2.1. Early Cancer Detection

Early detection of cancer is crucial for effective treatment and disease management to reduce cancer-related deaths and improve patient outcomes. CTCs offer the potential for liquid biopsy-based screening, allowing the identification of cancers at an earlier, more treatable stage [26]. CTCs were first detected in cancer in the eighteenth century [27]. However, the process of local invasion and extravasation of CTCs has recently been shown to occur within a short span of time [28], suggesting that CTCs can be detected in the bloodstream at early stages of cancer, potentially allowing for early diagnosis before tumors become clinically evident [29,30]. A study involving 667 participants, of whom 235 were healthy individuals and 432 were patients with either colorectal cancer (CRC) or adenomas, showed that CTCs can be used to distinguish healthy individuals from patients with CRC or adenomas with a detection sensitivity of up to 95.2%, even before colonoscopy [31]. Another study evaluating patients with chronic obstructive pulmonary disease (COPD) without clinically diagnosed lung cancer revealed that five out of 168 patients had detectable CTCs. Notably, all five individuals with detectable CTCs developed lung nodules within 1–4 years [32]. A third study involving patients with suspected prostate cancer based on high serum prostate-specific antigen (PSA) levels also revealed a high positive CTC-predicted biopsy outcome and prostate cancer aggressiveness [33]. Thus, the importance of using CTCs to predict disease occurrence cannot be underestimated. Additionally, capturing and analyzing CTCs using liquid biopsy techniques offer a non-invasive alternative to traditional tissue biopsies, providing a real-time snapshot of the tumor’s genetic and phenotypic characteristics.

2.2. Prognostic Indicators

The presence of CTCs in the bloodstream provides valuable prognostic information, aiding in predicting disease outcomes and guiding treatment decisions [34,35,36]. Studies have shown that higher CTC counts and the presence of CTC clusters are associated with poorer outcomes across various cancer types [37,38]. In clinical settings, CTCs are commonly used as a liquid biopsy method to screen for tumors, monitor disease, and predict patients’ prognoses [39]. A CTC count cutoff value of ≥3 CTCs/7.5 mL blood is considered unfavorable for metastatic colorectal cancer [40]. In a study involving hormone receptor-positive (HR+) metastatic breast cancer patients, the overall survival (OS) and progression-free survival (PFS) of patients with CTC counts $\ge$ 5 per 7.5 mL blood after treatment was significantly worse than those of patients with <5 CTCs [41]. Also, CTC counts ≥ 10 per 5 mL blood in small-cell lung cancer (SCLC) patients were closely associated with advanced stage (high lymph node metastasis and distant metastasis), indicating a more unfavorable prognosis [42]. These recent investigations have refined our understanding of CTCs as robust prognostic indicators, guiding clinicians in predicting disease outcomes and tailoring treatment strategies. Multiple detection methods have been developed to comprehensively characterize CTCs, providing valuable insights into the likely cause of disease [39,43]. CTC enumeration is increasingly being incorporated into clinical practice as a predictive tool, and CTC counts are being used to stratify patients, helping tailor treatment plans based on individual prognoses [44].

2.3. Tumor Heterogeneity

Tumor cells obtained from liquid biopsies exhibit genetic and phenotypic diversity, reflecting heterogeneity within the primary tumor [13,45]. Numerous studies have discovered the presence of different CTC subpopulations in cancers [13,46,47,48]. For instance, Freed and colleagues identified two CTC subpopulations expressing epithelial cell adhesion molecule, EpCAM (CTC^EpCAM), or fibroblast activation protein-alpha, FAPα (CTC^FAPα), in pancreatic ductal adenocarcinoma (PDAC) patients. Using the ratios of CTC^FAPα to CTC^EpCAM, they were able to stratify patients as responders versus non-responders to niraparib treatment [46]. In a non-small cell lung cancer (NSCLC) study, the authors were able to detect different gene signatures related to therapy resistance (MET and HER3) and the initiation of metastasis (ALHD1) using CTCs [49]. The spectrum of cancer heterogeneity has long been under scrutiny as a factor allowing the tumor to adapt to different microenvironmental stressors with different subpopulations that may evolve to increase disease aggressiveness and decrease therapeutic response [50]. The study of CTCs, therefore, allows researchers to understand and monitor tumor heterogeneity, providing crucial information for devising effective and personalized treatment strategies.

2.4. Metastasis and Disease Progression

Metastasis accounts for more than 90% of cancer-related mortalities [51,52,53]. This is because treatment options available for patients with metastatic solid tumors are rarely curative [54,55]. Metastatic events in cancer involve the spread of tumor cells from the primary to secondary sites, following a phenotypic transition from epithelial to mesenchymal phenotype, cancer cell invasion into circulation, dormancy, and colonization at distant sites [56,57]. CTCs can be released by aggressive and metastatic tumors into circulation, where they extravasate to other remote sites for continuous colonization, leading to the growth of further lesions [58]. Nonetheless, research suggests that CTCs can be shed from primary tumors at early stages of cancer, challenging the traditional view that metastasis occurs primarily in advanced disease [6]. This early dissemination contributes to the understanding of metastatic potential and the dynamics of cancer progression [6,59]. Following the injection of pancreatic cancer cells expressing fluorescent proteins into the earlobes of mice to form solid tumors, the presence of CTCs with fluorescent proteins was detected in the bloodstream of the mice at different stages of development [60]. Using quantum dots, the researchers identified cells with high metastatic potential; those expressing clusters of differentiation, CD24+ and CD133+ [60]. The development of metastatic niches often signifies a significant progression in the tumor stage, and studies have linked CTC characteristics, such as the presence of CTC clusters, to increased metastatic potential, aiding in the identification of patients at higher risk [61,62,63]. In metastatic breast cancer, a CTC count ≥ 5 in 7.5 mL of blood correlates with worse overall survival and progression-free survival [40]. Indeed, a CTC count of less than five in patients with stage IV breast cancer is used to classify the tumor as stage IV indolent, whereas a CTC count greater than five classifies the tumor as stage IV aggressive [40]. CTC clusters exhibit stemness characteristics and can evade the immune system by recruiting immunosuppressive cells [64]. This attribute helps prevent CTCs from being attacked by antitumor immune cells like natural killer (NK) cells, thereby increasing their metastatic potential [64,65,66]. In circulation, CTCs are protected from shear forces and shielded from immune detection through interactions with platelets [67]. Other blood cells, like macrophages, are able to interact directly with CTCs to protect them from being phagocytosed [67]. Szczerba et al. also identified and associated CTC–neutrophil interactions with cell cycle progression, leading to more efficient metastasis formation [68]. Using a mass spectrometry-based untargeted metabolomics approach, human colorectal cancer CTC-derived cells were shown to have low or high metastatic potential based on metabolic features [69]. A combination of metabolites, such as glutamic acid, malic acid, lactic acid, and aspartic acid, along with higher CTC counts, positively predicted the metastatic risk in patients, providing evidence of the influence of metabolic phenotype on the metastatic potential of cells [69]. Recently, CTCs were shown to have unexpectedly high levels of OXPHOS compared to glycolytic signatures [70]. This metabolic reprogramming was the opposite of the common “Warburg Effect” seen in metastatic cancer cells, suggesting an additional layer of regulative complexities in cancer metastasis [70]. Metabolic reprogramming of CTCs enables them to survive harsh conditions in the bloodstream and enhances their ability to establish a favorable microenvironment for metastasis, known as metastatic niches [71]. The molecular mechanisms by which CTCs influence the pre-metastatic niche (PMN), prepare distant organs for colonization, and contribute to the metastatic process are yet to be fully understood. However, CTCs acquire enhanced migratory and invasive capabilities when undergoing epithelial–mesenchymal transition (EMT) [72]. Recent discoveries have elucidated the dynamic nature of EMT in CTCs, identifying hybrid epithelial/mesenchymal states that may contribute to metastatic progression [38]. For instance, the presence of both epithelial and mesenchymal markers indicates the occurrence of intrahepatic metastasis, while the presence of mesenchymal phenotypes prompts the development of extrahepatic metastasis [38]. Expression of mesenchymal markers like N-cadherin, vimentin, snail, and slug have also been detected in CTCs, highlighting their use in metastasis prediction [73,74]. Using CTC-based information to assess the risk of metastasis will help implement more aggressive treatment strategies for patients with a higher likelihood of developing metastatic disease.

2.5. Treatment Response Monitoring

Changes in CTC counts and characteristics during treatment can indicate treatment response or resistance [41]. Real-time monitoring of CTC dynamics will allow for timely adjustments to therapeutic strategies. To monitor patient response to therapy, longitudinal tissue biopsies must be collected. However, this procedure is often invasive and complicated by the location and size of tumors [75]. Therefore, CTCs can serve as dynamic biomarkers for monitoring treatment response and assessing the efficacy of therapies. Indeed, CTCs from patients with either chemosensitive or chemorefractory SCLC were tumorigenic in immune-compromised mice, and their resultant CTC-derived explants mirrored the donor patients’ response to platinum and etoposide chemotherapy [76]. Molecular alterations that affect a tumor cell’s response to specific drugs can also be determined through molecular profiling of CTCs. For example, the expression level of cyclin D1 (CCND1) was shown to be significantly reduced in patients with head and neck squamous cell carcinoma (HNSCC) following nivolumab treatment [77]. In contrast, the expression of NANOG increased significantly [77]. Changes in CTC count or specific genetic alterations can, thus, indicate whether a treatment effectively targets the tumor, enabling timely adjustments to the therapeutic approach.

2.6. Minimal Residual Disease Monitoring

CTCs can be used to monitor minimal residual disease (MRD) after surgery or other treatments, helping identify potential disease recurrence early. Li and colleagues used preoperative CTC concentration to predict postoperative recurrence or metastasis in patients with NSCLC [78]. Detection of CTCs pre- and post-adjuvant chemotherapy can also serve as prognostic indicators of early relapse [34]. These indicators allow for investigations into novel therapeutic approaches to curb relapse and drug resistance. CTC-based MRD monitoring has also been explored as a valuable tool in post-treatment surveillance, offering insights into the effectiveness of interventions and informing decisions regarding additional therapies [79]. CTCs can enter a state of dormancy, temporarily evading the immune system and therapeutic interventions [80,81]. Recent studies have shed light on the mechanisms governing CTC dormancy and the factors that lead to their reactivation, contributing to a deeper understanding of cancer relapse [82,83,84]. Molecular characterization of CTCs can also help identify and analyze drug-tolerant clones within the tumor microenvironment (TME) [85].

2.7. Personalized Medicine

Precision oncology aims to treat patients according to the molecular characteristics of their tumors, adjusting these treatment strategies as the tumors evolve [86]. Molecular characterization of CTCs contributes to identifying actionable mutations and potential therapeutic targets. Whole exome sequencing (WES) of patient CTC samples has been shown to reflect the genomic characteristics of their corresponding solid tumors more accurately [87,88,89]. This genomic information can be crucial in developing personalized treatment plans. Functional mutations in driver genes like EGFR, KRAS, and TP53 can be determined quickly and used to stratify patients for therapy [89]. Mutational characterization of CTCs can also help physicians decipher if and when a patient is developing resistance to a particular chemotherapeutic agent, thereby allowing for proactive treatment decisions [90]. In this regard, CTC-based liquid biopsies facilitate the development of personalized treatment plans, allowing for the selection of targeted therapies based on the specific genetic profile of the tumor. Furthermore, CTC-based liquid biopsies are increasingly integrated into clinical trials and treatment decision-making.

5.1. Polymerase Chain Reaction (PCR)

Liquid biopsies contain CTCs and other tumor-derived materials shed into the bloodstream, such as circulating tumor nucleic acids, including DNA (ctDNA), RNA (ctRNA), exosomes, and other microvesicles [145,146,147]. ctDNA, derived from apoptotic or necrotic tumor cells and CTCs, can be used to predict changes to therapeutic response [148]. The FDA approved the Cobas EGFR mutational test for the management of therapy in lung cancer [149]. This was a result of the detection and mutational testing (Cobas EGFR mutation test) of ctDNA from NSCLC patients, which showed the importance of ctDNA as a biomarker in cancer diagnosis and prognosis [150,151]. Different types of PCR methods have been developed with the aim of detecting and characterizing CTCs and ctDNA [152,153,154,155]. These methods continue to be improved to increase sensitivity and allow for accurate and quantitative analyses of CTCs [111]. The development of droplet digital PCR (ddPCR) has allowed for the partitioning of a sample into many “droplets,” enabling the amplification of rare mutations [153,156]. The ddPCR method offers several advantages over conventional quantitative and real-time PCR [157,158,159,160]. It has improved sensitivity [158], is less susceptible to PCR inhibitors [157], and allows for absolute quantification without the need for an external calibration curve [160]. CTCs can also be quantified independently of nucleic acid extraction using real-time quantitative PCR (Q-PCR) [155]. In the article by Mei and colleagues, CTCs were isolated using tag-DNA-modified CK19 antibody and magnetic beads conjugated with EpCAM antibody. They reported a detection rate of 92.3% in the clinical tumor blood samples, and by quantifying the tag-DNA that had immobilized on the tumor cells, they showed a correlation between CTC counts and tumor stage/status [155]. As PCR methods improve, single-cell and next-generation sequencing can be integrated to enhance CTC characterization and their roles in cancer.

5.2. Single-Cell Analysis

Genomic and phenotypic characteristics of cells differ within a patient’s tumor (intratumor heterogeneity) and between tumors of the same type (intertumor heterogeneity) [161]. These heterogeneous differences contribute to treatment failure and disease recurrence, as there is no one-size-fits-all treatment approach [85]. Evidence has shown that CTCs detected in patients represent an array of cell states with varying genetic and phenotypic profiles [97,162]. Therefore, advanced technologies like single-cell RNA sequencing (scRNA-seq), single-cell protein analysis, and imaging techniques are needed [163]. These techniques allow for detailed molecular and phenotypic characterization with the potential to reveal deep insights into intratumor heterogeneity and cellular plasticity and help identify pathways activated in different cell states, details often masked by profiling pooled cells [163]. Traditional methods of CTC analyses have targeted the use of epithelial biomarkers, whose expression may not be universal across all tumors [120]. Recent improvements in single-cell analysis have focused on enhancing sensitivity, reducing technical variabilities, increasing throughput, and upgrading data analysis tools [164,165,166]. Upgrades in single-cell analysis packages, such as Seurat and Uniform Manifold Approximation and Projection (UMAP), have enabled better clustering analysis and classification of CTCs into multiple subtypes [167,168]. Single-cell sequencing analysis of CTCs from SCLC patients showed a global increase in intratumoral heterogeneity (ITH), including heterogeneous expression of potential therapeutic resistance pathways, like EMT, between different cellular subpopulations following treatment resistance [48]. Indeed, serial profiling of the CTCs post-relapse confirmed increased ITH, suggesting that treatment resistance was characterized by coexisting subpopulations of cells with heterogeneous gene expression, leading to multiple concurrent resistance mechanisms [48]. This finding effectively highlights the need for clinical efforts targeted at developing combination therapies for treatment-naïve SCLC tumors in order to increase initial response and counteract the emergence of ITH and diverse resistance mechanisms [48]. Another analysis of prostate CTCs revealed heterogeneity in signaling pathways like non-canonical Wnt signaling that could contribute to treatment failure or therapeutic resistance (antiandrogen resistance) [169]. By integrating single-cell and batch RNA sequencing, Zhang et al. found gene markers associated with CD8⁺ T cell infiltration (LGR5, CCR7, STC2, DEFB1, TYK2, SCARB1, AICDA, and ULBP2) in HNSCC, which can serve as predictors of disease prognosis and clinical treatment indicators [170]. These findings may change the way cancer patients are staged and risk-stratified and provide new prognostic approaches for the identification of targeted therapy and resistance mechanisms.

5.3. Next-Generation Sequencing (NGS)

High-throughput sequencing of CTC-derived DNA or RNA can allow for a comprehensive genomic and transcriptomic analysis to detect heterogeneous and shared mutational signatures within and between different cancer types [171,172]. This could provide better insight into a patient’s genetic makeup, which in turn can guide clinicians for better disease management. The challenges in sequencing the CTC genome and transcriptome include low abundance in the bloodstream, making their isolation difficult [173], significant genetic heterogeneity compared to the primary tumor, which can affect the capture of the full spectrum of mutations present [15], and the need for sophisticated bioinformatics tools and computational resources for data analysis and interpretation [174]. However, improvements in the isolation and capture of CTCs, the ease of use of different analytical tools, and the removal of biases introduced during sample and sequencing library preparation are increasing the possibility of detecting rare mutations in CTCs [175,176]. By targeting mutational hotspots, a combination of whole-genome amplification, PCR, and Sanger sequencing was used to examine point mutations in the KRAS, BRAF, and PIK3CA genes in CTCs of patients with CRC. The authors detected single-cell mutations in the genes. Interestingly, these mutations were not found in the corresponding tumors [177]. Gkountela and colleagues conducted a comparative analysis of the methylation landscape of single CTCs and CTC clusters from breast cancer patients and mouse models to reveal similarity patterns to embryonic stem cells and identified pharmacological agents that can target clustering, blunt metastasis spreading, and suppress stemness [61]. They observed hypomethylation in the binding sites for OCT4, NANOG, SOX2, and SIN3A of CTC clusters, similar to embryonic stem cells, and identified an FDA-approved Na⁺/P⁺ ATPase inhibitor that enabled the dissociation of CTC clusters into single cells. Thus, they established a link between specific DNA methylation changes and the promotion of cancer stemness and metastasis and pointed to cluster-targeting compounds to suppress the spread of cancer [61]. In a study investigating somatic mutations present in CTCs from colorectal cancer patients, the frequencies of somatic mutations present in the CTCs correlated with prognostic markers and resembled mutational signatures present in the primary tumor [178]. These findings have resulted from significant improvements in the isolation and enrichment of CTCs and efficient whole-genome amplification (WGA) and NGS workflows that reduce bias with improving coverage, sensitivity, and specificity [179,180]. As more targeted cancer panels become increasingly available, the possibility of detecting more actionable mutations will increase, with lower costs and minimal requirements for specialized equipment [181].

5.4. In Situ Analysis

Techniques that enable in situ analysis of CTCs directly within the bloodstream or in patient-derived samples provide a real-time understanding of their behavior. The advantage of in situ analysis is that challenges with traditional CTC isolation methods, which compromise CTC integrity, are avoided. These approaches also eliminate potential biases introduced by ex vivo isolation and culture, offering a more accurate representation of CTC biology. CellCollector CANCER01 (DC01) is an approach developed for the in vivo isolation of CTCs from the peripheral blood of cancer patients [182]. The DC01 device enables in vivo isolation and enumeration of CTCs by capturing EpCAM-positive CTCs through a detector placed in the peripheral vein of cancer patients via a cannula [183]. This device has been shown to be tolerated for 30 min in vivo by patients without any side effects [184]. In a study evaluating the feasibility of CTC detection and monitoring in high-risk non-metastatic prostate cancer (PCa) patients undergoing radiotherapy, the authors show that CTCs could be detected before and after radiotherapy using the DC01 device in vivo [184]. Figure 2a below shows images of the captured CTCs. The CTCs were positive for pan-cytokeratin (pan-CK; green) and negative for CD45-red (Figure 2a). This study used the human prostate cancer cell line LNCAP as a positive control (Figure 2b), with non-specific binding lymphocytes as an internal negative control (Figure 2b,c). Three CTC clusters, each containing 2–3 CTCs, were detected in samples from two patients, with total CTC counts of 10 and 15, respectively (Figure 2d).

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Figure 2

Circulating tumor cells (CTCs) and CTC clusters were detected by the DC01 device in patients with high-risk non-metastatic prostate cancer (PCa). (a) Micrographs of five CTCs on DC01 detected from three patients; CTCs were defined as being positive for nucleic staining and pan-CK (pan-cytokeratin) and negative for CD45 by immunofluorescence staining (DNA (blue) and pan-CK (green)). Scale bar: 20 μm. (b) Images of control samples for CTC staining panel, upper panel: LNCaP cells captured on DC01 as positive controls for the CTC staining panel by immunofluorescence staining (DNA (blue) and pan-CK (green)); lower panel: leukocytes attached to DC01 served as negative controls for the CTC staining panel by immunofluorescence staining (DNA (blue) and CD45 (red)). Scale bar: 20 μm. (c) Scanning electron microscope image showing the surface of DC01 and blood components, including unspecific binding of leucocytes onto DC01. Scale bar (from left to right): 90 μm, 30 μm, and 9 μm. (d) Three CTC clusters on DC01 detected from two patients; CTC clusters were found as a cluster of CTCs being positive for nucleic staining and pan-CK and negative for CD45 by immunofluorescence staining (DNA (blue) and pan-CK (green)). All CTCs were negative for PSA, so this channel is not shown. Exposure time for each channel: nucleus DNA, 800~1000 ms; pan-CK, 3000 ms; CD45, 6000 ms. Scale bar: 20 μm. Source: Reprinted from [184] under an open-access Creative Commons CC BY 4.0 license.

In the medical community, simple, easy, and sensitive methods to monitor tumor growth are essential for patient care [185]. These may come in the form of improvements or modifications to existing technology, allowing for economical and effective characterization of CTCs. For instance, confocal line scanning, which can be implemented in any confocal microscope system, helped detect CTCs and CTC clusters in vivo in the blood vessels of live mice [186]. Kuo and colleagues also used multi-photon microscopy and antibody-conjugated quantum dots to image CTCs in real-time in living animals [60]. They detected different subpopulations of CTCs, especially those with high metastatic potential—CD24⁺ and CD133⁺ CTCs [60]. These simple and direct noninvasive strategies are needed to detect and investigate the mechanistic underpinnings of tumor metastasis and functionally characterize CTCs.