Publications

Background

• Survival for metastatic melanoma has improved since 2011, due to improvements in systemic therapy, including immune checkpoint inhibitors and targeted agents. However, brain metastases (MBM) remain a significant cause of morbidity and mortality in patients with metastatic melanoma.
• Recently, combined checkpoint inhibition (CTLA-4 + PD-1), and combination targeted therapy (BRAF + MEK) were both shown to have efficacy in treating brain metastases, with efficacy similar to that of treating systemic disease.^1,2 Yet there are no defined biomarkers to guide treatment for patients with resistant MBM.
• The biological underpinnings of melanoma brain metastases, as compared to other melanoma tumors (primary, non-CNS metastases) remains unclear. Increasing evidence suggests a distinct evolution, with unique molecular features.3 Activation of the MAPK pathway, as well as the PI3K-AKT pathway, have been implicated in the pathogenesis of MBM.⁴
• Herein, we seek to understand the interplay between PD-L1, TMB, BRAF, and other oncogenic pathways among melanoma brain metastases (MBM), as compared against cutaneous melanoma (CM) and other non-CNS melanoma metastases (MOM).

Methods

• Tumors submiUed to Caris Life Sciences (Phoenix, AZ) for routine molecular profiling between January 2015 and January 2018 were reviewed from a deidentified database. We analyzed a total of 132 MBM, 745 CM and 1190 MOM.
• NGS was performed on genomic DNA isolated from FFPE tumor samples using the NextSeq (592-genes)/MiSeq pladorm (45-gene) (Illumina, Inc., San Diego, CA). All variants were detected with greater than 99% confidence based on allele frequency and amplicon coverage, with an average sequencing depth of coverage greater than 500 and an analytic sensitivity of 5%.
• Microsatellite instability (MSI) was examined by counting number of microsatellite loci that were altered by somatic insertion or deletion counted for each sample. The threshold to determine MSI by NGS was determined to be 46 or more loci with insertions or deletions to generate a sensitivity of > 95% and specificity of > 99%.
• Tumor mutational burden (TMB) was estimated from 592 genes (1.4 megabases [MB] sequenced per tumor) by counting all non-synonymous missense mutations found per tumor that had not been previously described as germline alterations. TMB was determined as high or low using a threshold of ≥17 mutations/Mb.
• IHC was performed on FFPE sections of glass slides. PD-L1 testing was performed using the SP142 (Ventana, Tucson, AZ) anti-PD-L1 clone as measured on tumor cells. PD-L1 positivity was evaluated using a threshold of 1+ staining intensity on ≥1% of tumor cells.
• Comparison of molecular profiles, including cancer-related genes and recurrently altered pathways, between tumor sites, and by genomic subgroup (BRAF, NRAS, KIT, NF1), Chi-square, t-tests, and Wilcoxon test were performed for comparative analyses using R (version 3.5.0).

Conclusions

• Melanoma brain metastases (MBM) demonstrate a unique molecular profile, when compared to primary cutaneous melanoma (CM) and other non-CNS melanoma metastases (MOM).
• MBM were associated with higher rates of BRAF mutations, as well as higher TMB and higher PD-L1 expression.
• Genetic alterations among genes associated with epigenetic modification were frequently seen among MBM. We noted significant alterations among PBRM1 and SETD2, which have not been previously identified in the context of MBM.
• Pathway analyses revealed higher rates of genetic alterations in the MAPK pathway, as well as SWI/SNF and chromatin remodeling pathways, among MBM.
• Our data suggests that epigenetic modification may play an important role in the biology of melanoma brain metastases, warranting further investigation.
• Ongoing studies will further analyze differences among other sites of melanoma metastases.