Cell-type-directed design of synthetic enhancers.

Transcriptional enhancers act as docking stations for combinations of transcription factors and thereby regulate spatiotemporal activation of their target genes1. It has been a long-standing goal in the field to decode the regulatory logic of an enhancer and to understand the details of how spatiotemporal gene expression is encoded in an enhancer sequence. Here we show that deep learning models2-6, can be used to efficiently design synthetic, cell-type-specific enhancers, starting from random sequences, and that this optimization process allows detailed tracing of enhancer features at single-nucleotide resolution. We evaluate the function of fully synthetic enhancers to specifically target Kenyon cells or glial cells in the fruit fly brain using transgenic animals. We further exploit enhancer design to create 'dual-code' enhancers that target two cell types and minimal enhancers smaller than 50 base pairs that are fully functional. By examining the state space searches towards local optima, we characterize enhancer codes through the strength, combination and arrangement of transcription factor activator and transcription factor repressor motifs. Finally, we apply the same strategies to successfully design human enhancers, which adhere to enhancer rules similar to those of Drosophila enhancers. Enhancer design guided by deep learning leads to better understanding of how enhancers work and shows that their code can be exploited to manipulate cell states.

Suz12 inactivation cooperates with JAK3 mutant signaling in the development of T-cell acute lymphoblastic leukemia.

The polycomb repressive complex 2, with core components EZH2, SUZ12, and EED, is responsible for writing histone 3 lysine 27 trimethylation histone marks associated with gene repression. Analysis of sequence data from 419 T-cell acute lymphoblastic leukemia (T-ALL) cases demonstrated a significant association between SUZ12 and JAK3 mutations. Here we show that CRISPR/Cas9-mediated inactivation of Suz12 cooperates with mutant JAK3 to drive T-cell transformation and T-ALL development. Gene expression profiling integrated with ChIP-seq and ATAC-seq data established that inactivation of Suz12 led to increased PI3K/mammalian target of rapamycin (mTOR), vascular endothelial growth factor (VEGF), and WNT signaling. Moreover, a drug screen revealed that JAK3/Suz12 mutant leukemia cells were more sensitive to histone deacetylase (HDAC)6 inhibition than JAK3 mutant leukemia cells. Among the broad genome and gene expression changes observed on Suz12 inactivation, our integrated analysis identified the PI3K/mTOR, VEGF/VEGF receptor, and HDAC6/HSP90 pathways as specific vulnerabilities in T-ALL cells with combined JAK3 and SUZ12 mutations.

Malt1 self-cleavage is critical for regulatory T cell homeostasis and anti-tumor immunity in mice.

Mucosa-associated lymphoid tissue 1 (Malt1) regulates immune cell function by mediating the activation of nuclear factor κB (NF-κB) signaling through both its adaptor and proteolytic function. Malt1 is also a target of its own protease activity and this self-cleavage further contributes to NF-κB activity. Until now, the functional distinction between Malt1 self-cleavage and its general protease function in regulating NF-κB signaling and immune activation remained unclear. Here we demonstrate, using a new mouse model, the importance of Malt1 self-cleavage in regulating expression of NF-κB target genes and subsequent T cell activation. Significantly, we further establish that Treg homeostasis is critically linked to Malt1 function via a Treg intrinsic and extrinsic mechanism. TCR-mediated Malt1 proteolytic activity and self-cleavage was found to drive Il2 expression in conventional CD4+ T cells, thereby regulating Il2 availability for Treg homeostasis. Remarkably, the loss of Malt1-mediated self-cleavage alone was sufficient to cause a significant Treg deficit resulting in increased anti-tumor immune reactivity without associated autoimmunity complications. These results establish for the first time that inhibition of MALT1 proteolytic activity could be a viable therapeutic strategy to augment anti-tumor immunity.

Hedgehog pathway activation in T-cell acute lymphoblastic leukemia predicts response to SMO and GLI1 inhibitors.

T-cell acute lymphoblastic leukemia (T-ALL) is an aggressive childhood leukemia that is caused by the accumulation of multiple genomic lesions resulting in transcriptional deregulation and increased cell proliferation and survival. Through analysis of gene expression data, we provide evidence that the hedgehog pathway is activated in 20% of T-ALL samples. Hedgehog pathway activation is associated with ectopic expression of the hedgehog ligands Sonic hedgehog (SHH) or Indian hedgehog (IHH), and with upregulation of the transcription factor GLI1 Ectopic expression of SHH or IHH in mouse T cells in vivo caused hedgehog pathway activation in both lymphoid and epithelial cells in the thymus and resulted in increased expression of important T-cell stimulatory ligands (Dll4, Il7, and Vegf) by thymic epithelial cells. In T-ALL cell lines, pharmacological inhibition or short interfering RNA-mediated knockdown of SMO or GLI1 led to decreased cell proliferation. Moreover, primary T-ALL cases with high GLI1 messenger RNA levels, but not those with low or undetectable GLI1 expression, were sensitive to hedgehog pathway inhibition by GANT61 or GDC-0449 (vismodegib) using ex vivo cultures and in vivo xenograft models. We identify the hedgehog pathway as a novel therapeutic target in T-ALL and demonstrate that hedgehog inhibitors approved by the US Food and Drug Administration could be used for the treatment of this rare leukemia.

NUP214-ABL1-mediated cell proliferation in T-cell acute lymphoblastic leukemia is dependent on the LCK kinase and various interacting proteins.

The NUP214-ABL1 fusion protein is a constitutively active protein tyrosine kinase that is found in 6% of patients with T-cell acute lymphoblastic leukemia and that promotes proliferation and survival of T-lymphoblasts. Although NUP214-ABL1 is sensitive to ABL1 kinase inhibitors, development of resistance to these compounds is a major clinical problem, underlining the need for additional drug targets in the sparsely studied NUP214-ABL1 signaling network. In this work, we identify and validate the SRC family kinase LCK as a protein whose activity is absolutely required for the proliferation and survival of T-cell acute lymphoblastic leukemia cells that depend on NUP214-ABL1 activity. These findings underscore the potential of SRC kinase inhibitors and of the dual ABL1/SRC kinase inhibitors dasatinib and bosutinib for the treatment of NUP214-ABL1-positive T-cell acute lymphoblastic leukemia. In addition, we used mass spectrometry to identify protein interaction partners of NUP214-ABL1. Our results strongly support that the signaling network of NUP214-ABL1 is distinct from that previously reported for BCR-ABL1. Moreover, we found that three NUP214-ABL1-interacting proteins, MAD2L1, NUP155, and SMC4, are strictly required for the proliferation and survival of NUP214-ABL1-positive T-cell acute lymphoblastic leukemia cells. In conclusion, this work identifies LCK, MAD2L1, NUP155 and SMC4 as four new potential drug targets in NUP214-ABL1-positive T-cell acute lymphoblastic leukemia.

Single-cell spatial multi-omics and deep learning dissect enhancer-driven gene regulatory networks in liver zonation.

In the mammalian liver, hepatocytes exhibit diverse metabolic and functional profiles based on their location within the liver lobule. However, it is unclear whether this spatial variation, called zonation, is governed by a well-defined gene regulatory code. Here, using a combination of single-cell multiomics, spatial omics, massively parallel reporter assays and deep learning, we mapped enhancer-gene regulatory networks across mouse liver cell types. We found that zonation affects gene expression and chromatin accessibility in hepatocytes, among other cell types. These states are driven by the repressors TCF7L1 and TBX3, alongside other core hepatocyte transcription factors, such as HNF4A, CEBPA, FOXA1 and ONECUT1. To examine the architecture of the enhancers driving these cell states, we trained a hierarchical deep learning model called DeepLiver. Our study provides a multimodal understanding of the regulatory code underlying hepatocyte identity and their zonation state that can be used to engineer enhancers with specific activity levels and zonation patterns.

Cooperative Enhancer Activation by TLX1 and STAT5 Drives Development of NUP214-ABL1/TLX1-Positive T Cell Acute Lymphoblastic Leukemia.

The NUP214-ABL1 fusion is a constitutively activated tyrosine kinase that is significantly associated with overexpression of the TLX1 and TLX3 transcription factors in T cell acute lymphoblastic leukemia (T-ALL). Here we show that NUP214-ABL1 cooperates with TLX1 in driving T-ALL development using a transgenic mouse model and human T-ALL cells. Using integrated ChIP-sequencing, ATAC-sequencing, and RNA-sequencing data, we demonstrate that TLX1 and STAT5, the downstream effector of NUP214-ABL1, co-bind poised enhancer regions, and cooperatively activate the expression of key proto-oncogenes such as MYC and BCL2. Inhibition of STAT5, downregulation of TLX1 or MYC, or interference with enhancer function through BET-inhibitor treatment leads to reduction of target gene expression and induction of leukemia cell death.

HOXA9 Cooperates with Activated JAK/STAT Signaling to Drive Leukemia Development.

Leukemia is caused by the accumulation of multiple genomic lesions in hematopoietic precursor cells. However, how these events cooperate during oncogenic transformation remains poorly understood. We studied the cooperation between activated JAK3/STAT5 signaling and HOXA9 overexpression, two events identified as significantly co-occurring in T-cell acute lymphoblastic leukemia. Expression of mutant JAK3 and HOXA9 led to a rapid development of leukemia originating from multipotent or lymphoid-committed progenitors, with a significant decrease in disease latency compared with JAK3 or HOXA9 alone. Integrated RNA sequencing, chromatin immunoprecipitation sequencing, and Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) revealed that STAT5 and HOXA9 have co-occupancy across the genome, resulting in enhanced STAT5 transcriptional activity and ectopic activation of FOS/JUN (AP1). Our data suggest that oncogenic transcription factors such as HOXA9 provide a fertile ground for specific signaling pathways to thrive, explaining why JAK/STAT pathway mutations accumulate in HOXA9-expressing cells.Significance: The mechanism of oncogene cooperation in cancer development remains poorly characterized. In this study, we model the cooperation between activated JAK/STAT signaling and ectopic HOXA9 expression during T-cell leukemia development. We identify a direct cooperation between STAT5 and HOXA9 at the transcriptional level and identify PIM1 kinase as a possible drug target in mutant JAK/STAT/HOXA9-positive leukemia cases. Cancer Discov; 8(5); 616-31. ©2018 AACR.This article is highlighted in the In This Issue feature, p. 517.

Rer1p maintains ciliary length and signaling by regulating γ-secretase activity and Foxj1a levels.

Cilia project from the surface of most vertebrate cells and are important for several physiological and developmental processes. Ciliary defects are linked to a variety of human diseases, named ciliopathies, underscoring the importance of understanding signaling pathways involved in cilia formation and maintenance. In this paper, we identified Rer1p as the first endoplasmic reticulum/cis-Golgi-localized membrane protein involved in ciliogenesis. Rer1p, a protein quality control receptor, was highly expressed in zebrafish ciliated organs and regulated ciliary structure and function. Both in zebrafish and mammalian cells, loss of Rer1p resulted in the shortening of cilium and impairment of its motile or sensory function, which was reflected by hearing, vision, and left-right asymmetry defects as well as decreased Hedgehog signaling. We further demonstrate that Rer1p depletion reduced ciliary length and function by increasing γ-secretase complex assembly and activity and, consequently, enhancing Notch signaling as well as reducing Foxj1a expression.

Exome sequencing identifies mutation in CNOT3 and ribosomal genes RPL5 and RPL10 in T-cell acute lymphoblastic leukemia.

T-cell acute lymphoblastic leukemia (T-ALL) is caused by the cooperation of multiple oncogenic lesions. We used exome sequencing on 67 T-ALLs to gain insight into the mutational spectrum in these leukemias. We detected protein-altering mutations in 508 genes, with an average of 8.2 mutations in pediatric and 21.0 mutations in adult T-ALL. Using stringent filtering, we predict seven new oncogenic driver genes in T-ALL. We identify CNOT3 as a tumor suppressor mutated in 7 of 89 (7.9%) adult T-ALLs, and its knockdown causes tumors in a sensitized Drosophila melanogaster model. In addition, we identify mutations affecting the ribosomal proteins RPL5 and RPL10 in 12 of 122 (9.8%) pediatric T-ALLs, with recurrent alterations of Arg98 in RPL10. Yeast and lymphoid cells expressing the RPL10 Arg98Ser mutant showed a ribosome biogenesis defect. Our data provide insights into the mutational landscape of pediatric versus adult T-ALL and identify the ribosome as a potential oncogenic factor.

High accuracy mutation detection in leukemia on a selected panel of cancer genes.

With the advent of whole-genome and whole-exome sequencing, high-quality catalogs of recurrently mutated cancer genes are becoming available for many cancer types. Increasing access to sequencing technology, including bench-top sequencers, provide the opportunity to re-sequence a limited set of cancer genes across a patient cohort with limited processing time. Here, we re-sequenced a set of cancer genes in T-cell acute lymphoblastic leukemia (T-ALL) using Nimblegen sequence capture coupled with Roche/454 technology. First, we investigated how a maximal sensitivity and specificity of mutation detection can be achieved through a benchmark study. We tested nine combinations of different mapping and variant-calling methods, varied the variant calling parameters, and compared the predicted mutations with a large independent validation set obtained by capillary re-sequencing. We found that the combination of two mapping algorithms, namely BWA-SW and SSAHA2, coupled with the variant calling algorithm Atlas-SNP2 yields the highest sensitivity (95%) and the highest specificity (93%). Next, we applied this analysis pipeline to identify mutations in a set of 58 cancer genes, in a panel of 18 T-ALL cell lines and 15 T-ALL patient samples. We confirmed mutations in known T-ALL drivers, including PHF6, NF1, FBXW7, NOTCH1, KRAS, NRAS, PIK3CA, and PTEN. Interestingly, we also found mutations in several cancer genes that had not been linked to T-ALL before, including JAK3. Finally, we re-sequenced a small set of 39 candidate genes and identified recurrent mutations in TET1, SPRY3 and SPRY4. In conclusion, we established an optimized analysis pipeline for Roche/454 data that can be applied to accurately detect gene mutations in cancer, which led to the identification of several new candidate T-ALL driver mutations.