Liquid biopsy for gastric cancer: Techniques, applications, and future directions.

After the study of circulating tumor cells in blood through liquid biopsy (LB), this technique has evolved to encompass the analysis of multiple materials originating from the tumor, such as nucleic acids, extracellular vesicles, tumor-educated platelets, and other metabolites. Additionally, research has extended to include the examination of samples other than blood or plasma, such as saliva, gastric juice, urine, or stool. LB techniques are diverse, intricate, and variable. They must be highly sensitive, and pre-analytical, patient, and tumor-related factors significantly influence the detection threshold, diagnostic method selection, and potential results. Consequently, the implementation of LB in clinical practice still faces several challenges. The potential applications of LB range from early cancer detection to guiding targeted therapy or immunotherapy in both early and advanced cancer cases, monitoring treatment response, early identification of relapses, or assessing patient risk. On the other hand, gastric cancer (GC) is a disease often diagnosed at advanced stages. Despite recent advances in molecular understanding, the currently available treatment options have not substantially improved the prognosis for many of these patients. The application of LB in GC could be highly valuable as a non-invasive method for early diagnosis and for enhancing the management and outcomes of these patients. In this comprehensive review, from a pathologist's perspective, we provide an overview of the main options available in LB, delve into the fundamental principles of the most studied techniques, explore the potential utility of LB application in the context of GC, and address the obstacles that need to be overcome in the future to make this innovative technique a game-changer in cancer diagnosis and treatment within clinical practice.

tRNA-derived small RNAs in human cancers: roles, mechanisms, and clinical application.

Transfer RNA (tRNA)-derived small RNAs (tsRNAs) are a new type of non-coding RNAs (ncRNAs) produced by the specific cleavage of precursor or mature tRNAs. tsRNAs are involved in various basic biological processes such as epigenetic, transcriptional, post-transcriptional, and translation regulation, thereby affecting the occurrence and development of various human diseases, including cancers. Recent studies have shown that tsRNAs play an important role in tumorigenesis by regulating biological behaviors such as malignant proliferation, invasion and metastasis, angiogenesis, immune response, tumor resistance, and tumor metabolism reprogramming. These may be new potential targets for tumor treatment. Furthermore, tsRNAs can exist abundantly and stably in various bodily fluids (e.g., blood, serum, and urine) in the form of free or encapsulated extracellular vesicles, thereby affecting intercellular communication in the tumor microenvironment (TME). Meanwhile, their abnormal expression is closely related to the clinicopathological features of tumor patients, such as tumor staging, lymph node metastasis, and poor prognosis of tumor patients; thus, tsRNAs can be served as a novel type of liquid biopsy biomarker. This review summarizes the discovery, production, and expression of tsRNAs and analyzes their molecular mechanisms in tumor development and potential applications in tumor therapy, which may provide new strategies for early diagnosis and targeted therapy of tumors.

Prognostic Value of Liquid-Biopsy-Based Biomarkers in Upper Tract Urothelial Carcinoma.

Currently, there are no reliable prognostic factors to determine which upper tract urothelial carcinoma (UTUC) patients will progress after radical nephroureterectomy (RNU). We aim to evaluate whether liquid-biopsy-based biomarkers (circulating tumor cells (CTCs), cell-free DNA (cfDNA), and circulating tumor DNA (ctDNA)) were able to predict clinical outcomes in localized UTUC patients undergoing RNU. Twenty patients were prospectively enrolled between 2021 and 2023. Two blood samples were collected before RNU and three months later. CTCs and cfDNA were isolated and evaluated using the IsoFlux system and Quant-iT PicoGreen dsDNA kit, respectively. Droplet digital PCR was performed to determine ctDNA status. Cox regression analysis was performed on CTCs, cfDNA, and ctDNA at two different follow-up time points to examine their influence on tumor progression and cancer-specific survival (CSS). During a median follow-up of 18 months, seven (35%) patients progressed and three (15%) died. Multivariate analysis demonstrated that cfDNA levels three months after RNU are a significant predictor of tumor progression (HR = 1.085; p = 0.006) and CSS (HR = 1.168; p = 0.029). No associations were found between CTC enumeration and ctDNA status with any of the clinical outcomes evaluated. The evaluation of cfDNA levels in clinical practice could improve the disease management of UTUC patients.

Unlocking Precision Medicine: Liquid Biopsy Advancements in Renal Cancer Detection and Monitoring.

Renal cell carcinoma (RCC) remains a formidable diagnostic challenge, especially in the context of small renal masses. The quest for non-invasive screening tools and biomarkers has steered research towards liquid biopsy, focusing on microRNAs (miRNAs), exosomes, and circulating tumor cells (CTCs). MiRNAs, small non-coding RNAs, exhibit notable dysregulation in RCC, offering promising avenues for diagnosis and prognosis. Studies underscore their potential across various biofluids, including plasma, serum, and urine, for RCC detection and subtype characterization. Encouraging miRNA signatures show correlations with overall survival, indicative of their future relevance in RCC management. Exosomes, with their diverse molecular cargo, including miRNAs, emerge as enticing biomarkers, while CTCs, emanating from primary tumors into the bloodstream, provide valuable insights into cancer progression. Despite these advancements, clinical translation necessitates further validation and standardization, encompassing larger-scale studies and robust evidence generation. Currently lacking approved diagnostic assays for renal cancer, the potential future applications of liquid biopsy in follow-up care, treatment selection, and outcome prediction in RCC patients are profound. This review aims to discuss and highlight recent advancements in liquid biopsy for RCC, exploring their strengths and weaknesses in the comprehensive management of this disease.

Plasma extracellular vesicles in meningioma patients following radiotherapy as liquid biopsy- a prospective explorative biomarker study (ARO 2023-05/AG-NRO-07).

BACKGROUND: While surgical resection remains the primary treatment approach for symptomatic or growing meningiomas, radiotherapy represents an auspicious alternative in patients with meningiomas not safely amenable to surgery. Biopsies are often omitted in light of potential postoperative neurological deficits, resulting in a lack of histological grading and (molecular) risk stratification. In this prospective explorative biomarker study, extracellular vesicles in the bloodstream will be investigated in patients with macroscopic meningiomas to identify a biomarker for molecular risk stratification and disease monitoring. METHODS: In total, 60 patients with meningiomas and an indication of radiotherapy (RT) and macroscopic tumor on the planning MRI will be enrolled. Blood samples will be obtained before the start, during, and after radiotherapy, as well as during clinical follow-up every 6 months. Extracellular vesicles will be isolated from the blood samples, quantified and correlated with the clinical treatment response or progression. Further, nanopore sequencing-based DNA methylation profiles of plasma EV-DNA will be generated for methylation-based meningioma classification. DISCUSSION: This study will explore the dynamic of plasma EVs in meningioma patients under/after radiotherapy, with the objective of identifying potential biomarkers of (early) tumor progression. DNA methylation profiling of plasma EVs in meningioma patients may enable molecular risk stratification, facilitating a molecularly-guided target volume delineation and adjusted dose prescription during RT treatment planning.

Nanobiotechnology augmented cancer stem cell guided management of cancer: liquid-biopsy, imaging, and treatment.

Cancer stem cells (CSCs) represent both a key driving force and therapeutic target of tumoral carcinogenesis, tumor evolution, progression, and recurrence. CSC-guided tumor diagnosis, treatment, and surveillance are strategically significant in improving cancer patients' overall survival. Due to the heterogeneity and plasticity of CSCs, high sensitivity, specificity, and outstanding targeting are demanded for CSC detection and targeting. Nanobiotechnologies, including biosensors, nano-probes, contrast enhancers, and drug delivery systems, share identical features required. Implementing these techniques may facilitate the overall performance of CSC detection and targeting. In this review, we focus on some of the most recent advances in how nanobiotechnologies leverage the characteristics of CSC to optimize cancer diagnosis and treatment in liquid biopsy, clinical imaging, and CSC-guided nano-treatment. Specifically, how nanobiotechnologies leverage the attributes of CSC to maximize the detection of circulating tumor DNA, circulating tumor cells, and exosomes, to improve positron emission computed tomography and magnetic resonance imaging, and to enhance the therapeutic effects of cytotoxic therapy, photodynamic therapy, immunotherapy therapy, and radioimmunotherapy are reviewed.

MIR145 Core Promoter Methylation in Pretreatment Cell-Free DNA: A Liquid Biopsy Tool for Muscle-Invasive Bladder Cancer Treatment Outcome.

PURPOSE: The lack of personalized management of bladder cancer (BlCa) results in patients' lifelong post-treatment monitoring with invasive interventions, underlying the urgent need for tailored and minimally invasive health care services. On the basis of our previous findings on miR-143/145 cluster methylation in bladder tumors, we evaluated its clinical significance in pretreatment cell-free DNA (cfDNA) of patients with BlCa. MATERIALS AND METHODS: Methylation analysis was performed in our screening cohort (120 patients with BlCa; 20 age-matched healthy donors) by bisulfite-based pyrosequencing. Tumor recurrence/progression for patients with non-muscle-invasive bladder cancer, and progression and mortality for patients with muscle-invasive bladder cancer (MIBC) were used as clinical end point events in survival analysis. Bootstrap analysis was applied for internal validation of Cox regression models and decision curve analysis for assessment of clinical benefit on disease prognosis. RESULTS: Decreased methylation of MIR145 core promoter in pretreatment cfDNA was associated with short-term disease progression (multivariate Cox: hazard ratio [HR], 2.027 [95% CI, 1.157 to 3.551]; P = .010) and poor overall survival (multivariate Cox: HR, 2.098 [95% CI, 1.154 to 3.817]; P = .009) of patients with MIBC after radical cystectomy (RC). Multivariate models incorporating MIR145 promoter methylation in cfDNA with tumor stage clearly ameliorated patients' risk stratification, highlighting superior clinical benefit in MIBC prognostication. CONCLUSION: Reduced pretreatment cfDNA methylation of MIR145 core promoter was markedly correlated with increased risk for short-term progression and worse survival of patients with MIBC after RC and adjuvant therapy, supporting modern personalized and minimally invasive prognosis. Methylation profiling of MIR145 core promoter in pretreatment cfDNA could serve as a minimally invasive and independent predictor of MIBC treatment outcome and emerge as a promising marker for blood-based test in BlCa.

Pushing the Boundaries of Liquid Biopsies for Early Precision Intervention.

Liquid biopsies are emerging as powerful minimally invasive approaches that have the potential to solve several long-standing problems spanning the continuum of cancer care: early detection of cancer, minimal residual disease tracking, and refinement of the heterogeneity of clinical responses together with therapeutic response monitoring in the metastatic setting. Existing challenges driven by technical limitations and establishment of the clinical value of liquid biopsies represent fields of active research that call for convergence science approaches to bridge scientific discovery with clinical care.

Cancer-derived exosomes as novel biomarkers in metastatic gastrointestinal cancer.

Gastrointestinal cancer (GIC) is the most prevalent and highly metastatic malignant tumor and has a significant impact on mortality rates. Nevertheless, the swift advancement of contemporary technology has not seamlessly aligned with the evolution of detection methodologies, resulting in a deficit of innovative and efficient clinical assays for GIC. Given that exosomes are preferentially released by a myriad of cellular entities, predominantly originating from neoplastic cells, this confers exosomes with a composition enriched in cancer-specific constituents. Furthermore, exosomes exhibit ubiquitous presence across diverse biological fluids, endowing them with the inherent advantages of non-invasiveness, real-time monitoring, and tumor specificity. The unparalleled advantages inherent in exosomes render them as an ideal liquid biopsy biomarker for early diagnosis, prognosticating the potential development of GIC metastasis.In this review, we summarized the latest research progress and possible potential targets on cancer-derived exosomes (CDEs) in GIC with an emphasis on the mechanisms of exosome promoting cancer metastasis, highlighting the potential roles of CDEs as the biomarker and treatment in metastatic GIC.

Liquid biopsy techniques and lung cancer: diagnosis, monitoring and evaluation.

Lung cancer stands as the most prevalent form of cancer globally, posing a significant threat to human well-being. Due to the lack of effective and accurate early diagnostic methods, many patients are diagnosed with advanced lung cancer. Although surgical resection is still a potential means of eradicating lung cancer, patients with advanced lung cancer usually miss the best chance for surgical treatment, and even after surgical resection patients may still experience tumor recurrence. Additionally, chemotherapy, the mainstay of treatment for patients with advanced lung cancer, has the potential to be chemo-resistant, resulting in poor clinical outcomes. The emergence of liquid biopsies has garnered considerable attention owing to their noninvasive nature and the ability for continuous sampling. Technological advancements have propelled circulating tumor cells (CTCs), circulating tumor DNA (ctDNA), extracellular vesicles (EVs), tumor metabolites, tumor-educated platelets (TEPs), and tumor-associated antigens (TAA) to the forefront as key liquid biopsy biomarkers, demonstrating intriguing and encouraging results for early diagnosis and prognostic evaluation of lung cancer. This review provides an overview of molecular biomarkers and assays utilized in liquid biopsies for lung cancer, encompassing CTCs, ctDNA, non-coding RNA (ncRNA), EVs, tumor metabolites, TAAs and TEPs. Furthermore, we expound on the practical applications of liquid biopsies, including early diagnosis, treatment response monitoring, prognostic evaluation, and recurrence monitoring in the context of lung cancer.

A cfDNA methylation-based tissue-of-origin classifier for cancers of unknown primary.

Cancers of Unknown Primary (CUP) remains a diagnostic and therapeutic challenge due to biological heterogeneity and poor responses to standard chemotherapy. Predicting tissue-of-origin (TOO) molecularly could help refine this diagnosis, with tissue acquisition barriers mitigated via liquid biopsies. However, TOO liquid biopsies are unexplored in CUP cohorts. Here we describe CUPiD, a machine learning classifier for accurate TOO predictions across 29 tumour classes using circulating cell-free DNA (cfDNA) methylation patterns. We tested CUPiD on 143 cfDNA samples from patients with 13 cancer types alongside 27 non-cancer controls, with overall sensitivity of 84.6% and TOO accuracy of 96.8%. In an additional cohort of 41 patients with CUP CUPiD predictions were made in 32/41 (78.0%) cases, with 88.5% of the predictions clinically consistent with a subsequent or suspected primary tumour diagnosis, when available (23/26 patients). Combining CUPiD with cfDNA mutation data demonstrated potential diagnosis re-classification and/or treatment change in this hard-to-treat cancer group.

Emerging role of exosomes as a liquid biopsy tool for diagnosis, prognosis & monitoring treatment response of communicable & non-communicable diseases.

ABSTRACT: From an initial thought of being used as a cellular garbage bin to a promising target for liquid biopsies, the role of exosomes has drastically evolved in just a few years of their discovery in 1983. Exosomes are naturally secreted nano-sized vesicles, abundant in all types of body fluids and can be isolated intact even from the stored biological samples. Being stable carriers of genetic material (cellular DNA, mRNA and miRNA) and having specific cargo (signature content of originating cells), exosomes play a crucial role in pathogenesis and have been identified as a novel source of biomarkers in a variety of disease conditions. Recently exosomes have emerged as a promising 'liquid biopsy tool'and have shown great potential in the field of non-invasive disease diagnostics, prognostics and treatment response monitoring in both communicable as well as non-communicable diseases. However, there are certain limitations to overcome which restrict the use of exosome-based liquid biopsy as a gold standard testing procedure in routine clinical practices. The present review summarizes the current knowledge on the role of exosomes as the liquid biopsy tool in diagnosis, prognosis and treatment response monitoring in communicable and non-communicable diseases and highlights the major limitations, technical advancements and future prospects of the utilization of exosome-based liquid biopsy in clinical interventions.

A comprehensive guide to extract information from extracellular vesicles: a tutorial review towards novel analytical developments.

In the medical field, extracellular vesicles (EVs) are gaining importance as they act as cells mediators. These are phospholipid bilayer vesicles and contain crucial biochemical information about their mother cells being carrier of different biomolecules such as small molecules, proteins, lipids, and nucleic acids. After release into the extracellular matrix, they enter the systemic circulation and can be found in all human biofluids. Since EVs reflect the state of the cell of origin, there is exponential attention as potential source of new circulating biomarkers for liquid biopsy. The use of EVs in clinical practice faces several challenges that need to be addressed: these include the standardization of lysis protocols, the availability of low-cost reagents and the development of analytical tools capable of detecting biomarkers. The process of lysis is a crucial step that can impact all subsequent analyses, towards the development of novel analytical strategies. To aid researchers to support the evolution of measurement science technology, this tutorial review evaluates and discuss the most commonly protocols used to characterize the contents of EVs, including their advantages and disadvantages in terms of experimental procedures, time and equipment. The purpose of this tutorial review is to offer practical guide to researchers which are intended to develop novel analytical approaches. Some of the most significant applications are considered, highlighting their main characteristics divided per mechanism of action. Finally, comprehensive tables which provide an overview at a glance are provided to readers.

Cerebrospinal Fluid Liquid Biopsies in the Evaluation of Adult Gliomas.

PURPOSE OF REVIEW: This review aims to discuss recent research regarding the biomolecules explored in liquid biopsies and their potential clinical uses for adult-type diffuse gliomas. RECENT FINDINGS: Evaluation of tumor biomolecules via cerebrospinal fluid (CSF) is an emerging technology in neuro-oncology. Studies to date have already identified various circulating tumor DNA, extracellular vesicle, micro-messenger RNA and protein biomarkers of interest. These biomarkers show potential to assist in multiple avenues of central nervous system (CNS) tumor evaluation, including tumor differentiation and diagnosis, treatment selection, response assessment, detection of tumor progression, and prognosis. In addition, CSF liquid biopsies have the potential to better characterize tumor heterogeneity compared to conventional tissue collection and CNS imaging. Current imaging modalities are not sufficient to establish a definitive glioma diagnosis and repeated tissue sampling via conventional biopsy is risky, therefore, there is a great need to improve non-invasive and minimally invasive sampling methods. CSF liquid biopsies represent a promising, minimally invasive adjunct to current approaches which can provide diagnostic and prognostic information as well as aid in response assessment.

Benchmarking digital PCR partition classification methods with empirical and simulated duplex data.

Digital PCR (dPCR) is a highly accurate technique for the quantification of target nucleic acid(s). It has shown great potential in clinical applications, like tumor liquid biopsy and validation of biomarkers. Accurate classification of partitions based on end-point fluorescence intensities is crucial to avoid biased estimators of the concentration of the target molecules. We have evaluated many clustering methods, from general-purpose methods to specific methods for dPCR and flowcytometry, on both simulated and real-life data. Clustering method performance was evaluated by simulating various scenarios. Based on our extensive comparison of clustering methods, we describe the limits of these methods, and formulate guidelines for choosing an appropriate method. In addition, we have developed a novel method for simulating realistic dPCR data. The method is based on a mixture distribution of a Poisson point process and a skew-$t$ distribution, which enables the generation of irregularities of cluster shapes and randomness of partitions between clusters ('rain') as commonly observed in dPCR data. Users can fine-tune the model parameters and generate labeled datasets, using their own data as a template. Besides, the database of experimental dPCR data augmented with the labeled simulated data can serve as training and testing data for new clustering methods. The simulation method is available as an R Shiny app.

A Quest for Survival: A Review of the Early Biomarkers of Pancreatic Cancer and the Most Effective Approaches at Present.

Pancreatic cancer (PC) is the most lethal type of cancer; it has the lowest 5-year survival rate among all other types of cancers. More than half of PC cases are diagnosed at an advanced stage due to PC's insidious and non-specific symptoms. Surgery remains the most efficacious treatment option currently available, but only 10-20% of PC cases are resectable upon diagnosis. As of now, the sole biomarker approved by the United States Food and Drug Administration (US-FDA) for PC is carbohydrate antigen 19-9 (CA19-9); however, its use is limited for early diagnosis. An increasing number of studies have investigated a combination of biomarkers. Lately, there has been considerable interest in the application of a liquid biopsy, including the utilization of microRNAs (miRNAs), circulating tumor DNA (ctDNA), and circulating tumor cells (CTCs). Screening for PC is indicated for high-risk patients; studies on new diagnostic models combined with biomarkers for early detection have also shown promising results in terms of the ability of these models and biomarkers to aid clinicians in deciding on whether to start screening. This review seeks to provide a concise overview of the advancements in relation to existing biomarkers and explore novel strategies for the early detection of PC.

Precision cancer classification using liquid biopsy and advanced machine learning techniques.

Cancer presents a significant global health burden, resulting in millions of annual deaths. Timely detection is critical for improving survival rates, offering a crucial window for timely medical interventions. Liquid biopsy, analyzing genetic variations, and mutations in circulating cell-free, circulating tumor DNA (cfDNA/ctDNA) or molecular biomarkers, has emerged as a tool for early detection. This study focuses on cancer detection using mutations in plasma cfDNA/ctDNA and protein biomarker concentrations. The proposed system initially calculates the correlation coefficient to identify correlated features, while mutual information assesses each feature's relevance to the target variable, eliminating redundant features to improve efficiency. The eXtrem Gradient Boosting (XGBoost) feature importance method iteratively selects the top ten features, resulting in a 60% dataset dimensionality reduction. The Light Gradient Boosting Machine (LGBM) model is employed for classification, optimizing its performance through a random search for hyper-parameters. Final predictions are obtained by ensembling LGBM models from tenfold cross-validation, weighted by their respective balanced accuracy, and averaged to get final predictions. Applying this methodology, the proposed system achieves 99.45% accuracy and 99.95% AUC for detecting the presence of cancer while achieving 93.94% accuracy and 97.81% AUC for cancer-type classification. Our methodology leads to enhanced healthcare outcomes for cancer patients.

Extracellular Vesicles as Novel Diagnostic and Therapeutic Agents for Non-Melanoma Skin Cancer: A Systematic Review.

Standard non-melanoma skin cancer (NMSC) treatment involves surgery, recently combined with chemotherapy or immunotherapy in cases of advanced tumors. EVs, including exosomes, are integral to carcinogenesis, and are found in NMSC releasing mediators impacting tumor progression. Nevertheless, the precise intercellular signaling role of NMSC-derived EVs remains unclear. This review aims to elucidate their potential role in NMSC diagnosis and treatment. This systematic review encompassed literature searches in electronic databases from inception to September 2023, based on certain inclusion and exclusion criteria, addressing NMSC-derived EVs, their molecular cargo, and their implications in the diagnosis, prognosis, and treatment of NMSC. Key components were identified. Extracellular vesicle (EV) proteins and RNA have emerged as diagnostic biomarkers in EV-based liquid biopsy. Circular RNA CYP24A1, known for its molecular stability, holds promise as a diagnostic biomarker. Long noncoding RNAs (lincRNA-PICSAR) and Desmoglein 2 (DSg2) are linked to drug resistance, serving as prognostic biomarkers. EV mediators are being actively investigated for their potential role as drug delivery agents. In conclusion, this systematic review showed that NMSC-derived EVs display promise as therapeutic targets and diagnostic biomarkers. Further research is imperative to fully comprehend EV mechanisms and explore their potential in cancer diagnosis and treatment.

Liquid Biopsy: A Game Changer for Type 2 Diabetes.

As the burden of type 2 diabetes (T2D) continues to escalate globally, there is a growing need for novel, less-invasive biomarkers capable of early diabetes detection and monitoring of disease progression. Liquid biopsy, recognized for its minimally invasive nature, is increasingly being applied beyond oncology, and nevertheless shows its potential when the collection of the tissue biopsy is not possible. This diagnostic approach involves utilizing liquid biopsy markers such as cell-free nucleic acids, extracellular vesicles, and diverse metabolites for the molecular diagnosis of T2D and its related complications. In this context, we thoroughly examine recent developments in T2D liquid biopsy research. Additionally, we discuss the primary challenges and future prospects of employing liquid biopsy in the management of T2D. Prognosis, diagnosis and monitoring of T2D through liquid biopsy could be a game-changing technique for personalized diabetes management.