Insulin receptor orchestrates kidney antibacterial defenses.

Urinary tract infection (UTI) commonly afflicts people with diabetes. This augmented infection risk is partly due to deregulated insulin receptor (IR) signaling in the kidney collecting duct. The collecting duct is composed of intercalated cells (ICs) and principal cells (PCs). Evidence suggests that ICs contribute to UTI defenses. Here, we interrogate how IR deletion in ICs impacts antibacterial defenses against uropathogenic Escherichia coli. We also explore how IR deletion affects immune responses in neighboring PCs with intact IR expression. To accomplish this objective, we profile the transcriptomes of IC and PC populations enriched from kidneys of wild-type and IC-specific IR knock-out mice that have increased UTI susceptibility. Transcriptomic analysis demonstrates that IR deletion suppresses IC-integrated stress responses and innate immune defenses. To define how IR shapes these immune defenses, we employ murine and human kidney cultures. When challenged with bacteria, murine ICs and human kidney cells with deregulated IR signaling cannot engage central components of the integrated stress response-including activating transcriptional factor 4 (ATF4). Silencing ATF4 impairs NFkB activation and promotes infection. In turn, NFkB silencing augments infection and suppresses antimicrobial peptide expression. In diabetic mice and people with diabetes, collecting duct cells show reduced IR expression, impaired integrated stress response engagement, and compromised immunity. Collectively, these translational data illustrate how IR orchestrates collecting duct antibacterial responses and the communication between ICs and PCs.

PP2A is a therapeutically targetable driver of cell fate decisions via a c-Myc/p21 axis in human and murine acute myeloid leukemia.

Dysregulated cellular differentiation is a hallmark of acute leukemogenesis. Phosphatases are widely suppressed in cancers but have not been traditionally associated with differentiation. In this study, we found that the silencing of protein phosphatase 2A (PP2A) directly blocks differentiation in acute myeloid leukemia (AML). Gene expression and mass cytometric profiling revealed that PP2A activation modulates cell cycle and transcriptional regulators that program terminal myeloid differentiation. Using a novel pharmacological agent, OSU-2S, in parallel with genetic approaches, we discovered that PP2A enforced c-Myc and p21 dependent terminal differentiation, proliferation arrest, and apoptosis in AML. Finally, we demonstrated that PP2A activation decreased leukemia-initiating stem cells, increased leukemic blast maturation, and improved overall survival in murine Tet2-/-Flt3ITD/WT and human cell-line derived xenograft AML models in vivo. Our findings identify the PP2A/c-Myc/p21 axis as a critical regulator of the differentiation/proliferation switch in AML that can be therapeutically targeted in malignancies with dysregulated maturation fate.

Microglia-targeted inhibition of miR-17 via mannose-coated lipid nanoparticles improves pathology and behavior in a mouse model of Alzheimer's disease.

Neuroinflammation and accumulation of Amyloid Beta (Aß) accompanied by deterioration of special memory are hallmarks of Alzheimer's disease (AD). Effective preventative and treatment options for AD are still needed. Microglia in AD brains are characterized by elevated levels of microRNA-17 (miR-17), which is accompanied by defective autophagy, Aß accumulation, and increased inflammatory cytokine production. However, the effect of targeting miR-17 on AD pathology and memory loss is not clear. To specifically inhibit miR-17 in microglia, we generated mannose-coated lipid nanoparticles (MLNPs) enclosing miR-17 antagomir (Anti-17 MLNPs), which are targeted to mannose receptors readily expressed on microglia. We used a 5XFAD mouse model (AD) that recapitulates many AD-related phenotypes observed in humans. Our results show that Anti-17 MLNPs, delivered to 5XFAD mice by intra-cisterna magna injection, specifically deliver Anti-17 to microglia. Anti-17 MLNPs downregulated miR-17 expression in microglia but not in neurons, astrocytes, and oligodendrocytes. Anti-17 MLNPs attenuated inflammation, improved autophagy, and reduced Aß burdens in the brains. Additionally, Anti-17 MLNPs reduced the deterioration in spatial memory and decreased anxiety-like behavior in 5XFAD mice. Therefore, targeting miR-17 using MLNPs is a viable strategy to prevent several AD pathologies. This selective targeting strategy delivers specific agents to microglia without the adverse off-target effects on other cell types. Additionally, this approach can be used to deliver other molecules to microglia and other immune cells in other organs.

Targeting OCT3 attenuates doxorubicin-induced cardiac injury.

Doxorubicin is a commonly used anticancer agent that can cause debilitating and irreversible cardiac injury. The initiating mechanisms contributing to this side effect remain unknown, and current preventative strategies offer only modest protection. Using stem-cell-derived cardiomyocytes from patients receiving doxorubicin, we probed the transcriptomic landscape of solute carriers and identified organic cation transporter 3 (OCT3) (SLC22A3) as a critical transporter regulating the cardiac accumulation of doxorubicin. Functional validation studies in heterologous overexpression models confirmed that doxorubicin is transported into cardiomyocytes by OCT3 and that deficiency of OCT3 protected mice from acute and chronic doxorubicin-related changes in cardiovascular function and genetic pathways associated with cardiac damage. To provide proof-of-principle and demonstrate translational relevance of this transport mechanism, we identified several pharmacological inhibitors of OCT3, including nilotinib, and found that pharmacological targeting of OCT3 can also preserve cardiovascular function following treatment with doxorubicin without affecting its plasma levels or antitumor effects in multiple models of leukemia and breast cancer. Finally, we identified a previously unrecognized, OCT3-dependent pathway of doxorubicin-induced cardiotoxicity that results in a downstream signaling cascade involving the calcium-binding proteins S100A8 and S100A9. These collective findings not only shed light on the etiology of doxorubicin-induced cardiotoxicity, but also are of potential translational relevance and provide a rationale for the implementation of a targeted intervention strategy to prevent this debilitating side effect.

AN OUTBREAK OF FELINE INFECTIOUS PERITONITIS IN THREE RELATED SAND CATS (FELIS MARGARITA) IN HUMAN CARE.

Feline infectious peritonitis (FIP) is a systemic disease in felid species caused by infection with mutated forms of feline coronavirus (FCoV), and outbreaks can devastate exotic felid populations in human care. Feline infectious peritonitis was diagnosed in three of four related juvenile sand cats (Felis margarita) from a single institution over a 6-wk period. Case 1 was a 7-mon-old male found deceased with no premonitory signs. Case 2, an 8-mon-old male (littermate to Case 1), and Case 3, a 6-mon-old male (from a different litter with identical parentage), were evaluated for lethargy and anorexia 1 mon after Case 1. Both exhibited transient anisocoria and progressive lethargy, anorexia, and dehydration despite antibiotic and supportive treatment. Approximately 1 wk after initial presentation, Case 2 was humanely euthanized, and Case 3 was found deceased. Necropsy findings included intrathoracic and/or intra-abdominal lymphadenopathy (3/3 cases), bicavitary effusion (2/3), multifocal tan hepatic and intestinal nodules (1/3), and multifocal yellow renal nodules (1/3). Histologically, all cats had severe pyogranulomatous vasculitis in multiple organs, and the presence of FCoV antigen was confirmed using immunohistochemical staining. Next-generation sequencing of the virus from Case 3's affected kidney demonstrated ∼93% homology to the UG-FH8 virus, a serotype 1 feline alphacoronavirus isolated from Denmark. Future research will focus on comparative viral genomic sequencing with the goals of identifying potential sources of FCoV infection and identifying features that may have contributed to the development of FIP in this species.

Genetic analysis of a malignant meningioma and associated metastases.

To identify genes altered in a highly aggressive metastatic meningioma primary as well as its metastases. Exome sequencing of a primary anaplastic meningioma and metastatic lesions in which DNA could be extracted and compared to germline DNA. Genetic analysis of the metastatic sites found 31 common mutations among the primary tumor and two metastatic sites. Additionally, genetic mutations were identified which were either infrequently (MUC3A, ALDH1A3, HOXA1) or not at all previously described in meningiomas (CASS4, CMKLR1). Exome sequencing of a metastatic meningioma and its distant metastases outside the CNS identified mutations that were not previously well described.

ROR1-targeted delivery of miR-29b induces cell cycle arrest and therapeutic benefit in vivo in a CLL mouse model.

Chronic lymphocytic leukemia (CLL) occurs in 2 major forms: aggressive and indolent. Low miR-29b expression in aggressive CLL is associated with poor prognosis. Indiscriminate miR-29b overexpression in the B-lineage of mice causes aberrance, thus warranting the need for selective introduction of miR-29b into B-CLL cells for therapeutic benefit. The oncofetal antigen receptor tyrosine kinase orphan receptor 1 (ROR1) is expressed on malignant B-CLL cells, but not normal B cells, encouraging us with ROR1-targeted delivery for therapeutic miRs. Here, we describe targeted delivery of miR-29b to ROR1+ CLL cells leading to downregulation of DNMT1 and DNMT3A, modulation of global DNA methylation, decreased SP1, and increased p21 expression in cell lines and primary CLL cells in vitro. Furthermore, using an Eµ-TCL1 mouse model expressing human ROR1, we report the therapeutic benefit of enhanced survival via cellular reprograming by downregulation of DNMT1 and DNMT3A in vivo. Gene expression profiling of engrafted murine leukemia identified reprogramming of cell cycle regulators with decreased SP1 and increased p21 expression after targeted miR-29b treatment. This finding was confirmed by protein modulation, leading to cell cycle arrest and survival benefit in vivo. Importantly, SP1 knockdown results in p21-dependent compensation of the miR-29b effect on cell cycle arrest. These studies form a basis for leukemic cell-targeted delivery of miR-29b as a promising therapeutic approach for CLL and other ROR1+ B-cell malignancies.

Diverse AR-V7 cistromes in castration-resistant prostate cancer are governed by HoxB13.

The constitutively active androgen receptor (AR) splice variant 7 (AR-V7) plays an important role in the progression of castration-resistant prostate cancer (CRPC). Although biomarker studies established the role of AR-V7 in resistance to AR-targeting therapies, how AR-V7 mediates genomic functions in CRPC remains largely unknown. Using a ChIP-exo approach, we show AR-V7 binds to distinct genomic regions and recognizes a full-length androgen-responsive element in CRPC cells and patient tissues. Remarkably, we find dramatic differences in AR-V7 cistromes across diverse CRPC cells and patient tissues, regulating different target gene sets involved in CRPC progression. Surprisingly, we discover that HoxB13 is universally required for and colocalizes with AR-V7 binding to open chromatin across CRPC genomes. HoxB13 pioneers AR-V7 binding through direct physical interaction, and collaborates with AR-V7 to up-regulate target oncogenes. Transcriptional coregulation by HoxB13 and AR-V7 was further supported by their coexpression in tumors and circulating tumor cells from CRPC patients. Importantly, HoxB13 silencing significantly decreases CRPC growth through inhibition of AR-V7 oncogenic function. These results identify HoxB13 as a pivotal upstream regulator of AR-V7-driven transcriptomes that are often cell context-dependent in CRPC, suggesting that HoxB13 may serve as a therapeutic target for AR-V7-driven prostate tumors.

CLEAR: coverage-based limiting-cell experiment analysis for RNA-seq.

BACKGROUND: Direct cDNA preamplification protocols developed for single-cell RNA-seq have enabled transcriptome profiling of precious clinical samples and rare cell populations without the need for sample pooling or RNA extraction. We term the use of single-cell chemistries for sequencing low numbers of cells limiting-cell RNA-seq (lcRNA-seq). Currently, there is no customized algorithm to select robust/low-noise transcripts from lcRNA-seq data for between-group comparisons. METHODS: Herein, we present CLEAR, a workflow that identifies reliably quantifiable transcripts in lcRNA-seq data for differentially expressed genes (DEG) analysis. Total RNA obtained from primary chronic lymphocytic leukemia (CLL) CD5+ and CD5- cells were used to develop the CLEAR algorithm. Once established, the performance of CLEAR was evaluated with FACS-sorted cells enriched from mouse Dentate Gyrus (DG). RESULTS: When using CLEAR transcripts vs. using all transcripts in CLL samples, downstream analyses revealed a higher proportion of shared transcripts across three input amounts and improved principal component analysis (PCA) separation of the two cell types. In mouse DG samples, CLEAR identifies noisy transcripts and their removal improves PCA separation of the anticipated cell populations. In addition, CLEAR was applied to two publicly-available datasets to demonstrate its utility in lcRNA-seq data from other institutions. If imputation is applied to limit the effect of missing data points, CLEAR can also be used in large clinical trials and in single cell studies. CONCLUSIONS: lcRNA-seq coupled with CLEAR is widely used in our institution for profiling immune cells (circulating or tissue-infiltrating) for its transcript preservation characteristics. CLEAR fills an important niche in pre-processing lcRNA-seq data to facilitate transcriptome profiling and DEG analysis. We demonstrate the utility of CLEAR in analyzing rare cell populations in clinical samples and in murine neural DG region without sample pooling.

TET1 reprograms the epithelial ovarian cancer epigenome and reveals casein kinase 2α as a therapeutic target.

Ten-eleven translocation methylcytosine dioxygenase-1, TET1, takes part in active DNA demethylation. However, our understanding of DNA demethylation in cancer biology and its clinical significance remain limited. This study showed that TET1 expression correlated with poor survival in advanced-stage epithelial ovarian carcinoma (EOC), and with cell migration, anchorage-independent growth, cancer stemness, and tumorigenicity. In particular, TET1 was highly expressed in serous tubal intraepithelial carcinoma (STIC), a currently accepted type II EOC precursor, and inversely correlated with TP53 mutations. Moreover, TET1 could demethylate the epigenome and activate multiple oncogenic pathways, including an immunomodulation network having casein kinase II subunit alpha (CK2α) as a hub. Patients with TET1high CK2αhigh EOCs had the worst outcomes, and TET1-expressing EOCs were more sensitive to a CK2 inhibitor, both in vitro and in vivo. Our findings uncover the oncogenic and poor prognostic roles of TET1 in EOC and suggest an unexplored role of epigenetic reprogramming in early ovarian carcinogenesis. Moreover, the immunomodulator CK2α represents a promising new therapeutic target, warranting clinical trials of the tolerable CK2 inhibitor, CX4945, for precision medicine against EOC. Copyright © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

SMaSH: Sample matching using SNPs in humans.

BACKGROUND: Inadvertent sample swaps are a real threat to data quality in any medium to large scale omics studies. While matches between samples from the same individual can in principle be identified from a few well characterized single nucleotide polymorphisms (SNPs), omics data types often only provide low to moderate coverage, thus requiring integration of evidence from a large number of SNPs to determine if two samples derive from the same individual or not. METHODS: We select about six thousand SNPs in the human genome and develop a Bayesian framework that is able to robustly identify sample matches between next generation sequencing data sets. RESULTS: We validate our approach on a variety of data sets. Most importantly, we show that our approach can establish identity between different omics data types such as Exome, RNA-Seq, and MethylCap-Seq. We demonstrate how identity detection degrades with sample quality and read coverage, but show that twenty million reads of a fairly low quality RNA-Seq sample are still sufficient for reliable sample identification. CONCLUSION: Our tool, SMASH, is able to identify sample mismatches in next generation sequencing data sets between different sequencing modalities and for low quality sequencing data.

Agonist and antagonist switch DNA motifs recognized by human androgen receptor in prostate cancer.

Human transcription factors recognize specific DNA sequence motifs to regulate transcription. It is unknown whether a single transcription factor is able to bind to distinctly different motifs on chromatin, and if so, what determines the usage of specific motifs. By using a motif-resolution chromatin immunoprecipitation-exonuclease (ChIP-exo) approach, we find that agonist-liganded human androgen receptor (AR) and antagonist-liganded AR bind to two distinctly different motifs, leading to distinct transcriptional outcomes in prostate cancer cells. Further analysis on clinical prostate tissues reveals that the binding of AR to these two distinct motifs is involved in prostate carcinogenesis. Together, these results suggest that unique ligands may switch DNA motifs recognized by ligand-dependent transcription factors in vivo. Our findings also provide a broad mechanistic foundation for understanding ligand-specific induction of gene expression profiles.

FuSpot: a web-based tool for visual evaluation of fusion candidates.

BACKGROUND: Gene fusions often occur in cancer cells and in some cases are the main driver of oncogenesis. Correct identification of oncogenic gene fusions thus has implications for targeted cancer therapy. Recognition of this potential has led to the development of a myriad of sequencing-based fusion detection tools. However, given the same input, many of these detectors will find different fusion points or claim different sets of supporting data. Furthermore, the rate at which these tools falsely detect fusion events in data varies greatly. This discrepancy between tools underscores the fact that computation algorithms still cannot perfectly evaluate evidence; especially when provided with small amounts of supporting data as is typical in fusion detection. We assert that when evidence is provided in an easily digestible form, humans are more proficient in identifying true positives from false positives. RESULTS: We have developed a web tool that, given the genomic coordinates of a candidate fusion breakpoint, will extract fusion and non-fusion reads adjacent to the fusion point from partner transcripts, and color code reads by transcript origin and read orientation for ease of intuitive inspection by the user. Fusion partner transcript read alignments are performed using a novel variant of the Smith-Waterman algorithm. CONCLUSIONS: Combined with dynamic filtering parameters, the visualization provided by our tool introduces a powerful new investigative step that allows researchers to comprehensively evaluate fusion evidence. Additionally, this allows quick identification of false positives that may deceive most fusion detectors, thus eliminating unnecessary gene fusion validation. We apply our visualization tool to publicly available datasets and provide examples of true as well as false positives reported by open source fusion detection tools.

Statistical methods for detecting differentially methylated regions based on MethylCap-seq data.

DNA methylation is a well-established epigenetic mark, whose pattern throughout the genome, especially in the promoter or CpG islands, may be modified in a cell at a disease stage. Recently developed probabilistic approaches allow distributing methylation signals at nucleotide resolution from MethylCap-seq data. Standard statistical methods for detecting differential methylation suffer from 'curse of dimensionality' and sparsity in signals, resulting in high false-positive rates. Strong correlation of signals between CG sites also yields spurious results. In this article, we review applicability of high-dimensional mean vector tests for detection of differentially methylated regions (DMRs) and compare and contrast such tests with other methods for detecting DMRs. Comprehensive simulation studies are conducted to highlight the performance of these tests under different settings. Based on our observation, we make recommendations on the optimal test to use. We illustrate the superiority of mean vector tests in detecting cancer-related canonical gene pathways, which are significantly enriched for acute myeloid leukemia and ovarian cancer.

Prognostic and biologic significance of long non-coding RNA profiling in younger adults with cytogenetically normal acute myeloid leukemia.

Long non-coding ribonucleic acids (RNAs) are a novel class of RNA molecules, which are increasingly recognized as important molecular players in solid and hematologic malignancies. Herein we investigated whether long non-coding RNA expression is associated with clinical and molecular features, as well as outcome of younger adults (aged <60 years) with de novo cytogenetically normal acute myeloid leukemia. Whole transcriptome profiling was performed in a training (n=263) and a validation set (n=114). Using the training set, we identified 24 long non-coding RNAs associated with event-free survival. Linear combination of the weighted expression values of these transcripts yielded a prognostic score. In the validation set, patients with high scores had shorter disease-free (P<0.001), overall (P=0.002) and event-free survival (P<0.001) than patients with low scores. In multivariable analyses, long non-coding RNA score status was an independent prognostic marker for disease-free (P=0.01) and event-free survival (P=0.002), and showed a trend for overall survival (P=0.06). Among multiple molecular alterations tested, which are prognostic in cytogenetically normal acute myeloid leukemia, only double CEBPA mutations, NPM1 mutations and FLT3-ITD associated with distinct long non-coding RNA signatures. Correlation of the long non-coding RNA scores with messenger RNA and microRNA expression identified enrichment of genes involved in lymphocyte/leukocyte activation, inflammation and apoptosis in patients with high scores. We conclude that long non-coding RNA profiling provides meaningful prognostic information in younger adults with cytogenetically normal acute myeloid leukemia. In addition, expression of prognostic long non-coding RNAs associates with oncogenic molecular pathways in this disease. clinicaltrials.gov Identifier: 00048958 (CALGB-8461), 00899223 (CALGB-9665), and 00900224 (CALGB-20202).

Expression and prognostic impact of lncRNAs in acute myeloid leukemia.

Long noncoding RNAs (lncRNAs) are transcripts longer than 200 nucleotides, located within the intergenic stretches or overlapping antisense transcripts of protein coding genes. LncRNAs are involved in numerous biological roles including imprinting, epigenetic regulation, apoptosis, and cell cycle. To determine whether lncRNAs are associated with clinical features and recurrent mutations in older patients (aged ≥60 y) with cytogenetically normal (CN) acute myeloid leukemia (AML), we evaluated lncRNA expression in 148 untreated older CN-AML cases using a custom microarray platform. An independent set of 71 untreated older patients with CN-AML was used to validate the outcome scores using RNA sequencing. Distinctive lncRNA profiles were found associated with selected mutations, such as internal tandem duplications in the FLT3 gene (FLT3-ITD) and mutations in the NPM1, CEBPA, IDH2, ASXL1, and RUNX1 genes. Using the lncRNAs most associated with event-free survival in a training cohort of 148 older patients with CN-AML, we derived a lncRNA score composed of 48 lncRNAs. Patients with an unfavorable compared with favorable lncRNA score had a lower complete response (CR) rate [P < 0.001, odds ratio = 0.14, 54% vs. 89%], shorter disease-free survival (DFS) [P < 0.001, hazard ratio (HR) = 2.88] and overall survival (OS) (P < 0.001, HR = 2.95). The validation set analyses confirmed these results (CR, P = 0.03; DFS, P = 0.009; OS, P = 0.009). Multivariable analyses for CR, DFS, and OS identified the lncRNA score as an independent marker for outcome. In conclusion, lncRNA expression in AML is closely associated with recurrent mutations. A small subset of lncRNAs is correlated strongly with treatment response and survival.

Methyl-CpG/MBD2 Interaction Requires Minimum Separation and Exhibits Minimal Sequence Specificity.

Determining the pattern of methylation at CpG dinucleotides in a cell remains an essential component of epigenetic profiling. The correlations among methylation, gene expression, and accompanying disease have just begun to be explored. Many experiments for sensing methylation use a relatively inexpensive, high-throughput approach with a methyl-binding domain (MBD) protein that preferentially binds to methylated CpGs. Here, we characterize the cooperativity and sequence specificity of MBD2-DNA binding in a pulldown experiment revealing three potential biases in such experiments. The first is caused by steric clashes between two MBD2 proteins at mCpGs separated by 2 bp or less, which suggests that simultaneous binding at these sites is inhibited. This is confirmed by comparing input versus pulldown high-throughput sequencing data on M.SssI-treated samples, from which we also find that pulldown efficiency sharply increases for DNA fragments with four or more mCpGs. Analysis of these two data sets was again employed to investigate MBD2's sequence preferences surrounding a methylated CpG (mCpG). In comparing the distributions of bases at positions with respect to an mCpG, statistically significant preferences for certain bases were found, although the corresponding biases in pulldown efficiency were all <5%. While this suggests that mCpG sequence context can mostly be ignored in MBD2 binding, the statistical certainty exhibited by our high-throughput approach bodes well for future applications.

PrEMeR-CG: inferring nucleotide level DNA methylation values from MethylCap-seq data.

MOTIVATION: DNA methylation is an epigenetic change occurring in genomic CpG sequences that contribute to the regulation of gene transcription both in normal and malignant cells. Next-generation sequencing has been used to characterize DNA methylation status at the genome scale, but suffers from high sequencing cost in the case of whole-genome bisulfite sequencing, or from reduced resolution (inability to precisely define which of the CpGs are methylated) with capture-based techniques. RESULTS: Here we present a computational method that computes nucleotide-resolution methylation values from capture-based data by incorporating fragment length profiles into a model of methylation analysis. We demonstrate that it compares favorably with nucleotide-resolution bisulfite sequencing and has better predictive power with respect to a reference than window-based methods, often used for enrichment data. The described method was used to produce the methylation data used in tandem with gene expression to produce a novel and clinically significant gene signature in acute myeloid leukemia. In addition, we introduce a complementary statistical method that uses this nucleotide-resolution methylation data for detection of differentially methylated features.

Integrated analysis of genome-wide DNA methylation and gene expression profiles in molecular subtypes of breast cancer.

Aberrant DNA methylation of CpG islands, CpG island shores and first exons is known to play a key role in the altered gene expression patterns in all human cancers. To date, a systematic study on the effect of DNA methylation on gene expression using high resolution data has not been reported. In this study, we conducted an integrated analysis of MethylCap-sequencing data and Affymetrix gene expression microarray data for 30 breast cancer cell lines representing different breast tumor phenotypes. As well-developed methods for the integrated analysis do not currently exist, we created a series of four different analysis methods. On the computational side, our goal is to develop methylome data analysis protocols for the integrated analysis of DNA methylation and gene expression data on the genome scale. On the cancer biology side, we present comprehensive genome-wide methylome analysis results for differentially methylated regions and their potential effect on gene expression in 30 breast cancer cell lines representing three molecular phenotypes, luminal, basal A and basal B. Our integrated analysis demonstrates that methylation status of different genomic regions may play a key role in establishing transcriptional patterns in molecular subtypes of human breast cancer.

Tcl1 protein functions as an inhibitor of de novo DNA methylation in B-cell chronic lymphocytic leukemia (CLL).

B-cell chronic lymphocytic leukemia (CLL) is the most common human leukemia. Deregulation of the T-cell leukemia/lymphoma 1 oncogene (TCL1) in mouse B cells causes a CD5(+) leukemia similar to aggressive human CLL. To examine the mechanisms by which Tcl1 protein exerts its oncogenic activity in B cells, we performed proteomics experiments to identify its interacting partners. We found that Tcl1 physically interacts with de novo DNA methylthansferases Dnmt3A and Dnmt3B. We further investigated the effects of Tcl1 up-regulation on the enzymatic activity of Dnmt3A and found that Tcl1 overexpression drastically inhibits Dnmt3A function. In addition, B cells from TCL1 transgenic mice showed a significant decrease in DNA methylation compared with WT controls. Similarly, CLL samples with high Tcl1 expression showed a decrease in DNA methylation compared with CLL samples with low Tcl1 expression. Given the previous reports of inactivating mutations of DNMT3A in acute myelogenous leukemia and myelodysplastic syndrome, our results suggest that inhibition of de novo DNA methylation may be a common oncogenic mechanism in leukemogenesis.