Summary By analyzing gene expression data in gliobastoma in combination with matched microRNA profiles, we have uncovered a post-transcriptional regulation layer of surprising magnitude, comprising over 248,000 microRNA (miR)-mediated interactions. These include ~7,000 genes whose transcripts act as miR ‘sponges’ and 148 genes that act through alternative, non-sponge interactions. Biochemical analyses in cell lines confirmed that this network regulates established drivers of tumor initiation and subtype, including PTEN, PDGFRA, RB1, VEGFA, STAT3, and RUNX1, suggesting that these interactions mediate crosstalk between canonical oncogenic pathways. RNA silencing of 13 microRNA-mediated PTEN regulators, whose locus deletions are predictive of PTEN expression variability, was sufficient to downregulate PTEN in a 3′ UTR-dependent manner and to increase tumor-cell growth rates. Thus, this miR-mediated network provides a mechanistic, experimentally validated rationale for the loss of PTEN expression in a large number of glioma samples with an intact PTEN locus.

Assembly of a mixed interaction network specific to human B cells.Identification and validation of master regulators of germinal center reaction.MYB and FOXM1 are synergistic master regulators of proliferation in germinal center B cells and control a new protein complex involving replication and mitotic-related genes.

Highlights d 3F3-FMA is identified in a screen as a selective ferroptosisimmunostaining reagent d The antigen of 3F3-FMA is identified as the transferrin receptor 1 protein (TfR1) d Anti-TfR1 antibodies can detect ferroptosis by immunofluorescence and flow cytometry d Anti-TfR1 and anti-MDA antibodies detect ferroptosis in xenograft cancer models

The ability of a transcription factor to regulate its targets is modulated by a variety of genetic and epigenetic mechanisms, resulting in highly context-dependent regulatory networks. However, high-throughput methods for the identification of proteins that affect transcription factor activity are still largely unavailable. Here we introduce a systems biology framework, MINDy (Modulator Inference by Network Dynamics), for the genome-wide identification of post-translational modulators of transcription factor activity within a specific cellular context. When used to dissect the regulation of MYC activity in human B lymphocytes, the approach inferred novel modulators of MYC function, which act by distinct mechanisms, including protein turn-over, transcriptional complex formation, and selective enzyme recruitment. MINDy is generally applicable to study the post-translational modulation of mammalian transcription factors in any cellular context. As such it provides a useful resource to dissect context-specific signaling pathways and combinatorial transcriptional regulation.