Representation in the (Artificial) Immune System

Much of contemporary research in Artificial Immune Systems (AIS) has partitioned into either algorithmic machine learning and optimisation, or, modelling biologically plausible dynamical systems, with little overlap between. We propose that this dichotomy is somewhat to blame for the lack of significant advancement of the field in either direction and demonstrate how a simplistic interpretation of Perelson’s shape-space formalism may have largely contributed to this dichotomy. In this paper, we motivate and derive an alternative representational abstraction. To do so we consider the validity of shape-space from both the biological and machine learning perspectives. We then take steps towards formally integrating these perspectives into a coherent computational model of notions such as life-long learning, degeneracy, constructive representations and contextual recognition—rhetoric that has long inspired work in AIS, while remaining largely devoid of operational definition

Signaling by the Epstein-Barr virus LMP1 protein induces potent cytotoxic CD4(+) and CD8(+) T cell responses

The B-lymphotropic Epstein-Barr virus (EBV), pandemic in humans, is rapidly controlled on initial infection by T cell surveillance; thereafter, the virus establishes a lifelong latent infection in the host. If surveillance fails, fatal lymphoproliferation and lymphomagenesis ensue. The initial T cell response consists of predominantly CD8(+) cytotoxic T cells and a smaller expansion of CD4(+) cells. A major approach to treating EBV-associated lymphomas is adoptive transfer of autologous or allogeneic T cells that are stimulated/expanded on EBV-transformed B cells. Strikingly, the clinical response correlates with the frequency of CD4 cells in the infused T cells. Although in vitro studies suggested that EBV-specific CD4 cells develop cytotoxicity, they have not been comprehensively characterized and the molecular mechanism underlying their formation remains unknown. Our recent work, using a transgenic approach in mice, has revealed a central role for the EBV signaling molecule LMP1 in immune surveillance and transformation of EBV-infected B cells. The mouse model offers a unique tool for uncovering basic features of EBV immunity. Here, we show that LMP1 expression in B cells induces potent cytotoxic CD4 and CD8 T cell responses, by enhancing antigen presentation and costimulation by CD70, OX40 ligand, and 4-1BB ligand. Our data further suggest that cytotoxic CD4 cells hold superior therapeutic value for LMP1 (EBV)-driven lymphomas. These findings provide insights into EBV immunity, demonstrating that LMP1 signaling alone is sufficient to induce a prominent cytotoxic CD4 response, and suggest strategies for immunotherapy in EBV-related and other cancers

Inhibition of Haspin Kinase Promotes Cell-Intrinsic and Extrinsic Antitumor Activity.

Patients with melanoma resistant to RAF/MEK inhibitors (RMi) are frequently resistant to other therapies, such as immune checkpoint inhibitors (ICI), and individuals succumb to their disease. New drugs that control tumor growth and favorably modulate the immune environment are therefore needed. We report that the small-molecule CX-6258 has potent activity against both RMi-sensitive (RMS) and -resistant (RMR) melanoma cell lines. Haspin kinase (HASPIN) was identified as a target of CX-6258. HASPIN inhibition resulted in reduced proliferation, frequent formation of micronuclei, recruitment of cGAS, and activation of the cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) pathway. In murine models, CX-6258 induced a potent cGAS-dependent type-I IFN response in tumor cells, increased IFNγ-producing CD8 <sup>+</sup> T cells, and reduced Treg frequency in vivo. HASPIN was more strongly expressed in malignant compared with healthy tissue and its inhibition by CX-6258 had minimal toxicity in ex vivo-expanded human tumor-infiltrating lymphocytes (TIL), proliferating TILs, and in vitro differentiated neurons, suggesting a potential therapeutic index for anticancer therapy. Furthermore, the activity of CX-6258 was validated in several Ewing sarcoma and multiple myeloma cell lines. Thus, HASPIN inhibition may overcome drug resistance in melanoma, modulate the immune environment, and target a vulnerability in different cancer lineages. SIGNIFICANCE: HASPIN inhibition by CX-6258 is a novel and potent strategy for RAF/MEK inhibitor-resistant melanoma and potentially other tumor types. HASPIN inhibition has direct antitumor activity and induces a favorable immune microenvironment

A single-amino-acid variant of the H60 CD8 epitope generates specific immunity with diverse TCR recruitment

TCR of CD8 T cells recognizes peptides of 8–9 amino acids in length (epitope) complexed with MHC class I. Peptide ligands differing from an epitope by one or two amino acids are thought to modulate the immune response specific to that epitope. H60 is a minor histocompatibility antigen for which the specific CD8 T-cell response dominates during alloresponse after MHC-matched allogeneic transplantation. In the present study, we developed a transgenic mouse (designated H60H Tg) expressing a variant of H60, designated H60H, in which the arginine residue at position 4 of the H60 epitope sequence (LTFNYRNL) is replaced by a histidine residue (LTFHYRNL). Immunization of female C57BL/6 mice with splenocytes from male H60H Tg induced a CD8 T cell primary response and memory response after re-challenge. The response was CD4 help-dependent, demonstrating the potency of H60H as a cellular antigen. The response induced by the H60H cellular antigen was comparable to that induced by H60 in its peak magnitude and overall immune kinetics. H60H challenge recruited broadly diverse TCRs to the specific response, shaping a TCR repertoire different from that of the natural H60 epitope. However, some of the TCRs did overlap between the H60H- and H60-specific CD8 T cells, suggesting that H60H might modulate the H60-specific response. These results may provide a basis for the modulation of the H60-specific CD8 T-cell response