Dual-specificity protein phosphatase DUSP4 regulates response to MEK inhibition in BRAF wild-type melanoma.

BACKGROUND: Aiming to improve treatment options for BRAF wild-type melanoma, we previously conducted the DOC-MEK study of docetaxel with MEK inhibitor (MEKi) selumetinib or placebo, revealing trends to prolongation of progression-free survival (hazard ratio 0.75, P = 0.130), and improved response rates (32% vs 14%, P = 0.059) with docetaxel plus selumetinib. NRAS status did not associate with outcome. Here, the aim was to identify novel biomarkers of response to MEKi. METHODS: A MEK 6 gene signature was quantified using NanoString and correlated with clinical outcomes. Two components of the gene signature were investigated by gene silencing in BRAF/NRAS wild-type melanoma cells. RESULTS: In melanomas of patients on the selumetinib but not the placebo arm, two gene signature components, dual-specificity protein phosphatase 4 (DUSP4) and ETS translocation variant 4 (ETV4), were expressed more highly in responders than non-responders. In vitro, ETV4 depletion inhibited cell survival but did not influence sensitivity to MEKi selumetinib or trametinib. In contrast, DUSP4-depleted cells showed enhanced cell survival and increased resistance to both selumetinib and trametinib. CONCLUSIONS: ETV4 and DUSP4 associated with clinical response to docetaxel plus selumetinib. DUSP4 depletion induced MEKi resistance, suggesting that DUSP4 is not only a biomarker but also a mediator of MEKi sensitivity. CLINICAL TRIAL REGISTRATION: DOC-MEK (EudraCT no: 2009-018153-23).

Clinically Viable Gene Expression Assays with Potential for Predicting Benefit from MEK Inhibitors.

Purpose: To develop a clinically viable gene expression assay to measure RAS/RAF/MEK/ERK (RAS-ERK) pathway output suitable for hypothesis testing in non-small cell lung cancer (NSCLC) clinical studies.Experimental Design: A published MEK functional activation signature (MEK signature) that measures RAS-ERK functional output was optimized for NSCLC in silico NanoString assays were developed for the NSCLC optimized MEK signature and the 147-gene RAS signature. First, platform transfer from Affymetrix to NanoString, and signature modulation following treatment with KRAS siRNA and MEK inhibitor, were investigated in cell lines. Second, the association of the signatures with KRAS mutation status, dynamic range, technical reproducibility, and spatial and temporal variation was investigated in NSCLC formalin-fixed paraffin-embedded tissue (FFPET) samples.Results: We observed a strong cross-platform correlation and modulation of signatures in vitro Technical and biological replicates showed consistent signature scores that were robust to variation in input total RNA; conservation of scores between primary and metastatic tumor was statistically significant. There were statistically significant associations between high MEK (P = 0.028) and RAS (P = 0.003) signature scores and KRAS mutation in 50 NSCLC samples. The signatures identify overlapping but distinct candidate patient populations from each other and from KRAS mutation testing.Conclusions: We developed a technically and biologically robust NanoString gene expression assay of MEK pathway output, compatible with the quantities of FFPET routinely available. The gene signatures identified a different patient population for MEK inhibitor treatment compared with KRAS mutation testing. The predictive power of the MEK signature should be studied further in clinical trials. Clin Cancer Res; 23(6); 1471-80. ©2016 AACRSee related commentary by Xue and Lito, p. 1365.

Correlation between MEK signature and Ras gene alteration in advanced gastric cancer.

MEK inhibitor (selumetinib) is a potent, orally active inhibitor of MAPK/ERK pathway. It is important to develop an accurate and robust method indicative of RAS pathway activity to stratify potential patients who can benefit from selumetinib treatment in gastric cancer (GC). First, we surveyed the sensitivity to selumetinib in a panel of 22 GC cell lines and correlated with MEK signature to selumetinib sensitivity. Next, we analyzed MEK signature via nanostring assay in two Asian cohorts using clinical samples (n = 218) and then performed a correlative analysis with MEK signature status and KRAS genotype in GC. MEK signature was predictive of response of selumetinib in GC cell lines regardless of KRAS mutation status. The proportion of high MEK signature by nanostring assay was 6.9% and the proportion of high MEK signature was significantly higher in KRAS altered group in a Korean cohort. None of PIK3CA altered cases belonged to high MEK signature group. MEK high signature was more prevalent in intestinal type by Lauren classification. The correlation between MEK signature, KRAS alteration and treatment response to selumetinib should be validated in prospective clinical trials.

EGFR mutation detection in ctDNA from NSCLC patient plasma: A cross-platform comparison of leading technologies to support the clinical development of AZD9291.

OBJECTIVES: To assess the ability of different technology platforms to detect epidermal growth factor receptor (EGFR) mutations, including T790M, from circulating tumor DNA (ctDNA) in advanced non-small cell lung cancer (NSCLC) patients. MATERIALS AND METHODS: A comparison of multiple platforms for detecting EGFR mutations in plasma ctDNA was undertaken. Plasma samples were collected from patients entering the ongoing AURA trial (NCT01802632), investigating the safety, tolerability, and efficacy of AZD9291 in patients with EGFR-sensitizing mutation-positive NSCLC. Plasma was collected prior to AZD9291 dosing but following clinical progression on a previous EGFR-tyrosine kinase inhibitor (TKI). Extracted ctDNA was analyzed using two non-digital platforms (cobas(®) EGFR Mutation Test and therascreen™ EGFR amplification refractory mutation system assay) and two digital platforms (Droplet Digital™ PCR and BEAMing digital PCR [dPCR]). RESULTS: Preliminary assessment (38 samples) was conducted using all four platforms. For EGFR-TKI-sensitizing mutations, high sensitivity (78-100%) and specificity (93-100%) were observed using tissue as a non-reference standard. For the T790M mutation, the digital platforms outperformed the non-digital platforms. Subsequent assessment using 72 additional baseline plasma samples was conducted using the cobas(®) EGFR Mutation Test and BEAMing dPCR. The two platforms demonstrated high sensitivity (82-87%) and specificity (97%) for EGFR-sensitizing mutations. For the T790M mutation, the sensitivity and specificity were 73% and 67%, respectively, with the cobas(®) EGFR Mutation Test, and 81% and 58%, respectively, with BEAMing dPCR. Concordance between the platforms was >90%, showing that multiple platforms are capable of sensitive and specific detection of EGFR-TKI-sensitizing mutations from NSCLC patient plasma. CONCLUSION: The cobas(®) EGFR Mutation Test and BEAMing dPCR demonstrate a high sensitivity for T790M mutation detection. Genomic heterogeneity of T790M-mediated resistance may explain the reduced specificity observed with plasma-based detection of T790M mutations versus tissue. These data support the use of both platforms in the AZD9291 clinical development program.

Evaluating Robustness and Sensitivity of the NanoString Technologies nCounter Platform to Enable Multiplexed Gene Expression Analysis of Clinical Samples.

Analysis of clinical trial specimens such as formalin-fixed paraffin-embedded (FFPE) tissue for molecular mechanisms of disease progression or drug response is often challenging and limited to a few markers at a time. This has led to the increasing importance of highly multiplexed assays that enable profiling of many biomarkers within a single assay. Methods for gene expression analysis have undergone major advances in biomedical research, but obtaining a robust dataset from low-quality RNA samples, such as those isolated from FFPE tissue, remains a challenge. Here, we provide a detailed evaluation of the NanoString Technologies nCounter platform, which provides a direct digital readout of up to 800 mRNA targets simultaneously. We tested this system by examining a broad set of human clinical tissues for a range of technical variables, including sensitivity and limit of detection to varying RNA quantity and quality, reagent performance over time, variability between instruments, the impact of the number of fields of view sampled, and differences between probe sequence locations and overlapping genes across CodeSets. This study demonstrates that Nanostring offers several key advantages, including sensitivity, reproducibility, technical robustness, and utility for clinical application.