Detection of Leptomeningeal Disease Using Cell-Free DNA From Cerebrospinal Fluid.

Importance: Leptomeningeal disease (LMD) is a devastating complication of cancer that is frequently underdiagnosed owing to the low sensitivity of cerebrospinal fluid (CSF) cytologic assessment, the current benchmark diagnostic method. Improving diagnostic sensitivity may lead to improved treatment decisions. Objective: To assess whether cell-free DNA (cfDNA) analysis of CSF may be used to diagnose LMD more accurately than cytologic analysis. Design, Setting, and Participants: This diagnostic study conducted in a neuro-oncology clinic at 2 large, tertiary medical centers assessed the use of genomic sequencing of CSF samples obtained from 30 patients with suspected or confirmed LMD from 2015 through 2018 to identify tumor-derived cfDNA. From the same CSF samples, cytologic analyses were conducted, and the results of the 2 tests were compared. This study consisted of 2 patient populations: 22 patients with cytologically confirmed LMD without parenchymal tumors abutting their CSF and 8 patients with parenchymal brain metastases with no evidence of LMD. Patients were considered positive for the presence of LMD if previous CSF cytologic analysis was positive for malignant cells. The analysis was conducted from 2015 to 2018. Main Outcomes and Measures: The primary outcome was the diagnostic accuracy of cfDNA analysis, defined as the number of tests that resulted in correct diagnoses out of the total number of tests assayed. Hypotheses were formed before data collection. Results: In total, 30 patients (23 women [77%]; median age, 51 years [range, 28-81 years]), primarily presenting with metastatic solid malignant neoplasms, participated in this study. For 48 follow-up samples from patients previously diagnosed via cytologic analysis as having LMD with no parenchymal tumor abutting CSF, cfDNA findings were accurate in the assessment of LMD in 45 samples (94%; 95% CI, 83%-99%), whereas cytologic analysis was accurate in 36 samples (75%; 95% CI, 60%-86%), a significant difference (P = .02). Of 43 LMD-positive samples, CSF cfDNA analysis was sensitive to LMD in 40 samples (93%; 95% CI, 81%-99%), and cytologic analysis was sensitive to LMD in 31 samples (72%; 95% CI, 56%-85%), a significant difference (P = .02). For 3 patients with parenchymal brain metastases abutting the CSF and no suspicion of LMD, cytologic findings were negative for LMD in all 3 patients, whereas cfDNA findings were positive in all 3 patients. Conclusions and Relevance: This diagnostic study found improved sensitivity and accuracy of cfDNA CSF testing vs cytologic assessment for diagnosing LMD with the exception of parenchymal tumors abutting CSF, suggesting improved ability to diagnosis LMD. Consideration of incorporating CSF cfDNA analysis into clinical care is warranted.

Genomic characterization of human brain metastases identifies drivers of metastatic lung adenocarcinoma.

Brain metastases from lung adenocarcinoma (BM-LUAD) frequently cause patient mortality. To identify genomic alterations that promote brain metastases, we performed whole-exome sequencing of 73 BM-LUAD cases. Using case-control analyses, we discovered candidate drivers of brain metastasis by identifying genes with more frequent copy-number aberrations in BM-LUAD compared to 503 primary LUADs. We identified three regions with significantly higher amplification frequencies in BM-LUAD, including MYC (12 versus 6%), YAP1 (7 versus 0.8%) and MMP13 (10 versus 0.6%), and significantly more frequent deletions in CDKN2A/B (27 versus 13%). We confirmed that the amplification frequencies of MYC, YAP1 and MMP13 were elevated in an independent cohort of 105 patients with BM-LUAD. Functional assessment in patient-derived xenograft mouse models validated the notion that MYC, YAP1 or MMP13 overexpression increased the incidence of brain metastasis. These results demonstrate that somatic alterations contribute to brain metastases and that genomic sequencing of a sufficient number of metastatic tumors can reveal previously unknown metastatic drivers.