I presented my work leveraging single cell genomic technologies in clinical brain tumours to understand them, characterise them, with a new lens and an increased resolution or new resolution that only became possible just a few years ago. It takes the primary self-sequencing nucleic acids from an individual cell. You have to understand that for the longest time what scientists have done is take a piece of tissue and measure nucleic acids, either DNA or RNA, and they had to rely on a piece of tissue because you needed so much starting material to actually extract information. Now, over the years these techniques have become way more sensitive and people have worked out methods to start from a smaller and smaller and smaller amount of tissue up to the point where now it’s possible to do this kind of analysis from individual cells. Obviously individual cells is a special unit that’s the holy grail to achieve because now you’re dealing with the actual unit that is composing the body, that is driving the cancer. You can profile and understand each unit separately and you get away from a lot of the problems that we had up to now which is how to make sense of some of the signal because by combining different cell types together it’s sometimes hard to tease apart what is the source of any given stimulus.
I would say for DNA analysis, doing bulk analysis as has been done up to now has been extremely powerful and revolutionary. I don’t expect single cell DNA analysis to yield completely revolutionary information. However, I would say the opposite is true for RNA analysis, the RNA obviously is the analysis of the expression profile of a cell, what portion of the genome the cell is utilising. Because you have so many different cell types and mixed together in a clinical specimen, you have malignant cells, you have immune cells, you have microenvironmental cells, you have stromal cells, all that signal if you analyse it combined, as was done up to now, is really complicated to understand whereas once you profile the individual units then you understand the expression profile of individual units you can make a lot of sense of the information you get.
I would say different granularities so on the malignant cell side we can understand what type of cell programmes those malignant cells are trying to recapitulate and relate them to normal development. So in the field of gliomas what my lab has been doing a lot is characterising the developmental stage of cancer cell using those techniques and the power is that we get a very robust signature from any malignant cell and we can assign the cancer cell an identity – things like being a stem cell or being a more differentiated malignant cell. While we do that at the same time we can infer things like cell cycle activity and understand what is the driving force of the tumour. What we have found is that in many of those clinical specimens of gliomas the driving force is a stem cell and this is evidence now that we’ve been able to profile directly from patient specimens. You might have heard of the stem cell theory in gliomas for a while but these were inferred from functional assays in classes of disease that are distinct from the one we study now. Doing the single cell genomic analysis allowed us to generalise those kinds of theories and delineate the type of programmes that are driving clinical gliomas in defined subsets of disease.
The added power is that with those assays, while we infer the malignant cell state and the programmes that drive the tumours, we get from the same cell genetic information so we can infer the mutational status of that cell, we can infer the clonality of that cell. Again, it’s a new resolution, it allows us to understand what the genetics is doing in terms of cellular programmes. We like to think of cancer as a genetic disease, and it is a genetic disease, but we tend to forget that the genetics only operates within a certain cell type and depending on the cell type the genetics might have a different impact on the transcription programme of the cells. Again, by being able to profile tumours at cellular resolution we can now integrate genetics into developmental contexts and understand exactly what the genetics is doing to the malignant cells.
Does this lead to areas where new targeted therapies can be offered?
That’s the hope. I’m very active on the basic science spectrum so I don’t think enough about therapeutics, I more think about characterising and understanding tumour biology. But I must say we’ve been doing those efforts now in different classes of disease and we’ve definitely highlighted candidate vulnerabilities that some of them are being followed up by others, we don’t do clinical trials but I’ve received emails from some people following up on some of the stuff. We also are now characterising the immune compartment and there as well we’re finding novel ways to modulate the immune response to tumours that we could only highlight with those techniques. Those pathways would not have come to light had we used another approach so I’m fairly optimistic that down the line it will lead to something novel but I must say I’m also very active on the basic science level and not so much on the translational part.
I would say it’s exciting times, to be honest with you. I’ve been in this field now since I did my PhD, it’s maybe fifteen years altogether with my PhD, post-doc and now my lab. I feel like the field of brain tumours has changed a lot, I think we understand them really well in terms of genetics, what drives them. We are now beginning to add cellularity to the context, we’re beginning to characterise the immune environment and the different modalities that are available, both new targeted therapies but also immunomodulatory methods and capacity to target lineage with specific engineered CAR T-cells, all of that is converging into a really nice level of energy coupled to things like single cell genomics. There has never been a better chance to do something about those tumours. And I mean it, I don’t think we’re going to go another fifteen, twenty years without seeing real progress for patients. It’s always hard when you’re a patient and when you’re in the public you see a lot of agitation and a lot of expectation and maybe that doesn’t translate immediately into the clinic. But the progress that is being made is really tremendous and I think that progress will lead to new therapeutics.