Background
The utilization of PD1 and CTLA4 inhibitors has revolutionized the treatment of malignant
melanoma (MM). However, resistance to targeted and immune-checkpoint-based therapies
still poses a significant problem.
Objective
Here, we mine large-scale MM proteogenomic data to identify druggable targets and
forecast treatment efficacy and resistance.
Methods
Leveraging protein profiles from established MM subtypes and molecular structures
of 82 cancer treatment drugs, we identified nine candidate hub proteins, mTOR, FYN,
PIK3CB, EGFR, MAPK3, MAP4K1, MAP2K1, SRC, and AKT1, across five distinct MM subtypes.
These proteins are potential drug targets applicable to one or multiple MM subtypes.
Additionally, by integrating proteogenomic profiles obtained from MM subtypes with
MM cell line dependency and drug sensitivity data, we identified a total of 162 potentially
targetable genes. Lastly, we identified 20 compounds exhibiting potential drug impact
in at least one melanoma subtype.
Results
Employing these unbiased approaches, we have uncovered compounds targeting ferroptosis
demonstrating a striking 30× fold difference in sensitivity among different subtypes.
Conclusions
Our results suggest innovative and novel therapeutic strategies by stratifying melanoma
samples through proteomic profiling, offering a spectrum of novel therapeutic interventions
and prospects for combination therapy.
