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Background Heterogeneity and lack of targeted therapies represent the two main impediments to precision treatment of triple-negative breast cancer (TNBC), and therefore, molecular subtyping and identification of therapeutic pathways are required to optimize medical care. The aim of the present study was to define robust TNBC subtypes with clinical relevance. Methods Gene expression profiling by means of DNA chips was conducted in an internal TNBC cohort composed of 238 patients. In addition, external data ( n  = 257), obtained by using the same DNA chip, were used for validation. Fuzzy clustering was followed by functional annotation of the clusters. Immunohistochemistry was used to confirm transcriptomics results: CD138 and CD20 were used to test for plasma cell and B lymphocyte infiltrations, respectively; MECA79 and CD31 for tertiary lymphoid structures; and UCHL1/PGP9.5 and S100 for neurogenesis. Results We identified three molecular clusters within TNBC: one molecular apocrine (C1) and two basal-like-enriched (C2 and C3). C2 presented pro-tumorigenic immune response (immune suppressive), high neurogenesis (nerve infiltration), and high biological aggressiveness. In contrast, C3 exhibited adaptive immune response associated with complete B cell differentiation that occurs in tertiary lymphoid structures, and immune checkpoint upregulation. External cohort subtyping by means of the same approach proved the robustness of these results. Furthermore, plasma cell and B lymphocyte infiltrates, tertiary lymphoid structures, and neurogenesis were validated at the protein levels by means of histological evaluation and immunohistochemistry. Conclusion Our work showed that TNBC can be subcategorized in three different subtypes characterized by marked biological features, some of which could be targeted by specific therapies.

Immunotherapies are rapidly being integrated into standard of care (SOC) therapy in conjunction with surgery, chemotherapy, and radiotherapy for many cancers and a large number of clinical studies continue to explore immunotherapy alone and as part of combination therapies in patients with cancer. It is evident that clinical effectiveness of immunotherapy is limited to a subset of patients and improving immunotherapy related outcomes remains a major scientific and clinical effort. Understanding the immune cell subset phenotype and activation/functional status (cellular immunome) prior to and post therapy is therefore critical to develop biomarkers that (1) will predict if a patient will respond to immunotherapy and (2) are a result of immunotherapy. In this study, we investigated local (tumor) and peripheral (blood) cellular immunome of patients with melanoma, breast cancer, and brain cancer using a rapid and reliable standardized, multiparameter flow cytometry assay. We used this approach to monitor changes in the peripheral cellular immunome in women with breast cancer undergoing SOC therapy. Our analysis is unique because it is conducted using matched fresh tumor tissue and blood from patients in real-time, within 2-3 h of sample acquisition, and provides insight into the innate and adaptive immune cell profile in blood and tumor. Specific to blood, this approach involves no manipulation and evaluates all immune subsets such as T cells, B cells, natural killer (NK) cells, monocytes, dendritic cells (DCs), neutrophils, eosinophils, and basophils using 0.5 ml of blood. Analysis of the corresponding tumor provides much needed insight into the phenotype and activation status of immune cells, especially T and B cells, in the tumor microenvironment vs. the periphery. This analysis will be used to assess baseline and therapy-mediated changes in local and peripheral cellular immunome in patients with glioblastoma, breast cancer, and melanoma in planned immunotherapy clinical studies.

It is increasingly clear that an extraordinarily diverse range of clinically important conditions—including infections, vaccinations, autoimmune diseases, transplants, transfusion reactions, aging, and cancers—leave telltale signatures in the millions of V(D)J-rearranged antibody and T cell receptor [TR per the Human Genome Organization (HUGO) nomenclature but more commonly known as TCR] genes collectively expressed by a person’s B cells (antibodies) and T cells. We refer to these as the immunome . Because of its diversity and complexity, the immunome provides singular opportunities for advancing personalized medicine by serving as the substrate for a highly multiplexed, near-universal blood test. Here we discuss some of these opportunities, the current state of immunome-based diagnostics, and highlight some of the challenges involved. We conclude with a call to clinicians, researchers, and others to join efforts with the Adaptive Immune Receptor Repertoire Community (AIRR-C) to realize the diagnostic potential of the immunome.

Longitudinal sampling of tumor tissue from patients with solid cancers, aside from melanoma and a few other cases, is often unfeasible, and thus may not capture the plasticity of interactions between the tumor and immune system under selective pressure of a given therapy. Peripheral blood analyses provide salient information about the human peripheral immunome while offering technical and practical advantages over traditional tumor biopsies, and should be utilized where possible alongside interrogation of the tumor. Some common blood-based biomarkers used to study the immune response include immune cell subsets, circulating tumor DNA, and protein analytes such as cytokines. With the recent explosion of immune checkpoint inhibitors (ICI) as a modality of treatment in multiple cancer types, soluble immune checkpoints have become a relevant area of investigation for peripheral immune-based biomarkers. However, the exact functions of soluble immune checkpoints and their roles in cancer for the most part remain unclear. This review discusses current literature on the production, function, and expression of nine soluble immune checkpoints – sPD-L1, sPD-1, sCTLA4, sCD80, sTIM3, sLAG3, sB7-H3, sBTLA, and sHVEM – in patients with solid tumors, and explores their role as biomarkers of response to ICI as well as to conventional therapies (chemotherapy, radiotherapy, targeted therapy, and surgery) in cancer patients.

The immune cellular landscape from the gastric mucosa remains largely unknown despite its relevance in several inflammatory conditions. Human gastric biopsies were obtained from the antrum, body and incisura from 10 individuals to obtain lamina propria mononuclear cells that were further characterized by spectral cytometry. Phenotypic hierarchical analyses identified a total of 52 different immune cell subsets within the human gastric mucosa revealing that T-cells (> 60%) and NK cells (> 20%) were the main populations. Within T-cells, CD4 + and CD8 + were equally represented with both subsets displaying mainly a memory and effector phenotype. NK cells, on the contrary, were largely of the early phenotype. No regional differences were observed for any subsets among the 3 locations. Following unsupervised analysis, a total of 82 clusters were found. Again, no differences were observed amongst locations although a great degree of inter-individual variability was found, largely influenced by the presence of H. pylori infection and dyspepsia. We have unraveled the human gastric immune cellular subset composition and a unique interindividual immune fingerprint with no inter-regional variations.

Tumor immune microenvironment (TIME) plays a key role to understand how tumors respond to prostate cancer (PC) therapies and potential mechanisms of resistance. Previous research has suggested that specific genomic aberrations, such as microsatellite instability (MSI) or CDK12 bi-allelic loss can allow PC patients more likely to respond to immune checkpoint inhibitors (ICI) or other immune therapies. However, responses to these treatments remain highly variable even in selected patients. Thus, it is essential to obtain more information about tumor immune cells that infiltrate these tumors, and on their plasticity and interactions, in order to better understand the underlying biology to allow development of new therapeutic strategies. This review analyzes: 1) How interactions among immune cell populations and other cells infiltrating the tumor stroma can modulate the progression of PC, 2) How the standard therapies to treat PC (such as androgen deprivation therapy, new androgen-directed hormone therapy or chemotherapy) may influence the dynamic changes of the immunome and 3) What are the limitations in characterizing the immune landscape of the host´s response to tumors.

Zika virus (ZIKV) can be vertically transmitted during pregnancy resulting in a range of adverse pregnancy outcomes. The decidua is commonly found to be infected by ZIKV, yet the acute immune response to infection remains understudied in vivo . We hypothesized that in vivo African-lineage ZIKV infection induces a pro-inflammatory response in the decidua. To test this hypothesis, we evaluated the decidua in pregnant rhesus macaques within the first two weeks following infection with an African-lineage ZIKV and compared our findings to gestationally aged-matched controls. Decidual leukocytes were phenotypically evaluated using spectral flow cytometry, and cytokines and chemokines were measured in tissue homogenates from the decidua, placenta, and fetal membranes. The results of this study did not support our hypothesis. Although ZIKV RNA was detected in the decidual tissue samples from all ZIKV infected dams, phenotypic changes in decidual leukocytes and differences in cytokine profiles suggest that the decidua undergoes mild anti-inflammatory changes in response to that infection. Our findings emphasize the immunological state of the gravid uterus as a relatively immune privileged site that prioritizes tolerance of the fetus over mounting a pro-inflammatory response to clear infection.

Coronavirus disease 2019 (COVID-19) affects the population unequally, with a greater impact on older and immunosuppressed people. Hence, we performed a prospective experimental cohort study to characterise the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccination in immune-compromised patients (older adults and oncohaematologic patients), compared with healthy counterparts, based on deep characterisation of the circulating immune cell subsets. While acquired humoral and cellular memory did not predict subsequent infection 18 months after full vaccination, spectral and computational cytometry revealed several subsets within the CD8 T-cells, B-cells, natural killer (NK) cells, monocytes and TEMRA Tγδ cells that were differentially expressed in individuals who were subsequently infected and not infected not just following immunisation, but also prior to vaccination. Of note, we found up to seven clusters within the TEMRA Tγδ cell population, with some of them being expanded and others decreased in subsequently infected individuals. Moreover, some of these cellular clusters were also related to COVID-19-induced hospitalisation in oncohaematologic patients. Therefore, we have identified a cellular signature that even before vaccination is related to COVID-19 vulnerability as opposed to the acquisition of cellular and/or humoral memory following vaccination with SARS-CoV-2 messenger RNA (mRNA) vaccines.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating chronic condition with no identified diagnostic biomarkers to date. Its prevalence is as high as 0.89% according to metastudies, with a quarter of patients bed- or home-bound, which presents a serious public health challenge. Investigations into the inflammation-immunity axis is encouraged by links to outbreaks and disease waves. Recently, the research of our group revealed that antibodies to beta2-adrenergic (anti-β2AdR) and muscarinic acetylcholine (anti-M4) receptors demonstrate sensitivity to the progression of ME/CFS. The purpose of this study is to investigate the joint potential of inflammatome-characterized by interferon (IFN)- , tumor necrosis factor (TNF)-α, interleukin (IL)-2, IL-21, Il-23, IL-6, IL-17A, Activin-B, immunome (IgG1, IgG2, IgG3, IgG4, IgM, and IgA), and receptor-based biomarkers (anti-M3, anti-M4, and anti-β2AdR)-for evaluating ME/CFS progression, and to identify an optimal selection for future validation in prospective clinical studies. A dataset was used originating from 188 individuals, namely, 54 healthy controls, 30 patients with a \"mild\" condition, 73 patients with a \"moderate\" condition, and 31 patients with a \"severe\" condition, clinically assessed by Fukuda/CDC 1994 and international consensus criteria. Inflammatome, immunome, and receptor-based biomarkers were determined in blood plasma via ELISA and multiplex methods. Statistical analysis was done via correlation analysis, principal component analysis, linear discriminant analysis, and random forest classification; inter-group differences were tested via nonparametric Kruskal-Wallis test followed by the two-stage linear step-up procedure of Benjamini, Krieger, and Yekutieli, and via Mann-Whitney test. The association between inflammatome and immunome markers is broader and stronger (coupling) in the severe group. Principal component factoring separates components associated with inflammatome, immunome, and receptor biomarkers. Random forest modeling demonstrates an excellent accuracy of over 90% for splitting healthy/with condition groups, and 45% for splitting healthy/severity groups. Classifiers with the highest potential are anti-β2AdR, anti-M4, IgG4, IL-2, and IL-6. The association between inflammatome and immunome markers is a candidate for controlled clinical study of ME/CFS progression markers that could be used for treatment individualization. Thus, the coupling effects between inflammation and immunity are potentially beneficial for the identification of prognostic factors in the context of ME/CFS progression mechanism studies.

The aim of the study was to characterize the circulating immunome of patients with EoE before and after proton pump inhibitor (PPI) treatment in order to identify potential non-invasive biomarkers of treatment response. PBMCs from 19 healthy controls and 24 EoE patients were studied using a 39-plex spectral cytometry panel. The plasmacytoid dendritic cell (pDC) population was differentially characterized by spectral cytometry analysis and immunofluorescence assays in esophageal biopsies from 7 healthy controls and 13 EoE patients. Interestingly, EoE patients at baseline had lower levels of circulating pDC compared with controls. Before treatment, patients with EoE who responded to PPI therapy had higher levels of circulating pDC and classical monocytes, compared with non-responders. Moreover, following PPI therapy pDC levels were increased in all EoE patients, while normal levels were only restored in PPI-responding patients. Finally, circulating pDC levels inversely correlated with peak eosinophil count and pDC count in esophageal biopsies. The number of tissue pDCs significantly increased during active EoE, being even higher in non-responder patients when compared to responder patients pre-PPI. pDC levels decreased after PPI intake, being further restored almost to control levels in responder patients post-PPI. We hereby describe a unique immune fingerprint of EoE patients at diagnosis. Moreover, circulating pDC may be also used as a novel non-invasive biomarker to predict subsequent response to PPI treatment.