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Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas

Nature Medicine volume 25, pages 597–602 (2019)Cite this article

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Abstract

Spitzoid melanoma is a specific morphologic variant of melanoma that most commonly affects children and adolescents, and ranges on the spectrum of malignancy from low grade to overtly malignant. These tumors are generally driven by fusions of ALK, RET, NTRK1/3, MET, ROS1 and BRAF1,2. However, in approximately 50% of cases no genetic driver has been established2. Clinical whole-genome and transcriptome sequencing (RNA-Seq) of a spitzoid tumor from an adolescent revealed a novel gene fusion of MAP3K8, encoding a serine-threonine kinase that activates MEK3,4. The patient, who had exhausted all other therapeutic options, was treated with a MEK inhibitor and underwent a transient clinical response. We subsequently analyzed spitzoid tumors from 49 patients by RNA-Seq and found in-frame fusions or C-terminal truncations of MAP3K8 in 33% of cases. The fusion transcripts and truncated genes all contained MAP3K8 exons 1–8 but lacked the autoinhibitory final exon. Data mining of RNA-Seq from the Cancer Genome Atlas (TCGA) uncovered analogous MAP3K8 rearrangements in 1.5% of adult melanomas. Thus, MAP3K8 rearrangements—uncovered by comprehensive clinical sequencing of a single case—are the most common genetic event in spitzoid melanoma, are present in adult melanomas and could be amenable to MEK inhibition.

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Fig. 1: Diagnosis and treatment history.
Fig. 2: Clinical genomics sequencing.
Fig. 3: Recurrent MAP3K8 fusions/truncations in a spitzoid melanoma cohort.
Fig. 4: MAP3K8 fusions and truncations in TCGA melanoma samples.

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Data availability

The raw whole-genome sequencing, exome and RNA-Seq dataset generated for the index patient are available in St. Jude Cloud, https://platform.stjude.cloud/requests/publications?publication_accession=SJC-PB-1018, and have also been deposited in European Genome-Phenome Archive under accession number EGAS00001003430. RNA-Seq data from archival samples are available from the authors upon reasonable request and with permission from the St. Jude Children’s Research Hospital IRB.

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Acknowledgements

We thank S. Brady for critical review of the manuscript. This work was funded by the American Lebanese Syrian Associated Charities of St. Jude Children’s Research Hospital.

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Authors and Affiliations

  1. Department of Computational Biology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Scott Newman, Antonina Silkov, Stephen V. Rice, Ying Shao, Bridget Shaner, Heather Mulder, Gang Wu, Xin Zhou, John Easton & Jinghui Zhang

  2. Department of Chemical Biology & Therapeutics, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Liying Fan & Philip M. Potter

  3. Department of Oncology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Allison Pribnow, Kim E. Nichols, Alberto Pappo & Armita Bahrami

  4. Department of Pediatrics, Division of Hematology/Oncology, Stanford University School of Medicine, Palo Alto, CA, USA

    Allison Pribnow

  5. Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA

    Seungjae Lee, Joy Nakitandwe, Sheila Shurtleff, Elizabeth M. Azzato, David W. Ellison, James R. Downing & Armita Bahrami

  6. Departments of Pathology and Translational Research, Institute Curie, Paris, France

    Raymond Barnhill

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Contributions

A.S. performed clinical genomics case reviews and analyzed RNA-Seq data. S.V.R., G.W. and X.Z. provided bioinformatics analysis and support. S.L. performed FISH assays. Y.S., B.S. and H.M. performed research sample quality control and sequencing under the supervision of J.E. J.N. performed clinical sequencing. S.S., K.E.N. and E.A. provided clinical genomics case review and reporting. R.B. provided archival samples for analysis and critical review of the data. L.F. performed functional validations and imunoblots under the supervision of P.M.P. and A.P. A.P. managed the original clinical case and performed data analysis and interpretation. K.E.N., D.W.E. and J.R.D. provided project oversight. A.B. provided pathology classifications and supervised IHC and FISH experiments. S.N., J.Z. and A.B. conceived of the study, performed the clinical review and data analysis and drafted the manuscript.

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Correspondence to Scott Newman, Jinghui Zhang or Armita Bahrami.

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Extended data

Extended Data Fig. 1 Clinical Course.

Timeline of the clinical course imaging, and treatment regimens, are shown as colored rectangles along the horizontal timeline. For treatments, HLP is hyperthermic limb perfusion, TVEC is talimogene laherparaepvec and LTT462 is an ERK inhibitor. Subsequent Figures within this manuscript showing specimens or images from this timeline are indicated.

Extended Data Fig. 2 TERT rearrangement in the initial tumor.

a, Copy number segments from CONSERTING43; red shows a gain in copy number, blue a loss. b, Scatterplot of normalized sequencing coverage from whole-genome sequencing confirms a 75 kb region of neutral copy number encompassing the TERT locus flanked by deletions. c, Structural variant junctions are shown in blue for junctions within the same chromosome and red for junctions linking different chromosomes; the genome position of the partner locus is shown inline. d, RefSeq gene model showing the position of TERT. e, RNA-Seq coverage shows that TERT is expressed. We inspected RNA-Seq coverage at this locus for our 49 additional patient samples and found TERT expression to be absent. f, Splice junctions detected in RNA-Seq and quantified according to the y axis. Canonical splices are shown in blue and non-canonical splices are in red. g, An image of break-apart FISH for TERT performed on the primary tumor from the index case showing split red and green signals, consistent with TERT rearrangement. We performed FISH on 5 additional tumors and found this locus not to be rearranged. All FISH images are at ×100 magnification.

Extended Data Fig. 3 MAP3K8 and GNG2 copy number and expression in initial and relapsed tumors.

a, Chromosome 10 and b, chromosome 14 copy number profile from CONSERTING. Gray scatterplot represents normalized whole-genome sequencing read depth arranged by genome position on the x axis. Changes in copy number are evident as segmental shifts on the y axis. Although a deletion is evident at the start of 14q, no copy number changes are present at the MAP3K8 (chr10:30,720,950-30,752,762) or GNG2 (chr14:52,325,022-52,438,518) loci in the initial tumor sample (black arrows represent the locations of MAP3K8 and GNG2) on chromosomes 10 and 14, respectively. In the relapsed sample, the copy number of both loci is increased. c, RNA-Seq coverage with the initial tumor sample’s MAP3K8 and GNG2 loci in the upper panels and the relapsed tumor below. MAP3K8 and GNG2 expression are increased approximately threefold in the relapsed sample.

Extended Data Fig. 4 MAP3K8 mutations across cBioPortal studies.

ProteinPaint32 representation of MAP3K8 mutations found over 226 studies housed within cBioPortal16. Specific amino acid changes are shown as lollipops with a size proportional to their frequency in the cohort. The most frequently mutated tumor types were uterine endometrioid carcinoma (n = 25), colorectal adenocarcinoma (n = 21) and cutaneous melanoma (n = 20). A hotspot at R442 is indicated by the black arrow. According to ELM44 (http://elm.eu.org/), Arg442 is part of the sequence KRQRSLYIDL described previously as a MAPK docking site in MAP kinase substrates45. Interestingly, because the MAP3K8 truncation in SJMEL054992_D1 is at codon R440, only R442 is excluded from the truncated MAP3K8.

Extended Data Fig. 5 MAP3K8 fused and truncated samples from TCGA.

RNA-Seq coverage overlapping the MAP3K8 locus is shown in the blue histograms. Each histogram is scaled according to the corresponding y axis. Black arrows indicate the positions of fusions or truncations as outlined in Supplementary Table 6. The MAP3K8 locus of all seven rearranged samples is shown.

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Unprocessed Western blot image

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Newman, S., Fan, L., Pribnow, A. et al. Clinical genome sequencing uncovers potentially targetable truncations and fusions of MAP3K8 in spitzoid and other melanomas. Nat Med 25, 597–602 (2019). https://doi.org/10.1038/s41591-019-0373-y

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