Search Results (354)

Background and Objectives: Low-grade triple-negative breast carcinomas (LG-TNBCs) represent a rare subset of breast cancers that deviate from the aggressive clinical course typically associated with triple-negative tumors. This narrative review aims to consolidate current knowledge on LG-TNBCs, highlighting their diagnostic features, molecular characteristics, and clinical implications to guide appropriate patient management and prevent overtreatment. Materials and Methods: We conducted a comprehensive narrative review using PubMed/MEDLINE, Embase, and Scopus databases up to September 2025. Search terms included combinations of “triple-negative breast carcinoma”, “low-grade”, “adenoid cystic carcinoma”, “secretory carcinoma”, “acinic cell carcinoma”, “tall cell carcinoma with reversed polarity”, “low-grade adenosquamous carcinoma”, and “fibromatosis-like metaplastic carcinoma.” Studies reporting clinicopathologic, immunohistochemical, or molecular data were included. Results: LG-TNBCs include seven distinct entities: adenoid cystic carcinoma, secretory carcinoma, acinic cell carcinoma, tall cell carcinoma with reversed polarity, low-grade adenosquamous carcinoma, fibromatosis-like metaplastic carcinoma, and mucoepidermoid carcinoma. These neoplasms are characterized by distinct morphologic patterns, specific immunohistochemical profiles, and recurrent molecular alterations such as ETV6-NTRK3 fusions and MYB rearrangements. Despite their triple-negative immunoprofile, they demonstrate indolent clinical behavior with excellent prognosis and low metastatic potential, although local recurrence is reported in variants exhibiting infiltrative, locally aggressive behavior. Conclusions: Recognition of LG-TNBCs is essential to prevent overtreatment and guide personalized patient management. Molecular characterization provides diagnostic confirmation and therapeutic opportunities, particularly for NTRK-fusion-positive tumors treatable with targeted inhibitors, highlighting the importance of precision medicine in rare breast tumors. Full article

Atherogenic dyslipidemia (AD) is a high-risk phenotype for cardiovascular disease, characterized by elevated triglycerides, increased small dense low-density lipoprotein cholesterol (sdLDL-C), and frequently coexisting hypertension. Although FTO gene variants have been implicated in lipid dysregulation, their role in AD among Latin American women remains poorly defined. We conducted a case–control study in 219 working perimenopausal women (97 AD cases and 122 controls). Sociodemographic, clinical, and biochemical variables were assessed. Three FTO SNPs (rs9939609, rs9940128, and rs8050136) were genotyped. Associations were evaluated using logistic regression models adjusted for age and BMI, with gene–environment interactions tested for smoking. Linkage disequilibrium (LD) and haplotype analyses were also performed. Women with AD exhibited significantly higher triglycerides, LDL-C, and sdLDL-C, along with increased hypertension prevalence, but no differences in BMI or glycemia. Multivariable models identified LDL-C (aOR ≈ 8), triglycerides, sdLDL-C, and systolic blood pressure as the strongest determinants of AD. The rs8050136 AA genotype was associated with a fourfold higher risk (aOR = 4.12; 95% CI: 1.49–11.95, p = 0.007). Smoking independently doubled AD risk (aOR = 2.33) and amplified the effect of rs8050136. Adjusted haplotype analysis revealed that the A-A-A (aOR = 5.33; 95% CI: 1.42–20.00) and A-G-A combinations (aOR = 2.54; 95% CI: 1.01–6.38) were significantly associated with AD. FTO polymorphisms, particularly rs8050136 and the A-A-A and A-G-A haplotypes, contribute independently and supra-additively to AD risk. The observed gene–environment interaction with smoking emphasizes the multifactorial nature of AD and supports genotype-based risk stratification and targeted preventive strategies in precision cardiovascular medicine. Full article

Background/Objectives: Heart Failure (HF) remains a leading cause of hospitalization and mortality worldwide, representing a significant burden on patients and healthcare systems. Despite advances in pharmacological and device-based therapies, readmission rates remain high and traditional monitoring approaches often fail to detect early physiological deterioration. This review examines the clinical utility and implementation challenges of remote hemodynamic monitoring in HF, highlighting its role in improving patient outcomes and guiding precision care. Method: A comprehensive narrative review was conducted using PubMed, Scopus, and Web of Science databases to identify peer-reviewed English-language studies published in the past ten years. Results: Monitoring hemodynamic status is essential for preventing HF readmissions, as elevated filling pressures often precede symptoms. Previous studies suggest that traditional methods may be less effective in detecting early changes, which could contribute to delays in initiating treatment. Remote monitoring offers continuous, individualized assessment and has shown potential to reduce hospitalizations, though its effectiveness varies across populations and settings. Telemonitoring primarily targets patients at higher risk of hospitalization, such as those classified as New York Heart Association(NYHA) class III and individuals with comorbidities that exacerbate HF. Remote hemodynamic monitoring presents notable clinical advantages, although its widespread adoption faces several challenges (i.e., the invasiveness of some monitoring systems; limited patient adherence due to technical complexity or cognitive and physical barriers; difficulties associated with comorbidities; variability in the efficacy of monitoring strategies across populations; difficulties faced by healthcare teams in managing and interpreting large volumes of real-time data; cost-effectiveness issues related to devices and infrastructure costs). Addressing these limitations will be essential to fully understanding the potential of remote monitoring in HF care. Conclusions: Remote hemodynamic monitoring enables early detection of physiological deterioration in HF, allowing timely interventions that reduce hospitalizations and improve outcomes. Emerging evidence suggests that, in contrast to traditional approaches, this method has the potential to support more personalized, data-driven care. Integrating biopsychosocial, gender, and intersectional perspectives further aligns this strategy with precision medicine, enhancing its effectiveness and equity in clinical practice. Despite promising recent advances, further research is essential to broaden the scientific evidence base and to enhance support for clinical decision-making. Full article

Despite advances in lipid-lowering and antithrombotic therapy, patients with acute coronary syndromes remain at elevated risk for recurrent events due to persistent atherosclerotic inflammation. This review evaluates inflammation as a therapeutic target in secondary prevention and discusses established, investigational, and emerging strategies. Colchicine, now FDA-approved for cardiovascular risk reduction, lowered major adverse cardiovascular events in COLCOT and LoDoCo2. Canakinumab (IL-1β inhibition) reduced recurrent events in proportion to IL-6 and hsCRP suppression, while ziltivekimab (IL-6 inhibition) achieved profound biomarker reductions but remains investigational. Early-phase studies of anakinra (IL-1 receptor antagonist) and dapansutrile (oral NLRP3 inhibitor) showed anti-inflammatory effects in early trials, whereas varespladib and darapladib illustrated the challenges of targeting lipid-associated pathways. Beyond direct immunomodulators, GLP-1 receptor agonists and SGLT2 inhibitors provide both cardioprotective and anti-inflammatory benefits, reinforcing their expanding role post-ACS. Additional emerging avenues include triptolidiol, dasatinib, and BTK or JAK/STAT inhibitors, while novel approaches, such as nanozyme delivery systems and CRISPR-based editing, extend the therapeutic horizon. This review highlights the potential of inflammation-targeted therapies to advance secondary prevention in ACS by integrating current evidence and perspectives on future therapeutic developments. Full article

Background: Hemodynamic management in veno-arterial extracorporeal membrane oxygenation (V-A ECMO) is inherently complex, as extracorporeal circulation profoundly alters preload, afterload, ventriculo-arterial coupling and tissue perfusion. This review summarizes current and emerging monitoring strategies to guide initiation, maintenance and weaning. Methods: A structured literature search was performed in PubMed and Scopus (1990–2025), including clinical studies, consensus statement and expert reviews addressing hemodynamic monitoring in V-A ECMO. Results: A multiparametric framework is required. Echocardiography remains central for assessing biventricular performance, aortic valve dynamics and ventricular unloading. Pulmonary artery catheterization provides complementary data on filling pressures, cardiac output and global oxygen balance. Metabolic indices such as lactate clearance and veno-arterial CO₂ gap, together with regional oximetry (NIRS), inform the adequacy of systemic and tissue perfusion. Microcirculatory monitoring, though technically demanding, has shown prognostic value, particularly during weaning. Additional adjuncts include arterial pulse pressure, end-tidal CO₂ and waveform analysis. Phenotype oriented priorities, such as detection of differential hypoxemia, prevention of left ventricular distension or surveillance for limb ischemia, require tailored monitoring strategies. Artificial intelligence and machine learning represent future avenues for integrating multiparametric data into predictive models. Conclusions: No single modality can capture the hemodynamic complexity of V-A ECMO. Precision monitoring demands a dynamic, phenotype-specific and time-dependent approach that integrates systemic, cardiac, metabolic and microcirculatory variables. Such individualized strategies hold promise to optimize outcomes, reduce complications and align V-A ECMO management with the principles of precision medicine. Full article

Cancer therapy is rapidly evolving from a one-size-fits-all paradigm toward highly personalized approaches. Traditional chemotherapies and radiotherapies, while broadly applied, often yield suboptimal outcomes due to tumor heterogeneity and are limited by significant toxicities. In contrast, precision oncology tailors prevention, diagnosis, and treatment to the individual patient’s genetic and molecular profile. Key advancements underscore this shift: molecularly targeted drugs (e.g., trastuzumab for HER2-positive breast cancer, EGFR and ALK inhibitors for lung cancer) have improved efficacy and reduced toxicity compared to conventional therapy. Pharmacokinetic (PK) and pharmacodynamic (PD) considerations are central to personalizing treatment, explaining variability in drug exposure and response among patients and guiding dose optimization. Modern strategies like therapeutic drug monitoring and model-informed precision dosing seek to maintain drug levels in the therapeutic range, improving outcomes. Immunotherapies, including checkpoint inhibitors and CAR-T cells, have transformed oncology, though patient selection via biomarkers (such as PD-L1 expression or tumor mutational burden) is critical to identify likely responders. Innovative drug delivery systems, notably nanomedicine, address PK challenges by enhancing tumor-specific drug accumulation and enabling novel therapeutics. Furthermore, rational combination regimens (informed by PK/PD and tumor biology) are being designed to achieve synergistic efficacy and overcome resistance. Key barriers include the high cost of biomarker testing, insufficient laboratory infrastructure, and inconsistent reimbursement policies. Operational inefficiencies such as long turnaround times or lack of clinician awareness further limit the use of precision diagnostics. Regulatory processes also remain complex, particularly around the co-development of targeted drugs and companion diagnostics, and the evidentiary requirements for rare subgroups. Addressing these barriers will require harmonized policies, investment in infrastructure, and educational initiatives to ensure that the promise of personalized medicine becomes accessible to all patients. Ensuring that advances are implemented responsibly—guided by pharmacological insights, supported by real-world evidence, and evaluated within ethical and economic frameworks—will be critical to realizing the full potential of personalized cancer medicine. Full article

Background/Objectives: In reverse shoulder arthroplasty (RSA), precise K-wire positioning of the glenoid component is critical to prevent complications such as glenoid loosening or instability as well as premature implant failure. Optimal component placement must adhere to individualized preoperative plans to account for patient-specific anatomical conditions. Conventional methods often fail to achieve this level of accuracy, undermining the need for personalized medicine. Intraoperative navigation systems are growing in use to improve accuracy in orthopedic surgery. This study aimed to compare the accuracy of K-wire positioning in a 3D-printed model of the scapula using conventional versus navigated methods. Methods: We recruited 20 participants: 10 experienced surgeons and 10 inexperienced medical students. Each participant performed four K-wire drillings—two with conventional instruments and two with an intraoperative navigation system. A novel target system, BoneTrack3D, was used to measure accuracy. We assessed the absolute deviation of the entry and exit points as well as the three-dimensional drilling angle. Results: The navigated method was significantly more accurate for all measured parameters at a family-wise significance level of α = 0.05. The median absolute deviation for the entry point was 1.6 mm with navigation versus 3.0 mm with the conventional method (p < 0.001). Similarly, the exit point deviation was 1.8 mm with navigation versus 6.7 mm conventionally (p < 0.001). The drilling angle deviation also showed significant improvement with navigation, at 2.6° compared to 8.9° conventionally (p < 0.001). However, the navigated method took longer, with a median drilling time of 100.0 s compared to 55.0 s for the conventional method (p < 0.001). The navigated method provided consistent and superior results regardless of a participant’s surgical experience. Conclusions: Navigated techniques for K-wire positioning in RSA demonstrate enhanced accuracy in a 3D-printed model, effectively executing a precise, patient-specific preoperative plan. This could be a direct contribution to personalized medicine, ensuring the final implant alignment is tailored to the individual’s anatomy. Furthermore, intraoperative navigation may contribute to a flatter learning curve, thereby increasing accessibility for surgeons with varying levels of experience. Although navigation introduces additional costs and longer initial procedure times, these drawbacks could be offset by improved technical outcomes and a reduced risk of complications. Future studies, including randomized clinical trials and cost-effectiveness analyses, should seek to validate these results in clinical settings with longer follow-up periods and larger patient cohorts to define long-term value and utility of navigation systems in reverse shoulder arthroplasty. Full article

Only about 5% of colorectal cancers are hereditary, which is due to the low carrier rate of pathogenic gene mutations. The typical pattern of these cases is intergenerational aggregation within families and early onset. But public awareness of early diagnosis and intervention of HCRC is insufficient, resulting in most patients being diagnosed only after developing cancer, thereby missing the optimal window for treatment. This article reviews the latest developments in precision screening, treatment, evaluation and prevention strategies for HCRC, including innovative uses of artificial intelligence (AI) in molecular diagnostics, imaging technology advances, and potential application prospects. Regarding precision screening, tests of genomics, transcriptomics, microbiome, etc., combined with personalised risk stratification, can, respectively, effectively detect pathogenic mutations and “cancer-promoting” intestinal environments in the preclinical stage. AI combined with endoscopic and imaging tools has improved the accuracy of polyp detection and tumor profiling. Liquid biopsy and molecular marker detection provide new non-invasive monitoring solutions. In precision treatment, beyond traditional approaches like surgery and chemotherapy, immunotherapy with checkpoint inhibitors may be considered for HCRC patients with mismatch repair deficiency (dMMR). For patients harboring somatic mutations such as KRAS or BRAF V600E, targeted therapy can be guided by these specific mutations. Regarding precision assessment, AI incorporates microsatellite instability (MSI) detection and imaging diagnostic techniques, crucial for integrating genetic, environmental, and lifestyle data in follow-up. This helps assess the risk of recurrence and adjust the long-term medication regimens, as well as provide effective nutritional support and psychological counselling. In summary, the rapid development of precision medicine is driving the clinical management of HCRC into the era of tailored care, aiming to optimise patient outcomes. Full article

Genetic background is a critical determinant of disease expression, arrhythmic vulnerability, and therapeutic response in inherited cardiomyopathies. Implantable cardioverter-defibrillators (ICD) remain the cornerstone for primary prevention of sudden cardiac death, yet conventional selection based on left ventricular ejection fraction does not adequately reflect the heterogeneity of genetic substrates. Increasing evidence demonstrates that pathogenic variants differ not only in prevalence across cardiomyopathy subtypes but also in prognostic impact. Truncating variants, particularly in genes encoding structural proteins, are often associated with severe remodeling, progressive dysfunction, and high arrhythmic risk, whereas missense variants may confer variable expressivity, ranging from aggressive arrhythmogenic phenotypes to milder or late-onset disease. This variability underscores the importance of distinguishing variant classes in clinical decision-making. Integrating genetic information with advanced imaging markers, such as late gadolinium enhancement, allows refinement of arrhythmic risk stratification beyond static thresholds and supports more tailored ICD allocation. Nevertheless, translation into routine practice is limited by challenges in variant interpretation, phenotypic overlap between cardiomyopathy subtypes, and the lack of prospective validation of genotype-based models. In the precision medicine era, evolving strategies should move toward dynamic, multimodal approaches that combine genotype, phenotype, and imaging biomarkers, enabling more accurate prediction of arrhythmic risk and more cost-effective use of ICD therapy. Full article

Ovarian follicular fluid (FF) is a metabolically active and biomarker-rich medium that mirrors the oocyte microenvironment. Its analysis is increasingly recognized in infertility diagnostics and assisted reproductive technologies (ART) for assessing oocyte competence, understanding reproductive disorders, and guiding personalized treatment. However, FF’s high viscosity, complex composition, and biochemical variability challenge reproducibility in sample preparation and molecular profiling. Sonication-based extraction has emerged as an effective approach to address these issues. By exploiting acoustic cavitation, sonication improves protein solubilization, metabolite release, and lipid recovery, while reducing solvent use and processing time. This review synthesizes recent advances in sonication-assisted FF analysis across proteomics, metabolomics, and lipidomics, emphasizing parameter optimization, integration with advanced mass spectrometry workflows, and emerging applications in microfluidics, automation, and point-of-care devices. Clinical implications are discussed in the context of enhanced biomarker discovery pipelines, real-time oocyte selection, and ART outcome prediction. Key challenges, such as preventing biomolecule degradation, standardizing protocols, and achieving inter-laboratory reproducibility, are addressed alongside regulatory considerations. Future directions highlight the potential of combining sonication with multi-omics strategies and AI-driven analytics, paving the way for high-throughput, standardized, and clinically actionable FF analysis to advance precision reproductive medicine. Full article

Acute leukemias are highly aggressive hematologic malignancies that demand intensive chemotherapy regimens. However, drug toxicity remains a major barrier to treatment success and patient survival. In this context, pharmacogenomics offers a promising strategy by identifying single-nucleotide variants (SNVs) that influence drug metabolism, efficacy, and toxicity, ultimately impacting treatment outcomes. This study analyzed data from the ClinPGx/PharmGKB database to identify clinically annotated variants related to chemotherapy response in Acute Myeloid Leukemia (AML) and Acute Lymphoblastic Leukemia (ALL). A total of 24 variants were curated for AML and 57 for ALL. Among these, nonsynonymous variants were most frequent in ALL (31.6%), while synonymous variants predominated in AML (33.3%). Although traditionally considered neutral, synonymous and intronic variants may influence gene expression through regulatory or splicing mechanisms. The analysis revealed clinically significant variants associated with chemotherapy response, particularly in the ABCB1 gene, observed in 12.5% of AML and 10.5% of ALL cases. Several variants, particularly TPMT, NUDT15, ABCC1, SLC28A3, and RARG, were associated with severe adverse effects such as myelotoxicity, mucositis, cardiotoxicity, and hepatotoxicity. This study reinforces the importance of genetic variants in modulating the therapeutic response and toxicity to chemotherapy drugs in acute leukemias. Analysis of ClinPGx/PharmGKB data emphasizes ABCB1 as a potential resistance marker and supports pre-treatment genotyping of genes like TPMT and NUDT15 to prevent severe toxicities. Future advances should include the expansion of pharmacogenetic studies in underrepresented populations and the clinical validation of new markers in prospective trials, aiming to consolidate precision medicine as a routine part of the therapeutic management of acute leukemias. Full article

Secondary peritonitis is a life-threatening intra-abdominal condition arising from gastrointestinal perforation, chemical injury, or catheter-related infections, characterized by marked heterogeneity in presentation and progression. Major subtypes include stercoraceous peritonitis with fecal contamination, fibrinous peritonitis triggered by bile or gastric contents, peritoneal dialysis-associated infections, and pancreatitis-associated chemical peritonitis. Regardless of etiology, these conditions share profound local and systemic inflammatory responses, contributing to high morbidity and mortality. Biomarkers such as procalcitonin (PCT), interleukin-6 (IL-6), high mobility group box 1 (HMGB1), C-reactive protein (CRP), lipopolysaccharide (LPS), neutrophil-to-lymphocyte ratio (NLR), and neutrophil gelatinase-associated lipocalin (NGAL) have emerged as tools for early diagnosis, subtype stratification, and monitoring of therapeutic response. Their prognostic value is particularly relevant in peritoneal dialysis and postoperative intensive care. Advances in multi-omics, patient-derived organoids, peritoneum-on-chip models, and microbiota profiling are reshaping understanding of peritoneal pathophysiology, revealing cellular heterogeneity, immune-microenvironment interactions, and mechanisms of fibrotic remodeling. Key translational challenges include assessing whether omics-derived signatures can predict the need for early re-laparotomy or the risk of abdominal compartment syndrome. Integration of high-dimensional biomarker profiling with mechanistic and functional studies promises a new era of precision medicine in secondary peritonitis, enabling risk-adapted interventions, complication prevention, and tailored strategies to improve outcomes. Full article

Neurodevelopmental disorders (NDDs) represent a heterogeneous group of diseases with a variety of clinical presentations related to different genetic, epigenetic, and environmental etiologies. Numerous pathogenic variants have been identified by comprehensive genetic approaches such as next-generation sequencing and chromosomal microarray analyses. This study included eleven pediatric patients with NDDs who were referred to our Molecular Medicine (MM) unit for further diagnostic workup. Whole exome sequencing (WES) was performed, and data were analyzed as part of a contracted service with the National Genomic Center and iBioScience LTD. Likely pathogenic single nucleotide variants in genes DDX3X c.869C>A, p.S290* and CNOT1 c.920delG, p.G307Afs*32 in two patients, and pathogenic copy number variants in the 16p11.2 (16:29,690,418-30,200,285)x3 and 16p12.1-p11.2 (16:27,078,317-29,001,333)x3 regions in a third patient with NDDs were identified. In a fourth patient, the c.6839A>G, p.Gln2280Arg variant of uncertain significance was found in the NIPBL gene. Altogether, our study has revealed four novel variants in genes previously linked to NDDs. Identification of genetic causes of NDDs not only promotes establishing a more precise diagnosis and improves our understanding of disease pathogenesis but may also provide better means for developing preventive measures for the recurrence of this serious condition. Full article

Staining-based assays are widely used for cell analysis but are invasive, alter physiology, and prevent longitudinal monitoring. Label-free, morphology-based approaches could enable real-time, non-invasive drug testing, yet detection of subtle and dynamic changes has remained difficult. We developed a deep learning framework for stain-free monitoring of leukemia cell cultures using automated bright-field microscopy in a semi-automated culture system (AICE3, LABMaiTE, Augsburg, Germany). YOLOv8 models were trained on images from K562, HL-60, and Kasumi-1 cells, using an NVIDIA DGX A100 GPU for training and tested on GPU and CPU environments for real-time performance. Comparative benchmarking with RT-DETR and interpretability analyses using Eigen-CAM and radiomics (RedTell) was performed. YOLOv8 achieved high accuracy (mAP@0.5 > 98%, precision/sensitivity > 97%), with reproducibility confirmed on an independent dataset from a second laboratory and an AICE3 setup. The model distinguished between morphologically similar leukemia lines and reliably classified untreated versus differentiated K562 cells (hemin-induced erythroid and PMA-induced megakaryocytic; >95% accuracy). Incorporation of decitabine-treated cells demonstrated applicability to drug testing, revealing treatment-specific and intermediate phenotypes. Longitudinal monitoring captured culture- and time-dependent drift, enabling separation of temporal from drug-induced changes. Radiomics highlighted interpretable features such as size, elongation, and texture, but with lower accuracy than the deep learning approach. To our knowledge, this is the first demonstration that deep learning resolves subtle, drug-induced, and time-dependent morphological changes in unstained leukemia cells in real time. This approach provides a robust, accessible framework for label-free longitudinal drug testing and establishes a foundation for future autonomous, feedback-driven platforms in precision oncology. Ultimately, this approach may also contribute to more precise and adaptive clinical decision-making, advancing the field of personalized medicine. Full article

MicroRNAs (miRNAs) are critical regulators of gene expression in cancer biology and cardiovascular disease. miR-106b-5p, a member of the miR-106b-25 cluster, has been widely studied for its oncogenic activity in various malignancies. However, its role as a direct molecular driver of anthracycline-induced cardiotoxicity has only recently been uncovered. This finding highlights new therapeutic possibilities at the intersection of oncology and cardiovascular medicine. This review outlines the dual role of miR-106b-5p as a key modulator in both tumor progression and chemotherapy-induced cardiac dysfunction. miR-106b-5p is upregulated in numerous cancers—including breast, prostate, lung, gastric, colorectal, hepatocellular, and esophageal—and promotes tumorigenesis via suppression of tumor suppressors such as PTEN, BTG3, p21, and SMAD7, leading to activation of oncogenic pathways like PI3K/AKT and TGF-β. Importantly, we present the first evidence that miR-106b-5p is significantly upregulated in the myocardium in response to doxorubicin treatment, where it drives left ventricular dysfunction by targeting PR55α, a key regulator of PP2A activity. This pathway results in cytoplasmic HDAC4 accumulation, aberrant activation of the YY1 transcription factor, and upregulation of sST2, a biomarker linked to adverse cardiac remodeling and poor prognosis. In response, we developed AM106, a novel locked nucleic acid antagomir that silences miR-106 b-5p. Preclinical studies demonstrate that AM106 restores PR55α/PP2A activity, reduces sST2 expression, and prevents structural and functional cardiac damage without compromising anti-tumor efficacy. In parallel, artificial intelligence (AI) tools could be leveraged in the future—based on established AI applications in miRNA cancer research—to accelerate the identification of miR-106b-5p-related biomarkers and guide personalized therapy selection. Our findings position miR-106b-5p as a previously unrecognized molecular bridge between cancer and doxorubicin-induced cardiotoxicity. The development of the AM106 antagomir represents a promising approach with potential clinical applicability in cardio-oncology, offering dual benefits: tumor control and cardioprotection. Coupling this innovation with AI-driven analysis of patient data may enable precision risk stratification, early intervention, and improved outcomes. miR-106b-5p thus emerges as a central therapeutic target and biomarker candidate for transforming the clinical management of cancer patients at risk for heart failure. Full article