A stable, highly concentrated fluorous nanoemulsion formulation for in vivo cancer imaging via 19F-MRI.

Magnetic resonance imaging (MRI) is a routine diagnostic modality in oncology that produces excellent imaging resolution and tumor contrast without the use of ionizing radiation. However, improved contrast agents are still needed to further increase detection sensitivity and avoid toxicity/allergic reactions associated with paramagnetic metal contrast agents, which may be seen in a small percentage of the human population. Fluorine-19 (19F)-MRI is at the forefront of the developing MRI methodologies due to near-zero background signal, high natural abundance of 100%, and unambiguous signal specificity. In this study, we have developed a colloidal nanoemulsion (NE) formulation that can encapsulate high volumes of the fluorous MRI tracer, perfluoro-[15-crown-5]-ether (PFCE) (35% v/v). These nanoparticles exhibit long-term (at least 100 days) stability and high PFCE loading capacity in formulation with our semifluorinated triblock copolymer, M2F8H18. With sizes of approximately 200 nm, these NEs enable in vivo delivery and passive targeting to tumors. Our diagnostic formulation, M2F8H18/PFCE NE, yielded in vivo 19F-MR images with a high signal-to-noise ratio up to 100 in a tumor-bearing mouse model at clinically relevant scan times. M2F8H18/PFCE NE circulated stably in the vasculature, accumulated in high concentration of an estimated 4-9 × 1017 19F spins/voxel at the tumor site, and cleared from most organs over the span of 2 weeks. Uptake by the mononuclear phagocyte system to the liver and spleen was also observed, most likely due to particle size. These promising results suggest that M2F8H18/PFCE NE is a favorable 19F-MR diagnostic tracer for further development in oncological studies and potential clinical translation.

Anticancer Metallocenes and Metal Complexes of Transition Elements from Groups 4 to 7.

With the progression in the field of bioinorganic chemistry, the role of transition metal complexes as the most widely used therapeutics is becoming a more and more attractive research area. The complexes of transition metals possess a great variety of attractive pharmacological properties, including anticancer, anti-inflammatory, antioxidant, anti-infective, etc., activities. Transition metal complexes have proven to be potential alternatives to biologically active organic compounds, especially as antitumor agents. The performance of metal coordination compounds in living systems is anticipated to differ generally from the action of non-metal-containing drugs and may offer unique diagnostic and/or therapeutic opportunities. In this review, the rapid development and application of metallocenes and metal complexes of elements from Groups 4 to 7 in cancer diagnostics and therapy have been summarized. Most of the heavy metals discussed in the current review are newly discovered metals. That is why the use of their metal-based compounds has attracted a lot of attention concerning their organometallic and coordination chemistry. All of this imposes more systematic studies on their biological activity, biocompatibility, and toxicity and presupposes further investigations.

miRNA Expression Profiling in Human Breast Cancer Diagnostics and Therapy.

Breast cancer is one of the most commonly diagnosed cancer types worldwide. Regarding molecular characteristics and classification, it is a heterogeneous disease, which makes it more challenging to diagnose. As is commonly known, early detection plays a pivotal role in decreasing mortality and providing a better prognosis for all patients. Different treatment strategies can be adjusted based on tumor progression and molecular characteristics, including personalized therapies. However, dealing with resistance to drugs and recurrence is a challenge. The therapeutic options are limited and can still lead to poor clinical outcomes. This review aims to shed light on the current perspective on the role of miRNAs in breast cancer diagnostics, characteristics, and prognosis. We discuss the potential role of selected non-coding RNAs most commonly associated with breast cancer. These include miR-21, miR-106a, miR-155, miR-141, let-7c, miR-335, miR-126, miR-199a, miR-101, and miR-9, which are perceived as potential biomarkers in breast cancer prognosis, diagnostics, and treatment response monitoring. As miRNAs differ in expression levels in different types of cancer, they may provide novel cancer therapy strategies. However, some limitations regarding dynamic alterations, tissue-specific profiles, and detection methods must also be raised.

Current Challenges of Methylation-Based Liquid Biopsies in Cancer Diagnostics.

In current clinical practice, effective cancer testing and screening paradigms are limited to specific types of cancer, exhibiting varying efficiency, acceptance, and adherence. Cell-free DNA (cfDNA) methylation profiling holds promise in providing information about the presence of malignity regardless of its type and location while leveraging blood-based liquid biopsies as a method to obtain analytical samples. However, technical difficulties, costs and challenges resulting from biological variations, tumor heterogeneity, and exogenous factors persist. This method exploits the mechanisms behind cfDNA release but faces issues like fragmentation, low concentrations, and high background noise. This review explores cfDNA methylation's origins, means of detection, and profiling for cancer diagnostics. The critical evaluation of currently available multi-cancer early detection methods (MCEDs) as well as tests targeting single genes, emphasizing their potential and limits to refine strategies for early cancer detection, are explained. The current methodology limitations, workflows, comparisons of clinically approved liquid biopsy-based methylation tests for cancer, their utilization in companion diagnostics as well as the biological limitations of the epigenetics approach are discussed, aiming to help healthcare providers as well as researchers to orient themselves in this increasingly complex and evolving field of diagnostics.

Review of the application of the most current sophisticated image processing methods for the skin cancer diagnostics purposes.

This paper presents the most current and innovative solutions applying modern digital image processing methods for the purpose of skin cancer diagnostics. Skin cancer is one of the most common types of cancers. It is said that in the USA only, one in five people will develop skin cancer and this trend is constantly increasing. Implementation of new, non-invasive methods plays a crucial role in both identification and prevention of skin cancer occurrence. Early diagnosis and treatment are needed in order to decrease the number of deaths due to this disease. This paper also contains some information regarding the most common skin cancer types, mortality and epidemiological data for Poland, Europe, Canada and the USA. It also covers the most efficient and modern image recognition methods based on the artificial intelligence applied currently for diagnostics purposes. In this work, both professional, sophisticated as well as inexpensive solutions were presented. This paper is a review paper and covers the period of 2017 and 2022 when it comes to solutions and statistics. The authors decided to focus on the latest data, mostly due to the rapid technology development and increased number of new methods, which positively affects diagnosis and prognosis.

Rational Design of NIR-II Emitting Conjugated Polymer Derived Nanoparticles for Image-Guided Cancer Interventions.

Due to the reduced absorption, light scattering, and tissue autofluorescence in the NIR-II (1000-1700 nm) region, significant efforts are underway to explore diverse material platforms for in vivo fluorescence imaging, particularly for cancer diagnostics and image-guided interventions. Of the reported imaging agents, nanoparticles derived from conjugated polymers (CPNs) offer unique advantages to alternative materials including biocompatibility, remarkable absorption cross-sections, exceptional photostability, and tunable emission behavior independent of cell labeling functionalities. Herein, the current state of NIR-II emitting CPNs are summarized and structure-function-property relationships are highlighted that can be used to elevate the performance of next-generation CPNs. Methods for particle processing and incorporating cancer targeting modalities are discussed, as well as detailed characterization methods to improve interlaboratory comparisons of novel materials. Contemporary methods to specifically apply CPNs for cancer diagnostics and therapies are then highlighted. This review not only summarizes the current state of the field, but offers future directions and provides clarity to the advantages of CPNs over other classes of imaging agents.

Exploring the State of Cancer Imaging Research in Africa.

INTRODUCTION: The growing cancer burden in Africa demands urgent action. Medical imaging is crucial for cancer diagnosis and management and is an essential enabler of precision medicine. To understand the readiness for quantitative imaging analysis to support cancer management in Africa, we analyzed the utilization patterns of imaging modalities for cancer research across the continent. METHODS: We retrieved articles by systematically searching PubMed, using a combination of search terms {"Neoplasm"} AND {"Radiology" or "Diagnostic imaging" or "Radiography" or "Interventional Radiology" or "Radiotherapy" or "Radiation Oncology"} AND {Africa∗ or 54 African countries}. Articles describing cancer diagnosis or management in humans with the utilization of imaging were included. Exclusion criteria were review articles, non-English articles, publications before 2000, noncancer diagnoses, and studies conducted outside Africa. RESULTS: The analysis of diagnostic imaging in Africa revealed a diverse utilization pattern across different cancer types and regions. The literature search identified 107 publications on cancer imaging in Africa. The studies were carried out in 19 African countries on 12 different cancer types with 6 imaging modalities identified. Most cancer imaging research studies used multiple imaging modalities. Ultrasound was the most used distinct imaging modality and MRI was the least frequently used. Most research studies originated from Nigeria, South Africa, and Egypt. CONCLUSION: We demonstrate substantial variability in the presence of imaging modalities, widespread utilization of ultrasonography, and limited availability of advanced imaging modalities for cancer research.

Nanotechnological advances in cancer: therapy a comprehensive review of carbon nanotube applications.

Nanotechnology is revolutionising different areas from manufacturing to therapeutics in the health field. Carbon nanotubes (CNTs), a promising drug candidate in nanomedicine, have attracted attention due to their excellent and unique mechanical, electronic, and physicochemical properties. This emerging nanomaterial has attracted a wide range of scientific interest in the last decade. Carbon nanotubes have many potential applications in cancer therapy, such as imaging, drug delivery, and combination therapy. Carbon nanotubes can be used as carriers for drug delivery systems by carrying anticancer drugs and enabling targeted release to improve therapeutic efficacy and reduce adverse effects on healthy tissues. In addition, carbon nanotubes can be combined with other therapeutic approaches, such as photothermal and photodynamic therapies, to work synergistically to destroy cancer cells. Carbon nanotubes have great potential as promising nanomaterials in the field of nanomedicine, offering new opportunities and properties for future cancer treatments. In this paper, the main focus is on the application of carbon nanotubes in cancer diagnostics, targeted therapies, and toxicity evaluation of carbon nanotubes at the biological level to ensure the safety and real-life and clinical applications of carbon nanotubes.

Routine molecular applications and recent advances in breast cancer diagnostics.

Cancer stands as one of the most common and lethal diseases, imposing a substantial burden on global mortality rates. Breast cancer is distinct from other forms of cancer in which it is the primary cause of death for women. Early detection of breast cancer can significantly lower the risk of mortality, improving the prognosis for those who are affected. The death rate of breast cancer has been steadily rising, according to epidemiological data, especially since the COVID-19 pandemic. This emphasizes the necessity of sensitive and precise technologies that can be utilized in early breast cancer diagnosis. In this process, biomarkers play a pivotal role by facilitating the early detection and diagnosis of breast cancer. Currently, a wide variety of cancer biomarkers have been identified, improving the accuracy of cancer diagnosis. These biomarkers can be applied in liquid biopsies as well as on solid tissues. In the context of breast cancer, biomarkers are particularly valuable for determining who is predisposed to the disease, predicting prognosis at the time of diagnosis, and selecting the best course of therapy. This review comprehensively explores the recently developed gene-based biomarkers from biofluids that are used in the context of breast cancer, as well as the conventional and cutting-edge techniques that have been employed for breast cancer diagnosis.

Three musketeers of PDA-based MRI contrasting and therapy.

Polydopamine (PDA) stands as a versatile material explored in cancer nanomedicine for its unique properties, offering opportunities for multifunctional drug delivery platforms. This study explores the potential of utilizing a one-pot synthesis to concurrently integrate Fe, Gd and Mn ions into porous PDA-based theranostic drug delivery platforms called Ferritis, Gadolinis and Manganis, respectively. Our investigation spans the morphology, magnetic properties, photothermal characteristics and cytotoxicity profiles of those potent nanoformulations. The obtained structures showcase a spherical morphology, robust magnetic response and promising photothermal behaviour. All of the presented nanoparticles (NPs) display pronounced paramagnetism, revealing contrasting potential for MRI imaging. Relaxivity values, a key determinant of contrast efficacy, demonstrated competitive or superior performance compared to established, used contrasting agents. These nanoformulations also exhibited robust photothermal properties under near infra-red irradiation, showcasing their possible application for photothermal therapy of cancer. Our findings provide insights into the potential of metal-doped PDA NPs for cancer theranostics.

Recent Advances in Fluorescent Probes for G-quadruplex DNAs / RNAs.

Guanine-quadruplexes (G4s) are high-level structures formed by the folding of guaninerich nucleic acid sequences. G4s play important roles in various physiological processes, such as gene transcription, replication, recombination, and maintenance of chromosomal stability. Specific and sensitive monitoring of G4s lays the foundation for further understanding the structure, content, distribution, and function of G4s in organisms, which is important for the treatment and diagnosis of diseases. Moreover, visualization of G4s will provide new ideas for developing antitumor strategies targeting G4s. The design and development of G4-specific ligands are challenging due to the subtle differences in the structure of G4s. This review focuses on the progress of research on G4 fluorescent probes and their binding mechanisms to G4s. Finally, the challenges and future prospects for better detection and targeting of G4s in different organisms are discussed. This paper provides ideas for the development of novel G4 fluorescent probes.

Sensitive electrochemical biosensor for rapid detection of sEV-miRNA based turbo-like localized catalytic hairpin assembly.

Small extracellular vesicle-associated microRNAs (sEV-miRNAs) have emerged as critical biomarkers for cancer diagnosis, yet the rapid detection of these low-abundance molecules in clinical samples remains a formidable challenge. Herein, a simple turbo-like localized catalytic hairpin assembly (TL-CHA) was proposed for sEV-miR-1246 measurement. This electrochemical sensor achieves dual localization through the ingeniously use of AuNPs and DNA nanowires, which provides rich sites for CHA cascade amplification, significantly enhancing the effective reaction and amplify the detection response. Leveraging this innovative design, this biosensor demonstrated the ability to detect sEV-miRNA at concentrations as low as 5.24 aM in a time frame of 30 min. The precision of the measurements was validated through reverse transcription quantitative polymerase chain reaction. Furthermore, the sensor was used for analyzing plasma samples from gastric cancer patients yielded AUC values of 0.973 for all stages and 0.945 for early stages. This demonstrates the sensor's robust performance in both the staging diagnosis and early screening of gastric cancer. Therefore, this platform has great potential for the clinical cancer diagnosis.

Multiplexed Opto-Microfluidic Biosensing: Advanced Platform for Prostate Cancer Detection.

Cancer stands as a prominent global cause of mortality, necessitating early detection to augment survival rates and alleviate economic burdens on healthcare systems. In particular, prostate cancer (PCa), impacting 1.41 million men globally in 2020, accentuates the demand for sensitive and cost-effective detection methods beyond traditional prostate-specific antigen (PSA) testing. While clinical techniques exhibit limitations, biosensors emerge as compact, user-friendly alternatives to traditional laboratory approaches. However, existing biosensors predominantly concentrate on PSA detection, prompting the necessity for advancing toward multiplex sensing platforms. This study introduces a compact opto-microfluidic sensor featuring a substrate of gold nanospikes, fabricated via electrodeposition, for enhanced sensitivity. Embedded within a microfluidic chip, this nanomaterial enables the precise and concurrent measurement of PSA, alongside two complementary PCa biomarkers, matrix metalloproteinase-2 (MMP-2) and anti-α-methylacyl-CoA racemase (anti-AMACR) in diluted human plasma, offering a comprehensive approach to PSA analysis. Taking advantage of the localized surface plasmon resonance principle, this biosensor offers robustness and sensitivity in real sample analysis without the need for labeling agents. With the limit of detection at 0.22, 0.37, and 0.18 ng/mL for PSA, MMP-2, and anti-AMACR, respectively, this biosensing platform holds promise for point-of-care analysis, underscoring its potential impact on medical diagnostics.

Association of microRNA-21 expression with breast cancer subtypes and its potential as an early biomarker.

Breast cancer has become the most diagnosed cancer worldwide in 2020 with high morbidity and mortality rates. The alarming increase in breast cancer incidence has sprung many researchers to focus on developing novel screening tests to identify early breast cancer which will allow clinicians to provide timely and effective treatments. With much evidence supporting the notion that the deregulation of miRNAs (a class of non-coding RNA) greatly contributes to cancer initiation and progression, the promising role of miRNAs as cancer biomarkers is gaining traction in the research world. Among the upregulated miRNAs identified in breast carcinogenesis, miR-21 was shown to be significantly expressed in breast cancer tissues and bodily fluids of breast cancer patients. Therein, this review paper aims to provide an overview of breast cancer, the role and significance of miR-21 in breast cancer pathogenesis, and its potential as a breast cancer biomarker. The paper also discusses the current types of tumor biomarkers and their limitations, the presence of miR-21 in extracellular vesicles and plasma, screening methods available for miRNA detection along with some challenges faced in developing diagnostic miR-21 testing for breast cancer to provide readers with a comprehensive outlook based on using miR-21 in clinical settings.

Assessing the complementary information from an increased number of biologically relevant features in liquid biopsy-derived RNA-Seq data.

Liquid biopsy-derived RNA sequencing (lbRNA-seq) exhibits significant promise for clinic-oriented cancer diagnostics due to its non-invasiveness and ease of repeatability. Despite substantial advancements, obstacles like technical artefacts and process standardisation impede seamless clinical integration. Alongside addressing technical aspects such as normalising fluctuating low-input material and establishing a standardised clinical workflow, the lack of result validation using independent datasets remains a critical factor contributing to the often low reproducibility of liquid biopsy-detected biomarkers. Considering the outlined drawbacks, our objective was to establish a workflow/methodology characterised by: 1. Harness the rich diversity of biological features accessible through lbRNA-seq data, encompassing a holistic range of molecular and functional attributes. These components are seamlessly integrated via a Machine Learning-based Ensemble Classification framework, enabling a unified and comprehensive analysis of the intricate information encoded within the data. 2. Implementing and rigorously benchmarking intra-sample normalisation methods to heighten their relevance within clinical settings. 3. Thoroughly assessing its efficacy across independent test sets to ascertain its robustness and potential utility. Using ten datasets from several studies comprising three different sources of biological material, we first show that while the best-performing normalisation methods depend strongly on the dataset and coupled Machine Learning method, the rather simple Counts Per Million method is generally very robust, showing comparable performance to cross-sample methods. Subsequently, we demonstrate that the innovative biofeature types introduced in this study, such as the Fraction of Canonical Transcript, harbour complementary information. Consequently, their inclusion consistently enhances prediction power compared to models relying solely on gene expression-based biofeatures. Finally, we demonstrate that the workflow is robust on completely independent datasets, generally from different labs and/or different protocols. Taken together, the workflow presented here outperforms generally employed methods in prediction accuracy and may hold potential for clinical diagnostics application due to its specific design.

Cost Analysis of Prostate Cancer Care Using a Biomarker-enhanced Diagnostic Strategy with Stockholm3.

Background and objective: Building on previous research demonstrating better prostate cancer (PC) diagnostics via a biomarker-enhanced approach, this study focuses on cost analysis of PC care using the Stockholm3 test. We assessed the economic impact in European health care systems using real-world evidence for diagnostic outcomes and relevant costs. Methods: We evaluated two PC diagnostic strategies: (1) the conventional prostate-specific antigen (PSA) strategy with magnetic resonance imaging (MRI) and (2) PSA testing with a reflex to biomarkers at PSA ≥1.5 ng/ml in guiding decisions to perform MRI. Data from the Swedish National Prostate Cancer Register and Capio St. Göran Hospital provided real-world evidence, supplemented by health economic modeling. A comprehensive cost analysis was conducted using a Markov model for treatment pathways for four PC disease states and overall spending, for which costs from various European health care systems were used. A deterministic sensitivity analysis was performed across different cost and diagnostic scenarios. Key finding and limitations: The average cost for the four disease states was €2 182 for benign disease, €10 023 for low-grade disease, €13 073 for intermediate- to high-grade localized or locally advance disease, and €271 210 for metastatic disease. The overall spending was €358 239 (7.7%) lower per 1000 men tested in the biomarker-enhanced strategy in comparison to the PSA strategy. The primary cost saving was attributed to lower treatment expenses for metastatic disease. Sensitivity analysis affirmed the robustness of the findings across various diagnostic and treatment scenarios. Conclusions and clinical implications: Biomarker-enhanced diagnostic strategies may reduce health care costs for PC management and are likely to improve quality-adjusted life years in a scenario in which metastatic disease is reduced. Patient summary: We explored different ways to detect prostate cancer more cost-effectively. We found that using a specific blood test, called Stockholm3, after a PSA (prostate-specific antigen) test to decide if an MRI scan (magnetic resonance imaging) is necessary could save money, mainly by identifying localized cancer earlier and reducing the need for expensive treatments for advanced cancer.

Canine Cancer Diagnostics by X-ray Diffraction of Claws.

We report the results of X-ray diffraction (XRD) measurements of the dogs' claws and show the feasibility of using this approach for early, non-invasive cancer detection. The obtained two-dimensional XRD patterns can be described by Fourier coefficients, which were calculated for the radial and circular (angular) directions. We analyzed these coefficients using the supervised learning algorithm, which implies optimization of the random forest classifier by using samples from the training group and following the calculation of mean cancer probability per patient for the blind dataset. The proposed algorithm achieved a balanced accuracy of 85% and ROC-AUC of 0.91 for a blind group of 68 dogs. The transition from samples to patients additionally improved the ROC-AUC by 10%. The best specificity and sensitivity values for 68 patients were 97.4% and 72.4%, respectively. We also found that the structural parameter (biomarker) most important for the diagnostics is the intermolecular distance.

Epigenetic changes associated with Bacillus Calmette-Guerin (BCG) treatment in bladder cancer.

Bacillus Calmette-Guérin (BCG) treatment for non-muscle invasive bladder cancer (NMIBC) is an established immunotherapeutic, however, a significant portion of patients do not respond to treatment. Despite extensive research into the therapeutic mechanism of BCG, gaps remain in our understanding. This review specifically focuses on the epigenomic contributions in the immune microenvironment, in the context of BCG treatment for NMIBC. We also summarise the current understanding of NMIBC epigenetic characteristics, and discuss how future targeted strategies for BCG therapy should incorporate epigenomic biomarkers in conjunction with genomic biomarkers.

An advanced 3D DNA nanoplatform for spatiotemporally confined enhanced dual-mode biosensing MicroRNA in cancer cell.

Dual-mode signal output platforms have demonstrated considerable promise due to their improved anti-interference capability and inherent signal self-correction. Nevertheless, traditional discrete-distributed signal probes often encounter significant drawbacks, including limited mass transfer efficiency, diminished signal strength, and instability in intricate biochemical environments. In response to these challenges, a scalable and hyper-compacted 3D DNA nanoplatform resembling "periodic focusing heliostat" has been developed for synergistically enhanced fluorescence (FL) and surface-enhanced Raman spectroscopy (SERS) biosensing of miRNA in cancer cells. Our approach utilized a distinctive assembly strategy integrating gold nanostars (GNS) as fundamental "heliostat units" linked by palindromic DNA sequences to facilitate each other hand-in-hand cascade alignment and condensed into large scale nanostructures. This configuration was further augmented by the incorporation of gold nanoparticles (GNP) via strong Au-S bonds, resulting in a sturdy framework for improved signal transduction. The initiation of this assembly process was mediated by the hybridization of dsDNA to miRNA-21, which served as a primer for polymerization and nicking reactions, thus generating a multifunctional T2 probe. This probe is intricately designed with three distinct parts: a 3'-palindromic end for structural integrity, a central region for capturing SERS-active probes (Cy3-P2), and a 5'-segment for attaching fluorescence reporters. Upon integration T2 into the GNS-based heliostat unit, it promotes palindromic arm-induced aggregation and plasma exciton coupling between plasma nanoparticles and signal transduction tags. This clustered arrangement creates a high-density "hot spot" array that maximizes the local electromagnetic fields necessary for enhanced SERS and FL response. This superstructure supports enhanced aggregation-induced signal amplification for both SERS and FL, offering exceptional sensitivity with LOD as low as 0.0306 pM and 0.409 pM. The efficacy of this method was demonstrated in the evaluation of miRNA-21 in various cancer cell lines.

Identification of novel snoRNA-based biomarkers for clear cell renal cell carcinoma from urine-derived extracellular vesicles.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC with high rates of metastasis. Targeted therapies such as tyrosine kinase and checkpoint inhibitors have improved treatment success, but therapy-related side effects and tumor recurrence remain a challenge. As a result, ccRCC still have a high mortality rate. Early detection before metastasis has great potential to improve outcomes, but no suitable biomarker specific for ccRCC is available so far. Therefore, molecular biomarkers derived from body fluids have been investigated over the past decade. Among them, RNAs from urine-derived extracellular vesicles (EVs) are very promising. METHODS: RNA was extracted from urine-derived EVs from a cohort of 78 subjects (54 ccRCC patients, 24 urolithiasis controls). RNA-seq was performed on the discovery cohort, a subset of the whole cohort (47 ccRCC, 16 urolithiasis). Reads were then mapped to the genome, and expression was quantified based on 100 nt long contiguous genomic regions. Cluster analysis and differential region expression analysis were performed with adjustment for age and gender. The candidate biomarkers were validated by qPCR in the entire cohort. Receiver operating characteristic, area under the curve and odds ratios were used to evaluate the diagnostic potential of the models. RESULTS: An initial cluster analysis of RNA-seq expression data showed separation by the subjects' gender, but not by tumor status. Therefore, the following analyses were done, adjusting for gender and age. The regions differentially expressed between ccRCC and urolithiasis patients mainly overlapped with small nucleolar RNAs (snoRNAs). The differential expression of four snoRNAs (SNORD99, SNORD22, SNORD26, SNORA50C) was validated by quantitative PCR. Confounder-adjusted regression models were then used to classify the validation cohort into ccRCC and tumor-free subjects. Corresponding accuracies ranged from 0.654 to 0.744. Models combining multiple genes and the risk factors obesity and hypertension showed improved diagnostic performance with an accuracy of up to 0.811 for SNORD99 and SNORA50C (p = 0.0091). CONCLUSIONS: Our study uncovered four previously unrecognized snoRNA biomarkers from urine-derived EVs, advancing the search for a robust, easy-to-use ccRCC screening method.