The science and medicine of human immunology

Biochemical and hematological reference intervals in rhesus and cynomolgus macaques and implications for vaccine and drug development

Nonhuman primates have a key role in the evaluation of novel therapeutics including vaccine and drug development. Monitoring biochemical and hematological parameters of macaques is critical to understand toxicity and safety, but general reference intervals following standardized guidelines remain to be determined. Here we compiled multiple internal datasets to define normal ranges of classical biochemical and hematological parameters in Indian and Chinese rhesus macaques as well as cynomolgus macaques. Furthermore, the combination of hematological data with phenotypic information of cells obtained by flow cytometry enabled analyses of specific immune cell subsets. We found that vaccination generally induced transient changes at 24 h in cell frequencies accompanied by fluctuation in selected liver enzymes and metabolites. However, most parameters remained within our identified reference intervals. These deviations did not lead to noticeable side effects. Fluctuation in selected biochemical and hematological parameters was accompanied with differentiation of CD14+CD16+ intermediate monocytes and upregulation of genes associated with interleukin-1 signaling. By contrast, two animals with noticeable side effects showed sustained deviations. This study provides insights into baseline and vaccine-induced biochemical and hematological profiles of healthy macaques, facilitating the interpretation of toxicity and safety assessments in preclinical trials of novel therapies.

Type 1 Diabetes: A Guide to Autoimmune Mechanisms for Clinicians

Type 1 diabetes (T1D) results from the destruction of pancreatic beta cells by autoreactive T lymphocytes, leading to insulin deficiency and lifelong insulin dependence. It develops in genetically predisposed individuals, triggered by environmental or immunological factors. Although the exact causes of T1D remain unknown, the autoimmune pathogenesis of the disease is clearly indicated by the genetic risk conferred by allelic human leukocyte antigens (HLA), the almost obligatory presence of islet cell autoantibodies (AAbs) and immune cell infiltration of pancreatic islets from patients. At the same time, epidemiological data point to a role of environmental factors, notably enteroviral infections, in the disease, although precise causative links between specific pathogens and T1D have been difficult to establish. Studies of human pancreas organs from patients made available through repositories and the advent of high-dimensional high-throughput technologies for genomic and proteomic studies have significantly elucidated our understanding of the disease in recent years and provided mechanistic insights that can be exploited for innovative targeted therapeutic approaches. This short overview will summarise current salient knowledge on immune cell and beta cell dysfunction in T1D pathogenesis. PLAIN LANGUAGE SUMMARY: Type 1 diabetes (T1D) is a chronic disease where the body's own immune system attacks and destroys the insulin-producing beta cells in the pancreas. This leads to a lack of insulin, a hormone essential for regulating blood sugar, which means people with T1D need insulin for life. The disease can develop at any age but is most diagnosed in children and young adults. Despite advances in treatment, T1D still significantly reduces life expectancy, especially in countries with fewer healthcare resources. T1D develops in people with a genetic predisposition, often triggered by environmental factors such as viral infections or changes in the gut microbiome. The disease progresses silently through three stages: Stage 1: Autoantibodies to beta cell components appear, signalling the immune system is reacting against the pancreas, but there are no symptoms; Stage 2: Beta cell function starts to decline, but fasting blood sugar is still normal; Stage 3: Enough beta cells are destroyed that fasting blood sugar rises, and symptoms of diabetes appear. The risk of progressing from stage 1 to full-blown diabetes is about 35-50% within five years, and even higher from stage 2. Over 60 genes are linked to T1D risk, most of which affect how the immune system works. The strongest genetic risk comes from specific versions of histocompatibility genes, which help the immune system distinguish between the body's own cells and invaders. Some types of these genes make it easier for the immune system to mistakenly attack beta cells. However, 90% of people diagnosed with T1D have no family member with T1D, showing that genetics is only part of the story. Environmental factors also play a big role. For example, certain viral infections, especially with viruses infecting the intestine, are associated with a higher risk of developing T1D. The gut microbiome - the community of bacteria living in our intestines - also influences risk, with healthier, more diverse microbiomes appearing to offer some protection. In T1D, immune cells - especially so-called T lymphocytes - mistake beta cells in the pancreas for threats and destroy them. This process is called autoimmunity. The attack is often reflected by the presence of autoantibodies against proteins found in beta cells. Over time, as more beta cells are lost, the body can no longer produce enough insulin, leading to the symptoms of diabetes. Interestingly, not all people with T1D have the same pattern of disease. For example, children diagnosed before age 7 often have more aggressive disease, more autoantibodies, and stronger genetic risk factors than those diagnosed later. Much of our understanding of T1D has come from studying animal models, but new technologies now allow researchers to study human pancreas tissue and blood immune cells in greater detail. Scientists are also exploring how the gut microbiome, diet, and environmental exposures contribute to T1D risk and progression. Treatment currently focuses on replacing insulin, but researchers are working on therapies that target the immune system or aim to protect or replace beta cells. Strategies include immunotherapy, gene therapy, and even modifying the gut microbiome. The goal is to prevent or reverse the disease, not just manage its symptoms. In summary, T1D is a complex autoimmune disease influenced by both genes and the environment. It progresses silently before symptoms appear, and while insulin therapy is life-saving, new research is paving the way for treatments that could one day halt or even prevent the disease.

Human naïve B cells show evidence of anergy and clonal redemption following vaccination

In an era of predicted emerging pandemics, the production of effective vaccines may require an in-depth understanding of the biology of human naive B (BN) cells. Here we provide evidence that the majority of BN cells expressed CD73, an ecto-5'-nucleotidase often associated with immune cell suppression, and demonstrated features of anergy, including an IgMlowIgD+ surface phenotype, reduced calcium flux in response to IgM crosslinking, and increased PTEN expression. Analysis of antibody sequences encoded by the inherently autoreactive VH4-34 heavy chain produced by plasmablasts seven days following influenza vaccination showed that in younger but not in older individuals, anergic BN cells provided a reservoir of B cells capable of responding to vaccination by somatic mutation, resulting in diversification and loss of autoreactivity. These results suggest that effective human vaccines may require the ability to awaken or 'redeem' anergic BN cells that can be repurposed to participate in pathogen-specific responses.

Altered baseline immunological state and impaired immune response to SARS-CoV-2 mRNA vaccination in lung transplant recipients

The effectiveness of COVID-19 mRNA vaccines is diminished in organ transplant patients. Using a multi-omics approach, we investigate the immunological state of lung transplant (LTX) recipients at baseline and after SARS-CoV-2 mRNA vaccination compared to healthy controls (HCs). LTX patients exhibit a baseline immune profile resembling severe COVID-19 and sepsis, characterized by elevated pro-inflammatory cytokines (e.g., EN-RAGE [also known as S100A12], interleukin [IL]-6), reduced human leukocyte antigen (HLA)-DR expression on monocytes and dendritic cells, impaired cytokine production, and increased plasma microbial products. Single-cell RNA sequencing identifies an enriched monocyte cluster in LTX patients marked by high S100A family expression and reduced cytokine and antigen presentation genes. Post vaccination, LTX patients show diminished antibody, B cell, and T cell responses, along with blunted innate immune signatures. Integrative analysis links these altered baseline immunological features to impaired vaccine responses. These findings provide critical insights into the immunosuppressed condition of LTX recipients and their reduced vaccine-induced adaptive and innate immune responses.

Immunocytes in the tumor microenvironment: recent updates and interconnections

The tumor microenvironment (TME) is a complex, dynamic ecosystem where tumor cells interact with diverse immune and stromal cell types. This review provides an overview of the TME's evolving composition, emphasizing its transition from an early pro-inflammatory, immune-promoting state to a later immunosuppressive milieu characterized by metabolic reprogramming and hypoxia. It highlights the dual roles of key immunocytes-including T lymphocytes, natural killer cells, macrophages, dendritic cells, and myeloid-derived suppressor cells-which can either inhibit or support tumor progression based on their phenotypic polarization and local metabolic conditions. The article further elucidates mechanisms of immune cell plasticity, such as the M1/M2 macrophage switch and the balance between effector T cells and regulatory T cells, underscoring their impact on tumor growth and metastasis. Additionally, emerging therapeutic strategies, including checkpoint inhibitors and chimeric antigen receptor (CAR) T and NK cell therapies, as well as approaches targeting metabolic pathways, are discussed as promising avenues to reinvigorate antitumor immunity. By integrating recent molecular insights and clinical advancements, the review underscores the importance of deciphering the interplay between immunocytes and the TME to develop more effective cancer immunotherapies.

A systems biology approach to define SARS-CoV-2 correlates of protection

Correlates of protection (CoPs) for SARS-CoV-2 have yet to be sufficiently defined. This study uses the machine learning platform, SIMON, to accurately predict the immunological parameters that reduced clinical pathology or viral load following SARS-CoV-2 challenge in a cohort of 90 non-human primates. We found that anti-SARS-CoV-2 spike antibody and neutralising antibody titres were the best predictors of clinical protection and low viral load in the lung. Since antibodies to SARS-CoV-2 spike showed the greatest association with clinical protection and reduced viral load, we next used SIMON to investigate the immunological features that predict high antibody titres. It was found that a pre-immunisation response to seasonal beta-HCoVs and a high frequency of peripheral intermediate and non-classical monocytes predicted low SARS-CoV-2 spike IgG titres. In contrast, an elevated T cell response as measured by IFNγ ELISpot predicted high IgG titres. Additional predictors of clinical protection and low SARS-CoV-2 burden included a high abundance of peripheral T cells. In contrast, increased numbers of intermediate monocytes predicted clinical pathology and high viral burden in the throat. We also conclude that an immunisation strategy that minimises pathology post-challenge did not necessarily mediate viral control. This would be an important finding to take forward into the development of future vaccines aimed at limiting the transmission of SARS-CoV-2. These results contribute to SARS-CoV-2 CoP definition and shed light on the factors influencing the success of SARS-CoV-2 vaccination.

Development of a personalized digital biomarker of vaccine-associated reactogenicity using wearable sensors and digital twin technology

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.

Comprehensive analysis of mitochondrial solute carrier family 25 (SLC25) identifies member 19 (SLC25A19) as a regulatory factor in hepatocellular carcinoma

BACKGROUND

The mitochondrial solute carrier family 25 (SLC25) is known to play a pivotal role in oncogenesis, yet its specific involvement in hepatocellular carcinoma (HCC) remains poorly elucidated.

METHODS

In this study, we performed a clustering analysis of HCC patients in the Cancer Genome Atlas database based on the expression levels of SLC25 members, and conducted clinical feature analysis for each patient within the clusters. Subsequently, we developed a prognostic model using a Lasso regression approach with SLC25A19, SLC25A49, and SLC25A51 as features, and generated a risk score for each HCC patient. We then identified SLC25A19 as a potential prognostic marker for HCC through single-cell analysis, and validated this finding using in vitro and in vivo experiments.

RESULTS

Our results revealed significant differences in the expression of most SLC25 family members in HCC patients, enabling the stratification of patients into three clusters, with those in cluster 1 exhibiting the most favorable prognosis and showing a correlation with enhanced immune infiltration. The risk scores derived from the features SLC25A19, SLC25A49, and SLC25A51 effectively predicted the prognosis of HCC patients, with area under the curve (AUC) values exceeding 0.7 in the test group. Single-cell analysis further demonstrated h eightened expression of SLC25A19 in the immune microenvironment of HCC, and in vitro experiments indicated that SLC25A19 may regulate the proliferation, migration, invasion, cycle, and apoptosis of liver cancer cells through the Wnt pathway. In the HepG2 animal model, overexpression of SLC25A19 significantly promotes tumor growth, while knockdown inhibits tumor growth. Analysis of patient tumor tissues shows that SLC25A19 is highly expressed in liver cancer tissues and is associated with CD8+ T cell infiltration.

CONCLUSIONS

In conclusion, our comprehensive analysis of the role of SLC25 in HCC unveiled SLC25A19 as a potential regulatory factor in HCC.

Systems Human Immunology and AI: Immune Setpoint and Immune Health

The immune system, critical for human health and implicated in many diseases, defends against pathogens, monitors physiological stress, and maintains tissue and organismal homeostasis. It exhibits substantial variability both within and across individuals and populations. Recent technological and conceptual progress in systems human immunology has provided predictive insights that link personal immune states to intervention responses and disease susceptibilities. Artificial intelligence (AI), particularly machine learning (ML), has emerged as a powerful tool for analyzing complex immune data sets, revealing hidden patterns across biological scales, and enabling predictive models for individualistic immune responses and potentially personalized interventions. This review highlights recent advances in deciphering human immune variation and predicting outcomes, particularly through the concepts of immune setpoint, immune health, and use of the immune system as a window for measuring health. We also provide a brief history of AI; review ML modeling approaches, including their applications in systems human immunology; and explore the potential of AI to develop predictive models and personal immune state embeddings to detect early signs of disease, forecast responses to interventions, and guide personalized health strategies.

Age-dependent cytokine surge in blood precedes cancer diagnosis

Aging is associated with increased variability and dysregulation of the immune system. We performed a system-level analysis of serum cytokines in a longitudinal cohort of 133 healthy individuals over 9 y. We found that cancer incidence is a major contributor to increased cytokine abundance variability. Circulating cytokines increase up to 4 y before a cancer diagnosis in subjects with age over 80 y. We also analyzed cytokine expression in 10 types of early-stage cancers from The Cancer Genome Atlas. We found that a similar set of cytokines is upregulated in tumor tissues, specifically after the age of 80 y. Similarly, cellular senescence activity and CDKN1A/p21 expression increase with age in cancer tissues. Finally, we demonstrated that the cytokine levels in serum can be used to predict cancers among subjects age at 80+ y. Our results suggest that latent senescent cancers contribute to age-related chronic inflammation.

Autophagosomes coated in situ with nanodots act as personalized cancer vaccines

Autophagosome cancer vaccines can promote cross-presentation of multiple tumour antigens and induce cross-reactive T cell responses. However, so far, there is no effective method for obtaining a highly immunogenic autophagosomal cancer vaccine because autophagosomes, once formed, quickly fuse with lysosomes and cannot easily escape from cells. Here we report a functional Ti2NX nanodot that caps the autophagosome membrane lipid phosphatidylinositol-4-phosphate, blocking the fusion of autophagosomes with lysosomes and producing stable nanodot-coated autophagosomes in tumours. The formed nanodot-coated autophagosomes can escape from cancer cells to lymph nodes, where they activate tumour-specific T cells. We show that our approach reduces tumour burden and provide long-term immune surveillance protection for cured mice. This work provides a method for the direct formation of personalized autophagosome-based cancer vaccines in vivo, offering a promising strategy for tumour treatment.

Temporal Transcriptomic Analysis of Periodontal Disease Progression and Its Molecular Links to Systemic Diseases

Periodontal disease, a prevalent oral inflammatory condition, is implicated in exacerbating systemic diseases. However, the molecular mechanisms underlying this association remain unclear. In this study, we performed RNA sequencing of gingival tissue samples collected from a mouse model of periodontal disease at multiple time points to investigate dynamic transcriptomic changes during disease progression. Our analysis revealed distinct temporal gene expression patterns associated with the key inflammatory and immune response pathways. These findings suggest stepwise molecular progression in the periodontal inflammatory process, potentially contributing to systemic inflammation through shared signaling networks. We further identified specific genes and pathways that may mediate the bidirectional relationship between periodontal disease and systemic conditions such as cardiovascular disease and diabetes. By elucidating the temporal dynamics of molecular changes in periodontal disease, this study provides insights into the pathogenesis and its systemic implications. It identifies potential biomarkers and therapeutic targets for local and systemic disease management.

Signature of collagen alpha-1(x) gene expression in human cancers and their therapeutic implications

Cancers are a class of disorders that entail uncontrollably unwanted cell development with dissemination. One in six fatalities globally is attributed to cancer, a global health issue. The analysis of the entire DNA sequence and how it expresses itself in tumor cells is known as cancer genomics. The development of novel cancer treatments has been facilitated because of the genomics method. COL10A1 gene, a short chain collagen, and an interstitial matrix component, acts as a predictive biomarker for cancer prognosis. Recognizing the fundamental consequences of mutations in the COL10A1 gene and its expression in cancer is crucial. Analyzing the COL10A1 gene expression with a data set and gene expression patterns shows the level of display of the tumor. Examining the therapeutic techniques of COL10A1 gene expression leads to early detection, screening, radiation therapy, and advanced developments. This review highlights the value of the COL10A1 gene in breast, gastric, pancreatic, lung, and colorectal cancers, emphasizing its role in gene expression patterns and therapeutic techniques.

Integrative Mapping of Pre-existing Immune Landscapes for Vaccine Response Prediction

Predicting individual vaccine responses remains a significant challenge due to the complexity and variability of immune processes. To address this gap, we developed immunaut, an open-source, data-driven framework implemented as an R package specifically designed for all systems vaccinologists seeking to analyze and predict immunological outcomes across diverse vaccination settings. Leveraging one of the most comprehensive live attenuated influenza vaccine (LAIV) datasets to date - 244 Gambian children enrolled in a phase 4 immunogenicity study - immunaut integrates humoral, mucosal, cellular, transcriptomic, and microbiological parameters collected before and after vaccination, providing an unprecedentedly holistic view of LAIV-induced immunity. Through advanced dimensionality reduction, clustering, and predictive modeling, immunaut identifies distinct immunophenotypic responder profiles and their underlying baseline determinants. In this study, immunaut delineated three immunophenotypes: (1) CD8 T-cell responders, marked by strong baseline mucosal immunity and extensive prior influenza virus exposure that boosts memory CD8 T-cell responses, without generating influenza virus-specific antibody responses; (2) Mucosal responders, characterized by pre-existing systemic influenza A virus immunity (specifically to H3N2) and stable epithelial integrity, leading to potent mucosal IgA expansions and subsequent seroconversion to influenza B virus; and (3) Systemic, broad influenza A virus responders, who start with relatively naive immunity and leverage greater initial viral replication to drive broad systemic antibody responses against multiple influenza A virus variants beyond those included in the LAIV vaccine. By integrating pathway-level analysis, model-derived contribution scores, and hierarchical decision rules, immunaut elucidates how distinct immunological landscapes shape each response trajectory and how key baseline features, including pre-existing immunity, mucosal preparedness, and cellular support, dictate vaccine outcomes. Collectively, these findings emphasize the power of integrative, predictive frameworks to advance precision vaccinology, and highlight immunaut as a versatile, community-available resource for optimizing immunization strategies across diverse populations and vaccine platforms.

Trends in ready-to-use portable electrochemical sensing devices for healthcare diagnosis

Compared with previous decades, healthcare has emerged as a key global concern in light of the recurrent outbreak of pandemics. The initial stage in the provision of healthcare involves the process of diagnosis. Countries worldwide advocate for healthcare research due to its efficacy and capacity to assist diverse populations. Enhanced levels of healthcare management can be attained by the implementation of rapid diagnostic procedures and cognitive data analysis. Therefore, there is a constant need for smart therapeutics, analytical tools, and diagnostic systems to improve health and well-being. The past decade witnessed enormous growth in the sensing detection systems integrated into smartphones with printed electrodes and wearable patches for the screening of various healthcare diagnostics biomarkers and therapeutic drugs. This review focuses on the expansion of point-of-care technologies and their incorporation into a broader array of portable devices, a critical aspect in the context of decentralized societies and their healthcare systems. Discussions are broadly focused on the different sensing platforms such as solid electrodes, screen-printed electrodes, and paper-based sensing strategies for the detection of various biomarkers and therapeutic drugs. We also discuss the next-generation healthcare wearable sensing device importance and future research possibilities. Finally, the portable electrochemical sensing devices and their future perspective developments towards healthcare diagnosis are critically summarized.

Development and validation of a comprehensive predictive model for surgical planning in patients with renal cell carcinoma and inferior vena cava tumor thrombus

OBJECTIVE

To investigate preoperative predictors for selecting different surgical approaches in patients with renal cell carcinoma with inferior vena cava (IVC) tumor thrombus (RCC-IVCTT), and to establish and validate corresponding predictive models.

METHODS

Clinical data of 583 RCC-IVCTT patients were retrospectively analyzed. Of these, 465 cases were used to construct predictive models, and 118 cases were used for validation. Univariate and multivariate analyses identified independent predictors for surgical strategies. Two nomogram prediction models were established based on relevant independent factors to predict surgical approach.

RESULTS

In the development cohort, 342 patients underwent IVC thrombectomy (IVCT), 91 underwent IVC cavectomy (IVCC), and 32 underwent IVC reconstruction (IVCR). Multivariate logistic regression analysis identified the following predictors for inability to perform IVCT: higher Mayo classification of tumor thrombus (TT), IVC wall invasion, presence of bland thrombus, pan-immune-inflammation value (PIV) > 358 × 109, and maximum anteroposterior (AP) diameter of IVC at renal vein ostium (RVo) > 24 mm. Platelet >170 × 109/L and inadequate collateral circulation were predictors for IVCR. The developed model predicted capacity of the nomogram was evaluated in terms of its calibration, discrimination, and clinical utility. The validation set confirmed these findings.

CONCLUSION

The comprehensive preoperative predictive model for RCC-IVCTT patients aids in preoperative determination of the required surgical approach and necessity for IVC angiography, facilitating perioperative preparation and reducing unnecessary invasive examinations.

Influence of immunological awareness on enhancing the overall complying with health instructions and necessary vaccines during epidemics and pandemics

Immunological awareness plays a pivotal role in promoting adherence to health instructions during public health emergencies. This study assessed the influence of specialized immunology education on compliance behaviors among higher education students. To assess the influence of specialized immunology education on compliance behaviors toward health instructions and necessary vaccines during epidemics and pandemics among higher education students. A cross-sectional survey was conducted among 532 students at King Faisal University, Saudi Arabia using stratified random sampling. A validated questionnaire examined demographics, health awareness, and specific immunological knowledge. Regression analysis was performed to assess predictors of compliance with health instructions. Considerable knowledge gaps were found around fundamental immunological concepts despite fair awareness about vaccines. Marked disparities existed across gender and academic disciplines. Regression modeling established specialized immunology training as a significant predictor of compliance with guidelines like masking and vaccination during epidemics (p < .001). The findings highlight the need for customized immunology curricula targeting students from nonscientific backgrounds. Incorporating immunology training in continuing education programs for healthcare professionals and public officials can further promote compliance. Multifaceted public health campaigns combining immunology education with initiatives to address socio-cultural barriers are warranted. Further research should explore sustainable educational interventions to enhance long-term retention and integration of immunology knowledge into health behaviors.

5-Hydroxymethylcytosine Profiles of cfDNA in Urine as Diagnostic, Differential Diagnosis and Prognostic Markers for Multiple Myeloma

BACKGROUND

An effective urine-based method for the diagnosis, differential diagnosis and prognosis of multiple myeloma (MM) has not yet been developed. Urine cell-free DNA (cfDNA) carrying cancer-specific genetic and epigenetic aberrations may enable a noninvasive "liquid biopsy" for diagnosis and monitoring of cancer.

METHODS

We first identified MM-specific hydroxymethylcytosine signatures by comparing 64 MM patients, 23 amyloidosis (AM) patients and 59 healthy cohort. Then, we applied a machine learning algorithm to develop diagnostic and differential diagnosis model. Finally, the prognosis of MM patients was predicted based on their survival time at the last follow-up.

RESULTS

We identified 11 5hmC markers using logistic regression algorithm could effectively diagnosis MM (AUC = 0.902), and achieved 85.00% specificity and 85.71% sensitivity. These 11 markers could also effectively differential diagnosis MM (AUC = 0.805) with 88.89% specificity and 73.08% sensitivity. In addition, the prognostic prediction model also effectively predicted the prognosis of patients with MM (p < 0.01), of which 4 differential markers (RAPGEF2, BRD1, TET2, TRAF3IP2) could independently predict the prognosis of MM.

CONCLUSIONS

Together, our findings showed the value of urine cfDNA hydroxymethylcytosine markers in the diagnosis, differential diagnosis and prognosis of MM. Meantime, our study provides a promising and completely non-invasive method for the diagnosis, differential diagnosis and prognosis prediction of MM.

Prognostic and predictive value of pathohistological features in gastric cancer and identification of SLITRK4 as a potential biomarker for gastric cancer

The aim of this study was to develop a quantitative feature-based model from histopathologic images to assess the prognosis of patients with gastric cancer. Whole slide image (WSI) images of H&E-stained histologic specimens of gastric cancer patients from The Cancer Genome Atlas were included and randomly assigned to training and test groups in a 7:3 ratio. A systematic preprocessing approach was employed as well as a non-overlapping segmentation method that combined patch-level prediction with a multi-instance learning approach to integrate features across the slide images. Subjects were categorized into high- or low-risk groups based on the median risk score derived from the model, and the significance of this stratification was assessed using a log-rank test. In addition, combining transcriptomic data from patients and data from other large cohort studies, we further searched for genes associated with pathological features and their prognostic value. A total of 165 gastric cancer patients were included for model training, and a total of 26 features were integrated through multi-instance learning, with each process generating 11 probabilistic features and 2 predictive labeling features. We applied a 10-fold Lasso-Cox regression model to achieve dimensionality reduction of these features. The predictive accuracy of the model was verified using Kaplan-Meyer (KM) curves for stratification with a consistency index of 0.741 for the training set and 0.585 for the test set. Deep learning-based resultant supervised pathohistological features have the potential for superior prognostic stratification of gastric cancer patients, transforming image pixels into an effective and labor-saving tool to optimize the clinical management of gastric cancer patients. Also, SLITRK4 was identified as a prognostic marker for gastric cancer.

Immune dynamics shaping pre-metastatic and metastatic niches in liver metastases: from molecular mechanisms to therapeutic strategies

Liver metastases are commonly detected in the advanced stages of various malignant tumors, representing a significant clinical challenge. Throughout the process of liver metastases formation, immune cells play a pivotal role, particularly in the pre-metastatic and metastatic niches within the liver. Immune cells establish extensive and intricate interactions with tumor cells and other components in the liver, collectively promoting and sustaining the growth of liver metastases. Despite the limited efficacy of existing therapeutic modalities against some advanced liver metastases, novel immune-based treatment approaches are continuously being explored and validated. Building on the systematic elucidation of the immunosuppressive characteristics of liver metastases, we explored the potential of novel immunotherapies applicable to patients with liver metastases from multiple dimensions.

Unraveling the Immune Web: Advances in SMI Capsular Fibrosis from Molecular Insights to Preclinical Breakthroughs

Breast implant surgery has evolved significantly, yet challenges such as capsular contracture remain a persistent concern. This review presents an in-depth analysis of recent advancements in understanding the immune mechanisms and clinical implications associated with silicone mammary implants (SMIs). The article systematically examines the complex interplay between immune responses and capsular fibrosis, emphasizing the pathophysiological mechanisms of inflammation in the etiology of this fibrotic response. It discusses innovations in biomaterial science, including the development of novel anti-biofilm coatings and immunomodulatory surfaces designed to enhance implant integration and minimize complications. Emphasis is placed on personalized risk assessment strategies, leveraging molecular insights to tailor interventions and improve patient outcomes. Emerging therapeutic targets, advancements in surgical techniques, and the refinement of post-operative care are also explored. Despite notable progress, challenges such as the variability in immune responses, the long-term efficacy of new interventions, and ethical considerations remain. Future research directions are identified, focusing on personalized medicine, advanced biomaterials, and bridging preclinical findings with clinical applications. As we advance from bench to bedside, this review illuminates the path forward, where interdisciplinary collaboration and continued inquiry weave together to enhance the art and science of breast implant surgery, transforming patient care into a realm of precision and excellence.

The Microbe, the Infection Enigma, and the Host

Human infectious diseases are unique in that the discovery of their environmental trigger, the microbe, was sufficient to drive the development of extraordinarily effective principles and tools for their prevention or cure. This unique medical prowess has outpaced, and perhaps even hindered, the development of scientific progress of equal magnitude in the biological understanding of infectious diseases. Indeed, the hope kindled by the germ theory of disease was rapidly subdued by the infection enigma, in need of a host solution, when it was realized that most individuals infected with most infectious agents continue to do well. The root causes of disease and death in the unhappy few remained unclear. While canonical approaches in vitro (cellular microbiology), in vivo (animal models), and in natura (clinical studies) analyzed the consequences of infection with a microbe, considered to be the cause of disease, in cells, tissues, or organisms seen as a uniform host, alternative approaches searched for preexisting causes of disease, particularly human genetic and immunological determinants in populations of diverse individuals infected with a trigger microbe.

BCL2L1 is regulated by the lncRNA MIR4435-2HG-miR-513a-5p-BCL2L1 ceRNA axis and serves as a biomarker for pancreatic adenocarcinoma treatment and prognosis

Pancreatic adenocarcinoma (PAAD) is one of the most malignant cancers. After escaping death, cancer cells are made more metastatic, aggressive, and also drug-resistant through anoikis resistance. The aim of this study is to explore the molecular mechanisms of anoikis-related genes in PAAD and to identify potential key biomarkers. We integrated information about PAAD from The Cancer Genome Atlas (TCGA) and The Genotype-Tissue Expression (GTEx) databases and identified anoikis-related gene BCL2L1 by survival analysis, univariate Cox regression analysis, and multifactorial Cox regression analysis. Various bioinformatics approaches showed that BCL2L1 was a valuable prognostic marker that might be involved in PAAD development and progression through different mechanisms, including cancer intervention, genomic heterogeneity, and RNA modifications. Our analysis showed that BCL2L1 expression also closely correlates with the expression of various immune checkpoint inhibitors. In particular, we found that long non-coding RNA MIR4435-2HG acted as ceRNA sponging miR-513a-5p to promote the expression of BCL2L1, thereby promoting pancreatic cancer cells proliferation. In conclusion, BCL2L1 expression regulated by the MIR4435-2HG-miR-513a-5p-BCL2L1 ceRNA axis might be used as a biomarker for cancer prognosis, treatment selection, and follow-up in PAAD patients.

Genome-wide association studies of COVID-19 vaccine seroconversion and breakthrough outcomes in UK Biobank

Understanding the genetic basis of COVID-19 vaccine seroconversion is crucial to study the role of genetics on vaccine effectiveness. In our study, we used UK Biobank data to find the genetic determinants of COVID-19 vaccine-induced seropositivity and breakthrough infections. We conducted four genome-wide association studies among vaccinated participants for COVID-19 vaccine seroconversion and breakthrough susceptibility and severity. Our findings confirmed a link between the HLA region and seroconversion after the first and second doses. Additionally, we identified 10 genomic regions associated with breakthrough infection (SLC6A20, ST6GAL1, MUC16, FUT6, MXI1, MUC4, HMGN2P18-KRTCAP2, NFKBIZ and APOC1), and one with breakthrough severity (APOE). No significant evidence of genetic colocalisation was found between those traits. Our study highlights the roles of individual genetic make-up in the varied antibody responses to COVID-19 vaccines and provides insights into the potential mechanisms behind breakthrough infections occurred even after the vaccination.

Small-molecule-based targeted therapy in liver cancer

Liver cancer is one of the most prevalent malignant tumors worldwide. According to the Barcelona Clinic Liver Cancer staging criteria, clinical guidelines provide tutorials to clinical management of liver cancer at their individual stages. However, most patients diagnosed with liver cancer are at advanced stage; therefore, many researchers conduct investigations on targeted therapy, aiming to improve the overall survival of these patients. To date, small-molecule-based targeted therapies are highly recommended (first line: sorafenib and lenvatinib; second line: regorafenib and cabozantinib) by current the clinical guidelines of the American Society of Clinical Oncology, European Society for Medical Oncology, and National Comprehensive Cancer Network. Herein, we summarize the small-molecule-based targeted therapies in liver cancer, including the approved and preclinical therapies as well as the therapies under clinical trials, and introduce their history of discovery, clinical trials, indications, and molecular mechanisms. For drug resistance, the revealed mechanisms of action and the combination therapies are also discussed. In fact, the known small-molecule-based therapies still have limited clinical benefits to liver cancer patients. Therefore, we analyze the current status and give our ideas for the urgent issues and future directions in this field, suggesting clues for novel techniques in liver cancer treatment.

Cell-surface Milieu Remodeling in Human Dendritic Cell Activation

Dendritic cells (DCs) are specialized sentinel and APCs coordinating innate and adaptive immunity. Through proteins on their cell surface, DCs sense changes in the environment, internalize pathogens, present processed Ags, and communicate with other immune cells. By combining chemical labeling and quantitative mass spectrometry, we systematically profiled and compared the cell-surface proteomes of human primary conventional DCs (cDCs) in their resting and activated states. TLR activation by a lipopeptide globally reshaped the cell-surface proteome of cDCs, with >100 proteins upregulated or downregulated. By simultaneously elevating positive regulators and reducing inhibitory signals across multiple protein families, the remodeling creates a cell-surface milieu promoting immune responses. Still, cDCs maintain the stimulatory-to-inhibitory balance by leveraging a distinct set of inhibitory molecules. This analysis thus uncovers the molecular complexity and plasticity of the cDC cell surface and provides a roadmap for understanding cDC activation and signaling.

Bioresponsive Immunotherapeutic Materials

The human immune system is an interaction network of biological processes, and its dysfunction is closely associated with a wide array of diseases, such as cancer, infectious diseases, tissue damage, and autoimmune diseases. Manipulation of the immune response network in a desired and controlled fashion has been regarded as a promising strategy for maximizing immunotherapeutic efficacy and minimizing side effects. Integration of "smart" bioresponsive materials with immunoactive agents including small molecules, biomacromolecules, and cells can achieve on-demand release of agents at targeted sites to reduce overdose-related toxicity and alleviate off-target effects. This review highlights the design principles of bioresponsive immunotherapeutic materials and discusses the critical roles of controlled release of immunoactive agents from bioresponsive materials in recruiting, housing, and manipulating immune cells for evoking desired immune responses. Challenges and future directions from the perspective of clinical translation are also discussed.

Cryo-PRO facilitates whole blood cryopreservation for single-cell RNA sequencing of immune cells from clinical samples

Single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells (PBMCs) has enhanced our understanding of host immune mechanisms in small cohorts, particularly in diseases with complex and heterogeneous immune responses such as sepsis. However, PBMC isolation from blood requires technical expertise, training, and approximately two hours of onsite processing using Ficoll density gradient separation ('Ficoll') for scRNA-seq compatibility, precluding large-scale sample collection at most clinical sites. To minimize onsite processing, we developed Cryo-PRO (Cryopreservation with PBMC Recovery Offsite), a method of PBMC isolation from cryopreserved whole blood that allows immediate onsite sample cryopreservation and subsequent PBMC isolation in a central laboratory prior to sequencing. We compared scRNA-seq results from samples processed using Cryo-PRO versus standard onsite Ficoll separation in 23 patients with sepsis. Critical scRNA-seq outputs including cell substate fractions and marker genes were similar for each method across multiple cell types and substates, including an important monocyte substate enriched in patients with sepsis (Pearson correlation 0.78, p<0.001; 70% of top marker genes shared). Cryo-PRO reduced onsite sample processing time from >2 hours to <15 minutes and was reproducible across two enrollment sites, thus demonstrating potential for expanding scRNA-seq in multicenter studies of sepsis and other diseases.

Transforming vaccinology

The COVID-19 pandemic placed the field of vaccinology squarely at the center of global consciousness, emphasizing the vital role of vaccines as transformative public health tools. The impact of vaccines was recently acknowledged by the award of the 2023 Nobel Prize in Physiology or Medicine to Katalin Kariko and Drew Weissman for their seminal contributions to the development of mRNA vaccines. Here, we provide a historic perspective on the key innovations that led to the development of some 27 licensed vaccines over the past two centuries and recent advances that promise to transform vaccines in the future. Technological revolutions such as reverse vaccinology, synthetic biology, and structure-based design transformed decades of vaccine failures into successful vaccines against meningococcus B and respiratory syncytial virus (RSV). Likewise, the speed and flexibility of mRNA vaccines profoundly altered vaccine development, and the advancement of novel adjuvants promises to revolutionize our ability to tune immunity. Here, we highlight exciting new advances in the field of systems immunology that are transforming our mechanistic understanding of the human immune response to vaccines and how to predict and manipulate them. Additionally, we discuss major immunological challenges such as learning how to stimulate durable protective immune response in humans.

Immunomics in one health: understanding the human, animal, and environmental aspects of COVID-19

The coronavirus disease 2019 (COVID-19) pandemic underscores the critical need to integrate immunomics within the One Health framework to effectively address zoonotic diseases across humans, animals, and environments. Employing advanced high-throughput technologies, this interdisciplinary approach reveals the complex immunological interactions among these systems, enhancing our understanding of immune responses and yielding vital insights into the mechanisms that influence viral spread and host susceptibility. Significant advancements in immunomics have accelerated vaccine development, improved viral mutation tracking, and broadened our comprehension of immune pathways in zoonotic transmissions. This review highlights the role of animals, not merely as carriers or reservoirs, but as essential elements of ecological networks that profoundly influence viral epidemiology. Furthermore, we explore how environmental factors shape immune response patterns across species, influencing viral persistence and spillover risks. Moreover, case studies demonstrating the integration of immunogenomic data within the One Health framework for COVID-19 are discussed, outlining its implications for future research. However, linking humans, animals, and the environment through immunogenomics remains challenging, including the complex management of vast amounts of data and issues of scalability. Despite challenges, integrating immunomics data within the One Health framework significantly enhances our strategies and responses to zoonotic diseases and pandemic threats, marking a crucial direction for future public health breakthroughs.

Deciphering bone marrow engraftment after allogeneic stem cell transplantation in humans using single-cell analyses

BACKGROUNDDonor cell engraftment is a prerequisite of successful allogeneic hematopoietic stem cell transplantation. Based on peripheral blood analyses, it is characterized by early myeloid recovery and T and B cell lymphopenia. However, cellular networks associated with bone marrow engraftment of allogeneic human cells have been poorly described.METHODSMass cytometry and CITE-Seq analyses were performed on bone marrow cells 3 months after transplantation in patients with acute myelogenous leukemia.RESULTSMass cytometric analyses in 26 patients and 20 healthy controls disclosed profound alterations in myeloid and B cell progenitors, with a shift toward terminal myeloid differentiation and decreased B cell progenitors. Unsupervised analysis separated recipients into 2 groups, one of them being driven by previous graft-versus-host disease (R2 patients). We then used single-cell CITE-Seq to decipher engraftment, which resolved 36 clusters, encompassing all bone marrow cellular components. Hematopoiesis in transplant recipients was sustained by committed myeloid and erythroid progenitors in a setting of monocyte-, NK cell-, and T cell-mediated inflammation. Gene expression revealed major pathways in transplant recipients, namely, TNF-α signaling via NF-κB and the IFN-γ response. The hallmark of allograft rejection was consistently found in clusters from transplant recipients, especially in R2 recipients.CONCLUSIONBone marrow cell engraftment of allogeneic donor cells is characterized by a state of emergency hematopoiesis in the setting of an allogeneic response driving inflammation.FUNDINGThis study was supported by the French National Cancer Institute (Institut National du Cancer; PLBIO19-239) and by an unrestricted research grant by Alexion Pharmaceuticals.

Nanomaterials in Immunology: Bridging Innovative Approaches in Immune Modulation, Diagnostics, and Therapy

The intersection of immunology and nanotechnology has provided significant advancements in biomedical research and clinical applications over the years. Immunology aims to understand the immune system's defense mechanisms against pathogens. Nanotechnology has demonstrated its potential to manipulate immune responses, as nanomaterials' properties can be modified for the desired application. Research has shown that nanomaterials can be applied in diagnostics, therapy, and vaccine development. In diagnostics, nanomaterials can be used for biosensor development, accurately detecting biomarkers even at very low concentrations. Therapeutically, nanomaterials can act as efficient carriers for delivering drugs, antigens, or genetic material directly to targeted cells or tissues. This targeted delivery improves therapeutic efficacy and reduces the adverse effects on healthy cells and tissues. In vaccine development, nanoparticles can improve vaccine durability and extend immune responses by effectively delivering adjuvants and antigens to immune cells. Despite these advancements, challenges regarding the safety, biocompatibility, and scalability of nanomaterials for clinical applications are still present. This review will cover the fundamental interactions between nanomaterials and the immune system, their potential applications in immunology, and their safety and biocompatibility concerns.

Pro-apoptotic gene BAX is a pan-cancer predictive biomarker for prognosis and immunotherapy efficacy

BACKGROUND

Apoptosis Regulator BCL2 Associated X (BAX) is a pro-apoptotic gene. Apoptosis is one of the important components of immune response and immune regulation. However, there is no systematic pan-cancer analysis of BAX.

METHODS

Original data of this study were downloaded from TCGA databases and GTEX databases. We conducted the gene expression analysis and survival analysis of BAX in 33 types of cancer via Gene Expression Profiling Interactive Analysis (GEPIA) database. Real-time PCR and immunohistochemistry (IHC) were further performed to examine the BAX expression in cancer cells and tissues. Moreover, the relationship between BAX and immune infiltration and gene alteration was studied by the Tumor Immune Estimation Resource (TIMER) and cBioPortal tools. Protein-protein interaction analysis was performed in the STRING database. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were utilized to evaluate the enrichment analysis.

RESULTS

BAX was highly expressed in most cancers and was associated with poor prognosis in nine cancer types. In addition, BAX showed significant clinical relevance, and the mRNA expression of BAX was also strongly associated with drug sensitivity of many drugs. Furthermore, BAX may participate in proliferation and metastasis of many cancers and was associated with methylation. Importantly, BAX expression was positively correlated with most immune infiltrating cells.

CONCLUSION

Our findings suggested that BAX can function as an oncogene and may be used as a potential predictive biomarker for prognosis and immunotherapy efficacy of human cancer, which could provide a new approach for cancer therapy.

Immune Dysfunction in Schizophrenia Spectrum Disorders

Evidence from epidemiological, clinical, and biological research resulted in the immune hypothesis: the hypothesis that immune system dysfunction is involved in the pathophysiology of schizophrenia spectrum disorders (SSD). The promising implication of this hypothesis is the potential to use existing immunomodulatory treatment for innovative interventions for SSD. Here, we provide a selective historical review of important discoveries that have shaped our understanding of immune dysfunction in SSD. We first explain the basic principles of immune dysfunction, after which we travel more than a century back in time. Starting our journey with neurosyphilis-associated psychosis in the nineteenth century, we continue by evaluating the role of infections and autoimmunity in SSD and findings from assessment of immune function using new techniques, such as cytokine levels, microglia density, neuroimaging, and gene expression. Drawing from these findings, we discuss anti-inflammatory interventions for SSD, and we conclude with a look into the future.

Deciphering Immune Responses to Immunization via Transcriptional Analysis: A Narrative Review of the Current Evidence towards Personalized Vaccination Strategies

The development of vaccines has drastically reduced the mortality and morbidity of several diseases. Despite the great success of vaccines, the immunological processes involved in protective immunity are not fully understood and several issues remain to be elucidated. Recently, the advent of high-throughput technologies has enabled a more in-depth investigation of the immune system as a whole and the characterization of the interactions of numerous components of immunity. In the field of vaccinology, these tools allow for the exploration of the molecular mechanisms by which vaccines can induce protective immune responses. In this review, we aim to describe current data on transcriptional responses to vaccination, focusing on similarities and differences of vaccine-induced transcriptional responses among vaccines mostly in healthy adults, but also in high-risk populations, such as the elderly and children. Moreover, the identification of potential predictive biomarkers of vaccine immunogenicity, the effect of age on transcriptional response and future perspectives for the utilization of transcriptomics in the field of vaccinology will be discussed.

Extracellular vesicles: an emerging tool for wild immunology

The immune system is crucial for defending organisms against pathogens and maintaining health. Traditionally, research in immunology has relied on laboratory animals to understand how the immune system works. However, there is increasing recognition that wild animals, due to their greater genetic diversity, lifespan, and environmental exposures, have much to contribute to basic and translational immunology. Unfortunately, logistical challenges associated with collecting and storing samples from wildlife, and the lack of commercially available species-specific reagents have hindered the advancement of immunological research on wild species. Extracellular vesicles (EVs) are cell-derived nanoparticles present in all body fluids and tissues of organisms spanning from bacteria to mammals. Human and lab animal studies indicate that EVs are involved in a range of immunological processes, and recent work shows that EVs may play similar roles in diverse wildlife species. Thus, EVs can expand the toolbox available for wild immunology research, helping to overcome some of the challenges associated with this work. In this paper, we explore the potential application of EVs to wild immunology. First, we review current understanding of EV biology across diverse organisms. Next, we discuss key insights into the immune system gained from research on EVs in human and laboratory animal models and highlight emerging evidence from wild species. Finally, we identify research themes in wild immunology that can immediately benefit from the study of EVs and describe practical considerations for using EVs in wildlife research.

Shortwave-infrared-light-emitting probes for the in vivo tracking of cancer vaccines and the elicited immune responses

Tracking and imaging immune cells in vivo non-invasively would offer insights into the immune responses induced by vaccination. Here we report a cancer vaccine consisting of polymer-coated NaErF4/NaYF4 core-shell down-conversion nanoparticles emitting luminescence in the near-infrared spectral window IIb (1,500-1,700 nm in wavelength) and with surface-conjugated antigen (ovalbumin) and electrostatically complexed adjuvant (class-B cytosine-phosphate-guanine). Whole-body wide-field imaging of the subcutaneously injected vaccine in tumour-bearing mice revealed rapid migration of the nanoparticles to lymph nodes through lymphatic vessels, with two doses of the vaccine leading to the complete eradication of pre-existing tumours and to the prophylactic inhibition of tumour growth. The abundance of antigen-specific CD8+ T lymphocytes in the tumour microenvironment correlated with vaccine efficacy, as we show via continuous-wave imaging and lifetime imaging of two intravenously injected near-infrared-emitting probes (CD8+-T-cell-targeted NaYbF4/NaYF4 nanoparticles and H-2Kb/ovalbumin257-264 tetramer/PbS/CdS quantum dots) excited at different wavelengths, and by volumetrically visualizing the three nanoparticles via light-sheet microscopy with structured illumination. Nanoparticle-based vaccines and imaging probes emitting infrared light may facilitate the design and optimization of immunotherapies.

Analysis and prediction of research hotspots and trends in heart failure research

Background and objectives

Comprehensive data analyses in heart failure research can provide academics with information and help policymakers formulate relevant policies. We collected data from reports published between 1945 and 2021 to identify research topics, trends, and cross-domains in the heart failure disease literature.

Methods

Text fragments were extracted and clustered from the titles and abstracts in 270617 publications using artificial intelligence techniques. Two algorithms were used to corroborate the results and ensure that they were reliable. Experts named themes and document clusters based on the results of these semiautomated methods. Using consistent methods, we identified and flagged 107 heart failure topics and 16 large document clusters (divided into two groups by time). The annual vocabularies of research hotspots were calculated to draw attention to niche research fields.

Results

Clinical research is an expanding field, followed by basic research and population research. The most frequently raised issues were intensive care treatment for heart failure, applications of artificial intelligence technologies, cardiac assist devices, stem cells, genetics, and regional distribution and use of heart failure-related health care. Risk scoring and classification, care for patients, readmission, health economics of treatment and care, and cell regeneration and signaling pathways were among the fastest-growing themes. Drugs, signaling pathways, and biomarkers were all crucial issues for clinical and basic research in the entire population. Studies on intelligent medicine and telemedicine, interventional therapy for valvular disease, and novel coronavirus have emerged recently.

Conclusion

Clinical and population research is increasingly focusing on the customization of intelligent treatments, improving the quality of patients' life, and developing novel treatments. Basic research is increasingly focusing on regenerative medicine, translational medicine, and signaling pathways. Additionally, each research field exhibits mutual fusion characteristics. Medical demands, new technologies, and social support are all potential drivers for these changes.

Multi-omic profiling reveals the endogenous and neoplastic responses to immunotherapies in cutaneous T cell lymphoma

Cutaneous T cell lymphomas (CTCLs) are skin cancers with poor survival rates and limited treatments. While immunotherapies have shown some efficacy, the immunological consequences of administering immune-activating agents to CTCL patients have not been systematically characterized. We apply a suite of high-dimensional technologies to investigate the local, cellular, and systemic responses in CTCL patients receiving either mono- or combination anti-PD-1 plus interferon-gamma (IFN-γ) therapy. Neoplastic T cells display no evidence of activation after immunotherapy. IFN-γ induces muted endogenous immunological responses, while anti-PD-1 elicits broader changes, including increased abundance of CLA+CD39+ T cells. We develop an unbiased multi-omic profiling approach enabling discovery of immune modules stratifying patients. We identify an enrichment of activated regulatory CLA+CD39+ T cells in non-responders and activated cytotoxic CLA+CD39+ T cells in leukemic patients. Our results provide insights into the effects of immunotherapy in CTCL patients and a generalizable framework for multi-omic analysis of clinical trials.

Relationship between HLA genetic variations, COVID-19 vaccine antibody response, and risk of breakthrough outcomes

The rapid global distribution of COVID-19 vaccines, with over a billion doses administered, has been unprecedented. However, in comparison to most identified clinical determinants, the implications of individual genetic factors on antibody responses post-COVID-19 vaccination for breakthrough outcomes remain elusive. Here, we conducted a population-based study including 357,806 vaccinated participants with high-resolution HLA genotyping data, and a subset of 175,000 with antibody serology test results. We confirmed prior findings that single nucleotide polymorphisms associated with antibody response are predominantly located in the Major Histocompatibility Complex region, with the expansive HLA-DQB1*06 gene alleles linked to improved antibody responses. However, our results did not support the claim that this mutation alone can significantly reduce COVID-19 risk in the general population. In addition, we discovered and validated six HLA alleles (A*03:01, C*16:01, DQA1*01:02, DQA1*01:01, DRB3*01:01, and DPB1*10:01) that independently influence antibody responses and demonstrated a combined effect across HLA genes on the risk of breakthrough COVID-19 outcomes. Lastly, we estimated that COVID-19 vaccine-induced antibody positivity provides approximately 20% protection against infection and 50% protection against severity. These findings have immediate implications for functional studies on HLA molecules and can inform future personalised vaccination strategies.

The Impact of Immune System Aging on Infectious Diseases

Immune system aging is becoming a field of increasing public health interest because of prolonged life expectancy, which is not paralleled by an increase in health expectancy. As age progresses, innate and adaptive immune systems undergo changes, which are defined, respectively, as inflammaging and immune senescence. A wealth of available data demonstrates that these two conditions are closely linked, leading to a greater vulnerability of elderly subjects to viral, bacterial, and opportunistic infections as well as lower post-vaccination protection. To face this novel scenario, an in-depth assessment of the immune players involved in this changing epidemiology is demanded regarding the individual and concerted involvement of immune cells and mediators within endogenous and exogenous factors and co-morbidities. This review provides an overall updated description of the changes affecting the aging immune system, which may be of help in understanding the underlying mechanisms associated with the main age-associated infectious diseases.

Early B cell transcriptomic markers of measles-specific humoral immunity following a 3rd dose of MMR vaccine

B cell transcriptomic signatures hold promise for the early prediction of vaccine-induced humoral immunity and vaccine protective efficacy. We performed a longitudinal study in 232 healthy adult participants before/after a 3rd dose of MMR (MMR3) vaccine. We assessed baseline and early transcriptional patterns in purified B cells and their association with measles-specific humoral immunity after MMR vaccination using two analytical methods ("per gene" linear models and joint analysis). Our study identified distinct early transcriptional signatures/genes following MMR3 that were associated with measles-specific neutralizing antibody titer and/or binding antibody titer. The most significant genes included: the interleukin 20 receptor subunit beta/IL20RB gene (a subunit receptor for IL-24, a cytokine involved in the germinal center B cell maturation/response); the phorbol-12-myristate-13-acetate-induced protein 1/PMAIP1, the brain expressed X-linked 2/BEX2 gene and the B cell Fas apoptotic inhibitory molecule/FAIM, involved in the selection of high-affinity B cell clones and apoptosis/regulation of apoptosis; as well as IL16 (encoding the B lymphocyte-derived IL-16 ligand of CD4), involved in the crosstalk between B cells, dendritic cells and helper T cells. Significantly enriched pathways included B cell signaling, apoptosis/regulation of apoptosis, metabolic pathways, cell cycle-related pathways, and pathways associated with viral infections, among others. In conclusion, our study identified genes/pathways linked to antigen-induced B cell proliferation, differentiation, apoptosis, and clonal selection, that are associated with, and impact measles virus-specific humoral immunity after MMR vaccination.

Isotype switching in human memory B cells sets intrinsic antigen-affinity thresholds that dictate antigen-driven fates

Memory B cells (MBCs) play a critical role in protection against homologous and variant pathogen challenge by either differentiating to plasma cells (PCs) or to germinal center (GC) B cells. The human MBC compartment contains both switched IgG+ and unswitched IgM+ MBCs; however, whether these MBC subpopulations are equivalent in their response to B cell receptor cross-linking and their resulting fates is incompletely understood. Here, we show that IgG+ and IgM+ MBCs can be distinguished based on their response to κ-specific monoclonal antibodies of differing affinities. IgG+ MBCs responded only to high-affinity anti-κ and differentiated almost exclusively toward PC fates. In contrast, IgM+ MBCs were eliminated by apoptosis by high-affinity anti-κ but responded to low-affinity anti-κ by differentiating toward GC B cell fates. These results suggest that IgG+ and IgM+ MBCs may play distinct yet complementary roles in response to pathogen challenge ensuring the immediate production of high-affinity antibodies to homologous and closely related challenges and the generation of variant-specific MBCs through GC reactions.

A genetic variant in the immune-related gene ERAP1 affects colorectal cancer prognosis

BACKGROUND

Findings on the association of genetic factors and colorectal cancer (CRC) survival are limited and inconsistent, and revealing the mechanism underlying their prognostic roles is of great importance. This study aimed to explore the relationship between functional genetic variations and the prognosis of CRC and further reveal the possible mechanism.

METHODS

We first systematically performed expression quantitative trait locus (eQTL) analysis using The Cancer Genome Atlas (TCGA) dataset. Then, the Kaplan-Meier analysis was used to filter out the survival-related eQTL target genes of CRC patients in two public datasets (TCGA and GSE39582 dataset from the Gene Expression Omnibus database). The seven most potentially functional eQTL single nucleotide polymorphisms (SNPs) associated with six survival-related eQTL target genes were genotyped in 907 Chinese CRC patients with clinical prognosis data. The regulatory mechanism of the survival-related SNP was further confirmed by functional experiments.

RESULTS

The rs71630754 regulating the expression of endoplasmic reticulum aminopeptidase 1 ( ERAP1 ) was significantly associated with the prognosis of CRC (additive model, hazard ratio [HR]: 1.43, 95% confidence interval [CI]: 1.08-1.88, P = 0.012). The results of dual-luciferase reporter assay and electrophoretic mobility shift assay showed that the A allele of the rs71630754 could increase the binding of transcription factor 3 (TCF3) and subsequently reduce the expression of ERAP1 . The results of bioinformatic analysis showed that lower expression of ERAP1 could affect the tumor immune microenvironment and was significantly associated with severe survival outcomes.

CONCLUSION

The rs71630754 could influence the prognosis of CRC patients by regulating the expression of the immune-related gene ERAP1 .

TRIAL REGISTRATION

No. NCT00454519 ( https://clinicaltrials.gov/ ).

Innovative translational platforms for rapid developing clinical vaccines against COVID-19 and other infectious disease

A vaccine is a biological preparation that contains the antigen capable of stimulating the immune system to form the defense against pathogens. Vaccine development often confronts big challenges, including time/energy-consuming, low efficacy, lag to pathogen emergence and mutation, and even safety concern. However, these seem now mostly conquerable through constructing the advanced translational platforms that can make innovative vaccines, sometimes, potentiated with a distinct multifunctional VADS (vaccine adjuvant delivery system), as evidenced by the development of various vaccines against the covid-19 pandemic at warp speed. Particularly, several covid-19 vaccines, such as the viral-vectored vaccines, mRNA vaccines and DNA vaccines, regarded as the innovative ones that are rapidly made via the high technology-based translational platforms. These products have manifested powerful efficacy while showing no unacceptable safety profile in clinics, allowing them to be approved for massive vaccination at also warp speed. Now, the proprietary translational platforms integrated with the state-of-the-art biotechnologies, and even the artificial intelligence (AI), represent an efficient mode for rapid making innovative clinical vaccines against infections, thus increasingly attracting interests of vaccine research and development. Herein, the advanced translational platforms for making innovative vaccines, together with their design principles and immunostimulatory efficacies, are comprehensively elaborated.

Prognostic value of the peripheral blood lymphocyte/monocyte ratio combined with 18F-FDG PET/CT in patients with diffuse large B-cell lymphoma

OBJECTIVE

To explore the prognostic value of the peripheral blood lymphocyte/monocyte ratio (LMR) combined with 18F-FDG PET/CT for diffuse large B-cell lymphoma (DLBCL).

METHODS

The clinical data of 203 patients with primary DLBCL who were hospitalized to the First People's Hospital of Lianyungang between January 2017 and December 2022 were retrospectively analyzed. Before and after three courses of treatment, PET/CT was performed on forty DLBCL patients. The subject operating characteristic (ROC) curve has been employed to determine the most effective LMR cutoff points. According to the criteria for assessing the efficacy of Lugano lymphoma, the PET/CT findings after 3 courses of treatment were specified as complete remission (CR), partial remission (PR), stable disease (SD) and disease progression (PD). The CR group, PR+SD group, and PD group were the three groups created from the four outcomes. Results were analyzed using the Cox proportional risk model, the Kaplan-Meier method (K-M), and the log-rank test.

RESULTS

An optimal cutoff point of 3.00 for the LMR in 203 patients was determined by the SPSS 26 software ROC curve. When LMR≥3.00, the 1-year, 3-year, and 5-year OS (Overall Survival) rates are 98%, 88%, and 64% respectively, and the PFS (Progression-free Survival) rates are 90%, 75%, and 56% respectively. When LMR <3.00, the 1-year, 3-year, and 5-year OS rates are 96%, 72%, and 28% respectively, and the PFS rates are 83%, 60%, and 28% respectively. A lower LMR was substantially related with shorter OS, and PFS, according to a K-M survival analysis (P<0.005). LMR<3.00 was an independent predictor of OS, based on a multifactorial Cox analysis (P=0.037). K-M survival analysis of the 18F-FDG PET/CT results of 40 patients revealed that both OS and PFS were statistically significant (P<0.001). Patients were separated into 3 groups combining LMR and 18F-FDG PET/CT: PET/CT CR patients with LMR≥3.00, PET/CT PD patients with LMR<3.00, and others. The Kaplan-Meier analysis revealed that there were significant differences in OS and PFS for each of the three groups (P<0.001). ROC curves showed that the area under the curve (AUC) of the combined testing of the two was 0.735, and the combined testing of the two was better compared to testing alone (PET/CT AUC=0.535, LMR AUC=0.567). This indicates that combining both PET/CT and LMR is a favorable prediction for DLBCL.

CONCLUSION

A decreased LMR at initial diagnosis suggests an unfavorable prognosis for DLBCL patients; For patients with DLBCL, combining 18F-FDG PET/CT and the LMR has a better predictive value.

The significance of HAUS1 and its relationship with immune microenvironment in hepatocellular carcinoma

Background: HAUS Augmin-like complex subunit 1(HAUS1), as a controlling gene, which affected the production of spindle was firstly discovered in Drosophila cells. Although HAUS1 has been intensively studied, but its significance and relationship with the immune microenvironment in Hepatocellular carcinoma (HCC) remain unclear. Materials and Methods: All data of HCC in this paper were obtained from The Cancer Genome Atlas(TCGA), Genotype-Tissue Expression (GTEx), Gene Expression Omnibus (GEO) and the Human Protein Atlas(HPA) database. The role and potential value of HAUS1 in the tumorigenesis and development of HCC were studied by applying plenty of bioinformatics analysis methods. Knocked down the expression of HAUS1 through siRNA and further investigated the function of HAUS1 in HCC Results: HAUS1 was highly expressed in HCC, which led to a poor prognosis. ROC curve analysis showed that HAUS1 had a excellent diagnostic value. It was also associated with clinical stage, pathological grade and AFP of HCC. Univariate and multivariate COX regression analysis showed that HAUS1 was an independent prognostic factor for HCC patients. HAUS1 was associated with immune cells infiltrate and immune checkpoints in HCC, and it could generate significative therapeutic results when combined with anti-CTLA4 and anti-CD274 treatment. In vitro experiments, HAUS1 was found to promote the proliferation, invasion and metastasis, participated in cell cycle regulation and inhibited apoptosis of HCC. Conclusion: These results suggested that HAUS1 might serve as a potential therapeutic target, as well as a diagnostic, prognostic, and survival biomarker for HCC.

Bibliometric analysis of photodynamic therapy and immune response from 1989-2023

Objective: Photodynamic therapy (PDT) is a minimally invasive treatment approach for precancerous and cancerous lesions, known for its ability to activate the host immune response. This study conducted a bibliometric analysis to identify the research trends and hotspots related to the immune response in PDT. Methods: We analyzed articles and reviews published from 1989 to 2023, retrieved from the Web of Science database. Using Citespace and VOSviewer, we visualized the distribution patterns of these studies in time and space. Results: The analysis revealed a substantial increase in the number of publications on PDT-related immune response since 1989. A total of 1,688 articles from 1,701 institutions were included in this analysis. Among thei nstitutions, the Chinese Academy of Sciences demonstrated exceptional productivity and a willingness to collaborate with others. Additionally, 8,567 authors contributed to the field, with Mladen Korbelik, Michael R. Hamblin, and Wei R. Chen being the most prolific contributors. The current research focus revolves around novel strategies to enhance antitumor immunity in PDT, including PDT-based dendritic cell vaccines, combination therapies with immune checkpoint inhibitors (ICIs), and the use of nanoparticles for photosensitizer delivery. Furthermore, genes such as CD8A, TNF, CD4, IFNG, CD274, IL6, IL10, CALR, HMGB1, and CTLA4 have been evaluated in the context of PDT-related immunity. Conclusion: PDT not only achieves tumor ablation but also stimulates the immune response, bolstering antitumor immunity. This study highlights the emerging hotspots in PDT-related immune response research and provides valuable insights for future investigations aimed at further enhancing antitumor immunity.

Special Issue "Immunoanalytical and Bioinformatics Methods in Immunology Research"

To effectively control and prevent diseases on a global scale, it is essential to employ precise, sensitive, selective, and rapid immunoanalytical methods [...].