A Predictor of Pathological Complete Response to Neoadjuvant Chemotherapy Stratifies Triple Negative Breast Cancer Patients with High Risk of Recurrence.

We developed a test to predict which patients will achieve pathological complete response (pCR) to neoadjuvant chemotherapy (NAC) and which will have residual disease (RD). Gene expression data from pretreatment biopsies of patients with all breast cancer subtypes were combined into a 519-patient cohort containing 177 TNBC patients. Two RNA classifiers of 16 genes each were sequentially applied to the total cohort, classifying patients into 3 distinct classes. The test performance was further validated in an independent 304-patient cohort. The test accurately identified 70.5% (79/112) of pCR and 83.5% (340/407) of RD patients in the total population, and 75.0% (45/60) of pCR and 75.2% (88/117) of RD patients in the TNBC subset. For the independent cohort, the test identified 91.5% RD patients in the total population and 86.2% RD patients in the TNBC subset. However, the identification of pCR in both total and TNBC population are as low as 21.1% and 30%, respectively. The TNBC RD patients were subdivided by our classifiers, with one class showing significantly higher levels of Ki67 expression and having significantly poorer survival rates than the other classes. This stratification of patients may allow predicted residual disease classes to be assigned an alternative therapy.

A Novel Panel of 80 RNA Biomarkers with Differential Expression in Multiple Human Solid Tumors against Healthy Blood Samples.

The aim of this study was to identify genes with higher expression in solid tumor cells by comparing human tumor biopsies with healthy blood samples using both in silico statistical analysis and experimental validations. This approach resulted in a novel panel of 80 RNA biomarkers with high discrimination power to detect circulating tumor cells in blood samples. To identify the 80 RNA biomarkers, Affymetrix HG-U133 plus 2.0 microarrays datasets were used to compare breast tumor tissue biopsies and breast cancer cell lines with blood samples from patients with conditions other than cancer. A total of 859 samples were analyzed at the discovery stage, consisting of 417 mammary tumors, 41 breast lines, and 401 control samples. To confirm this discovery, external datasets of eight types of tumors were used, and experimental validation studies (NanoString n-counter gene expression assay) were performed, totaling 5028 samples analyzed. In these analyses, the 80 biomarkers showed higher expression in all solid tumors analyzed relative to healthy blood samples. Experimental validation studies using NanoString assay confirmed the results were not dependent of the gene expression platform. A panel of 80 RNA biomarkers was described here, with the potential to detect solid tumor cells present in the blood of multiple tumor types.

Expression Concordance of 325 Novel RNA Biomarkers between Data Generated by NanoString nCounter and Affymetrix GeneChip.

BACKGROUND: With the development of new drug combinations and targeted treatments for multiple types of cancer, the ability to stratify categories of patient populations and to develop companion diagnostics has become increasingly important. A panel of 325 RNA biomarkers was selected based on cancer-related biological processes of healthy cells and gene expression changes over time during nonmalignant epithelial cell organization. This "cancer in reverse" approach resulted in a panel of biomarkers relevant for at least 7 cancer types, providing gene expression profiles representing key cellular signaling pathways beyond mutations in "driver genes." Objective. To further investigate this biomarker panel, the objective of the current study is to (1) validate the assay reproducibility for the 325 RNA biomarkers and (2) compare gene expression profiles side by side using two technology platforms. METHODS AND RESULTS: We have mapped the 325 RNA transcripts and in a custom NanoString nCounter expression panel to be compared to all potential probe sets in the Affymetrix Human Genome U133 Plus 2.0. The experiments were conducted with 10 unique biological formalin-fixed paraffin-embedded (FFPE) breast tumor samples. Each site extracted RNA from four sections of 10-micron thick FFPE tissue over three different days by two different operators using an optimized standard operating procedure and quality control criteria. Samples were analyzed using mas5 in BioConductor and NanoStringNorm in R. Pearson correlation showed reproducibility between sites for all 60 samples with r = 0.995 for Affymetrix and r = 0.999 for NanoString. Correlation in multiple days and multiple users was for Affymetrix r = (0.962 - 0.999) and for NanoString r = (0.982 - 0.991). CONCLUSION: The 325 RNA biomarkers showed reproducibility in two technology platforms with moderate to high concordance. Future directions include performing clinical validation studies and generating rationale for patient selection in clinical trials using the technically validated assay.

The NCATS BioPlanet - An Integrated Platform for Exploring the Universe of Cellular Signaling Pathways for Toxicology, Systems Biology, and Chemical Genomics.

Chemical genomics aims to comprehensively define, and ultimately predict, the effects of small molecule compounds on biological systems. Chemical activity profiling approaches must consider chemical effects on all pathways operative in mammalian cells. To enable a strategic and maximally efficient chemical profiling of pathway space, we have created the NCATS BioPlanet, a comprehensive integrated pathway resource that incorporates the universe of 1,658 human pathways sourced from publicly available, manually curated sources, which have been subjected to thorough redundancy and consistency cross-evaluation. BioPlanet supports interactive browsing, retrieval, and analysis of pathways, exploration of pathway connections, and pathway search by gene targets, category, and availability of corresponding bioactivity assay, as well as visualization of pathways on a 3-dimensional globe, in which the distance between any two pathways is proportional to their degree of gene component overlap. Using this resource, we propose a strategy to identify a minimal set of 362 biological assays that can interrogate the universe of human pathways. The NCATS BioPlanet is a public resource, which will be continually expanded and updated, for systems biology, toxicology, and chemical genomics, available at http://tripod.nih.gov/bioplanet/.

Genome-wide and single-cell analyses reveal a context dependent relationship between CBP recruitment and gene expression.

Genome-wide distribution of histone H3K18 and H3K27 acetyltransferases, CBP (CREBBP) and p300 (EP300), is used to map enhancers and promoters, but whether these elements functionally require CBP/p300 remains largely uncertain. Here we compared global CBP recruitment with gene expression in wild-type and CBP/p300 double-knockout (dKO) fibroblasts. ChIP-seq using CBP-null cells as a control revealed nearby CBP recruitment for 20% of constitutively-expressed genes, but surprisingly, three-quarters of these genes were unaffected or slightly activated in dKO cells. Computationally defined enhancer-promoter-units (EPUs) having a CBP peak near the enhancer-like element were more predictive, with CBP/p300 deletion attenuating expression of 40% of such constitutively-expressed genes. Examining signal-responsive (Hypoxia Inducible Factor) genes showed that 97% were within 50 kilobases of an inducible CBP peak, and 70% of these required CBP/p300 for full induction. Unexpectedly, most inducible CBP peaks occurred near signal-nonresponsive genes. Finally, single-cell expression analysis revealed additional context dependence where some signal-responsive genes were not uniformly dependent on CBP/p300 in individual cells. While CBP/p300 was needed for full induction of some genes in single-cells, for other genes CBP/p300 increased the probability of maximal expression. Thus, target gene context influences the transcriptional requirement for CBP/p300, possibly by multiple mechanisms.

CREST maps somatic structural variation in cancer genomes with base-pair resolution.

We developed 'clipping reveals structure' (CREST), an algorithm that uses next-generation sequencing reads with partial alignments to a reference genome to directly map structural variations at the nucleotide level of resolution. Application of CREST to whole-genome sequencing data from five pediatric T-lineage acute lymphoblastic leukemias (T-ALLs) and a human melanoma cell line, COLO-829, identified 160 somatic structural variations. Experimental validation exceeded 80%, demonstrating that CREST had a high predictive accuracy.

T cell receptor CDR3 sequence but not recognition characteristics distinguish autoreactive effector and Foxp3(+) regulatory T cells.

The source, specificity, and plasticity of the forkhead box transcription factor 3 (Foxp3)(+) regulatory T (Treg) and conventional T (Tconv) cell populations active at sites of autoimmune pathology are not well characterized. To evaluate this, we combined global repertoire analyses and functional assessments of isolated T cell receptors (TCR) from TCRalpha retrogenic mice with autoimmune encephalomyelitis. Treg and Tconv cell TCR repertoires were distinct, and autoantigen-specific Treg and Tconv cells were enriched in diseased tissue. Autoantigen sensitivity and fine specificity of these cells intersected, implying that differences in responsiveness were not responsible for lineage specification. Notably, autoreactive Treg and Tconv cells could be fully distinguished by an acidic versus aliphatic variation at a single TCR CDR3 residue. Our results imply that ontogenically distinct Treg and Tconv cell repertoires with convergent specificities for autoantigen respond during autoimmunity and argue against more than limited plasticity between Treg and Tconv cells during autoimmune inflammation.

Large-scale analysis of thermostable, mammalian proteins provides insights into the intrinsically disordered proteome.

Intrinsically disordered proteins are predicted to be highly abundant and play broad biological roles in eukaryotic cells. In particular, by virtue of their structural malleability and propensity to interact with multiple binding partners, disordered proteins are thought to be specialized for roles in signaling and regulation. However, these concepts are based on in silico analyses of translated whole genome sequences, not on large-scale analyses of proteins expressed in living cells. Therefore, whether these concepts broadly apply to expressed proteins is currently unknown. Previous studies have shown that heat-treatment of cell extracts lead to partial enrichment of soluble, disordered proteins. On the basis of this observation, we sought to address the current dearth of knowledge about expressed, disordered proteins by performing a large-scale proteomics study of thermostable proteins isolated from mouse fibroblast cells. With the use of novel multidimensional chromatography methods and mass spectrometry, we identified a total of 1320 thermostable proteins from these cells. Further, we used a variety of bioinformatics methods to analyze the structural and biological properties of these proteins. Interestingly, more than 900 of these expressed proteins were predicted to be substantially disordered. These were divided into two categories, with 514 predicted to be predominantly disordered and 395 predicted to exhibit both disordered and ordered/folded features. In addition, 411 of the thermostable proteins were predicted to be folded. Despite the use of heat treatment (60 min at 98 degrees C) to partially enrich for disordered proteins, which might have been expected to select for small proteins, the sequences of these proteins exhibited a wide range of lengths (622 +/- 555 residues (average length +/- standard deviation) for disordered proteins and 569 +/- 598 residues for folded proteins). Computational structural analyses revealed several unexpected features of the thermostable proteins: (1) disordered domains and coiled-coil domains occurred together in a large number of disordered proteins, suggesting functional interplay between these domains; and (2) more than 170 proteins contained lengthy domains (>300 residues) known to be folded. Reference to Gene Ontology Consortium functional annotations revealed that, while disordered proteins play diverse biological roles in mouse fibroblasts, they do exhibit heightened involvement in several functional categories, including, cytoskeletal structure and cell movement, metabolic and biosynthetic processes, organelle structure, cell division, gene transcription, and ribonucleoprotein complexes. We believe that these results reflect the general properties of the mouse intrinsically disordered proteome (IDP-ome) although they also reflect the specialized physiology of fibroblast cells. Large-scale identification of expressed, thermostable proteins from other cell types in the future, grown under varied physiological conditions, will dramatically expand our understanding of the structural and biological properties of disordered eukaryotic proteins.

Globin lentiviral vector insertions can perturb the expression of endogenous genes in beta-thalassemic hematopoietic cells.

Although hematopoietic cell gene therapy using retroviral vectors has recently achieved success in clinical trials, safety issues regarding vector insertional mutagenesis have emerged. Vector insertion, resulting in transcriptional activation of proto-oncogenes, played a role in the development of lymphoid leukemia in an X-linked severe combined immunodeficiency trial, and caused myeloid clonal dominance in a trial for chronic granulomatous disease. These events have raised the question of whether gene therapy for other disorders such as beta-thalassemia and sickle cell disease may hold a similar risk. In this study, we prospectively evaluated whether gamma-globin lentiviral vectors containing enhancer elements from the beta-globin locus control region could alter the expression of genes near the vector insertion. We studied this question in primary, clonal murine beta-thalassemic erythroid cells, where globin regulatory elements are highly active. We found an overall incidence of perturbed expression in 28% of the transduced clones, with 11% of all genes contained within a 600-kilobase region surrounding the vector-insertion site demonstrating altered expression. This rate was higher than that observed for a lentiviral vector containing a viral long-terminal repeat (LTR). This is the first direct evidence that lentiviral vectors can cause insertional dysregulation of cellular genes at a frequent rate.

Influenza in migratory birds and evidence of limited intercontinental virus exchange.

Migratory waterfowl of the world are the natural reservoirs of influenza viruses of all known subtypes. However, it is unknown whether these waterfowl perpetuate highly pathogenic (HP) H5 and H7 avian influenza viruses. Here we report influenza virus surveillance from 2001 to 2006 in wild ducks in Alberta, Canada, and in shorebirds and gulls at Delaware Bay (New Jersey), United States, and examine the frequency of exchange of influenza viruses between the Eurasian and American virus clades, or superfamilies. Influenza viruses belonging to each of the subtypes H1 through H13 and N1 through N9 were detected in these waterfowl, but H14 and H15 were not found. Viruses of the HP Asian H5N1 subtypes were not detected, and serologic studies in adult mallard ducks provided no evidence of their circulation. The recently described H16 subtype of influenza viruses was detected in American shorebirds and gulls but not in ducks. We also found an unusual cluster of H7N3 influenza viruses in shorebirds and gulls that was able to replicate well in chickens and kill chicken embryos. Genetic analysis of 6,767 avian influenza gene segments and 248 complete avian influenza viruses supported the notion that the exchange of entire influenza viruses between the Eurasian and American clades does not occur frequently. Overall, the available evidence does not support the perpetuation of HP H5N1 influenza in migratory birds and suggests that the introduction of HP Asian H5N1 to the Americas by migratory birds is likely to be a rare event.

Expression of SMARCB1 modulates steroid sensitivity in human lymphoblastoid cells: identification of a promoter SNP that alters PARP1 binding and SMARCB1 expression.

Although cure rate of childhood acute lymphoblastic leukemia (ALL) has surpassed 80%, drug resistance remains a major cause of treatment failure. We previously identified a panel of 33 genes differentially expressed in prednisolone sensitive versus resistant ALL cells from newly diagnosed children. Here we used bioinformatics to identify resistance genes most likely to contain single nucleotide polymorphisms (SNPs) in their promoter region. The highest priority gene was SMARCB1, a core member of the SWI/SNF complex which promotes glucocorticoid effects through nucleosome remodeling. We identified several SNPs in the SMARCB1 promoter in lymphoblastoid cells from 90 individuals in the Centre d'Etude du Polymorphisme Humain (CEPH) panel. Among these SNPs, the -228G>T SNP (allele frequency 9.4%) was the only one that significantly increased reporter activity in human ALL cell lines. Furthermore, we identified nuclear protein poly (ADP-ribose) polymerase family, member 1 (PARP1) as a nuclear protein binding to the SMARCB1 promoter and showed that the -228 SNP significantly altered PARP1 binding affinity. The -228G>T SNP altered SMARCB1 mRNA and protein levels and a positive association was found between the SMARCB1 mRNA level and both the -228 genotype and prednisolone sensitivity in CEPH cell lines. Finally, knockdown experiments performed in human ALL cell lines confirmed that lower SMARCB1 expression increased prednisolone resistance. In summary, we provide functional evidence that SMARCB1 is involved in prednisolone resistance and identified a promoter SNP that alters the level of SMARCB1 mRNA and protein expression and the binding of PARP1 to the SMARCB1 promoter.

Persistent host markers in pandemic and H5N1 influenza viruses.

Avian influenza viruses have adapted to human hosts, causing pandemics in humans. The key host-specific amino acid mutations required for an avian influenza virus to function in humans are unknown. Through multiple-sequence alignment and statistical testing of each aligned amino acid, we identified markers that discriminate human influenza viruses from avian influenza viruses. We applied strict thresholds to select only markers which are highly preserved in human influenza virus isolates over time. We found that a subset of these persistent host markers exist in all human pandemic influenza virus sequences from 1918, 1957, and 1968, while others are acquired as the virus becomes a seasonal influenza virus. We also show that human H5N1 influenza viruses are significantly more likely to contain the amino acid predominant in human strains for a few persistent host markers than avian H5N1 influenza viruses. This sporadic enrichment of amino acids present in human-hosted viruses may indicate that some H5N1 viruses have made modest adaptations to their new hosts in the recent past. The markers reported here should be useful in monitoring potential pandemic influenza viruses.

Proteomic studies of the intrinsically unstructured mammalian proteome.

Intrinsically unstructured proteins (IUPs) represent an important class of proteins primarily involved in cellular signaling and regulation. The aim of this study was to develop methodology for the enrichment and identification of IUPs. We show that heat treatment of NIH3T3 mouse fibroblast cell extracts at 98 degrees C selects for IUPs. The majority of these IUPs were cytosolic or nuclear proteins involved in cell signaling or regulation. These studies represent the first large-scale experimental investigation of the intrinsically unstructured mammalian proteome.

Large-scale sequence analysis of avian influenza isolates.

The spread of H5N1 avian influenza viruses (AIVs) from China to Europe has raised global concern about their potential to infect humans and cause a pandemic. In spite of their substantial threat to human health, remarkably little AIV whole-genome information is available. We report here a preliminary analysis of the first large-scale sequencing of AIVs, including 2196 AIV genes and 169 complete genomes. We combine this new information with public AIV data to identify new gene alleles, persistent genotypes, compensatory mutations, and a potential virulence determinant.

Identification and characterization of novel benzil (diphenylethane-1,2-dione) analogues as inhibitors of mammalian carboxylesterases.

Carboxylesterases (CE) are ubiquitous enzymes responsible for the metabolism of xenobiotics. Because the structural and amino acid homology among esterases of different classes, the identification of selective inhibitors of these proteins has proved problematic. Using Telik's target-related affinity profiling (TRAP) technology, we have identified a class of compounds based on benzil (1,2-diphenylethane-1,2-dione) that are potent CE inhibitors, with K(i) values in the low nanomolar range. Benzil and 30 analogues demonstrated selective inhibition of CEs, with no inhibitory activity toward human acetylcholinesterase or butyrylcholinesterase. Analysis of structurally related compounds indicated that the ethane-1,2-dione moiety was essential for enzyme inhibition and that potency was dependent on the presence of, and substitution within, the benzene ring. 3D-QSAR analyses of these benzil analogues for three different mammalian CEs demonstrated excellent correlations of observed versus predicted K(i) (r(2) > 0.91), with cross-validation coefficients (q(2)) of 0.9. Overall, these results suggest that selective inhibitors of CEs with potential for use in clinical applications can be designed.

Computational prediction of protein-protein interactions.

Eukaryotic proteins typically contain one or more modular domains such as kinases, phosphatases, and phoshopeptide-binding domains, as well as characteristic sequence motifs that direct post-translational modifications such as phosphorylation, or mediate binding to specific modular domains. A computational approach to predict protein interactions on a proteome-wide basis would therefore consist of identifying modular domains and sequence motifs from protein primary sequence data, creating sequence specificity-based algorithms to connect a domain in one protein with a motif in another in "interaction space," and then graphically constructing possible interaction networks. Computational methods for predicting modular domains in proteins have been quite successful, but identifying the short sequence motifs these domains recognize has been more difficult. We are developing improved methods to identify these motifs by combining experimental and computational techniques with databases of sequences and binding information. Scansite is a web-accessible program that predicts interactions between proteins using experimental binding data from peptide library and phage display experiments. This program focuses on domains important in cell signaling, but it can, in principle, be used for other interactions if the domains and binding motifs are known. This chapter describes in detail how to use Scansite to predict the binding partners of an input protein, and how to find all proteins that contain a given sequence motif.

Scansite 2.0: Proteome-wide prediction of cell signaling interactions using short sequence motifs.

Scansite identifies short protein sequence motifs that are recognized by modular signaling domains, phosphorylated by protein Ser/Thr- or Tyr-kinases or mediate specific interactions with protein or phospholipid ligands. Each sequence motif is represented as a position-specific scoring matrix (PSSM) based on results from oriented peptide library and phage display experiments. Predicted domain-motif interactions from Scansite can be sequentially combined, allowing segments of biological pathways to be constructed in silico. The current release of Scansite, version 2.0, includes 62 motifs characterizing the binding and/or substrate specificities of many families of Ser/Thr- or Tyr-kinases, SH2, SH3, PDZ, 14-3-3 and PTB domains, together with signature motifs for PtdIns(3,4,5)P(3)-specific PH domains. Scansite 2.0 contains significant improvements to its original interface, including a number of new generalized user features and significantly enhanced performance. Searches of all SWISS-PROT, TrEMBL, Genpept and Ensembl protein database entries are now possible with run times reduced by approximately 60% when compared with Scansite version 1.0. Scansite 2.0 allows restricted searching of species-specific proteins, as well as isoelectric point and molecular weight sorting to facilitate comparison of predictions with results from two-dimensional gel electrophoresis experiments. Support for user-defined motifs has been increased, allowing easier input of user-defined matrices and permitting user-defined motifs to be combined with pre-compiled Scansite motifs for dual motif searching. In addition, a new series of Sequence Match programs for non-quantitative user-defined motifs has been implemented. Scansite is available via the World Wide Web at http://scansite.mit.edu.