A Highly Sensitive and Quantitative Test Platform for Detection of NSCLC EGFR Mutations in Urine and Plasma.

INTRODUCTION: In approximately 60% of patients with NSCLC who are receiving EGFR tyrosine kinase inhibitors, resistance develops through the acquisition of EGFR T790M mutation. We aimed to demonstrate that a highly sensitive and quantitative next-generation sequencing analysis of EGFR mutations from urine and plasma specimens is feasible. METHODS: Short footprint mutation enrichment next-generation sequencing assays were used to interrogate EGFR activating mutations and the T790M resistance mutation in urine or plasma specimens from patients enrolled in TIGER-X (NCT01526928), a phase 1/2 clinical study of rociletinib in previously treated patients with EGFR mutant-positive advanced NSCLC. RESULTS: Of 63 patients, 60 had evaluable tissue specimens. When the tissue result was used as a reference, the sensitivity of EGFR mutation detection in urine was 72% (34 of 47 specimens) for T790M, 75% (12 of 16) for L858R, and 67% (28 of 42) for exon 19 deletions. With specimens that met a recommended volume of 90 to 100 mL, the sensitivity was 93% (13 of 14 specimens) for T790M, 80% (four of five) for L858R, and 83% (10 of 12) for exon 19 deletions. A comparable sensitivity of EGFR mutation detection was observed in plasma: 93% (38 of 41 specimens) for T790M, 100% (17 of 17) for L858R, and 87% (34 of 39) for exon 19 deletions. Together, urine and plasma testing identified 12 additional T790M-positive cases that were either undetectable or inadequate by tissue test. In nine patients monitored while receiving treatment with rociletinib, a rapid decrease in urine T790M levels was observed by day 21. CONCLUSIONS: DNA derived from NSCLC tumors can be detected with high sensitivity in urine and plasma, enabling diagnostic detection and monitoring of therapeutic response from these noninvasive "liquid biopsy" samples.

Neuronal classification and marker gene identification via single-cell expression profiling of brainstem vestibular neurons subserving cerebellar learning.

Identification of marker genes expressed in specific cell types is essential for the genetic dissection of neural circuits. Here we report a new strategy for classifying heterogeneous populations of neurons into functionally distinct types and for identifying associated marker genes. Quantitative single-cell expression profiling of genes related to neurotransmitters and ion channels enables functional classification of neurons; transcript profiles for marker gene candidates identify molecular handles for manipulating each cell type. We apply this strategy to the mouse medial vestibular nucleus (MVN), which comprises several types of neurons subserving cerebellar-dependent learning in the vestibulo-ocular reflex. Ion channel gene expression differed both qualitatively and quantitatively across cell types and could distinguish subtle differences in intrinsic electrophysiology. Single-cell transcript profiling of MVN neurons established six functionally distinct cell types and associated marker genes. This strategy is applicable throughout the nervous system and could facilitate the use of molecular genetic tools to examine the behavioral roles of distinct neuronal populations.