Cerebrospinal fluid as a liquid biopsy for molecular characterization of brain metastasis in patients with non-small cell lung cancer.

OBJECTIVES: Non-small cell lung cancer (NSCLC) with brain metastases (BM) is a challenging clinical issue with poor prognosis. No data exist regarding extensive genetic analysis of cerebrospinal fluid (CSF) and its correlation to associated tumor compartments. MATERIALS AND METHODS: We designed a study across multiple NSCLC patients with matched material from four compartments; primary tumor, BM, plasma and CSF. We performed enrichment-based targeted next-generation sequencing analysis of ctDNA and exosomal RNA in CSF and plasma and compared the outcome with the solid tumor compartments. RESULTS: An average of 105 million reads per sample was generated with fractions of mapped reads exceeding 99% in all samples and with a mean coverage above 10,000x. We observed a high degree of overlap in variants between primary lung tumor and BM. Variants specific for the BM/CSF compartment included in-frame deletions in AR, FGF10 and TSC1 and missense mutations in HNF1a, CD79B, BCL2, MYC, TSC2, TET2, NRG1, MSH3, NOTCH3, VHL and EGFR. CONCLUSION: Our approach of combining ctDNA and exosomal RNA analyses in CSF presents a potential surrogate for BM biopsy. The specific variants that were only observed in the CNS compartments could serve as targets for individually tailored therapies in NSCLC patients with BM.

Validation of a high resolution NGS method for detecting spinal muscular atrophy carriers among phase 3 participants in the 1000 Genomes Project.

BACKGROUND: Spinal muscular atrophy (SMA) is the most common pan-ethnic cause of early childhood death due to mutations in a single gene, SMN1. Most chromosome 5 homologs have a functional gene and dysfunctional copy, SMN2, with a single synonymous base substitution that results in faulty RNA splicing. However, the copy number of SMN1 and SMN2 is highly variable, and one in 60 adults worldwide are SMA carriers. Although population-wide screening is recommended, current SMA carrier tests have not been incorporated into targeted gene panels. METHODS: Here we describe a novel computational protocol for determining SMA carrier status based solely on individual exome data. Our method utilizes a Bayesian hierarchical model to quantify an individual's carrier probability given only his or her SMN1 and SMN2 reads at six loci of interest. RESULTS: We find complete concordance with results obtained with the current qPCR-based testing standard in known SMA carriers and affecteds. We applied our protocol to the phase 3 cohort of the 1,000 Genomes Project and found carrier frequencies in multiple populations consistent with the present literature. CONCLUSION: Our process is a convenient, robust alternative to qPCR, which can easily be integrated into the analysis of large multi-gene NGS carrier screens.