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Cancers display significant heterogeneity with respect to tissue of origin, driver mutations, and other features of the surrounding tissue. It is likely that individual tumors engage common patterns of the immune system-here "archetypes"-creating prototypical non-destructive tumor immune microenvironments (TMEs) and modulating tumor-targeting. To discover the dominant immune system archetypes, the University of California, San Francisco (UCSF) Immunoprofiler Initiative (IPI) processed 364 individual tumors across 12 cancer types using standardized protocols. Computational clustering of flow cytometry and transcriptomic data obtained from cell sub-compartments uncovered dominant patterns of immune composition across cancers. These archetypes were profound insofar as they also differentiated tumors based upon unique immune and tumor gene-expression patterns. They also partitioned well-established classifications of tumor biology. The IPI resource provides a template for understanding cancer immunity as a collection of dominant patterns of immune organization and provides a rational path forward to learn how to modulate these to improve therapy.

Fetal life and early infancy are recognized as a critical period to shape the immune system for life. Slowly the neonatal immune system changes its regulatory responses into effector responses. Genes, environmental factors and the interaction between both, the epigenome, will influence this maturation process and different developmental trajectories might be initiated leading to disease pathways. This concept has been recognized in the 1000 days campaign and the WHO’s Every Newborn Action Plan but pathophysiological mechanisms supporting this theory are mostly unidentified. In this thesis, it is pitched that immune homeostasis in early life is (partly) achieved by the unique increased ability of neonatal immunity to induce adaptive immune tolerance and that innate cells play an important role in driving this mechanism. Indeed, the predilection of neonatal naive CD4+ T cells to differentiate into FOXP3+ Tregs, in which PD-1/PD-L1 interactions play a role through a mechanism involving PKB signaling (chapter 2), and the inability to differentiate into TH17 cells, which is blocked at the level of RORC2 (chapter 3), confirmed a profound programmed development of na.ve T cells upon activation and their role in the development of immune tolerance in early life. Neonatal T cells develop the capacity to differentiate into TH17 cells during the first 3 months and retained a propensity to become Treg cells until the age of at least 12 months (chapter 4). However, IL-17, as well as high levels of IL-6 and TNFα are produced in vivo during severe neonatal infections, when strong pro-inflammatory stimuli are present. Thus, deficient innate and effector responses in neonates are partial and can be overcome once innate stimuli are strong enough (chapter 5). System immunology, provided that it is standardized in use (chapter 6), enables identification of divergent patterns in immune maturation related to long term health outcomes. It is crucial for long term health outcomes to protect and secure this programmed, age-dependent and stereotypic immune development. Therefore, unnecessary (longtime) antibiotic treatment should be avoided since this will disturb proper immune development by means of destruction of the composition of the microbiome and subsequently affects proper immune maturation. Development and clinical implementation of better diagnostic tools to identify or exclude neonatal sepsis are mandatory to secure future health outcomes.

Natalizumab (NTZ) and autologous hematopoietic stem cell transplantation (AHSCT) are two successful treatments for relapsing-remitting multiple sclerosis (RRMS), an autoimmune T-cell-driven disorder affecting the central nervous system that is characterized by relapses interspersed with periods of complete or partial recovery. Both RRMS treatments have been documented to impact T-cell subpopulations and the T-cell receptor (TCR) repertoire in terms of clone frequency, but, so far, the link between T-cell naive and memory populations, autoimmunity, and treatment outcome has not yet been established hindering insight into the post-treatment TCR landscape of MS patients. To address this important knowledge gap, we tracked peripheral T-cell subpopulations (naïve and memory CD4+ and CD8+) across 15 RRMS patients before and after two years of continuous treatment (NTZ) and a single treatment course (AHSCT) by high-throughput TCRß sequencing. We found that the two MS treatments left treatment-specific multidimensional traces in patient TCRß repertoire dynamics with respect to clonal expansion, clonal diversity and repertoire architecture. Comparing MS TCR sequences with published datasets suggested that the majority of public TCRs belonged to virus-associated sequences. In summary, applying multi-dimensional computational immunology to a TCRß dataset of treated MS patients, we show that qualitative changes of TCRß repertoires encode treatment-specific information that may be relevant for future clinical trials monitoring and personalized MS follow-up, diagnosis and treatment regimes. Natalizumab (NTZ) and autologous hematopoietic stem cell transplantation (AHSCT) are two successful treatments for relapsing–remitting multiple sclerosis (RRMS), an autoimmune T-cell–driven disorder affecting the central nervous system that is characterized by relapses interspersed with periods of complete or partial recovery. Both RRMS treatments have been documented to impact T-cell subpopulations and the T-cell receptor (TCR) repertoire in terms of clone frequency, but, so far, the link between T-cell naive and memory populations, autoimmunity, and treatment outcome has not yet been established hindering insight into the posttreatment TCR landscape of MS patients. To address this important knowledge gap, we tracked peripheral T-cell subpopulations (naive and memory CD4+ and CD8+) across 15 RRMS patients before and after 2 years of continuous treatment (NTZ) and a single treatment course (AHSCT) by high-throughput TCRβ sequencing. We found that the two MS treatments left treatment-specific multidimensional traces in patient TCRβ repertoire dynamics with respect to clonal expansion, clonal diversity, and repertoire architecture. Comparing MS TCR sequences with published datasets suggested that the majority of public TCRs belonged to virus-associated sequences. In summary, applying multidimensional computational immunology to a TCRβ dataset of treated MS patients, we show that qualitative changes of TCRβ repertoires encode treatment-specific information that may be relevant for future clinical trials monitoring and personalized MS follow-up, diagnosis, and treatment regimens.