Circulating tumor cells as a response monitor in stage IV non-small cell lung cancer

Dissemination of tumor cells through the circulation may be key in the progression of solid tumors, including lung cancer. The management of NSCLC has shifted over the past decade. Molecular based treatment decisions are now considered standard of care, and improved outcomes are seen with targeted therapy compared to chemotherapy in certain subgroups. However, drug development faces several hurdles, including the lack of access to pharmacodynamic markers and longitudinally collected tumor specimens [1, 2]. Surprisingly, circulating tumor cell (CTC) isolation technologies have yet to perform robustly in NSCLC relative to the success of studies in small-cell lung cancer (SCLC) or prostate cancer. The use of liquid biopsies to assess CTC enumeration either as a whole, or for specific subgroups, could enhance the understanding of disease progression, and has already been shown to carry prognostic information in several cancer types, including lung cancer [3‐8].

CTCs are defined as cells that have been released into the peripheral blood from either the primary tumor or metastatic sites. CTCs have been shown to fluctuate with therapy and predict response to certain agents, indicating the potential for these cells to serve as a predictive biomarker. It is important to note that molecular characterization and enumeration of CTCs has been conducted on several different cancer types using a variety of detection methods integrated with molecular characterization [9‐11].

However, clinicians do not commonly use CTC information to make treatment decisions, despite its potential prognostic and predictive value [12, 13]. The scant amount of data regarding treatment and outcomes associated with CTC monitoring is surprising. One reason CTC monitoring has not been adopted in clinical lung cancer practice is the low prevalence or inability to detect CTCs in certain cancers, such as NSCLC [5‐8]. As well as, there is a general lack of sufficient evidence for clinical utility in a specific context of use that can support clinical decision making to improved outcomes for NSCLC patients. Currently there are no FDA approved assays for the detection of CTCs in lung cancer patients. CellSearch^® (Veridex, Raritan NJ), the current clinical standard for CTC enumeration in breast, prostate and colorectal cancer, uses immunomagnetic enrichment of epithelial cell adhesion molecule (EpCAM) expressing cells, but is not approved in NSCLC. This may be due to the highly variable CTC detection rates that have been reported in stage IV NSCLC patients using CellSearch^®, as well as the fact that tumor cells with low EpCAM expression such as NSCLC may escape detection by this method [6, 8, 14‐21]. Furthermore, potential utility of CTCs in the clinical setting is limited by the several different methods and cellular thresholds that have been employed in CTC detection studies from a variety of NSCLC cohorts, restricting the possibility of comparative findings.

Here we use a non-enrichment based high-definition single cell assay (HD-SCA) workflow to detect CTCs based on morphology and high-throughput analysis in stage IV NSCLC patients. Assessment of CTCs using the HD-SCA workflow has previously been investigated in 78 early and late stage chemotherapy naïve lung cancer patients, which showed a high prevalence (61% positive) of CTCs in stage IV patients [22]. CTC positivity based on the HD-SCA workflow is inclusive of cellular morphology with interrogation of all nucleated cells from the liquid biopsy, enabling the possibility to serve as a disease and therapy resistance monitoring test, especially for patients with EpCAM low or negative disease. This study reports the analysis of CTCs with longitudinal surveillance of stage IV NSCLC patients entering different lines of therapy, in association with progression-free (PFS) and overall survival (OS).

Detection and characterization of CTCs from the liquid biopsy is a powerful diagnostic and prognostic tool for cancer patients, providing insight into the potential of therapy failure. The HD-SCA technology is a validated rare cell detection workflow that has joined forces with other technologies to build the Blood Profiling Atlas Commons (Blood PAC) by standardizing methods for analysis of circulating tumor cell morphology, genomics and proteomics, with simultaneous cell-free genomics. The goal of BloodPAC is to provide the scientific knowledge so physicians and patients are more informed about their disease and can make better-informed decisions. Recently Epic Sciences, using a very similar methodology as presented here, released the only predictive and prognostic test for the detection of CTCs positive for nuclear-localized androgen receptor splice variant 7 (AR-V7) in metastatic castration-resistant prostate cancer (mCRPC). The Epic AR-V7 assay shows that detection of even one CTC with nuclear AR-V7 positivity translates to resistance to enzalutamide and abiraterone and sensitivity to the taxanes in mCRPC [37‐39]. This supports our data due to the utilization of analogous technology, justifying further study into the clinical utility of the HD-SCA workflow for the identification of a biomarker in NSCLC patients. The other FDA approved CTC detection technology (CellSearch^®) involves enrichment for EpCAM, with subsequent identification of CTCs using CK expression. In a direct comparison to CellSearch^®, the HD-SCA workflow detects significantly more CTCs in a higher proportion of patients with higher sensitivity; while healthy donor samples present with ≤ 1 CTC/mL [23]. Various enrichment and identification methods lead to a variety of test results and different sensitivities and/or specificities. Only through use of a non-EpCAM based approach, such as the HD-SCA workflow, can all potential CTCs be monitored, including EpCAM-low or negative cells.

The term ‘liquid biopsy’ refers to analyses typically performed on peripheral blood collected from a patient, but each technological platform produces different results due to inherent design components optimizing evaluation of different analytes. At baseline 63% of our patients had HD-CTCs, while overall 58% of the total samples collected during this longitudinal study were positive. Of the studies that have evaluated advanced NSCLC, only a few have reported a similar baseline detection rate [24, 32]. Over the past years exciting technologies have been developed based on various physical and biological properties. Using CellSearch^®, Punnoose et al. detected CTCs in 78% of samples [8], while other studies using that platform have shown much lower detection rates of 23% [6], 36.4% [15], 41.9% [19], 32% [20], and 30.9% [21]. Higher detection rates have been reported for NSCLC using a magnetic sifter (100%) [40], vortex chip (100%) [41], DFF (100%) [42], MCA (77%) [20], Cyttel (87%) [35], CanPatrol CTC enrichment (79%) [43], and multi-immunofluorescence staining (100%) [44].

Multiple studies have indicated that baseline CTC counts are prognostic in NSCLC [7, 15, 16, 19, 24, 34, 35, 45], but the prognostic significance of CTC dynamics over the course of treatment is still unclear and may provide more utility in clinical management of metastatic lung cancer. Patient management would be revolutionized if through monitoring the dynamics of CTCs, patients could be classified into prognostic groups with specific treatment plans to alter the course of disease, i.e. predictive classifications. Krebs et al. [7] has reported a threshold of CTC levels that was prognostic, and for patients positive at baseline an increasing CTC level was associated with poor prognosis and a lack of response. Punnoose et al. [8] also showed that an increase in CTC counts after treatment was associated with a poor response, but that absolute CTC levels were not prognostic. Both of these studies utilized the CellSearch^® platform for CTC detection and enumeration. Zhang et al. [35] analyzed 46 advanced NSCLC patients using the Cyttel method, showing CTC dynamics were not correlated to RECIST evaluation, but patients with an increasing CTC profile had either SD or PR. More recently He et al. [46] analyzed 66 stage IV NSCLC patients using flow cytometry, in which patients with effective treatment (60.6%) had a decrease in CTC count from baseline. Significant differences between these studies that may provide insight into the discordance of results include (i) different CTC detection methods, (ii) patient population disease stage, (iii) patient inclusion criteria, (iv) follow up period, and (v) definition of CTC increase/decrease.

A strong prognostic correlation of HD-CTC dynamics was identified in which patients displaying an increase in HD-CTCs after entering a new line of chemotherapy, typically within three months, do significantly better in terms of PFS and OS than patients who don’t exhibit that change. It should be noted that this analysis was not pre-specified and will require validation in an independent cohort. Although the association between an increase in HD-CTCs during therapy and prolonged PFS and OS may be counterintuitive, when considering the setting of metastatic disease as opposed to limited disease, it is unsurprising. The prognostic value of CTC enumeration alone may be largely lost in patients where metastatic disease has already been established. We further suggest that the improved survival outcomes seen in patients with increasing HD-CTC levels may be the result of chemotherapy effectively acting in the tumor tissue, causing it to shed cells into the circulation. This is corroborated by the fact that all patients with increasing HD-CTC levels shortly after initiation of treatment show clinical response or stable disease according to the assessment of PFS. This demonstrates that CTC kinetics over time are more relevant than enumeration at a single timepoint, implying that CTC prognostic ability is dependent on the specific context of use.

To better understand the prognostic significance of CTCs for differential treatments, we looked at those patients specifically being treated with bevacizumab. The monoclonal antibody against VEGF, bevacizumab, has been shown to improve OS in NSCLC when combined with chemotherapy [47]. It is well recognized that bevacizumab, through the inhibition of tumor angiogenesis, leads to intra-tumoral hypoxia triggering tumor progression, invasive cell behavior, and EMT [48]. Because the HD-SCA technology is independent of EpCAM expression it is uniquely positioned to be able to evaluate CTC fluctuations on bevacizumab therapy. In the small cohort of bevacizumab treated NSCLC patients, we showed that a baseline threshold of HD-CTC enumeration was prognostic of survival. Unfortunately the small sample size in the kinetics cohort limits our statistical analysis of cellular dynamics, warranting further study. Previous studies have shown a decrease in CTC count from baseline in breast cancer patients [49] and in colorectal cancer [50, 51] receiving bevacizumab. It is reasonable to think that different treatments affect the disease and therefore the CTCs in unique ways, suggesting that CTC prognostic ability may be therapeutic dependent. This would imply the need to develop a cellular signature specific to the treatment type. Further research will be vital in understanding the relationship between CTCs and clinical response to specific treatments.

In a previous publication utilizing the HD-SCA workflow, Nieva et al. [24] showed detection of HD-CTCs in 68% of samples from patients with NSCLC and this is consistent with our finding in this follow up study. Nieva et al. [24] averaged all CTC counts from multiple blood draws for each individual patient to show a survival difference with a threshold of 5 CTCs/mL. Conducting a similar analysis on the cohort presented here confirms that higher numbers of detected CTCs were associated with poor PFS (Additional file 4: Figure S2). Survival analysis for the study presented here was conducted in a more finely temporally nuanced method, utilizing each individual blood draw as well as the change in CTC dynamics, wherein each draw is dependent on the previous to show the effects of cellular kinetics. Additionally, here we emphasize the time of sample collection as key to understanding the cellular changes, in which data from the specific timepoint of 3 months post start of treatment was analyzed, as compared to our colleagues’ analysis which used all samples, include those collected at 180 + days post baseline draw.

The primary tumor, CTCs, and metastatic lesions show considerable heterogeneity in cellular morphology. Depending on the CTC criteria used for each detection platform, specific subpopulations of CTCs are identifiable. In a meta-analysis conducted by Wang et al. [52] different CTC subpopulations were determined to be of predictive clinical value. Using the HD-SCA workflow various candidate cells are monitored, but are not defined as classic CTCs. The key issue is whether these different subtypes of circulating cells reflect the primary tumor or if they are distinct. Muinelo-Romay et al. [19] enrolled 43 newly diagnosed NSCLC patients, and found a statistically positive correlation between intact CTCs and apoptotic CTC or CK fragments using CellSearch^®. The data presented here also indicates a correlation between HD-CTCs and candidate CTC cells identified by HD-SCA, indicative of a common origin. Taken together this demonstrates that the various candidate cells detected by each platform are subgroups of CTCs which may have prognostic significance. This is reflected here by the observable shorter OS probability with higher baseline cell counts of CTC-Small and CTC-NoCytokeratin cells. Interestingly, this also suggests that morphologically distinct cells lacking an epithelial biomarker may be critical in predicting patient outcomes. This is supported by the work from Nel et al. [44] showing an association between mesenchymal CTCs and poor response, which is also confirmed by the Yin et al. [53] study in which EpCAM negative CTCs were associated with shorter survival. In optimizing CTC detection for clinical utility, it will be crucial to monitor all subpopulations of CTCs for identification of specific cells driving metastasis and chemotherapeutic resistance, while also obtaining a complete representation of the tumor heterogeneity.

Not all CTCs may be tumor initiating cells, but may indeed be a good biomarker for response. CTCs may be the result of either spontaneous release or as a direct result of medical procedures (biopsy/surgery). In specific cases a simple ‘CTC yes’ vs. ‘CTC no’ may be prognostics, especially when determining the best therapy. For some patients, ‘CTC yes’ may suggest a more aggressive treatment plan is needed. Other patients with ‘CTC no’ may do well on a less aggressive treatment plan, possibly sparing them side effects. Absolute CTC count beyond this scenario has not been proven clinically meaningful. The use of CTC kinetics may be clinically useful in monitoring response and survival of individual patients. Patient-specific CTC kinetic rates could be utilized as a companion tool to clinical imaging, allowing for better stratification of patients for specific therapeutics or early detection of treatment failure.

The data presented here motivates the potential use of CTC kinetics for monitoring response to therapy and improving the ability to define prognosis. The scenarios that are most relevant would be (1) measurement of baseline CTC counts for patients entering bevacizumab treatment, (2) assessment of other candidate cell populations prior to treatment for prognostic insight, and (3) the use of CTC kinetics as a marker for progression to trigger imaging and/or additional molecular studies. This should motivate a larger, fully powered study with a larger cohort of stage IV NSCLC patients entering a new or first line of therapy and peripheral blood sample collections that are more frequent than the protocol used here. By understanding the dynamic processes of CTCs, we can monitor important functions or behaviors of the cellular network induced by changing conditions due to the initiation of treatment. The results presented open new avenues of investigation into the complex role of CTCs in cancer research and clinical management by suggesting that the level and dynamics of CTCs may indicate very different biological and pharmacological phenomena at different stages of disease and timepoints of treatment. This type of dynamic biomarker will become a key component in the evaluation of an end point in clinical trials to monitor efficacy of therapy by distinguishing responding from non-responding patients, facilitate the identification of new therapeutic targets, as well as expedite approval for novel anticancer therapies for NSCLC.