SummaryPharmacologic inhibition of LSD1 promotes blast cell differentiation in acute myeloid leukemia (AML) with MLL translocations. The assumption has been that differentiation is induced through blockade of LSD1’s histone demethylase activity. However, we observed that rapid, extensive, drug-induced changes in transcription occurred without genome-wide accumulation of the histone modifications targeted for demethylation by LSD1 at sites of LSD1 binding and that a demethylase-defective mutant rescued LSD1 knockdown AML cells as efficiently as wild-type protein. Rather, LSD1 inhibitors disrupt the interaction of LSD1 and RCOR1 with the SNAG-domain transcription repressor GFI1, which is bound to a discrete set of enhancers located close to transcription factor genes that regulate myeloid differentiation. Physical separation of LSD1/RCOR1 from GFI1 is required for drug-induced differentiation. The consequent inactivation of GFI1 leads to increased enhancer histone acetylation within hours, which directly correlates with the upregulation of nearby subordinate genes.

Here, we show that new mitochondrial biogenesis is required for the anchorage independent survival and propagation of cancer stem-like cells (CSCs). More specifically, we used the drug XCT790 as an investigational tool, as it functions as a specific inhibitor of the ERRα-PGC1 signaling pathway, which governs mitochondrial biogenesis. Interestingly, our results directly demonstrate that XCT790 efficiently blocks both the survival and propagation of tumor initiating stem-like cells (TICs), using the MCF7 cell line as a model system. Mechanistically, we show that XCT790 suppresses the activity of several independent signaling pathways that are normally required for the survival of CSCs, such as Sonic hedgehog, TGFβ-SMAD, STAT3, and Wnt signaling. We also show that XCT790 markedly reduces oxidative mitochondrial metabolism (OXPHOS) and that XCT790-mediated inhibition of CSC propagation can be prevented or reversed by Acetyl-L-Carnitine (ALCAR), a mitochondrial fuel. Consistent with our findings, over-expression of ERRα significantly enhances the efficiency of mammosphere formation, which can be blocked by treatment with mitochondrial inhibitors. Similarly, mammosphere formation augmented by FOXM1, a downstream target of Wnt/β-catenin signaling, can also be blocked by treatment with three different classes of mitochondrial inhibitors (XCT790, oligomycin A, or doxycycline). In this context, our unbiased proteomics analysis reveals that FOXM1 drives the expression of >90 protein targets associated with mitochondrial biogenesis, glycolysis, the EMT and protein synthesis in MCF7 cells, processes which are characteristic of an anabolic CSC phenotype. Finally, doxycycline is an FDA-approved antibiotic, which is very well-tolerated in patients. As such, doxycycline could be re-purposed clinically as a ‘safe’ mitochondrial inhibitor, to target FOXM1 and mitochondrial biogenesis in CSCs, to prevent tumor recurrence and distant metastasis, thereby avoiding patient relapse.

The iTRAQ (isobaric tags for relative and absolute quantification) technique is widely employed in proteomic workflows requiring relative quantification. Here, we review the iTRAQ literature; in particular, we focus on iTRAQ usage in relation to other commonly used quantitative techniques e.g. stable isotope labelling in culture (SILAC), label-free methods and selected reaction monitoring (SRM). As a result, we identify several issues arising with respect to iTRAQ. Perhaps frustratingly, iTRAQ's attractiveness has been undermined by a number of technical and analytical limitations: it may not be truly quantitative, as the changes in abundance reported will generally be underestimated. We discuss weaknesses and strengths of iTRAQ as a methodology for relative quantification in the light of this and other technical issues. We focus on technical developments targeted at iTRAQ accuracy and precision, use of 4-plex over 8-plex reagents and application of iTRAQ to post-translational modification (PTM) workflows. We also discuss iTRAQ in relation to label-free approaches, to which iTRAQ is losing ground.