Neuroblastoma is one of the most aggressive solid tumors of early childhood. Amplification of the MYCN oncogene has been found in around 30% of neuroblastoma patients and is associated with rapid tumor progression and poor prognosis. As metabolic adaptations are crucial for cancer cell survival, identifying metabolic discrepancies of aggressive tumors may be central in order to find new treatment strategies. We have recently demonstrated that a small chemical molecule, 10058-F4, previously identified as a c-MYC inhibitor also targets the MYCN/MAX complex resulting in apoptosis and neuronal differentiation in MYCN-amplified neuroblastoma cells. Importantly, we found that inhibition of MYCN results in changes in neuroblastoma cell metabolism including mitochondrial dysfunction leading to accumulation of intracellular lipid droplets (Zirath, PNAS 2013; Muller, PloS One, 2014).
We have now analyzed the effects of several small molecule MYC inhibitors including the structurally unrelated 10074-G5, the BET-domain inhibitor JQ1 and the Aurora A kinase inhibitor Alisertib on neuroblastoma cells. Our data show that treatment with all three compounds resulted in accumulation of cytoplasmic lipid droplets and in neural differentiation. Next we were interested in the extent of generality of this response and have therefore extended our study to a panel of different cancer cell types, including medulloblastoma, glioblastoma, melanoma, hepatocarcinoma, lung, ovary, breast, colon, prostate and cervical cancer. We found a cell type-dependent response to the treatments; some cells showing accumulation of neutral lipids while others not. Importantly, some of the treatments gave rise to morphological changes resembling cellular differentiation into neural or glial lineages. We are now performing functional assays using Seahorse Flux Analyzer to study the metabolic changes as well as analyzing expression of neural and glial differentiation markers in response to treatment in neuroblastoma and medulloblastoma cells. Our goals are to identify the types of cancers that are sensitive to MYC-inhibiting strategies and to analyze the mechanism of action of MYC inhibitors for development of future tailored therapies.