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Anti-PD1 treatment has improved the survival of metastatic melanoma patients, yet it is unknown which patients benefit from the treatment. In this exploratory study, we aimed to understand the effects of anti-PD1 therapy on the patients’ immune system and discover the characteristics that would result in successful treatment. We collected peripheral blood (PB) samples from 17 immuno-oncology-naïve metastatic melanoma patients before and after 1 and 3 months of anti-PD1 therapy. In addition, matching tumor biopsies at the time of diagnosis were collected for tissue microarray. The complete blood counts, PB immunophenotype, serum cytokine profiles, and tumor-infiltrating lymphocytes were analyzed and correlated with the clinical data. Patients were categorized based on their disease control into responders (complete response, partial response, stable disease > 6 months, N = 11) and non-responders (progressive disease, stable disease ≤ 6 months, N = 6). During therapy, the PB natural killer T (NKT) cell frequency, expression of CD25 and CD45RO on cytotoxic natural killer (NK) cells, and serum CXC chemokine levels were significantly increased in responders. Furthermore, higher age together with age-associated characteristics from PB, lower frequency of PB-naïve CD8+ T cells, and elevated levels of serum MCP-4 and OPG were discovered as baseline predictors of treatment response. We therefore propose that in addition to T cells, anti-PD1 treatment is associated with NK- and NKT-cell population dynamics, and that the age-associated characteristics from PB together with older age may contribute to prolonged PFS in anti-PD1-treated melanoma patients. Electronic supplementary material The online version of this article (10.1007/s00262-020-02497-9) contains supplementary material, which is available to authorized users.

Molecular mimicry is known to be one of the leading mechanisms by which infectious agents may induce autoimmunity. However, whether a similar mechanism triggers anti-tumor immune response is unexplored, and the role of anti-viral T-cells infiltrating the tumor has remained anecdotal. To address this question, we first developed a bioinformatic tool to identify tumor peptides with high similarity to viral epitopes. Using peptides identified by this tool, we showed that, in mice, viral pre-existing immunity enhanced the efficacy of cancer immunotherapy via molecular mimicry. Specifically, when treated with a cancer vaccine consisting of peptides with a high degree of homology with specific viral peptides, the mice with induced pre-existing immunity to these viral peptides showed significantly better anti-tumor response.To understand whether this mechanism could partly explain immunotherapy-response in humans, we analyzed a cohort of melanoma patients undergoing PD1 treatment with high IgG titer for Cytomegalovirus (CMV). In this cohort of patients, we showed that high level of CMV-antibodies was associated with a prolonged progression free survival, and found that in some cases PBMCs could cross-react with both melanoma and CMV homologous peptides. Finally, T cell TCR sequencing revealed expansion of the same CD8+ T-cell clones, when PBMCs were pulsed with tumor- or homologous viral peptides.In conclusion, we have demonstrated that pre-existing immunity and molecular mimicry could explain part of the response observed in immunotherapy. Most importantly, we have developed a tool able to identify tumor antigens and neoantigens based on their similarity to pathogen antigens, in order to exploit molecular mimicry and cross-reactive T-cells in cancer vaccine development.One Sentence SummaryMolecular mimicry can play a role in anti-tumor immune responses and should thus be further exploited in the development of novel cancer treatments.

Molecular mimicry is known to be one of the leading mechanisms by which infectious agents may induce autoimmunity. However, whether a similar mechanism triggers anti-tumor immune response is unexplored, and the role of anti-viral T-cells infiltrating the tumor has remained anecdotal. To address this question, we first developed a bioinformatic tool to identify tumor peptides with high similarity to viral epitopes. Using peptides identified by this tool, we showed that, in mice, viral pre-existing immunity enhanced the efficacy of cancer immunotherapy via molecular mimicry. Specifically, when treated with a cancer vaccine consisting of peptides with a high degree of homology with specific viral peptides, the mice with induced pre-existing immunity to these viral peptides showed significantly better anti-tumor response.To understand whether this mechanism could partly explain immunotherapy-response in humans, we analyzed a cohort of melanoma patients undergoing PD1 treatment with high IgG titer for Cytomegalovirus (CMV). In this cohort of patients, we showed that high level of CMV-antibodies was associated with a prolonged progression free survival, and found that in some cases PBMCs could cross-react with both melanoma and CMV homologous peptides. Finally, T-cell TCR sequencing revealed expansion of the same CD8+ T-cell clones, when PBMCs were pulsed with tumor- or homologous viral peptides.In conclusion, we have demonstrated that pre-existing immunity and molecular mimicry could explain part of the response observed in immunotherapy. Most importantly, we have developed a tool able to identify tumor antigens and neoantigens based on their similarity to pathogen antigens, in order to exploit molecular mimicry and cross-reactive T-cells in cancer vaccine development. Citation Format: Jacopo Chiaro, Henna Kasanen, Thomas Whalley, Cristian Capasso, Sara Feola, Mikaela Grönholm, Firas Hamdan, Karita Peltonen, Micaela Hernberg, Siru Mäkelä, Hanna Karhapää, Paul Brown, Beatriz Martins, Manlio Fusciello, Erkko Ylösmäki, Anna Kreutzman, Satu Mustjoki, Barbara Szomolay, Vincenzo Cerullo. Viral molecular mimicry influences the antitumor immune response in murine and human melanoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 1488.

Each patient's cancer has a unique molecular makeup, often comprised of distinct cancer cell subpopulations. Improved understanding of dynamic processes between cancer cell populations is therefore critical for making treatment more effective and personalized. It has been shown that immunotherapy increases the survival of melanoma patients. However, there remain critical open questions, such as timing and duration of immunotherapy and its added benefits when combined with other types of treatments. We introduce a model for the dynamics of active killer T-cells and cancer cell subpopulations. Rather than defining the cancer cell populations based on their genetic makeup alone, we consider also other, non-genetic differences that make the cell populations either sensitive or resistant to a therapy. Using the model, we make predictions of possible outcomes of the various treatment strategies in virtual melanoma patients, providing hypotheses regarding therapeutic efficacy and side-effects. It is shown, for instance, that starting immunotherapy with a denser treatment schedule may enable changing to a sparser schedule later during the treatment. Furthermore, combination of targeted and immunotherapy results in a better treatment effect, compared to mono-immunotherapy, and a stable disease can be reached with a patient-tailored combination. These results offer better understanding of the competition between T-cells and cancer cells, toward personalized immunotherapy regimens.