Novel cell adhesion/migration pathways are predictive markers of HDAC inhibitor resistance in cutaneous T cell lymphoma

BACKGROUND: Treatment for Cutaneous T Cell Lymphoma (CTCL) is generally not curative. Therefore, selecting therapy that is effective and tolerable is critical to clinical decision-making. Histone deacetylase inhibitors (HDACi), epigenetic modifier drugs, are commonly used but effective in only ~30% of patients. There are no predictive markers of HDACi response and the CTCL histone acetylation landscape remains unmapped. We sought to identify pre-treatment molecular markers of resistance in CTCL that progressed on HDACi therapy. METHODS: Purified T cells from 39 pre/post-treatment peripheral blood samples and skin biopsies from 20 patients were subjected to RNA-seq and ChIP-seq for histone acetylation marks (H3K14/9 ac, H3K27ac). We correlated significant differences in histone acetylation with gene expression in HDACi-resistant/sensitive CTCL. We extended these findings in additional CTCL patient cohorts (RNA-seq, microarray) and using ELISA in matched CTCL patient plasma. FINDINGS: Resistant CTCL exhibited high levels of histone acetylation, which correlated with increased expression of 338 genes (FDR \u3c 0·05), including some novel to CTCL: BIRC5 (anti-apoptotic); RRM2 (cell cycle); TXNDC5, GSTM1 (redox); and CXCR4, LAIR2 (cell adhesion/migration). Several of these, including LAIR2, were elevated pre-treatment in HDACi-resistant CTCL. In CTCL patient plasma (n = 6), LAIR2 protein was also elevated (p \u3c 0·01) compared to controls. INTERPRETATION: This study is the first to connect genome-wide differences in chromatin acetylation and gene expression to HDACi-resistance in primary CTCL. Our results identify novel markers with high pre-treatment expression, such as LAIR2, as potential prognostic and/or predictors of HDACi-resistance in CTCL. FUNDING: NIH:CA156690, CA188286; NCATS: WU-ICTS UL1 TR000448; Siteman Cancer Center: CA091842

cis-regulatory circuits regulating NEK6 kinase overexpression in transformed B cells Are super-enhancer independent

Alterations in distal regulatory elements that control gene expression underlie many diseases, including cancer. Epigenomic analyses of normal and diseased cells have produced correlative predictions for connections between dysregulated enhancers and target genes involved in pathogenesis. However, with few exceptions, these predicted cis-regulatory circuits remain untested. Here, we dissect cis-regulatory circuits that lead to overexpression of NEK6, a mitosis-associated kinase, in human B cell lymphoma. We find that only a minor subset of predicted enhancers is required for NEK6 expression. Indeed, an annotated super-enhancer is dispensable for NEK6 overexpression and for maintaining the architecture of a B cell-specific regulatory hub. A CTCF cluster serves as a chromatin and architectural boundary to block communication of the NEK6 regulatory hub with neighboring genes. Our findings emphasize that validation of predicted cis-regulatory circuits and super-enhancers is needed to prioritize transcriptional control elements as therapeutic targets

Identification of transcriptional regulatory networks specific to pilocytic astrocytoma.

BackgroundPilocytic Astrocytomas (PAs) are common low-grade central nervous system malignancies for which few recurrent and specific genetic alterations have been identified. In an effort to better understand the molecular biology underlying the pathogenesis of these pediatric brain tumors, we performed higher-order transcriptional network analysis of a large gene expression dataset to identify gene regulatory pathways that are specific to this tumor type, relative to other, more aggressive glial or histologically distinct brain tumours.MethodsRNA derived from frozen human PA tumours was subjected to microarray-based gene expression profiling, using Affymetrix U133Plus2 GeneChip microarrays. This data set was compared to similar data sets previously generated from non-malignant human brain tissue and other brain tumour types, after appropriate normalization.ResultsIn this study, we examined gene expression in 66 PA tumors compared to 15 non-malignant cortical brain tissues, and identified 792 genes that demonstrated consistent differential expression between independent sets of PA and non-malignant specimens. From this entire 792 gene set, we used the previously described PAP tool to assemble a core transcriptional regulatory network composed of 6 transcription factor genes (TFs) and 24 target genes, for a total of 55 interactions. A similar analysis of oligodendroglioma and glioblastoma multiforme (GBM) gene expression data sets identified distinct, but overlapping, networks. Most importantly, comparison of each of the brain tumor type-specific networks revealed a network unique to PA that included repressed expression of ONECUT2, a gene frequently methylated in other tumor types, and 13 other uniquely predicted TF-gene interactions.ConclusionsThese results suggest specific transcriptional pathways that may operate to create the unique molecular phenotype of PA and thus opportunities for corresponding targeted therapeutic intervention. Moreover, this study also demonstrates how integration of gene expression data with TF-gene and TF-TF interaction data is a powerful approach to generating testable hypotheses to better understand cell-type specific genetic programs relevant to cancer

An integrated approach to characterize transcription factor and microRNA regulatory networks involved in Schwann cell response to peripheral nerve injury

BACKGROUND: The regenerative response of Schwann cells after peripheral nerve injury is a critical process directly related to the pathophysiology of a number of neurodegenerative diseases. This SC injury response is dependent on an intricate gene regulatory program coordinated by a number of transcription factors and microRNAs, but the interactions among them remain largely unknown. Uncovering the transcriptional and post-transcriptional regulatory networks governing the Schwann cell injury response is a key step towards a better understanding of Schwann cell biology and may help develop novel therapies for related diseases. Performing such comprehensive network analysis requires systematic bioinformatics methods to integrate multiple genomic datasets. RESULTS: In this study we present a computational pipeline to infer transcription factor and microRNA regulatory networks. Our approach combined mRNA and microRNA expression profiling data, ChIP-Seq data of transcription factors, and computational transcription factor and microRNA target prediction. Using mRNA and microRNA expression data collected in a Schwann cell injury model, we constructed a regulatory network and studied regulatory pathways involved in Schwann cell response to injury. Furthermore, we analyzed network motifs and obtained insights on cooperative regulation of transcription factors and microRNAs in Schwann cell injury recovery. CONCLUSIONS: This work demonstrates a systematic method for gene regulatory network inference that may be used to gain new information on gene regulation by transcription factors and microRNAs

Computational identification of the normal and perturbed genetic networks involved in myeloid differentiation and acute promyelocytic leukemia

A dissection of the genetic networks and circuitries is described for two form of leukaemia. Integrating transcription factor binding and gene expression profiling, networks are revealed that underly this important human disease

Determining subpopulation methylation profiles from bisulfite sequencing data of heterogeneous samples using DXM

Epigenetic changes, such as aberrant DNA methylation, contribute to cancer clonal expansion and disease progression. However, identifying subpopulation-level changes in a heterogeneous sample remains challenging. Thus, we have developed a computational approach, DXM, to deconvolve the methylation profiles of major allelic subpopulations from the bisulfite sequencing data of a heterogeneous sample. DXM does not require prior knowledge of the number of subpopulations or types of cells to expect. We benchmark DXM\u27s performance and demonstrate improvement over existing methods. We further experimentally validate DXM predicted allelic subpopulation-methylation profiles in four Diffuse Large B-Cell Lymphomas (DLBCLs). Lastly, as proof-of-concept, we apply DXM to a cohort of 31 DLBCLs and relate allelic subpopulation methylation profiles to relapse. We thus demonstrate that DXM can robustly find allelic subpopulation methylation profiles that may contribute to disease progression using bisulfite sequencing data of any heterogeneous sample

Enhancer Sequence Variants and Transcription-Factor Deregulation Synergize to Construct Pathogenic Regulatory Circuits in B-Cell Lymphoma

SummaryMost B-cell lymphomas arise in the germinal center (GC), where humoral immune responses evolve from potentially oncogenic cycles of mutation, proliferation, and clonal selection. Although lymphoma gene expression diverges significantly from GC B cells, underlying mechanisms that alter the activities of corresponding regulatory elements (REs) remain elusive. Here we define the complete pathogenic circuitry of human follicular lymphoma (FL), which activates or decommissions REs from normal GC B cells and commandeers enhancers from other lineages. Moreover, independent sets of transcription factors, whose expression was deregulated in FL, targeted commandeered versus decommissioned REs. Our approach revealed two distinct subtypes of low-grade FL, whose pathogenic circuitries resembled GC B or activated B cells. FL-altered enhancers also were enriched for sequence variants, including somatic mutations, which disrupt transcription-factor binding and expression of circuit-linked genes. Thus, the pathogenic regulatory circuitry of FL reveals distinct genetic and epigenetic etiologies for GC B-cell transformation

Mcl1 haploinsufficiency protects mice from Myc-induced acute myeloid leukemia

Antiapoptotic BCL2 family members have been implicated in the pathogenesis of acute myelogenous leukemia (AML), but the functional significance and relative importance of individual proteins (e.g., BCL2, BCL-XL, and myeloid cell leukemia 1 [MCL1]) remain poorly understood. Here, we examined the expression of BCL2, BCL-XL, and MCL1 in primary human hematopoietic subsets and leukemic blasts from AML patients and found that MCL1 transcripts were consistently expressed at high levels in all samples tested. Consistent with this, Mcl1 protein was also highly expressed in myeloid leukemic blasts in a mouse Myc-induced model of AML. We used this model to test the hypothesis that Mcl1 facilitates AML development by allowing myeloid progenitor cells to evade Myc-induced cell death. Indeed, activation of Myc for 7 days in vivo substantially increased myeloid lineage cell numbers, whereas hematopoietic stem, progenitor, and B-lineage cells were depleted. Furthermore, Mcl1 haploinsufficiency abrogated AML development. In addition, deletion of a single allele of Mcl1 from fully transformed AML cells substantially prolonged the survival of transplanted mice. Conversely, the rapid lethality of disease was restored by coexpression of Bcl2 and Myc in Mcl1-haploinsufficient cells. Together, these data demonstrate a critical and dose-dependent role for Mcl1 in AML pathogenesis in mice and suggest that MCL1 may be a promising therapeutic target in patients with de novo AML

Epigenomic regulation of human T-cell leukemia virus by chromatin-insulator CTCF

Human T-cell leukemia virus type 1 (HTLV-1) is a retrovirus that causes an aggressive T-cell malignancy and a variety of inflammatory conditions. The integrated provirus includes a single binding site for the epigenomic insulator, CCCTC-binding protein (CTCF), but its function remains unclear. In the current study, a mutant virus was examined that eliminates the CTCF-binding site. The mutation did not disrupt the kinetics and levels of virus gene expression, or establishment of or reactivation from latency. However, the mutation disrupted the epigenetic barrier function, resulting in enhanced DNA CpG methylation downstream of the CTCF binding site on both strands of the integrated provirus and H3K4Me3, H3K36Me3, and H3K27Me3 chromatin modifications both up- and downstream of the site. A majority of clonal cell lines infected with wild type HTLV-1 exhibited increased plus strand gene expression with CTCF knockdown, while expression in mutant HTLV-1 clonal lines was unaffected. These findings indicate that CTCF binding regulates HTLV-1 gene expression, DNA and histone methylation in an integration site dependent fashion