Targeted next generation sequencing identifies clinically actionable mutations in patients with melanoma

Abstract

Somatic sequencing of cancers has produced new insight into tumorigenesis, tumor heterogeneity, and disease progression, but the vast majority of genetic events identified are of indeterminate clinical significance. Here, we describe a NextGen sequencing approach to fully analyzing 248 genes, including all those of known clinical significance in melanoma. This strategy features solution capture of DNA followed by multiplexed, high-throughput sequencing and was evaluated in 31 melanoma cell lines and 18 tumor tissues from patients with metastatic melanoma. Mutations in melanoma cell lines correlated with their sensitivity to corresponding small molecule inhibitors, confirming, for example, lapatinib sensitivity in ERBB4 mutant lines and identifying a novel activating mutation of BRAF. The latter event would not have been identified by clinical sequencing and was associated with responsiveness to a BRAF kinase inhibitor. This approach identified focal copy number changes of PTEN not found by standard methods, such as comparative genomic hybridization (CGH). Actionable mutations were found in 89% of the tumor tissues analyzed, 56% of which would not be identified by standard-of-care approaches. This work shows that targeted sequencing is an attractive approach for clinical use in melanoma.

Keywords: clinical trials; diagnostics; genomics; resequencing; therapeutics.

Figure 1. Aggregate Analysis of Mutation Calls

(A) Co-occurrence of mutations in melanoma cell lines including SNVs, CNV calls from SNP array, and both. (B) Co-occurrence of mutations in metastatic cutaneous melanoma showing KIT mutations in BRAF and NRAS wild type lines. (C) Putative somatic mutation rates in melanoma cell lines and (D) putative somatic mutations in tumors.

Figure 2. Non-Frameshift BRAF Mutation Sensitive to PLX4032

(A) Mel537 cell line aggregate read depth and mapped reads show homozygous non-frameshift deletion mutation in exon 12 of BRAF. (B) Structural alignment of inhibitor bound BRAF structure (CYAN) to inhibitor bound EGFR (GREEN) showing structural homology of the BRAF exon 12 deletion (RED) and know activating EGFR exon 19 deletions (PINK). (C) ERK and activated ERK (pERK) blots in serum-starved lines with and without PLX4032 treatment. (D) PLX4032 sensitivity of SKMEL27 (BRAF V600E), Mel537, and VMM39 (NRAS Q61R). (E) ERK and activated ERK (pERK) blots in serum-starved lines with and without MEK inhibition by GSK112. (F) GSK112 sensitivity of SKMEL27, Mel537 and VMM39.

Figure 3. ERBB4 Mutation Predicts Lapatinib Sensitivity

(A) Previously reported mutations in ERBB4 (PINK) and in three cell lines (BLACK) span multiple domains of the gene. (B) Lapatinib sensitivity in three ERBB4 mutant lines was increased compared to ERBB3 wild type lines (p = 0.1).

Figure 4. Sequencing Detects Focal Deletions at High Resolution

(A) CNV calls using SNP microarrays. (B) Sequencing coverage of PTEN exons in WM2664, PMWK, SKMEL24 and UACC257 with very low coverage in a PTEN deletion line (PMWK) as well as isolated exons in other lines (red arrowheads). (C) Aggregated mutation rates in selected tumor suppressor genes in cell lines using CGH array and sequencing.