Non-genomic and Immune Evolution of Melanoma Acquiring MAPKi Resistance

Melanoma: the intersection of molecular targeted therapy and immune checkpoint inhibition

Melanoma is at the forefront of development of systemic therapeutics with both molecular targeted therapies and immune checkpoint inhibitors as cornerstones of treatment. Although responses to molecularly targeted therapy is largely from blockade of oncogenic pathways, evidence is emerging of the immunomodulatory effects from BRAF inhibition. Additionally programmed-death-1 (PD-1) inhibitors have revolutionized the treatment of melanoma and are set to pave future improvements in other solid tumors. Combinations of PD-1 inhibitors with novel immune checkpoints or with molecularly targeted therapies are under investigation and may improve on the considerable progress made.

Personalized Preclinical Trials in BRAF Inhibitor-Resistant Patient-Derived Xenograft Models Identify Second-Line Combination Therapies

PURPOSE

To test second-line personalized medicine combination therapies, based on genomic and proteomic data, in patient-derived xenograft (PDX) models.

EXPERIMENTAL DESIGN

We established 12 PDXs from BRAF inhibitor-progressed melanoma patients. Following expansion, PDXs were analyzed using targeted sequencing and reverse-phase protein arrays. By using multi-arm preclinical trial designs, we identified efficacious precision medicine approaches.

RESULTS

We identified alterations previously described as drivers of resistance: NRAS mutations in 3 PDXs, MAP2K1 (MEK1) mutations in 2, BRAF amplification in 4, and aberrant PTEN in 7. At the protein level, re-activation of phospho-MAPK predominated, with parallel activation of PI3K in a subset. Second-line efficacy of the pan-PI3K inhibitor BKM120 with either BRAF (encorafenib)/MEK (binimetinib) inhibitor combination or the ERK inhibitor VX-11e was confirmed in vivo Amplification of MET was observed in 3 PDX models, a higher frequency than expected and a possible novel mechanism of resistance. Importantly, MET amplification alone did not predict sensitivity to the MET inhibitor capmatinib. In contrast, capmatinib as single agent resulted in significant but transient tumor regression in a PDX with resistance to BRAF/MEK combination therapy and high pMET. The triple combination capmatinib/encorafenib/binimetinib resulted in complete and sustained tumor regression in all animals.

CONCLUSIONS

Genomic and proteomic data integration identifies dual-core pathway inhibition as well as MET as combinatorial targets. These studies provide evidence for biomarker development to appropriately select personalized therapies of patients and avoid treatment failures. See related commentary by Hartsough and Aplin, p. 1550.

Beyond Genomics: Multidimensional Analysis of Cancer Therapy Resistance

Cancer resistance to therapy occurs through a selection process generally thought to be driven by mutations. In a recent study, Hugo et al. use multidimensional analysis of the dynamic genetic, transcriptional, epigenetic, and immune landscape alterations in baseline and MAPK inhibitor-resistant melanoma tumors, demonstrating a role for 'non-genomic' drivers in cancer evolution.