SUMMARY PARAGRAPH Transcription factors (TF) recognize specific genomic sequences to regulate complex gene expression programs. Although it is well established that TFs bind specific DNA sequences using a combination of base readout and shape recognition, some fundamental aspects of protein-DNA binding remain poorly understood 1 , 2 . Many DNA-binding proteins induce changes in the DNA structure outside the intrinsic B-DNA envelope. However, how the energetic cost associated with distorting DNA contributes to recognition has proven difficult to study because the distorted DNA exists in low-abundance in the unbound ensemble 3 – 9 . Here, we use a novel high-throughput assay called SaMBA ( Sa turation M ismatch- B inding A ssay) to investigate the role of DNA conformational penalties in TF-DNA recognition. In SaMBA, mismatches are introduced to pre-induce DNA structural distortions much larger than those induced by changes in Watson-Crick sequence. Strikingly, approximately 10% of mismatches increased TF binding, and at least one mismatch was found that increased the binding affinity for each of 22 examined TFs. Mismatches also converted non-specific sites into high-affinity sites, and high-affinity sites into super-sites stronger than any known canonical binding site. Determination of high-resolution X-ray structures, combined with NMR measurements and structural analyses revealed that many of the mismatches that increase binding induce distortions similar to those induced by protein binding, thus pre-paying some of the energetic cost to deform the DNA. Our work indicates that conformational penalties are a major determinant of protein-DNA recognition, and reveals mechanisms by which mismatches can recruit TFs and thus modulate replication and repair activities in the cell 10 , 11 .

Glucocorticoids (GCs), including dexamethasone (dex), are a central component of combination chemotherapy for childhood B-cell precursor acute lymphoblastic leukemia (B-ALL). GCs work by activating the GC receptor (GR), a ligand-induced transcription factor, which in turn regulates genes that induce leukemic cell death. Which GR-regulated genes are required for GC cytotoxicity, which pathways affect their regulation, and how resistance arises are not well understood. Here, we systematically integrate the transcriptional response of B-ALL to GCs with a next-generation short hairpin RNA screen to identify GC-regulated "effector" genes that contribute to cell death, as well as genes that affect the sensitivity of B-ALL cells to dex. This analysis reveals a pervasive role for GCs in suppression of B-cell development genes that is linked to therapeutic response. Inhibition of phosphatidylinositol 3-kinase δ (PI3Kδ), a linchpin in the pre-B-cell receptor and interleukin 7 receptor signaling pathways critical to B-cell development (with CAL-101 [idelalisib]), interrupts a double-negative feedback loop, enhancing GC-regulated transcription to synergistically kill even highly resistant B-ALL with diverse genetic backgrounds. This work not only identifies numerous opportunities for enhanced lymphoid-specific combination chemotherapies that have the potential to overcome treatment resistance, but is also a valuable resource for understanding GC biology and the mechanistic details of GR-regulated transcription.

Glucocorticoids (GCs) are used in combination chemotherapies as front-line treatment for B cell acute lymphoblastic leukemia (B-ALL). Although effective, many patients relapse and become resistant to chemotherapy and GCs in particular. Why these patients relapse is not clear. We took a comprehensive, functional genomics approach to identify sources of GC resistance. A genome-wide shRNA screen identified the transcriptional coactivators EHMT2, EHMT1, and CBX3 as important contributors to GC-induced cell death. This complex selectively supports GC-induced expression of genes contributing to cell death. A metaanalysis of gene expression data from B-ALL patient specimens revealed that Aurora kinase B (AURKB), which restrains GC signaling by phosphorylating EHMT1-2, is overexpressed in relapsed B-ALL, suggesting it as a potential contributor to relapse. Inhibition of AURKB enhanced GC-induced expression of cell death genes, resulting in potentiation of GC cytotoxicity in cell lines and relapsed B-ALL patient samples. This function for AURKB is distinct from its canonical role in the cell cycle. These results show the utility of functional genomics in understanding mechanisms of resistance and rapidly identifying combination chemotherapeutics.

Growth plate chondrocytes produce proteoglycan-rich type II collagen extracellular matrix (ECM). During cell maturation and hypertrophy, ECM is reorganized via a process regulated by 1α,25 (OH) 2 D 3 and involving matrix metalloproteinases (MMPs), including MMP-3and MMP-2. 1α,25 (OH) 2 D 3 regulates MMP incorporation into matrix vesicles (MVs), where they are stored until released. Like plasma membranes (PM), MVs contain the 1α,25(OH) 2 D 3 -binding protein ERp60, phospholipase A 2 (PLA 2 ), and caveolin-1, but lack nuclear vitamin D receptors (VDRs). Chondrocytes produce 1α,25(OH) 2 D 3 (10 −8 M), which binds ERp60, activating PLA 2 , and resulting lysophospholipids lead MV membrane disorganization, releasing active MMPs. MV MMP-3 activates TGF-β1 stored in the ECM as large latent TGF-β1 complexes, consisting of latent TGF-β1 binding protein, latency associated peptide, and latent TGF-β1. Others have shown that MMP-2 specifically activates TGF-β2. TGF-β1 regulates 1α,25(OH) 2 D 3 -production, providing a mechanism for local control of growth factor activation. 1α,25(OH) 2 D 3 activates PKCα in the PM via ERp60-signaling through PLA 2 , lysophospholipid production, and PLCβ. It also regulates distribution of phospholipids and PKC isoforms between MVs and PMs, enriching the MVs in PKCζ. Direct activation of MMP-3 in MVs requires ERp60. However, when MVs are treated with 1α,25 (OH) 2 D 3 , PKCζ activity is decreased and PKCα is unaffected, suggesting a more complex feedback mechanism, potentially involving MV lipid signaling.