Clinical and translational roles of circulating tumor cells in non-small cell and small cell lung cancer: a narrative review

Abstract

Background and Objective

Circulating tumor cells (CTCs) are malignant cells shed into blood that enable noninvasive, longitudinal assessment of lung cancer. Increasing evidence frames CTCs within a circulating tumor microenvironment (cTME) and broader circulating tumor-associated cell (CTAC) ecosystems that include multicellular clusters and circulating tumor endothelial cells (CTECs). We summarize definitions, detection approaches, and clinical applications of CTC-centered liquid biopsy in non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC).

Methods

A comprehensive literature search was conducted in PubMed, Embase, Web of Science, and Google Scholar using the terms “non-small cell lung cancer”, “small cell lung cancer”, and “circulating tumor cells”. Relevant clinical, basic, and translational studies were selected and synthesized to outline current knowledge and future directions.

Key Content and Findings

CTCs can be enriched by immunoaffinity, size, or microfluidic platforms, enabling enumeration and downstream profiling. In both NSCLC and SCLC, CTC positivity and higher burden are associated with worse survival, with the strongest effects in SCLC and with circulating tumor emboli (CTE). Serial monitoring provides early signals of response or failure; and post-treatment supports minimal residual disease (MRD) detection and relapse prediction. Molecular and phenotypic profiling enables driver and resistance tracking, including epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), while CTECs may add vascular and immune-relevant information.

Conclusions

CTC-based assays have the potential to complement imaging and tissue biopsy across screening research, prognostication, therapeutic monitoring, MRD assessment, and personalized care. Clinical translation requires standardized preanalytical workflows, harmonized thresholds, and prospective trials testing CTC-guided management.

Introduction

Circulating tumor cells (CTCs) are cancer cells that detach from primary or metastatic lesions and enter the bloodstream, functioning as a liquid biopsy that can be sampled noninvasively (1-3). During hematogenous transit, CTC survival and metastatic competence are shaped by a dynamic circulating tumor microenvironment (cTME) that includes biophysical forces, platelet interactions, immune surveillance, endothelial interfaces, soluble mediators, and extracellular vesicles (EVs) that collectively influence immune evasion and dissemination efficiency (4-6). In parallel, circulating tumor-associated cells (CTACs) extend the analytic focus beyond isolated CTCs to tumor-related cellular populations and heterotypic circulating units that better capture tumor-host interactions in blood (7). This framework is particularly relevant in lung cancer, including non-small cell lung cancer (NSCLC) and small cell lung cancer (SCLC), where dissemination dynamics and treatment contexts differ substantially (8,9).

Methodological advances now support this transition from counting to ecosystem-level characterization. Established enrichment strategies based on biological markers and biophysical properties are increasingly complemented by assays designed to preserve multicellular structures and to recover additional cellular components of the circulating compartment. Circulating tumor endothelial cells (CTECs) represent an aneuploid endothelial lineage population linked to tumor neovascularization and metastatic progression, and they provide a vascular-focused cellular readout that is not captured by CTC counts alone (10). In advanced NSCLC, programmed death ligand 1 (PD-L1) positive aneuploid CTECs have been reported in association with resistance to checkpoint blockade immunotherapy, supporting their potential relevance to immune checkpoint inhibitor (ICI) monitoring (11). More broadly, the field is moving toward integrated liquid biopsy strategies that combine cellular analytes with circulating tumor deoxyribonucleic acid (ctDNA), and EVs, to obtain a more complete and actionable profile of disease biology (4,12-14).

This review synthesizes findings from basic, clinical, and translational studies on CTC applications across various stages of lung cancer management. We begin with early detection, then evaluate prognostic significance in NSCLC and SCLC, then assess monitoring of treatment response, detection of minimal residual disease (MRD) and prediction of relapse, and finally the use of CTC analysis to guide personalized therapy. Throughout, we highlight the strengths and limitations of current assays, sources of variability that affect interpretation, and practical considerations for implementation in real-world practice. We present this article in accordance with the Narrative Review reporting checklist (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-1-0025/rc).

Methods

A narrative review of the literature was conducted using a search of PubMed, Embase, Web of Science, and Google Scholar using a combination of the terms: “non-small cell lung cancer”, “small cell lung cancer”, and “circulating tumor cells” with Boolean operators AND/OR. The search was initially performed on 30 September 2025 and updated on February 28, 2026, covering all years from database inception up to this date. We included English articles reporting CTCs in NSCLC and SCLC. We excluded editorials or letters without original data. See Table 1 for the search strategy summary.

Table 1. Summary of the search strategy.

Items	Specification
Date of search	30 September 2025; February 28, 2026
Databases and other sources searched	PubMed, Embase, Web of Science and Google Scholar
Search terms used	“non-small cell lung cancer”, “small cell lung cancer”, “lung cancer”, and “circulating tumor cells”, “recurrence”, “survival” and “outcomes”
Timeframe	From database inception to February 28, 2026
Inclusion and exclusion criteria	Inclusion: original studies, clinical trials, and review articles in English. Exclusion: conference abstracts without full text, editorials, letters, and non-English publications
Selection process	W.L., A.T.C.C., and J.W.Y.C. independently screened titles and abstracts, followed by full-text review. Discrepancies were resolved through discussion and consensus with C.S.H.N.

Definition, source and testing of CTCs

Early studies defined CTCs as rare tumor cells that circulate among billions of normal blood cells, and some of them can seed metastases at distant organs (15). Contemporary evidence emphasizes that the fate of CTCs in circulation is shaped by the cTME, a flowing and time-varying milieu that modulates mechanical stress tolerance, immune escape, and vascular interactions during transit (4,5). Within this view, CTC-based liquid biopsy increasingly intersects with the broader category of CTACs, which captures tumor-related cellular populations and heterotypic circulating units that reflect tumor-host interplay in blood (7). CTECs constitute a notable component of this landscape as an aneuploid endothelial lineage population implicated in neovascularization and metastatic progression (10).

CTCs arise when cancer cells escape the primary tumor microenvironment, cross the endothelial barrier or lymphatic system and enter the circulation; because of shear stress and immune surveillance, their numbers rarely exceed a few cells per millilitre of blood (16). They are heterogeneous: CTCs may originate from the primary lesion or metastatic deposits, they can exist as single cells or clusters and may display epithelial, mesenchymal, or hybrid phenotypes (17,18). Although sparse, often fewer than ten cells per milliliter (19), their presence is clinically significant: numerous studies have linked CTCs to disease progression, recurrence and poor prognosis (20-22). CTCs are increasingly used to monitor treatment response, predict relapse and guide precision therapy (23). In solid tumors, the source of CTCs can be multifaceted, and the term CTC is generally used in this context rather than for hematologic malignancies in which malignant cells are inherently circulating. Cancer cells may enter the circulation by active intravasation, during which epithelial cells undergo epithelial-mesenchymal transition (EMT) to acquire mobility, detach from the tumour mass and invade blood vessels (24). They can also be shed passively into the bloodstream when tumour vasculature is compromised, or they may intravasate through lymphatic vessels that eventually drain into the thoracic duct (25,26). CTCs can be found as single cells or as multicellular clusters, which are also described as circulating tumor emboli (CTE). These clustered circulating units often interact with platelets and immune cells to form protective thrombi that shield them from shear stress and immune attacks and enhance their adhesion and extravasation (4,27-29). CTC clusters have substantially higher metastatic potential than single CTCs in experimental and clinical studies (30). In clinical cohorts, clusters have commonly been operationally defined as three or more contiguous tumor cells in circulation, and their detection has been associated with adverse outcomes (31,32). Metastasis models suggest at least two waves of dissemination: cells may spread directly from the primary tumour to blood or lymph nodes, and later CTCs released from established metastases can seed secondary or tertiary lesions (33,34). Tumor-derived factors and stromal interactions support intravasation and survival in circulation. Most CTCs perish quickly under mechanical and immune pressures, but a minority survive, undergo mesenchymal to epithelial transition, and extravasate to become disseminated tumor cells at distant organs (35-37). CTCs have been detected not only in peripheral blood but also in malignant pleural or peritoneal effusions and cerebrospinal fluid, indicating that different body fluids may serve as reservoirs for these cells (38,39). Understanding these origins and routes underscores the dynamic and heterogeneous nature of CTC dissemination, which varies according to tumour biology, vascular integrity and microenvironmental interactions.

Because circulating analytes are rare and heterogeneous, testing typically involves an enrichment step followed by detection and molecular characterization, and each approach entails trade-offs in capture efficiency, purity, and phenotypic coverage; these methods and their principal advantages and limitations are summarized in Table 2. Existing methods exploit either biological properties, such as cell-surface markers, or biophysical properties, such as size and deformability. Immunoaffinitybased techniques use antibodies or aptamers to capture tumor cells by targeting epithelial markers such as epithelial cell adhesion molecule and cytokeratins. Examples include the CellSearch system cleared by the United States Food and Drug Administration and platforms that use positive selection or leukocyte depletion for negative selection (40,41). Size-based and morphology-based methods rely on the larger size and lower deformability of many CTCs to filter or separate them for cytologic or molecular analysis (42-44). Microfluidic technologies combine these principles in miniature devices with spiral channels, herringbone structures, or vortex traps that enrich rare circulating populations by inertial focusing, deterministic lateral displacement, or label-free hydrodynamic separation (22,46,47). Detection after enrichment may involve immunocytochemistry, fluorescence in situ hybridization (FISH), flow cytometry, nucleic‑acid amplification or nextgeneration sequencing to enumerate cells and interrogate their genetic or phenotypic features (48-50). More recently, an immunocytology and glass slide-based workflow has been developed that enables both microscopic CTC enumeration and downstream epidermal growth factor receptor (EGFR) mutation testing by digital polymerase chain reaction (dPCR) using deoxyribonucleic acid (DNA) extracted from slide-mounted CTCs, supporting a practical hospital laboratory pipeline (51). Emerging assays use nanomaterials, surfaceenhanced Raman scattering, electrochemical sensors and quantum dots to improve sensitivity and enable multiplexed analyses (52-55).

Table 2. Summary of enrichment and detection methods for CTACs, including CTCs and CTECs.

Stage	Method category	Principle and typical targets	Representative examples	Main advantages	Main limitations
Enrichment	Immunoaffinity positive selection	Antibody or aptamer capture using epithelial markers such as EpCAM and cytokeratins	CellSearch system and other EpCAM based platforms (3,40,41)	High specificity for epithelial CTCs, some workflows are standardized, compatible with downstream staining and enumeration	May miss CTCs with low epithelial marker expression after epithelial to mesenchymal transition including EMT-related phenotypes, marker heterogeneity reduces sensitivity
	Immunoaffinity negative selection	Leukocyte depletion, commonly via CD45, enriches remaining non leukocyte fraction	CD45 depletion-based workflows (40,41)	Less dependent on epithelial markers, may retain broader CTC phenotypes	Purity can be limited by residual leukocytes, risk of CTC loss during depletion steps, downstream identification can be labor intensive
	Size based and morphology-based filtration	Physical retention based on larger size and lower deformability of CTCs	ISET filtration, membrane filtration devices, microelectromechanical filters (42-45)	Label free enrichment that can capture epithelial and non-epithelial phenotypes, preserves morphology for cytology and some molecular tests	May miss small CTCs below 5 micrometers and highly deformable phenotypes, clogging and variable recovery, purity may be limited by co captured blood cells
	Microfluidic label free separation	Hydrodynamic or inertial effects separate cells without markers	Spiral channels, deterministic lateral displacement, vortex traps (22,46,47)	Gentle processing that may preserve viability, scalable throughput, captures marker low phenotypes	Requires specialized devices and expertise, performance varies by device design and sample quality, purity may still require additional steps
	Microfluidic immunocapture	Antibody coated microstructures increase contact and capture efficiency	Herringbone structures with antibody capture (22,46,47)	High contact efficiency, integrates capture and processing in compact systems	Still marker dependent, surface binding may affect viability, limited standardization across platforms
Detection and characterization	Immunocytochemistry	Staining for tumor markers with leukocyte exclusion for identification and enumeration	Cytokeratin and DAPI staining with CD45 exclusion (48-50)	Direct visualization, supports phenotyping, compatible with routine microscopy	Marker dependence, interpretation variability, limited multiplexing
	FISH	Single cell detection of genomic alterations	Rearrangement and copy number testing on enriched CTCs (48-50)	Single cell resolution, useful for fusions and copy number, actionable alterations in selected settings	Labor intensive, limited targets per assay, requires intact cells and expertise
	Aneuploidy based imaging FISH for CTC and CTEC	Co-detect aneuploid CTC and CTEC with immunostaining	SE iFISH based detection of aneuploid CTCs and CTECs, including PD-L1 and vimentin phenotyping (10,11)	Captures EpCAM low phenotypes and includes CTEC	Standardization and expertise dependent
	Flow cytometry	Multiparameter fluorescence based rare event detection	Antibody panel-based CTC enumeration (48-50)	High throughput, quantitative phenotyping	Rare event gating is challenging, background interference, requires robust marker panels
	RT PCR	Amplification of tumor associated transcripts	Transcript based detection assays (48-50)	High analytical sensitivity	Susceptible to contamination, transcript variability, limited morphological confirmation
	Next generation sequencing	Bulk or single cell DNA or RNA profiling of enriched CTCs	Targeted panels, single cell sequencing (48-50)	Enables genotyping, heterogeneity and resistance assessment	Requires adequate cell number and quality, higher cost and complexity, potential amplification bias in single cell workflows
	Immunocytology plus dPCR	Slide based enumeration with targeted EGFR testing	Immunocytology based platform with dPCR for EGFR mutation testing (51)	Combines counting and EGFR mutation testing	Targeted variants only, false negatives possible
	Nanomaterial enabled assays	Nanomaterials enhance capture, signal, or multiplexed readouts	Nanomaterial capture and sensing platforms (52-55)	Potentially higher sensitivity and multiplexing	Limited standardization, variable reproducibility, clinical validation still evolving
	SERS, electrochemical sensors, quantum dots	Optical or electrical signal amplification for sensitive detection	SERS assays, electrochemical sensors, quantum dot labeling (52-55)	High sensitivity, multiplex capability	Specialized instrumentation, limited clinical standardization, workflow dependent performance
Cross cutting	Assay performance metrics	Capture efficiency, purity, detection limit, throughput, biocompatibility	Comparative evaluations across platforms (56)	Supports method selection and interpretation	Trade-offs across metrics, limited head-to-head clinical utility comparisons

CTAC, circulating tumor associated cells; CTC, circulating tumor cell; CTEC, circulating tumor endothelial cell; DAPI, 4’,6 diamidino 2 phenylindole; dPCR, digital polymerase chain reaction; EGFR, epidermal growth factor receptor; EMT, epithelial to mesenchymal transition; EpCAM, epithelial cell adhesion molecule; FISH, fluorescence in situ hybridization; iFISH, imaging fluorescence in situ hybridization; ISET, isolation by size of epithelial tumor cells; NGS, next generation sequencing; PD-L1, programmed death ligand 1; RT-PCR, reverse transcription polymerase chain reaction; SERS, surface enhanced Raman scattering; SE iFISH, subtraction enrichment and immunostaining fluorescence in situ hybridization.

Beyond single-cell enumeration, increasing attention is directed toward recovering multicellular structures and additional circulating cellular populations that reflect vascular and immune biology. CTECs provide a cellular window into tumor-associated angiogenesis and vascular remodeling, and they have been proposed as complementary biomarkers alongside CTCs for disease monitoring and risk stratification (10). These developments align with a broader move toward integrated liquid biopsy strategies that combine cellular and acellular analytes to improve clinical interpretability and actionability (4,12).

Method selection also introduces technological blind spots with clinical implications. Marker-dependent capture can under-recover epithelial marker low populations, including cells that have undergone EMT and adopt hybrid phenotypes, which may be enriched among metastasis competent and treatment resistant subsets (3,57). Size-based enrichment can similarly bias recovery by depleting very small CTCs, including sub-five-micrometer populations that were historically discarded but are increasingly reported in contemporary cytology and aneuploidy-based workflows (45). These considerations support a shift from single modality enrichment toward complementary, phenotype-inclusive strategies when assays are intended for clinical risk stratification or longitudinal monitoring rather than enumeration alone (3). Critical performance metrics for any CTC assay include capture efficiency, purity, detection limit, throughput and biocompatibility, and different approaches trade off between these parameters (56). Together, these testing strategies allow clinicians to isolate and characterize CTCs for prognostic evaluation, therapy monitoring and exploration of tumour heterogeneity.

Early detection and screening

Detecting lung cancer at an early stage substantially improves survival, yet current screening with low-dose computed tomography (CT) has important limitations, including high false positive rates. CTCs have been explored as a complementary biomarker for early lung cancer detection in high-risk populations. Notably, a landmark prospective study by Ilie et al. identified “sentinel” CTCs in 3% of asymptomatic chronic obstructive pulmonary disease (COPD) patients (5 of 168) who had no radiologic evidence of cancer at baseline. Remarkably, all CTC-positive patients developed lung nodules visible on annual CT scans within 1–4 years, and were diagnosed with early-stage lung cancer (58). This suggests CTCs can precede imaging detection of lung tumors, potentially serving as an early warning sign. The AIR project in France prospectively evaluated CTCs in heavy smokers undergoing annual CT screening. The trial protocol has been published, and the results showed that CTC detection was associated with a higher likelihood of cancer detection during screening follow-up. Combining CTC status with CT findings also improved the positive predictive value of screening (23,59). They reported that integrating CTC analysis could enhance lung cancer screening, especially in COPD patients who are at elevated risk. These findings underscore a potential role for CTCs in early detection: a blood test for CTCs might identify high-risk individuals who warrant closer surveillance or intervention even before a tumor is visible by imaging. However, challenges remain, as early-stage lung cancers shed very few CTCs (60). Sensitive technologies, for example, isolation by size or microfluidic enrichment, are required to capture rare cells. Specificity is also crucial. A small fraction of individuals with COPD had cells with CTC-like features that required careful validation to confirm malignancy (61).

Prognostic significance of CTCs in NSCLC and SCLC

To contextualize the prognostic evidence across NSCLC and SCLC, we synthesize representative studies, including study design, CTC thresholds, and associated clinical outcomes, in Table 3. CTC enumeration has strong prognostic value in lung cancer, as shown by numerous studies and meta-analyses. In general, the presence of CTCs or higher CTC counts correlates with worse outcomes in both NSCLC and SCLC (57,64,68). A 2022 meta-analysis by Jin et al. pooled 27 studies with 2,957 patients and found that detection of CTCs was associated with significantly shorter overall survival (OS) in lung cancer [hazard ratio (HR) 2.51, 95% confidence interval (CI): 2.06–3.05]. The effect was particularly pronounced in SCLC, where CTC-positive SCLC patients had more than three-fold higher risk of death compared to CTC-negative (HR for OS 3.11, 95% CI: 2.59–3.73). NSCLC patients also showed worse survival (HR 2.11, 95% CI: 1.63–2.73) if CTCs were detectable, though the HRs were somewhat lower than in SCLC (57). These consistent findings establish CTC count as an independent prognostic biomarker in lung cancer.

Table 3. Key prognostic studies of CTCs in lung cancer and associated clinical outcomes.

Study	Design	Population and setting	Assay and sampling	CTC definition or threshold	Main prognostic findings
					OS, months	PFS, months
Jin et al., 2022 (57)	Meta-analysis	NSCLC and SCLC, 27 studies, 2,957 patients	Across included studies	CTC detectable versus not detectable	HR =2.51, 95% CI: 2.06–3.05, P<0.01	HR =2.66, 95% CI: 2.10–3.37, P<0.01
		SCLC	Across included studies	CTC detectable versus not detectable	HR =3.11, 95% CI: 2.59–3.73	NA
		NSCLC	Across included studies	CTC detectable versus not detectable	HR =2.11, 95% CI: 1.63–2.73, P<0.05	NA
Krebs et al., 2011 (62)	Single-center prospective study	Stage III or IV NSCLC both before and after administration of one cycle of standard chemotherapy	CellSearch, peripheral blood	Fewer than five CTCs in 7.5 mL of blood compared with five or more CTCs before chemotherapy	8.1 vs. 4.3, P<0.001	6.8 vs. 2.4, P<0.001
Punnoose et al., 2012 (63)	Single-arm phase II clinical trial	NSCLC treated with erlotinib and pertuzumab	CellSearch, peripheral blood	Clearance or reduction during therapy versus persistently high	NA	Patients who cleared or reduced CTCs during therapy had better DFS than those with persistently high counts, P=0.050
Crosbie et al., 2016 (31)	Single-center prospective study	Stage I to IIIA NSCLC undergoing a curative-intent operation	CellSearch, pulmonary vein blood	≥18 CTCs per 7.5 mL of blood versus <18 CTCs per 7.5 mL of blood	High CTC detection was associated with reduced OS, P=0.055	Any peripheral CTC detection was associated with reduced DFS, P=0.08
			CellSearch, peripheral blood	≥1 CTC per 7.5 mL of blood versus not detectable	Any CTC detection was associated with reduced OS, P=0.04	Any CTC detection was associated with reduced DFS, P=0.01
				≥1 CTE per 7.5 mL of blood versus not detectable	Any CTE detection was associated with reduced OS, P=0.02	Any CTE detection was associated with reduced DFS, P=0.01
Hou et al., 2012 (32)	Single-center prospective study	SCLC receiving chemotherapy	CellSearch, peripheral blood	≥50 CTCs per 7.5 mL of blood versus <50 CTCs per 7.5 mL of blood before chemotherapy	5.4 vs. 11.5, P<0.001	4.6 vs. 8.8, P<0.001
				≥1 CTE per 7.5 mL of blood versus not detectable before chemotherapy	4.3 vs. 10.4, P<0.001	4.6 vs. 8.2, P<0.001
				≥50 CTCs per 7.5 mL of blood versus <50 CTCs per 7.5 mL of blood after one chemotherapy cycle	4.1 versus 10.4, P<0.001	4.1 vs. 9.6, P<0.001
Huang et al., 2013 (64)	Systematic meta-analysis	NSCLC, 20 studies, 1,576 patients	Across included studies	CTC positive versus negative	RR =2.19, 95% CI: 1.53–3.12, P<0.001	RR =2.14, 95% CI: 1.36–3.38, P<0.001
Hiltermann et al., 2012 (65)	Multicenter prospective study	SCLC	CellSearch, peripheral blood	CTCs >215 per 7.5 mL of blood versus <2 CTCs per 7.5 mL of blood	157 vs. 729 days, P<0.001	NA
Tay et al., 2019 (66)	Randomised controlled trial	Limited stage SCLC	CellSearch, peripheral blood	CTCs ≥2 per 7.5 mL of blood versus <2 CTCs per 7.5 mL of blood	15.1 vs. 26.7, P=0.003	10.9 vs. 18.5, P=0.009
				CTCs ≥15 per 7.5 mL of blood versus <15 CTCs per 7.5 mL of blood	5.9 vs. 26.7, P<0.001	5.5 vs. 19.0, P<0.001
				CTCs ≥50 per 7.5 mL of blood versus <50 CTCs per 7.5 mL of blood	8.6 vs. 20.8, P<0.001	6.1 vs. 16.7, P<0.001
Wang et al., 2025 (67)	Single-center prospective, non-interventional study	Limited extensive stage SCLC receiving chemotherapy	Subtraction enrichment and immunostaining-fluorescence in situ hybridization, peripheral blood	CTC-WBC detectable versus not detectable, pre-treatment	20.13 vs. 33.30, P=0.33	NA
				CTC-WBC detectable versus not detectable, post-treatment	23.03 vs. 42.63, P=0.62	NA
				Triploid CTCs ≥3 per 7.5 mL of blood versus <3 CTCs per 7.5 mL of blood, post-treatment	20.13 vs. 33.30, P=0.44	NA
				Small CTCs ≥3 per 7.5 mL of blood versus <3 CTCs per 7.5 mL of blood, post-treatment	27.79 vs. 23.93, P=0.88	NA
		Extensive stage SCLC receiving chemotherapy		CTC-WBC detectable versus not detectable pre-treatment	9.47 vs. 13.07, P=0.02	NA
				CTC-WBC detectable versus not detectable post-treatment	9.60 vs. 13.13, P=0.03	NA
				Triploid CTCs ≥3 per 7.5 mL of blood versus <3 CTCs per 7.5 mL of blood, post-treatment	11.09 vs. 11.13, P=0.02	NA
				Small CTCs ≥3 per 7.5 mL of blood versus <3 CTCs per 7.5 mL of blood, post-treatment	10.93 vs. 13.13, P=0.01	NA

CI, confidence interval; CTC, circulating tumor cell; CTE, circulating tumor emboli; DFS, disease-free survival; HR, hazard ratio; NA, not applicable; NSCLC, non-small cell lung cancer; OS, overall survival; PFS, progression-free survival; RR, relative risk; SCLC, small cell lung cancer; WBC, white blood cell.

In NSCLC, prognostic studies have involved both early-stage and advanced-stage patients. One influential study by Krebs and colleagues in 2011 used the CellSearch platform to enumerate CTCs in advanced NSCLC patients. They found that having ≥5 CTCs per 7.5 mL blood was associated with significantly worse survival. Patients with high CTC counts had shorter median progression-free survival (PFS) and OS than those with fewer than five CTCs (P<0.001) (62). In a clinical trial cohort treated with erlotinib and pertuzumab, Punnoose and colleagues reported that patients who cleared or reduced CTC counts during therapy achieved better disease-free survival (DFS) than those with persistently high counts (P=0.050), indicating that dynamic CTC change carries prognostic information in addition to baseline burden (63). The sampling site may also influence the measured risk. Blood from the pulmonary vein draining the tumor often contains higher CTC counts than peripheral blood (P=0.002) (31). In a surgical cohort of stage I to III lung cancer, Dejima et al. reported significantly higher CTC levels in pulmonary venous and pulmonary arterial blood than in peripheral blood, accompanied by a greater number of small and large CTC clusters (51). CTE, also termed CTC clusters, represents a clinically relevant organization state in circulation. In prior lung cancer cohorts, clusters have commonly been defined as three or more contiguous tumor cells in a single aggregate (32). The number of pulmonary vein CTCs and CTE were significantly correlated (r=0.51, P=0.002) (31). The presence of CTE, defined as at least one cluster per 7.5 mL of blood, was associated with a significant reduction in DFS (P=0.011) and OS (P=0.024). The detection of any CTCs (≥1 CTC per 7.5 mL of blood) in peripheral blood was associated with reduced DFS (P=0.011) and OS (P=0.037) (31). These observations support the view that prognostic information is carried not only by CTC burden but also by the organization of tumor cells and their interaction patterns in the circulating compartment (4). The prognostic value of early-stage NSCLC continues to be validated. A 2022 systematic meta-analysis of 20 studies with 1,576 patients reported that CTC positivity was linked to shorter PFS and OS, as well as to higher tumor stage and nodal metastasis (64).

SCLC is a high-grade neuroendocrine carcinoma that is typically disseminated at diagnosis, and CTC counts in SCLC tend to be much higher than in NSCLC (8). Extensive-stage SCLC patients often have CTC counts in the hundreds or even thousands, reflecting the vast tumor cell burden (65). Accordingly, prognostic studies in SCLC have shown very strong correlations of CTC number with patient outcomes. In a seminal study, Hou and colleagues reported that SCLC patients with ≥50 CTCs at baseline had significantly shorter survival than those with fewer CTCs (HR 2.45, 95% CI: 1.39–4.30; P=0.002). And the change in the number of CTC after one chemotherapy cycle, and the presence of CTE were reported as independent prognostic factors for SCLC patients receiving chemotherapy (32). These findings are consistent with a cTME-oriented perspective in which clustered circulating structures and tumor host interactions influence dissemination efficiency and clinical outcomes (4).

Any detectable CTCs in SCLC generally indicate poor prognosis, with epithelial CTCs conferring the greatest risk (57). Even in limited stage disease confined to one hemithorax, CTCs can be present. A cut-off of 15 CTCs/7.5 mL has been proposed as an optimal prognostic threshold in limited disease. Patients below that threshold had significantly longer median survival than those above it (66). Another study found that in extensive stage SCLC, patients with small cell CTCs greater than 2 per 6 mL or triploid CTCs greater than 2 per 6 mL after treatment had poorer OS than those below these thresholds (P=0.011 and P=0.018). In both limited- and extensive-stage SCLC, the positive detection of tetraploid CTCs after treatment was associated with lower survival rates (P=0.041 and P=0.049). The presence of CTC-white blood cell (WBC) clusters at baseline and after treatment was significantly associated with poorer OS in extensive stage SCLC (P=0.016 and P=0.028), but not in limited stage SCLC (P=0.355 and P=0.621) (67).

Interestingly, SCLC CTCs frequently form clusters, and their presence portends particularly poor outcomes. Clusters of CTCs exhibit cooperative survival advantages in the circulation and a higher metastatic potential (30,69). Overall, SCLC patients with higher CTC counts or CTC clusters at baseline have poor prognoses, whereas a minority of patients who have no detectable CTCs have favorable prognoses. The prognostic power of CTCs in SCLC is so robust that some have proposed incorporating CTC count into staging or response criteria for clinical trials (70). A plausible biological explanation for the high CTC load in SCLC is intense angiogenesis and vascular leakiness. Hamilton and colleagues observed that tumors shed CTCs profusely through leaky neovasculature, whereas lower microvessel density in NSCLC may limit CTC release (8). In summary, CTC enumeration provides critical prognostic information in lung cancer. A higher CTC count consistently indicates a worse prognosis, with the most extreme effect observed in SCLC.

CTCs for monitoring therapeutic response

Beyond baseline risk stratification, CTCs are valuable as a dynamic biomarker to monitor treatment efficacy in real time. Changes in CTC counts during therapy often correlate with tumor response or progression earlier than traditional imaging. This allows CTCs to serve as an early indicator of whether a therapy is working.

SCLC typically responds dramatically to first-line chemotherapy, but relapse is rapid. CTC kinetics in SCLC can mirror this transient response. In a multicenter study that measured CTCs before, during, and after chemotherapy, counts fell after one cycle in most patients, consistent with tumor reduction (65). The magnitude of decline, and especially the absolute count after the first cycle, was highly prognostic for OS and outperformed radiographic response. Patients whose counts fell to very low levels, including zero, lived longer than those with persistently high post cycle counts. In extensive disease, a reduction greater than 89% after the first cycle predicted a higher probability of radiologic response (71). Another study also found that a reduction in CTCs after the first chemotherapy cycle was associated with a lower risk of death (HR 0.24, 95% CI: 0.09–0.61) (72). By contrast, an absent or minimal decline suggests nonresponse and may warrant early treatment adjustment. Rising counts during or after chemotherapy often anticipate clinical progression. For example, in extensive disease, patients with a rebound in CTCs during treatment had a shorter time to progression than those whose counts remained suppressed (65). Another study also found that the detection of CTC-WBC clusters was associated with a poorer chemotherapy response (P=0.030) (73). In limited disease, higher baseline burden of CD44 variant 6 positive CTCs and CTC-endothelial ratios, as well as the presence of CTC and WBC clusters at baseline, correlated with treatment response and distant metastasis, particularly to the brain, whereas these associations were not observed in extensive disease (74). These findings illustrate that CTC trends act as an early response monitor in SCLC, heralding treatment success or failure ahead of scans. Indeed, persistently high or rising CTCs during therapy signal chemoresistance and impending relapse.

In chemotherapy cohorts, a meta-analysis stratified patients by CTC conversion status. Clearance from positive to negative during treatment was associated with significantly better disease control than persistence of positivity or new positivity. Groups with persistent or newly emergent CTCs had a markedly higher risk of progression than those who became or remained negative, with a relative risk of approximately six to eight (68). This indicates that the disappearance of CTCs on therapy is a favorable sign, whereas the appearance of new CTCs is ominous. In advanced disease treated with EGFR inhibitors or other targeted agents, case reports and small series show that decreases in CTC burden or shifts in CTC morphology coincide with radiographic tumor shrinkage, whereas increases anticipate progression (75). In patients with anaplastic lymphoma kinase (ALK) rearrangement, dynamic changes in a composite CTC score have been proposed as a predictor of response to crizotinib (76,77). CTC trajectories can also provide lead time to recurrence in early-stage settings. In stage I NSCLC treated with stereotactic body radiation therapy, pretreatment CTC positivity followed by post treatment monitoring identified recurrence or progression in advance; post treatment negativity was consistent with disease control (78). Overall, platforms and cut points vary across studies, and standardized thresholds for CTC change in NSCLC have not been established. Despite methodological diversity, the direction of change, falling versus rising, consistently conveys actionable information about treatment efficacy. Tracking CTC counts and phenotypes through therapy enables earlier assessment of response than periodic imaging alone. A sharp decline or clearance is an encouraging sign, whereas persistently high or increasing levels indicate treatment failure and poor prognosis.

In addition to CTC dynamics, circulating endothelial lineage populations may provide complementary information during systemic therapy. CTECs are aneuploid tumor-derived endothelial cells linked to neovascularization and disease progression, and they have been proposed as circulating biomarkers that reflect tumor vascular activity (10). In advanced NSCLC, PD-L1-positive aneuploid CTECs have been reported in association with resistance to checkpoint blockade immunotherapy, suggesting potential relevance for ICI era monitoring and response stratification (11). Further studies are needed to define standardized thresholds and to determine how combined CTC and CTEC trajectories should be integrated with imaging and other liquid biopsy analytes in routine practice.

Detecting MRD and predicting relapse

After definitive therapy such as surgical resection or curative chemoradiation, detecting MRD remains a major challenge because standard imaging often misses microscopic cancer. CTCs, together with ctDNA, are being evaluated as sensitive tools to identify residual disease and to predict relapse before clinical or radiologic evidence appears.

In NSCLC treated with curative intent, multiple studies show that postoperative CTC detection correlates strongly with eventual relapse. In a prospective trial of early-stage disease, CTCs were measured before surgery, immediately after surgery, and on postoperative days 1 and 3. Counts generally declined in the immediate postoperative period, consistent with removal of the source. Patients who showed an early increase within 3 days almost uniformly recurred during follow up, whereas those without a rebound tended to remain disease-free. An increase on days 1 or 3 was a significant predictor of later relapse, supporting the use of CTC testing for MRD detection after surgery (79). Among the 100 patients included in the TRACERx study, 48% were found to have pulmonary venous CTCs. These CTCs are associated with a specific recurrence of lung cancer and remain an independent predictor of recurrence even after adjusting for tumor stage in the multivariate analysis (80). Moreover, a meta-analysis in 2022 aggregated data from 18 studies and found that both pre-operative (HR 2.95, 95% CI: 1.90–4.59; P<0.00001) and post-operative CTC detection (HR 2.73, 95% CI: 1.94–3.85; P<0.00001) predict increased risk of recurrence in resectable NSCLC (81). Even a single detected CTC after surgery may signal residual malignant cells capable of seeding new lesions. Serial surveillance can therefore enable molecular relapse detection months before metastases are visible on CT (82). In one study, patients who had undetectable CTCs after surgery and remained negative during surveillance had very low recurrence rates, whereas those who converted from CTC-negative to positive in follow-up almost invariably relapsed, with CTC positivity preceding radiologic relapse by a median of 5.5 months (83). These findings position CTCs as a cellular MRD marker that complements circulating tumor DNA, which provides genomic evidence.

In SCLC, the surgical pathway is uncommon, but the MRD concept applies to systemic therapy. A complete response on imaging rarely equates to eradication. Persistence of CTCs after initial chemotherapy represents residual disease and is associated with inferior PFS outcomes. A small study showed that both baseline CTC number and the change after the first cycle were significant prognostic factors for PFS survival (84). Clearance may approximate a molecular complete remission, whereas residual CTCs indicate unseen disease.

MRD assessment with CTCs has two practical implications. First, early intervention: patients who remain CTC positive after curative treatment may benefit from adjuvant strategies or closer monitoring, and trials are needed to test whether acting on post treatment CTC status improves outcomes. Second, risk-adapted follow-up: patients who are consistently CTC negative may be monitored less intensively, while CTC-positive patients could undergo more frequent imaging or be prioritized for adjuvant trials. Challenges include a lack of standardized assays and the possibility of false positives immediately after surgery; for example, benign epithelial cells disrupted by operative manipulation may transiently mimic CTCs (61,85). Rigorous confirmation, such as verification of tumor-specific mutations or DNA methylation patterns, improves specificity. When applied carefully, post-treatment CTC detection is a powerful predictor of recurrence and a candidate trigger for adaptive surveillance pathways (86-88).

Guiding personalized therapy with CTC analysis and future directions

One of the most exciting frontiers is the use of CTCs to guide personalized therapy—that is, to tailor treatments based on molecular or phenotypic analysis of CTCs. Because CTCs originate from tumor sites, they can carry actionable information such as gene mutations, receptor status, or drug resistance markers. Obtaining this information from CTCs can help select targeted therapies or understand mechanisms of resistance, all without an invasive tissue biopsy.

In NSCLC, identification of oncogenic drivers such as EGFR mutations and ALK rearrangements is central to treatment selection. CTCs can serve as an alternative source of tumor DNA or ribonucleic acid (RNA) for genotyping. Using a filtration-based FISH assay, Pailler and colleagues detected echinoderm microtubule-associated protein-like 4-ALK rearrangements in CTCs from ALK-positive patients and not in ALK-negative patients, demonstrating that a blood test can identify candidates for ALK inhibitor therapy (89). Longitudinal sampling in that study showed that ALK-positive CTC counts declined with crizotinib and rose at progression, indicating utility for treatment monitoring. Investigators have also detected EGFR mutations, including T790M, in CTCs, informing use of tyrosine kinase inhibitors and the switch to third-generation agents at resistance (90,91). Using dPCR on DNA extracted from pulmonary venous CTCs, Dejima et al. detected EGFR exon 19 deletions and L856R in CTCs and reported concordance with paired tumor tissue, with a sensitivity of 0.75 and specificity of 1.0, albeit with some false negative results (51). Although circulating tumor DNA is widely used for mutation testing, CTC analysis enables single-cell sequencing that can uncover intrapatient heterogeneity in mutations and copy number changes that might be missed in bulk plasma DNA (92,93). For example, CTC-derived RNA has identified ROS1 proto-oncogene, receptor tyrosine kinase fusion transcripts in situations where tissue biopsy was not feasible, enabling successful crizotinib therapy (94,95). When adequate CTCs are captured, concordance between CTC genotypes and tumor tissue genotypes is generally high (96). Thus, CTC genotyping can enable personalized medicine by matching patients to targeted treatments based on real-time molecular status, especially when tumor tissue is unavailable or a repeat biopsy is risky.

Genomic profiling captures actionable targets and specific resistance mutations, yet drug sensitivity also evolves through dynamic and non-genomic mechanisms that may not be predictable from baseline sequencing alone. Functional diagnostics based on viable CTACs have therefore emerged as a complementary strategy for treatment selection and longitudinal resistance surveillance. Chemo-response profiling (CRP) evaluates ex vivo sensitivity and resistance of live CTACs to cytotoxic chemotherapy agent panels, enabling real-time estimation of therapeutic vulnerability in the context of the patient’s current tumor state. In a large clinical study, CRP of CTACs showed high concordance with objective radiologic outcomes, including concordance approaching 97 percent for first-line response in a therapy naïve subset and approximately 87 percent concordance with treatment failure in a blinded subset of pretreated patients with radiologic progression (7). These data suggest that functional profiling can complement static genotyping by identifying emerging resistance phenotypes earlier in the treatment course and by supporting rational selection or de-selection of cytotoxic backbones in combination strategies (14).

Phenotypic profiling further expands clinical utility. Protein expression on CTCs, such as PD-L1 in NSCLC or delta-like ligand 3 in SCLC, can be measured to assess eligibility for targeted or immune therapies, although this remains investigational and requires standardization (97,98). In SCLC, CTC-derived xenografts have been established by implanting patient CTCs into immunocompromised mice. These xenografts preserve genetic and functional features of the donor tumors and mirror clinical drug sensitivity and resistance, enabling individualized drug testing in the laboratory (99-101). While culture of CTCs is technically difficult due to rarity and apoptosis, successful expansion and drug sensitivity assays have been reported in selected cases, supporting the feasibility of a CTC-based functional test to anticipate therapeutic response (102,103).

Tumors evolve under treatment pressure, and serial profiling is often required to track acquired resistance in real time. Serial sequencing of CTCs can reveal emergent resistance mutations, such as ALK kinase domain mutations that mediate resistance to crizotinib or EGFR C797S after osimertinib, before clinical progression. This information can guide the selection of next-generation inhibitors (104,105). However, resistance trajectories also reflect adaptive and non-genomic programs, including phenotype switching and microenvironment-mediated protection, which may not be captured by targeted sequencing alone. In this setting, longitudinal integration of molecular tracking with functional CRP on viable CTACs offers a pragmatic way to monitor dynamic shifts in sensitivity and to anticipate loss of benefit before radiologic progression becomes evident (7,14). Shifts in CTC phenotype, including transitions from epithelial to mesenchymal states, may indicate increased invasiveness and metastatic potential and can suggest changes in therapeutic strategy. In SCLC, many patients develop CTCs with EMT or stem-like features after chemotherapy, which are linked to chemoresistance. Re expression of neuroendocrine and transition markers has been observed at relapse, and co-culture studies suggest that interactions between CTCs and immune cells can promote survival under therapy (106-109). These insights support translational approaches that combine cytotoxic therapy with agents targeting transition programs or immune pathways. In summary, CTC-based personalization spans three complementary uses: identification of druggable targets, elucidation of resistance mechanisms, and functional testing of therapy on patient-derived cells. While much remains in development, several applications, including ALK testing on CTCs, are moving toward clinical use. Integration of CTC analyses with other liquid biopsy components, such as circulating tumor DNA and exosomes, will likely provide a more comprehensive and real-time picture of tumor biology, enabling adaptive precision therapy in lung cancer.

Despite promising applications in risk stratification, treatment monitoring, and MRD assessment, several gaps remain before routine implementation; priority future directions are summarized in Table 4. A key future direction is comprehensive cTME profiling through integrated liquid biopsy. Multi-analyte strategies that combine cellular components, including CTCs, CTC clusters, and CTECs, with acellular analytes such as ctDNA and EVs aim to capture complementary layers of tumor biology and tumor host interaction (4,12,13). ctDNA supports sensitive genomic detection and longitudinal tracking, while cellular analytes enable single-cell phenotyping and functional inference, and EVs provide abundant and stable cargo that reflects intercellular communication in the circulating compartment (4,13). Early clinical utility studies of multi-analyte liquid biopsy approaches support feasibility for treatment selection in advanced refractory settings, motivating prospective validation in disease-specific contexts such as lung cancer (14). Progress toward implementation will depend on standardized pre-analytical workflows, harmonized reporting across analyte classes, and prospective trials that test whether integrated cTME outputs improve outcomes.

Table 4. Future work needed to advance CTC applications in lung cancer.

Priority area	Key questions	What needs to be done
Assay standardization and harmonization	How can results be comparable across platforms and centers	Harmonize pre analytical handling, enrichment and detection workflows, and reporting templates. Define quality control metrics for capture efficiency, purity, and detection limits. Establish reference materials and external proficiency testing
Taxonomy and reporting consistency	How should CTAC components be named and reported across studies	Standardize nomenclature and minimum reporting items for CTAC, including CTC, CTE, and CTEC. Require explicit operational definitions for clusters, host cell associated complexes, and endothelial lineage populations
Defining clinically actionable thresholds	What cutoffs should be used for positivity and for response assessment in NSCLC and SCLC	Derive and validate thresholds by stage and treatment context. Specify timepoints for baseline and on treatment sampling. Link thresholds to meaningful outcomes
Capturing epithelial low and transitional, and small size phenotypes	How to avoid missing EMT associated small size CTC that older methods under recover	Use complementary enrichment strategies that reduce reliance on epithelial markers and rigid size filters. Implement multi marker panels that include epithelial, mesenchymal, and stem like features and validate recovery of small size populations
CTEC biology and clinical relevance	When do CTEC add value beyond CTC for risk stratification and monitoring	Standardize CTEC identification criteria and phenotyping. Determine links with angiogenesis and metastatic progression, and define clinical contexts where CTEC adds independent predictive value
ICI era immune and vascular readouts	Can circulating immune and vascular signals predict ICI resistance and guide early adaptation	Prospectively test whether PD-L1 and related phenotypes on circulating cells, including CTEC, predict ICI benefit and resistance. Define how to integrate these readouts with imaging and clinical endpoints
Total cTME profiling and integrated liquid biopsy	When should cellular analytes be combined with ctDNA and extracellular vesicles	Define complementary roles of cellular phenotyping versus genomic signals and vesicle cargo. Build integrated risk models for recurrence and resistance and validate them prospectively
Clinical utility of CTC guided management	Does acting on integrated circulating results improve outcomes	Test whether biomarker guided treatment switch, escalation, or de-escalation improves survival or reduces unnecessary imaging, using prospective interventional designs
MRD implementation	Can post treatment circulating signals guide adjuvant therapy and surveillance intensity	Define optimal post treatment time windows to avoid transient false positives. Develop confirmatory workflows using orthogonal methods such as mutation or methylation verification, and evaluate integrated models combining cellular and acellular analytes
Functional diagnostics and live CTAC testing	Can chemo response profiling and other functional assays guide dynamic therapy selection	Validate feasibility, turnaround time, and reproducibility in lung cancer cohorts. Benchmark concordance with outcomes and define clinical decision points where functional readouts change management
Clinical laboratory implementation and equity	Is testing cost effective, scalable, and accessible	Study cost, turnaround time, staffing and training needs, and reimbursement pathways. Define clinical pathways where added value is clearest and assess equity impacts across settings

CTAC, circulating tumor associated cells; CTC, circulating tumor cell; ctDNA, circulating tumor deoxyribonucleic acid; CTE, circulating tumor emboli; CTEC, circulating tumor endothelial cell; cTME, circulating tumor microenvironment; EMT, epithelial to mesenchymal transition; ICI, immune checkpoint inhibitor; MRD, minimal residual disease; NSCLC, non-small cell lung cancer; PD-L1, programmed death ligand 1; SCLC, small cell lung cancer.

Several limitations should be acknowledged. First, the evidence base is heterogeneous across study designs, assay platforms, and sampling schedules, which hinders cross-study comparison and prevents uniform positivity thresholds in NSCLC and SCLC. Second, substantial pre-analytical and analytical variability in collection conditions, transport time, processing protocols, enrichment markers, and detection readouts affects yield and phenotype. Epithelial antigen-based capture can under-recover epithelial marker low subpopulations, including EMT transition-associated phenotypes, while purely size-based approaches can bias recovery against very small CTCs that may carry prognostic information in contemporary workflows. Third, many reports are single-center with modest sample sizes and often mix stages and treatment contexts, introducing selection bias and limiting generalizability. Fourth, although serial CTC changes frequently precede radiologic findings, prospective interventional trials demonstrating that management is altered on the basis of circulating analyte results improve outcomes remain scarce. Finally, in MRD assessment, transient postoperative positives and the absence of standardized confirmatory workflows reduce specificity and complicate interpretation. Rigorous confirmation, such as verification of tumor-specific mutations or methylation patterns, can improve specificity, but standardized pathways remain needed for routine implementation.

Conclusions

Across basic, clinical, and translational studies, CTC-based analysis has matured from simple enumeration into a circulating ecosystem readout that complements imaging and tissue biopsy in lung cancer. In high-risk cohorts, CTC positivity can precede radiologic detection, supporting its potential role in screening enrichment when paired with low-dose CT. Prognostic data are consistent across platforms: in NSCLC and SCLC, detectable CTCs and higher burdens associate with inferior survival, with large effects in SCLC and additional risk carried by CTE- and leukocyte-associated clusters. Longitudinal monitoring adds clinical utility. Treatment-associated declines generally track response, whereas persistently or rebound anticipate progression; and after curative intent treatment, postoperative positivity identifies MRD and predicts relapse months before imaging in selected studies. Beyond counting, molecular and phenotypic profiling, and viable CTAC-based functional assays can support driver detection, resistance surveillance, and therapy selection when tissue is limited, while CTECs provide a vascular-focused biomarker that may inform angiogenesis-related biology and ICI era monitoring. The major barriers to routine implementation remain assay heterogeneity, pre-analytical variability, and a lack of harmonized thresholds across disease stages and treatment contexts. Future progress will depend on standardized workflows, integrated multi analyte strategies combining cellular and acellular biomarkers, and prospective interventional trials that test whether management adapted to circulating analyte results improves patient outcomes.

Supplementary

The article’s supplementary files as

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.