BACKGROUND:Effective response to vaccination requires activation of the innate immune system, triggering the synthesis of inflammatory cytokines. The degree of subjective symptoms related to this, referred to as reactogenicity, may predict their eventual immune response. However, the subjective nature of these symptoms is influenced by the nocebo effect, making it difficult to accurately quantify a person's physiologic response. The use of wearable sensors allows for the identification of objective evidence of physiologic changes a person experiences following vaccination, but as these changes are subtle, they can only be detected when an individual's pre-vaccination normal variability is considered. METHODS:We use a wearable torso sensor patch and a machine learning method of similarity-based modeling (SBM) to create a physiologic digital twin for 88 people receiving 104 COVID vaccine doses. By using each individual's pre-vaccine digital twin, we are able to effectively control for expected physiologic variations unique to that individual, leaving only vaccine-induced differences. We use these individualized differences between the pre- and post-vaccine period to develop a multivariate digital biomarker for objectively measuring the degree and duration of physiologic changes each individual experiences following vaccination. RESULTS:Here we show that the multivariate digital biomarker better predicted systemic reactogenicity than any one physiologic data type and correlated with vaccine-induced changes in humoral and cellular immunity in a 20-person subset. CONCLUSIONS:A digital biomarker is capable of objectively identifying an individual's unique response to vaccination and could play a future role in personalizing vaccine regimens.

Protective immunity to dengue virus (DENV) requires antibody response to all four serotypes. Systems vaccinology identifies a multi-OMICs pre-vaccination signature and mechanisms predictive of broad antibody responses after immunization with a tetravalent live attenuated DENV vaccine candidate (Butantan-DV/ TV003). Anti-inflammatory pathways, including TGF-b signaling expressed by CD68low low monocytes, and the metabolites phosphatidylcholine (PC) and phosphatidylethanolamine (PE) positively correlate with broadly neutralizing antibody responses against DENV. In contrast, expression of pro-inflammatory pathways and cytokines (IFN and IL-1) in CD68hi hi monocytes and primary and secondary bile acids negatively correlates with broad DENV-specific antibody responses. Induction of TGF-b and IFNs is done respectively by PC/ PE and bile acids in CD68low low and CD68hi hi monocytes. The inhibition of viral sensing by PC/PE-induced TGF-b is confirmed in vitro. . Our studies show that the balance between metabolites and the pro- or anti-inflammatory state of innate immune cells drives broad and protective B cell response to a live attenuated dengue vaccine.

Abstract Introduction High-dimension cytometry panels have become a hallmark of clinical phase 1 and 2 trials. These panels can provide hundreds of readouts and need to be combined with subject metadata (e.g., health data, demographics, timepoint, and dose) to provide insights on the identification of biomarkers. Several bioinformatics tools are available to interpret these complex datasets; however, these usually require significant expertise in data manipulation, which sometimes forces the person doing the data interpretation to outsource the data visualization and statistical analysis to a bioinformatics team. As a consequence, the scientist can be one step-removed from the “raw” data, critically preventing the interpretation of biomarker effects in the context of the raw staining profiles and associated quality controls (e.g. in-run controls). Here, we show how a new tool integrated with the CellEngine cytometry analysis software can accelerate data interpretation without removing the scientist from the raw data. Methods The visualization tool pulls live data from CellEngine, displaying both study- and cohort-level information in summary views as well as the sample-level staining profiles. As a live link, any changes made in CellEngine, such as ones to gating and compensation, or the addition of new samples during an ongoing study, are automatically reflected in the dashboard. This link also gives the ability to consult staining profiles and performance of controls directly within the tool without having to switch between applications. CellEngine is capable of analyzing 10,000s of samples at once, and thus can handle the largest of studies. Results Here, we show how the visualization tool was used to accelerate the data interpretation of two different flow cytometry assays. In the first example, lymphodepletion and immune system reconstitution in patients undergoing CAR-T cell therapy was monitored using the tool. The live update of analysed data within the tool, coupled with the ability to verify the performance of the two controls ran with each sample, accelerated the data interpretation and improved the data quality. In the second example, we show how the software was used to follow cytokines responses across different timepoints in a vaccination program where samples were analysed using a polyfunctional intra-cellular cytokine staining panel. The tool greatly accelerated the interrogation of this complex data set and allowed the identification of trends within the different T cell responses. Conclusion This new tool can help maximize the utility of high-dimensional cytometry in clinical trial analysis while allowing to keep the crucial link between graphical representation of large number of samples and the data associated with each individual flow cytometry staining profile. Citation Format: Damien Montamat-Sicotte, Zach Bjornson, Dean Franckaert, Nicholas Dupuis, Eustache Paramithiotis. Deployment of a visualization tool directly linked to the CellEngine cytometry analysis software to accelerate analysis of complex cytometry data sets in the context of ongoing clinical trials [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7434.

Effective response to vaccination requires activation of the innate immune system, triggering the synthesis of inflammatory cytokines. The subjective symptoms related to this, referred to as reactogenicity, affect a variable percentage of vaccinated people to different degrees, with evidence supporting a relationship between the severity of symptoms a person experiences and their eventual immune response. Wearable sensors allow for the identification of objective evidence of physiologic changes a person experiences in response to vaccine-induced inflammation, but as these changes are subtle, they can only be detected when an individual’s pre-vaccination normal variability is considered. We used a wearable torso sensor patch and a machine learning method of similarity-based modeling (SBM), which learns the dynamic interplay between multivariate input sources, to create a physiologic digital twin for 88 people receiving 104 vaccine doses. By effectively removing expected variations and leaving only vaccine-induced differences, we developed a multivariate digital biomarker that incorporates changes in multiple continuously monitored physiologic data streams to measure the degree and duration of vaccine induced inflammation. This objective measure correlated with subjective symptoms, and in a 20-person subset, both humoral and cellular immunogenicity.### Competing Interest StatementThe current study was sponsored by physIQ, Inc. (Chicago, IL, USA) a company that has since been purchased by Prolaio, Inc. (Scottsdale, AZ, USA). A patent was filed by physIQ for the digital biomarker described. Some co-authors are employees of the company (JS, MG, SW) or a paid consultant (SRS). HG and EP are employees of CellCarta Bioscience, Inc. (Montreal, QC, Canada).### Funding StatementThe study was funded by physIQ, Inc. (Chicago, IL, USA) a company that has since been purchased by Prolaio, Inc. (Scottsdale, AZ, USA). Some co-authors are employees of the company (JS, MG, SW) or a paid consultant (SRS).### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:The manuscript contains data from two near-identical prospective studies. The Sterling IRB gave ethical approval for the VIII study. The IRB of Purdue University gave ethical approval for the COmMON SENS study.I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesThe data obtained in the study is the property of the sponsor. Data sharing can be determined on a per case basis via request to authors.

The COVID pandemic exposed the critical role T cells play in initial immunity, the establishment and maintenance of long term protection, and of durable responsiveness against novel viral variants. A growing body of evidence indicates that adding measures of cellular immunity will fill an important knowledge gap in vaccine clinical trials, likely leading to improvements in the effectiveness of the next generation vaccines against current and emerging variants. In depth cellular immune monitoring in Phase II trials, particularly for high risk populations such as the elderly or immune compromised, should result in better understanding of the dynamics and requirements for establishing effective long term protection. Such analyses can result in cellular immunity correlates that can then be deployed in Phase III studies using appropriate, scalable technologies. Measures of cellular immunity are less established than antibodies as correlates of clinical immunity, and some misconceptions persist about cellular immune monitoring usefulness, cost, complexity, feasibility, and scalability. We outline the currently available cellular immunity assays, review their readiness for use in clinical trials, their logistical requirements, and the type of information each assay generates. The objective is to provide a reliable source of information that could be leveraged to develop a rational approach for comprehensive immune monitoring during vaccine development.

Background SARS-CoV-2 remains a world-wide health issue. SARS-CoV-2-specific immunity is induced upon both infection and vaccination. However, defining the long-term immune trajectory, especially after infection, is limited. In this study, we aimed to further the understanding of long-term SARS-CoV-2-specific immune response after infection. Results We conducted a longitudinal cohort study among 93 SARS-CoV-2 recovered individuals. Immune responses were continuously monitored for up to 20 months after infection. The humoral responses were quantified by Spike- and Nucleocapsid-specific IgG levels. T cell responses to Spike- and non-Spike epitopes were examined using both intercellular cytokine staining (ICS) assay and Activation-Induced marker (AIM) assay with quantification of antigen-specific IFNγ production. During the 20 months follow-up period, Nucleocapsid-specific antibody levels and non-Spike-specific CD4 + and CD8 + T cell frequencies decreased in the blood. However, a majority of participants maintained a durable immune responses 20 months after infection: 59% of the participants were seropositive for Nucleocapsid-specific IgG, and more than 70% had persisting non-Spike-specific T cells. The Spike-specific response initially decreased but as participants were vaccinated against COVID-19, Spike-specific IgG levels and T cell frequencies were boosted reaching similar or higher levels compared to 1 month post-infection. The trajectory of infection-induced SARS-CoV-2-specific immunity decreases, but for the majority of participants it persists beyond 20 months. The T cell response displays a greater durability. Vaccination boosts Spike-specific immune responses to similar or higher levels as seen after primary infection. Conclusions For most participants, the response persists 20 months after infection, and the cellular response appears to be more long-lived compared to the circulating antibody levels. Vaccination boosts the S-specific response but does not affect the non-S-specific response. Together, these findings support the understanding of immune contraction, and with studies showing the immune levels required for protection, adds to the knowledge of durability of protection against future SARS-CoV-2.

Neuroendocrine tumors constitute a heterogeneous group of tumors arising from hormone-secreting cells and are generally associated with a dysfunction of secretion. Pheochromocytoma (Pheo) is a neuroendocrine tumor that develops from chromaffin cells of the adrenal medulla, and is responsible for an excess of catecholamine secretion leading to severe clinical symptoms such as hypertension, elevated stroke risk and various cardiovascular complications. Surprisingly, while the hypersecretory activity of Pheo is well known to pathologists and clinicians, it has never been carefully explored at the cellular and molecular levels. In the present study, we have combined catecholamine secretion measurement by carbon fiber amperometry on human tumor cells directly cultured from freshly resected Pheos, with the analysis by mass spectrometry of the exocytotic proteins differentially expressed between the tumor and the matched adjacent non-tumor tissue. In most patients, catecholamine secretion recordings from single Pheo cells revealed a higher number of exocytic events per cell associated with faster kinetic parameters. Accordingly, we unravel significant tumor-associated modifications in the expression of key proteins involved in different steps of the calcium-regulated exocytic pathway. Altogether, our findings indicate that dysfunction of the calcium-regulated exocytosis at the level of individual Pheo cell is a cause of the tumor-associated hypersecretion of catecholamines.

COVID-19 vaccine clinical development was conducted with unprecedented speed. Immunity measurements were concentrated on the antibody response which left significant gaps in our understanding how robust and long-lasting immune protection develops. Better understanding the cellular immune response will fill those gaps, especially in the elderly and immunocompromised populations which not only have the highest risk for severe infection, but also frequently have inadequate antibody responses. Although cellular immunity measurements are more logistically complex to conduct for clinical trials compared to antibody measurements, the feasibility and benefit of doing them in clinical trials has been demonstrated and so should be more widely adopted. Adding significant cellular response metrics will provide a deeper understanding of the overall immune response to COVID-19 vaccination, which will significantly inform vaccination strategies for the most vulnerable populations. Better monitoring of overall immunity will also substantially benefit other vaccine development efforts, and indeed any therapies that involve the immune system as part of the therapeutic strategy.

Abstract Background To curb the tuberculosis (TB) epidemic, new cases must be prevented. Preventive therapy is an effective intervention but treating all individuals with latent TB infection (LTBI) based on current diagnostics, tuberculin skin test (TST) and interferon gamma release assay (IGRA), is not feasible. Using proteomic analysis we are developing a peripheral blood marker of LTBI infection that would identify people at high risk for TB progression. Methods Plasma was collected in an ongoing TB household contact study in Kampala, Uganda in which TST-/IGRA- are enrolled and followed for IGRA/TST conversion. Longitudinal sample sets (0,6,12 months) from 81 participants including 24 TST/IGRA converters, 29 resisters (remained TST/IGRA negative), and 28 baseline positives (LTBI) underwent proteomic and multiplex cytokine analysis. Proteomic analysis was performed by multiple reaction monitoring mass spectrometry (MRM-MS) using an MRM-MS assay containing 163 host proteins represented by 392 unique peptides, all of which we have described to significantly change during Mtb infection in our previous study of household contact converters. Results Differential expression of proteins measured by MRM-MS and cytokine assays were assessed. The largest number of significant changes were measured in the LTBI vs Converter comparison. The vast majority of the changes were elevated expression in the converter group compared to the latent group, suggesting that all the biologies affected were induced in the converters (Figure 1). We identified protein panels that were able to predict conversion as in our earlier study. However, the protein panels defined in our earlier study that could distinguish a future converter from a future resister with high fidelity did not have a similar performance in this study. Figure 1Differential expression analysis of latent TB, LTBI vs. converter. Significant changes by both p-value (set at 0.05) and q-value (a correction for multiple comparisons, set at 0.10). Conclusion Peripheral blood protein changes are associated with conversion to LTBI. In this study we found that the protein panels predictive of conversion were different from our previous study. While there are many possible reasons, an important difference between the two studies was the definition of conversion: TST in the older study and QuantiFERON in the current study. We are continuing to investigate this difference and developing time-sensitive protein panels to capture recent conversion. Disclosures Eustache Paramithiotis, PhD, CellCarta Biosciences: Employee.

First-generation anit-SARS-CoV-2 vaccines were highly successful. They rapidly met an unforeseen emergency need, saved millions of lives, and simultaneously eased the burden on healthcare systems worldwide. The first-generation vaccines, however, focused too narrowly on antibody-based immunity as the sole marker of vaccine trial success, resulting in large knowledge gaps about waning vaccine protection, lack of vaccine robustness to viral mutation, and lack of efficacy in immunocompromised populations. Detailed reviews of first-generation vaccines, including their mode of action and geographical distribution, have been published elsewhere. Second-generation clinical trials must address these gaps by evaluating a broader range of immune markers, including those representing cell-mediated immunity, to ensure the most protective and long-lasting vaccines are brought to market.

Development of fully protective dengue virus (DV) vaccines has been problematic as infection with DV requires a broad antibody immune response that targets all 4 possible serotypes. Herein, we used an integrated systems vaccinology approach to identify prevaccination features that allow the development of fully protective DV-specific antibody responses. This approach allowed us to identify a transcription network in a subset of monocytes defined by the expression of CD68 and downstream of specific pro- and anti-inflammatory cytokines. Moreover, we identified metabolites as drivers of an immune response that induced neutralizing antibodies to the 4 DV serotypes. Specifically, PC/PE drove the production of TGF-B in CD68 low monocytes, which was a positive correlate of the protective antibody response. In contrast, primary and secondary bile acids triggered a proinflammatory response downstream of TGR5 signaling and inflammasome activation in CD68 high monocytes, which was associated to a non-protective antibody response. These features were validated in vitro in primary myeloid cells. Our results highlight the role of cell and systemic metabolism as regulators of protective immune responses to vaccination, and that systems vaccinology is a key tool to identify such mechanisms.

MS-based immunopeptidomics is maturing into an automatized and high-throughput technology, producing small- to large-scale datasets of clinically relevant major histocompatibility complex (MHC) class I-associated and class II-associated peptides. Consequently, the development of quality control (QC) and quality assurance systems capable of detecting sample and/or measurement issues is important for instrument operators and scientists in charge of downstream data interpretation. Here, we created MhcVizPipe (MVP), a semiautomated QC software tool that enables rapid and simultaneous assessment of multiple MHC class I and II immunopeptidomic datasets generated by MS, including datasets generated from large sample cohorts. In essence, MVP provides a rapid and consolidated view of sample quality, composition, and MHC specificity to greatly accelerate the "pass-fail" QC decision-making process toward data interpretation. MVP parallelizes the use of well-established immunopeptidomic algorithms (NetMHCpan, NetMHCIIpan, and GibbsCluster) and rapidly generates organized and easy-to-understand reports in HTML format. The reports are fully portable and can be viewed on any computer with a modern web browser. MVP is intuitive to use and will find utility in any specialized immunopeptidomic laboratory and proteomics core facility that provides immunopeptidomic services to the community.

Pheochromocytoma (Pheo) is a neuroendocrine tumor that develops from chromaffin cells of the adrenal medulla, and is responsible of an excess of catecholamines secretion leading to severe clinical symptoms such as hypertension, elevated stroke risk and various cardiovascular complications. Surprisingly, hypersecretory activity of Pheo has never been explored at the cellular and molecular levels from individual tumor cells. In the present study, we have combined catecholamine secretion measurement by carbon fiber amperometry on human tumor cells directly cultured from freshly resected Pheo, with the analysis by mass spectrometry of the exocytotic proteins differentially expressed between the tumor and the matched adjacent non-tumor tissue. Catecholamine secretion recordings from individual Pheo cells obtained from most patients reveal a higher number of exocytic events per cell associated with faster kinetic parameters. Accordingly, we unravel significant tumor-associated modifications in the expression of key proteins involved in different steps of the calcium-regulated exocytic pathway. Altogether, our findings indicate that dysfunction of the calcium-regulated exocytosis at the level of individual Pheo cell is a cause of the tumor-associated hypersecretion of catecholamines.

Recombinant DNA technology has, in the last decades, contributed to a vast expansion of the use of protein drugs as pharmaceutical agents. However, such biological drugs can lead to the formation of anti-drug antibodies (ADAs) that may result in adverse effects, including allergic reactions and compromised therapeutic efficacy. Production of ADAs is most often associated with activation of CD4 T cell responses resulting from proteolysis of the biotherapeutic and loading of drug-specific peptides into major histocompatibility complex (MHC) class II on professional antigen-presenting cells. Recently, readouts from MHC-associated peptide proteomics (MAPPs) assays have been shown to correlate with the presence of CD4 T cell epitopes. However, the limited sensitivity of MAPPs challenges its use as an immunogenicity biomarker. In this work, MAPPs data was used to construct an artificial neural network (ANN) model for MHC class II antigen presentation. Using Infliximab and Rituximab as showcase stories, the model demonstrated an unprecedented performance for predicting MAPPs and CD4 T cell epitopes in the context of protein-drug immunogenicity, complementing results from MAPPs assays and outperforming conventional prediction models trained on binding affinity data.

The objective of this study was to identify blood-based protein biomarkers of early stage Mycobacterium tuberculosis (Mtb) infection. We utilized plasma and serum specimens from TB patients and their contacts (age≥12) enrolled in a household contact study in Uganda. In the discovery phase cross-sectional samples from 104 HIV-uninfected persons classified as either active TB, latent Mtb infection (LTBI), tuberculin skin test (TST) converters, or persistent TST-negative were analyzed. Two hundred eighty-nine statistically significant (false discovery rate corrected p<0.05) differentially expressed proteins were identified across all comparisons. Proteins associated with cellular immunity and lipid metabolism were induced early after Mtb infection. One hundred and fifty-nine proteins were selected for a targeted mass spectrometry assay. A set of longitudinal samples from 52 TST-negative subjects who converted to TST-positive or remained TST-negative were analyzed, and multivariate logistic regression was used to identify unique protein panels able to predict TST conversion with cross-validated AUC>0.85. Panel performance was confirmed with an independent validation set of longitudinal samples from 16 subjects. These candidate protein biomarkers may allow for the identification of recently Mtb infected individuals at highest risk for developing active TB and most likely to benefit from preventive therapy.