Enhancing detection and monitoring of circulating tumor cells: Integrative approaches in liquid biopsy advances

Abstract

Liquid biopsy offers a minimally invasive method for detecting and monitoring cancer, with key biomarkers including circulating tumor cells (CTCs), cell-free DNA (cfDNA), and extracellular vesicles (EVs). Among these, CTCs provide dynamic insights into tumor heterogeneity, metastatic potential, and therapeutic resistance through molecular profiling and single-cell analysis. This review examines recent advancements in technologies such as microfluidics, nanotechnology, and next-generation sequencing (NGS), which have improved the accuracy and clinical use of CTC detection. A comparative analysis of liquid biopsy techniques highlights the strengths and limitations of key platforms, including NGS, digital PCR (ddPCR), and quantitative PCR (qPCR), providing insights into diagnostic accuracy and clinical significance. Combining genomic, transcriptomic, and proteomic analyses with artificial intelligence (AI) tools has enhanced tumor profiling and supports personalized treatment decisions in precision oncology. Despite notable progress, issues like assay standardization, sample variability, regulatory complexity, and data integration still limit widespread clinical use. Future directions emphasize interdisciplinary innovation, clinical validation, and robust bioinformatics frameworks to facilitate the seamless incorporation of CTC-based liquid biopsy into standard oncology practice. Overcoming these challenges may allow liquid biopsy to become a standard tool for early cancer detection, ongoing monitoring, and individualized treatment.

1. Introduction

Circulating tumor cells (CTCs), released from both primary and metastatic tumors, are valuable indicators for monitoring tumor progression and treatment response [[1], [2], [3], [4]]. Since their initial discovery in the 19th century, CTCs have garnered significant attention due to their central role in hematogenous dissemination and their dynamic reflection of tumor heterogeneity [5]. Unlike conventional tissue biopsies, which offer a static and localized snapshot, CTC analysis allows continuous, non-invasive monitoring of tumor evolution, clonal selection, and the emergence of drug resistance [6], making CTC-based liquid biopsy a valuable tool in precision oncology. Recent improvements in techniques such as microfluidic capture, immunoaffinity enrichment, and label-free detection have enhanced the accuracy of CTC identification [[7], [8], [9], [10]]. Molecular analysis of CTCs provides insights into how tumors evolve, resist treatment, and spread [11]. Furthermore, the integration of next-generation sequencing (NGS) and single-cell transcriptomics has revolutionized CTC research, enabling high-resolution molecular characterization and refining the identification of actionable therapeutic targets for personalized interventions [12]. Despite these advancements, the clinical translation of CTC-based liquid biopsy continues to face critical challenges related to standardization of assays, pre-analytical variability, and regulatory approvals [13]. Addressing these barriers demands the incorporation of multi-omics approaches, artificial intelligence (AI)-driven analytics, and robust validation frameworks to enhance reliability, reproducibility, and clinical applicability [14].

While CTCs remain at the forefront of liquid biopsy innovation, their diagnostic and prognostic value is further enhanced when combined with other circulating biomarkers such as cell-free DNA (cfDNA) and extracellular vesicles (EVs) [15]. cfDNA analysis has demonstrated substantial potential in detecting tumor-specific genetic and epigenetic alterations and in monitoring minimal residual disease (MRD), complementing the phenotypic and functional information obtained from CTCs [16]. Similarly, EVs, including exosomes, mediate intercellular communication and carry molecular signatures that provide additional layers of biomarker discovery [17]. The synergistic integration of CTCs, cfDNA, and EVs within multi-analyte liquid biopsy platforms holds the promise of refining cancer diagnostics, improving therapeutic decision-making, and driving the development of personalized treatment strategies.

This review critically evaluates emerging technological innovations that enhance CTC detection, isolation, and molecular profiling, highlighting the transformative potential of liquid biopsy in tracking tumor heterogeneity, disease progression, and therapy resistance [1,5]. Despite notable progress, challenges related to assay standardization, data harmonization, and clinical validation continue to limit the widespread adoption of CTC-based liquid biopsy [13,16]. Bridging the gap between bench-side innovation and bedside application, the integration of CTC analysis into clinical workflows represents a paradigm shift in real-time tumor monitoring. Continued interdisciplinary advances will be pivotal in fully realizing the impact of CTC-based liquid biopsy in early cancer detection, precision therapeutic monitoring, and the next generation of personalized oncology.

2. Liquid biopsy: transforming cancer diagnostics and management with a focus on CTCs

Liquid biopsy has emerged as a transformative, non-invasive alternative to traditional tissue biopsies, providing real-time insights into tumor dynamics. Among various analytes, CTCs have been recognized as pivotal biomarkers, offering critical information on tumor progression, metastatic potential, and therapeutic response [18]. As cellular representatives of disease evolution, CTCs mirror tumor heterogeneity and therapy resistance mechanisms [19]. Despite their rarity in circulation, continuous advancements in detection and molecular characterization technologies have significantly expanded their clinical applicability.

2.1. Defining key components: CTCs, cfDNA, and EVs

Liquid biopsy leverages the detection and analysis of circulating biomarkers to monitor tumor biology dynamically. CTCs, shed from primary and metastatic tumors into the bloodstream, provide direct phenotypic and molecular insights into disease processes [4]. Their enumeration, morphological assessment, and molecular profiling have been extensively correlated with prognosis, therapeutic efficacy, and metastatic risk [16,18]. However, the low abundance of CTCs (approximately 1–10 cells/mL of blood) presents technical challenges [20], prompting the development of innovative microfluidic enrichment strategies and single-cell sequencing technologies that enable more precise characterization and identification of actionable targets [[7], [8], [9], [10]]. cfDNA comprises short DNA fragments released into circulation from apoptotic and necrotic tumor cells [21]. Analysis of cfDNA mutations, copy number variations, and methylation signatures using digital droplet PCR (ddPCR) and NGS platforms has allowed non-invasive tumor genotyping and the monitoring of minimal residual disease (MRD) with high specificity [22]. However, cfDNA lacks the cellular context necessary for assessing phenotypic plasticity or metastatic potential [23].

Conversely, EVs, including exosomes, are nano-sized vesicles secreted by tumor cells that carry a rich cargo of proteins, lipids, and nucleic acids [17]. EVs play critical roles in remodeling the tumor microenvironment, facilitating immune evasion, and promoting metastatic dissemination [24]. Advances in EV isolation techniques, such as ultracentrifugation, size-exclusion chromatography, and nanoparticle tracking, have greatly enhanced the clinical utility of EV profiling in cancer management [25]. Table 1 presents a comparative overview of the clinical relevance of CTCs, cfDNA, and EVs, emphasizing their respective contributions to early detection, prognosis, and therapeutic monitoring. The integration of these biomarkers within multi-omics frameworks further enhances the predictive precision of liquid biopsy. Fig. 1 illustrates the key components of liquid biopsy, highlighting their biological roles and clinical applications.

Table 1.

Key biomarkers (CTCs, cfDNA, exosomes) with their clinical significance and associated cancer types.

Biomarker	Clinical significance	Associated cancer types	References
CTCs	Serve as non-invasive indicators of tumor presence, metastatic potential, and treatment efficacy. Quantification and molecular characterization of CTCs provide insights into tumor heterogeneity, drug resistance, and prognosis. CTC enumeration is an FDA-approved prognostic biomarker in metastatic breast, prostate, and colorectal cancers.	Breast, prostate, colorectal, lung, pancreatic, gastric, hepatocellular carcinoma, glioblastoma, non-small cell lung cancer (NSCLC), small cell lung cancer (SCLC), malignant melanoma, renal cell carcinoma, head and neck squamous cell carcinoma (HNSCC), bladder cancer, esophageal cancer	[192], [193], [194]
cfDNA	Provides genetic information about tumor heterogeneity and clonal evolution. Useful for detecting actionable mutations (e.g., EGFR, KRAS, BRAF, TP53) and assessing minimal residual disease (MRD). Can be used for early cancer detection, treatment monitoring, and recurrence prediction.	Breast, lung (NSCLC, SCLC), colorectal, pancreatic, gastric, hepatocellular carcinoma, glioblastoma, meningioma, ovarian, endometrial, esophageal, prostate, bladder, renal cell carcinoma, head and neck cancers	[195], [196], [197]
EVs	Facilitate intercellular communication by transporting tumor-derived proteins, lipids, and nucleic acids (mRNA, miRNA, lncRNA, circRNA). Play key roles in tumor progression, immune modulation, drug resistance, and biomarker discovery. Potential therapeutic targets and delivery vehicles for cancer therapy.	Breast, ovarian, pancreatic, lung, gastric, hepatocellular carcinoma, colorectal, prostate, glioblastoma, melanoma, esophageal, bladder, head and neck cancers	198,199

Fig. 1.

Unique contributions and overlapping roles of CTCs, cfDNA, and EVs in cancer diagnostics.

2.2. Advantages over conventional tissue biopsies

Liquid biopsy addresses many of the limitations of traditional tissue biopsies. [26]. It enables frequent, minimally invasive sampling for real-time monitoring of tumor dynamics, circumventing the need for repeated surgical interventions [27]. This approach not only reduces patient discomfort and procedural risks but also improves compliance with disease surveillance protocols. A major advantage of liquid biopsy, particularly CTC analysis, is its capacity to capture tumor heterogeneity and clonal evolution over time [28]. In contrast to static tissue biopsies that provide localized information, liquid biopsy offers a dynamic, real-time assessment of treatment-induced selection pressures and emerging resistance mechanisms [29]. Changes in CTC profiles can help adjust treatment before clinical signs of progression appear [30]. Additionally, liquid biopsy enhances early detection of recurrence by tracking CTC levels and cfDNA mutational changes, facilitating timely clinical intervention [31,32]. Its cost-effectiveness and scalability make it an attractive option for longitudinal monitoring across diverse patient populations. As summarized in Table 2, liquid biopsy provides key advantages over traditional tissue biopsy, including reduced invasiveness, faster turnaround, scalability, and compatibility with modern technologies. Clinical studies in advanced cancer have shown that CTCs can effectively guide treatment decisions. Although CTCs are scarce, recent advances in enrichment and detection methods have improved their reliability. Culturing CTCs in vitro can further enhance our understanding of metastasis and support the development of personalized therapies. Importantly, the integration of NGS, AI, and machine learning (ML) is expanding the clinical potential of liquid biopsy. These tools improve molecular profiling, enable early cancer detection, and support dynamic treatment monitoring, reinforcing the role of liquid biopsy in precision oncology.

Table 2.

Comparative analysis of traditional tissue biopsy versus liquid biopsy [195,200,201].

Comparison criteria	Traditional biopsy	Liquid biopsy	Comparative analysis
Invasiveness	Highly invasive; requires surgical or needle-based extraction, with procedural risks.	Minimally invasive; blood draw-based, reducing patient risk and discomfort.	Liquid biopsy significantly minimizes invasiveness, enhancing patient safety and compliance.
Turnaround Time	Longer (days to weeks) due to tissue processing and histological evaluation.	Faster (within days) due to direct molecular assays.	Liquid biopsy provides quicker results, enabling timely clinical decisions.
Cost	Higher costs associated with surgery, hospitalization, and complex tissue analysis.	Lower costs, mainly linked to blood sampling and molecular diagnostics.	Liquid biopsy is generally more cost-effective for longitudinal monitoring.
Accuracy	Gold standard for diagnosis but limited in representing tumor heterogeneity.	High sensitivity and specificity with evolving accuracy through multi-omics and AI integration.	Liquid biopsy enhances real-time tumor heterogeneity assessment, complementing traditional biopsy.
Sample representation	Captures only a specific tumor region at one time.	Reflects dynamic tumor evolution by analyzing circulating biomarkers.	Liquid biopsy offers broader and temporal tumor representation.
Monitoring capabilities	Requires repeated invasive procedures for follow-up.	Allows serial, non-invasive monitoring of MRD and therapy resistance.	Liquid biopsy facilitates safer and more frequent disease monitoring.
Technological advances	Based on imaging, histopathology, and immunohistochemistry (IHC).	Incorporates NGS, ddPCR, single-cell profiling, and AI-powered analytics.	Liquid biopsy leverages cutting-edge technologies for enhanced molecular insights.
Clinical utility	Essential for initial diagnosis, staging, and primary treatment guidance.	Emerging as a complementary tool for early detection, prognosis, and treatment adaptation.	Liquid biopsy is expanding its clinical utility across the cancer care continuum.
Challenges	Sampling bias, procedural complications, and limited ability to monitor tumor evolution.	Issues with assay standardization, pre-analytical variability, and clinical validation.	Both approaches have challenges; liquid biopsy requires further standardization for routine use.

2.3. Technological innovations enhancing liquid biopsy functionality

Recent technological innovations have further refined the diagnostic capabilities of liquid biopsy, particularly through the integration of AI and advanced computational tools [33]. AI-based algorithms are revolutionizing the interpretation of vast multi-omics datasets by identifying subtle biomarker patterns and predicting therapeutic responses with remarkable accuracy [34]. These platforms enable rapid, automated analysis of CTC morphology, cfDNA mutation landscapes, and EV-derived molecular signatures, facilitating precise and data-driven clinical decision-making [35]. Beyond computational advancements, imaging technologies have also elevated liquid biopsy. High-content imaging systems and microfluidic chip-based capture platforms now allow real-time visualization of CTC clusters within circulation, which are implicated in metastasis and therapy resistance [36,37]. Furthermore, hybrid techniques integrating molecular imaging with liquid biopsy have enabled spatial mapping of tumor microenvironment interactions, offering unprecedented insights into metastatic biology [38].

Fig. 2 outlines the workflow of integrated liquid biopsy platforms, demonstrating the collection, processing, and analysis of CTCs, cfDNA, and EVs for clinical applications [39]. The combined integration of multi-omics technologies and AI-powered analytics facilitates comprehensive tumor profiling, early detection of therapeutic resistance, and dynamic adaptation of treatment strategies [40]. These innovations collectively reinforce the role of liquid biopsy as a cornerstone of precision oncology [41]. By enabling non-invasive, high-resolution tumor monitoring in real time, liquid biopsy bridges the translational gap between research advancements and clinical application [42]. As the field evolves, future efforts must focus on addressing challenges related to assay standardization, regulatory validation, and clinical integration [43]. Emphasizing interdisciplinary collaboration and technological innovation will be critical to ensuring that liquid biopsy becomes an indispensable tool in the continuum of cancer care [44].

Fig. 2.

Comprehensive workflow of integrated liquid biopsy techniques for cancer diagnostics and monitoring.

3. Technological advancements in CTC profiling

Advances in technology have significantly enhanced the detection, isolation, and molecular characterization of CTCs, enabling real-time, high-precision insights into tumor biology [41]. Given their critical role in metastasis and therapy resistance, CTCs have emerged as cornerstone biomarkers within the liquid biopsy landscape [41]. Breakthroughs in microfluidics, nanotechnology, and NGS have dramatically improved the sensitivity, specificity, and throughput of CTC detection, thereby expanding their clinical applicability [45]. These technological innovations are reshaping cancer diagnostics, paving the way for early disease detection, dynamic monitoring, and personalized therapeutic strategies [46].

3.1. Microfluidic devices: enhancing precision in rare CTC isolation

Microfluidic technologies have revolutionized CTC isolation by exploiting physical and biological properties such as size, deformability, and surface markers, outperforming traditional enrichment methods [47]. The rarity of CTCs in peripheral blood (∼1–10 cells/mL) demands highly efficient isolation platforms, and microfluidic devices offer superior specificity and recovery rates [48]. These devices utilize size-based filtration, deformability, and immunoaffinity principles to selectively isolate viable CTCs while minimizing contamination with hematologic components [49]. Size-based microfluidic systems are designed to allow smaller blood cells to pass through while retaining larger CTCs based on their distinct biophysical characteristics [50]. Deformability-based platforms leverage the mechanical differences between tumor cells and normal blood cells to achieve selective enrichment while keeping CTCs intact for further molecular analysis [48]. Immunoaffinity-based microfluidic devices use surface antigen-antibody interactions, targeting markers such as epithelial cell adhesion molecule (EpCAM) to achieve high-purity CTC capture [51]. Next-generation lab-on-a-chip systems further enhance CTC isolation by integrating multiple separation modalities, improving diagnostic accuracy, and enabling real-time disease monitoring [52,53]. Automation within microfluidic platforms also ensures standardized workflows, reproducibility, and scalability for clinical application. Table 3 provides a comparative overview of leading current technologies employed for CTC and cfDNA detection [54]. These advancements are crucial for early cancer detection and offer clinicians timely, actionable insights into disease progression [55].

Table 3.

Summary of current modern technologies for CTC and cfDNA detection.

Technology	Type	Principle	Advantages	Limitations	References
Microfluidics	CTCs	Utilizes fluid dynamics and microscale channels to isolate tumor cells based on size, deformability, surface markers, and affinity techniques.	High throughput; Requires minimal sample volume; Automation potential Capable of single-cell analysis.	Requires precise control of flow dynamics; Potential for cell loss due to shear stress; Device clogging issues.	[202,203]
Immunomagnetic Capture	CTCs	Uses magnetic beads coated with antibodies specific to tumor markers (e.g., EpCAM) to selectively isolate CTCs from blood samples.	High specificity; Suitable for rare cell detection; Compatible with downstream molecular analysis.	Specificity depends on marker expression; Loss of antigen-negative CTCs; Requires additional purification steps.	[204]
Size-Based Filtration	CTCs	Separates CTCs from normal blood cells based on size and deformability through microporous membranes or microfluidic devices.	Simple and cost-effective methodology; Label-free technique; Effective for larger CTCs.	May miss smaller or highly deformable CTCs; Limited to size-dependent separation; Variability in cutoff size selection	[205]
Next-Generation Sequencing (NGS)	cfDNA	High-throughput sequencing technology enables comprehensive genomic analysis of cfDNA to detect somatic mutations, CNVs, and epigenetic modifications.	Highly sensitive and specific; Enables whole-genome/exome sequencing; Provides insights into tumor evolution and resistance mechanisms.	High cost; Requires specialized bioinformatics expertise; Data interpretation complexity	[206]
Digital PCR (dPCR)	cfDNA	Amplifies and partitions DNA into thousands of separate reactions, allowing precise quantification of mutations.	Extremely sensitive; Capable of absolute quantification of target DNA; Useful for detecting low-frequency mutations	Limited multiplexing capability; Higher reagent costs compared to qPCR; Requires droplet-based or chip-based platforms	[207]
Droplet-Based Technologies	cfDNA	Uses droplet microfluidics to partition cfDNA into nanoliter droplets for single-molecule analysis, enabling digital PCR and NGS applications.	High throughput; Efficient use of reagents; Compatible with single-cell sequencing	Technical challenges in droplet generation and stability; Requires specialized microfluidic instrumentation.	[208]
Lateral Flow Assays (LFAs)	CTCs, cfDNA	Uses antibodies or nucleic acid probes immobilized on a strip to visually detect CTCs or cfDNA fragments in a rapid, point-of-care manner.	Fast and cost-effective; Portable and user-friendly; Minimal sample processing required.	Lower sensitivity compared to PCR and sequencing-based methods; Semi-quantitative results; May require secondary validation	[209]
Electrochemical biosensors	cfDNA	Uses electrochemical signals (e.g., impedance, voltammetry) to detect cfDNA based on hybridization with complementary probes.	Highly sensitive and real-time detection; Potential for point-of-care applications; - Low sample volume required	Requires probe optimization for specificity; Surface fouling may affect signal quality	[210]
CRISPR-based detection	CTCs, cfDNA	Utilizes CRISPR-Cas enzymes for sequence-specific detection of oncogenic mutations in cfDNA or CTC-derived RNA.	Ultra-high specificity; Minimal sample input; Potential for rapid, point-of-care testing	Requires precise guide RNA design; Emerging technology; clinical validation ongoing	[211]

3.2. Nanotechnology-based approaches: boosting sensitivity and specificity

Nanotechnology has dramatically improved the sensitivity and specificity of CTC detection [56]. Functionalized nanoparticles, including gold, magnetic, and silica-based nanomaterials, enhance CTC capture efficiency by selectively binding to tumor-specific surface markers [57]. These nanoparticles are engineered to target markers such as EpCAM and tumor-associated antigens, ensuring high-affinity binding and improved detection [58]. The integration of nanotechnology with microfluidic platforms has led to the development of nano-enhanced assays, significantly lowering detection thresholds and enabling the identification of minimal residual disease (MRD) [59,60]. Detecting rare CTCs post-treatment offers critical insights into the risk of disease relapse and therapeutic resistance [61]. Beyond diagnostics, nanoparticle-based systems have enabled targeted drug delivery strategies, wherein therapeutic agents are conjugated to nanocarriers designed to selectively target and eliminate CTCs [62,63]. Nanotechnology thus plays dual roles, advancing both CTC detection and therapeutic targeting, making it a powerful tool in the arsenal of precision oncology [64]. Additionally, nano-enabled single-cell proteomics platforms have deepened our understanding of CTC heterogeneity, uncovering metastatic subpopulations and resistance phenotypes [65]. Collectively, these innovations underscore the transformative role of nanotechnology in expanding the frontiers of cancer diagnostics and management [66].

3.3. Next-generation sequencing (NGS): comprehensive molecular profiling of CTCs

NGS technologies have enabled comprehensive molecular profiling of CTCs, facilitating the detection of genetic mutations, epigenetic alterations, and markers of therapeutic resistance [67,68]. A major advancement lies in the application of single-cell sequencing to CTCs, offering unprecedented insights into intratumoral heterogeneity, clonal evolution, and epithelial-mesenchymal transition (EMT) processes [69]. Traditional bulk sequencing methods often obscure cellular diversity, whereas single-cell RNA sequencing (scRNA-seq) enables the resolution of distinct molecular subpopulations within the CTC pool [70]. These findings are key to understanding how tumors resist treatment and to designing personalized therapies [71]. The integration of NGS with AI-driven analytics has further enhanced CTC profiling capabilities by enabling automated pattern recognition, mutation detection, and predictive modeling [41,72]. Moreover, multi-omics integration—combining genomic, transcriptomic, and proteomic analyses of CTCs—offers a holistic view of tumor biology, bridging molecular discoveries with clinical application [73].

As the field of CTC-based liquid biopsy continues to advance, future research must focus on standardizing methodologies, expanding multicenter validation studies, and refining bioinformatics pipelines to enhance translational applicability [74]. The next frontier lies in developing multi-modal liquid biopsy platforms that seamlessly integrate CTC analysis with cfDNA sequencing, EV profiling, and AI-powered diagnostics, thereby providing a comprehensive and dynamic portrait of tumor evolution [75]. Collectively, these technological innovations establish CTCs as cornerstone biomarkers in precision oncology, unlocking new avenues for non-invasive cancer detection, real-time monitoring of therapeutic efficacy, and targeted intervention strategies [76]. By combining the precision of microfluidics, the sensitivity of nanotechnology, and the depth of NGS-powered molecular insights, liquid biopsy is poised to transform the future of cancer care, accelerating the clinical implementation of personalized medicine [77].

4. Integrated approaches for enhanced detection in liquid biopsy

Given the complexity of tumor biology, integrating multiple biomolecular platforms enables a comprehensive, dynamic, and high-resolution characterization of malignancies [78]. While liquid biopsy initially focused on individual biomarkers, recent advancements have transformed it into a multi-parametric diagnostic tool, providing real-time insights into tumor progression, metastasis, and therapeutic response [79]. Among circulating biomarkers, CTCs have emerged as particularly informative, offering both phenotypic and molecular perspectives on tumor evolution [80]. Analyzing CTCs, cfDNA, and EVs together within a liquid biopsy framework can improve diagnosis, prognosis, and real-time treatment monitoring [81].

4.1. Synergistic benefits of CTC and cfDNA dual analysis

The integration of CTC analysis with cfDNA sequencing has significantly advanced liquid biopsy applications, enhancing the ability to capture tumor heterogeneity, clonal evolution, and therapy resistance [82]. CTCs represent viable tumor cells actively disseminating into circulation, reflecting real-time biological processes, while cfDNA constitutes a molecular byproduct of apoptotic and necrotic tumor cells, harboring tumor-specific genetic alterations [83]. Together, this dual-analyte approach provides a more holistic and dynamic view of tumor evolution, facilitating early detection, therapy response assessment, and predictive modeling of disease progression [71]. CTC analysis offers insights into phenotypic plasticity, including epithelial-mesenchymal transition (EMT) status, metastatic potential, and resistance mechanisms [84], whereas cfDNA sequencing identifies actionable genomic alterations critical for refining targeted therapies and monitoring emerging resistant clones [85]. The application of advanced technologies such as single-cell RNA sequencing (scRNA-seq) and whole-genome sequencing (WGS) to CTCs and cfDNA further enhances the molecular resolution of liquid biopsy [86]. Detection platforms like digital droplet PCR (ddPCR), NGS, and CRISPR-based assays have improved sensitivity and specificity, enabling real-time monitoring and adaptive therapy adjustments [87]. Fig. 3 illustrates the detection capabilities of various CTC profiling techniques, emphasizing the superior diagnostic power of dual biomarker analysis. This combined approach marks a significant step forward in personalized oncology, enabling dynamic, real-time disease surveillance and improving clinical decision-making [88].

Fig. 3.

Comparative analysis of CTC detection methods: sensitivity, specificity, and clinical applicability.

4.2. Exosome profiling: insights into the tumor microenvironment and metastasis

Exosomes play a fundamental role in tumor communication with the microenvironment, immune evasion, and metastatic progression [89]. These nano-sized vesicles, actively secreted by tumor cells, encapsulate oncogenic proteins, lipids, mRNA, and miRNA, acting as molecular mediators that influence tumor behavior and therapy resistance [90]. Profiling exosomal cargo provides critical insights into tumor biology and serves as a promising source of novel prognostic and predictive biomarkers [91]. The combination of exosome profiling with CTC and cfDNA analysis substantially enhances the molecular landscape captured by liquid biopsy [92]. Exosomes contribute to the conditioning of the pre-metastatic niche and facilitate immune system modulation, both essential for successful metastatic colonization [93]. Their intrinsic stability in circulation and the advent of efficient isolation techniques such as ultracentrifugation, immunoaffinity capture, and nanoparticle tracking have significantly improved their clinical applicability [94]. Integrative approaches, such as combining exosomal RNA (exoRNA) analysis with CTC transcriptomics, offer deeper insights into the molecular pathways driving tumor progression, aiding in therapeutic targeting and precision treatment development [71,95]. Exosome profiling improves tumor classification and therapy monitoring, strengthening the overall value of liquid biopsy.

4.3. Multi-omics platforms: combining genomic, transcriptomic, and proteomic data

The emergence of multi-omics liquid biopsy platforms, combining genomic, transcriptomic, and proteomic analyses, has significantly advanced cancer diagnostics by enabling detailed molecular characterization of tumors [86]. Through the integration of CTC-derived single-cell transcriptomics, cfDNA mutation profiling, and exosomal proteomics, multi-omics approaches capture tumor heterogeneity at multiple biological levels, refining disease stratification and predictive modeling [96]. Single-cell transcriptomic analyses of CTCs provide unprecedented insights into clonal diversity, EMT progression, and metastatic dissemination patterns [97]. When combined with cfDNA-based mutation tracking and exosomal biomarker profiling, these multi-omics strategies substantially improve biomarker discovery and therapeutic targeting [98]. The application of artificial intelligence (AI) and machine learning (ML) algorithms has further propelled multi-omics integration, enabling the identification of complex biomarker signatures and enhancing predictive capabilities [99]. AI-driven analytics facilitate early diagnosis, treatment optimization, and the identification of emerging resistance mechanisms through sophisticated pattern recognition across large multi-modal datasets [100].

Table 4 summarizes the transformative potential of AI-enhanced multi-omics analyses, highlighting their impact on personalized oncology and biomarker-driven therapy selection.

Table 4.

AI-driven multi-omics integration in liquid biopsy.

Multi-omics component	AI-driven enhancement	Clinical application	References
CTC single-cell transcriptomics	AI models identify clonal diversity, epithelial-mesenchymal transition (EMT) markers, and stemness signatures through deep learning-based clustering and feature selection.	Enables real-time monitoring of metastatic progression and treatment response.	212
cfDNA mutation profiling	Machine learning algorithms detect low-frequency mutations, tumor evolution patterns, and minimal residual disease (MRD) through error-correction methods.	Facilitates early resistance detection and personalized therapy adaptation.	213
Exosomal proteomics	AI-driven proteomic analysis deciphers key protein biomarkers associated with tumor heterogeneity, immune evasion, and therapy resistance.	Enhances therapy response prediction and biomarker discovery for targeted interventions.	214
AI-powered data integration	Correlates multi-omics data (CTCs, cfDNA, exosomes) using deep learning frameworks, enhancing feature selection and predictive modeling.	Advances precision oncology by improving diagnostic accuracy and personalized treatment plans.	215
Spatial imaging-liquid biopsy hybrids	AI-driven fusion of spatial transcriptomics with liquid biopsy-derived molecular data for integrative tumor profiling.	Enables tumor microenvironment characterization and identification of immune escape mechanisms.	216
Longitudinal biomarker tracking	AI-based longitudinal models analyze temporal biomarker changes to predict tumor evolution, resistance mechanisms, and relapse probability.	Supports adaptive treatment strategies and dynamic disease monitoring.	217

Several cutting-edge advancements are accelerating the clinical translation of integrated liquid biopsy approaches. AI-driven predictive modeling enhances biomarker discovery by identifying high-confidence molecular signatures [101]; spatial imaging-liquid biopsy hybrids provide integrated molecular and spatial insights into tumor architecture [102]; and longitudinal biomarker tracking enables dynamic real-time monitoring of therapy-induced tumor evolution [103]. As liquid biopsy technologies continue to evolve, their seamless integration into routine oncology practice will facilitate precision-guided therapeutics, accelerate early detection strategies, and enable real-time tumor surveillance [104]. The convergence of CTCs, cfDNA, and exosomal biomarkers within an AI-powered multi-omics framework represents a significant milestone in cancer diagnostics, providing high-resolution, real-time molecular insights that drive personalized therapeutic interventions [105]. Through multi-analyte approaches, oncology is transitioning towards a truly individualized care paradigm, where therapeutic regimens are continuously optimized based on real-time molecular profiling [106].

Ultimately, the integration of CTCs, cfDNA, and exosomal biomarkers within liquid biopsy frameworks enhances the depth of tumor characterization, refines diagnostic accuracy, and improves clinical outcomes, ushering in a new era of precision cancer management [107,108].

5. Clinical translation of liquid biopsy techniques: opportunities and challenges

Recent advancements in liquid biopsy technologies have positioned CTCs as cornerstone biomarkers, offering a minimally invasive and dynamic approach to cancer detection and treatment monitoring [109]. By enabling real-time tracking of tumor evolution, liquid biopsy enhances early detection, therapeutic response evaluation, and metastasis prediction [110]. However, the widespread clinical adoption of CTC-based liquid biopsy still faces significant challenges, including assay standardization, analytical validation, and regulatory approvals [111]. Addressing these barriers is essential for realizing the full potential of liquid biopsy in precision oncology [112].

5.1. Applications in early detection and monitoring

Liquid biopsy has revolutionized early cancer detection by offering superior sensitivity and specificity compared to traditional diagnostic approaches [113]. The combined detection of CTCs and cfDNA enables the identification of malignancies at very early stages, often before the onset of clinical symptoms [114], a crucial advantage for improving patient survival and enabling timely interventions [115]. CTCs provide detailed phenotypic and molecular insights into tumor heterogeneity, metastatic potential, and therapy resistance [106], while cfDNA offers a complementary perspective by capturing tumor-specific genetic alterations [116]. Integration of CTC enumeration and molecular profiling with cfDNA mutation analysis enhances diagnostic precision, enabling the detection of actionable mutations and patient stratification for targeted therapies [117]. Table 5 summarizes key clinical trials supporting the efficacy of CTC-based liquid biopsy in disease monitoring and treatment planning. Moreover, CTC characterization aids in predicting metastatic progression through the analysis of morphological features, gene expression profiles, and epithelial-mesenchymal transition (EMT) markers [118,119]. The addition of exosome profiling further enriches tumor characterization, capturing biomolecular signatures reflective of the tumor microenvironment and malignancy progression [120]. This integrated multi-analyte approach strengthens precision oncology efforts by enabling individualized treatment strategies, recurrence surveillance, and adaptive therapy optimization [121].

Table 5.

Summary of clinical trials investigating liquid biopsy applications in cancer diagnostics and monitoring.

Trial name	Cancer type	Biomarker	Objective	Key findings/Outcomes
NCT02868788	Non-Small Cell Lung Cancer	cfDNA	To assess the efficacy of cfDNA in monitoring treatment response and detecting resistance mutations.	cfDNA dynamics correlated with imaging results; enabled earlier prediction of resistance mutations and treatment failure.
NCT03595960	Breast Cancer	CTCs	Evaluate CTCs as predictors of response to targeted therapies.	Higher baseline CTC counts were linked to poorer prognosis; dynamic CTC changes reflected treatment effectiveness.
NCT03448716	Colorectal Cancer	cfDNA and CTCs	To analyze the role of liquid biopsy in guiding clinical decisions during therapy.	Liquid biopsy-guided therapy adjustments improved patient outcomes; showed superior sensitivity for recurrence detection over standard imaging.
NCT04116567	Ovarian Cancer	cfDNA Methylation Patterns	Investigate cfDNA methylation signatures for early detection and monitoring of disease recurrence.	Identified tumor-specific methylation markers; demonstrated high predictive value for relapse risk assessment.
NCT03612586	Pancreatic Cancer	CTCs	Evaluate the role of CTCs in detecting metastatic progression and therapeutic response.	CTC presence strongly associated with disease progression; provided real-time insights into therapeutic efficacy.
NCT04212836	Multiple Cancer Types	cfDNA and Exosomal Biomarkers	Explore multi-omics integration of cfDNA and exosome analysis for enhanced tumor monitoring.	AI-driven multi-omics analysis improved tumor heterogeneity characterization and personalized treatment response evaluation.
NCT05059444	Prostate Cancer	CTCs and RNA Profiling	Assess RNA signatures in CTCs for monitoring androgen receptor signaling inhibitors.	RNA-based CTC profiling accurately predicted treatment resistance and disease progression.
NCT04717129	Glioblastoma	cfDNA and Tumor-Derived EVs	Investigate extracellular vesicle (EV)-based cfDNA for non-invasive brain tumor monitoring.	Liquid biopsy enabled early detection of tumor progression and response to targeted therapy.

5.2. Real-time assessment of therapeutic efficacy

CTC-based liquid biopsy provides dynamic monitoring of treatment efficacy, allowing real-time assessment of tumor adaptation under therapeutic pressure [122]. Molecular and functional profiling of CTCs reveals therapy-induced clonal evolution and emerging resistance mechanisms [123]. For instance, cfDNA-detected resistance mutations can preemptively indicate treatment failure, prompting therapeutic adjustments [131]. Changes in CTC counts correlate strongly with treatment responses: declining levels suggest therapeutic success, while rising counts indicate resistance or disease progression [124]. Single-cell sequencing of CTCs enables high-resolution molecular profiling, elucidating EMT dynamics, clonal diversification, and resistance mechanisms [125,126]. Integration of CTC transcriptomics with cfDNA mutational profiling refines predictive models of therapeutic response, facilitating adaptive treatment strategies that improve patient outcomes [127].

5.3. Challenges in clinical implementation

Despite its transformative potential, CTC-based liquid biopsy faces significant hurdles in clinical standardization and regulatory acceptance [128]. The heterogeneity of detection methodologies leads to variability in CTC isolation efficiency, purity, and downstream analyses [129], underscoring the urgent need for standardized protocols [130]. To gain regulatory approval, tests must be carefully validated for accuracy, reliability, and clinical relevance [131]. The complex regulatory landscape often delays clinical translation, necessitating harmonized frameworks and cross-institutional collaborations [132]. Table 6 outlines major regulatory considerations critical for integrating CTC-based diagnostics into routine oncology care. Another major challenge lies in integrating the high-dimensional datasets generated by multi-omics liquid biopsy approaches [133]. Effective interpretation requires sophisticated bioinformatics pipelines, AI-driven analytics, and interdisciplinary collaboration among oncologists, bioinformaticians, and molecular pathologists [134]. Developing robust, real-time, clinically actionable computational tools is key to unlocking the full potential of liquid biopsy [135,136]. Ongoing clinical trials and research collaborations are paving the way for broader clinical adoption [136,137]. As summarized in Table 7, efforts to standardize protocols, streamline regulatory pathways, and advance computational analytics are critical for establishing liquid biopsy as a mainstay in precision oncology. By overcoming these barriers, CTC-based liquid biopsy is poised to revolutionize cancer detection, monitoring, and individualized treatment planning [138,139].

Table 6.

Key regulatory considerations for CTC-based liquid biopsy [26,218].

Regulatory challenge	Description	Potential solutions
Standardization of CTC Enumeration	Variability in detection methods affects reliability and reproducibility.	Establish global consensus guidelines and standardized protocols for CTC isolation and quantification.
Analytical Sensitivity & Specificity	Validation hurdles, including false positives/negatives, delay clinical adoption.	Implement harmonized regulatory frameworks with predefined performance metrics and inter-laboratory proficiency testing.
Data Integration Complexity	High-dimensional multi-omics datasets require advanced computational tools for meaningful interpretation.	Develop AI-driven bioinformatics pipelines and standardized data-sharing frameworks to enhance interoperability.
Cross-Institutional Variability	Differences in sample processing, CTC enrichment techniques, and analytical methods across laboratories hinder consistency.	Conduct multi-center validation studies with standardized methodologies and proficiency testing programs.
Clinical Utility Demonstration	Lack of large-scale, multi-phase clinical trials proving CTC-based liquid biopsy effectiveness in routine oncology care.	Expand real-world application studies, integrate CTC-based assays into precision oncology trials, and ensure post-market surveillance.
Regulatory Approval Pathways	Lack of clear regulatory pathways for novel CTC-based assays leads to prolonged approval times.	Advocate for adaptive regulatory frameworks that expedite approvals for validated CTC technologies with demonstrated clinical impact.
Reimbursement & Cost Barriers	High costs and lack of reimbursement policies limit clinical adoption.	Develop health-economic models demonstrating cost-effectiveness and advocate for insurance coverage policies.

Table 7.

Strategies to overcome challenges in CTC-based liquid biopsy.

Challenge	Current limitation	Proposed solution
CTC isolation & purity	Variability in detection methods and purity levels due to differences in isolation techniques.	Establish standardized isolation protocols integrating microfluidics, immunomagnetic capture, and size-based filtration.
Multi-Omics data interpretation	Complexity in integrating CTCs, cfDNA, and exosomal biomarkers for precision oncology.	AI- and ML-driven bioinformatics pipelines for multi-omics data harmonization and predictive modeling.
Regulatory approval hurdles	Stringent validation requirements and lengthy approval processes for clinical implementation.	Develop collaborative regulatory frameworks with adaptive approval pathways for novel liquid biopsy assays.
Clinical adoption	Limited physician awareness and reluctance to transition from traditional biopsies.	Implement comprehensive training programs and clinical guidelines to enhance physician familiarity and confidence.
Reproducibility	Variability in results across laboratories due to differences in sample processing and analysis.	Establish cross-laboratory standardization through multi-center validation studies and proficiency testing programs.
Real-time data utility	Delays in clinical decision-making due to manual data analysis and interpretation.	Integrate automated AI-powered reporting systems for real-time analysis and clinical decision support.
Cost and reimbursement issues	High costs of CTC-based assays and lack of insurance reimbursement limit accessibility.	Develop cost-effectiveness models and advocate for reimbursement policies through health economic studies.
Tumor heterogeneity representation	Single time-point CTC analysis may not capture real-time tumor evolution.	Implement longitudinal monitoring strategies using serial liquid biopsies for dynamic disease tracking.

5.4. Clinical validation and real-world applications of CTC-based liquid biopsy

The clinical translation of CTC-based liquid biopsy has accelerated, driven by high-impact studies demonstrating its potential in early detection, real-time therapeutic monitoring, and prognostic assessment across cancer types [140]. Integration of CTC enumeration and molecular profiling into clinical workflows is reshaping personalized oncology strategies [141].

5.4.1. CTCs in breast cancer: monitoring treatment response and predicting outcomes

A landmark Phase III trial (SWOG S0500) validated CTC enumeration as a real-time predictor of treatment efficacy in metastatic breast cancer (MBC), showing that persistent high CTC levels after initial chemotherapy cycles correlated with poor progression-free survival (PFS) and overall survival (OS) [142,143]. This highlighted the utility of early therapeutic intervention based on CTC dynamics [144]. Recent HER2-positive breast cancer trials demonstrated that dynamic changes in CTC-HER2 status during therapy could guide switching between HER2-targeted treatments, as being evaluated in the ongoing PERSEVERE study [[145], [146], [147]].

5.4.2. CTC-based prognostic insights in colorectal cancer

In colorectal cancer (CRC), the VISNU-1 trial confirmed that high baseline CTC counts predict poor OS and PFS in patients receiving first-line chemotherapy [71,148,149]. Molecular profiling of CTCs has also revealed key mutations (e.g., KRAS, BRAF), enabling the early detection of treatment resistance and facilitating adaptive therapy strategies [150,151].

5.4.3. CTCs in lung cancer: early detection and therapy guidance

In lung cancer, the STIC CTC METABREAST study demonstrated that baseline CTC levels can predict treatment responses, guiding the choice between endocrine therapy and chemotherapy [134]. In NSCLC, CTC-derived PD-L1 expression has emerged as a promising biomarker to predict immunotherapy response, complementing tissue-based PD-L1 testing [133,[152], [153], [154]].

5.4.4. CTCs as a surrogate biomarker for MRD in prostate cancer

In prostate cancer, the PROPHECY trial demonstrated that AR-V7-positive CTCs predict poor response to androgen receptor inhibitors, influencing treatment decisions between hormonal therapy and chemotherapy [[155], [156], [157]]. The ongoing IMPACT trial explores CTC-based stratification for early therapeutic interventions in high-risk prostate cancer patients [158].

5.4.5. Clinical translation and future implications

The incorporation of CTC-based liquid biopsy into oncology practice is revolutionizing cancer monitoring and individualized treatment [159]. Real-time CTC profiling enables personalization of therapy based on tumor evolution and resistance emergence [160,161]. The detection of markers such as PD-L1 and AR-V7 within CTCs has introduced new standards for guiding immunotherapy and hormonal therapy selection [162]. Future research must focus on standardizing CTC detection protocols, integrating AI-driven analytics, and expanding clinical trials to establish universal guidelines [133,163]. CTC-based liquid biopsy is advancing precision oncology by enabling adaptive, personalized treatment strategies, reducing unnecessary interventions, and improving clinical outcomes. The clinical validation of CTC-based liquid biopsy underscores its transformative potential across multiple cancer types, setting the stage for its broader integration into precision oncology. While significant progress has been made in early detection, therapeutic monitoring, and prognostic modeling, the expanding applications of liquid biopsy extend beyond current clinical practice.

6. Potential applications of liquid biopsy with special focus on CTCs: advancements in cancer diagnostics and management

Liquid biopsy has emerged as a transformative platform in cancer diagnostics and therapeutic monitoring, offering a non-invasive, dynamic, and high-resolution approach for assessing tumor evolution in real time [164]. Among its various analytes, CTCs serve as central biomarkers, providing comprehensive insights into tumor heterogeneity, metastatic potential, and treatment resistance [165]. This section explores the diverse applications of CTC-based liquid biopsy across research, clinical practice, and pharmaceutical development, underscoring its growing impact on advancing precision oncology [166].

6.1. Role of liquid biopsy in cancer research and biomarker discovery

In oncological research, CTC analysis has revolutionized biomarker discovery and validation, facilitating the identification of tumor-specific genetic, epigenetic, and proteomic signatures critical for early cancer detection and targeted therapy development [167]. Unlike static tissue biopsies, CTC-based liquid biopsy enables real-time molecular profiling of live tumor cells, capturing dynamic tumor evolution and therapy-induced clonal selection [168]. The integration of advanced isolation techniques, such as microfluidic enrichment, immunoaffinity capture, and label-free detection platforms, has significantly improved CTC capture efficiency, enabling the study of rare metastatic subpopulations with unprecedented precision [169]. Furthermore, NGS and single-cell RNA sequencing (scRNA-seq) have facilitated high-resolution molecular characterization of CTCs, unveiling driver mutations, transcriptional alterations, and epithelial-mesenchymal transition (EMT)-associated gene expression patterns [170]. This helps improve early detection and supports the design of biomarker-based treatments [171]. Additionally, CTC-derived biomarkers offer great promise for patient stratification based on tumor biology, guiding personalized treatment plans [172]. By correlating CTC phenotypic and molecular characteristics with clinical outcomes, researchers are refining predictive models of disease progression and therapy response, paving the way for more effective targeted interventions [16]. Multi-omics profiling, integrating CTCs, cfDNA, and exosomes, further enhances the diagnostic power of liquid biopsy by offering a multidimensional view of tumor evolution [75].

6.2. Clinical applications: enhancing early detection, monitoring, and personalized treatment

In clinical practice, CTC-based liquid biopsy plays a pivotal role in real-time tumor monitoring, providing a minimally invasive alternative to tissue biopsies, particularly in cases involving anatomically challenging or surgically inaccessible tumors [173]. Serial tracking of CTC burden and molecular alterations enables early detection of disease recurrence, therapeutic resistance, and treatment efficacy [174]. Longitudinal CTC monitoring allows clinicians to detect emerging drug resistance mutations, phenotypic shifts, and clonal evolution, enabling proactive therapeutic adjustments [18]. For instance, an increase in mesenchymal-like CTCs often signals therapy resistance and metastatic progression, warranting shifts toward EMT-targeted therapies [175]. Conversely, a sustained decline in CTC counts following treatment correlates with favorable prognosis, reinforcing their clinical significance [176,177]. Moreover, the integration of CTC analysis with cfDNA mutation profiling and exosome-derived molecular signatures provides a comprehensive real-time assessment of tumor dynamics. This multi-analyte approach enables oncologists to design tailored therapeutic regimens, reduce unnecessary treatments, and ultimately improve patient survival outcomes.

6.3. Pharmaceutical applications: optimizing drug development and clinical trial design

The pharmaceutical industry is increasingly utilizing CTC-based liquid biopsy to optimize drug development and refine clinical trial design. Real-time monitoring of tumor evolution via CTC analysis enhances patient stratification for personalized treatments, improving therapeutic precision [178].

Pharmaceutical companies are employing CTC enumeration and molecular profiling to assess drug efficacy, predict resistance mechanisms, and optimize clinical trial inclusion criteria [179]. By identifying tumor-specific markers within CTC populations, researchers can tailor drug targeting strategies, maximizing therapeutic efficacy while minimizing adverse effects [180,181]. Additionally, CTC-based liquid biopsy serves as a valuable companion diagnostic tool, accelerating the development of biomarker-driven therapies [8]. One promising application involves tracking therapy-induced mutations and resistance pathways using CTC-derived RNA sequencing, which enables early intervention strategies such as combination therapy or second-line treatment adaptations [182]. This is particularly impactful in immuno-oncology, where immune checkpoint inhibitor resistance remains a significant challenge. Furthermore, CTC-based approaches are transforming clinical trial methodologies by enabling real-time patient monitoring, interim data-driven protocol adjustments, and more efficient regulatory approval processes. By continuously monitoring CTC dynamics and cfDNA alterations, researchers can optimize trial endpoints and reduce trial durations, thereby accelerating the clinical development of innovative therapies. As liquid biopsy technologies continue to advance, CTC-based approaches are poised to become indispensable in the evolving landscape of precision oncology. Future research must focus on standardizing CTC detection methods, optimizing bioinformatics pipelines, and advancing AI-driven biomarker discovery [183]. Key emerging trends include the development of CTC-derived organoids for functional drug testing, enabling patient-specific drug response modeling and truly personalized therapeutic selection; AI-powered predictive modeling of CTC transcriptomes to refine tumor evolution models and enhance therapy resistance prediction; and spatial mapping of CTCs within the bloodstream to deepen our understanding of metastatic dissemination pathways [184]. By addressing existing technical and clinical challenges, CTC-based liquid biopsy holds the potential to become a cornerstone of precision medicine, enabling earlier cancer detection, real-time monitoring, and biomarker-guided therapeutic interventions. The continuous refinement of CTC isolation, characterization technologies, and integration with multi-omics profiling will accelerate the transition toward an individualized oncology landscape, ultimately transforming cancer diagnosis, prognosis, and treatment paradigms.

7. Future directions and emerging trends in CTC-based liquid biopsy

As liquid biopsy technologies continue to advance, innovations in microfluidics, nanotechnology, artificial intelligence (AI), and multi-omics integration are driving improvements in the precision, sensitivity, and clinical applicability of CTC-based diagnostics [185]. CTCs are now seen as important real-time markers for tracking cancer, guiding treatment, and predicting spread, reinforcing their central role in precision oncology. However, their rarity in circulation presents significant technical challenges, necessitating the development of highly efficient isolation and molecular characterization platforms [186]. The integration of microfluidic systems has revolutionized CTC capture, enabling high-throughput, label-free enrichment with enhanced purity and cell viability, thereby facilitating downstream molecular analyses [50]. Concurrently, nanotechnology-driven approaches utilizing functionalized nanoparticles conjugated with CTC-specific biomarkers have enhanced the high-affinity capture and multi-modal characterization of CTCs across genomic, transcriptomic, and proteomic dimensions [56]. Advances in imaging methodologies, such as fluorescence-based high-content imaging and imaging mass cytometry, provide real-time tracking of CTCs in circulation, offering critical insights into metastatic progression, cellular heterogeneity, and treatment response [187].

AI and ML are transforming the landscape of CTC-based liquid biopsy by enhancing data interpretation, biomarker discovery, and clinical decision-making processes. AI-driven algorithms now analyze large-scale datasets derived from CTC morphology, single-cell transcriptomics, and multi-omics profiles to refine diagnosis and predict therapeutic responses [188]. Deep learning models facilitate image-based CTC classification and mutation profiling, improving detection accuracy, automating phenotypic analyses, and optimizing therapeutic targeting strategies [161]. The role of CTC analysis in personalized medicine continues to expand, particularly in the monitoring of minimal residual disease (MRD) and the early detection of disease relapse [189]. Unlike static tissue biopsies, which provide only a single snapshot of tumor biology, serial CTC profiling enables longitudinal monitoring of clonal evolution, therapy-induced resistance mechanisms, and tumor progression dynamics [190]. One of the most promising applications of CTC analysis is its capacity to guide therapeutic decisions based on the detection of dynamic molecular changes. Evaluation of CTC-derived transcriptomic and proteomic alterations enables the early identification of resistance markers, allowing for timely adjustment of targeted therapies or immunotherapy regimens [16].

Additionally, combining trends in CTC enumeration with cfDNA mutational profiling enhances patient stratification based on therapeutic response likelihood, thereby optimizing clinical outcomes [3]. The integration of CTC profiling with radiomic and imaging-based data further refines treatment response prediction, linking CTC phenotypic diversity to imaging-derived tumor characteristics and facilitating precision-guided therapeutic adaptations [191]. However, some important challenges still need to be addressed. Standardization of sample collection, processing, and data interpretation is critical for clinical implementation. Variability in isolation methodologies, discrepancies in molecular characterization protocols, and the absence of universally accepted clinical thresholds for CTC enumeration continue to impede widespread adoption. Establishing harmonized standard operating procedures (SOPs) across academic institutions, clinical laboratories, and industry stakeholders is essential to ensure reproducibility and clinical reliability. Regulatory approval remains another major hurdle. CTC-based diagnostics require extensive validation to demonstrate analytical performance, clinical sensitivity, and prognostic utility. Collaborative efforts among regulatory agencies, scientific consortia, and industry partners are needed to develop clear guidelines that facilitate the approval and commercialization of CTC-based assays.

Future research should prioritize the development of automated, AI-enhanced CTC detection platforms to improve standardization and reproducibility. Advancements in single-cell multi-omics profiling will be crucial for enabling detailed characterization of CTC heterogeneity and therapy resistance pathways. Additionally, integrating spatial and temporal CTC tracking with advanced imaging technologies will refine real-time, patient-specific therapeutic strategies.

As the field progresses, CTC-based diagnostics are poised to become integral components of next-generation cancer care, enabling ultra-sensitive early detection, adaptive therapeutic monitoring, and real-time precision medicine applications. Emerging trends in multi-omics integration, AI-driven biomarker discovery, and lab-on-a-chip microfluidic technologies will further establish CTCs as indispensable biomarkers within the liquid biopsy landscape. By overcoming current technical and regulatory barriers, CTC-based liquid biopsy is set to revolutionize cancer diagnostics, therapeutic decision-making, and clinical trial optimization. Over the next decade, the seamless integration of CTC analysis into routine oncology workflows is anticipated, ushering in an era of real-time molecular surveillance and patient-centric precision oncology.

8. Conclusion

This review highlights the pivotal role of liquid biopsy in advancing modern oncology, with a special emphasis on CTCs as central biomarkers for understanding tumor heterogeneity, disease progression, and therapeutic resistance. The integration of CTC analysis with complementary biomarkers such as cfDNA and exosomal profiling has significantly enhanced the real-time monitoring of tumor dynamics, offering a comprehensive and multidimensional molecular snapshot of cancer evolution. Technological advancements in microfluidics, nanotechnology, and NGS have substantially improved the sensitivity, specificity, and resolution of CTC isolation and characterization, enabling early detection, precise treatment stratification, and real-time assessment of therapeutic response. Emerging applications of AI and ML are revolutionizing the interpretation of complex multi-omics datasets, uncovering hidden biomarker patterns and refining predictive models for therapy resistance and disease progression. Nanotechnology-driven innovations, including the development of functionalized nanoparticles and the exploration of nanorobots for targeted therapeutic delivery, are further expanding the clinical utility of CTC-based liquid biopsy, facilitating real-time molecular surveillance and precision-targeted interventions. Together, these developments are helping establish liquid biopsy as a key tool in personalized cancer care by enabling non-invasive, real-time monitoring and adaptive therapeutic management. Despite these promising developments, several challenges must be addressed to achieve the widespread clinical adoption of CTC-based liquid biopsy. These include the standardization of sample collection and processing methodologies, the validation of predictive biomarkers across diverse patient populations, and the establishment of robust regulatory frameworks to ensure reproducibility, consistency, and clinical reliability. As the field continues to evolve, the convergence of multi-omics profiling, AI-driven analytics, and real-time liquid biopsy surveillance is poised to expand the applications of CTC-based technologies, solidifying their role in next-generation oncology diagnostics and therapeutics. With ongoing innovation and cooperation between researchers, clinicians, and regulators, liquid biopsy holds the potential to revolutionize cancer diagnosis, monitoring, and treatment—ushering in a new era of precision, personalization, and patient-centered oncology.

Credit author statement

Thanmayi Velpula: Investigation; Validation; Writing–original draft; Viswanath Buddolla: Concept, Resources; Supervision; Project administration; Reviewing & editing.

Ethical statement

This review forms part of a project approved by the Institutional Animal Ethics Committee (IAEC) of Dr. Buddolla's Institute of Life Sciences, Tirupati, India (DRBILS/IAEC/LS/2023/01).

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work, we used LINER-AI to enhance the clarity, structure, and scientific presentation of the manuscript. After utilizing this tool, we thoroughly reviewed and edited the content to ensure its accuracy, originality, and alignment with the objectives of the publication. We take full responsibility for the content of the publication.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.