Search Results (7,750)

Background: Alopecia areata (AA) is a common autoimmune alopecia disease. Evidence suggests that autophagy-related genes (ARGs) may contribute to its pathophysiology. This study aims to explore and identify potential autophagy-related biomarkers and molecular subtypes in AA. Methods: In this study, autophagy-related differential expression genes (ARDEGs) in AA were identified by comparing the differentially expressed genes (DEGs) in the GSE68801 dataset with the ARGs. Then, we applied three different machine learning methods to identify key hub genes and further verified them on independent datasets. We used the receiver operating characteristic (ROC) curve to evaluate the diagnostic potential of these hub genes and constructed a predictive nomogram. In addition, this study also used the consensus clustering method to define two AA subtypes and explored their immune characteristics and functional pathways through ssGSEA, MCPcounter and enrichment analysis. Experimental validation included qRT-PCR for four hub genes and Western blotting for critical autophagy markers. Results: Our analysis detected 10 ARDEGs in AA. Applying three machine learning algorithms, we identified four candidate hub genes, ATG9B, EIF4EBP1, WIPI1 and CCR2, and verified their expression patterns in independent cohorts. The combined four-gene model and nomogram showed potential diagnostic performance. Consensus cluster analysis divided AA cases into two subtypes, each associated with different immune infiltration and functional pathways. Downregulation of ATG9B and EIF4EBP1 and upregulation of CCR2 were verified by qRT-PCR. Western blotting further suggested altered autophagy-related protein expression in AA lesions, characterized by a reduced LC3B-II/I ratio and Beclin-1 expression and increased SQSTM1 expression. Conclusions: This study identified four candidate autophagy-related genes and two exploratory molecular subtypes in AA and may provide clues for understanding autophagy-related immune dysregulation and support further validation of candidate diagnostic markers. Full article

Acerola (Malpighia emarginata DC.) is one of the richest natural sources of vitamin C and an important source of phenolic compounds, carotenoids, and bioactive polysaccharides. Although the fruit can be consumed fresh, it is more commonly processed into juices and frozen pulp, generating substantial amounts of by-products (pomace, peels, and seeds), corresponding to approximately 20–60% of the fruit biomass, with high phytochemical content. These fractions represent underutilized sources of bioactive compounds. This narrative review, supported by a structured literature search, integrates evidence on the phytochemical composition of acerola pulp and its by-products and relates these profiles to biological effects in experimental and human studies, focusing on compound characterization, composition–function relationships, and underlying mechanisms. Key compounds, including ascorbic acid, hydroxycinnamic acids, flavonoids, and polysaccharides, are associated with the modulation of redox homeostasis, inflammatory signaling, and lipid metabolism, particularly under high-fat dietary conditions. Human evidence remains limited but suggests matrix-dependent effects on vitamin C bioavailability and selected cardiometabolic markers. Overall, the evidence is constrained by methodological heterogeneity, limited clinical data, and insufficient characterization of bioactive fractions. Future research should prioritize detailed phytochemical profiling, dose–response relationships, bioavailability assessment, and well-controlled clinical trials incorporating molecular biomarkers, supporting the development of acerola-derived matrices as functional and bioactive-rich ingredients. Full article

Major depressive disorder (MDD) and anxiety disorders are increasingly understood as conditions involving complex metabolic dysregulation across multiple biological domains. This review aimed to synthesize current clinical and translational evidence on amino acid metabolism, lipid metabolism and short-chain fatty acids (SCFAs) as potential biomarkers, and components of integrative metabolic profiling in these disorders. A structured narrative approach was applied, focusing on studies assessing metabolomic alterations, their clinical correlates and their potential role in patient stratification, and treatment response. The available evidence indicates that amino acid disturbances, particularly within the tryptophan–kynurenine pathway, represent the most consistent and clinically interpretable findings. Lipid-related alterations, especially involving long-chain polyunsaturated fatty acids, provide complementary insights into membrane function, inflammation and neuroplasticity. In contrast, SCFAs appear to function as context-dependent markers rather than robust standalone biomarkers, with their clinical relevance depending on biological matrix, metabolic context and host–microbiota interactions. Importantly, most studies assess individual metabolites rather than integrated metabolic profiles, limiting their interpretability within a metabolomic framework. Overall, current evidence supports a shift toward integrative biomarker models that combine metabolic data with selected molecular and clinical parameters. Future research should focus on standardized, reproducible profiling approaches to enable biologically informed stratification and personalized treatment strategies. Full article

Background/Objectives: KRAS mutations are among the most common oncogenic driver alterations in non-small cell lung cancer (NSCLC) and define a biologically heterogeneous disease. In the current era of molecular oncology, with targeted therapies increasingly incorporated into clinical practice, the prognostic relevance of individual KRAS mutation subtypes and their relationship with immune biomarkers such as programmed cell death ligand 1 (PD-L1) require further clarification. This study aimed to evaluate the prognostic impact of KRAS mutation subtypes and their association with PD-L1 expression in patients with NSCLC. Methods: In this retrospective analysis, 150 patients with KRAS-mutant NSCLC who underwent next-generation sequencing at Trakya University Faculty of Medicine between January 2015 and December 2023 were included. Clinicopathological features, KRAS mutation subtypes, PD-L1 expression, and survival outcomes were assessed. Overall survival (OS) and progression-free survival (PFS) were estimated using the Kaplan–Meier method, and prognostic factors were evaluated using Cox regression analyses. Results: KRAS G12C was the most frequent subtype (40.7%), followed by G12V (20.7%) and G12D (14.7%). OS differed significantly among KRAS mutation subtypes (log-rank p = 0.007), with median OS values of 18 months for G12D, 11 months for G12C, 11 months for other rare variants, 9 months for G12A and G12V, and 5 months for G13. PD-L1 positivity was significantly higher in KRAS G12C tumors compared with non-G12C subtypes and remained independently associated with improved OS in multivariate Cox regression analysis (HR = 0.622; 95% CI, 0.426–0.907; p = 0.014). In multivariate analysis, age, ECOG performance status, disease stage, and PD-L1 positivity were independent prognostic factors, whereas KRAS mutation subtype did not retain independent prognostic significance. Conclusions: These findings suggest that KRAS-mutant NSCLC represents a clinically and molecularly heterogeneous subgroup and that integrating KRAS mutation subtypes with immune biomarkers may support more refined prognostic stratification. Full article

Background/Objectives: Liposarcoma represents a heterogeneous group of mesenchymal malignancies with distinct molecular profiles and clinical behaviors. While localized disease is managed with surgical resection, advanced or metastatic liposarcoma poses a significant therapeutic challenge due to limited response to traditional cytotoxic chemotherapy. This review summarizes current evidence-based systemic therapies and highlights recent advances in subtype-driven treatment strategies. Methods: We review key clinical trials supporting the use of anthracycline regimens, trabectedin, eribulin, and nuclear export inhibition with selinexor, as well as emerging targeted approaches directed at MDM2 and CDK4 amplification. In addition, we discuss the evolving role of immunotherapy, including checkpoint inhibitors and engineered T-cell receptor therapies targeting cancer–testis antigens. Results: Integrating molecular biology with therapeutic development, we emphasize the importance of histologic and genomic classification in guiding treatment selection and clinical trial design. Conclusion: Continued progress in biomarker-driven strategies and rational combination therapies is expected to further refine personalized treatment approaches and improve outcomes for patients with advanced liposarcoma. Full article

Obesity is a major global health challenge characterized by chronic low-grade inflammation, oxidative stress, and an increased risk of cardiometabolic disorders. Although sex-related differences in inflammatory and redox biomarkers have been reported in obese populations, the molecular mechanisms underlying this heterogeneity remain incompletely understood. In this study, we applied a proteomics-based approach to investigate urinary extracellular vesicles from 45 obese individuals (BMI 30–40 kg/m²; age 50–70 years) in order to identify molecular signatures associated with metabolic dysregulation. Shotgun proteomics analysis performed by nanoLC–MS/MS enabled the identification of 3822 proteins. Hierarchical clustering of proteomic profiles revealed two distinct molecular groups, predominantly enriched in males (Group I) and females (Group II). Label-free quantitative analysis identified 466 differentially abundant proteins between the two clusters. Functional enrichment analysis highlighted pathways associated with immune response, metabolic regulation, and redox homeostasis, including glycolysis/gluconeogenesis, lysosome activity, leukocyte transendothelial migration, and glutathione, cysteine and methionine metabolism. Notably, proteins related to ferroptosis were enriched, suggesting the involvement of iron-dependent oxidative cell death mechanisms in the metabolic imbalance observed in a subset of subjects. Furthermore, the non-enzymatic glycosylation of urinary proteins was significantly higher in Group I compared with Group II (p = 0.0002), indicating increased formation of advanced glycation products in individuals with a more pronounced pro-oxidant state. Preliminary follow-up data suggested a higher incidence of pathological events, including cardiovascular complications, among individuals belonging to Group I. Overall, these findings demonstrate that urinary proteomic profiling can identify distinct molecular phenotypes among obese individuals and highlight oxidative stress, ferroptosis, and protein glycation as potential determinants of metabolic vulnerability, supporting the use of non-invasive proteomic approaches for improved risk stratification in obesity. Full article

Exposure to blast waves without kinetic, penetrating, thermal, or toxic components causes a distinct form of traumatic brain injury, termed primary blast-induced TBI (pbTBI). Clinical manifestations of pbTBI span a wide spectrum, ranging from life-threatening intracranial hemorrhage, hyperemia, and delayed cerebral edema to mild and transient neurological symptoms without detectable structural abnormalities on routine imaging. At the mild end of the spectrum, symptoms after a single exposure may resolve quickly, yet repeated exposures—even at very low levels, termed “subconcussive”—can develop into post-concussive syndrome (PCS) or persistent post-concussive symptoms (PPCS) in a subset of individuals. Despite extensive studies, the molecular pathobiology linking primary blast exposure to delayed and sometimes chronic neurobehavioral deficits remains incompletely understood. A mechanistic framework connecting blast-wave physics to biomechanics to biological vulnerability may therefore help define exposure hazards, interpret clinical symptomatology, and guide diagnostic and therapeutic development. This review summarizes the physics of primary blast waves, the resulting biomechanical responses, and candidate biological substrates, emphasizing structures and interfaces with distinct acoustic impedances across anatomical, tissue, cellular, and molecular scales. We synthesize evidence supporting the hypothesis that the cerebral vasculature and endothelial cells represent critically vulnerable substrates of primary blast-wave injury, in part because the vascular tree constitutes the brain’s largest and most widely distributed interface between compartments with different acoustic impedances. Across experimental and human studies, endothelial stress, vascular injury, and downstream neuroinflammation emerge as convergent molecular responses to primary blast exposure. Temporal dynamics are central to understanding pbTBI because many blast-induced processes unfold in sequential phases. These observations support conceptualizing pbTBI as a condition characterized by prominent cerebrovascular injury of varying severity with secondary consequences for neuronal signaling, network function, and behavior. Within this framework, cerebrovascular and neurovascular unit (NVU) dysfunction provides a parsimonious bridge between primary blast-wave exposure and chronic symptom trajectories, where vascular pathology may offer more accessible therapeutic targets than neuronal injury. Key knowledge gaps include identifying which physical component(s) of the blast are most injurious, establishing biologically meaningful dose–response relationships at molecular and physiological levels, and defining windows of vulnerability during recovery that are relevant to repeated exposures. Addressing these gaps is essential for refining safety protocols, improving diagnostic specificity through mechanism-informed biomarkers, and developing evidence-based molecular and vascular therapeutic targets for pbTBI-associated conditions. Progress will require integrating waveform-aware dosimetry with longitudinal physiological and molecular monitoring across both preclinical and human cohorts. Such integration offers a practical path toward translating blast physics into actionable medical guidance for prevention, triage, and recovery management. Full article

Survivors of primary gastric lymphoma (PGL) face a significantly elevated and persistent risk of developing second primary malignancies (SPMs), with gastric adenocarcinoma representing the most frequent SPM and standardized incidence ratios reaching up to 16-fold above the general population. This excess risk persists for decades after initial treatment and is associated with increased cause-specific mortality compared to matched primary cancers. Among patients with PGL, approximately 5% develop gastric cancer (with two-thirds being metachronous), and nearly 15% harbor precancerous lesions including atrophic gastritis, intestinal metaplasia, and dysplasia. Beyond gastric malignancies, survivors also experience elevated rates of extra-gastric SPMs, particularly digestive system tumors (43%), respiratory cancers (21%), and urinary tract malignancies (13%). Key risk factors include treatment with immunochemotherapy or radiotherapy, advanced age, male sex, advanced stage at diagnosis, ulcerative-type lymphoma morphology, and persistent Helicobacter pylori (HP) infection. Patients receiving combined chemoradiotherapy demonstrate the highest SPM risk, particularly for gastric and pancreatic cancers. These findings underscore the critical importance of lifelong, risk-adapted surveillance strategies integrating both hematology and gastroenterology follow-up. Annual endoscopic surveillance is recommended for high-risk patients, with intervals adjusted according to lymphoma histology, HP status, and the presence of precancerous gastric lesions. Mandatory HP eradication with confirmation of response is essential for reducing gastric cancer risk. Future research priorities include prospective, standardized studies to better quantify SPM risk, validation of molecular and microbiological biomarkers for individualized risk stratification, and development of predictive models to enable personalized surveillance protocols and improve long-term outcomes in this vulnerable population. Full article

Neurodegenerative disorders, including Alzheimer’s disease (AD), Parkinson’s disease (PD), Huntington’s disease (HD), and amyotrophic lateral sclerosis (ALS), arise from highly interconnected molecular and cellular abnormalities that progressively lead to neuronal dysfunction, synaptic failure, and cell death. This review provides a unified framework to understand the interrelated molecular mechanisms driving these diseases, with a focus on identifying key disease-specific intervention nodes. Core contributors include oxidative stress, mitochondrial dysfunction, protein aggregation, neuroinflammation, and emerging roles of peroxisomal dysfunction in redox imbalance, lipid dysregulation, and inflammatory amplification. Single-target therapies often show limited efficacy due to the complex, interconnected nature of these pathways. In contrast, polypharmacology, which targets multiple disease-relevant mechanisms simultaneously, offers a more promising therapeutic strategy. This review critically examines how pathway crosstalk drives neurodegenerative progression, with particular emphasis on mitochondrial–ROS–inflammatory signaling, aggregation–proteostasis failure, synaptic–neuroimmune dysfunction, and gut–brain communication. It evaluates various multi-node intervention strategies, including multi-target-directed ligands (MTDLs), molecular hybrids, natural products, drug repurposing, and nanocarrier-based delivery systems. Advances in network pharmacology, artificial intelligence (AI), bioinformatics, and multi-omics have enhanced the identification of actionable therapeutic nodes, candidate compounds, and brain-targeted delivery platforms. Notably, the NOD-like receptor pyrin domain-containing protein 3 (NLRP3) inflammasome and cyclic GMP–AMP synthase (cGAS)—stimulator of interferon genes (STING) pathways—play distinct roles in neuroinflammation, amplifying neuronal damage by releasing inflammatory cytokines and inducing mitochondrial dysfunction. However, successful translation into clinical practice remains constrained by challenges such as blood–brain barrier penetration, patient heterogeneity, and biomarker limitations. The review advocates for a shift towards mechanism-informed, patient-stratified polypharmacological strategies to better address the network pathology of neurodegeneration, despite significant translational hurdles. Full article

Background/Objectives: Psychotic relapse affects over 80% of individuals with schizophrenia-spectrum disorders, driving long-term disability and hospitalization. Clinical relapse management relies on symptomatic monitoring without objective neurobiological tools to guide individualized antipsychotic decisions. Methods: This systematic review synthesizes evidence on neurophysiological, blood-based, molecular, neuroimaging, and digital biomarkers for relapse prediction in schizophrenia-spectrum disorders. Results: Following the PRISMA 2020 guidelines, five databases were searched through March 2026 for longitudinal biomarker studies. Quality was assessed using the Newcastle-Ottawa Scale and PROBAST; findings were synthesized narratively due to substantial heterogeneity. From the 6812 citations screened, 21 studies were included across clinical high-risk, first-episode, and established illness populations. Conclusions: Mismatch negativity and P300 event-related potential (P300) showed the most consistent associations with relapse vulnerability, with mismatch negativity demonstrating relative independence from antipsychotic effects. Inflammatory and neuroendocrine markers—interleukin-6, C-reactive protein, and cortisol awakening response—predicted poor treatment response in multiple longitudinal investigations. Peripheral blood gene expression profiling identified TCF4 network dysregulation as a candidate molecular marker of impending relapse. Neuroimaging models did not outperform standard clinical variables. Digital phenotyping showed ecological promise but remains methodologically nascent. No single biomarker achieves sufficient accuracy for clinical implementation. Neurophysiological and inflammatory markers are the most tractable candidates for monitoring protocols. Future research should prioritize multimodal longitudinal designs, external validation, and systematic antipsychotic confounding control. Among the biomarkers reviewed, mismatch negativity and the interleukin-6/cortisol awakening response combination represent the most tractable candidates for pilot clinical implementation, particularly in specialized early psychosis services and antipsychotic dose-reduction research contexts; no biomarker currently achieves sufficient accuracy for routine use in maintenance treatment decisions. Full article

The skin is a complex immunological organ in which reactive oxygen species (ROS)-related pathways and host–microbe interactions synergically maintain immune homeostasis. Dysregulation of several oxidative mechanisms, including lipid peroxidation, mitochondrial dysfunction, ferroptosis, and impaired antioxidant defenses, alongside gut microbiome imbalance, is increasingly recognized as a key modulator of the immune response involved in disease onset and progression. However, their role in immune-mediated dermatoses remains incompletely defined. This narrative review aims to provide a comprehensive overview of the contribution of these altered pathways to the pathogenesis and prognosis of the major immune-mediated skin diseases. Across all conditions examined, elevated oxidative biomarkers, such as malondialdehyde (MDA), advanced glycation end-products (AGEs), advanced oxidation protein products (AOPPs), 8-hydroxydeoxyguanosine (8-OHdG), and reduced antioxidant capacity are consistently reported. Ferroptosis, driven by iron-dependent lipid peroxidation and dysfunction of Glutathione peroxidase 4 (GPX4), emerges as a relevant cell death pathway, particularly in psoriasis and atopic dermatitis (AD). In parallel, dysbiosis of the gut and skin microbiomes, characterized by depletion of short-chain fatty acid (SCFA)-producing taxa such as Faecalibacterium prausnitzii, Bifidobacterium, and Akkermansia muciniphila, has been reported across multiple diseases. Particular attention is given to shared molecular axes, such as the disruption of epithelial barrier integrity, activation of innate and adaptive immune responses, and the role of microbial-derived metabolites in modulating redox signaling, unraveling a bidirectional crosstalk. Emerging therapeutic strategies targeting these bidirectional crosstalks show biological plausibility and promising preliminary results. Integrating redox and microbial profiling into clinical practice may improve patient stratification and foster the development of more personalized therapeutic approaches beyond conventional immunological treatments. Full article

Tuberculosis remains one of the leading infectious causes of morbidity and mortality worldwide, disproportionately affecting women of reproductive age, particularly in low- and middle-income countries. Tuberculosis during pregnancy represents a major clinical challenge, as physiological and immunological changes associated with pregnancy may obscure symptoms, delay diagnosis, and contribute to adverse maternal and perinatal outcomes. This narrative review provides an updated and clinically oriented overview of tuberculosis during pregnancy, with particular emphasis on diagnostic challenges, imaging strategies, microbiological testing, maternal–fetal complications, and therapeutic management. Key topics include symptom-based screening, tuberculin skin test and interferon gamma release assays, as well as molecular diagnostic methods such as GeneXpert Mycobacterium tuberculosis/Rifampicin (MTB/RIF) and Xpert MTB/RIF Ultra, chest radiography, computed tomography, and emerging biomarkers. We also discuss the impact of tuberculosis on pregnancy outcomes, including prematurity, low birth weight, maternal morbidity, and neonatal complications, as well as the particular challenges posed by human immunodeficiency virus HIV coinfection and multidrug-resistant tuberculosis. Current treatment strategies, preventive approaches, postpartum care, neonatal management, and Bacille Calmette–Guérin vaccination are reviewed in light of contemporary evidence and international recommendations. Finally, we highlight practical diagnostic algorithms, current evidence gaps, and priorities for future research aimed at improving maternal and neonatal outcomes in both high- and low-resource settings. Full article

In the human reproductive system, extracellular vesicles (EVs) have been recognized as playing a vital role in mediating cell–cell communication. They are considered critical for embryo development, implantation, gamete interaction, and fertilization. The various cargoes carried by EVs, depending on the physiological and pathological state of the cell, include proteins, lipids, nucleic acids, and mitochondrial components. EVs are recognized as critical carriers of redox-related signals and mitochondrial components, linking oxidative stress (OS) to reproductive failure and influencing gamete quality and embryo competence. Although considerable progress has been made, research remains poorly integrated, despite individual omics technologies providing valuable molecular insights. The use of multi-omics technologies, including transcriptomics, proteomics, metabolomics, and microbiome analysis, has been proposed as a global approach to understanding the complexities associated with EVs and discovering new biomarkers associated with infertility. ML and AI have been proposed to identify predictive signatures linked to ART effectiveness and reproductive outcomes, with a strong capacity to handle high-dimensional data. The review aims to provide an overview of current knowledge on EV-mediated redox–mitochondrial signaling in human reproduction, while highlighting the importance of emerging multi-omics and AI technologies for EV-mediated biomarker development. The review discusses the promise of EVs in the development of minimally invasive diagnostic approaches and therapeutic interventions, as well as the challenges in the standardization, integration, and clinical translation of EV-mediated research. In addition, the review proposes integrating computational approaches to better understand molecular pathways involved in the development of next-generation precision medicine in human reproduction. Full article

Background/Objective: With rising per capita sugar consumption, skin glycation-related issues including dullness, homeostasis disruption and accelerated wrinkling have gained widespread attention. However, globally standardized and rigorous evaluation criteria for anti-glycation efficacy remain lacking. This study aimed to establish stage-specific glycation injury cell models and elucidate the stage-dependent molecular mechanisms of glycation-induced fibroblast damage, providing a standardized reference for anti-glycation efficacy assessment. Methods: Three glycation injury models were constructed in human foreskin fibroblasts (HFF-1): early-stage (glucose-induced), intermediate-stage (glyoxal-induced), and late-stage (advanced glycation end products (AGEs)-induced). Core biomarkers including Nε-(carboxymethyl)lysine (CML), collagen type I (Col I) and elastin (ELN) were used to optimize modeling conditions via Cell Counting Kit-8 (CCK-8) and enzyme-linked immunosorbent assay (ELISA). Untargeted metabolomics based on ultra-high-performance liquid chromatography (UHPLC)-Q Exactive Orbitrap was applied to identify differential metabolites and perturbed pathways, following Metabolomics Standards Initiative (MSI) Level 2 identification criteria. Results: Optimal conditions were determined as 50 mmol/L glucose for 48 h, 0.5 mmol/L glyoxal for 48 h, and 200 μg/mL AGEs for 24 h. A total of 319, 34 and 148 differential metabolites were identified in the three groups, respectively. Six key pathways were significantly perturbed. Early and intermediate models shared similar mechanisms (purine metabolism disturbance), while the late model showed distinct alterations in pyrimidine, nicotinate, arachidonic acid and steroid hormone metabolism. Conclusions: Three stable stage-specific glycation models were successfully established in HFF-1 cells. Significant differences in metabolic profiles and mechanisms exist across the three stages, providing a rational basis for model selection and theoretical support for anti-glycation efficacy evaluation. Full article

Purpose: Prostate cancer is one of the most common malignancies in men, yet current prognostic methods remain suboptimal. Emerging evidence indicates that microRNAs (miRNAs) play critical roles in prostate cancer progression. This study aimed to identify miRNAs associated with adverse clinical outcomes by comparing miRNA expression profiles between prostate tumors with unfavorable versus favorable prognostic features. Materials and Methods: High-throughput next-generation sequencing (NGS) was used to analyze miRNA expression in formalin-fixed, paraffin-embedded prostate cancer tissue samples. Patients were classified into favorable or unfavorable prognosis groups based on risk stratification scores, Gleason grade group, and biochemical recurrence. Differentially expressed miRNAs were identified using a fold-change threshold ≥2 and a false discovery rate (FDR) <0.05. Predicted target genes and pathway analyses were conducted to generate candidate regulatory hypotheses rather than confirm mechanistic relationships. Results: Several miRNAs were differentially expressed according to prognostic category. miR-206 was significantly downregulated in high-risk tumors compared with low-risk tumors. High-Gleason-grade tumors showed reduced expression of miR-7704 and miR-4454, while miR-25-3p and let-7f-5p were upregulated. In patients with early biochemical recurrence, miR-7704 and miR-10400-5p were downregulated relative to those with prolonged recurrence-free survival. Target prediction analysis identified CPEB3, HAND1, PTAR1, and SPRYD4 as shared candidate targets, with CPEB3 emerging as a prioritized candidate supported by consistency in external datasets rather than a confirmed molecular target. Conclusions: Distinct miRNA expression patterns correlate with prostate cancer aggressiveness and clinical outcomes. miR-206, miR-7704, miR-4454, miR-25-3p, and let-7f-5p represent candidate prognostic biomarkers. Their shared target CPEB3 should be interpreted as a prioritized candidate for future investigation. Given the very small sample size and the lack of qRT-PCR and functional validation, these findings should be considered preliminary and hypothesis-generating, requiring validation in larger independent cohorts and experimental studies. Full article