Scandinavian Journal of Immunology最新文献

The diagnosis, management and potential eradication of cancer depend on tumour type, stage, extent and anatomical location. While surgery, chemotherapy and radiotherapy remain central, advances in molecular oncology have shifted treatment toward personalised approaches. Identification of tumour-specific molecular abnormalities and biomarkers has enabled targeted therapies that eliminate malignant cells while limiting damage to normal tissues. Cancer immunotherapy has emerged as a promising, non-invasive strategy that activates the immune system to recognise and attack tumour-specific antigens. Preventive vaccines based on weakened or inactivated viruses have achieved notable success in reducing virus-associated cancers. Therapeutic vaccines targeting tumour-associated antigens (TAAs) and patient-specific neoantigens aim to elicit strong cytotoxic and helper T-cell responses against established tumours. Advances in genomic sequencing, bioinformatics-driven neoantigen prediction and single-cell profiling now enable accurate identification of tumour-specific targets. This review highlights progress in cancer vaccine research, focusing on strategies targeting TAAs, neoantigens and delivery platforms such as dendritic cell-based systems, nucleic acid vaccines (DNA and mRNA), synthetic long peptides and viral or bacterial vectors. Clinical evidence shows that neoantigen vaccines induce potent tumour-specific T-cell responses with minimal autoimmunity and gain enhanced efficacy when combined with immune checkpoint inhibitors or adoptive T-cell transfer (ACT) using tumour-infiltrating lymphocytes (TILs). By reinvigorating anti-tumour T cells within the tumour microenvironment, these combination approaches support durable tumour regression and improved outcomes. Despite unresolved challenges, advances in AI-guided target discovery, nanotechnology-based delivery systems and scalable manufacturing offer promising solutions for achieving precise and durable cancer treatment.

Methotrexate (MTX) is one of the most prevalent drugs used in the treatment of autoimmune disorders as it has an established role in preventing T and B cell proliferation which reduces the severity of autoimmunity. However, MTX in combination with several other drugs is commonly used as chemotherapeutic regimens for the treatment of breast cancer (BC). Given the critical role of immune cells-particularly T and B cells-in recognising and eliminating tumor cells, we sought to investigate the impact of MTX on immune cell regulation in the context of breast cancer. CD4⁺ T follicular helper (Tfh) cells are recognised for their anti-tumor potential during BC progression, as they support B cell differentiation and proliferation within germinal centres. In this study, we specifically aimed to observe the regulatory role of MTX during in vitro human Tfh cell differentiation under normal circumstances, and within in vivo 4T1 metastatic tumour-bearing mice. Our findings reveal that MTX exerts a dual and context-dependent role in modulating Tfh cell differentiation and function across the two models. Furthermore, we explored the influence of the AMPK activator AICAR in combination with MTX in both the human and mouse models. MTX when used in combination with AICAR, rescued human Tfh cell differentiation in vitro from MTX-mediated suppression. In the 4T1 mouse model, the synergistic administration of MTX and AICAR significantly enhanced the proliferation of Tfh cells, along with increases in germinal centre B cells, memory B cells, and plasma cells in both circulation and tumor-draining lymph nodes.

We recently reported that a homozygous deletion in the complement factor H-related (CFHR) locus predisposed kidney transplant patients to rejection. As donors carried intact genes, the susceptibility may have resulted from an alloimmune reaction to FHR proteins. However, we found no evidence for an anti-FH response. It is therefore possible that CFHR deletions as such affect the rejection risk. Here, we used MLPA and WGS to fine-map and sequence the CFHR region in rs7542235-GG patients, a SNP tagging for ΔCFHR3-1 deletion. Our results confirmed that all patients with this SNP harboured deletions of various sizes encompassing CFHR1. Furthermore, patients with homozygous ΔCFHR3-1 were homozygous for rs6677604-A, a SNP tagging for deletions of CFHR3-1 locus, confirming that allele A tags for deletion of both CFHR3 and CFHR1. Proteomics analyses in a larger population demonstrated that rs7542235-G and rs6677604-A associate with expression levels of several proteins involved in regulating alloimmune response. We observed that while increasing the rejection risk, the ΔCFHR3-1 did not associate with baseline disease or specific clinical characteristics. To conclude, the various deletion types found in patients shared the deletion of the CFHR1 gene confirming its association with variant rs7542235. Also, both deletion-tagging alleles are associated with altered expression of FHR proteins.

Anti-acetylcholine receptor (AChR) and anti-muscle-specific tyrosine kinase (MuSK) autoantibody detection is crucial in the diagnosis and choice of treatment of myasthenia gravis (MG). We conducted a multicentre prospective study comparing radioimmunoprecipitation assay (RIPA), enzyme-linked immunosorbent assay (ELISA) and fixed cell-based assay (F-CBA) for anti-AChR and anti-MuSK antibody detection in 78 patients with suspected MG with at least 6 months of clinical follow-up. In the diagnosis of seropositive MG (anti-AChR+anti-MuSK abs), RIPA was most sensitive (82.8%) compared to ELISA (81.0%) and F-CBA (70.7%). F-CBA exhibited the highest specificity overall (95.0%). For anti-AChR detection, F-CBA demonstrated a sensitivity of 73.6% and specificity of 95.0%; ELISA showed sensitivity and specificity of 81.1% and 85.0%, respectively; and RIPA yielded sensitivity and specificity of 81.1% and 95.0%. Sensitivity of F-CBA improved when sera were tested at lower dilution (1:5) versus the manufacturer's recommended 1:10, without compromising specificity. Agreement among methods was almost perfect for anti-AChR detection (Cohen's Kappa > 0.81). For anti-MuSK detection, agreement was substantial between ELISA and RIPA, moderate between ELISA and F-CBA, and fair between RIPA and F-CBA. Higher anti-AChR antibody levels were found in generalised versus ocular MG by both RIPA and ELISA. F-CBA confirmed its optimal specificity while the sensitivity seems to be influenced by sample dilution. In conclusion, given the radioactive nature of RIPA and consequent limitations, F-CBA may represent a valid alternative in anti-AChR and anti-MuSK antibody detection in MG diagnosis. We suggest that the use of live-CBA or RIPA could be reserved for inconclusive cases.

Vitiligo is a complex autoimmune disease of the skin characterised by the loss of melanocytes, resulting in depigmented patches on the skin. Despite advances in clinical diagnosis and treatment, challenges such as delayed diagnosis and limited therapeutic efficacy remain. Artificial intelligence (AI), particularly machine learning (ML) and deep learning (DL), has become a transformative tool in medical science, offering new approaches for early diagnosis, treatment optimization, and drug repurposing. This review examines the current status and recent advances in AI-based methods for vitiligo, highlighting deep neural network diagnostic tools, transformer-based image classifiers, and predictive models that surpass the accuracy of dermatologists. Moreover, AI-driven analyses of gene expression, protein interactions, and pharmacological networks have facilitated drug repurposing and accelerated therapeutic discovery. However, several challenges hinder the full clinical integration of AI. These include the need for large, diverse, high-quality datasets; limited representation of darker skin tones; lack of model interpretability; and ethical issues related to patient privacy, data ownership, and accountability for diagnostic errors. Integrating AI tools into existing healthcare systems also requires overcoming interoperability barriers and adapting clinical workflows. Addressing these challenges through the development of explainable, ethically governed, and inclusively trained AI systems will be crucial for realising the full potential of AI in improving vitiligo diagnosis and treatment outcomes.

Immune thrombocytopenia (ITP) is an acquired autoimmune disorder characterised by immune-mediated platelet destruction, yet its metabolic underpinnings remain incompletely understood. In this study, we applied a non-targeted serum metabolomics approach to characterise metabolic alterations in ITP and to explore candidate diagnostic biomarkers. A total of 37 serum samples were collected, including 20 from patients with ITP and 17 from age- and sex-matched healthy individuals. Global metabolite profiling was performed, followed by quantitative analyses, identification of differentially expressed metabolites, and functional annotation. Machine learning algorithms were then used to construct a diagnostic prediction model based on differential metabolites. Compared with healthy controls, ITP patients exhibited a distinct metabolic signature dominated by alterations in lipids and lipid-like molecules, with 680 metabolites upregulated and 589 downregulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed prominent involvement of lipid metabolism, cholesterol metabolism, and unsaturated fatty acid metabolism pathways. Among the differential metabolites, isopimpinellin and oleic acid emerged as highly characteristic of ITP. The prediction model built on these metabolomic features achieved a sensitivity of 78%, a specificity of 100%, and an area under the receiver operating characteristic curve of 0.83, indicating promising diagnostic performance. These findings suggest that dysregulated lipid metabolism is a central feature of ITP and support the potential of serum metabolomics-based machine learning models to aid in the identification of novel biomarkers and to improve early diagnosis of this immune-mediated thrombocytopenia.

Multiple sclerosis (MS) is a prevalent autoimmune disease with increasing incidence in certain populations, and autologous haematopoietic stem cell transplantation (aHSCT) represents an important therapeutic option. Cytomegalovirus (CMV) has been implicated in the pathophysiology of several immune-mediated conditions, prompting evaluation of its potential influence on transplant outcomes. We analysed MS patients who underwent aHSCT between 2015 and 2023 with 12-month follow-up using the 'Mexican method,' assessing clinical response through the change in Expanded Disability Status Scale (EDSS) score from pre-transplant to 12 months post-procedure. Among 135 patients, 93 were classified as responders and 42 as non-responders. Lower pre-transplant EDSS was associated with a better response (p = 0.001), and women showed significantly greater improvement following aHSCT (p = 0.012). Higher serum IgG anti-CMV levels correlated with improved clinical outcomes (p = 0.021), suggesting that prior CMV exposure may be linked to enhanced response to aHSCT. These findings highlight a potential modulatory role of CMV serostatus in transplant efficacy and support the need for further studies to clarify the biological basis and clinical relevance of this association.

Thrombocytopenia has been increasingly observed in patients with rheumatoid arthritis (RA) in clinical practice. However, whether this association reflects a causal relationship remains unclear. This study aims to investigate the causal effect of RA on the risk of developing immune thrombocytopenia (ITP) and to evaluate the potential mediating role of C-reactive protein (CRP) in this relationship. This study combined a cross-sectional survey of data from the National Health and Nutrition Examination Survey (NHANES) 2003-2018 and two-sample Mendelian randomisation (MR) analyses. The observational study utilised multivariable logistic regression to examine the association between RA and ITP. The MR analysis used single-nucleotide polymorphisms (SNPs) as instrumental variables to evaluate the causal relationship between RA and ITP, as well as the mediating effect of CRP. The observational analysis demonstrated a significant positive association between RA and ITP after full adjustment for confounding variables (OR = 2.92, 95% CI: 1.93-4.44, p < 0.001). This association remained consistent across all predefined subgroups. MR analysis indicated a positive causal effect of genetically predicted RA on ITP risk (OR = 1.218, 95% CI: 1.093-1.356, p < 0.05). Mediation analysis estimated that CRP accounted for approximately 9% (95% CI: 3%-17%) of the total effect. The robustness of both observational and causal findings was upheld through sensitivity analyses. This study demonstrates a significant association between RA and ITP, with CRP partially mediating this relationship.