Leveraging shape screening and molecular dynamics simulations to optimize PARP1-Specific chemo/radio-potentiators for antitumor drug design.

PARP1 plays a pivotal role in DNA repair within the base excision pathway, making it a promising therapeutic target for cancers involving BRCA mutations. Current study is focused on the discovery of PARP inhibitors with enhanced selectivity for PARP1. Concurrent inhibition of PARP1 with PARP2 and PARP3 affects cellular functions, potentially causing DNA damage accumulation and disrupting immune responses. In step 1, a virtual library of 593 million compounds has been screened using a shape-based screening approach to narrow down the promising scaffolds. In step 2, hierarchical docking approach embedded in Schrödinger suite was employed to select compounds with good dock score, drug-likeness and MMGBSA score. Analysis supplemented with decomposition energy, molecular dynamics (MD) simulations and hydrogen bond frequency analysis, pinpointed that active site residues; H862, G863, R878, M890, Y896 and F897 are crucial for specific binding of ZINC001258189808 and ZINC000092332196 with PARP1 as compared to PARP2 and PARP3. The binding of ZINC000656130962, ZINC000762230673, ZINC001332491123, and ZINC000579446675 also revealed interaction involving two additional active site residues of PARP1, namely N767 and E988. Weaker or no interaction was observed for these residues with PARP2 and PARP3. This approach advances our understanding of PARP-1 specific inhibitors and their mechanisms of action, facilitating the development of targeted therapeutics.

Canine Mammary Tumors: Classification, Biomarkers, Traditional and Personalized Therapies.

In recent years, many studies have focused their attention on the dog as a proper animal model for human cancer. In dogs, mammary tumors develop spontaneously, involving a complex interplay between tumor cells and the immune system and revealing several molecular and clinical similarities to human breast cancer. In this review, we summarized the major features of canine mammary tumor, risk factors, and the most important biomarkers used for diagnosis and treatment. Traditional therapy of mammary tumors in dogs includes surgery, which is the first choice, followed by chemotherapy, radiotherapy, or hormonal therapy. However, these therapeutic strategies may not always be sufficient on their own; advancements in understanding cancer mechanisms and the development of innovative treatments offer hope for improved outcomes for oncologic patients. There is still a growing interest in the use of personalized medicine, which should play an irreplaceable role in the research not only in human cancer therapy, but also in veterinary oncology. Moreover, immunotherapy may represent a novel and promising therapeutic option in canine mammary cancers. The study of novel therapeutic approaches is essential for future research in both human and veterinary oncology.

AUD in perspective.

Alcohol is a major cause of pre-mature death and individual suffering worldwide, and the importance of diagnosing and treating AUD cannot be overstated. Given the global burden and the high attributable factor of alcohol in a vast number of diseases, the need for additional interventions and the development of new medicines is considered a priority by the World Health Organization (WHO). As of today, AUD is severely under-treated with a treatment gap nearing 90%, strikingly higher than that for other psychiatric disorders. Patients often seek treatment late in the progress of the disease and even among those who seek treatment only a minority receive medication, mirroring the still-prevailing stigma of the disease, and a lack of access to effective treatments, as well as a reluctance to total abstinence. To increase adherence, treatment goals should focus not only on maintaining abstinence, but also on harm reduction and psychosocial functioning. A personalised approach to AUD treatment, with a holistic view, and tailored therapy has the potential to improve AUD treatment outcomes by targeting the heterogeneity in genetics and pathophysiology, as well as reason for, and reaction to drinking. Also, the psychiatric co-morbidity rates are high in AUD and dual diagnosis can worsen symptoms and influence treatment response and should be considered in the treatment strategies.

Warfarin-A natural anticoagulant: A review of research trends for precision medication.

BACKGROUND: Warfarin is a widely prescribed anticoagulant in the clinic. It has a more considerable individual variability, and many factors affect its variability. Mathematical models can quantify the quantitative impact of these factors on individual variability. PURPOSE: The aim is to comprehensively analyze the advanced warfarin dosing algorithm based on pharmacometrics and machine learning models of personalized warfarin dosage. METHODS: A bibliometric analysis of the literature retrieved from PubMed and Scopus was performed using VOSviewer. The relevant literature that reported the precise dosage of warfarin calculation was retrieved from the database. The multiple linear regression (MLR) algorithm was excluded because a recent systematic review that mainly reviewed this algorithm has been reported. The following terms of quantitative systems pharmacology, mechanistic model, physiologically based pharmacokinetic model, artificial intelligence, machine learning, pharmacokinetic, pharmacodynamic, pharmacokinetics, pharmacodynamics, and warfarin were added as MeSH Terms or appearing in Title/Abstract into query box of PubMed, then humans and English as filter were added to retrieve the literature. RESULTS: Bibliometric analysis revealed important co-occuring MeShH and index keywords. Further, the United States, China, and the United Kingdom were among the top countries contributing in this domain. Some studies have established personalized warfarin dosage models using pharmacometrics and machine learning-based algorithms. There were 54 related studies, including 14 pharmacometric models, 31 artificial intelligence models, and 9 model evaluations. Each model has its advantages and disadvantages. The pharmacometric model contains biological or pharmacological mechanisms in structure. The process of pharmacometric model development is very time- and labor-intensive. Machine learning is a purely data-driven approach; its parameters are more mathematical and have less biological interpretation. However, it is faster, more efficient, and less time-consuming. Most published models of machine learning algorithms were established based on cross-sectional data sourced from the database. CONCLUSION: Future research on personalized warfarin medication should focus on combining the advantages of machine learning and pharmacometrics algorithms to establish a more robust warfarin dosage algorithm. Randomized controlled trials should be performed to evaluate the established algorithm of warfarin dosage. Moreover, a more user-friendly and accessible warfarin precision medicine platform should be developed.

An Integrated Care Approach to Improve Well-Being in Breast Cancer Patients.

BACKGROUND: Breast cancer (BC) treatment has recently been revolutionized by the introduction of newer targeted agents, that helped tailoring therapies around the single patient. Along with increased survival rates, a careful evaluation of diet, lifestyle habits, physical activity, emotional and psychological experiences linked to the treatment journey, is now mandatory. However, a true proposal for an omnicomprehensive and "integrative" approach is still lacking in literature. METHODS: A scientific board of internationally recognized specialists throughout different disciplines designed a shared proposal of holistic approach for BC patients. RESULTS: A narrative review, containing information on BC treatment, endocrinological and diet aspects, physical activity, rehabilitation, integrative medicine, and digital narrative medicine, was developed. CONCLUSIONS: In the context of a patient-centered care, BC treatment cannot be separated from a patient's long-term follow-up and care, and an organized interdisciplinary collaboration is the future in this disease's cure, to make sure that our patients will live longer and better. TRIAL REGISTRATION: NCT05893368: New Model for Integrating Person-based Care (PbC) in the Treatment of Advanced HER2-negative Breast Cancer (PERGIQUAL). Registration date: 29th May 2023.

Effect of tumor heterogeneity on enhancing drug delivery to vascularized tumors using thermo-sensitive liposomes triggered by hyperthermia: A multi-scale and multi-physics computational model.

In this study, a novel multi-scale and multi-physics image-based computational model is introduced to assess the delivery of doxorubicin (Dox) loaded temperature-sensitive liposomes (TSLs) in the presence of hyperthermia. Unlike previous methodologies, this approach incorporates capillary network geometry extracted from images, resulting in a more realistic physiological tumor model. This model holds significant promise in advancing personalized medicine by integrating patient-specific tumor properties. The finite element method is employed to solve the equations governing intravascular and interstitial fluid flows, as well as the transport of therapeutic agents within the tissue. Realistic biological conditions and intricate processes like intravascular pressure, drug binding to cells, and cellular uptake are also considered to enhance the model's accuracy. The results underscore the significant impact of vascular architecture on treatment outcomes. Variation in vascular network pattern yielded changes of up to 38 % in the fraction of killed cells (FKCs) parameter under identical conditions. Pressure control of the parent vessels can also improve FKCs by approximately 17 %. Tailoring the treatment plan based on tumor-specific parameters emerged as a critical factor influencing treatment efficacy. For instance, changing the time interval between the administration of Dox-loaded TSLs and hyperthermia can result in a 48 % improvement in treatment outcomes. Additionally, devising a customized heating schedule led to a 20 % increase in treatment efficacy. Our proposed model highlights the significant effect of tumor characteristics and vascular network structure on the final treatment outcomes of the presented combination treatment.

An IoT-fuzzy intelligent approach for holistic management of COVID-19 patients.

In this study, an internet of things (IoT)-enabled fuzzy intelligent system is introduced for the remote monitoring, diagnosis, and prescription of treatment for patients with COVID-19. The main objective of the present study is to develop an integrated tool that combines IoT and fuzzy logic to provide timely healthcare and diagnosis within a smart framework. This system tracks patients' health by utilizing an Arduino microcontroller, a small and affordable computer that reads data from various sensors, to gather data. Once collected, the data are processed, analyzed, and transmitted to a web page for remote access via an IoT-compatible Wi-Fi module. In cases of emergencies, such as abnormal blood pressure, cardiac issues, glucose levels, or temperature, immediate action can be taken to monitor the health of critical COVID-19 patients in isolation. The system employs fuzzy logic to recommend medical treatments for patients. Sudden changes in these medical conditions are remotely reported through a web page to healthcare providers, relatives, or friends. This intelligent system assists healthcare professionals in making informed decisions based on the patient's condition.

Gastric cancer patient-derived organoids model for the therapeutic drug screening.

BACKGROUND: Gastric cancer (GC) is a highly heterogeneous disease featuring many various histological and molecular subtypes. Therefore, it is imperative to have well-characterized in vitro models for personalized treatment development. Gastric cancer patient-derived organoids (PDOs), re-capitulating in vivo conditions, exhibit high clinical efficacy in predicting drug sensitivity to facilitate the development of cancer precision medicine. METHODS: PDOs were established from surgically resected GC tumor tissues. Histological and molecular characterization of PDOs and primary tissues were performed via IHC and sequencing analysis. We also conducted drug sensitivity tests using PDO cultures with five chemotherapeutic drugs and twenty-two targeted drugs. RESULTS: We have successfully constructed a PDOs biobank that included EBV+, intestinal/CIN, diffuse/GS, mixed and Her2+ GC subtypes, and these PDOs captured the pathological and genetic characteristics of corresponding tumors and exhibited different sensitivities to the tested agents. In a clinical case study, we performed an additional drug sensitivity test for a patient who reached an advanced progressive stage after surgery. We discovered that the combination of napabucasin and COTI-2 exhibited a stronger synergistic effect than either drug alone. CONCLUSION: PDOs maintained the histological and genetic characteristics of original cancer tissues. PDOs biobank opens up new perspectives for studying cancer cell biology and personalized medicine as a preclinical study platform.

Drug-loaded vegan gummies for personalized dosing of simethicone: A feasibility study of semi-solid extrusion-based 3D printing of pectin-based low-calorie drug gummies.

Chewable gummies are an attractive dosage form for all age groups because of their appearance and texture. Although, this dosage form has been highly preferred administering nutraceuticals, its application in the pharmaceutical sector is worth exploring. In this study, simethicone (SMT), an OTC drug prescribed for anti-flatulence was incorporated in pectin- based, low-calorie, 3D printed gummies. Semi-solid extrusion (SSE)-based 3D printing was used to dispense personalized dose of SMT i.e 40 mg for children and 125 mg for adults. Formulation optimization was carried out based on the texture profile of the gummies, using a texture analyzer. The inks were thoroughly characterized for their rheological behavior since it is a critical attribute for SSE-based 3D printing. Printing parameters like the printing speed, layer height and the type of the nozzle were optimized based on the printing accuracy achieved. The printed gummies were further evaluated for their disintegration time, drug content, weight variation, water activity and total microbial count. SSE-based 3D printing was found to be an effective tool to print pectin-based shear thinning gels for accurate drug dispensing. The texture profile of the printed gummies was comparable to the gummies prepared by conventional method as well as the marketed samples.

Printing a cure: A tailored solution for localized drug delivery in liver cancer treatment.

Adjuvant chemotherapy is highly recommended for liver cancer to enhance survival rates due to its tendency to recur frequently. Localized drug-eluting implants have gained traction as an alternative to overcome the limitations of systemic chemotherapy. This work describes the development of biodegradable 3D printed (3DP) bilayer films loaded with 5-fluorouracil (5FU) and cisplatin (Cis) with different infill percentages where the 5FU layers were 40%, 30%, and 30% and Cis layers were 10%, 15%, and 10% for films A, B, and C, respectively. The relevant characterization tests were performed, and the drug content of films was 0.68, 0.50, and 0.50 mg of 5FU and 0.39, 0.80, and 0.34 mg of Cis for films A, B, and C, respectively. Cis release was affected by the alterations to the film design, where films A, B, and C showed complete release at 12, 14, and 23 days, respectively. However, 5FU was released over 24 h for all films. The films were stable for up to two weeks after storage at 25 °C/65% relative humidity and four weeks at 4 °C where drug content, tensile strength, FTIR, and thermal analysis results demonstrated negligible alterations. The cytotoxicity of the films was assessed by MTS assays using HepG2 cell lines demonstrating up to 81% reduction in cell viability compared to blank films. Moreover, apoptosis was confirmed by Western Blots and the determination of mitochondrial cell potential, highlighting the potential of these films as a promising approach in adjuvant chemotherapy.

Targosomes: Anti-HER2 PLGA nanocarriers for bioimaging, chemotherapy and local photothermal treatment of tumors and remote metastases.

Developing combined cancer therapy strategies is of utmost importance as it can enhance treatment efficacy, overcome drug resistance, and ultimately improve patient outcomes by targeting multiple pathways and mechanisms involved in cancer growth and progression. Specifically, the potential of developing a combination chemo&photothermal therapy using targeted polymer nanoparticles as nanocarriers offers a promising approach for synergistic cancer treatment by combining the benefits of both therapies, such as targeted drug delivery and localized hyperthermia. Here, we report the first targeted anti-HER2 PLGA nanocarriers, called targosomes, that simultaneously possess photothermal, chemotherapeutic and diagnostic properties using only molecular payloads. Biocompatible poly(lactic-co-glycolic acid), PLGA, nanoparticles were loaded with photosensitizer phthalocyanine, diagnostic dye Nile Blue, and chemotherapeutic drug irinotecan, which was chosen as a result of screening a panel of theragnostic nanoparticles. The targeted delivery to cell surface oncomarker HER2 was ensured by nanoparticle modification with the anti-HER2 monoclonal antibody, trastuzumab, using the one-pot synthesis method without chemical conjugation. The irradiation tests revealed prominent photothermal properties of nanoparticles, namely heating by 35 °C in 10 min. Nanoparticles exhibited a 7-fold increase in binding and nearly an 18-fold increase in cytotoxicity for HER2-overexpressing cells compared to cells lacking HER2 expression. This enhancement of cytotoxicity was further amplified by >20-fold under NIR light irradiation. In vivo studies proved the efficacy of nanoparticles for bioimaging of primary tumor and metastasis sites and demonstrated 93% tumor growth inhibition, making these nanoparticles excellent candidates for translation into theragnostic applications.

Classification of preeclampsia according to molecular clusters with the goal of achieving personalized prevention.

The prevention of pre-eclampsia is difficult due to the syndromic nature and multiple underlying mechanisms of this severe complication of pregnancy. The current clinical distinction between early- and late-onset disease, although clinically useful, does not reflect the true nature and complexity of the pathologic processes leading to pre-eclampsia. The current gaps in knowledge on the heterogeneous molecular pathways of this syndrome and the lack of adequate, specific diagnostic methods are major obstacles to early screening and tailored preventive strategies. The development of novel diagnostic tools for detecting the activation of the identified disease pathways would enable early, accurate screening and personalized preventive therapies. We implemented a holistic approach that includes the utilization of different proteomic profiling methods of maternal plasma samples collected from various ethnic populations and the application of systems biology analysis to plasma proteomic, maternal demographic, clinical characteristic, and placental histopathologic data. This approach enabled the identification of four molecular subclasses of pre-eclampsia in which distinct and shared disease mechanisms are activated. The current review summarizes the results and conclusions from these studies and the research and clinical implications of our findings.

Treatable traits and challenges in the clinical management of non-tuberculous mycobacteria lung disease in people with cystic fibrosis.

INTRODUCTION: Over the last ten years an increasing prevalence and incidence of non-tuberculous mycobacteria (NTM) has been reported among patients with cystic fibrosis (CF) Viviani (J Cyst Fibros, 15(5):619-623, 2016). NTM pulmonary disease has been associated with negative clinical outcomes and often requires pharmacological treatment. Although specific guidelines help clinicians in the process of diagnosis and clinical management, the focus on the multidimensional assessment of concomitant problems is still scarce. MAIN BODY: This review aims to identify the treatable traits of NTM pulmonary disease in people with CF and discuss the importance of a multidisciplinary approach in order to detect and manage all the clinical and behavioral aspects of the disease. The multidisciplinary complexity of NTM pulmonary disease in CF requires careful management of respiratory and extra-respiratory, including control of comorbidities, drug interactions and behavioral factors as adherence to therapies. CONCLUSIONS: The treatable trait strategy can help to optimize clinical management through systematic assessment of all the aspects of the disease, providing a holistic treatment for such a multi-systemic and complex condition.

The Evolving Landscape: Exploring the Future of Myelodysplastic Syndrome Treatment with Dr. Rami Komrokji.

This perspective delves into the evolving landscape of Myelodysplastic Syndrome (MDS) treatment. MDS presents a significant clinical challenge, often progressing to acute myeloid leukemia. For low-risk MDS, the emphasis is on personalized care through comprehensive risk assessment, clinical monitoring, and tailored interventions, including promising agents like erythropoiesis-stimulating agents, lenalidomide, and luspatercept, with the anticipation of an expanding therapeutic arsenal and early intervention for improved outcomes. In contrast, high-risk MDS treatment is evolving towards upfront doublet or triplet therapies with a focus on minimal residual disease (MRD) monitoring. A holistic approach integrates various modalities, including stem cell transplant and post-transplant maintenance, all guided by individual patient circumstances. Risk-adapted strategies are crucial for enhancing patient outcomes. Precision medicine for MDS treatment is budding, largely driven by Next Generation Sequencing (NGS). NGS aids in early diagnosis, prognostication, and the targeting of specific mutations, with molecular data increasingly informing treatment responses and allowing for tailored interventions. Clinical trials within homogeneous patient groups with similar molecular profiles are becoming more common, enhancing treatment precision. In conclusion, the future of MDS treatment is moving towards personalized medicine, leveraging advanced technologies like NGS and molecular insights to improve outcomes in the realm of hematological malignancies.

Variability in the Clinical Effects of the Omega-3 Polyunsaturated Fatty Acids DHA and EPA in Cardiovascular Disease-Possible Causes and Future Considerations.

Cardiovascular disease (CVD) that includes myocardial infarction and stroke, is the leading cause of mortality worldwide. Atherosclerosis, the primary underlying cause of CVD, can be controlled by pharmacological and dietary interventions, including n-3 polyunsaturated fatty acid (PUFA) supplementation. n-3 PUFA supplementation, primarily consisting of eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA), has shown promise in reducing atherosclerosis by modulating risk factors, including triglyceride levels and vascular inflammation. n-3 PUFAs act by replacing pro-inflammatory fatty acid types in cell membranes and plasma lipids, by regulating transcription factor activity, and by inducing epigenetic changes. EPA and DHA regulate cellular function through shared and differential molecular mechanisms. Large clinical studies on n-3 PUFAs have reported conflicting findings, causing confusion among the public and health professionals. In this review, we discuss important factors leading to these inconsistencies, in the context of atherosclerosis, including clinical study design and the differential effects of EPA and DHA on cell function. We propose steps to improve clinical and basic experimental study design in order to improve supplement composition optimization. Finally, we propose that understanding the factors underlying the poor response to n-3 PUFAs, and the development of molecular biomarkers for predicting response may help towards a more personalized treatment.

High residual cardiovascular risk after lipid-lowering: prime time for Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive medicine.

As time has come to translate trial results into individualized medical diagnosis and therapy, we analyzed how to minimize residual risk of cardiovascular disease (CVD) by reviewing papers on "residual cardiovascular disease risk". During this review process we found 989 papers that started off with residual CVD risk after initiating statin therapy, continued with papers on residual CVD risk after initiating therapy to increase high-density lipoprotein-cholesterol (HDL-C), followed by papers on residual CVD risk after initiating therapy to decrease triglyceride (TG) levels. Later on, papers dealing with elevated levels of lipoprotein remnants and lipoprotein(a) [Lp(a)] reported new risk factors of residual CVD risk. And as new risk factors are being discovered and new therapies are being tested, residual CVD risk will be reduced further. As we move from CVD risk reduction to improvement of patient management, a paradigm shift from a reductionistic approach towards a holistic approach is required. To that purpose, a personalized treatment dependent on the individual's CVD risk factors including lipid profile abnormalities should be configured, along the line of P5 medicine for each individual patient, i.e., with Predictive, Preventive, Personalized, Participatory, and Psycho-cognitive approaches.

Clinical Cases and the Molecular Profiling of a Novel Childhood Encephalopathy-Causing GNAO1 Mutation P170R.

De novo mutations in GNAO1, the gene encoding the major neuronal G protein Gαo, cause a spectrum of pediatric encephalopathies with seizures, motor dysfunction, and developmental delay. Of the >80 distinct missense pathogenic variants, many appear to uniformly destabilize the guanine nucleotide handling of the mutant protein, speeding up GTP uptake and deactivating GTP hydrolysis. Zinc supplementation emerges as a promising treatment option for this disease, as Zn2+ ions reactivate the GTP hydrolysis on the mutant Gαo and restore cellular interactions for some of the mutants studied earlier. The molecular etiology of GNAO1 encephalopathies needs further elucidation as a prerequisite for the development of efficient therapeutic approaches. In this work, we combine clinical and medical genetics analysis of a novel GNAO1 mutation with an in-depth molecular dissection of the resultant protein variant. We identify two unrelated patients from Norway and France with a previously unknown mutation in GNAO1, c.509C>G that results in the production of the Pro170Arg mutant Gαo, leading to severe developmental and epileptic encephalopathy. Molecular investigations of Pro170Arg identify this mutant as a unique representative of the pathogenic variants. Its 100-fold-accelerated GTP uptake is not accompanied by a loss in GTP hydrolysis; Zn2+ ions induce a previously unseen effect on the mutant, forcing it to lose the bound GTP. Our work combining clinical and molecular analyses discovers a novel, biochemically distinct pathogenic missense variant of GNAO1 laying the ground for personalized treatment development.

Modeling and Remodeling the Cell: How Digital Twins and HCMV Can Elucidate the Complex Interactions of Viral Latency, Epigenetic Regulation, and Immune Responses.

Purpose of Review: Human cytomegalovirus (HCMV), while asymptomatic in most, causes significant complications during fetal development, following transplant or in immunosuppressed individuals. The host-virus interactions regulating viral latency and reactivation and viral control of the cellular environment (immune regulation, differentiation, epigenetics) are highly complex. Understanding these processes is essential to controlling infection and can be leveraged as a novel approach for understanding basic cell biology. Recent Findings: Immune digital twins (IDTs) are digital simulations integrating knowledge of human immunology, physiology, and patient-specific clinical data to predict individualized immune responses and targeted treatments. Recent studies used IDTs to elucidate mechanisms of T cells, dendritic cells, and epigenetic control-all key to HCMV biology. Summary: Here, we discuss how leveraging the unique biology of HCMV and IDTs will clarify immune response dynamics, host-virus interactions, and viral latency and reactivation and serve as a powerful IDT-validation platform for individualized and holistic health management.

New Community and Sociohealth Challenges Arising from the Early Diagnosis of Mild Cognitive Impairment (MCI).

Population aging increases the risk of developing neurodegenerative diseases that cause cognitive impairment. Advances in clinical practice and greater social awareness of the importance of cognitive impairment have led to an increase in the number of people with early diagnosis, predementia. Increasing access to biomarkers to assess whether Alzheimer's disease (AD) is the underlying cause of mild cognitive impairment (MCI) has undoubted clinical benefits (access to potentially disease-modifying treatments, among others) but is also responsible for new social-health care challenges. Understanding the psychosocial impact of a diagnosis of MCI due to AD or another neurodegenerative disease is essential to create future strategies to reduce the emotional overload of patients, their risk of discrimination and stigmatization, and to favor their social inclusion. We present a narrative review of the diagnostic process of mild cognitive impairment in clinical practice, with a holistic person-centered approach, and discuss the implications of such diagnosis (benefits and risks) and strategies on how to address them.

A Protocol for Organoids from the Urine of Bladder Cancer Patients.

This study investigates the feasibility of establishing urine-derived tumor organoids from bladder cancer (BC) patients as an alternative to tissue-derived organoids. BC is one of the most common cancers worldwide and current diagnostic methods involve invasive procedures. Here, we investigated the potential of using urine samples, which contain exfoliated tumor cells, to generate urine-derived BC organoids (uBCOs). Urine samples from 29 BC patients were collected and cells were isolated and cultured in a three-dimensional matrix. The establishment and primary expansion of uBCOs were successful in 83% of the specimens investigated. The culturing efficiency of uBCOs was comparable to cancer tissue-derived organoids. Immunohistochemistry and immunofluorescence to characterize the uBCOs exhibited similar expressions of BC markers compared to the parental tumor. These findings suggest that urine-derived BC organoids hold promise as a non-invasive tool for studying BC and evaluating therapeutic responses. This approach could potentially minimize the need for invasive procedures and provide a platform for personalized drug screening. Further research in this area may lead to improved diagnostic and treatment strategies for BC patients.