2018 will be remembered as a decisive year for immuno-oncology. In particular, Nobel Prize winners James Allison of MD Anderson Cancer Center in Houston, Texas, and Tasuku Honjo of Kyoto University in Japan lifted the field of immunotherapy to international recognition for those outside the scientific and medical communities. For the patient, these new alternatives to standard oncology therapies offer new hope for life-extending treatments using immunotherapy.

Advancements in cancer immunotherapy

Mobilising the body’s own immune cells to fight against cancer has broadened current treatment possibilities, especially in advanced cases. In recent years, combination therapies using immune checkpoint blockades have become more complex, since they now require data analysis to select the right patient and match him or her to the right drug or clinical trial.

Notably, the evolution of IO drug therapy is affecting two key areas. First, the oncologist has more options to offer relevant, life-saving treatment to the cancer patient based on individual biomarker analysis of his/her tissue samples. And second, the role and requirements of the pathologist will evolve to respond to the demands of both the patient and the oncologist because the right treatment decision will require a full understanding of the tumor immune microenvironment beyond PDL-1 and should include the integration of additional patient data.

Current pathology practices and challenges

Today, in order to determine a patient’s eligibility for a drug, oncologists need to request an ever-expanding array of tests from different sources, such as immune-histochemistry or mutational analysis, etc. However, most requests are costly; this is the case with sophisticated technology for genetic diagnostics. Also, each test that is performed competes for the scarce amount of tumor tissue samples.

For modern-day pathologists, today’s practices have their own challenges, since the different IHC-based tests for different drugs, even of the same target, require assay-specific antibody clones and variable cut off points. This includes being able to manually read, count, and score tumor tissue samples, a process that can be extremely tedious. To make things worse, new drugs usually come with new (companion) tests, for which the pathologist needs additional training and resources. This can be a continuous challenge to stay abreast of new studies and developments.

How will the role of the pathologist evolve?

The role of the pathologist will evolve to oversee and coordinate, as well as correlate different tests and their results. It will go beyond reading tissue images to leading a team of experts to interpret and integrate a multitude of molecular test results. Ultimately, the increasingly consultative role of the pathologist in relation to the oncologists and radiologists will become even more critical for therapeutic decisions. To evolve in this role, pathologists will need to have better ‘toolkits’ at hand for patient profiling that should help them understand the interaction between individual cancer and the immune system through a multiplicity of data.

As the number of available drugs for targeted therapy continues to grow, oncologists and pathologists will require a more sophisticated decision platform to simplify the drug selection process. Thus, it is important that a single patient sample provides a comprehensive overview of available tissue biomarkers.

The Definiens Tissue Phenomics® methodology is closely integrated with assay development, image analysis, and bioinformatics to help reveal insights within the tissue. These insights become the basis for immune profiling, biomarker discovery, and patient stratification. By using computational and artificial intelligence, including deep learning, Tissue Phenomics can cope with large quantities of digital tissue samples and big data.

This methodology is automated to analyse multiple biomarkers for their spatial relationships on multiplexed IHC tissue slides and provide additional contextual information. Leveraging the rich content in the tumor microenvironment in the tissue sample, Tissue Phenomics quantifies the tumor immune interactions, a task that trained computer algorithms can do faster, more reliably, and more consistently.

This approach will become an integral part of the comprehensive diagnostic test to match patients with the best IO drug for their personalised therapy.

Preparation for the future

As the immune-oncology landscape continues to evolve, pathologists will lead the way with the power of tissue data and decisive treatment recommendations. Using the decision platform based on the Tissue Phenomics methodology, pathologists can confidently present these results at the tumor board, thus enabling oncologists to make better, more accurate and flexible decisions. In the end, these better decisions can lead to smarter drug selections to give patients what they need – personalised, more effective cancer treatment.

Ralf Huss is Chief Medical Officer at Definiens. He presented “Tissue phenomics: digital pathology + integrative data science + computational intelligence” at the Digital Pathology & AI Congress.

To learn more about how Tissue Phenomics works, please download a free chapter.

This article originally appeared on Global Exchange before Digital Pathology & AI Congress in London 2018.