﻿Good afternoon. My name is Jochem Gokemeijer. I am with Bristol Myers Squibb based out of
Cambridge, Massachusetts. And it's my great pleasure to talk to you this afternoon. First
of all, I would like to thank the organizers for inviting me to this very interesting workshop.
So, today I want to walk you through the immunogenicity risk assessment strategy that we
are using for our novel modalities. And in this case, I am talking about CAR T
cellular therapy and AAV gene therapy. I am going to assume that some of the previous speakers have
introduced these modalities to everybody. But in short, CAR T cellular therapy, allogenic T cells
that contain a engineered chimeric receptor to a tumor antigen thereby facilitating the destruction
of these tumor cells. Gene therapy AAV mediated delivery of a transgene to a target tissue to
replace a defective gene thereby alleviating the effects of the defect gene.
So, if we start with the immunogenicity risk of AAV gene therapy, the modality
being fairly complex, one of the main issues as discussed in previous talks, is the pre existing
antibodies to the capsid proteins thought to exist in up to 70 percent of patients, depending
on the age of the patients and the serotype of the virus. Second, the virus capsid protein as well as
the GpC rich regions of the transgene encoded DNA have the potential to activate toll like
receptor and pattern recognition receptors thereby activating the innate immune system,
which can result in crosstalk and cross activation of the adaptive immune system.
Next, the cellular immunogenicity or and humoral immunogenicity as a result of the intracellular
expression of the transgene and recognition and by T cells, which can result in a CTL
reaction, which can result in the destruction of the tissues that are expressing this
transgene. Class II mediated immune responses to the transgene, although probably only likely for
engineered transgene products, can result in anti drug antibodies to this transgene product.
As mentioned, obviously the immunogenicity of the transgene
is highly dependent on the level of engineering of the transgene. But also, on
the form that is expressed in the patient population, meaning a large
portion of the protein missing increases the risk of this transgene being recognized as non self.
For the CAR T immunogenicity risk potential, since the chimeric receptor is expressed intracellular,
we feel that the main risk for this modality involves the processing and presentation of this
transgene and being recognized as non self peptide resulting in either a cellular immune response,
which can result in a CTL reaction towards the CAR Ts and destruction of those cells. Or
a humoral immune response, which would result in anti drug antibodies that can recognize
the chimeric receptor and thereby inhibit and neutralize the efficacy of this modality.
So, in order to assess the immunogenicity risks of these modalities and allow us to move forward
and develop therapeutics with a decreased immunogenicity risk for our patients,
we have based our strategy mostly on the tools and strategies that were initially developed for
protein biologics, which is mostly as you can see in this slide here, a MHC class II mediated
humoral immune response. And the tools are mostly in silico methods to look for HLA binding
sequences within the biologics. In vitro MAPPS assay to assess the processing and presentation
of those biologics and the potential of these biologics to illicit a CD4 T cell proliferative
reaction in an in vitro assay. So, we have those tools in place and our strategy is mainly to see
what portions and how can we use those tools to assess the risk of these novel modalities.
So, the first tool that get heavily used in our organizations are the in-silico immunogenicity
risk assessment tools. These MHC class II predictive algorithms based on the structure
of the MHC binding groove are widely used for lead selection and deimmunization of protein
biologics. This information is also now submitted as part of the integrated summary of
immunogenicity and more complex systems biology in silico models are in development now to look at a
more of a population level immunogenicity impact. So, applying these tools to these novel modalities
as mentioned before, a lot of these CAR T and gene therapy therapeutics are intracellular expressed
and therefore have the potential to be presented on a class II MHC receptor. And I think the
encouraging, and for us, useful, is that most of the in-silico tools that are available actually
do have the option to look at MHC class I binding. And several studies have shown that in most cases
the class I prediction algorithms to be more reliable actually than the class II algorithms.
So, when we look at the immunogenicity risk with our in-silico methods, the majority of these
CAR T constructs are constructed from fully human proteins and domains. And those are, therefore,
less likely to pose an immunogenicity risk. The ScFvs that are used for these chimeric receptors
while in the past a lot of them were actually from a mouse source, now most of them are fully human.
So, when we look at the immunogenicity risk of these constructs, most of the risk is contained
within these CDRs because they are hypermutated and therefore can be recognized as non self.
The linkers between the different domains have the potential to be non self and then the junctions
between the different domains also have the potential to generate novel non human sequence.
For the gene therapy transgene constructs, as mentioned, if we are
replacing a complete wild type, fully human gene, those would obviously have
not that much immunogenicity risk although depending on what the patient population is
actually expressing. So, big gaps in those genes or point mutations would differ
from the transgene that we are introducing. So, it is worth it to closely look at your
transgene and compare that to what are the mutations in your patient population.
If the transgene is engineered, it's obviously worth it to look at
what portions are being engineered. What junction does that create between the domains? And
we can look with in silico methods to see if those portions are likely to
have binding potential for MHC class I and MHC class II.
So, here I am showing a in silico immunogenicity risk assessment for a CAR T construct. So,
we are using a MHC class I and an MHC class II algorithm. And what these methods do is they
really just look at the sequence of your construct and look at every possible peptide that can be
generated from these constructs and assesses the binding potential to the different MHC molecules.
In combination with that, we are using now a prediction elution. This is the likelihood that
that peptide will actually be processed and presented. And we do like to use multiple tools
to give this increased confidence in the binding prediction. So, as you can see in this
cartoon here, we like to express our potential binding,
potential on a scale of 1 to 10. And the different lines in this assessment here projected below the
different domains for CAR T constructs give you an idea of what the potential binding of these
junctions would be to MHC class II. So, as you can see here,
the junction between Domain and Domain 2 there is very little MHC class II binding. We can see that
it's also not very likely to be processed and presented on an MHC class II. There's
a little differentiation from human homology. So, there's a little bit of foreignness between these
junctions. And you can see that there is a few potential binding epitopes for MHC class I.
So, if we would look then to somewhat differently the junction between Domain 2 and Domain 3 is
somewhat more of a concern. It seems to be that there are multiple peptides that have a high
potential to bind to MHC class II. The prediction algorithm for presentation also shows that its
fairly likely that this peptide is being processed and presented on antigen presenting cells.
It's about, I think half of it is a non human sequence. And then there is a few peptides
that show some MHC class I binding risks. So, if we would go through our construct this way,
we would probably do some engineering on this junction. And we would experiment with moving
the junction between the domains, a few amino acids toward Domain 2 or towards Domain 3
and see if that would change the binding potential of this particular junction.
The next assay that we would use to further assess the immunogenicity risk of our construct is really
a follow on from the in-silico method where we would look with an in vitro assay to see what
is the likelihood that a predicted MHC binding peptide is actually being processed and presented.
And while we have developed these methods for MHC class II, we have now modified this in
vitro assay to not only look at presentation on MHC class II, but include MHC class I as well.
So, while traditionally for biologics we would use a monocyte derived dendritic cell to do the
take up and presentation of our biologics and subsequently we would IP and out the class II
receptor, we can modify this method and elude the MHC class I and class II molecules straight
from the CAR T construct as you can see here. And then the peptides that are docked within those MHC
molecules get sequenced by LCMS and then mapped back to the actual constructs. So, utilizing this
assay, this would give us an idea of what peptides are being presented by these chimeric T cells.
So, lastly, I do want to mention that obviously we are developing and using these predictive
immunogenicity tools for these novel modalities. I think one of the things that we don't know is, you
know, how predictive are these tools and when it comes to predicting immunogenicity in the clinic.
We are lacking a solid data set on what the correlation is between these methods
and what is observed in the clinic. So, one of the things that we will
have to do going forward is apply some reverse translational research to these modalities and
get data from the clinic including what are the T cell epitopes that are driving immunogenicity
once we observe immunogenicity so that we can further validate these methods and gain
a greater understanding of the immunogenicity of these novel modalities.
In summary, immunogenicity of novel modalities is often complex, and it can involve innate,
adaptive, and humoral immune systems. The risk assessment tools that we use for these
therapeutics can be modified from previously used immunogenicity
risk assessment tools. And as mentioned, we will need reverse translational research and data
to further understand immunogenicity and show utility of these tools.
Thank you very much. And I'll be happy to take any questions.