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Clinical, Molecular, and Immune Analysis of Dabrafenib-Trametinib

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Clinical, Molecular, and Immune Analysis of Dabrafenib-Trametinib Supplementary Online Content Chen G, McQuade JL, Panka DJ, et al. Clinical, molecular and immune analysis of dabrafenib-trametinib combination treatment for metastatic melanoma that progressed during BRAF inhibitor monotherapy: a phase 2 clinical trial. JAMA Oncology. Published online April 28, 2016. doi:10.1001/jamaoncol.2016.0509. eMethods. eReferences. eTable 1. Clinical efficacy eTable 2. Adverse events eTable 3. Correlation of baseline patient characteristics with treatment outcomes eTable 4. Patient responses and baseline IHC results eFigure 1. Kaplan-Meier analysis of overall survival eFigure 2. Correlation between IHC and RNAseq results eFigure 3. pPRAS40 expression and PFS eFigure 4. Baseline and treatment-induced changes in immune infiltrates eFigure 5. PD-L1 expression eTable 5. Nonsynonymous mutations detected by WES in baseline tumors This supplementary material has been provided by the authors to give readers additional information about their work. © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 eMethods Whole exome sequencing Whole exome capture libraries for both tumor and normal samples were constructed using 100ng genomic DNA input and following the protocol as described by Fisher et al.,3 with the following adapter modification: Illumina paired end adapters were replaced with palindromic forked adapters with unique 8 base index sequences embedded within the adapter. In-solution hybrid selection was performed using the Illumina Rapid Capture Exome enrichment kit with 38Mb target territory (29Mb baited). The targeted region includes 98.3% of the intervals in the Refseq exome database. Dual-indexed libraries were pooled into groups of up to 96 samples prior to hybridization. The enriched library pools were quantified via PicoGreen after elution from streptavadin beads and then normalized to a range compatible with sequencing template denature protocols. Libraries were sequenced using 76-bp paired-end reads. Output from Illumina software was processed by the Broad Picard data-processing pipeline to yield BAM files containing well-calibrated, aligned reads. Cross-contamination between samples from other individuals was monitored with the ContEst algorithm.4 Somatic single-nucleotide variants in targeted exons were identified with the MuTect algorithm,5 and small insertions or deletions with Indelocator (http://www.broadinstitute.org/cancer/cga/indelocator). Alterations were annotated using Oncotator (http://www.broadinstitute.org/cancer/cga/oncotator) and manually reviewed in the Integrative Genomics Viewer (IGV).6 Statistical analysis of recurrently mutated genes was performed using MutSig.7 Copy number aberrations were quantified using ReCapSeg (http://gatkforums.broadinstitute.org/discussion/5640/recapseg-overview), and reported for each gene as the segmented normalized log2-transformed copy ratio between each tumor sample and a panel of normal samples. Transcriptome sequencing Total RNA was quantified using the Quant-iT™ RiboGreen® RNA Assay Kit and normalized to 5ng/ul. To generate transcriptome libraries, an automated variant method of the Illumina TruSeq™ Stranded mRNA Sample Preparation Kit was used, which preserves strand orientation of the RNA transcript. Briefly, 200ng of total RNA were used for each tumor sample. Poly(A)+ mRNA was isolated using oligo(dT) beads, followed by heat fragmentation and cDNA synthesis. cDNA libraries were then prepared (end repair, base ‘A’ addition, adapter ligation, and enrichment) using Broad designed indexed adapters substituted in for multiplexing. After enrichment, the libraries were quantified with qPCR using the KAPA Library Quantification Kit for Illumina Sequencing Platforms and then pooled equimolarly. Pooled libraries were normalized to 2nM and denatured using 0.1 N NaOH prior to sequencing. Flowcell cluster amplification and sequencing were performed according to the manufacturer’s protocols using either the HiSeq 2000 or HiSeq 2500. Each run was a 101bp paired-end with an eight-base index barcode read. Data was analyzed using the Broad Picard Pipeline which includes de-multiplexing and data aggregation. Abundances of transcripts, expressed as fragments per kilobase of exon per million (FPKM, upper quartile normalized), were determined using RSEM.8 Immunohistochemistry IHC on FFPE tumor tissues was performed using antibodies against BRAFV600E (Ventana 790-4855), pMAPK(ERK1/2) (Cell Signaling 4376), pS6 (Cell Signaling 4858), pPRAS40 (Cell Signaling 13175), CD8 (Leica PA0183), and PD-L1 (Cell Signaling 13684). © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 Circulating BRAF Peripheral blood mononuclear cells (PBMC) isolated from blood were subjected to total RNA isolation using mirVana™ kit (AM1560). Amount of circulating BRAFV600 was determined from PBMC-derived RNA using RT-PCR as previously described.9 Briefly, wildtype BRAF sequence was digested away by a restrictive endonuclease (TspR1) that preferably digests wildtype BRAF at codon V600 but not BRAFV600, allowing for the detection of BRAFV600 with a BRAFV600-specific RT-PCR assay. © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 eReferences 1. Eisenhauer EA, Therasse P, Bogaerts J, et al. New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). European journal of cancer. Jan 2009;45(2):228-247. 2. Trotti A, Colevas AD, Setser A, et al. CTCAE v3.0: development of a comprehensive grading system for the adverse effects of cancer treatment. Seminars in radiation oncology. Jul 2003;13(3):176-181. 3. Fisher S, Barry A, Abreu J, et al. A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries. Genome biology. 2011;12(1):R1. 4. Cibulskis K, McKenna A, Fennell T, Banks E, DePristo M, Getz G. ContEst: estimating cross-contamination of human samples in next-generation sequencing data. Bioinformatics. Sep 15 2011;27(18):2601-2602. 5. Cibulskis K, Lawrence MS, Carter SL, et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nature biotechnology. Mar 2013;31(3):213-219. 6. Robinson JT, Thorvaldsdottir H, Winckler W, et al. Integrative genomics viewer. Nature biotechnology. Jan 2011;29(1):24-26. 7. Lawrence MS, Stojanov P, Polak P, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. Jul 11 2013;499(7457):214-218. 8. Li B, Dewey CN. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome. BMC bioinformatics. 2011;12:323. 9. Panka DJ, Buchbinder E, Giobbie-Hurder A, et al. Clinical utility of a blood-based BRAF(V600E) mutation assay in melanoma. Molecular cancer therapeutics. Dec 2014;13(12):3210-3218. © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 eTable 1 Clinical efficacy Confirmed Response No. % CR 0 0 PR 2 9 SD 7 30 PD 11 48 NE 3 13 © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 eTable 2 Adverse events All Grades Grade III/IV AE Number % Number % Any event 24 10 17 71 Fever 12 50 0 0 Nausea/vomiting 12 50 0 0 Fatigue 9 38 0 0 Chills 7 29 0 0 Dry mouth 6 25 0 0 Headache 6 25 0 0 Arthralgias 6 25 1 4 Anorexia 5 21 0 0 Constipation 5 21 0 0 Rash 5 21 0 0 Hot flashes 4 17 0 0 Actinic keratosis 0 0 0 0 Cutaneous SCC 0 0 0 0 Decreased ejection fraction 2 8 1 4 Blurred vision 1 4 0 0 Chorioretinopathy 0 0 0 0 Note: Adverse events occurring in >15% of patients and events of special interest © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 eTable 3 Correlation of baseline patient characteristics with treatment outcomes Variable PFS P-Value P-Value Hazard Ratio Disease Control Odds Ratio Age 0.99 0.36 1.32 0.72 Male Sex 0.99 0.98 6.67 0.12 Duration of Prior BRAFi 0.29 0.01 21.33 0.015 >6 months ECOG Performance Score 1- 1.05 0.92 0.60 0.58 2 Disease Stage 0.96 0.93 1.40 0.71 IIIC-M1B Mutation 0.99 0.99 2.86 0.42 V600K/R Baseline LDH 1.75 0.21 0.50 0.50 Elevated Time Lapse from Prior BRAFi 0.70 0.53 1.29 0.82 >0 months BRAFi Best Response 2.10 0.16 0 0.74 SD/PD MORs: Only MAPK Pathway 0.42 0.19 3.75 0.32 Reactivation © 2016 American Medical Association. All rights reserved. Downloaded From: https://jamanetwork.com/ on 09/30/2021 eTable 4 Patient responses and baseline IHC results Nu Pati PFS MAPK MAPK pPRAS4 pPRAS4 pS6 pS6 DC? mbe ent (weeks score class 0 score 0 class score class (1=yes, r ) 0=no) 1 Pt0 33.3 -0.06 Low 0.8 Low -1.0 Low 1 1 2 Pt0 12.7 0.30 High 0 Low -1.2 Low 1 2 3 Pt0 8.6 0 3 4 Pt0 19.4 5 5 Pt0 7.9 -0.61 Low 1.2 High 0.4 High 0 8 6 Pt0 3.9 0.67 High 2 High -0.7 Low 0 9 7 Pt1 2.3 1.07 High 2.7 High 1.5 High 0 8 Pt1 5.4 0 1 9 Pt1 15.0 1.31 High 0.2 Low 1.1 High 1 2 10 Pt1 7.6 1.51 High 1.6 High 0 3 11 Pt1 12.9 -0.55 Low 1 4 12 Pt1 32.0 1 5 13 Pt1 15.9 0.71 High 1 7 14 Pt1 35.9 0.51 High 1 8 15 Pt1 3.4 -0.47 Low 0.05 Low -0.8 Low 0 9 16 Pt2 15.9 0.67 High 0.8 High 0 0 17 Pt2 15.9 0.67 High -0.9 Low 0 1 18 Pt2 16.3 1 2 19 Pt2 23.6 1 3 20 Pt2 0.6 4 21 Pt2 7.9 0.48 High 1.1 High 0 6 22 Pt2 11.9 1.51 Low 1.3 High 0 7 23 Pt2 15.9 0 8 Note: Missing value= not evaluable, DC=Disease control © 2016 American Medical Association.
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