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Table S5, related to Figure S5C

Contains Supplementary materials and methods, Supplementary Figures S1-S9, Table S2, Table S4, Supplemental References Figure S1, related to Figure 1. Cell surface marker screening of A375P cells treated with vehicle (DMSO) or PLX. Figure S2, related to Figure 1. CD36 is a biomarker of the early stage of MAPK inhibition in melanoma. Figure S3, related to Figure 1. MAPK inhibition induces and maintains the CD36+ population in melanoma cells Figure S4, related to Figure 2. MAPKi induce the expression of genes involved in lipid catabolism in BRAFV600E melanomas. Figure S5, related to Figure 3. MAPK inhibition decreased the glycolytic flux in BRAF-mutated melanoma cells. Figure S6, related to Figure 4. Phenotypic and metabolic characterization of CD36 WT, CD36 KO, CD36+ and CD36- A375P cells. Figure S7, related to Figure 5. PPARα does not regulate CD36 expression. Figure S8, related to Figure 6. Role of glycolysis and FAO inhibitors in proliferation and resistance to MAPKi Figure S9, related to Figure 6. Effects of MAPK, glycolysis and FAO inhibition on mouse and tumor weight. Table S2, related to Figure 1, Figure 3, Figure 6, Figure S3 and Figure S6. Primer list. Table S4, related to Figure 1 and Figure S2. Cell lines, their mutational status and their responsiveness to MAPK inhibitors.

Purpose:Treatment of BRAFV600E-mutant melanomas with MAPK inhibitors (MAPKi) results in significant tumor regression, but acquired resistance is pervasive. To understand nonmutational mechanisms underlying the adaptation to MAPKi and to identify novel vulnerabilities of melanomas treated with MAPKi, we focused on the initial response phase during treatment with MAPKi.Experimental Design:By screening proteins expressed on the cell surface of melanoma cells, we identified the fatty acid transporter CD36 as the most consistently upregulated protein upon short-term treatment with MAPKi. We further investigated the effects of MAPKi on fatty acid metabolism using in vitro and in vivo models and analyzing patients' pre- and on-treatment tumor specimens.Results:Melanoma cells treated with MAPKi displayed increased levels of CD36 and of PPARα-mediated and carnitine palmitoyltransferase 1A (CPT1A)-dependent fatty acid oxidation (FAO). While CD36 is a useful marker of melanoma cells during adaptation and drug-tolerant phases, the upregulation of CD36 is not functionally involved in FAO changes that characterize MAPKi-treated cells. Increased FAO is required for BRAFV600E-mutant melanoma cells to survive under the MAPKi-induced metabolic stress prior to acquiring drug resistance. The upfront and concomitant inhibition of FAO, glycolysis, and MAPK synergistically inhibits tumor cell growth in vitro and in vivo.Conclusions:Thus, we identified a clinically relevant therapeutic approach that has the potential to improve initial responses and to delay acquired drug resistance of BRAFV600E-mutant melanoma.

Recent studies have revealed the importance of long noncoding RNAs (lncRNAs) as tissue-specific regulators of gene expression. There is ample evidence that distinct types of vasculature undergo tight transcriptional control to preserve their structure, identity, and functions. We determined, for the first time, the global lineage-specific lncRNAome of human dermal blood and lymphatic endothelial cells (BECs and LECs), combining RNA-Seq and CAGE-Seq. A subsequent genome-wide antisense oligonucleotide-knockdown screen of a robust set of BEC- and LEC-specific lncRNAs identified LETR1 as a critical gatekeeper of the global LEC transcriptome. Deep RNA-DNA, RNA-protein, and phenotype rescue analyses revealed that LETR1 acts as a nuclear trans-acting lncRNA modulating, via key epigenetic factors, the expression of essential target genes, including KLF4 and SEMA3C, governing the growth and migratory ability of LECs. Together, our study provides new evidence supporting the intriguing concept that every cell type expresses precise lncRNA signatures to control lineage-specific regulatory programs.