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Figure 1.
Study Enrollment Flow Diagram
Study Enrollment Flow Diagram

QC indicates quality control.

Figure 2.
Clinical Outcomes Associated With Dabrafenib-Trametinib Combination Treatment (CombiDT)
Clinical Outcomes Associated With Dabrafenib-Trametinib Combination Treatment (CombiDT)

A, Waterfall plot of maximum tumor reduction associated with CombiDT treatment. Each bar represents a single patient (only 19 bars presented because patient 9 had progression of nontarget lesions, had no measurement of target lesion at progression, and so is not included in the plot); the RECIST thresholds are as defined by Eisenhauer et al.19 Unless otherwise noted, all patients had BRAF V600E mutations. CR indicates confirmed complete response; PD, progressive disease; PR, confirmed partial response; SD, stable disease. B, Kaplan-Meier analysis of progression-free survival (PFS) for all patients treated with CombiDT. C, Kaplan-Meier PFS for patients whose prior BRAF inhibitor monotherapy (BRAFi) lasted 6 months or less vs longer than 6 months. D, Log2 ratio of levels of circulating BRAF V600 mutation in blood at cycle 1, day 8 (C1D8) of CombiDT compared with baseline in patients who did or did not achieve disease control (DC). The log2 ratio was less than 0 in 6 of 8 patients who achieved DC but in only 2 of 11 patients who did not (P = .02 by Fisher exact test).

Figure 3.
Pretreatment Molecular Features and Clinical Outcomes Associated With Dabrafenib-Trametinib Combination Treatment (CombiDT)
Pretreatment Molecular Features and Clinical Outcomes Associated With Dabrafenib-Trametinib Combination Treatment (CombiDT)

Baseline tumor biopsy specimens from 13 patients were subjected to extensive analysis. From the top to the bottom are illustrated findings of clinical evaluation (PFS and prior BRAFi), selected mutations (WES), BRAF splicing (RT-PCR), mutation burden (WES), copy number variations (WES), and baseline pMAPK and CD8 immune scores (IHC). The asterisk at patient 22 indicates that pMAPK and immune scores were not available for this patient; BRAFi, BRAF inhibitor therapy; IHC, immunohistochemical analysis; Non syn, nonsynonymous; PFS, progression-free survival; pMAPK, phosphorylated mitogen-activated protein kinase; RT-PCR, reverse transcription polymerase chain reaction analysis; Syn, synonymous; WES, whole-exome sequencing.

Figure 4.
MAPK Activity and Immune Infiltrate Findings in Association With CombiDT Therapy
MAPK Activity and Immune Infiltrate Findings in Association With CombiDT Therapy

A, Representative IHC specimens of pMAPK expression from baseline, early CombiDT treatment, and at disease progression on treatment. Dynamic changes in pMAPK were observed in patient 27, who achieved a partial response and then disease progression; no significant pMAPK inhibition was observed in patient 20, who experienced disease progression as best response (original magnification ×100 for all specimens but on-treatment patient 27 [×200]). B, Scores of pMAPK in baseline and on-treatment tumor specimens from 6 patients with paired evaluable samples; 3 of the 6 patients had no decrease in pMAPK with CombiDT. C, Heatmap of log2 gene expression (mean-centered) of 14 known BRAF V600–driven transcriptional targets of MAPK in samples of 12 BRAF V600 tumors analyzed by RNAseq. Blue (negative) and yellow (positive) rectangles are log2 gene expression values of each gene in each sample; the color scale at the bottom indicates the dynamic range of the heatmap. The MAPK z score represents the normalized and averaged expression level of the 14 genes: red indicates high activity; blue, low activity; T1, T2, and T3 indicate tumor number; and the red and black arrows point from baseline tumors to their matched on-treatment tumors. Patients 1 and 14, who were not evaluable for on-treatment MAPK inhibition by IHC, showed no decrease in MAPK z score after CombiDT. D, IHC-determined CD8 fraction in baseline (circles; n = 14) and on-treatment (triangles; n = 8) tumor specimens. Matched tumors from the same patient are connected by solid lines with arrowheads pointing to the on-treatment tumor. CombiDT indicates dabrafenib-trametinib combination treatment; IHC, immunohistochemical analysis; pMAPK, phosphorylated mitogen-activated protein kinase; Pt, patient; RNAseq, RNA sequencing.

Table.  
Patient Demographic and Clinical Characteristics
Patient Demographic and Clinical Characteristics
1.
Cancer Genome Atlas Network.  Genomic classification of cutaneous melanoma.  Cell. 2015;161(7):1681-1696.PubMedGoogle ScholarCrossref
2.
Davies  H, Bignell  GR, Cox  C,  et al.  Mutations of the BRAF gene in human cancer.  Nature. 2002;417(6892):949-954.PubMedGoogle ScholarCrossref
3.
Robert  C, Karaszewska  B, Schachter  J,  et al.  Improved overall survival in melanoma with combined dabrafenib and trametinib.  N Engl J Med. 2015;372(1):30-39.PubMedGoogle ScholarCrossref
4.
Larkin  J, Ascierto  PA, Dréno  B,  et al.  Combined vemurafenib and cobimetinib in BRAF-mutated melanoma.  N Engl J Med. 2014;371(20):1867-1876.PubMedGoogle ScholarCrossref
5.
Poulikakos  PI, Persaud  Y, Janakiraman  M,  et al.  RAF inhibitor resistance is mediated by dimerization of aberrantly spliced BRAF(V600E).  Nature. 2011;480(7377):387-390.PubMedGoogle ScholarCrossref
6.
Shi  H, Moriceau  G, Kong  X,  et al.  Melanoma whole-exome sequencing identifies (V600E)B-RAF amplification-mediated acquired B-RAF inhibitor resistance.  Nat Commun. 2012;3:724.PubMedGoogle ScholarCrossref
7.
Shi  H, Hugo  W, Kong  X,  et al.  Acquired resistance and clonal evolution in melanoma during BRAF inhibitor therapy.  Cancer Discov. 2014;4(1):80-93.PubMedGoogle ScholarCrossref
8.
Nazarian  R, Shi  H, Wang  Q,  et al.  Melanomas acquire resistance to B-RAF(V600E) inhibition by RTK or N-RAS upregulation.  Nature. 2010;468(7326):973-977.PubMedGoogle ScholarCrossref
9.
Emery  CM, Vijayendran  KG, Zipser  MC,  et al.  MEK1 mutations confer resistance to MEK and B-RAF inhibition.  Proc Natl Acad Sci U S A. 2009;106(48):20411-20416.PubMedGoogle ScholarCrossref
10.
Carlino  MS, Fung  C, Shahheydari  H,  et al.  Preexisting MEK1P124 mutations diminish response to BRAF inhibitors in metastatic melanoma patients.  Clin Cancer Res. 2015;21(1):98-105.PubMedGoogle ScholarCrossref
11.
Wagle  N, Emery  C, Berger  MF,  et al.  Dissecting therapeutic resistance to RAF inhibition in melanoma by tumor genomic profiling.  J Clin Oncol. 2011;29(22):3085-3096.PubMedGoogle ScholarCrossref
12.
Johannessen  CM, Boehm  JS, Kim  SY,  et al.  COT drives resistance to RAF inhibition through MAP kinase pathway reactivation.  Nature. 2010;468(7326):968-972.PubMedGoogle ScholarCrossref
13.
Villanueva  J, Vultur  A, Lee  JT,  et al.  Acquired resistance to BRAF inhibitors mediated by a RAF kinase switch in melanoma can be overcome by cotargeting MEK and IGF-1R/PI3K.  Cancer Cell. 2010;18(6):683-695.PubMedGoogle ScholarCrossref
14.
Paraiso  KH, Fedorenko  IV, Cantini  LP,  et al.  Recovery of phospho-ERK activity allows melanoma cells to escape from BRAF inhibitor therapy.  Br J Cancer. 2010;102(12):1724-1730.PubMedGoogle ScholarCrossref
15.
Kwong  LN, Boland  GM, Frederick  DT,  et al.  Co-clinical assessment identifies patterns of BRAF inhibitor resistance in melanoma.  J Clin Invest. 2015;125(4):1459-1470.PubMedGoogle ScholarCrossref
16.
Knight  DA, Ngiow  SF, Li  M,  et al.  Host immunity contributes to the anti-melanoma activity of BRAF inhibitors.  J Clin Invest. 2013;123(3):1371-1381.PubMedGoogle ScholarCrossref
17.
Long  GV, Stroyakovskiy  D, Gogas  H,  et al.  Combined BRAF and MEK inhibition versus BRAF inhibition alone in melanoma.  N Engl J Med. 2014;371(20):1877-1888.PubMedGoogle ScholarCrossref
18.
Johnson  DB, Flaherty  KT, Weber  JS,  et al.  Combined BRAF (dabrafenib) and MEK inhibition (trametinib) in patients with BRAFV600-mutant melanoma experiencing progression with single-agent BRAF inhibitor.  J Clin Oncol. 2014;32(33):3697-3704.PubMedGoogle ScholarCrossref
19.
Eisenhauer  EA, Therasse  P, Bogaerts  J,  et al.  New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1).  Eur J Cancer. 2009;45(2):228-247.PubMedGoogle ScholarCrossref
20.
Trotti  A, Colevas  AD, Setser  A,  et al.  CTCAE v3.0: development of a comprehensive grading system for the adverse effects of cancer treatment.  Semin Radiat Oncol. 2003;13(3):176-181.PubMedGoogle ScholarCrossref
21.
Cancer Genome Atlas Network.  Comprehensive molecular portraits of human breast tumours.  Nature. 2012;490(7418):61-70.PubMedGoogle ScholarCrossref
22.
Panka  DJ, Buchbinder  E, Giobbie-Hurder  A,  et al.  Clinical utility of a blood-based BRAF(V600E) mutation assay in melanoma.  Mol Cancer Ther. 2014;13(12):3210-3218.PubMedGoogle ScholarCrossref
23.
Pratilas  CA, Taylor  BS, Ye  Q,  et al.  (V600E)BRAF is associated with disabled feedback inhibition of RAF-MEK signaling and elevated transcriptional output of the pathway.  Proc Natl Acad Sci U S A. 2009;106(11):4519-4524.PubMedGoogle ScholarCrossref
24.
Chen  K, Meric-Bernstam  F, Zhao  H,  et al.  Clinical actionability enhanced through deep targeted sequencing of solid tumors.  Clin Chem. 2015;61(3):544-553.PubMedGoogle ScholarCrossref
25.
The R Foundation R: a language and environment for statistical computing. 2015; https://www.R-project.org/. Accessed June 4, 2015.
26.
Bollag  G, Hirth  P, Tsai  J,  et al.  Clinical efficacy of a RAF inhibitor needs broad target blockade in BRAF-mutant melanoma.  Nature. 2010;467(7315):596-599.PubMedGoogle ScholarCrossref
27.
Trunzer  K, Pavlick  AC, Schuchter  L,  et al.  Pharmacodynamic effects and mechanisms of resistance to vemurafenib in patients with metastatic melanoma.  J Clin Oncol. 2013;31(14):1767-1774.PubMedGoogle ScholarCrossref
28.
Morris  EJ, Jha  S, Restaino  CR,  et al.  Discovery of a novel ERK inhibitor with activity in models of acquired resistance to BRAF and MEK inhibitors.  Cancer Discov. 2013;3(7):742-750.PubMedGoogle ScholarCrossref
29.
Johnson  DB, Menzies  AM, Zimmer  L,  et al.  BRAF inhibitor acquired resistance: a multicenter meta-analysis of the spectrum and clinical implications of resistance mechanisms.  J Clin Oncol. 2015;33(suppl):abstract 9008.Google Scholar
30.
Carlino  MS, Todd  JR, Gowrishankar  K,  et al.  Differential activity of MEK and ERK inhibitors in BRAF inhibitor resistant melanoma.  Mol Oncol. 2014;8(3):544-554.PubMedGoogle ScholarCrossref
31.
Wagle  N, Van Allen  EM, Treacy  DJ,  et al.  MAP kinase pathway alterations in BRAF-mutant melanoma patients with acquired resistance to combined RAF/MEK inhibition.  Cancer Discov. 2014;4(1):61-68.PubMedGoogle ScholarCrossref
32.
Watson  IR, Li  L, Cabeceiras  PK,  et al.  The RAC1 P29S hotspot mutation in melanoma confers resistance to pharmacological inhibition of RAF.  Cancer Res. 2014;74(17):4845-4852.PubMedGoogle ScholarCrossref
33.
Frederick  DT, Piris  A, Cogdill  AP,  et al.  BRAF inhibition is associated with enhanced melanoma antigen expression and a more favorable tumor microenvironment in patients with metastatic melanoma.  Clin Cancer Res. 2013;19(5):1225-1231.PubMedGoogle ScholarCrossref
Original Investigation
August 2016

Clinical, Molecular, and Immune Analysis of Dabrafenib-Trametinib Combination Treatment for BRAF Inhibitor–Refractory Metastatic Melanoma: A Phase 2 Clinical Trial

Author Affiliations
  • 1Department of Melanoma Medical Oncology, University of Texas MD Anderson Cancer Center, Houston
  • 2Division of Cancer Medicine, University of Texas MD Anderson Cancer Center, Houston
  • 3Beth Israel Deaconess Medical Center, Boston, Massachusetts
  • 4Departments of Pathology and Translational and Molecular Pathology, University of Texas MD Anderson Cancer Center, Houston
  • 5Broad Institute, Cambridge, Massachusetts
  • 6Department of Surgical Oncology, University of Texas MD Anderson Cancer Center, Houston
  • 7Department of Genomic Medicine, University of Texas MD Anderson Cancer Center, Houston
  • 8Department of Biostatistics, University of Texas MD Anderson Cancer Center, Houston
  • 9Massachusetts General Hospital, Boston
  • 10California Pacific Medical Center Research Institute, San Francisco
  • 11Department of Systems Biology, University of Texas MD Anderson Cancer Center, Houston
JAMA Oncol. 2016;2(8):1056-1064. doi:10.1001/jamaoncol.2016.0509
Abstract

Importance  Combined treatment with dabrafenib and trametinib (CombiDT) achieves clinical responses in only about 15% of patients with BRAF inhibitor (BRAFi)-refractory metastatic melanoma in contrast to the higher response rate observed in BRAFi-naïve patients. Identifying correlates of response and mechanisms of resistance in this population will facilitate clinical management and rational therapeutic development.

Objective  To determine correlates of benefit from CombiDT therapy in patients with BRAFi-refractory metastatic melanoma.

Design, Setting, and Participants  Single-center, single-arm, open-label phase 2 trial of CombiDT treatment in patients with BRAF V600 metastatic melanoma resistant to BRAFi monotherapy conducted between September 2012 and October 2014 at the University of Texas MD Anderson Cancer Center. Key eligibility criteria for participants included BRAF V600 metastatic melanoma, prior BRAFi monotherapy, measurable disease (RECIST 1.1), and tumor accessible for biopsy.

Interventions  Patients were treated with dabrafenib (150 mg, twice daily) and trametinib (2 mg/d) continuously until disease progression or intolerance. All participants underwent a mandatory baseline biopsy, and optional biopsy specimens were obtained on treatment and at disease progression. Whole-exome sequencing, reverse transcription polymerase chain reaction analysis for BRAF splicing, RNA sequencing, and immunohistochemical analysis were performed on tumor samples, and blood was analyzed for levels of circulating BRAF V600.

Main Outcomes and Measures  The primary end point was overall response rate (ORR). Progression-free survival (PFS) and overall survival (OS) were secondary clinical end points.

Results  A total of 28 patients were screened, and 23 enrolled. Among evaluable patients, the confirmed ORR was 10%; disease control rate (DCR) was 45%, and median PFS was 13 weeks. Clinical benefit was associated with duration of prior BRAFi therapy greater than 6 months (DCR, 73% vs 11% for ≤6 months; P = .02) and decrease in circulating BRAF V600 at day 8 of cycle 1 (DCR, 75% vs 18% for no decrease; P = .02) but not with pretreatment mitogen-activated protein kinase (MAPK) pathway mutations or activation. Biopsy specimens obtained during treatment demonstrated that CombiDT therapy failed to achieve significant MAPK pathway inhibition or immune infiltration in most patients.

Conclusions and Relevance  The baseline presence of MAPK pathway alterations was not associated with benefit from CombiDT in patients with BRAFi-refractory metastatic melanoma. Failure to inhibit the MAPK pathway provides a likely explanation for the limited clinical benefit of CombiDT in this setting. Circulating BRAF V600 is a promising early biomarker of clinical response.

Trial Registration  clinicaltrials.gov Identifier: NCT01619774.

Introduction

Approximately 50% of cutaneous melanomas harbor a somatic BRAF V600 mutation that activates the mitogen-activated protein kinase (MAPK) signaling pathway.1,2 Two mutant-selective BRAF inhibitors (BRAFi), dabrafenib and vemurafenib, that have been approved by the US Food and Drug Administration for treating BRAF V600 metastatic melanoma achieve RECIST-criteria responses in about 50% of patients and disease control in about 90%.3,4 However, the development of resistance is nearly inevitable, and the median duration of response for these agents is approximately 6 months.

Multiple molecular changes that cause reactivation of MAPK pathway signaling have been identified in melanomas with acquired resistance to BRAFi treatment. These include alternate BRAF splicing or amplification,5-7NRAS and MEK mutations,8-11 and COT overexpression.12 Resistance can also be mediated by epigenetic upregulation of receptor tyrosine kinases (RTKs).8 Preclinical studies have demonstrated that combining BRAFi and MEK inhibitors (MEKi) can often both overcome such resistance mechanisms and forestall acquired resistance.8,9,12-14 In addition, there is growing evidence that the antitumor immune response is important to the clinical activity of BRAFi.4,15,16

Clinical studies have demonstrated that combined BRAFi and MEKi (BRAFi + MEKi) therapy in BRAFi-naïve patients with BRAF V600–mutant melanoma achieves response rates of around 70%, disease control rates (DCR) of greater than 90%, and median progression-free survival (PFS) of 10 to 12 months.3,17 However, in patients with BRAF V600–mutant melanoma who have developed resistance to BRAFi, the response rate to BRAFi + MEKi therapy is only about 15%.18 It is unclear which BRAFi-refractory patients would likely benefit from BRAFi + MEKi therapy. Furthermore, it is unknown why the combination has low activity in this setting.

We conducted a prospective phase 2 trial of dabrafenib (BRAFi) and trametinib (MEKi) combination (CombiDT) therapy in patients with metastatic melanoma whose disease previously progressed on single-agent BRAFi therapy. Biospecimens collected as part of this trial underwent integrated multiplatform analysis of tumor biopsy and serum specimens to elucidate molecular mechanisms of resistance and correlates of response. We report here the clinical outcomes and molecular and immunological effects of CombiDT therapy in these patients.

Box Section Ref ID

Key Points

  • Question Can analysis of clinical, molecular, and immunological characteristics of patients with melanoma refractory to BRAF inhibitor (BRAFi) therapy identify those who will respond to combined dabrafenib and trametinib (CombiDT) therapy?

  • Findings In this phase 2 clinical trial, CombiDT clinical benefit was associated with duration of prior BRAFi therapy greater than 6 months and early decrease in circulating BRAF V600 but not with baseline tumor molecular characteristics. CombiDT treatment failed to achieve significant MAPK (mitogen-activated protein kinase) pathway inhibition or immune infiltration in most patients.

  • Meaning Patients with longer duration of benefit on BRAFi monotherapy may benefit from salvage CombiDT treatment, and changes in circulating BRAF V600 may be an early surrogate of benefit.

Methods
Clinical Trial

This open-label, phase 2 study of CombiDT therapy in patients with BRAF V600–mutant metastatic melanoma resistant to BRAFi monotherapy was approved by the University of Texas MD Anderson Cancer Center institutional review board. Patients were recruited from a tertiary cancer hospital and provided their written informed consent for participation. The trial protocol is available in Supplement 1.

Inclusion criteria included age 16 years or older; Eastern Cooperative Oncology Group (ECOG) performance status, 0 to 2; histologically confirmed stage IV or unresectable stage III melanoma with a BRAF V600 mutation; disease progression on single-agent vemurafenib or dabrafenib therapy; measurable disease defined by RECIST 1.119; at least 1 tumor accessible for biopsy; adequate organ function; no active brain or leptomeningeal metastasis within 4 weeks; and no history of significant cardiac or ocular illness.

Patients were treated with dabrafenib (150 mg, twice daily) and trametinib (2 mg/d) continuously until disease progression or intolerance. Treatment response was assessed by RECIST 1.119 every 2 cycles (8 weeks). Severity of toxic effects was graded according to National Cancer Institute Common Terminology Criteria for Adverse Events (version 4.0).20

Biospecimens

Mandatory baseline tumor biopsy specimens were collected 0 to 4 days before the first doses of study drugs were administered. Optional tumor biopsies were performed between days 4 and 10 of cycle 1 and at time of disease progression. Blood samples were collected at baseline, on cycle 1 day 8 (C1D8), and intermittently thereafter.

Tumor biopsy specimens were divided, and the parts were treated in 2 different ways: two-thirds of each specimen was frozen in optimal cutting temperature compound, and one-third was formalin fixed and paraffin embedded. A hematoxylin-eosin–stained slide from each block was subjected to pathology review to determine the percentage of viable tumor cells. Frozen samples with greater than 70% viable tumor cells were subjected to DNA and RNA extraction, as previously described.21 Peripheral blood mononuclear cells (PBMCs) isolated from blood were subjected to total RNA isolation using the mirVana miRNA Isolation Kit (AM1560; Thermo Fischer Scientific Inc).

Molecular and Immune Analyses

The amount of circulating BRAF V600 was determined from PBMC-derived RNA as previously described.22BRAF splice variants were detected by reverse transcription polymerase chain reaction analysis (RT-PCR), as previously described.5 Whole-exome sequencing (WES) and RNA sequencing (RNAseq) were performed at the Broad Institute (eMethods in Supplement 2). MAPK z scores were determined by averaging normalized RNAseq gene expression of 14 known transcriptional targets of MAPK in BRAF V600–mutant melanoma15,23; immune z scores were determined using 105 genes that define the high-immune cluster of The Cancer Genome Atlas melanoma samples.1 Targeted next-generation sequencing of 200 cancer-related genes (T200) was performed as previously described.24 Immunohistochemical analysis (IHC) of formalin-fixed, paraffin-embedded tumor tissues was performed using antibodies against BRAF V600E, phosphorylated MAPK (pMAPK) (extracellular signal-related kinases 1/2 [ERK1/2]), phosphorylated S6 ribosomal protein (pS6), phosphorylated proline-rich Akt substrate of 40 kDa (pPRAS40), CD8, and programmed cell death ligand 1 (PD-L1). Scores were determined by multiplying pathologist-assessed IHC intensity with fraction of positive cells.

Statistical Analysis

The trial was designed to enroll 30 patients, with a target response rate of 25%, and with interim efficacy and safety monitoring. Though the prespecified stopping criteria were not met, this trial was terminated early owing to slowed accrual following approval of front-line CombiDT therapy. The primary efficacy end point was response rate by RECIST1.1.19 Overall survival (OS) and PFS were secondary end points. Kaplan-Meier curves were used to estimate the distribution of PFS and OS, and distributions were compared using the log-rank test. Univariate Cox proportional hazards regression was used to assess the association between PFS and the covariates of interest (age, sex, stage, lactate dehydrogenase [LDH] level, performance status, BRAF mutation, duration of BRAFi monotherapy, response to BRAFi monotherapy, interval from BRAFi monotherapy, and baseline molecular features). Univariate logistic regression and/or the Fisher exact test were used to assess the association between DCR and the same covariates. Pearson correlation analysis was used to assess the correlation between IHC and MAPK/immune scores. P < .05 was considered significant. R (version 3.2.2)25 and Prism 6 (GraphPad Software) were used for data analysis.25

Results
Patient Characteristics and Clinical Outcomes

Twenty-three patients were treated between September 28, 2012, and October 23, 2014 (Figure 1); 14 patients (61%) had IVc disease, and 9 (39%) had elevated LDH (Table). The majority (87%; n = 20) had a BRAF V600E mutation. With prior BRAFi monotherapy, 78% of patients (n = 18) had a confirmed response and 57% (n = 13) had duration of response greater than 6 months. Most patients (n = 20) had no interval between BRAFi monotherapy and CombiDT initiation; the intertreatment intervals for the 3 patients ranged from 3.5 to 12.0 months.

Among the 20 patients evaluable for response, 6 (30%) achieved transient clinical responses (1 complete response, 5 partial responses) (Figure 2A). However, only 2 patients (10%) had confirmed responses on consecutive computed tomography scans; 7 patients had confirmed stable disease, for an overall DCR of 45% (95% CI, 23%-68%) (eTable 1 in Supplement 2). The median PFS was 13 weeks (95% CI, 8-16 weeks) (Figure 2B). With a median follow-up of 5.9 months, the median OS was 10.2 months (95% CI, 4.9-not reached [median OS longer than median follow-up and thus could not be estimated]) (eFigure 1 in Supplement 2). The spectrum and rate of adverse events were similar to those reported previously with CombiDT17 (eTable 2 in Supplement 2), and only 3 patients required dose reduction.

Clinical Features and Circulating BRAF as Correlates of Response

Progression-free survival and DCR did not correlate significantly with LDH level, disease stage, BRAF mutation, performance status, prior immunotherapy, or interval from prior BRAFi monotherapy (eTable 3 in Supplement 2). Patients with duration of prior BRAFi monotherapy greater than 6 months had longer PFS (median, 16 vs 8 weeks; hazard ratio [HR], 0.29; P = .01) (Figure 2C) and higher DCR (73% vs 11%; odds ratio, 21.3; P = .02). Patients who had progressive disease as best response to prior BRAFi monotherapy had shorter PFS with CombiDT than patients who had achieved disease control (median, 8 vs 16 weeks; P = .04). A decrease in the level of circulating BRAF V600 at C1D8 was associated with improved disease control (75% DCR for C1D8-to-baseline BRAF V600 log2 ratio <0 vs 18% with ratio >0; P= .02) (Figure 2D).

BRAFi Resistance Mechanisms and Clinical Outcomes With CombiDT

Thirteen patients had DNA extracted from baseline tumor biopsy specimens of sufficient quality and amount for analysis by both WES and T200; 2 additional patients had T200 alone.24 Thirteen patients had tumor RNA sufficient for analysis by RT-PCR for BRAF alternative splicing. The results of these analyses are shown in Figure 3 (full WES results in eTable 5 in Supplement 2).

Alterations known to mediate BRAFi resistance by reactivating the MAPK pathway were detected at baseline in 5 (33%) of 15 evaluable patients, including NRAS Q61R (patient 19), NRAS G13R (patient 20), and MAP2K1 E203K (patient 18) mutations; BRAF amplification (patients 2 and 12); and BRAF aberrant splicing (patient 2 [in-frame insertion between exons 4 and 5] and patient 18 [skipping of exon 2]) (Figure 3). There was no significant difference in PFS (HR, 0.59; 95% CI, 0.18-1.88; P = .73) or DCR (OR, 1.50; 95% CI, 0.16-14.42; P = .36) associated with CombiDT therapy between patients with or without these alterations, nor did they correlate with baseline clinical characteristics or duration of prior BRAFi monotherapy.

Other genetic aberrations previously implicated in either melanoma pathogenesis or MAPK pathway inhibitor resistance are indicated in Figure 3. Two patients with baseline RAC1 P29S mutation had disease progression as their best response to CombiDT; both patients also received BRAFi monotherapy for 6 months or less.

WES of the CombiDT baseline sample for patient 9 failed to detect the presence of a BRAF mutation, although a BRAF V600E mutation had been detected in the primary tumor, and the patient had a complete response to prior vemurafenib monotherapy. No BRAF V600 mutation was detectable in the pre-CombiDT sample (which had approximately 80% tumor content on pathology review) by T200 sequencing (621 reads), RNAseq, or BRAF V600E IHC. Interestingly, high levels of circulating BRAF V600 were detected in the blood before and during CombiDT therapy, suggesting that the patient likely had both BRAF V600E–mutant and BRAF wild-type clones/metastases, although no other tumor samples were available for confirmatory analysis. This patient’s disease rapidly progressed on CombiDT therapy.

Patient 27 was evaluable for acquired resistance to CombiDT: the patient achieved a partial response and had evaluable baseline, on-treatment, and disease progression tumor biopsy specimens. WES of the lesion progressing on CombiDT therapy detected an NRAS Q61K mutation that was not present in the pre-CombiDT lesion. Notably, both patients (19 and 20) with an activating NRAS mutation in their pre-CombiDT tumor had disease progression as best response with CombiDT.

Direct Analysis of MAPK Pathway Activity

MAPK pathway activity was assessed directly by pMAPK (pERK1/2) IHC of formalin-fixed, paraffin-embedded tumor samples and transcriptionally by MAPK transcriptional output (z score) by RNAseq on available frozen tumor specimens (n = 14) (Figure 4A-C). The pMAPK IHC scores and MAPK z scores were highly concordant (R2 = 0.8, P = .003) in tumors with sufficient tissues for both assays (n = 8) (eFigure 2 in Supplement 2). Combining the results from the 2 methods, we found that 15 patients were evaluable for MAPK activity in their baseline tumors. Ten of the 15 patients had high baseline MAPK activity (pMAPK IHC score above the mean or MAPK z score >0). There was no significant difference in either PFS (HR, 0.81; 95% CI, 0.27-2.46; P = .71) or DCR (OR 1.20; 95% CI, 0.13-11.05; P > .99) between these patients and those without baseline MAPK activation.

Eight patients had both baseline and on-treatment biopsy specimens suitable for MAPK activity analysis. Analysis of the paired tumors demonstrated that 5 (63%) of 8 patients did not achieve MAPK inhibition on CombiDT therapy (Figure 4B and C). Patient 27 was the only patient to achieve greater than 90% inhibition of pMAPK, which was previously shown to correlate with clinical response with single-agent BRAFi therapy.26 This patient achieved a partial response, and at disease progression had a new NRAS Q61K mutation (Figure 3) and reactivation of MAPK signaling (Figure 4A).

Signaling by the mTOR complex (mechanistic target of rapamycin) was assessed by IHC for pS6. High pS6 expression, which was identified in 7 of 12 evaluable pretreatment samples, did not correlate significantly with PFS (HR, 1.76; 95% CI, 0.50-6.28; P = .38) or DCR (OR, 0.30; 95% CI, 0.02-4.91; P > .99) (eTable 4 in Supplement 2). Increased expression of pPRAS40, a marker of activation of the PI3K-AKT pathway, was elevated in specimens from 3 of 7 evaluable patients and correlated with a nonsignificant trend for shorter PFS (HR, 5.72; 95% CI, 0.58-56.21; P = .13) (eFigure 3 in Supplement 2).

Analyses of Tumor Immune Infiltration

Tumor biopsy specimens were analyzed by IHC to quantify CD8-positive T-cell infiltration and by RNAseq for immune-related gene expression to assess the antitumor immune response. The estimated fraction of CD8-positive cells by IHC correlated with z scores for genes overexpressed by The Cancer Genome Atlas “high-immune” tumors (R2 = 0.7; P = .004) (eFigure 2 in Supplement 2).1 Of 14 baseline tumors evaluated by IHC, only 1 (patient 02) had greater than 5% infiltration by CD8-positive T cells. This patient, who also achieved inhibition of pMAPK, demonstrated a marked increase in CD8-positive T-cell infiltration with CombiDT treatment and achieved stable disease (Figure 4D; eFigure 4A in Supplement 2). None of the other 8 patients with matched baseline and on-treatment samples developed increased immune infiltrate, as detected by IHC (Figure 4D) or RNAseq (eFigure 4B and C in Supplement 2).

Analysis by IHC revealed a lack of PD-L1 expression (≤2% of tumor cells) in 10 of 13 baseline tumors analyzed (eFigure 5 in Supplement 2). Only 1 of 6 patients with matched baseline and on-treatment tumors demonstrated an increase in PD-L1 with CombiDT therapy (patient 20).

Discussion

To our knowledge, this study represents the first prospective interrogation of the molecular, immunologic, and circulating correlates of response and mechanisms of resistance to CombiDT therapy in patients with BRAFi-refractory metastatic melanoma. This multiple-platform analysis of biospecimens allows for in-depth characterization of the heterogeneity of response and resistance to CombiDT in these patients. Our findings underscore the heterogeneity of BRAFi-resistant metastatic melanoma and provide new insights into the lack of efficacy of CombiDT therapy in this population.

The treatment outcomes in this trial (10% confirmed response, 45% DCR) are similar to a recent larger independent study of patients with BRAFi-refractory melanoma treated with CombiDT that did not require baseline biopsies.18 Improved outcomes with CombiDT in patients previously treated with BRAFi monotherapy for more than 6 months compared with 6 months or less have been observed in both studies, suggesting a potential clinical selection criteria for CombiDT.18 Notably, we did not observe any significant clinical differences between these groups at the start of CombiDT treatment in factors known to correlate with outcomes in advanced melanoma (ie, stage, LDH level).

Decrease in the level of mutant BRAF RNA in the blood after only 1 week of treatment correlated with better DCR. This result is consistent with previous findings in the front-line BRAFi monotherapy setting.22 Further validation is needed to confirm the utility of this highly sensitive and specific blood-based assay. However, our results suggest that such assays could contribute substantially to therapeutic development in BRAFi-refractory patients because early blood-based markers of efficacy could lead to rapid identification of effective therapies and spare patients prolonged treatment with ineffective therapies.

We hypothesized that the presence of baseline molecular events that reactivate the MAPK pathway would predict clinical benefit from CombiDT in BRAFi-refractory melanoma because multiple studies have shown efficacy with BRAFi + MEKi in preclinical models.8,12,13 However, neither the presence of mechanisms of resistance that reactivate the MAPK pathway nor direct assessment of MAPK activity correlated significantly with outcomes. This is likely due to the failure of CombiDT to meaningfully inhibit the pathway in this setting, demonstrated here for the first time by our analysis of on-treatment tumor specimens. This lack of pathway inhibition contrasts with the nearly universal pathway inhibition observed in BRAFi-naïve patients with metastatic melanoma treated with MAPK pathway inhibitors.27 It remains unclear why CombiDT fails to achieve pathway inhibition in most BRAFi-refractory patients, but our results support the critical need to obtain such biopsies to interpret results in future trials with other agents predicted to inhibit the pathway, such as ERK inhibitors.28 Furthermore, the failure to identify a putative genetic mechanism of resistance in every patient is consistent with prior studies and supports the need for inclusion of other platforms (ie, epigenetics) in investigating resistance.7

Our in-depth characterization also resulted in informative observations in individual patients. NRAS mutations are detected in about 20% of melanomas with acquired resistance to BRAFi monotherapy,7 and BRAFi + MEKi overcomes this resistance mechanism in preclinical models.8 However, we observed a new NRAS Q61K mutation in a progressing lesion of a patient who initially responded to CombiDT therapy, which corresponded with reactivation of MAPK signaling. Moreover, both patients in the study with pretreatment NRAS mutations failed to respond to CombiDT. These results are consistent with a recent retrospective analysis of patients with melanoma characterized by mechanisms of resistance to BRAFi29 and together support the need for alternative strategies to overcome resistance mediated by NRAS mutations.28,30 Our cohort also included 2 patients with baseline RAC1 P29S mutations, both of whom had disease progression as the best response with CombiDT therapy. The RAC1 P29S mutation is enriched in patients with rapid progression on BRAFi monotherapy31 and has been shown to mediate resistance to single-agent BRAFi and single-agent MEKi in preclinical models.32 Our observed clinical resistance to CombiDT provides further validation that RAC1 P29S is a clinically significant target and supports the need for therapies to overcome it.

Our cohort also included 1 patient with a tumor biopsied after progression on BRAFi monotherapy in which no BRAF V600 mutation could be detected by next-generation sequencing, RNAseq, or IHC. This patient had a documented BRAF V600E mutation in the primary melanoma, previously had a complete response to vemurafenib monotherapy lasting 7 months, and had mutant BRAF RNA detected in circulating blood. This finding again underscores the potential heterogeneity of BRAFi-refractory melanoma, including of different tumors within individual patients and the potential clinical utility of mutation detection with blood-based assays.

Immune cell infiltration and PD-L1 expression were low at baseline in most of these BRAFi-refractory patients, consistent with previous studies demonstrating loss of immune infiltration at progression on BRAFi monotherapy.33 While previous studies demonstrated that robust immune infiltration of tumors can be achieved with CombiDT in BRAFi-naïve melanomas,33 we observed no significant increase in 8 of 9 patients. Interestingly, the patient with the highest pretreatment CD8-positive tumor infiltration demonstrated an increased infiltration of T cells by IHC, increased expression of immune-related genes in the tumor by RNAseq, and achieved disease control with CombiDT therapy. This patient was also one of the few patients who achieved MAPK pathway inhibition with CombiDT. These findings suggest that the effects of CombiDT that promote the antitumor immune response in BRAFi-naïve patients are largely absent in BRAFi-refractory patients, which has potential implications for the optimal sequencing of targeted and immune therapies in this disease.

Conclusions

Together, our findings reinforce the clinical and molecular heterogeneity of patients with metastatic melanoma whose disease has progressed on BRAFi monotherapy. Given the recent approvals of CombiDT and vemurafenib + cobimetinib4 as front-line therapies, this study likely represents one of the last opportunities to assess combination therapy after BRAFi monotherapy. Our studies identify potential early markers of clinical activity for future therapies and improve our understanding of the likely basis for the limited activity of CombiDT in this setting. These findings also support the rationale for the analysis of blood and tumor samples in future studies to expedite the development of more effective treatments.

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Article Information

Accepted for Publication: February 11, 2016.

Corresponding Author: Michael A. Davies, MD, PhD, University of Texas MD Anderson Cancer Center, 1515 Holcombe, Unit 0430, Houston, TX 77030 (mdavies@mdanderson.org).

Published Online: April 28, 2016. doi:10.1001/jamaoncol.2016.0509.

Author Contributions: Dr Davies had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis. Drs Chen and McQuade contributed equally to this work.

Study concept and design: McQuade, Panka, Mu, Sullivan, Kim, Davies.

Acquisition, analysis, or interpretation of data: Chen, McQuade, Panka, Hudgens, Amin-Mansour, Mu, Bahl, Jane-Valbuena, Wani, Reuben, Creasy, Jiang, Cooper, Roszik, Bassett, Joon, Simpson, Mouton, Glitza, Patel, W.-J. Hwu, Amaria, Diab, P. Hwu, Lazar, Wargo, Garraway, Tetzlaff, Sullivan, Kim, Davies.

Drafting of the manuscript: Chen, McQuade, Panka, Amin-Mansour, Mu, Bahl, Bassett, Joon, Sullivan, Davies.

Critical revision of the manuscript for important intellectual content: Chen, McQuade, Panka, Hudgens, Amin-Mansour, Mu, Jane-Valbuena, Wani, Reuben, Creasy, Jiang, Cooper, Roszik, Bassett, Simpson, Glitza, Patel, W.-J. Hwu, Amaria, Diab, P. Hwu, Lazar, Wargo, Garraway, Tetzlaff, Sullivan, Kim, Davies.

Statistical analysis: Chen, Panka, Hudgens, Amin-Mansour, Mu, Bassett, Joon, Garraway.

Obtained funding: Kim, Davies.

Administrative, technical, or material support: Chen, Panka, Mu, Bahl, Wani, Reuben, Creasy, Jiang, Cooper, Roszik, P. Hwu, Wargo, Garraway, Tetzlaff.

Study supervision: Chen, W.-J. Hwu, Amaria, Kim, Davies.

Conflict of Interest Disclosures: Dr Wargo has honoraria from the speakers bureau of Dava Oncology and is an advisory board member for GlaxoSmithKline and Roche/Genentech. Dr Davies has received research support from GlaxoSmithKline, Roche/Genentech, Sanofi-Aventis, Myriad, Oncothyreon, and Astrazeneca, and has served on advisory boards for GlaxoSmithKline, Roche/Genentech, Novartis, Vaccinex, and Sanofi-Aventis. No other disclosures are reported.

Funding/Support: This work was supported by the Cancer Prevention and Research Institute of Texas (RP120505, 1R01CA187076-01, 5R01CA154710-03, P50 CA093459, and P30 CA016672), the Dr Miriam and Sheldon G. Adelson Medical Research Foundation, and the University of Texas MD Anderson Cancer Center Melanoma Moon Shots Program. Dr McQuade is supported by an ASCO Young Investigator Award and a T32 Institutional Training Grant (T32 CA009666). Dr Wargo acknowledges NIH grants 1K08CA160692-01A1, the Melanoma Research Alliance Team Science Award, and the Kennedy Memorial Foundation grant # 0727030.

Role of the Funder/Sponsor: The funders approved the design and conduct of the study; they had no role in the collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: We thank all the study investigators and their clinical teams for their contribution to this study, and the patients for agreeing to participate.

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