Research on biomarkers for CNS metastases—including CTCs, circulating tumor DNA (ctDNA) and single cell analyses—has significantly advanced in recent years[9, 14, 21, 22], but their clinical significance is still unknown. This is the largest study describing CSF-CTCs as a quantitative biomarker predicting outcome in patients with LM from solid tumors in a clinical setting. Our study demonstrates a continuous relationship between CSF-CTC count and mortality, with an excess risk of 0.5% for each additional CSF-CTC for patients with newly diagnosed LM. For patients with lung cancer and newly diagnosed LM, CSF-CTCs were an even stronger predictor, with an excess risk of death of 1% with each additional CSF-CTC. This association between CSF-CTC count and outcome may facilitate a potentially expanded utility of CSF-CTCs as a quantitative biomarker of disease burden in the CNS compartment: not only as a diagnostic test, but also as a prognostic tool for newly diagnosed LM.
Previously, studies exploring the utility of CTC detection in CSF have centered in its performance as a diagnostic tool in LM. Aside from its improved sensitivity for LM diagnosis, CSF-CTC analysis offers a distinct advantage over CSF cytology and neuroaxis imaging: its results are quantitative, providing an objective scale that contrasts with the binary outcomes of CSF cytology and the lack of reproducibility of MRI measurements. Our data show that presence of CSF-CTCs at or above the threshold of 61 CTCs/3 ml in patients with newly diagnosed LM more than doubles the risk of death in this population over our follow-up period (median follow-up 3.9 months). This cutoff could potentially be used for stratification of patients at the time of LM diagnosis and before initiation of treatment, including clinical trials, which is particularly important in a disease where prognosis has been considered universally poor.
In addition, our results suggest the potential superiority of CSF-CTCs over neuroimaging as a marker of quantitative CNS disease burden in patients with LM. We found a statistically significant association between positivity of brain and spine MRI for LM and CSF-CTC count, with median CSF-CTC count being higher for patients whose MRI was considered positive by the consensus of our three independent readers. This suggests there is a correlation between radiographic burden of disease in LM and CSF-CTC count, which in our data was maintained when analyzing nodular and linear enhancement in the brain, and linear enhancement on spine MRIs; nodular enhancement on spine MRIs was not associated with higher CSF-CTC count, perhaps due to the small number of patients (17/115). There was no association between any of these radiographic patterns of enhancement and overall survival in our sample, which is consistent with the findings of other studies . Moreover, MRIs of the brain and spine are difficult to interpret at early stages of LM, and the currently used criteria by the RANO-LM group lack reproducibility. Our results reflect this unreliability, with only moderate inter-rater agreement in determining presence of leptomeningeal enhancement in the brain, and better agreement on spine imaging. This underscores the challenges of interpreting MRIs in LM, even for neuroradiologists specializing in cancer imaging. For example, based on the combination of our independent assessments and official report, two patients from our newly diagnosed LM cohort would have been reclassified as not having LM, as their diagnosis was based exclusively on MRI findings (brain in one case and spine in the other) but all three independent readers considered their MRIs negative for LM. Both patients had negative cytology and no CSF-CTCs, highlighting that CSF-CTCs can provide a more objective measure of disease burden, and with a stronger correlation with survival than imaging.
With the expansion of liquid biopsies in recent years, enumeration of CTCs represents only one of the many analyses that can be performed in the CSF of patients with CNS metastases. In addition to being quantified, CSF-CTCs can also be isolated for genetic sequencing or even transcriptome analysis[21, 24–26], although currently these techniques are mostly relegated to the research setting and not routinely done in clinical practice. CtDNA can also be detected in the CSF of patients with both primary and metastatic brain tumors[27–29]; in patients with CNS metastases, ctDNA in CSF can contribute valuable information about the mutational profile in the CNS compartment, which may differ from the one in the primary tumor, potentially with therapeutic implications[27, 30]. The utility of CSF-CTCs and ctDNA as a method of liquid biopsy for patients with CNS metastases has not been directly compared, but these techniques likely provide complementary data.
LM are considered a separate biological entity from parenchymal BrM. Although the mechanisms of metastatic cell invasion of the CNS parenchyma are believed to be different from those of spread into the CSF[31–33], it has been recognized that one of the means of CSF dissemination leading to LM is through seeding from parenchymal lesions. In fact, it is not uncommon in clinical practice for BrM and LM to coexist, as demonstrated in our sample, in which 71% of patients with newly diagnosed LM had both LM and BrM. This includes a subset of 31 patients with newly diagnosed BrM who also had co-existing, newly diagnosed LM; in almost a third of these patients (9/31, 29%) the diagnosis of LM was exclusively based on a positive or suspicious CSF cytology, without evidence of LM on MRIs (Figure 1b). This highlights the importance of considering lumbar punctures in patients with BrM, in which CSF analysis may be the only way to diagnose LM at its early stages. Although LM and BrM are distinct clinicopathological entities in terms of their diagnosis, presentation, management, and prognosis, there is a degree of overlap between them that justifies exploring CSF-CTCs as a biomarker not only in LM, but potentially also in newly diagnosed BrM. As an example, among the 290 patients who had CSF-CTC analysis, there were 19 patients who had a CSF-CTC result above the threshold suggestive of LM diagnosis (≥3 CSF-CTCs/3 ml) but did not meet cytological and/or radiographic criteria for a diagnosis of LM. Of these, two patients likely truly had LM based on clinical criteria; of the remaining 17 patients, 12 had evidence of either dural (in one case) or superficial parenchymal brain metastases that could have conceivably shed malignant cells into the CSF, exemplifying how CSF-CTC quantification can be an indirect marker of disease burden in patients with BrM, even in the absence of overt LM.
A major strength of this study is the relatively large number of patients. Our study has several potential weaknesses, including its retrospective nature, which introduces the possibility of selection bias, as well as an element of variability in the timing of LM diagnosis across patients. Our initial overall sample of 290 patients was heterogeneous regarding time of LP in relation to patients’ clinical course and LM diagnosis. We tried to mitigate this effect by selecting a more homogeneous subgroup of patients with LM diagnosed within a specific timeframe in relation to CSF-CTC collection, but within this group there are a variety of factors that could not be controlled for, such as prior treatments received. An additional source of heterogeneity, commonly seen in studies involving LM patients due to the rarity of the disease, is the mix of different histologies, which could limit generalizability of the results. Importantly, we were able to reproduce the results from the overall cohort of 101 patients with newly diagnosed LM in the subgroup with the most common histology (44 patients with lung cancer). While CSF-CTCs were not able to predict survival in patients with breast cancer, we attribute this result to the smaller number of patients with this diagnosis potentially rendering the trend towards a difference in survival statistically non-significant, which is illustrated by CSF cytology also being unable to predict survival in this patient group despite having being validated as a prognostic tool in patients with LM.
Our study also suffers from the drawbacks inherent to CTC testing using the CellSearch® platform—including the inability to capture melanoma cells, or epithelial cancer cells that have lost EpCAM expression, which may happen as the disease evolves and tumor cells transition into a mesenchymal phenotype. However, the importance these EpCAM-negative CTCs may have in determining prognosis is unclear, as several studies analyzing CTCs from blood in patients with lung, breast and prostate cancer have found no correlation between CTCs discarded by the CellSearch® system and survival[36–38]. Lastly, another important limitation of our study is that we had access to a single CSF sample per patient, so the generalizability of our results to the dynamic changes of CSF-CTCs over time, although theoretically possible, is limited. Periodic analysis of CSF-CTCs in prospective trials could help establish this test as a marker of response to treatment or early recurrence, and a number of active clinical trials are now incorporating CSF-CTCs in their design.
In conclusion, our data shows that CSF-CTC analysis is a significant prognostic biomarker in patients with newly diagnosed LM, for whom it has a better correlation with outcome than both CSF cytology and MRI findings. Large prospective studies including patients with newly diagnosed BrM are needed to further define the utility of CSF-CTCs, ctDNA and other forms of liquid biopsy in the management of CNS metastases, with or without LM.