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Meyer, Clifford

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Meyer

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Clifford

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Meyer, Clifford
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    A systematic approach identifies FOXA1 as a key factor in the loss of epithelial traits during the epithelial-to-mesenchymal transition in lung cancer
    (BioMed Central, 2013) Wang, Haiyun; Meyer, Clifford; Fei, Teng; Wang, Gang; Zhang, Fan; Liu, X Shirley
    Background: The epithelial-to-mesenchymal transition is an important mechanism in cancer metastasis. Although transcription factors including SNAIL, SLUG, and TWIST1 regulate the epithelial-to-mesenchymal transition, other unknown transcription factors could also be involved. Identification of the full complement of transcription factors is essential for a more complete understanding of gene regulation in this process. Chromatin immunoprecipitation-sequencing (ChIP-Seq) technologies have been used to detect genome-wide binding of transcription factors; here, we developed a systematic approach to integrate existing ChIP-Seq and transcriptome data. We scanned multiple transcription factors to investigate their functional impact on the epithelial-to-mesenchymal transition in the human A549 lung adenocarcinoma cell line. Results: Among the transcription factors tested, impact scores identified the forkhead box protein A1 (FOXA1) as the most significant transcription factor in the epithelial-to-mesenchymal transition. FOXA1 physically associates with the promoters of its predicted target genes. Several critical epithelial-to-mesenchymal transition effectors involved in cellular adhesion and cellular communication were identified in the regulatory network of FOXA1, including FOXA2, FGA, FGB, FGG, and FGL1. The implication of FOXA1 in the epithelial-to-mesenchymal transition via its regulatory network indicates that FOXA1 may play an important role in the initiation of lung cancer metastasis. Conclusions: We identified FOXA1 as a potentially important transcription factor and negative regulator in the initial stages of lung cancer metastasis. FOXA1 may modulate the epithelial-to-mesenchymal transition via its transcriptional regulatory network. Further, this study demonstrates how ChIP-Seq and expression data could be integrated to delineate the impact of transcription factors on a specific biological process.
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    Analysis of optimized DNase-seq reveals intrinsic bias in transcription factor footprint identification
    (2014) He, Housheng Hansen; Meyer, Clifford; Hu, Sheng'en Shawn; Chen, Mei-Wei; Zang, Chongzhi; Liu, Yin; Rao, Prakash K.; Fei, Teng; Xu, Han; Long, Henry; Liu, X. Shirley; Brown, Myles
    DNase-seq is a powerful technique for identifying cis-regulatory elements across the genome. We studied the key experimental parameters to optimize the performance of DNase-seq. We found that sequencing short 50-100bp fragments that accumulate in long inter-nucleosome linker regions is more efficient for identifying transcription factor binding sites than using longer fragments. We also assessed the potential of DNase-seq to predict transcription factor occupancy through the generation of nucleotide-resolution transcription factor footprints. In modeling the sequence-specific DNaseI cutting bias we found a surprisingly strong effect that varied over more than two orders of magnitude. This confounds DNaseI footprint analysis to the extent that the nucleotide resolution cleavage patterns at most transcription factor binding sites are derived from intrinsic DNaseI cleavage bias rather than from specific protein-DNA interactions. In contrast, quantitative comparison of DNaseI hypersensitivity between states can predict transcription factor occupancy associated with particular biological perturbations.
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    MethylPurify: tumor purity deconvolution and differential methylation detection from single tumor DNA methylomes
    (BioMed Central, 2014) Zheng, Xiaoqi; Zhao, Qian; Wu, Hua-Jun; Li, Wei; Wang, Haiyun; Meyer, Clifford; Qin, Qian Alvin; Xu, Han; Zang, Chongzhi; Jiang, Peng; Li, Fuqiang; Hou, Yong; He, Jianxing; Wang, Jun; Zhang, Peng; Zhang, Yong; Liu, Xiaole
    We propose a statistical algorithm MethylPurify that uses regions with bisulfite reads showing discordant methylation levels to infer tumor purity from tumor samples alone. MethylPurify can identify differentially methylated regions (DMRs) from individual tumor methylome samples, without genomic variation information or prior knowledge from other datasets. In simulations with mixed bisulfite reads from cancer and normal cell lines, MethylPurify correctly inferred tumor purity and identified over 96% of the DMRs. From patient data, MethylPurify gave satisfactory DMR calls from tumor methylome samples alone, and revealed potential missed DMRs by tumor to normal comparison due to tumor heterogeneity. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0419-x) contains supplementary material, which is available to authorized users.
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    Gene expression profiling of human breast tissue samples using SAGE-Seq
    (Cold Spring Harbor Laboratory Press, 2010) Wu, Z. J.; Meyer, Clifford; Choudhury, S.; Shipitsin, M.; Maruyama, R.; Bessarabova, M.; Nikolskaya, T.; Sukumar, S.; Schwartzman, A.; Liu, Jun; Polyak, Kornelia; Liu, Xiaole
    We present a powerful application of ultra high-throughput sequencing, SAGE-Seq, for the accurate quantification of normal and neoplastic mammary epithelial cell transcriptomes. We develop data analysis pipelines that allow the mapping of sense and antisense strands of mitochondrial and RefSeq genes, the normalization between libraries, and the identification of differentially expressed genes. We find that the diversity of cancer transcriptomes is significantly higher than that of normal cells. Our analysis indicates that transcript discovery plateaus at 10 million reads/sample, and suggests a minimum desired sequencing depth around five million reads. Comparison of SAGE-Seq and traditional SAGE on normal and cancerous breast tissues reveals higher sensitivity of SAGE-Seq to detect less-abundant genes, including those encoding for known breast cancer-related transcription factors and G protein–coupled receptors (GPCRs). SAGE-Seq is able to identify genes and pathways abnormally activated in breast cancer that traditional SAGE failed to call. SAGE-Seq is a powerful method for the identification of biomarkers and therapeutic targets in human disease.
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    MM-ChIP enables integrative analysis of cross-platform and between-laboratory ChIP-chip or ChIP-seq data
    (Springer Science + Business Media, 2011) Chen, Yiwen; Meyer, Clifford; Liu, Tao; Li, Wei; Liu, Jun; Liu, Xiaole
    The ChIP-chip and ChIP-seq techniques enable genome-wide mapping of in vivo protein-DNA interactions and chromatin states. The cross-platform and between-laboratory variation poses a challenge to the comparison and integration of results from different ChIP experiments. We describe a novel method, MM-ChIP, which integrates information from cross-platform and between-laboratory ChIP-chip or ChIP-seq datasets. It improves both the sensitivity and the specificity of detecting ChIP-enriched regions, and is a useful meta-analysis tool for driving discoveries from multiple data sources.
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    Cell-type selective chromatin remodeling defines the active subset of FOXA1-bound enhancers
    (Cold Spring Harbor Laboratory Press, 2008) Eeckhoute, J.; Lupien, M.; Meyer, Clifford; Verzi, M. P.; Shivdasani, Ramesh; Liu, Xiaole; Brown, Myles
    Selective activity of a specific set of enhancers defines tissue-specific gene transcription. The pioneer factor FOXA1 has been shown to induce functional enhancer competency through chromatin openings. We have previously found that FOXA1 is recruited to thousands of regions across the genome of a given cell type. Here, we monitored the chromatin structure at FOXA1 binding sites on a chromosome-wide scale using formaldehyde assisted isolation of regulatory elements (FAIRE). Surprisingly, we find that a significant fraction of FOXA1-bound sites have a relatively closed chromatin conformation linked to a shift of the epigenetic signature toward repressive histone marks. Importantly, these sites are not correlated with gene expression in a given cell type suggesting that FOXA1 is required, but not sufficient, for the functional activity of bound enhancers. Interestingly, we find that a significant proportion of the inactive FOXA1-bound regulatory sites in one cell type are actually functional in another cellular context. We found that at least half of the FOXA1 binding sites from a given cell type are shared with another cell lineage. Mechanisms that restrict the activity of shared FOXA1-bound enhancers likely play a significant role in defining the cell-type-specific functions of FOXA1.
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    Differentiation-Specific Histone Modifications Reveal Dynamic Chromatin Interactions and Partners for the Intestinal Transcription Factor CDX2
    (Elsevier BV, 2010) Verzi, Michael P.; Shin, Hyunjin; He, H. Hansen; Sulahian, Rita; Meyer, Clifford; Montgomery, Robert K.; Fleet, James C.; Brown, Myles; Liu, Xiaole; Shivdasani, Ramesh
    Cell differentiation requires remodeling of tissue-specific gene loci and activities of key transcriptional regulators, which are recognized for their dominant control over cellular programs. Using epigenomic methods, we characterized enhancer elements specifically modified in differentiating intestinal epithelial cells and found enrichment of transcription factor-binding motifs corresponding to CDX2, a critical regulator of the intestine. Directed investigation revealed surprising lability in CDX2 occupancy of the genome, with redistribution from hundreds of sites occupied only in proliferating cells to thousands of new sites in differentiated cells. Knockout mice confirmed distinct Cdx2 requirements in dividing and mature adult intestinal cells, including responsibility for the active enhancer configuration associated with maturity. Dynamic CDX2 occupancy corresponds with condition-specific gene expression and, importantly, to differential co-occupancy with other tissue-restricted transcription factors such as GATA6 and HNF4A. These results reveal dynamic, context-specific functions and mechanisms of a prominent transcriptional regulator within a cell lineage.
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    ChiLin: a comprehensive ChIP-seq and DNase-seq quality control and analysis pipeline
    (BioMed Central, 2016) Qin, Qian; Mei, Shenglin; Wu, Qiu; Sun, Hanfei; Li, Lewyn; Taing, Len; Chen, Sujun; Li, Fugen; Liu, Tao; Zang, Chongzhi; Xu, Han; Chen, Yiwen; Meyer, Clifford; Zhang, Yong; Brown, Myles; Long, Henry W.; Liu, X. Shirley
    Background: Transcription factor binding, histone modification, and chromatin accessibility studies are important approaches to understanding the biology of gene regulation. ChIP-seq and DNase-seq have become the standard techniques for studying protein-DNA interactions and chromatin accessibility respectively, and comprehensive quality control (QC) and analysis tools are critical to extracting the most value from these assay types. Although many analysis and QC tools have been reported, few combine ChIP-seq and DNase-seq data analysis and quality control in a unified framework with a comprehensive and unbiased reference of data quality metrics. Results: ChiLin is a computational pipeline that automates the quality control and data analyses of ChIP-seq and DNase-seq data. It is developed using a flexible and modular software framework that can be easily extended and modified. ChiLin is ideal for batch processing of many datasets and is well suited for large collaborative projects involving ChIP-seq and DNase-seq from different designs. ChiLin generates comprehensive quality control reports that include comparisons with historical data derived from over 23,677 public ChIP-seq and DNase-seq samples (11,265 datasets) from eight literature-based classified categories. To the best of our knowledge, this atlas represents the most comprehensive ChIP-seq and DNase-seq related quality metric resource currently available. These historical metrics provide useful heuristic quality references for experiment across all commonly used assay types. Using representative datasets, we demonstrate the versatility of the pipeline by applying it to different assay types of ChIP-seq data. The pipeline software is available open source at https://github.com/cfce/chilin. Conclusion: ChiLin is a scalable and powerful tool to process large batches of ChIP-seq and DNase-seq datasets. The analysis output and quality metrics have been structured into user-friendly directories and reports. We have successfully compiled 23,677 profiles into a comprehensive quality atlas with fine classification for users. Electronic supplementary material The online version of this article (doi:10.1186/s12859-016-1274-4) contains supplementary material, which is available to authorized users.
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    High-dimensional genomic data bias correction and data integration using MANCIE
    (Nature Publishing Group, 2016) Zang, Chongzhi; Wang, Tao; Deng, Ke; Li, Bo; Hu, Sheng'en; Qin, Qian; Xiao, Tengfei; Zhang, Shihua; Meyer, Clifford; He, Housheng Hansen; Brown, Myles; Liu, Jun; Xie, Yang; Liu, X. Shirley
    High-dimensional genomic data analysis is challenging due to noises and biases in high-throughput experiments. We present a computational method matrix analysis and normalization by concordant information enhancement (MANCIE) for bias correction and data integration of distinct genomic profiles on the same samples. MANCIE uses a Bayesian-supported principal component analysis-based approach to adjust the data so as to achieve better consistency between sample-wise distances in the different profiles. MANCIE can improve tissue-specific clustering in ENCODE data, prognostic prediction in Molecular Taxonomy of Breast Cancer International Consortium and The Cancer Genome Atlas data, copy number and expression agreement in Cancer Cell Line Encyclopedia data, and has broad applications in cross-platform, high-dimensional data integration.
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    Response and resistance to BET bromodomain inhibitors in triple negative breast cancer
    (2015) Shu, Shaokun; Lin, Charles Y.; He, Housheng Hansen; Witwicki, Robert; Tabassum, Doris P.; Roberts, Justin M.; Janiszewska, Michalina; Huh, Sung Jin; Liang, Yi; Ryan, Jeremy; Doherty, Ernest; Mohammed, Hisham; Guo, Hao; Stover, Daniel G.; Ekram, Muhammad B.; Brown, Jonathan; D'Santos, Clive; Krop, Ian; Dillon, Deborah; McKeown, Michael; Ott, Christopher; Qi, Jun; Ni, Min; Rao, Prakash K.; Duarte, Melissa; Wu, Shwu-Yuan; Chiang, Cheng-Ming; Anders, Lars; Young, Richard A.; Winer, Eric; Letai, Antony; Barry, William T.; Carroll, Jason S.; Long, Henry; Brown, Myles; Liu, X. Shirley; Meyer, Clifford; Bradner, James E; Polyak, Kornelia
    Triple negative breast cancer (TNBC) is a heterogeneous and clinically aggressive disease for which there is no targeted therapy1-3. BET bromodomain inhibitors, which have shown efficacy in several models of cancer4-6, have not been evaluated in TNBC. These inhibitors displace BET bromodomain proteins such as BRD4 from chromatin by competing with their acetyllysine recognition modules, leading to inhibition of oncogenic transcriptional programs7-9. Here we report the preferential sensitivity of TNBCs to BET bromodomain inhibition in vitro and in vivo, establishing a rationale for clinical investigation and further motivation to understand mechanisms of resistance. In paired cell lines selected for acquired resistance to BET inhibition from previously sensitive TNBCs, we failed to identify gatekeeper mutations, new driver events or drug pump activation. BET-resistant TNBC cells remain dependent on wild-type BRD4, which supports transcription and cell proliferation in a bromodomain-independent manner. Proteomic studies of resistant TNBC identify strong association with MED1 and hyper-phosphorylation of BRD4 attributable to decreased activity of PP2A, identified here as a principal BRD4 serine phosphatase. Together, these studies provide a rationale for BET inhibition in TNBC and present mechanism-based combination strategies to anticipate clinical drug resistance.