Search Results (1,703)

Tumor-infiltrating lymphocytes (TILs) are thought to play important roles in tumor shrinkage and survival prolongation in patients with breast cancer receiving neoadjuvant chemotherapy (NAC). TILs are mononuclear immune cells such as lymphocytes and plasma cells, including CD4+ and CD8+ T cells, natural killer cells, B cells, macrophages, regulatory T cells (Tregs), and myeloid/dendritic cells. The pre-NAC presence of more T cells and fewer Tregs in biopsy samples of primary breast tumors is known to contribute to tumor shrinkage and prolonged survival. This review was conducted to elucidate these roles in patients with breast cancer treated with NAC. Publications selected for inclusion in this review were identified by a PubMed search for articles published in English, performed using the terms “breast cancer”, “neoadjuvant chemotherapy”, “tumor-infiltrating lymphocyte”, “pathological complete response”, and “immune response”. The search was completed in July 2024. The functional roles of TILs in the achievement of these outcomes may vary by tumor subtype; increases and decreases in TIL levels before and after NAC have been shown to have conflicting effects. Biomarkers have been reported to predict local responses in the tumor microenvironment (e.g., immune-related gene signatures) and systemic immune responses (e.g., neutrophil-to-lymphocyte and platelet-to-lymphocyte ratios). Immune gene signatures and immune cell infiltration do not appear to be universally associated with tumor response or outcome in patients with breast cancer treated with NAC. The functional roles of TILs in breast tumor response and breast cancer survival may vary by tumor subtype, and conflicting results for the same subtypes may be due to differences in NAC regimens, immune responses, tumor heterogeneity, sample size, and the technical methods used to evaluate TILs in tumor samples. Full article

The human microbiome is a critical factor in health and disease. While its association with breast cancer (BC) has been increasingly studied, this review provides a dedicated synthesis of the microbiota’s role in benign breast diseases (BBDs)—a common yet microbiologically overlooked spectrum of conditions. The primary aim of this work is to consolidate the current understanding of the composition, origins, and functional mechanisms of the mammary gland (MG) microbiota specifically in the context of BBD and to evaluate its potential for novel diagnostic and therapeutic targets. We detail the distinct MG microbiota, formed via exogenous (e.g., cutaneous, translocation) and endogenous (e.g., enteromammary, lymphohematogenous) pathways, and its interaction with the host through estrogen metabolism, immunomodulation, and epigenetic modifications. This narrative review reveals unique dysbiotic patterns in BBD, characterized by distinct microbial signatures, such as the enrichment of Corynebacterium kroppenstedtii in granulomatous mastitis and the presence of Staphylococcus aureus in fibroadenomas and lactational mastitis. Furthermore, specific gut microbial profiles are identified in BBD patients, including an increased abundance of genera such as Clostridium and Faecalibacterium, alongside a decrease in Collinsella and Alistipes compared to healthy controls. These specific taxa represent compelling candidates for diagnostic biomarkers. We conclude that microbial dysbiosis is a significant component of BBD pathogenesis. A paradigm shift toward multi-omics approaches and mechanistic studies is now essential to translate these associations into clinical applications. Understanding the BBD-specific microbiome holds the promise of revolutionizing patient care through microbiota-based diagnostics for differentiating benign subtypes and novel, personalized therapeutic strategies aimed at restoring microbial homeostasis. Full article

Glycosylation of surface proteins is a crucial post-translational modification that reflects the activation status of neutrophils, the predominant leukocyte subset in humans and horses. Neutrophils have emerged as active contributors to diseases mediated by the adaptive immune system, such as equine recurrent uveitis (ERU), a sight-threatening disease in horses and a unique model for studying the pathogenesis of autoimmune uveitis in humans. Since changes in surface glycosylation can impact neutrophil function, we were interested in the surface glycosylation landscape on neutrophils from healthy horses and the potential changes in surface glyco-signatures in ERU. Using 35 different plant lectins, we outlined a profile of surface-exposed glycan moieties on equine neutrophils and detected significantly increased O-glycosylation in a diseased state through Jacalin (JAC) binding via flow cytometry. Subsequent molecular weight comparison of JAC pull-down assay data and neutrophil proteomics indicated the surface proteins Integrin beta-2 and CUB domain-containing protein 1 as potential anchors for increased O-glycan levels in ERU. These findings give novel insights into neutrophil surface glycosylation in health and disease and propose O-glycosylation as a possible biomarker for autoimmune uveitis. Full article

Background/Objectives: Neurodegenerative diseases (NDs) such as Alzheimer’s (AD), Parkinson’s (PD), Huntington’s (HD), and Amyotrophic Lateral Sclerosis (ALS) are clinically distinct but share overlapping molecular mechanisms. Methods: To identify conserved systemic signatures, we analyzed blood RNA-Seq datasets using Weighted Gene Co-Expression Network Analysis (WGCNA), differential expression, pathway enrichment, and miRNA–mRNA network mapping. Results: Two modules, the red and turquoise, showed strong preservation across diseases. The red module was enriched for cytoskeletal and metabolic regulation, while the turquoise module involved immune, stress-response, and proteostatic pathways. Discussion: Key hub genes, such as HMGCR, ACTR2, MYD88, PTEN, EP300, and regulatory miRNAs like miR-29, miR-132, and miR-146a, formed interconnected networks reflecting shared molecular vulnerabilities. The absence of classical heat shock proteins in preserved blood modules highlights tissue-specific expression differences between blood and neural systems. Several hub genes overlap with known pharmacological targets, suggesting potential in translational relevance. Conclusions: Together, these findings reveal conserved blood-based transcriptional modules that suggest parallel central neurodegenerative processes and may support future biomarker development and possible therapeutic exploration. Full article

Schizophrenia is a highly polygenic and clinically heterogeneous disorder. We first review layer-specific evidence across genetics, epigenetics, transcriptomics, proteomics, and patient-derived induced pluripotent stem cell (iPSC) models, then integrate cross-layer findings. Genetics research identifies widespread risk architecture. Hundreds of loci from common, rare, and CNV analyses. Epigenetics reveals disease-associated DNA methylation and histone-mark changes. These occur at neuronally active enhancers and promoters, together with chromatin contacts that link non-coding risk to target genes. Transcriptomics show broad differential expression, isoform-level dysregulation, and disrupted co-expression modules. These alterations span synaptic signaling, mitochondrial bioenergetics, and immune programs. Proteomics demonstrates coordinated decreases in postsynaptic scaffold and mitochondrial respiratory-chain proteins in cortex, with complementary inflammatory signatures in serum/plasma. iPSC models recapitulate disease-relevant phenotypes: including fewer synaptic puncta and excitatory postsynaptic currents, electrophysiological immaturity, oxidative stress, and progenitor vulnerability. These same models show partial rescue under targeted perturbations. Integration across layers highlights convergent pathways repeatedly supported by ≥3 independent data types: synaptic signaling, immune/complement regulation, mitochondrial/energetic function, neurodevelopmental programs and cell-adhesion complexes. Within these axes, several cross-layer convergence genes/proteins (e.g., DLG4/PSD-95, C4A, RELN, NRXN1/NLGN1, OXPHOS subunits, POU3F2/BRN2, PTN) recur across cohorts and modalities. Framing results through cross-layer and shared-pathway convergence organizes heterogeneous evidence and prioritizes targets for mechanistic dissection, biomarker development, and translational follow-up. Full article

Gliomas are aggressive brain tumours with diverse histological and molecular features, complicating accurate diagnosis and treatment. Dysregulated lipid metabolism contributes to glioma progression, and analysing lipid profiles in plasma and tissue may enhance diagnostic and prognostic accuracy. This study investigated lipid dysregulation to identify key lipid signatures that distinguish glioma from other brain diseases and examined the associations between lipid biomarkers in glioma tissue and plasma. Biospecimens from 11 controls and 72 glioma patients of varying grades underwent lipidomic profiling using liquid chromatography-mass spectrometry. Univariate and multivariate analyses identified differentially abundant lipids, and correlation analysis evaluated the associations between tissue and plasma biomarkers. Lipidomic analysis revealed distinct lipid profiles in the tissues and plasma of glioma patients compared to those of controls. Prominent lipid metabolites in glioma tissues included LPC 21:3 (AUC = 0.925), DG 43:11 (AUC = 0.906), and PC 33:1 (AUC = 0.892), which served as effective biomarkers. Conversely, in plasma, lipid metabolites such as phosphatidylethanolamine (PE 21:3, AUC = 0.862), ceramide-1-phosphate (CerP 26:1, AUC = 0.861), and sphingomyelin (SM 24:3, AUC = 0.858) were identified as the most promising lipid biomarkers. Significant positive and negative correlations were observed between the tissue and plasma lipid biomarkers of glioma patients. Lipidomic profiling revealed aberrant lipid classes and pathways in glioma tissues and plasma, enhancing understanding of glioma heterogeneity and potential clinical applications. Full article

The adrenal glands are central to the stress response in cetaceans, yet their morphological and molecular changes under chronic stress remain poorly described. We investigated adrenal histology and protein composition in stranded common dolphins (Delphinus delphis) to assess whether post-mortem material can provide insights into stress physiology. Adrenal glands from 58 dolphins recovered along the Irish coast during a period of reported nutritional stress in the species were analyzed for adrenal mass, cortex-to-medulla (C:M) ratios, and cortical cell density. Additionally, two archival formalin-fixed, paraffin-embedded (FFPE) tissues were included in a pilot trial to assess the feasibility of protein extraction and mass spectrometry analysis. While adrenal mass did not differ significantly between stress types, chronically stressed dolphins exhibited significantly higher C:M ratios and cortical mass, consistent with cortical hypertrophy. Protein extraction from FFPE tissues was feasible, with the in-gel digestion method yielding more proteins (136) than the filter-aided sample preparation method (22). These findings demonstrate that histological and proteomic approaches can detect stress-related signatures in dolphins and highlight the potential of archival tissues for retrospective biomarker discovery. Full article

Anti-PD-1 therapies have transformed cancer treatment by restoring antitumor T cell activity. Despite their broad clinical use, variability in treatment response and immune-related adverse events underscore the need for therapeutic optimization. This article provides an integrative overview of the pharmacokinetics (PKs) of anti-PD-1 antibodies—such as nivolumab, pembrolizumab, and cemiplimab—and examines pharmacokinetic–pharmacodynamic (PK-PD) relationships, highlighting the impact of clearance variability on drug exposure, efficacy, and safety. Baseline clearance and its reduction during therapy, together with interindividual variability, emerge as important dynamic biomarkers with potential applicability across different cancer types for guiding individualized dosing strategies. The review also discusses established biomarkers for anti-PD-1 therapies, including tumor PD-L1 expression and immune cell signatures, and their relevance for patient stratification. The evidence supports a shift from traditional weight-based dosing toward adaptive dosing and therapeutic drug monitoring (TDM), especially in long-term responders and cost-containment contexts. Notably, the inclusion of clearance-based biomarkers—such as baseline clearance and its reduction—into therapeutic models represents a key step toward individualized, dynamic immunotherapy. In conclusion, optimizing anti-PD-1 therapy through PK-PD insights and biomarker integration holds promise for improving outcomes and reducing toxicity. Future research should focus on validating PK-based approaches and developing robust algorithms (machine learning models incorporating clearance, tumor burden, and other validated biomarkers) for tailored cancer treatment. Full article

Background/Objectives: Bladder cancer is characterized by high recurrence and progression rates, posing a challenge to current diagnostic and treatment strategies. This review aims to provide a comprehensive overview of emerging technologies, including novel PET tracers, AI-assisted cystoscopy, theragnostics, and molecular biomarkers. Methods: We performed a narrative review of the recent literature focusing on innovations in imaging, AI, theragnostics, and biomarker research relevant to bladder cancer diagnosis and management. Results: Several novel PET tracers, such as 68Ga-PSMA and fibroblast activation protein inhibitor (FAPI), demonstrated potential in improving detection sensitivity. AI-enhanced cystoscopy has shown promise in real-time lesion detection, while theragnostic agents enable combined diagnostic and therapeutic applications. Advances in molecular biomarkers, including circulating Tumor DNA (ctDNA) and gene expression signatures, offer new avenues for patient stratification and monitoring. Conclusions: Integration of advanced imaging, AI, theragnostics, and biomarker analysis may transform bladder cancer management, supporting personalized and more effective care strategies. Full article

Fibromyalgia is a chronic syndrome characterized by widespread musculoskeletal pain, fatigue, non-restorative sleep, and cognitive impairment. Its pathogenesis reflects a complex interplay between central and peripheral mechanisms, including altered pain modulation, neuroinflammation, mitochondrial dysfunction, autonomic imbalance, and genetic and epigenetic factors. Evidence from neuroimaging, omics studies, and neurophysiology supports this multifactorial model. Epidemiological updates confirm a global prevalence of 2–8%, with a strong female predominance and a significant impact on quality of life and healthcare costs. Diagnostic criteria have evolved from the 1990 American College of Rheumatology tender points to the 2010/2011 revisions and the 2016 update, improving case ascertainment but still lacking objective biomarkers. Recent omics and systems biology approaches have revealed transcriptional, proteomic, and metabolic signatures that may enable molecularly informed stratification. Therapeutic management remains multidisciplinary, combining pharmacological interventions (e.g., duloxetine, pregabalin, milnacipran) with non-pharmacological strategies such as graded aerobic exercise and cognitive behavioral therapy. Emerging approaches include drug repurposing to target neuroinflammation, mitochondrial dysfunction, and nociceptive pathways. Despite promising advances, progress is limited by small sample sizes, heterogeneous cohorts, and lack of standardization across studies. Future priorities include large-scale validation of biomarkers, integration of multi-omics with clinical phenotyping, and the design of precision-guided trials. By synthesizing mechanistic insights with clinical evidence, this review provides an updated framework for the diagnosis and management of fibromyalgia, highlighting pathways toward biomarker-guided, personalized medicine. Full article

Background: Personalizing adjuvant chemotherapy (ACT) after curative resection in early-stage NSCLC remains unmet because prior ACT-biomarker findings rarely reproduce across studies. Key barriers are platform and preprocessing heterogeneity, dominant batch effects, and incomplete ACT annotations. As a result, many signatures that perform well in a single cohort fail during external validation. We created an open, harmonized meta-database linking gene expression with curated ACT exposure and survival to enable fair benchmarking and modeling. Methods: A PRISMA-guided search of 999 GEO studies (through January 2025) used LLM-assisted triage of titles, clinical tables, and free text to identify datasets with explicit ACT status and patient-level survival. Eight Affymetrix microarray cohorts (GPL570/GPL96) met eligibility. Raw CEL files underwent robust multi-array average; probes were re-annotated to Entrez IDs and collapsed by median. Covariate-preserving ComBat adjusted platform/study while retaining several clinical factors. Batch structure was quantified by principal-component analysis (PCA) variance, silhouette width, and UMAP. Two quality-control (QC) filters, median M-score deviation and PCA leverage, flagged and removed technical outliers. Results: The final meta-database comprises 1340 patients (223 (16.6%) ACT; 1117 (83.4%) observation), 13,039 intersecting genes, and 594 overall-survival events. Batch-associated variance (PC1 + PC2) decreased from 63.1% to 20.1%, and mean silhouette width shifted from 0.82 to −0.19 post-correction. Seven arrays (0.5%) were excluded by QC. Event depth supports high-dimensional survival and heterogeneity-of-treatment modeling, and the multi-cohort design enables internal–external validation. Conclusions: This first open, rigorously harmonized NSCLC transcriptomic database provides the sample size, demographic diversity, and technical consistency required to benchmark ACT-benefit markers. By making these data openly available, it will accelerate equitable precision-oncology research and enable data-driven treatment decisions in early-stage NSCLC. Full article

Background: Maple syrup urine disease (MSUD) is a genetic disorder caused by mutations in the branched-chain α-ketoacid dehydrogenase (BCKDH) complex, leading to toxic buildup of branched-chain amino acids (BCAAs) and their ketoacid derivatives. While newborn screening (NBS) and molecular testing are standard diagnostic tools, they face challenges such as delayed results and false positives. Untargeted metabolomics has emerged as a complementary approach, offering comprehensive metabolic profiling and potential for novel biomarker discovery. We previously applied untargeted metabolomics to neonates with MSUD, identifying distinct metabolic signatures. Objective: This follow-up study investigates metabolic changes and biomarkers in pediatric MSUD patients and explores shared dysregulated metabolites between neonatal and pediatric MSUD. Methods: Dried blood spot (DBS) samples from pediatric MSUD patients (n = 14) and matched healthy controls (n = 14) were analyzed using LC/MS-based untargeted metabolomics. Results: In pediatric MSUD, 3716 metabolites were upregulated and 4038 downregulated relative to controls. Among 1080 dysregulated endogenous metabolites, notable biomarkers included uric acid, hypoxanthine, and bilirubin diglucuronide. Affected pathways included sphingolipid, glycerophospholipid, purine, pyrimidine, nicotinate, and nicotinamide metabolism, and steroid hormone biosynthesis. Seventy-two metabolites overlapped with neonatal MSUD cases, some exhibiting inverse trends between age groups. Conclusion: Untargeted metabolomics reveals that the metabolic profiling of MCUD pediatric patients different from that of their controls. Also, there are valuable age-specific and shared metabolic alterations in MSUD, enhancing the understanding of disease progression in MSUD patients. This supports its utility in improving diagnostic precision and developing personalized treatment strategies across developmental stages. Full article

Background: Invasive fungal infections (IFIs) remain a major cause of morbidity and mortality among immunocompromised patients, despite advances in antifungal therapy. Conventional diagnostics are limited, highlighting the need for novel biomarkers. Circulating microRNAs (miRNAs) and cell-free DNA (cfDNA) have emerged as promising tools due to their roles in immune regulation, pathogen–host interactions, and disease monitoring. This systematic review and meta-analysis evaluate their diagnostic and prognostic potential in fungal infections. Methods: A systematic search of PubMed, Web of Science, SCOPUS, and EMBASE was conducted up to May 2025 in line with PRISMA guidelines (PROSPERO protocol CRD42021287150). Eligible studies included clinical research on confirmed fungal infections assessing cfDNA or miRNAs. Random-effects meta-analyses were performed for cfDNA, and miRNA findings were synthesized descriptively. Results: In total, 526 studies were included. cfDNA positivity was observed in 12% of all tested samples (95% CI: 0.06–0.22) and in 79% of patients with proven fungal infections (95% CI: 0.62–0.90), supporting its value as a minimally invasive, culture-independent diagnostic marker. Six studies on miRNAs identified disease-specific signatures, including miR-132 and miRNA panels for aspergillosis, with high diagnostic accuracy (AUC ≥ 0.98). miR-146a, miR-223, and miR-545 further correlated with prognosis and mortality. Conclusions: cfDNA and miRNAs show strong potential for early diagnosis, prognosis, and treatment monitoring in IFIs. Standardized methodologies and large-scale validation are essential for clinical translation. Full article

Introduction: Primary glomerulopathies are immune-driven kidney diseases. IgA nephropathy (IgAN) and membranoproliferative glomerulonephritis (MPGN) are prevalent entities with a risk of chronic progression. Immune checkpoints, such as PD-1/PD-L1, CTLA-4/CD86, and CD200R/CD200, regulate activation and tolerance in T, B, and NK cells, and also exist in soluble forms, reflecting systemic immune balance. Objective: To compare immune checkpoint profiles in IgAN and MPGN versus healthy volunteers (HV) through surface expression, soluble serum levels, and PBMC transcripts, with attention to sex-related differences and diagnostic value assessed by ROC curves. Materials and Methods: Ninety age-matched subjects were studied: IgAN (n = 30), MPGN (n = 30), HV (n = 30). Flow cytometry evaluated checkpoint expression on CD4+/CD8+ T cells, CD19+ B cells, and NK cells. ELISA quantified sPD-1, sPD-L1, sCTLA-4, sCD86, sCD200, sCD200R; PBMC transcript levels were assessed. Group comparisons, sex stratification, and ROC analyses were performed. Results: Lymphocyte distributions were preserved, but IgAN patients showed anemia and impaired renal function, while MPGN patients had greater proteinuria and dyslipidemia. GN patients displayed increased PD-1/PD-L1 and CD200R/CD200, with reduced CTLA-4/CD86, compared to HV. Serum analysis revealed elevated sPD-1, sPD-L1, sCD200, sCD200R and decreased sCTLA-4, sCD86. PBMC transcripts paralleled these trends, with PD-1/PD-L1 mainly increased in MPGN. Sex had minimal impact. ROC analyses showed strong GN vs. HV discrimination by CD19⁺CTLA-4⁺, PD-1/PD-L1, and CD200/CD200R, but limited ability to separate IgAN from MPGN. Conclusions: IgAN and MPGN share a sex-independent checkpoint signature: PD-1/PD-L1 and CD200R/CD200 upregulation with CTLA-4/CD86 downregulation. CD19⁺, CTLA-4⁺, and soluble PD-1/PD-L1/CD200(R) emerge as promising biomarkers requiring further validation. Full article

Background/Objectives: Galectin-3 (Gal-3), encoded by LGALS3, is a β-galactoside-binding lectin involved in diverse tumor-associated processes, including immune modulation, cell cycle regulation, and stress adaptation. Despite its known roles in cancer biology, the full extent of its molecular functions and prognostic relevance across tumor types remains incompletely understood. This study aimed to systematically investigate the transcriptomic impact of LGALS3 deletion and assess its clinical significance in cancer. Methods: We analyzed CRISPR-Cas9 knockout transcriptomic data from the SigCom LINCS database to characterize the consensus gene signature associated with LGALS3 loss using functional enrichment analyses. Pan-cancer survival analyses were conducted using TIMER2.0. Differential Gal-3 protein levels in ductal adenocarcinoma and normal pancreatic tissues were evaluated using the Human Protein Atlas. Finally, functional analyses were performed in pancreatic ductal adenocarcinoma (PDAC). Results: LGALS3 deletion across multiple cancer cell lines led to transcriptomic changes involving mitotic progression, stress responses, and axonal guidance pathways. High LGALS3 expression was significantly associated with worse overall survival in lower-grade glioma, PDAC, uveal melanoma, and kidney renal papillary cell carcinoma. LGALS3 knockout in YAPC cells recapitulated the pan-cancer findings, linking LGALS3 to cell morphogenesis and proliferation. Conclusions: These findings identify Galectin-3 as a key regulator of oncogenic programs and a potential prognostic biomarker in PDAC and other malignancies, with implications for therapeutic targeting. Full article