Search Results (128)

Oral squamous cell carcinoma (OSCC) is one of the most prevalent types of cancer in the oral cavity and head and neck region. Due to its location and psychological and social implications, early detection and treatment are very important. A liquid biopsy can be used to diagnose cancer by analyzing samples of bodily fluids, such as saliva, blood, or urine, for specific molecules released by tumor cells. The objective of this study was to evaluate the use of liquid biopsy in the diagnosis of oral squamous cell carcinoma. A systematic review was carried out, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines (PROSPERO: CRD420251238037). Articles taken into consideration for the review were published before 30 September 2025. The search for manuscripts for the review was conducted using PubMed, Scopus, Google Scholar, and Cochrane databases. Forty-three articles were deemed eligible for inclusion in the systematic review. Key data extracted from the studies included authorship, publication date, study location, methodology, number of participants, and reported complications. Most of the analyzed biomarkers showed promising potential for future use in liquid biopsy for OSCC diagnosis. Tumor DNA and miRNA demonstrated the highest diagnostic accuracy. The standard approach to diagnosis and planning treatment relies on tumor biopsy and diagnostic imaging. Liquid biopsy may complement this process by enabling early detection in high-risk populations and monitoring response to therapy. As such, it serves as a prognostic factor or therapeutic target, successfully identifying disease recurrence. Full article

Background/Objectives: Active surveillance (AS) has become the standard of care for many men with localised prostate cancer, aiming to avoid the overtreatment of indolent disease while maintaining oncological safety. Despite improvements in diagnostic techniques, misclassification at diagnosis and the limited ability to predict disease progression remain major challenges in AS. Novel molecular and genetic biomarkers, assessed through liquid biopsy approaches, offer the potential to refine patient selection and support risk-adapted monitoring in AS. Methods: We conducted a narrative review of biomarkers in the context of AS for prostate cancer, framing the discussion in terms of the challenges in AS and how biomarkers may address these. PubMed and Embase were searched for English-language peer-reviewed studies published between 2000 and 2025. International guidelines (AUA, EAU, NCCN, NICE) and reference lists were reviewed manually. Priority was given to large prospective cohorts, meta-analyses, and high-impact publications. Results: Blood-based assays such as PHI and the 4K score, urinary tests including ExoDx and SelectMDx, and the Prostate Urine Risk (PUR) signatures have all shown associations with disease progression or decisions to undergo earlier treatment. However, studies are often small, use surrogate endpoints, and lack validation in MRI-integrated cohorts. Biomarkers appear most informative in men with Gleason Grade 1 (GG1) disease, while evidence in GG2 cohorts is limited. Cost-effectiveness, heterogeneity of endpoints, and uncertainty in managing discordant biomarker and MRI results remain barriers to clinical adoption. Conclusions: Molecular and genetic biomarkers show promise for improving AS by reducing diagnostic misclassification and enhancing prediction of progression. Future research should define clinically relevant cut-offs, clarify integration with MRI, and evaluate longitudinal use. Demonstrating utility in contemporary cohorts could enable the development of biomarker-guided, personalised AS that maintains safety while minimising harm. Full article

Prostate cancer (PCa) is a common malignancy in men worldwide, with incidence projected to rise in the coming years. Traditional screening and diagnostic methods, such as prostate-specific antigen (PSA) testing and biopsy, face limitations in specificity and invasiveness. Circulating microRNAs (miRNAs) have emerged as stable, non-invasive biomarkers obtainable via liquid biopsies (blood, urine, semen) that could transform PCa management. These small regulatory RNAs reflect underlying tumor biology and are detectable at early disease stages, enabling improved early detection when used alongside or in place of PSA. Distinct miRNA expression patterns correlate with tumor aggressiveness. For example, miR-141 and miR-375 are elevated in metastatic cases, whereas let-7 family members and miR-326 are upregulated in aggressive disease, highlighting their prognostic value. Moreover, dynamic changes in reported miRNAs during therapy provide real-time insights into treatment response. In androgen-deprivation therapy (ADT), oncogenic miRNAs, such as miR-21 and miR-125b, increase upon resistance, whereas a decline in tumor-suppressive miRNAs, such as miR-23b/-27b, flags the transition to castration-resistant PCa (CRPC). Similarly, baseline levels of miRNAs (e.g., miR-200b/c, miR-20a) can predict chemotherapy outcomes. Integrating multi-miRNA panels has demonstrated superior accuracy for risk stratification and monitoring, paving the way for personalized treatment. Although promising, clinical implementation of miRNA-based assays requires further validation, standardization of protocols, and large-scale prospective studies. Harnessing circulating miRNAs could usher in a new era of precision oncology for PCa, improving early diagnosis, prognostication, and real-time therapeutic guidance. Full article

Background: Urothelial bladder carcinoma (UBC) is a disease that lacks robust non-invasive laboratory biomarkers. Recently, urine liquid biopsy has emerged as a promising tool for diagnosis and surveillance of patients with these tumors. The aim of this study was to evaluate the diagnostic potential of a urinary tumor DNA detection panel, which included eight common point mutations in TERT, GPR126, FGFR3, and PIK3CA genes, in UBC. Methods: The study included patients with histologically confirmed UBC (n = 88) and patients with cystitis, bladder leiomyomas, or other non-malignant conditions (control group; n = 72). DNA was extracted from whole urine specimens. ddPCR analysis was performed using the Bio-Rad QX200 AutoDG ddPCR system. Results: Urinary tumor DNA detection panel demonstrated a sensitivity of 78.4% and a specificity of 100% (AUC−ROC = 0.892). Detection rates for the analyzed mutations were the following: 54.5%, 37.5%, 28.4%, and 38.6% for TERT, GPR126, FGFR3, and PIK3CA, respectively. Pairwise comparisons of mutant allele fractions (MAFs) for samples simultaneously positive for ≥2 mutations revealed an absence of significant differences (p > 0.05), except for the pair of FGFR3 vs. PIK3CA (p = 0.03). MAFs were not associated with any clinical and demographic features (p > 0.05), with the only exception being the tumor size: patients with tumors larger than 2.16 cm³ had higher MAFs than the rest (23.4 [1.8; 46.3] vs. 1.6 [0; 24.6] %, respectively, p = 0.02). Conclusions: Upon further validation, the presented tumor DNA detection panel for ddPCR might become a useful tool for diagnostic purposes in UBC. Full article

Background/Objectives: Differential scanning calorimetry (DSC) analysis of blood plasma, also known as thermal liquid biopsy (TLB), is a promising approach for disease detection and monitoring; however, its wider adoption in clinical settings has been hindered by labor-intensive data processing workflows, particularly baseline correction. Methods: We developed and tested two automated algorithms to address critical bottlenecks in TLB analysis: (1) a baseline-correction algorithm utilizing rolling-variance analysis for endpoint detection, and (2) a signal-detection algorithm that applies auto-regressive integrated moving average (ARIMA)-based stationarity testing to determine whether a profile contains interpretable thermal features. Both algorithms are implemented in ThermogramForge, an open-source R Shiny web application providing an end-to-end workflow for data upload, processing, and report generation. Results: The baseline-correction algorithm demonstrated excellent performance on plasma TLB data (characterized by high heat capacity), matching the quality of rigorous manual processing. However, its performance was less robust for low signal biofluids, such as urine, where weak thermal transitions reduce the reliability of baseline estimation. To address this, a complementary signal-detection algorithm was developed to screen for TLB profiles with discernable thermal transitions prior to baseline correction, enabling users to exclude non-informative data. The signal-detection algorithm achieved near-perfect classification accuracy for TLB profiles with well-defined thermal transitions and maintained a low false-positive rate of 3.1% for true noise profiles, with expected lower performance for borderline cases. The interactive review interface in ThermogramForge further supports quality control and expert refinement. Conclusions: The automated baseline-correction and signal-detection algorithms, together with their web-based implementation, substantially reduce analysis time while maintaining quality, supporting more efficient and reproducible TLB research. Full article

Background/Objectives: Urothelial carcinoma of the bladder (UCC) is a leading cause of cancer-related death globally. Given that urine is in direct contact with the tumor, it represents a highly valuable source for non-invasive molecular analysis. Methods: This study utilized liquid biopsies from 41 UCC patients and 27 non-cancerous hematuria controls to identify novel diagnostic and prognostic biomarkers via proteomic and transcriptomic analysis. Results: Urine proved to be a reliable source, yielding a mean tumor cell fraction of 0.605 (95% CI: 0.505–0.705). We identified 11 genes with concurrent alteration at both the urinary protein and mRNA levels. Notably, four upregulated markers, CYTB, C1QC, SBP1, and ANXA4, demonstrated strong diagnostic potential, with AUC values greater than 0.70. CYTB and ANXA4 were detectable even in early-stage UCC (stages Cis, I, and II). Furthermore, we identified two proteins, CATC and SPB10, that were markedly upregulated in recurrent UCC and correlated with poor overall survival, positioning them as potential prognostic markers for recurrence risk. Conclusions: This study confirms the utility of urine as a reliable medium for detecting UCC tumor cells, offering promising markers for both early-stage diagnosis and predicting NMIBC recurrence. Full article

The detection of soluble proteins in biological fluids, as a form of liquid biopsy, is a promising tool for cancer diagnosis and prognosis, as it is less invasive than traditional diagnostic methods. CD44 is one of the most recognized markers of cancer stem cells, a small subset of cells responsible for cancer initiation, progression, and metastasis. Given the importance of CD44 as a cancer biomarker, several review articles explore the diagnostic and therapeutic value of cell-surface CD44. In addition to being a membrane-anchored protein, CD44 is also shed from the cell surface and can be found in various biological fluids. However, the role of soluble CD44 in cancer has not been comprehensively discussed in recent reviews. Measuring soluble CD44 in various biological liquids can provide a practical and valuable tool for cancer diagnosis and treatment monitoring. Therefore, this review comprehensively discusses the role of soluble CD44 as a marker in various cancer types, including serum, saliva, urine, and other fluids. In particular, its role as an early cancer biomarker and as a predictive and prognostic biomarker in several cancers is discussed. This work also provides an overview of a wide range of analytical techniques used to detect soluble CD44. The value of cells expressing CD44 versus soluble CD44 as a biomarker is also compared. The review concludes with a perspective on future directions, emphasizing the shift toward non-invasive analytical methods and the need for standardization of detection, including multiple biomarkers during evaluation, to improve the accuracy of cancer diagnosis. Full article

Prostate cancer is one of the most common cancers affecting men, and finding better ways to detect and monitor it remains a top priority in oncology. In recent years, scientists have focused their attention on different classes of extracellular bodies, among them the small ones called exosomes. Exosomes are nanoscale extracellular vesicles (30–200 nm) released into body fluids, where they transport molecular cargo reflective of their cell of origin. Instead of serving as liquid biopsies themselves, exosomes present in accessible fluids such as plasma and urine can be analyzed as part of minimally invasive liquid biopsy strategies without the need for surgery or tissue sampling. In prostate cancer, exosomes are not just passive carriers: they actively influence how cancer grows, spreads, and responds to treatment. Exosomes can be extracted from simple fluid samples, opening the door to faster, safer, and more personalised approaches to diagnosis and care. Exosome content is analysed for the molecular profiling of tumours, including genomics, transcriptomics, proteomics, and metabolomics. This has led to the discovery of new biomarkers that may help detect prostate cancer earlier, predict its aggressiveness, and monitor the effectiveness of treatment. This review synthesizes current multi-omics data on exosomal cargo in prostate cancer, highlighting diagnostic, prognostic, and therapeutic implications as well as existing challenges to clinical translation. Full article

Prostate cancer (PC) remains a major cause of cancer deaths in men. The serum biomarker prostate-specific antigen (PSA) lacks specificity in distinguishing clinically significant PC (sPC) from insignificant PC (isPC), leading to overdiagnosis and overtreatment. Although magnetic resonance imaging (MRI) improves detection, it is expensive, is time-consuming, and may involve inter-reader discrepancies. Recently, metabolomics, which has a high analytical sensitivity and broad molecular-feature coverage, has emerged as a promising tool to risk-stratify PC. This review examined studies of blood and urine metabolomics for sPC biomarker identification. Significant metabolite changes in sPC patients often involved fatty acid metabolism, sphingolipid metabolism, glycolysis, the citric acid cycle, purine/pyrimidine metabolism, and tyrosine/phenylalanine metabolism. Specifically, more than one study reported increased lactate and phenylalanine levels, along with decreased tyrosine, xanthine, and histidine levels, in sPC patients. Several metabolic panels outperformed serum PSA in predicting sPC, particularly when combined with clinical factors. Among these, two urine-based tests may have higher accuracy in predicting sPC than most current commercially available assays. However, direct comparison between studies may be inappropriate due to methodological heterogeneity, the variability in biospecimen types, inconsistent use of digital rectal examinations, and different sPC definitions and predictive endpoints. Most relevant studies were of small sample size or lacked external validation. Despite these challenges, metabolomics-based liquid biopsies show strong potential for improving sPC detection. Future research should focus on protocol standardization, MRI integration, absolute metabolite quantification, and validation in large and independent cohorts to enhance model credibility. Full article

Background: Adenomyosis remains difficult to diagnose non-invasively due to clinical overlap with endometriosis and the limited specificity of imaging techniques. This pilot study evaluated whether serum- and urine-derived microRNA (miRNA) profiles, combined with machine-learning approaches, could support non-invasive diagnosis. Methods: Serum and urine samples were collected from 59 patients undergoing surgery for chronic pelvic pain at the Endometriosis Centre of RWTH Aachen University Hospital. Seven patients had isolated adenomyosis, 34 had histologically confirmed endometriosis, and 18 served as negative controls. miRNAs were profiled using next-generation sequencing. A structured feature-selection pipeline (variance filtering, univariate testing, mutual information, recursive feature elimination) was applied before training Logistic Regression, Random Forest, Support Vector Machine, and Decision Tree models using cross-validation. Model performance was evaluated using accuracy, precision, recall, F1 score, and ROC-AUC. Results: Distinct miRNA signatures were detected in both serum and urine, with urine-based models showing superior discriminatory performance. Logistic Regression and Support Vector Machine achieved excellent separation in urine datasets, although perfect AUC values must be interpreted cautiously due to the small number of adenomyosis cases. In serum, Random Forest achieved the highest AUC values (up to 0.98). Several miRNAs, including miR-183-3p, miR-320d-2, and miR-17, emerged as promising candidate biomarkers for differentiating adenomyosis from endometriosis and from negative controls. Conclusions: This pilot study demonstrates the feasibility of liquid-biopsy miRNA profiling combined with machine learning for non-invasive adenomyosis detection. Although results are preliminary and require validation in larger cohorts, urine miRNA profiles may represent a promising complementary tool to improve diagnostic accuracy and reduce diagnostic delay. Full article

Prostate cancer is one of the most common malignancies in men worldwide. Therefore, there is an urgent need to develop accurate, accessible biomarkers for diagnosis, prognosis, and therapy monitoring. Tumor markers, which can be measured in blood, urine, or tissue, provide valuable information regarding tumor presence, progression, and response to treatment. This review provides a comprehensive overview of routinely used diagnostic and emerging biomarkers for prostate cancer, based on a systematic MEDLINE/PubMed search. Key biomarkers analyzed include PSA and its derivatives, PCA3, and TMPRSS2-ERG, as well as genomic tests such as Prolaris, Decipher, and ConfirmMDx, and liquid biopsy-based tests such as ExoDx Prostate and SelectMDx. This narrative review demonstrates that although PSA remains the mainstay of prostate cancer diagnosis, emerging molecular and genomic biomarkers are enhancing diagnostic specificity, refining risk stratification, and enabling more personalized patient care. The integration of routinely used and novel biomarkers can improve early detection, optimize treatment decisions, and ultimately improve outcomes of prostate cancer patients. Full article

Cancer diagnosis requires alternative techniques that allow for early, non-invasive, or minimally invasive identification. Traditional methods, like tissue biopsies, are highly invasive and can be traumatic for patients. Liquid biopsy, a less invasive option, detects cancer biomarkers in body fluids such as blood and urine. However, early-stage cancer often presents low biomarker levels, making sensitivity a challenge for integrating liquid biopsy into early diagnosis. Recent studies revealed that extracellular vesicles (EVs) secreted by cells are apt markers for liquid biopsy. Detecting extracellular vesicles (EVs) for liquid biopsy faces challenges like low sensitivity, EV subtype heterogeneity, and difficulty isolating pure populations. Label-free methods, such as plasmonic biosensors and Raman spectroscopy, offer potential solutions by enabling direct analysis without markers, improving accuracy, and reducing complexity. This review paper discusses current challenges in EV-based liquid biopsy for cancer diagnosis and prognosis. It addresses the effective use of microfluidics and nano-plasmonic approaches to address these challenges. Enhancing label-free EV detection in liquid biopsy could revolutionize early cancer diagnosis by offering non-invasive, cost-effective, and rapid testing. This could improve patient outcomes through personalized treatment and ease the burden on healthcare systems. Full article

Background: Breast cancer remains a leading cause of cancer-related deaths despite advances in its diagnosis and treatment. Accurate evaluation of the response to neoadjuvant chemotherapy (NAC), especially in HER2-positive and triple-negative subtypes, is critical. The current methods, including imaging and liquid biopsies, have limitations. N-NOSE, a novel urine-based cancer screening test using Caenorhabditis elegans (C. elegans) chemotaxis, offers a non-invasive alternative. This study investigates the potential of N-NOSE to predict the NAC response in breast cancer patients for improved treatment evaluations. Materials and Methods: This prospective study enrolled 36 breast cancer patients undergoing NAC and surgery to assess the predictive power of the N-NOSE method using urine samples. A chemotaxis analysis of C. elegans was used to calculate the index reduction scores (IRS1–3), reflecting the changes in tumor-related odorants across the treatment stages. Results: Between August 2020 and May 2023, 36 breast cancer patients were enrolled to evaluate the predictive value of N-NOSE IRSs for NAC response. A pathological complete response (pCR) was achieved in 36.1% of the patients. Among the three IRS types analyzed in the 35 patients, IRS3, which showed the IRS at pre-treatment minus that after surgery, showed the highest predictive performance for a pCR, with an AUC of 0.75, indicating its potential utility as a non-invasive biomarker for treatment response evaluations. Conclusions: Index reduction scores evaluated using the N-NOSE method may reflect the efficacy of NAC in breast cancer patients. Future large-scale and multi-institutional prospective studies are warranted. Full article

Exosomes are 30–150 nm extracellular vesicles that play crucial roles in intercellular communication and hold significant potential as biomarkers for non-invasive liquid biopsy. However, the current isolation methods have limitations including being time-consuming, producing low yields, and having high costs. This study presents a novel automated exosome isolation method using EGCG-modified magnetic beads (EGCG@T) optimized for diverse biofluids including plasma, serum, urine, and saliva. We systematically investigated the optimal EGCG:T-Fe₃O₄ ratio (0.1:1), binding time, elution parameters, and extraction buffer composition for each biofluid type. The developed protocol was successfully integrated into an automated workflow using the Nextractor^® NX-Junior platform, combining exosome isolation and protein extraction into a single step. Western blot and ELISA analyses confirmed that the EGCG@T method yielded a significantly higher recovery of exosomal markers (CD9, CD63, CD81, TSG101, and ALIX) compared to conventional PEG precipitation, with the efficiency varying depending on the biofluid. Notably, CD63-positive exosomes were isolated with approximately two-fold higher efficiency from urine and 1.3-fold higher efficiency from saliva using the EGCG@T method. Our findings demonstrated that biofluid-specific optimization is essential for effective exosome isolation, as exosome subpopulations exhibited distinct physicochemical properties across different sample types. This automated, rapid, and efficient exosome isolation method provides a valuable platform for future clinical applications in non-invasive disease diagnosis and monitoring through liquid biopsy. Full article

Renal cell carcinoma (RCC) presents a significant diagnostic challenge, particularly in small renal masses. The search for non-invasive screening methods and biomarkers has directed research toward liquid biopsy, which focuses on microRNAs (miRNAs), exosomes, and circulating tumor cells (CTCs). miRNAs are small non-coding RNA molecules that show considerable dysregulation in RCC, and they have potential for both diagnostic and prognostic applications. Research has highlighted their utility on biofluids, such as plasma, serum, and urine, in detecting RCC and characterizing its subtypes. Promising miRNA signatures have been associated with overall survival, suggesting their potential importance in the management of RCC. Exosomes, which carry a variety of molecular components, including miRNAs, are emerging as valuable biomarkers, whereas CTCs, released from primary tumors into the bloodstream, provide critical information on cancer progression. However, translation of these findings into clinical practice requires additional validation and standardization through large-scale studies and robust evidence. Although there are currently no approved diagnostic tests for RCC, the future potential of liquid biopsy in monitoring, treatment decision-making, and outcome prediction in patients with this disease is significant. This review examined and discussed recent developments in liquid biopsy for RCC, assessing both the strengths and limitations of these approaches for managing this disease. Full article