Immuno-oncology 101 With Elfirede Nößner, HelmholzZentrum, Visiopharm Advisor

It is known that immune cells can destroy pathogens, so based on renal cell carcinoma research it was suspected that it could also destroy cancer cells. This is where Prof. Noessner’s immuno-oncology journey began.

In the course of her research she studied the following processes relevant for immuno-oncology together with the cells responsible for them:

• Killing: T-cells
• Removing the debris of the tumor: macrophages
• Antigen presentation: dendritic cells
• Antibody production: B-cells
• Immune response regulation: regulatory T cells and checkpoints: CTLA4 and PD1/PDL1

Killing is crucial for destroying the tumor, but without removing the debris of the killed cells the surrounding tissue will suffer.

Antigen presentation enables the immune system to see the enemy. If we do not have antigen presentation, the T-cells responsible for the killing process are blind and cannot recognize the enemy.

Antibody production is an upcoming research area of immuno-oncology however the processes are not well understood yet.

Regulation of the whole communication – stopping the immune response, prevents overshooting. In the body’s fight against the tumor, this regulation is coming too early, it stops the T-cells before killing all the tumor cells. This is detrimental in immuno-oncology. The stopping proteins are called checkpoints (e.g., CTLA4, PD1/PDL1) and to keep the T-cell attack going on, they need to be inhibited.

Due to digital pathology enabling the digitization of pathology images, both the immune cells and the checkpoints can be now visualized in the tissue. The visualization of the cells and processes relevant for immuno-oncology plays a crucial role in advancing cancer immunotherapy research.

Seeing is believing, so visualizing the cells and checkpoints has a great convincing effect for the scientific community, but it is also crucial for evaluating the effectiveness of the immune system. It makes it possible to see if the immune cells are in the right location (e.g., T-cells present within the tumor tissue) and in the right number. A great example of this proving that the numbers of T-cells in the tumor influence the patient prognosis more than the classical pathology grading approaches is the Immunoscore® of colon cancer. Quantification with image analysis of the numbers and locations of T-cells in colon cancer patients changed the way colon cancer therapy was approached so far.

This was an immuno-oncology breakthrough proving that T-cells can matter. However, they do not work all the time and the task of the scientists is to figure out how to activate them if they are not working. We need to understand what regulates the T-cells – one aspect are the checkpoints the other part is the regulatory cells. If the regulatory cells are close to the T-killer cells, the killer cells are inhibited. This can be only evaluated in an image – the proximity of the different cell types matters, and image analysis is the only way to accurately determine this information. The same counts for multi-marker analysis, as the human eye is not equipped to process such a large amount of information.

Even though a tissue image represents just one point in time, this information is enough to evaluate our starting point. This starting point can be used to launch the immune system to initiate the cancer defense cascade. This however is our assumption – just a hypothesis. And to confirm our hypothesis another image at a different time point will be necessary.

The immune system is a complex entity, but in order to fight cancer and advance immuno-oncology, we need to understand and learn to influence it. Digital pathology and image analysis have become indispensable tools in this mission.