic and immunofluorescent multiplex assays that include spatial analysis for biopharma companies advancing precision cancer therapeutics. These assay solutions are designed to rapidly translate biomarker discoveries into clinical testing and in doing so, enable development of companion diagnostics based on “spatial signatures” that more accurately predict patient response and enable a more personalized approach to therapy selection.
So, what are spatial signatures and how can they change the practice of cancer medicine? A signature in general represents a biological state unique to a specific tumor phenotype that takes the form of a pattern among multiple molecular markers, for example gene or protein expression, or genetic alterations such as mutations or fusions. A cancer spatial signature by extension is simply a signature where the spatial context of the cells are preserved and spatial information is incorporated into the signature definition.
Now we have a working definition of a spatial signature. But to truly understand why spatial signatures are important and why they represent a paradigm shift in immunotherapy predicitive biomarkers, its first necessary to review the current landscape for cancer biomarkers in general.
Better Biomarkers to Improve Disease Treatment
While targeted molecular therapies and immunotherapies represent a remarkable advance in the treatment of cancer, response rates remain low – from almost non-existent in pancreatic cancer to an average of 15-30% in most other tumor types.1 Accurately predicting whether patients will benefit from immunotherapy in particular is of paramount importance to both broaden their reach and avoid subjecting patients to potentially serious adverse events if they are unlikely to respond.
Current methods that form the basis of predictive biomarker strategies are traditional immunohistochemistry (IHC) and next-generation sequencing (NGS). Both techniques, however, have shortcomings when it comes to the discovery and clinical validation of spatial signatures. While IHC preserves the integrity of the tissue and spatial context, analysis is restricted to just a few biomarkers such as PD-(L)1 and standard cell types in the tumor microenvironment (TME). NGS yields a flood of biomarker data but requires tissue dissociation, leading to the loss of spatial information about cell-to-cell interactions.
Understanding the immune system is critically important to developing effective immunotherapies for cancer. In addition, the complexity of the immune repertoire and tumor itself requires a multiplex biomarker strategy to fully characterize the TME. Finally, what type of immune cells, and where they are located in the TME, has been shown to be important in predicting patient response to immuno-oncology therapies2. It is precisely for these reasons that spatial signatures hold such incredible promise to improve biomarker strategies in immuno-oncology and cancer in general.
Spatial signatures provide advantages over both IHC and NGS approaches for predicting response to immunotherapy.
Bringing Clarity to Complex Tumor and Immune Cell Interactions
Spatial biology is revolutionizing our understanding of the immense complexity and heterogeneity of tumor-immune cell interactions in the TME. This powerful technique answers a set of complex questions to reveal unique spatial phenotypic signatures that are enabling a new era of personalized medicine:
- What types of cells are present?
- What are their precise locations?
- What biomarkers are they co-expressing?
- How are the cells organized and interacting?
- What changes are occurring in response to treatment?
- How are regions of the tissue being reorganized?
The technique combines multiplex imaging, high-throughput instrumentation, and powerful algorithms, enabling more than one hundred biomarkers to be visualized, characterized, and quantified in a single tissue sample at single-cell resolution, while preserving spatial context. The morphological landscape of the TME is retained, allowing measurement of cell densities and interactions with much greater detail and clarity.
The resulting cell-by-cell maps of the TME provide deeper insights into tumor-immune biology. The presence, activation state of immune cells, as well as their spatial distribution relative to cancer cells in the TME offer the power to more accurately predict the response to immunotherapy.
Spatial signatures measure the interactions and densities of tumor and immune cells in the TME. A closer proximity of tumor cells and certain immune cells can determine how effectively the immune system can fight the tumor.
Setting a New Standard for Predictive Value
In a recent study, the accuracy of spatial signatures for predicting response to anti-PD-1/PD-L1 therapy was compared with PD-L1 IHC, TMB, and gene expression profiling.3 The meta-analysis of tumor specimens and response to therapy included more than 10 different solid tumor types in 8135 patients. Each study had assessed different types of biomarker assays for their value in predicting patient response to anti-PD-1/PD-L1 therapy.
Spatial signatures more accurately predicted patient response than the other assays. The findings strongly suggest an improved diagnostic benefit when spatial relationships and protein coexpression on specific cellular subsets are assessed.
Relative accuracy of biomarker testing modalities in predicting response to anti-PD-1/ anti-PD-L1 treatments.
Paving the Way to a New Era of Precision Medicine
The promise of immunotherapies will be realized, in part, with diagnostics based on clinically validated predictive spatial signatures. We are excited to partner with Agilent to create an end-to-end workflow solution for development and deployment of these multiplex tissue-based biomarkers. For biopharma companies developing companion diagnostics, our integrated platform can take them from biomarker discovery to the clinic, helping to usher in a new era of precision pathology and medicine and benefitting a larger portion of cancer patients.
- Esfahani, K et al. A review of cancer immunotherapy: from the past, to the present, to the future. Current oncology (Toronto, Ont.) vol. 27,Suppl 2 (2020): S87-S97. doi:10.3747/co.27.5223
- Binnewies, M., Roberts, E.W., Kersten, K. et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat Med 24, 541–550 (2018). doi: 10.1038/s41591-018-0014-x.
- Lu S, Stein JE, Rimm DL, Wang DW, Bell JM, Johnson DB, Sosman JA, Schalper KA, Anders RA, Wang H, Hoyt C, Pardoll DM, Danilova L, Taube JM. Comparison of Biomarker Modalities for Predicting Response to PD-1/PD-L1 Checkpoint Blockade: A Systematic Review and Meta-analysis. JAMA Oncol. 2019 Aug 1;5(8):1195-1204. doi: 10.1001/jamaoncol.2019.1549. PMID: 31318407; PMCID: PMC6646995.