Purpose Third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) have demonstrated potent activity against TKI resistance mediated by EGFR T790M. We studied whether noninvasive genotyping of cell-free plasma DNA (cfDNA) is a useful biomarker for prediction of outcome from a third-generation EGFR-TKI, osimertinib. Methods Plasma was collected from all patients in the first-in-man study of osimertinib. Patients who were included had acquired EGFR-TKI resistance and evidence of a common EGFR-sensitizing mutation. Genotyping of cell-free plasma DNA was performed by using BEAMing. Plasma genotyping accuracy was assessed by using tumor genotyping from a central laboratory as reference. Objective response rate (ORR) and progression-free survival (PFS) were analyzed in all T790M-positive or T790M-negative patients. Results Sensitivity of plasma genotyping for detection of T790M was 70%. Of 58 patients with T790M-negative tumors, T790M was detected in plasma of 18 (31%). ORR and median PFS were similar in patients with T790M-positive plasma (ORR, 63%; PFS, 9.7 months) or T790M-positive tumor (ORR, 62%; PFS, 9.7 months) results. Although patients with T790M-negative plasma had overall favorable outcomes (ORR, 46%; median PFS, 8.2 months), tumor genotyping distinguished a subset of patients positive for T790M who had better outcomes (ORR, 69%; PFS, 16.5 months) as well as a subset of patients negative for T790M with poor outcomes (ORR, 25%; PFS, 2.8 months). Conclusion In this retrospective analysis, patients positive for T790M in plasma have outcomes with osimertinib that are equivalent to patients positive by a tissue-based assay. This study suggests that, upon availability of validated plasma T790M assays, some patients could avoid a tumor biopsy for T790M genotyping. As a result of the 30% false-negative rate of plasma genotyping, those with T790M-negative plasma results still need a tumor biopsy to determine presence or absence of T790M.

Importance Plasma genotyping of cell-free DNA (cfDNA) has the potential to allow for rapid noninvasive genotyping while avoiding the inherent shortcomings of tissue genotyping and repeat biopsies. Objective To prospectively validate plasma droplet digital PCR (ddPCR) for the rapid detection of common EGFR and KRAS mutations as well as the EGFR T790M acquired resistance mutation. Design Eligible patients underwent an initial blood draw and immediate plasma ddPCR for EGFR exon 19 del, L858R, T790M and/or KRAS G12X between July 2014 and June 2015. All patients underwent biopsy for tissue genotyping which was used as the reference standard for comparison; rebiopsy was required for patients with acquired resistance to EGFR kinase inhibitors. Test turnaround time (TAT) was measured in business days from blood draw until test reporting. Setting National Cancer Institute (NCI) designated comprehensive cancer center. Participants Advanced non-squamous NSCLC patients that are either (i) newly diagnosed and planned for initial therapy or (ii) have developed acquired resistance to an EGFR kinase inhibitor and are planned for re-biopsy. Main Outcome Measure Plasma ddPCR assay sensitivity, specificity and TAT. Results 180 patients were enrolled in the study (120 newly diagnosed, 60 with acquired resistance). Tumor genotype included 80 EGFR exon 19/L858R mutants, 35 EGFR T790M, 25 KRAS G12X mutants. Median TAT for plasma ddPCR was 3 days. Tissue genotyping median TAT was 12 days for newly diagnosed patients and 27 days for acquired resistance patients. Plasma ddPCR exhibited a PPV of 100% (95%CI 91-100%) for EGFR 19 del, 100% (95%CI 85-100%) L858R and 100% (95%CI 79-100%) for KRAS, but lower for T790M at 79% (95%CI 62-91%). Sensitivity of plasma ddPCR was 82% (95%CI 69-91%) for EGFR 19 del, 74% (95%CI 55-88%) for L858R and 77% (95%CI 60-90%) for T790M but lower for KRAS at 64% (95%CI 43-82%). Sensitivity for EGFR or KRAS was higher in patients with multiple metastatic sites (p=0.001) and those with hepatic (p=0.001) or bone metastases (p=0.004), specifically. Conclusion Plasma ddPCR detects EGFR and KRAS mutations rapidly with the high specificity needed to select therapy and avoid repeat biopsies. This assay may also detect EGFR T790M missed by tissue genotyping due to tumor heterogeneity in resistant disease. This is the first prospective study to demonstrate the utility of ddPCR-based plasma genotyping in advanced NSCLC.

Purpose Tumor genotyping is a powerful tool for guiding non-small cell lung cancer (NSCLC) care, however comprehensive tumor genotyping can be logistically cumbersome. To facilitate genotyping, we developed a next-generation sequencing (NGS) assay using a desktop sequencer to detect actionable mutations and rearrangements in cell-free plasma DNA (cfDNA). Experimental Design An NGS panel was developed targeting 11 driver oncogenes found in NSCLC. Targeted NGS was performed using a novel methodology that maximizes on-target reads, and minimizes artifact, and was validated on DNA dilutions derived from cell lines. Plasma NGS was then blindly performed on 48 patients with advanced, progressive NSCLC and a known tumor genotype, and explored in two patients with incomplete tumor genotyping. Results NGS could identify mutations present in DNA dilutions at ≥0.4% allelic frequency with 100% sensitivity/specificity. Plasma NGS detected a broad range of driver and resistance mutations, including ALK, ROS1, and RET rearrangements, HER2 insertions, and MET amplification, with 100% specificity. Sensitivity was 77% across 62 known driver and resistance mutations from the 48 cases; in 29 cases with common EGFR and KRAS mutations, sensitivity was similar to droplet digital PCR. In two cases with incomplete tumor genotyping, plasma NGS rapidly identified a novel EGFR exon 19 deletion and a missed case of MET amplification. Conclusion Blinded to tumor genotype, this plasma NGS approach detected a broad range of targetable genomic alterations in NSCLC with no false positives including complex mutations like rearrangements and unexpected resistance mutations such as EGFR C797S. Through use of widely available vacutainers and a desktop sequencing platform, this assay has the potential to be implemented broadly for patient care and translational research.

Amplified and/or mutated MET can act as both a primary oncogenic driver and as a promoter of tyrosine kinase inhibitor (TKI) resistance in non-small cell lung cancer (NSCLC). However, the landscape of MET-specific targeting agents remains underdeveloped and understanding of mechanisms of resistance to MET TKIs is limited. Here we present a case of a patient with lung adenocarcinoma harboring both a mutation in EGFR and an amplification of MET, who after progression on erlotinib, responded dramatically to combined MET and EGFR inhibition with savolitinib and osimertinib. When resistance developed to this combination, a new MET kinase domain mutation, D1228V, was detected. Our in vitro findings demonstrate that MET D1228V induces resistance to type I MET TKIs through impaired drug binding while sensitivity to type II MET TKIs is maintained. Based on these findings, the patient was treated with erlotinib combined with cabozantinib, a type II MET inhibitor, and exhibited a response.

Background: Noninvasive genotyping using plasma cell-free DNA (cfDNA) has the potential to obviate the need for some invasive biopsies in cancer patients while also elucidating disease heterogeneity. We sought to develop an ultra-deep plasma next-generation sequencing (NGS) assay for patients with non-small-cell lung cancers (NSCLC) that could detect targetable oncogenic drivers and resistance mutations in patients where tissue biopsy failed to identify an actionable alteration.Patients and methods: Plasma was prospectively collected from patients with advanced, progressive NSCLC. We carried out ultra-deep NGS using cfDNA extracted from plasma and matched white blood cells using a hybrid capture panel covering 37 lung cancer-related genes sequenced to 50 000Â raw target coverage filtering somatic mutations attributable to clonal hematopoiesis. Clinical sensitivity and specificity for plasma detection of known oncogenic drivers were calculated and compared with tissue genotyping results. Orthogonal ddPCR validation was carried out in a subset of cases.Results: In 127 assessable patients, plasma NGS detected driver mutations with variant allele fractions ranging from 0.14% to 52%. Plasma ddPCR for EGFR or KRAS mutations revealed findings nearly identical to those of plasma NGS in 21 of 22 patients, with high concordance of variant allele fraction (r ¼ 0.98). Blinded to tissue genotype, plasma NGS sensitivity for de novo plasma detection of known oncogenic drivers was 75% (68/91). Specificity of plasma NGS in those who were driver-negative by tissue NGS was 100% (19/19). In 17 patients with tumor tissue deemed insufficient for genotyping, plasma NGS identified four KRAS mutations. In 23 EGFR mutant cases with acquired resistance to targeted therapy, plasma NGS detected potential resistance mechanisms, including EGFR T790M and C797S mutations and ERBB2 amplification.Conclusions: Ultra-deep plasma NGS with clonal hematopoiesis filtering resulted in de novo detection of targetable oncogenic drivers and resistance mechanisms in patients with NSCLC, including when tissue biopsy was inadequate for genotyping.

Purpose Plasma cell-free DNA (cfDNA) analysis is increasingly used clinically for cancer genotyping, but may lead to incidental identification of germline risk alleles. We studied EGFR T790M mutations in non-small cell lung cancer (NSCLC) toward the aim of discriminating germline and cancer-derived variants within cfDNA. Experimental Design Patients with EGFR-mutant NSCLC, some with known germline EGFR T790M, underwent plasma genotyping. Separately, deidentified genomic data and buffy coat specimens from a clinical plasma next-generation sequencing (NGS) laboratory were reviewed and tested. Results In patients with germline T790M mutations, the T790M allelic fraction (AF) in cfDNA approximates 50%, higher than that of EGFR driver mutations. Review of plasma NGS results reveals three groups of variants: a low AF tumor group, a heterozygous group (~50% AF), and a homozygous group (~100% AF). As the EGFR driver mutation AF increases, the distribution of the heterozygous group changes, suggesting increased copy number variation from increased tumor content. Excluding cases with high copy number variation, mutations can be differentiated into somatic variants and incidentally identified germline variants. We then developed a bioinformatic algorithm to distinguish germline and somatic mutations; blinded validation in 21 cases confirmed a 100% positive predictive value for predicting germline T790M. Querying a database of 31,414 patients with plasma NGS, we identified 48 with germline T790M, 43 with non-squamous NSCLC (p<0.0001). Conclusion With appropriate bioinformatics, plasma genotyping can accurately predict the presence of incidentally detected germline risk alleles. This finding in patients indicates a need for genetic counseling and confirmatory germline testing.

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