Dataset Information

Quantitative cerebrospinal fluid circulating tumor cells are a potential biomarker of response for proton craniospinal irradiation for leptomeningeal metastasis.

ABSTRACT:

Background

Leptomeningeal metastasis (LM) involves cerebrospinal fluid (CSF) seeding of tumor cells. Proton craniospinal irradiation (pCSI) is potentially effective for solid tumor LM. We evaluated whether circulating tumor cells (CTCs) in the CSF (CTC_CSF), blood (CTC_blood), and neuroimaging correlate with outcomes after pCSI for LM.

Methods

We describe a single-institution consecutive case series of 58 patients treated with pCSI for LM. Pre-pCSI CTCs, the change in CTC post-pCSI (Δ _CTC), and MRIs were examined. Central nervous system progression-free survival (CNS-PFS) and overall survival (OS) from pCSI were determined using Kaplan Meier analysis, Cox proportional-hazards regression, time-dependent ROC analysis, and joint modeling of time-varying effects and survival outcomes.

Results

The median CNS-PFS and OS were 6 months (IQR: 4-9) and 8 months (IQR: 5-13), respectively. Pre-pCSI CTC_CSF < 53/3mL was associated with improved CNS-PFS (12.0 vs 6.0 months, P < .01). Parenchymal brain metastases (n = 34, 59%) on pre-pCSI MRI showed worse OS (7.0 vs 13 months, P = .01). Through joint modeling, CTC_CSF was significantly prognostic of CNS-PFS (P < .01) and OS (P < .01). A Δ _CTC-CSF≥37 cells/3mL, the median Δ _CTC-CSF at nadir, showed improved CNS-PFS (8.0 vs 5.0 months, P = .02) and further stratified patients into favorable and unfavorable subgroups (CNS-PFS 8.0 vs 4.0 months, P < .01). No associations with CTC_blood were found.

Conclusion

We found the best survival observed in patients with low pre-pCSI CTC_CSF and intermediate outcomes for patients with high pre-pCSI CTC_CSF but large Δ _CTC-CSF. These results favor additional studies incorporating pCSI and CTC_CSF measurement earlier in the LM treatment paradigm.

SUBMITTER: Wijetunga NA

PROVIDER: S-EPMC8717892 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Background: Leptomeningeal metastasis (LM) has frequently been observed in patients with lung adenocarcinoma. So far, its diagnosis and disease course monitoring are still extremely difficult. Moreover, there is no effective treatment regimen for LM due to a lack knowledge on the molecular mechanism of LM. This study aimed to identify LM-related cerebrospinal fluid (CSF) miRNAs, which have potential value for diagnosing and monitoring LM and exploring the molecular mechanism. Methods: CSF miRNAs were screened and verified by microarray analysis and quantitative real-time PCR (qRT-PCR) in LM patients with lung adenocarcinoma and non-LM controls, and the diagnostic performance of candidate miRNAs was evaluated. Then, candidate miRNAs in matched CSF samples from LM patients at diagnosis, after initial therapy, at relapse, and after salvage therapy, were analyzed to assess the relationship between CSF miRNAs and LM disease course. The effect of candidate miRNAs on proliferation, invasion, and migration of lung adenocarcinoma cell lines was assessed. The targeted genes of the candidate miRNA were predicted by TargetScan, miRDB, and miRTarbase online analysis tools. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the functional categories of predicted target genes. Results: CSF miR-7975, miR-7977, and miR-7641 were screened and verified to be statistically significantly up-regulated in LM patients compared to non-LM controls. The three miRNAs, when combined, exhibited optimal diagnostic performance. Longitudinal data of CSF miR-7975 and miR-7977 correlated well with clinical courses of LM. Overexpression of miR-7977 promoted proliferation, migration, and invasion of lung adenocarcinoma cells. Moreover, 385 targeted genes of miR-7977 were predicted and were involved in various pathways related to cancer metastasis. Conclusions: This study offers insights for future research of CSF miRNAs as robust tools for diagnosing and monitoring LM. It also reveals a novel pathway for exploration of underlying mechanisms of LM.