Music enhances lipid nanoparticle brain delivery and mRNA transfection in brain cells.

Radiation-responsive Salmonella mediate therapeutics precise delivery for synergistic tumor radio-immunotherapy.

Intensivists are often plagued with the challenges of managing critically ill patients in the neurocritical intensive care unit (neuro ICU); one such challenge is the level of illness and the need for sedation, inhibiting the provider’s ability to adequately assess the patient. Most sedatives alter neurological and physical exam findings, only compounding potential barriers to providing the best care for each patient. It is important to emphasize that even in the altered mentation of these patients, physical and neurological exams reign supreme as diagnostic tools and should be used in conjunction with multimodal neuromonitoring methods, rather than labs or imaging alone. Additionally, selecting the appropriate analgesic(s) and sedative(s) based on these findings are highly important when determining the best course of individualized management. Thus, providers in the neuro ICU should be highly familiar with the appropriate analgesic and sedative options available in order to determine not only which may be best for each patient, but to also better understand how each drug may impact assessment findings. This comprehensive review aims to provide a structured overview of the pertinent sedatives commonly used in neuro ICUs, their risks and benefits, and how providers can best utilize each in practice to further improve patient outcomes. The novel contribution of this work provides comparative drug tables, dosing guidance for pediatric and very elderly (> 85-years-old) populations, and an exploration into the future possibilities of utilizing artificial intelligence and the human gut microbiome to further enhance the prospects of precision medicine.

Development of extracellular vesicles in diagnostics and therapeutics: From extracellular vesicles to precision medicine.

Acute lymphoblastic leukemia (ALL) driven by KMT2A rearrangements (KMT2A-r) is an aggressive hematologic malignancy with poor prognosis and a high incidence in infants. While KMT2A fusion proteins drive leukemogenesis through transcriptional dysregulation, recent discoveries have highlighted the pivotal role of non-coding RNAs (ncRNAs) in shaping the molecular and epigenetic landscape of this disease. These key regulators of gene expression influence chromatin dynamics, transcriptional activation, and post-transcriptional control. Circular RNAs (circRNAs) contribute to genome instability and facilitate chromosomal translocations, while some fusion-derived circRNAs (f-circRNAs) sustain oncogenic signaling and promote chemoresistance. Long non-coding RNAs (lncRNAs) orchestrate transcriptional programs that maintain leukemic stem cell properties and reinforce aberrant self-renewal pathways. MicroRNAs (miRNAs) modulate critical oncogenic networks by regulating KMT2A fusion transcripts and downstream effectors, thereby impacting drug resistance, apoptosis, and proliferation. Meanwhile, enhancer RNAs (eRNAs) fine-tune transcriptional activity and epigenetic regulation, influencing KMT2A target gene expression and chromatin accessibility. Collectively, these ncRNAs integrate into the complex regulatory circuits of KMT2A-r ALL, revealing their potential as biomarkers for disease classification, risk stratification, and treatment response prediction. Understanding their interplay with KMT2A fusion proteins not only provides new insights into leukemogenesis but also highlights promising opportunities for therapeutic intervention and precision medicine in this high-risk leukemia subtype.

The integration of single-cell sequencing and organoid technologies has been transformative for biomedical research, enabling investigations of organ development, disease mechanisms, and therapeutic innovation at even finer resolutions. Organoids serve as 3D in vitro models that replicate the structural and functional complexity of human tissues, while single-cell sequencing can resolve cellular heterogeneity, transcriptional dynamics, and lineage trajectories at high resolution. This review systematically explores the synergistic potential of these two technologies across multiple domains. First, it describes their application in studying the developmental mechanisms of organs including the brain, lungs, heart, liver, intestines, and kidneys, revealing key signaling pathways and cellular interaction networks. Then, it details their application in studying in vitro models of various diseases, including neurodegenerative disorders, genetic diseases, infectious diseases, metabolic syndrome, and tumors, advancing the in-depth analysis of pathological mechanisms. By leveraging patient-derived organoid biobanks, combining these two technologies can accelerate drug screening and precision, while utilizing transplantable tissue constructs to pioneer regenerative medicine strategies. This review also highlights the strengths of combining these two technologies in dynamically decoding cellular behavior and communication networks. By constructing physiologically relevant multifunctional research platforms, the integration of single-cell sequencing with organoid models will accelerate the elucidation of disease mechanisms and drive innovative breakthroughs in precision medicine and regenerative medicine. Looking ahead, the deep integration of single-cell sequencing with organoids, combined with cutting-edge technologies such as spatial transcriptomics and gene editing, will continue to propel life sciences toward a transformative leap from descriptive research to mechanism-driven, precision-oriented, and personalized approaches.

Asthma is a mosaic of phenotypes shaped by complex host-environment interactions. Among these, the microbiome has moved to a central determinant of disease expression, and airway and gut microbiome should be seen as active players in asthma pathophysiology. This review critically examines how environmental exposures, including pollution, drugs, diet, and climate, remodel microbial ecosystems, and reprogram immune responses in adults with asthma, with emphasis on clinical translation. Advances from multiomics, large-scale cohorts, and Mendelian randomization studies reinforce the concept of the gut-lung axis as a decisive modulator of asthma outcomes. Airway dysbiosis, often marked by Proteobacteria dominance, consistently correlates with poor asthma control, exacerbations, and steroid resistance. Environmental determinants of microbiome reshape erode immune tolerance. Microbial metabolites such as short-chain fatty acids act as molecular messengers capable of restoring epithelial and immune balance. These findings challenge the traditional inflammatory-centric view of asthma and demand broader mechanistic frameworks. The microbiome should be considered a central piece of the puzzle in asthma research. Precision medicine in adult asthma will remain aspirational unless microbiome-informed biomarkers and interventions are embraced. Robust interventional studies are urgently needed to translate this promise into practice.

Moyamoya vasculopathy is a progressive cerebrovascular steno-occlusive disease with variable presentation. As revascularization techniques, antiplatelet therapies, and imaging-based artificial intelligence (AI) diagnostics continue to advance, there is an emerging opportunity to refine patient stratification by integrating genetic profiling, neuroimaging phenotypes, and circulating biomarkers. The RNF213 locus (particularly p.R4810K) represents the primary susceptibility allele in East Asian cohorts, with secondary contributors including ACTA2 and GUCY1A3 showing incomplete penetrance. Emerging. data reveal dysregulated lipid metabolism, impaired arginine-arginine-nitric oxide (NO) and methionine signaling, heightened oxidative stress, and ferroptotic pathways. Proteomic studies identify disrupted angiogenic and cytoskeletal programs with potential biomarker utility in cerebrospinal fluid and serum. Current diagnostic standards employ MRI/MRA and digital subtraction angiography. Observational data support antiplatelet agents, including cilostazol, in reducing stroke recurrence and mortality. Direct and combined bypass approaches demonstrate superior outcomes in adult hemorrhagic disease, whereas indirect revascularization predominates in pediatric populations. Emerging AI-integrated diagnostic algorithms incorporating imaging and multiomic data exhibit promising diagnostic accuracy. Systematic integration of genotypic and multiomic profiling with hemodynamic assessment could enhance prognostic precision, optimize surgical timing, and guide antiplatelet selection in Moyamoya. Next step priorities include studying ethnically diverse multicenter registries and rigorous trials evaluating targeted and regenerative therapeutic strategies. Digital subtraction angiography (DSA)-guided diagnosis and individualized revascularization strategies remain the clinical standard.

Circulating tumor DNA (ctDNA) analysis has emerged as a powerful and minimally invasive approach for genomic profiling of metastatic castration-resistant prostate cancer (mCRPC), enabling real-time detection of tumor-derived mutations that guide therapy. Approximately 20% of mCRPC patients harbor alterations in homologous recombination repair (HRR) genes, most commonly BRCA1/2 and ATM, which are actionable with different poly-(ADP-ribose) polymerase inhibitors (PARPIs) used as monotherapy or in combination with androgen receptor signaling inhibitors (ARSIs). A smaller subset of patients with mismatch repair deficiency (MMRd) or microsatellite instability-high (MSI-high) tumors may benefit from immune checkpoint blockade with pembrolizumab. Different FDA-approved liquid biopsy assays detect these actionable alterations when tissue biopsies are unavailable or insufficient. This review summarizes current evidence on ctDNA-based genotyping in mCRPC, highlighting clinically actionable mutations, corresponding targeted therapies, and technical and analytical considerations for clinical implementation. By capturing DNA shed from multiple metastatic sites, ctDNA profiling provides a comprehensive view of tumor heterogeneity and enables serial monitoring of molecular evolution. Overall, ctDNA analysis represents a transformative advance in precision oncology, supporting personalized treatment selection and ongoing assessment of therapeutic response in mCRPC.

In this study, a comprehensive bioinformatics workflow is employed to investigate the impact of APOE gene variants on Alzheimer's disease (AD) and to explore their relevance for improving therapeutic strategies. Multiple databases were screened to identify key non-synonymous single nucleotide polymorphisms (nsSNPs) in APOE. Six variants: rs769452 (L46P), rs429358 (C130R), rs267606664 (G145D), rs121918393 (R154S), rs7412 (R176C), and rs267606661 (R269G) were selected, of which five were predicted to be deleterious. Given its high interaction score (0.789), the FDA-approved AD drug Donepezil was chosen as the ligand to assess binding with both wild-type and mutant APOE proteins. Structural modeling using AlphaFold3 generated high-quality APOE structures, and in silico mutagenesis revealed mutation-dependent destabilization. AutoDock4 molecular docking was performed to evaluate binding affinities of Donepezil with the predicted active-site residues of wild-type and mutant APOE. Furthermore, 100 ns molecular dynamics simulations using AMBER20 were conducted for all APOE-Donepezil complexes. Analyses of RMSD, RMSF, and radius of gyration indicated overall structural stability, residue-level flexibility, and protein compactness throughout the simulations. Interaction profiling revealed stable hydrophobic contacts and hydrogen bonds in both wild-type and mutant complexes. Our findings suggest that structural variations arising from APOE genotypes may modulate Donepezil binding and potentially influence therapeutic response in AD patients. However, these computational predictions require validation through biophysical assays, cellular experiments, and genotype-stratified clinical studies. Integrating molecular modeling with experimental research will be essential for advancing APOE-guided precision medicine and optimizing Donepezil therapy for Alzheimer's disease.

Diabetes mellitus (DM) and its complications pose a major global health burden, while currently used biomarkers such as HbA1c and microalbuminuria remain limited for early diagnosis and individualized management. Klotho, originally identified as an anti-aging protein, has recently gained increasing attention due to its roles in mineral metabolism, oxidative stress regulation, inflammation, and fibrosis. This review discusses the biological functions of Klotho and its involvement in the pathogenesis of DM, with a particular emphasis on its regulatory mechanisms in glucose metabolism and oxidative stress. We comprehensively summarize recent findings on the role of Klotho in diabetic complications, including diabetic kidney disease, retinopathy, neuropathy, and cardiovascular disease, and highlight evidence on Klotho gene polymorphisms that influence susceptibility to DM and its complications across different populations. Furthermore, we analyze the limitations of current studies, including inconsistent findings on circulating Klotho levels, lack of standardized detection methods, and insufficient large-scale clinical trials. Finally, this review explores the potential of Klotho as both a biomarker and therapeutic target, and outlines future research directions focusing on standardization, mechanistic studies, and translational applications to advance precision medicine in diabetes management.

Replicability analysis is a cornerstone for identifying genuine genetic associations in genome-wide association studies (GWAS), yet existing methods are constrained by their failure to account for linkage disequilibrium (LD) structure among single nucleotide polymorphisms (SNPs) or underuse of auxiliary information, limiting their reliability and statistical power. We develop CARLIS, a comprehensive covariate-assisted replicability analysis method to enhance both statistical rigor and biological interpretability while maintaining asymptotic false discovery rate control. CARLIS innovatively leverages a triplet hidden Markov model (HMM) to jointly characterize heterogeneous LD structures across two primary studies and an integrated auxiliary covariate (obtained via the Cauchy combination rule). The derived CARLIS statistic enables more efficient ranking of replicable SNPs by synthesizing cross-study and cross-SNP information through forward and backward probabilities. Computational scalability to genome-wide analyses is achieved through semiparametric estimation of composite null proportions and heterogeneous non-null density functions embedded in the HMM forward-backward algorithm. Extensive simulations demonstrate that CARLIS outperforms competing methods in statistical power while maintaining asymptotic false discovery rate control. Applications to replicability analysis of Parkinson's disease GWAS and pleiotropy analysis of bipolar disorder and schizophrenia GWAS show that CARLIS identifies more biologically relevant replicable variants, highlighting its potential to accelerate functional genomics discovery and advance precision medicine.

Cancer cell plasticity drives metastasis and therapy resistance through dynamic transitions between epithelial, mesenchymal, and neural crest stem-like (NCSC) states; however, a unifying mechanism that stabilizes these transitions remains undefined. To address this gap, we introduce a N-cadherin (CDH2)-centered redox–adhesion–exosome (RAX) hub that links oxidative signaling, adhesion dynamics, and exosome-mediated immune communication into a closed-loop framework. Within this network, reactive oxygen species (ROS) pulses license epithelial–mesenchymal transition (EMT), AXL–FAK/Src signaling consolidates mesenchymal adhesion, and selective exosomal cargoes—including miR-21, miR-200, miR-210, and PD-L1—propagate plasticity and immune evasion. Lipid peroxidation acts as a central checkpoint connecting ROS metabolism to PUFA membrane remodeling and ferroptosis vulnerability, buffered by NRF2–GPX4 and FSP1/DHODH axes, thereby converting transient oxidative pulses into persistent malignant states. Mechanistically, the RAX hub synthesizes findings from EMT/CSC biology, ferroptosis defenses, and exosome research into a self-reinforcing system that sustains tumor heterogeneity and stress resilience. Evidence from single-cell and spatial transcriptomics, intravital ROS imaging, and exosome cargo-selector studies supports the feasibility of this model. We further outline validation strategies employing HyPer–EMT–CDH2 tri-reporters, CRISPR perturbation of YBX1/ALIX cargo selectors, and spatial multi-omics in EMT-high tumors. Clinically, tumors enriched in EMT/NCSC programs—such as melanoma, neuroblastoma, small-cell lung cancer, pancreatic ductal adenocarcinoma, and triple-negative breast cancer (TNBC)—represent RAX-dependent contexts. These insights highlight biomarker-guided opportunities to target adhesion switches, ferroptosis defenses, and exosome biogenesis through lipid peroxidation-centered strategies using liquid-biopsy panels (exosomal CDH2, miR-200, miR-210) combined with organoid and xenograft models. By linking lipid peroxidation to ferroptosis defense and oxidative stress adaptation, the RAX hub aligns with the thematic focus of lipid metabolism and redox control in cancer progression. Collectively, the RAX framework may provide a conceptual basis for precision oncology by reframing metastasis and therapy resistance as emergent network properties.

Epidermal growth factor receptor ( EGFR )-mutant non-small cell lung cancer (NSCLC) has exemplified the advancement of precision oncology, yet inevitable resistance to tyrosine kinase inhibitors (TKIs) remains a challenge. Over the past decade, EGFR targeted therapies have extended beyond metastatic disease into early-stage and locally advanced settings, as demonstrated by ADAURA, NeoADAURA, and LAURA studies, which established osimertinib as the standard of care therapy across disease stages. Despite these advances, questions remain regarding the role of chemotherapy, duration of adjuvant targeted therapy, and the integration of ctDNA-guided minimal residual disease (MRD) monitoring in the early-stage setting. For metastatic disease, frontline combination strategies, such as osimertinib plus chemotherapy (FLAURA2) and amivantamab plus lazertinib (MARIPOSA), building on the EGFR -TKI backbone have improved progression-free and overall survival, particularly in higher-risk subgroups. However, as more therapeutic options emerge in the frontline and beyond, optimal treatment selection and sequencing become increasingly complex and tailored to individual risk factors, patient preferences, and disease biology. Following progression on third-generation TKIs, potential avenues for overcoming resistance include mechanism-based strategies targeting MET amplification or EGFR C797S, as well as mechanism-agnostic approaches such as bispecific antibodies and antibody-drug conjugates (ADCs). Collectively, these recent advances reflect the dynamic nature of the therapeutic landscape for EGFR -mutant NSCLC, which is becoming increasingly individualized, mechanism-informed, and resistance-adaptive, in efforts to achieve durable systemic and intracranial disease control.

Nanoparticle (NP)-based technologies are transforming the management of central nervous system (CNS) disorders such as Alzheimer's disease (AD), Parkinson's disease (PD), multiple sclerosis (MS), and brain cancer (BC), glioblastoma, by surpassing the blood-brain barrier (BBB) and blood-brain tumor barrier (BBTB). This review integrates NP approaches, comprising organic (e.g. liposomes, polymeric NPs), inorganic (e.g. gold, iron oxide), carbon-based, and hybrid systems, to overcome disease-specific barriers. In AD, superparamagnetic iron oxide NPs (SPIONs) and gold NPs (AuNPs) improve amyloid-beta plaque and tau protein detection, while liposomes precisely deliver anti-amyloid drugs. For PD, dopamine-loaded liposomes and cerium oxide NPs reinstate dopaminergic function and decrease oxidative stress, with improved motor outcomes. In MS, PEGylated liposomes and PLGA NPs regulate autoimmune responses, inducing remyelination and attenuating neuroinflammation. For BC, dendrimers and magnetic NPs facilitate targeted chemotherapy delivery across the BBB/BBTB, improving glioblastoma treatment outcomes. We compare NP types critically based on physicochemical characteristics, efficacy, toxicity, and clinical translation potential, highlighting gaps in long-term safety and scalability. Challenges like NP toxicity and regulatory complexities are discussed, suggesting biocompatible designs and standardized FDA/EMA pathways. By consolidating diagnostic and therapeutic innovations, this review outlines a roadmap for NP-based precision medicine, paving the way for clinical translation and better patient outcomes in CNS disorders and brain cancer.

Pediatric inflammatory bowel disease (pIBD) often begins early in life, progresses rapidly, and is associated with impaired growth and delayed development. These challenges demand treatment strategies that address both intestinal inflammation and the broader developmental needs of children. This review summarizes current advances in small-molecule therapies for pIBD based on published clinical trials, real-world studies, and mechanistic investigations retrieved from PubMed and clinical trial registries. Special emphasis is placed on Janus kinase (JAK) inhibitors and sphingosine-1-phosphate (S1P) modulators, which represent the main translational research focus in pediatric IBD. JAK inhibitors such as tofacitinib and upadacitinib have demonstrated promising efficacy in pediatric patients with refractory disease, although their use remains off-label worldwide. Long-term safety concerns persist, including infection risk, developmental effects, and potential risks of malignancy or major adverse cardiovascular events. S1P modulators such as ozanimod are under clinical evaluation in children, but robust long-term data are still lacking. Emerging technologies such as single-cell and spatial profiling have begun to reveal age-dependent remodeling of gut immune architecture, emphasizing the importance of developmentally informed therapeutic approaches. Small-molecule therapies offer a promising and mechanistically precise direction for the management of pIBD. Future progress will depend on age-specific clinical trials, physiologically based pharmacokinetic modeling, and biomarker discovery through integrated multiomics. Collaborative multicenter research is essential to optimize the safety and efficacy of these agents in children.

Chronic Kidney Disease (CKD) is a progressive condition characterized by the gradual loss of renal function over time, affecting millions worldwide and representing a significant public health challenge. CKD is associated with increased morbidity and mortality, primarily due to cardiovascular complications, and its prevalence continues to rise due to factors such as diabetes, hypertension, and aging populations. Despite advances in understanding its etiology, early detection remains a challenge, and current diagnostic methods often identify the disease at advanced stages, limiting therapeutic options and impacting patient outcomes. Early diagnosis of CKD is crucial for implementing interventions that can slow disease progression, prevent complications, and improve quality of life. Consequently, there is a growing emphasis on personalized management strategies tailored to the unique molecular and clinical profiles of patients. Personalized approaches enable targeted therapies, optimize treatment efficacy, and reduce adverse effects, ultimately transforming CKD care from a one-size-fits-all model to precision medicine. Multi-omics approaches have emerged as powerful tools in modern medicine, offering comprehensive insights into the molecular landscape of diseases like CKD. By integrating data from various biological layers, such as genomics, transcriptomics, proteomics, epigenomics, and metabolomics, researchers can achieve a holistic understanding of disease mechanisms, identify novel biomarkers, and uncover therapeutic targets. This systems biology perspective enables the characterization of individual variability, facilitating the development of personalized treatment strategies. In conclusion, multi-omics has the potential to revolutionize early diagnosis, refine patient stratification, and guide the design of targeted pharmacological interventions, paving the way for a new paradigm in disease management.

Sjögren's disease (SjD) exemplifies the intricate relationship between oral health and overall systemic wellness. Characterized by autoimmune-mediated destruction of exocrine glands, it commonly manifests as xerostomia (dry mouth) and keratoconjunctivitis sicca (dry eyes), yet its reach extends well beyond the salivary and lacrimal glands to involve musculoskeletal, renal, pulmonary, and neurological systems. Insights from national patient surveys underscore considerable unmet needs in SjD management, emphasizing the importance of early recognition of oral health challenges. Concurrently, advances in clinical and translational research deepen our understanding of SjD's underlying mechanisms, revealing novel diagnostic and therapeutic strategies that target immunological pathways, foster glandular regeneration, and may alter disease progression. By providing a cohesive synthesis of state-of-the-art evidence, this review aims to expand clinicians' and researchers' understanding of SjD pathogenesis, address new research areas and key gaps, highlight the critical role of medical partnerships in addressing both systemic and oral manifestations, and advance patient-centered strategies to improve detection, treatment, and long-term disease management of this multifaceted autoimmune disorder. We discuss immune-mediated tissue damage, the potential of emerging biomarkers, and innovative treatments, including biologic agents and regenerative techniques. Patient perspectives further illuminate the daily challenges posed by SjD, underscoring the need for interdisciplinary care models that integrate oral medicine, rheumatology, and other medical specialties. Taken together, these insights underscore the pressing need for heightened awareness and collaborative approaches to pave the way for precision medicine interventions that can transform current management paradigms and ultimately improve the lives of individuals affected by Sjögren's disease.

Neuropathic pain is a highly complex and disabling condition arising from diverse etiologies and characterized by significant biological, clinical, and neurofunctional heterogeneity. Contemporary analytical approaches—including predictive modeling, biomarker discovery, neuroimaging, electrophysiology, and physiological sensing—have begun to transform the way this condition is understood, diagnosed, and managed. This review integrates findings from twenty peer-reviewed studies across oncology, postsurgical pain, chronic neuropathic syndromes, and mechanistic research, with particular attention to implications for healthcare systems in Mexico, Colombia, and Ecuador. Using an integrative methodological framework grounded in the scientific method and refined through structured thematic analysis, the evidence reveals that analytical tools consistently outperform traditional assessment strategies when identifying high-risk patients, characterizing biological mechanisms, and distinguishing neuropathic pain phenotypes. Predictive models demonstrate strong potential for early identification of oncologic and postsurgical neuropathic pain trajectories. Molecular and metabolomic analyses highlight specific biochemical signatures linked to neuropathic progression. Neuroimaging and EEG studies reveal reproducible cortical and electrophysiological patterns that differentiate neuropathic pain states, while physiological sensing frameworks offer objective measurements of pain intensity in real time. Conceptual and therapeutic frameworks provide essential coherence, ensuring that analytical advances remain aligned with established diagnostic standards. Although scientific production is concentrated in Europe, North America, and Asia, the emerging participation of Latin America underscores the need for broader global integration of analytic methodologies. Overall, the findings indicate that analytic approaches are redefining neuropathic pain research, shifting the field from descriptive clinical observation toward mechanism-based, data-driven precision medicine capable of improving diagnosis, treatment, and health system responsiveness.

This study aimed to elucidate the molecular mechanisms underlying cisplatin resistance in oral squamous cell carcinoma (OSCC) and to identify prognostic biomarkers that can guide personalized treatment strategies. Differentially expressed genes (DEGs) between cisplatin-sensitive and resistant OSCC cells were identified using transcriptomic data from the GSE197561 dataset. Functional enrichment analyses were conducted to explore involved pathways. Weighted Gene Co-expression Network Analysis (WGCNA) and random survival forest algorithms were employed to identify key resistance-related gene modules and hub genes. Clinical relevance was validated using The Cancer Genome Atlas (TCGA) dataset, while immune cell profiling and functional validation in SCC9/CAL27 cisplatin-resistant models were conducted to elucidate biological significance. DEGs were significantly enriched in processes such as oxidative stress response, cell cycle regulation, and immune-inflammatory pathways. WGCNA and survival analysis identified a chemotherapy resistance-associated gene module and 10 core genes, including DUSP3 and SACM1L, whose high expression was correlated with poorer overall survival. A nomogram integrating TNM stage, age, and DUSP3 expression demonstrated superior predictive performance for patient prognosis. In analyses stratified by chemotherapy resistance, upregulated DUSP3 expression appeared to synergistically cooperate with malignant tumor progression. Immune profiling revealed reduced NK cell activity and decreased populations of resting CD4⁺ memory T cells in the resistant phenotype. Functional assays confirmed that cisplatin-resistant SCC9 and CAL27 cells exhibited accelerated proliferation and epithelial-mesenchymal transition (EMT), characterized by downregulated E-cadherin and upregulated N-cadherin and Vimentin. Notably, knockdown of DUSP3 significantly reversed these resistant phenotypes. This study provides a comprehensive multi-omics-based framework for understanding cisplatin resistance in OSCC. DUSP3 was identified as a key prognostic indicator, and the proposed nomogram may enhance precision oncology efforts for cisplatin-resistant OSCC patients.