There is no doubt that immuno-oncology has changed the standard of care for many cancers, but there are still a lot of unanswered questions. For example, why do some patients respond better to certain combinations? How can we predict what type of tumor is more or less likely to respond to a certain drug? Ultimately, the more we understand about cancer at the molecular level, the better scientists and clinicians can research how to best select the right combinations of therapies for each patient.


The emergence of digital pathology and, more specifically, its recent application to translational science, has allowed us to see cancer differently: literally and figuratively. Through technology like image analysis-based multiplexing, we can understand more about the immuno-biology of cancer and see complex interactions in the tumor microenvironment. Other advancements like deep learning are helping to meet the demand for quantifiable data and provide more specificity when it comes to accurately differentiating cell types in the tumor microenvironment and finding associations with response. Whether applied to standard H&E or immuno-stained samples, this rapidly progressing technology is essential for immuno-oncology research, ultimately informing the approach to rational combinations, patient selection and clinical trial design. Just as next-generation sequencing has created volumes of insights to inform our translational research, so too will quantitative image analysis and multiplexing generate new insights. Such data is emerging rapidly.


Beyond the exploratory clinical research, image analysis, multiplexing and deep learning have the potential to change pathology practice as it relates to cancer prognosis and prediction. The more we use these technologies in our research to identify biomarkers that can enrich patient populations, the more likely we will need to translate this technology into a complementary or companion diagnostic product. As such, it is important that we ask ourselves, “Is the market ready to embrace an image-based companion diagnostic?”  For the answer to be “Yes,” market access to this technology is essential… and today, we are not there. However, there are signs of change. The FDA approval of whole slide imaging is an important data point of progress and shows that the investment community, regulatory authorities and clinicians are willing to entertain its potential to change clinical practice. Potential avenues to deliver image-based companion diagnostics may include a distributed model where laboratories or “digital pathology imaging centers” purchase equipment and perform testing or a central laboratory model where a single specialty reference lab performs testing and delivers reports. Both are viable, but neither is firmly established.


As scientists navigate the new questions arising in immuno-oncology, digital pathology provides a lens through which we can begin to understand cancer biology, paving the way toward predictive diagnostics. And, as exploratory research in immuno-oncology expands, we will begin to see the approaches being applied broadly to immunotherapy R&D in other diseases. Precision medicine is on the horizon for immunotherapy, and digital pathology will be key in helping science get there.


The opinions expressed here are those of Dr. Michael C. Montalto in his personal capacity and not those of Bristol-Myers Squibb. Dr. Montalto currently serves on the board of directors of the Digital Pathology Association as President-elect and is currently the Executive Director and Head of Translational Pathology and Clinical Biomarker Laboratories at Bristol-Myers Squibb. In this role he leads genomics, genetics, flow cytometry, immunohistochemistry, and pathology laboratories in support of clinical trials, exploratory biomarker research and companion diagnostics development. Click here to learn more about Dr. Montalto's work.


Disclaimer: In seeking to foster discourse on a wide array of ideas, the Digital Pathology Association believes that it is important to share a range of prominent industry viewpoints. This article does not necessarily express the viewpoints of the DPA, however we view this as a valuable point with which to facilitate discussion.