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author:("Liu, dongzhai")
1.  Control of alveolar differentiation by the lineage transcription factors GATA6 and HOPX inhibits lung adenocarcinoma metastasis 
Cancer cell  2013;23(6):725-738.
Molecular programs that mediate normal cell differentiation are required for oncogenesis and tumor cell survival in certain cancers. How cell lineage restricted genes specifically influence metastasis is poorly defined. In lung cancers, we uncovered a transcriptional program that is preferentially associated with distal airway epithelial differentiation and lung adenocarcinoma (ADC) progression. This program is regulated in part by the lineage transcription factors GATA6 and HOPX. These factors can cooperatively limit the metastatic competence of ADC cells, by modulating overlapping alveolar differentiation and invasogenic target genes. Thus, GATA6 and HOPX are critical nodes in a lineage-selective pathway that directly links effectors of airway epithelial specification to the inhibition of metastasis in the lung ADC subtype.
PMCID: PMC3697763  PMID: 23707782
2.  Genotype-Selective Combination Therapies for Melanoma Identified by High Throughput Drug Screening 
Cancer discovery  2012;3(1):52-67.
Resistance and partial responses to targeted monotherapy are major obstacles in cancer treatment. Systematic approaches to identify efficacious drug combinations for cancer are not well established, especially in the context of genotype. To address this, we have tested pairwise combinations of an array of small molecule inhibitors on early passage melanoma cultures using combinatorial drug screening. Results reveal several inhibitor combinations effective for melanomas with activating RAS or BRAF mutations, including mutant BRAF melanomas with intrinsic or acquired resistance to vemurafenib. Inhibition of both EGFR and AKT sensitized treatment-resistant BRAF-mutant melanoma cultures to vemurafenib. Melanomas with RAS mutations were more resistant to combination therapies relative to BRAF mutants, but were sensitive to combinations of statins and cyclin-dependent kinase inhibitors in vitro and in vivo. These results demonstrate the utility of combinatorial drug screening for discovering unique treatment regimens that overcome resistance phenotypes of mutant BRAF and RAS driven melanomas.
PMCID: PMC3546137  PMID: 23239741
BRAF; RAS; melanoma; drug combinations; vemurafenib
3.  Microbial community resemblance methods differ in their ability to detect biologically relevant patterns 
Nature methods  2010;7(10):813-819.
The development of high-throughput sequencing methods allows for the characterization of microbial communities in a wide range of environments on an unprecedented scale. However, insight into microbial community composition is limited by our ability to detect patterns in this flood of sequences. Here we compare the performance of 51 analysis techniques using real and simulated bacterial 16S rRNA pyrosequencing datasets containing either clustered samples or samples arrayed across environmental gradients. We find that many diversity patterns are evident with severely undersampled communities, and that methods vary widely in their ability to detect gradients and clusters. Chi-squared distances and Pearson correlation distances perform especially well for detecting gradients, while Gower and Canberra distances perform especially well for detecting clusters. These results also provide a basis for understanding tradeoffs between number of samples and depth of coverage, tradeoffs which are important to consider when designing studies to characterize microbial communities.
PMCID: PMC2948603  PMID: 20818378
beta-diversity; high-throughput; pyrosequencing; community analysis; ordination; clustering
4.  GPHMM: an integrated hidden Markov model for identification of copy number alteration and loss of heterozygosity in complex tumor samples using whole genome SNP arrays 
Nucleic Acids Research  2011;39(12):4928-4941.
There is an increasing interest in using single nucleotide polymorphism (SNP) genotyping arrays for profiling chromosomal rearrangements in tumors, as they allow simultaneous detection of copy number and loss of heterozygosity with high resolution. Critical issues such as signal baseline shift due to aneuploidy, normal cell contamination, and the presence of GC content bias have been reported to dramatically alter SNP array signals and complicate accurate identification of aberrations in cancer genomes. To address these issues, we propose a novel Global Parameter Hidden Markov Model (GPHMM) to unravel tangled genotyping data generated from tumor samples. In contrast to other HMM methods, a distinct feature of GPHMM is that the issues mentioned above are quantitatively modeled by global parameters and integrated within the statistical framework. We developed an efficient EM algorithm for parameter estimation. We evaluated performance on three data sets and show that GPHMM can correctly identify chromosomal aberrations in tumor samples containing as few as 10% cancer cells. Furthermore, we demonstrated that the estimation of global parameters in GPHMM provides information about the biological characteristics of tumor samples and the quality of genotyping signal from SNP array experiments, which is helpful for data quality control and outlier detection in cohort studies.
PMCID: PMC3130254  PMID: 21398628
5.  A Negative Regulatory Loop between MicroRNA and Hox Gene Controls Posterior Identities in Caenorhabditis elegans 
PLoS Genetics  2010;6(9):e1001089.
MicroRNAs (miRNAs) have been found to regulate gene expression across eukaryotic species, but the function of most miRNA genes remains unknown. Here we describe how the analysis of the expression patterns of a well-conserved miRNA gene, mir-57, at cellular resolution for every minute during early development of Caenorhabditis elegans provided key insights in understanding its function. Remarkably, mir-57 expression shows strong positional bias but little tissue specificity, a pattern reminiscent of Hox gene function. Despite the minor defects produced by a loss of function mutation, overexpression of mir-57 causes dramatic posterior defects, which also mimic the phenotypes of mutant alleles of a posterior Hox gene, nob-1, an Abd homolog. More importantly, nob-1 expression is found in the same two posterior AB sublineages as those expressing mir-57 but with an earlier onset. Intriguingly, nob-1 functions as an activator for mir-57 expression; it is also a direct target of mir-57. In agreement with this, loss of mir-57 function partially rescues the nob-1 allele defects, indicating a negative feedback regulatory loop between the miRNA and Hox gene to provide positional cues. Given the conservation of the miRNA and Hox gene, the regulatory mechanism might be broadly used across species. The strategy used here to explore mir-57 function provides a path to dissect the regulatory relationship between genes.
Author Summary
miRNAs are small RNAs found in many multi-cellular species that inhibit gene expression. Many of them play important roles in cancer and cell fate determination, but the function of most miRNAs is uncertain. Using live cell imaging and automated expression analysis, we found a miRNA gene, mir-57, is expressed in a position rather than tissue dependent way. Hox genes also regulate cell fate patterning along anterior-posterior (a-p) axis across different tissues. By investigating interactions between genes of these classes expressed in mir-57 expressing cells, we demonstrated by both genetic analysis and gene expression assays that a negative feedback loop between a posterior Hox gene, nob-1, and mir-57 regulates posterior cell fate determination in C. elegans. On the one hand, the Hox gene is required for normal activation of mir-57 expression, and on the other, the Hox gene functions as a direct target of and is repressed by the miRNA. Given the conservation of the two genes, a negative feedback loop between Hox and miRNA genes might be broadly used across species to regulate cell fate along the a-p axis. Detailed expression analysis may provide a general way to dissect the regulatory role of miRNAs.
PMCID: PMC2932687  PMID: 20824072
6.  MixHMM: Inferring Copy Number Variation and Allelic Imbalance Using SNP Arrays and Tumor Samples Mixed with Stromal Cells 
PLoS ONE  2010;5(6):e10909.
Genotyping platforms such as single nucleotide polymorphism (SNP) arrays are powerful tools to study genomic aberrations in cancer samples. Allele specific information from SNP arrays provides valuable information for interpreting copy number variation (CNV) and allelic imbalance including loss-of-heterozygosity (LOH) beyond that obtained from the total DNA signal available from array comparative genomic hybridization (aCGH) platforms. Several algorithms based on hidden Markov models (HMMs) have been designed to detect copy number changes and copy-neutral LOH making use of the allele information on SNP arrays. However heterogeneity in clinical samples, due to stromal contamination and somatic alterations, complicates analysis and interpretation of these data.
We have developed MixHMM, a novel hidden Markov model using hidden states based on chromosomal structural aberrations. MixHMM allows CNV detection for copy numbers up to 7 and allows more complete and accurate description of other forms of allelic imbalance, such as increased copy number LOH or imbalanced amplifications. MixHMM also incorporates a novel sample mixing model that allows detection of tumor CNV events in heterogeneous tumor samples, where cancer cells are mixed with a proportion of stromal cells.
We validate MixHMM and demonstrate its advantages with simulated samples, clinical tumor samples and a dilution series of mixed samples. We have shown that the CNVs of cancer cells in a tumor sample contaminated with up to 80% of stromal cells can be detected accurately using Illumina BeadChip and MixHMM.
The MixHMM is available as a Python package provided with some other useful tools at
PMCID: PMC2879364  PMID: 20532221
7.  Accurate taxonomy assignments from 16S rRNA sequences produced by highly parallel pyrosequencers 
Nucleic Acids Research  2008;36(18):e120.
The recent introduction of massively parallel pyrosequencers allows rapid, inexpensive analysis of microbial community composition using 16S ribosomal RNA (rRNA) sequences. However, a major challenge is to design a workflow so that taxonomic information can be accurately and rapidly assigned to each read, so that the composition of each community can be linked back to likely ecological roles played by members of each species, genus, family or phylum. Here, we use three large 16S rRNA datasets to test whether taxonomic information based on the full-length sequences can be recaptured by short reads that simulate the pyrosequencer outputs. We find that different taxonomic assignment methods vary radically in their ability to recapture the taxonomic information in full-length 16S rRNA sequences: most methods are sensitive to the region of the 16S rRNA gene that is targeted for sequencing, but many combinations of methods and rRNA regions produce consistent and accurate results. To process large datasets of partial 16S rRNA sequences obtained from surveys of various microbial communities, including those from human body habitats, we recommend the use of Greengenes or RDP classifier with fragments of at least 250 bases, starting from one of the primers R357, R534, R798, F343 or F517.
PMCID: PMC2566877  PMID: 18723574
8.  Short-Term Temporal Variability in Airborne Bacterial and Fungal Populations▿  
Airborne microorganisms have been studied for centuries, but the majority of this research has relied on cultivation-dependent surveys that may not capture all of the microbial diversity in the atmosphere. As a result, our understanding of airborne microbial ecology is limited despite the relevance of airborne microbes to human health, various ecosystem functions, and environmental quality. Cultivation-independent surveys of small-subunit rRNA genes were conducted in order to identify the types of airborne bacteria and fungi found at a single site (Boulder, CO) and the temporal variability in the microbial assemblages over an 8-day period. We found that the air samples were dominated by ascomycete fungi of the Hypocreales order and a diverse array of bacteria, including members of the proteobacterial and Cytophaga-Flavobacterium-Bacteroides groups that are commonly found in comparable culture-independent surveys of airborne bacteria. Bacterium/fungus ratios varied by 2 orders of magnitude over the sampling period, and we observed large shifts in the phylogenetic diversity of bacteria present in the air samples collected on different dates, shifts that were not likely to be related to local meteorological conditions. We observed more phylogenetic similarity between bacteria collected from geographically distant sites than between bacteria collected from the same site on different days. These results suggest that outdoor air may harbor similar types of bacteria regardless of location and that the short-term temporal variability in airborne bacterial assemblages can be very large.
PMCID: PMC2223228  PMID: 17981945
9.  The Macaque Gut Microbiome in Health, Lentiviral Infection, and Chronic Enterocolitis 
PLoS Pathogens  2008;4(2):e20.
The vertebrate gut harbors a vast community of bacterial mutualists, the composition of which is modulated by the host immune system. Many gastrointestinal (GI) diseases are expected to be associated with disruptions of host-bacterial interactions, but relatively few comprehensive studies have been reported. We have used the rhesus macaque model to investigate forces shaping GI bacterial communities. We used DNA bar coding and pyrosequencing to characterize 141,000 sequences of 16S rRNA genes obtained from 100 uncultured GI bacterial samples, allowing quantitative analysis of community composition in health and disease. Microbial communities of macaques were distinct from those of mice and humans in both abundance and types of taxa present. The macaque communities differed among samples from intestinal mucosa, colonic contents, and stool, paralleling studies of humans. Communities also differed among animals, over time within individual animals, and between males and females. To investigate changes associated with disease, samples of colonic contents taken at necropsy were compared between healthy animals and animals with colitis and undergoing antibiotic therapy. Communities from diseased and healthy animals also differed significantly in composition. This work provides comprehensive data and improved methods for studying the role of commensal microbiota in macaque models of GI diseases and provides a model for the large-scale screening of the human gut microbiome.
Author Summary
Bacterial mutualists within the gastrointestinal tract aid digestion, promote development of the gut immune system, and provide competitive barriers to pathogen invasion. The host, in return, provides bacteria with safe housing and food during lean times. The composition of the gut microbiota is controlled in part by the host immune system. In a variety of disease states, immune function can be altered, and gut morbidity is often associated, leading to the hypothesis that alterations in the GI microbiota may contribute to disease. In this study, the gut microbiota was characterized in 100 samples from rhesus macaques using pyrosequencing, which allowed 141,000 sequences from 16S rRNA genes to be generated and analyzed. Healthy animals were compared to animals with gut disorders, induced, for example by advanced simian AIDS. Many factors contributed to changes in the microbiota, including the sex of the animal of origin. Animals with chronic colitis showed differences in composition of the GI microbiota compared to healthy animals, providing an association between altered microbiota and disease.
PMCID: PMC2222957  PMID: 18248093
10.  Short pyrosequencing reads suffice for accurate microbial community analysis 
Nucleic Acids Research  2007;35(18):e120.
Pyrosequencing technology allows us to characterize microbial communities using 16S ribosomal RNA (rRNA) sequences orders of magnitude faster and more cheaply than has previously been possible. However, results from different studies using pyrosequencing and traditional sequencing are often difficult to compare, because amplicons covering different regions of the rRNA might yield different conclusions. We used sequences from over 200 globally dispersed environments to test whether studies that used similar primers clustered together mistakenly, without regard to environment. We then tested whether primer choice affects sequence-based community analyses using UniFrac, our recently-developed method for comparing microbial communities. We performed three tests of primer effects. We tested whether different simulated amplicons generated the same UniFrac clustering results as near-full-length sequences for three recent large-scale studies of microbial communities in the mouse and human gut, and the Guerrero Negro microbial mat. We then repeated this analysis for short sequences (100-, 150-, 200- and 250-base reads) resembling those produced by pyrosequencing. The results show that sequencing effort is best focused on gathering more short sequences rather than fewer longer ones, provided that the primers are chosen wisely, and that community comparison methods such as UniFrac are surprisingly robust to variation in the region sequenced.
PMCID: PMC2094085  PMID: 17881377
11.  PyCogent: a toolkit for making sense from sequence 
Genome Biology  2007;8(8):R171.
The COmparative GENomic Toolkit, a framework for probabilistic analyses of biological sequences, devising workflows and generating publication quality graphics, has been implemented in Python.
We have implemented in Python the COmparative GENomic Toolkit, a fully integrated and thoroughly tested framework for novel probabilistic analyses of biological sequences, devising workflows, and generating publication quality graphics. PyCogent includes connectors to remote databases, built-in generalized probabilistic techniques for working with biological sequences, and controllers for third-party applications. The toolkit takes advantage of parallel architectures and runs on a range of hardware and operating systems, and is available under the general public license from .
PMCID: PMC2375001  PMID: 17708774
12.  Spontaneous tumour regression in keratoacanthomas is driven by Wnt/retinoic acid signalling cross-talk 
Nature Communications  2014;5:3543.
A fundamental goal in cancer biology is to identify the cells and signalling pathways that are keys to induce tumour regression. Here we use a spontaneously self-regressing tumour, cutaneous keratoacanthoma (KAs), to identify physiological mechanisms that drive tumour regression. By using a mouse model system that recapitulates the behaviour of human KAs, we show that self-regressing tumours shift their balance to a differentiation programme during regression. Furthermore, we demonstrate that developmental programs utilized for skin hair follicle regeneration, such as Wnt, are hijacked to sustain tumour growth and that the retinoic acid (RA) signalling pathway promotes tumour regression by inhibiting Wnt signalling. Finally, we find that RA signalling can induce regression of malignant tumours that do not normally spontaneously regress, such as squamous cell carcinomas. These findings provide new insights into the physiological mechanisms of tumour regression and suggest therapeutic strategies to induce tumour regression.
Keratoacanthomas are skin tumours that spontaneously regress but the mechanisms leading to regression are unknown. Here, using a mouse chemical carcinogenesis model, the authors show that tumour regression is driven by activation of retinoic acid signalling that induces Wnt inhibition and tumour differentiation.
PMCID: PMC3974217  PMID: 24667544

Results 1-12 (12)