Algorithm-based immune-epitope discovery

The goal of a personalized tumor immunotherapy is to identify tumor epitopes that are immunogenic and specific for a given patient. To do it, however, would require the knowledge of exact sequencing of a given "healthy" individual's proteome prior to tumor development. It is safe to assume that generic, public database would not provide the adequate tool.

In addition, the development for robust algorithms able to accurately predict the strength of binding of processed epitopes to MHC class I or II (or HLA) is an absolute must.

It appears that we are getting very close achieving this goal. I have already mentioned in my earlier post that journal Nature has published 5 separate papers about tumor immunology in December issue. However, my review showed that 3 of them were merely based on observation-type clinical data, more suitable for publication in journals like JAMA or Lancet, but not Nature. I am not sure why Nature has decided to include those 3 clinical papers in its publication list. However, 2 other papers that were mouse studies provided sufficiently robust experimental results for my analysis.

This 2nd study, led by Robert Schreiber at Washington University School of Medicine, has analysed mice immune response to aggressive sarcoma tumor cell line following anti-PD1 and/or anti-CTLA4 antibody therapy.  

Initial set of experiments indicated that anti-PD1 and/or anti-CTLA4 antibody therapy "helped" wild-type mice to reject the aggressive sarcoma cell lines in a T cell-dependent manner.

To understand the basis of tumor immunogenicity, the authors has applied 3 different epitope predicting algorithms to the available exome-sequencing data from one of the sarcoma cell line (d42m1-T3). With these in-silico generated epitope prediction methods, the authors were able to identify two dominant mutant epitopes, one from laminin alpha subunit 4 (Lama4) and another from asparagine-linked glycosylation 8 (Alg8).

Parallel experiments with TIL functional assay, tetramer binding and MHC peptide eluates mass spec analyses confirmed that these two mutations from sarcoma cell line (d42m1-T3) were the dominantly recognized by TIL following anti-PD1 therapy.

Additionally, Lama4 and Alg8 mutant peptides, but not wild-type variants, were immunogenic.

Moreover, mutant peptides + adjuvant immunized mice were able to reject sarcoma cell line.

Mechanistically, combination of anti-PD1 and/or anti-CTLA4 antibody therapy (but not anti-PD1 alone) augmented existing tumor-specific T cell numbers and their effect differentiation.

Note that anti-PD1 therapy alone were still able to protect mice from d42m1-T3 (see Fig. 1a), even though its effect on CD8 T cells was minimal, implying that the mode of action of anti-PD1 antibody therapy is less clear.

Here is my opinion: there is no doubt that tumors express mutant proteins (epitopes). If a mutant protein has a critical, obligatory function in fueling tumor growth, then the tumor cannot afford to lose it in an "escape phase" so targeting such epitopes would be useful. If however mutant protein does not have such function tumor will lose it easily once under pressure from T cells thus making immunotherapy less productive. Since we still do not know the function of many proteins it would be very difficult to identify "escape-proof" mutant epitopes for tumor immunotherapy.        

David Usharauli