Experimental models of undifferentiated pleomorphic sarcoma and malignant peripheral nerve sheath tumor.

Undifferentiated pleomorphic sarcoma (UPS) and malignant peripheral nerve sheath tumor (MPNST) are aggressive soft tissue sarcomas that do not respond well to current treatment modalities. The limited availability of UPS and MPNST cell lines makes it challenging to identify potential therapeutic targets in a laboratory setting. Understanding the urgent need for improved treatments for these tumors and the limited cellular models available, we generated additional cell lines to study these rare cancers. Patient-derived tumors were used to establish 4 new UPS models, including one radiation-associated UPS-UPS271.1, UPS511, UPS0103, and RIS620, one unclassified spindle cell sarcoma-USC060.1, and 3 new models of MPNST-MPNST007, MPNST3813E, and MPNST4970. This study examined the utility of the new cell lines as sarcoma models by assessing their tumorigenic potential and mutation status for known sarcoma-related genes. All the cell lines formed colonies and migrated in vitro. The in vivo tumorigenic potential of the cell lines and corresponding xenografts was determined by subcutaneous injection or xenograft re-passaging into immunocompromised mice. USC060.1 and UPS511 cells formed tumors in mice upon subcutaneous injection. UPS0103 and RIS620 tumor implants formed tumors in vivo, as did MPNST007 and MPNST3813E tumor implants. Targeted sequencing analysis of a panel of genes frequently mutated in sarcomas identified TP53, RB1, and ATRX mutations in a subset of the cell lines. These new cellular models provide the scientific community with powerful tools for detailed studies of tumorigenesis and for investigating novel therapies for UPS and MPNST.

PRDM16s transforms megakaryocyte-erythroid progenitors into myeloid leukemia-initiating cells.

Oncogenic mutations confer on cells the ability to propagate indefinitely, but whether oncogenes alter the cell fate of these cells is unknown. Here, we show that the transcriptional regulator PRDM16s causes oncogenic fate conversion by transforming cells fated to form platelets and erythrocytes into myeloid leukemia stem cells (LSCs). Prdm16s expression in megakaryocyte-erythroid progenitors (MEPs), which normally lack the potential to generate granulomonocytic cells, caused AML by converting MEPs into LSCs. Prdm16s blocked megakaryocytic/erythroid potential by interacting with super enhancers and activating myeloid master regulators, including PU.1. A CRISPR dropout screen confirmed that PU.1 is required for Prdm16s-induced leukemia. Ablating PU.1 attenuated leukemogenesis and reinstated the megakaryocytic/erythroid potential of leukemic MEPs in mouse models and human AML with PRDM16 rearrangement. Thus, oncogenic PRDM16 s expression gives MEPs an LSC fate by activating myeloid gene regulatory networks.

Multi-omic molecular profiling reveals potentially targetable abnormalities shared across multiple histologies of brain metastasis.

The deadly complication of brain metastasis (BM) is largely confined to a relatively narrow cross-section of systemic malignancies, suggesting a fundamental role for biological mechanisms shared across commonly brain metastatic tumor types. To identify and characterize such mechanisms, we performed genomic, transcriptional, and proteomic profiling using whole-exome sequencing, mRNA-seq, and reverse-phase protein array analysis in a cohort of the lung, breast, and renal cell carcinomas consisting of BM and patient-matched primary or extracranial metastatic tissues. While no specific genomic alterations were associated with BM, correlations with impaired cellular immunity, upregulated oxidative phosphorylation (OXPHOS), and canonical oncogenic signaling pathways including phosphoinositide 3-kinase (PI3K) signaling, were apparent across multiple tumor histologies. Multiplexed immunofluorescence analysis confirmed significant T cell depletion in BM, indicative of a fundamentally altered immune microenvironment. Moreover, functional studies using in vitro and in vivo modeling demonstrated heightened oxidative metabolism in BM along with sensitivity to OXPHOS inhibition in murine BM models and brain metastatic derivatives relative to isogenic parentals. These findings demonstrate that pathophysiological rewiring of oncogenic signaling, cellular metabolism, and immune microenvironment broadly characterizes BM. Further clarification of this biology will likely reveal promising targets for therapeutic development against BM arising from a broad variety of systemic cancers.

Enhancer reprogramming in PRC2-deficient malignant peripheral nerve sheath tumors induces a targetable de-differentiated state.

Malignant peripheral nerve sheath tumors (MPNSTs) are soft tissue sarcomas that frequently harbor genetic alterations in polycomb repressor complex 2 (PRC2) components-SUZ12 and EED. Here, we show that PRC2 loss confers a dedifferentiated early neural-crest phenotype which is exclusive to PRC2-mutant MPNSTs and not a feature of neurofibromas. Neural crest phenotype in PRC2 mutant MPNSTs was validated via cross-species comparative analysis using spontaneous and transgenic MPNST models. Systematic chromatin state profiling of the MPNST cells showed extensive epigenomic reprogramming or chromatin states associated with PRC2 loss and identified gains of active enhancer states/super-enhancers on early neural crest regulators in PRC2-mutant conditions around genomic loci that harbored repressed/poised states in PRC2-WT MPNST cells. Consistently, inverse correlation between H3K27me3 loss and H3K27Ac gain was noted in MPNSTs. Epigenetic editing experiments established functional roles for enhancer gains on DLX5-a key regulator of neural crest phenotype. Consistently, blockade of enhancer activity by bromodomain inhibitors specifically suppressed this neural crest phenotype and tumor burden in PRC2-mutant PDXs. Together, these findings reveal accumulation of dedifferentiated neural crest like state in PRC2-mutant MPNSTs that can be targeted by enhancer blockade.

Somatic Mutations in Circulating Cell-Free DNA and Risk for Hepatocellular Carcinoma in Hispanics.

Hispanics are disproportionally affected by liver fibrosis and hepatocellular carcinoma (HCC). Advanced liver fibrosis is a major risk factor for HCC development. We aimed at identifying somatic mutations in plasma cell-free DNA (cfDNA) of Hispanics with HCC and Hispanics with advanced liver fibrosis but no HCC. Targeted sequencing of over 262 cancer-associated genes identified nonsynonymous mutations in 22 of the 27 HCC patients. Mutations were detected in known HCC-associated genes (e.g., CTNNB1, TP53, NFE2L2, and ARID1A). No difference in cfDNA concentrations was observed between patients with mutations and those without detectable mutations. HCC patients with higher cfDNA concentrations or higher number of mutations had a shorter overall survival (p < 0.001 and p = 0.045). Nonsynonymous mutations were also identified in 17 of the 51 subjects with advanced liver fibrosis. KMT2C was the most commonly mutated gene. Nine genes were mutated in both subjects with advanced fibrosis and HCC patients. Again, no significant difference in cfDNA concentrations was observed between subjects with mutations and those without detectable mutations. Furthermore, higher cfDNA concentrations and higher number of mutations correlated with a death outcome in subjects with advanced fibrosis. In conclusion, cfDNA features are promising non-invasive markers for HCC risk prediction and overall survival.

Multiplex profiling of peritoneal metastases from gastric adenocarcinoma identified novel targets and molecular subtypes that predict treatment response.

OBJECTIVE: Peritoneal carcinomatosis (PC) occurs frequently in patients with gastric adenocarcinoma (GAC) and confers a poor prognosis. Multiplex profiling of primary GACs has been insightful but the underpinnings of PC's development/progression remain largely unknown. We characterised exome/transcriptome/immune landscapes of PC cells from patients with GAC aiming to identify novel therapeutic targets. DESIGN: We performed whole-exome sequencing (WES) and whole transcriptome sequencing (RNA-seq) on 44 PC specimens (43 patients with PC) including an integrative analysis of WES, RNA-seq, immune profile, clinical and pathological phenotypes to dissect the molecular pathogenesis, identifying actionable targets and/or biomarkers and comparison with TCGA primary GACs. RESULTS: We identified distinct alterations in PC versus primary GACs, such as more frequent CDH1 and TAF1 mutations, 6q loss and chr19 gain. Alterations associated with aggressive PC phenotypes emerged with increased mutations in TP53, CDH1, TAF1 and KMT2C, higher level of 'clock-like' mutational signature, increase in whole-genome doublings, chromosomal instability (particularly, copy number losses), reprogrammed microenvironment, enriched cell cycle pathways, MYC activation and impaired immune response. Integrated analysis identified two main molecular subtypes: 'mesenchymal-like' and 'epithelial-like' with discriminating response to chemotherapy (31% vs 71%). Patients with the less responsive 'mesenchymal-like' subtype had high expression of immune checkpoint T-Cell Immunoglobulin And Mucin Domain-Containing Protein 3 (TIM-3), its ligand galectin-9, V-domain Ig suppressor of T cell activation (VISTA) and transforming growth factor-ß as potential therapeutic immune targets. CONCLUSIONS: We have uncovered the unique mutational landscape, copy number alteration and gene expression profile of PC cells and defined PC molecular subtypes, which correlated with PC therapy resistance/response. Novel targets and immune checkpoint proteins have been identified with a potential to be translated into clinics.

A Cryptic BCR-PDGFRB Fusion Resulting in a Chronic Myeloid Neoplasm With Monocytosis and Eosinophilia: A Novel Finding With Treatment Implications.

RNA-seq was used to identify the partner gene and confirm the presence of a BCR-PDGFRB fusion. Identification of this fusion product resulted in successful treatment and long-term remission of this myeloid neoplasm. Based on our results, we suggest that despite current WHO recommendations, screening for PDGFRB rearrangement in cases of leukocytosis with eosinophilia and no other etiologic explanation is necessary, even if the karyotype is normal.

Variants with a low allele frequency detected in genomic DNA affect the accuracy of mutation detection in cell-free DNA by next-generation sequencing.

BACKGROUND: Next-generation sequencing of cell-free DNA (cfDNA) has been shown to be a useful noninvasive test for detecting mutations in solid tumors. METHODS: Targeted gene sequencing was performed with a panel of 263 cancer-related genes for cfDNA and genomic DNA of peripheral blood mononuclear cells (PBMCs) obtained from presurgical specimens of 6 lung cancer patients, and mutation calls in these samples were compared with those of primary tumors and corresponding patient-derived xenografts (PDXs). RESULTS: Approximately 67% of the mutations detected in the tumor samples (primary tumors and/or PDXs) were also detected in genomic DNA from PBMCs as background mutations. These background mutations consisted of germline polymorphisms and a group of mutations with low allele frequencies, mostly <10%. These variants with a low allele frequency were repeatedly detected in all types of samples from the same patients and at similarly low allele frequency levels in PBMCs from different patients; this indicated that their detection might be derived from common causes, such as homologous sequences in the human genome. Allele frequencies of mutations detected in both primary tumors and cfDNA showed 2 patterns: 1) low allele frequencies (approximately 1%-10%) in cfDNA but high allele frequencies (usually >10% or >3-fold increase) in primary tumors and further enrichment in PDXs and 2) similar allele frequencies across samples. CONCLUSIONS: Because only a small fraction of total cfDNA might be derived from tumor cells, only mutations with the first allele frequency pattern may be regarded as tumor-specific mutations in cfDNA. Effective filtering of background mutations will be required to improve the accuracy of mutation calls in cfDNA. Cancer 2018;124:1061-9. © 2017 American Cancer Society.

DOOR 2.0: presenting operons and their functions through dynamic and integrated views.

We have recently developed a new version of the DOOR operon database, DOOR 2.0, which is available online at http://csbl.bmb.uga.edu/DOOR/ and will be updated on a regular basis. DOOR 2.0 contains genome-scale operons for 2072 prokaryotes with complete genomes, three times the number of genomes covered in the previous version published in 2009. DOOR 2.0 has a number of new features, compared with its previous version, including (i) more than 250,000 transcription units, experimentally validated or computationally predicted based on RNA-seq data, providing a dynamic functional view of the underlying operons; (ii) an integrated operon-centric data resource that provides not only operons for each covered genome but also their functional and regulatory information such as their cis-regulatory binding sites for transcription initiation and termination, gene expression levels estimated based on RNA-seq data and conservation information across multiple genomes; (iii) a high-performance web service for online operon prediction on user-provided genomic sequences; (iv) an intuitive genome browser to support visualization of user-selected data; and (v) a keyword-based Google-like search engine for finding the needed information intuitively and rapidly in this database.

DMINDA: an integrated web server for DNA motif identification and analyses.

DMINDA (DNA motif identification and analyses) is an integrated web server for DNA motif identification and analyses, which is accessible at http://csbl.bmb.uga.edu/DMINDA/. This web site is freely available to all users and there is no login requirement. This server provides a suite of cis-regulatory motif analysis functions on DNA sequences, which are important to elucidation of the mechanisms of transcriptional regulation: (i) de novo motif finding for a given set of promoter sequences along with statistical scores for the predicted motifs derived based on information extracted from a control set, (ii) scanning motif instances of a query motif in provided genomic sequences, (iii) motif comparison and clustering of identified motifs, and (iv) co-occurrence analyses of query motifs in given promoter sequences. The server is powered by a backend computer cluster with over 150 computing nodes, and is particularly useful for motif prediction and analyses in prokaryotic genomes. We believe that DMINDA, as a new and comprehensive web server for cis-regulatory motif finding and analyses, will benefit the genomic research community in general and prokaryotic genome researchers in particular.

Revisiting operons: an analysis of the landscape of transcriptional units in E. coli.

BACKGROUND: Bacterial operons are considerably more complex than what were thought. At least their components are dynamically rather than statically defined as previously assumed. Here we present a computational study of the landscape of the transcriptional units (TUs) of E. coli K12, revealed by the available genomic and transcriptomic data, providing new understanding about the complexity of TUs as a whole encoded in the genome of E. coli K12. RESULTS AND CONCLUSION: Our main findings include that (i) different TUs may overlap with each other by sharing common genes, giving rise to clusters of overlapped TUs (TUCs) along the genomic sequence; (ii) the intergenic regions in front of the first gene of each TU tend to have more conserved sequence motifs than those of the other genes inside the TU, suggesting that TUs each have their own promoters; (iii) the terminators associated with the 3' ends of TUCs tend to be Rho-independent terminators, substantially more often than terminators of TUs that end inside a TUC; and (iv) the functional relatedness of adjacent gene pairs in individual TUs is higher than those in TUCs, suggesting that individual TUs are more basic functional units than TUCs.

Comprehensive characterization of the genomic alterations in human gastric cancer.

Gastric cancer is one of the most prevalent and aggressive cancers worldwide, and its molecular mechanism remains largely elusive. Here we report the genomic landscape in primary gastric adenocarcinoma of human, based on the complete genome sequences of five pairs of cancer and matching normal samples. In total, 103,464 somatic point mutations, including 407 nonsynonymous ones, were identified and the most recurrent mutations were harbored by Mucins (MUC3A and MUC12) and transcription factors (ZNF717, ZNF595 and TP53). 679 genomic rearrangements were detected, which affect 355 protein-coding genes; and 76 genes show copy number changes. Through mapping the boundaries of the rearranged regions to the folded three-dimensional structure of human chromosomes, we determined that 79.6% of the chromosomal rearrangements happen among DNA fragments in close spatial proximity, especially when two endpoints stay in a similar replication phase. We demonstrated evidences that microhomology-mediated break-induced replication was utilized as a mechanism in inducing ∼40.9% of the identified genomic changes in gastric tumor. Our data analyses revealed potential integrations of Helicobacter pylori DNA into the gastric cancer genomes. Overall a large set of novel genomic variations were detected in these gastric cancer genomes, which may be essential to the study of the genetic basis and molecular mechanism of the gastric tumorigenesis.

The percentage of bacterial genes on leading versus lagging strands is influenced by multiple balancing forces.

The majority of bacterial genes are located on the leading strand, and the percentage of such genes has a large variation across different bacteria. Although some explanations have been proposed, these are at most partial explanations as they cover only small percentages of the genes and do not even consider the ones biased toward the lagging strand. We have carried out a computational study on 725 bacterial genomes, aiming to elucidate other factors that may have influenced the strand location of genes in a bacterium. Our analyses suggest that (i) genes of some functional categories such as ribosome have higher preferences to be on the leading strands; (ii) genes of some functional categories such as transcription factor have higher preferences on the lagging strands; (iii) there is a balancing force that tends to keep genes from all moving to the leading and more efficient strand and (iv) the percentage of leading-strand genes in an bacterium can be accurately explained based on the numbers of genes in the functional categories outlined in (i) and (ii), genome size and gene density, indicating that these numbers implicitly contain the information about the percentage of genes on the leading versus lagging strand in a genome.

dbCAN: a web resource for automated carbohydrate-active enzyme annotation.

Carbohydrate-active enzymes (CAZymes) are very important to the biotech industry, particularly the emerging biofuel industry because CAZymes are responsible for the synthesis, degradation and modification of all the carbohydrates on Earth. We have developed a web resource, dbCAN (http://csbl.bmb.uga.edu/dbCAN/annotate.php), to provide a capability for automated CAZyme signature domain-based annotation for any given protein data set (e.g. proteins from a newly sequenced genome) submitted to our server. To accomplish this, we have explicitly defined a signature domain for every CAZyme family, derived based on the CDD (conserved domain database) search and literature curation. We have also constructed a hidden Markov model to represent the signature domain of each CAZyme family. These CAZyme family-specific HMMs are our key contribution and the foundation for the automated CAZyme annotation.

Integration of sequence-similarity and functional association information can overcome intrinsic problems in orthology mapping across bacterial genomes.

Existing methods for orthologous gene mapping suffer from two general problems: (i) they are computationally too slow and their results are difficult to interpret for automated large-scale applications when based on phylogenetic analyses; or (ii) they are too prone to making mistakes in dealing with complex situations involving horizontal gene transfers and gene fusion due to the lack of a sound basis when based on sequence similarity information. We present a novel algorithm, Global Optimization Strategy (GOST), for orthologous gene mapping through combining sequence similarity and contextual (working partners) information, using a combinatorial optimization framework. Genome-scale applications of GOST show substantial improvements over the predictions by three popular sequence similarity-based orthology mapping programs. Our analysis indicates that our algorithm overcomes the intrinsic issues faced by sequence similarity-based methods, when orthology mapping involves gene fusions and horizontal gene transfers. Our program runs as efficiently as the most efficient sequence similarity-based algorithm in the public domain. GOST is freely downloadable at http://csbl.bmb.uga.edu/~maqin/GOST.

KOBAS 2.0: a web server for annotation and identification of enriched pathways and diseases.

High-throughput experimental technologies often identify dozens to hundreds of genes related to, or changed in, a biological or pathological process. From these genes one wants to identify biological pathways that may be involved and diseases that may be implicated. Here, we report a web server, KOBAS 2.0, which annotates an input set of genes with putative pathways and disease relationships based on mapping to genes with known annotations. It allows for both ID mapping and cross-species sequence similarity mapping. It then performs statistical tests to identify statistically significantly enriched pathways and diseases. KOBAS 2.0 incorporates knowledge across 1327 species from 5 pathway databases (KEGG PATHWAY, PID, BioCyc, Reactome and Panther) and 5 human disease databases (OMIM, KEGG DISEASE, FunDO, GAD and NHGRI GWAS Catalog). KOBAS 2.0 can be accessed at http://kobas.cbi.pku.edu.cn.

Multi-modal molecular programs regulate melanoma cell state.

Melanoma cells display distinct intrinsic phenotypic states. Here, we seek to characterize the molecular regulation of these states using multi-omic analyses of whole exome, transcriptome, microRNA, long non-coding RNA and DNA methylation data together with reverse-phase protein array data on a panel of 68 highly annotated early passage melanoma cell lines. We demonstrate that clearly defined cancer cell intrinsic transcriptomic programs are maintained in melanoma cells ex vivo and remain highly conserved within melanoma tumors, are associated with distinct immune features within tumors, and differentially correlate with checkpoint inhibitor and adoptive T cell therapy efficacy. Through integrative analyses we demonstrate highly complex multi-omic regulation of melanoma cell intrinsic programs that provide key insights into the molecular maintenance of phenotypic states. These findings have implications for cancer biology and the identification of new therapeutic strategies. Further, these deeply characterized cell lines will serve as an invaluable resource for future research in the field.

The histologic phenotype of lung cancers is associated with transcriptomic features rather than genomic characteristics.

Histology plays an essential role in therapeutic decision-making for lung cancer patients. However, the molecular determinants of lung cancer histology are largely unknown. We conduct whole-exome sequencing and microarray profiling on 19 micro-dissected tumor regions of different histologic subtypes from 9 patients with lung cancers of mixed histology. A median of 68.9% of point mutations and 83% of copy number aberrations are shared between different histologic components within the same tumors. Furthermore, different histologic components within the tumors demonstrate similar subclonal architecture. On the other hand, transcriptomic profiling reveals shared pathways between the same histologic subtypes from different patients, which is supported by the analyses of the transcriptomic data from 141 cell lines and 343 lung cancers of different histologic subtypes. These data derived from mixed histologic subtypes in the setting of identical genetic background and exposure history support that the histologic fate of lung cancer cells is associated with transcriptomic features rather than the genomic profiles in most tumors.

Computational prediction of the osmoregulation network in Synechococcus sp. WH8102.

BACKGROUND: Osmotic stress is caused by sudden changes in the impermeable solute concentration around a cell, which induces instantaneous water flow in or out of the cell to balance the concentration. Very little is known about the detailed response mechanism to osmotic stress in marine Synechococcus, one of the major oxygenic phototrophic cyanobacterial genera that contribute greatly to the global CO2 fixation. RESULTS: We present here a computational study of the osmoregulation network in response to hyperosmotic stress of Synechococcus sp strain WH8102 using comparative genome analyses and computational prediction. In this study, we identified the key transporters, synthetases, signal sensor proteins and transcriptional regulator proteins, and found experimentally that of these proteins, 15 genes showed significantly changed expression levels under a mild hyperosmotic stress. CONCLUSIONS: From the predicted network model, we have made a number of interesting observations about WH8102. Specifically, we found that (i) the organism likely uses glycine betaine as the major osmolyte, and others such as glucosylglycerol, glucosylglycerate, trehalose, sucrose and arginine as the minor osmolytes, making it efficient and adaptable to its changing environment; and (ii) sigma38, one of the seven types of sigma factors, probably serves as a global regulator coordinating the osmoregulation network and the other relevant networks.

Blocking immunosuppressive neutrophils deters pY696-EZH2-driven brain metastases.

The functions of immune cells in brain metastases are unclear because the brain has traditionally been considered "immune privileged." However, we found that a subgroup of immunosuppressive neutrophils is recruited into the brain, enabling brain metastasis development. In brain metastatic cells, enhancer of zeste homolog 2 (EZH2) is highly expressed and phosphorylated at tyrosine-696 (pY696)-EZH2 by nuclear-localized Src tyrosine kinase. Phosphorylation of EZH2 at Y696 changes its binding preference from histone H3 to RNA polymerase II, which consequently switches EZH2's function from a methyltransferase to a transcription factor that increases c-JUN expression. c-Jun up-regulates protumorigenic inflammatory cytokines, including granulocyte colony-stimulating factor (G-CSF), which recruits Arg1+- and PD-L1+ immunosuppressive neutrophils into the brain to drive metastasis outgrowth. G-CSF-blocking antibodies or immune checkpoint blockade therapies combined with Src inhibitors impeded brain metastasis in multiple mouse models. These findings indicate that pY696-EZH2 can function as a methyltransferase-independent transcription factor to facilitate the brain infiltration of immunosuppressive neutrophils, which could be clinically targeted for brain metastasis treatment.