We’ve been tracking the cancer immunotherapy biomarker space closely via our Immuno-Oncology BioMAP for years and have witnessed the rapid growth and evolution of immuno-oncology first hand. The amount of investment (time, money, and resources) in cancer immunotherapy biomarker exploration has been staggering, yet, despite all the inertia and momentum around cancer immunotherapy biomarkers, one could argue that there hasn’t been much progression on the biomarker front since the beginning: other than PD-L1, only MSI has been approved by regulatory agencies and included on drug labels as a marker to predict response to cancer immunotherapy, and no novel immunotherapy biomarker outside of PD-L1 has achieved a category 1 evidence / consensus rating in NCCN guidelines.
From our discussions with oncology KOLs, one common hypothesis for this lack of progress is that the biomarkers being explored fail to capture the complexity of systems biology and tumor-immune interactions. Currently, the most common target for cancer immunotherapy biomarker exploration is tumor inflammation (i.e., the presence / absence of tumor-infiltrating immune cells) – the most clinically advanced biomarkers, PD-L1, TMB, and tumor inflammation gene expression signatures, are all direct or indirect measures of the presence / absence of immune cells in the tumor microenvironment. However, the lack of efficacy (to-date) of these markers suggests that the mere presence / absence of any given cell, protein, gene, or mutation may not be sufficient to understand cancer and predict who may or may not respond or how their response may evolve over time. Another class of biomarkers – functional biomarkers and analyses – which characterize the type and quality (not just the presence / absence) of an immune response, may provide additional levels of insight about the tumor-immune interaction that are necessary to derive a better understanding of disease and, potentially, clinical utility.
While functional markers and analyses are already being explored in I/O clinical trials, they often take a back seat to other markers and methods. This may be due to multiple reasons, such as the preference or necessity for fresh / viable samples for functional analyses (viable tissue sampling comes with logistical challenges), challenges with workflow standardization, and the perception that the tools, technologies, and methods for functional assays and analyses (e.g., ELISA, ELISPOT / interferon-gamma release assays, flow cytometry) are less powerful, precise, and sexy as some of the tools, technologies, and methods used for other types of cancer immunotherapy biomarkers (e.g., NGS for TMB, CGP, and gene expression profiling; multiplex spatial tissue profiling technologies). Recently, however, various platforms / technologies and methods have emerged that may advance the precision and power of immune functional analyses to new heights, potentially propelling these biomarkers into the spotlight.
Our analysis of I/O clinical trials indicates that functional biomarkers are explored in ~20% of all biomarker-containing I/O clinical trials and comprise ~9% of of all biomarker mentions (Figure 1). While functional markers / analyses can be used for predicting response, they are also uniquely positioned to serve multiple upstream and downstream applications as well. For example, functional analyses can be particularly useful in cell therapy development (e.g., selecting the most active engineered cells for expansion) and monitoring for immune responses post-treatment (e.g., assessing the ongoing cytotoxicity of therapeutic cells, or assessing the activation of antigen-specific T-cells in response to checkpoint inhibition). Indeed, the majority of mentions for functional markers and analyses are in the context of monitoring the immune response after treatment (Figure 2).
Functional assays generally consist of the measurement of proteins (typically cytokines / chemokines), RNA, or metabolites that are associated with particular cellular functional states, or which change in response to a stimulation or immune challenge event. Among trials which specify methods or technologies for immune functional analyses, cytokine analysis via ELISA (e.g., Luminex bead arrays, Meso Scale Discovery) or intracellular cytokine staining (flow cytometry), ELISPOT / interferon gamma release assays (e.g., ImmunoSpot), and tetramer / multimer assays are the most commonly explored techniques I/O clinical trials today (Figure 3).
The exploration of functional markers in clinical trials is still largely a research objective: >90% of functional markers are being explored within phase 1-2 trials and academic institutions represent 13/15 of the top primary sponsors of trials exploring functional markers. Among pharma companies exploring functional markers in trials, Janssen, Adaptimmune, Roche, and Novartis are the top sponsors of trials exploring functional markers (Figure 4).
Functional biomarkers are explored across multiple cancer types, with a distribution mirroring that of I/O trials in general, though with lung cancer slightly underrepresented compared to the broader I/O trial landscape (Figure 5).
While the current methods for exploration of immune function markers are effective, these methods, are generally limited in terms of automation, plex, and single-cell resolution, which are key parameters for enabling more advanced biomarker research and exploration. In recent years, however, the rise of single-cell, multiplex, and multi-omic analytical methods have been developed that enable more precise and powerful functional analyses.
Single-cell -omics platforms, such as those from 10X Genomics (Chromium), Mission Bio (Tapestri), BD Biosciences (Rhapsody), and Fluidigm (C1, CyTOF) all enable gene and/or protein expression profiling, which can be used to evaluate various cellular activation states at single-cell resolution, which can be critical to assessing the functional characteristics of a cell population. These platforms enable targeted and/or transcriptome-wide analyses and the analysis of dozens of protein markers simultaneously, providing the ability to interrogate cell populations and responses at a granular level. (For more info about the single-cell analysis market, keep an eye out for upcoming update to our single cell analysis market report – contact my colleague Miguel Edwards if you are interested in learning more).
Other companies, such as IsoPlexis (IsoLight) and Berkeley Lights (Lightning) have developed platforms and protocols for automated, live, single-cell analyses specifically for assessing cellular functionality using extracellular signaling analysis. IsoPlexis, for example, has developed a proprietary metric (PSI – Polyfunctional Strength Index) based on single-cell cytokine secretions (>30 plex) across up to 1,000 single cells in parallel (per chip), and has shown the ability to use PSI as both a predictive biomarker as well as a tool for assessing the potency of cell therapies during development. Berkeley Lights has also developed functional assay protocols to run on its benchtop Lighting optofluidic platform. Using precise optofluidic particle handling, Berkeley Lights has protocols to run up to 1,500 bead-based interferon gamma release assays in parallel (per chip), while enabling the extraction of the highest functional cell(s), live, from the chip for downstream characterization, processing, and expansion. While Berkeley Lights currently targets primarily development and production-related applications (e.g., cell therapy development), the company cites cellular biomarker and diagnostic R&D as an emerging application area. Both IsoPlexis’ IsoLight and Berkeley Lights’ Lightning platforms are automated systems with on-board incubation, liquid handling, and data analysis capabilities, addressing many of the pain points traditionally associated with performing functional assays at scale.
In addition to approaches that directly measure immune function at the single-cell level, other methods can provide a proxy for immune response at the cell population level. T-cell receptor (TCR) repertoire analysis (not included in the data cuts above), for example, can be used to assess the diversity of one’s immune cell population, which can be a predictive or prognostic measure, as well as the clonal evolution of T-cell populations over time, assessing how the immune system is responding to the presence of an antigen or the administration of an immunotherapy. Numerous companies (Adaptive Biotechnologies, ArcherDx, Takara Bio, Creative Biolabs, 10X Genomics, Berkeley Lights, Thermo Fisher, Illumina, iRepertoire, GeneWiz, Fluidigm, Invivoscribe, Beckman Coulter Life Sciences, among others) offer various kits, services, and data analysis packages for TCR repertoire analysis.
While immunotherapies have altered the cancer treatment paradigm, there remains significant progress to be made in predicting response and monitoring the efficacy of immunotherapies. Driven by technological advancements, functional analyses may provide the insights needed to drive progress towards development of new, clinically actionable biomarkers.
This analysis was powered by our Immuno-Oncology Biomarker Analysis Platform (BioMAP) – a database of biomarkers identified from immuno-oncology clinical trials. If you would like to learn more about our I/O BioMAP or precision medicine strategy consulting services, please contact [email protected]