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PubMed2000

An archaeal genomic signature.

Comparisons of complete genome sequences allow the most objective and comprehensive descriptions possible of a lineage's evolution. This communication uses the completed genomes from four major euryarchaeal taxa to define a genomic signature for the Euryarchaeota and, by extension, the Archaea as a whole. The signature is defined in terms of the set of protein-encoding genes found in at least two diverse members of the euryarchaeal taxa that function uniquely within the Archaea; most signature proteins have no recognizable bacterial or eukaryal homologs. By this definition, 351 clusters of signature proteins have been identified. Functions of most proteins in this signature set are currently unknown. At least 70% of the clusters that contain proteins from all the euryarchaeal genomes also have crenarchaeal homologs. This conservative set, which appears refractory to horizontal gene transfer to the Bacteria or the Eukarya, would seem to reflect the significant innovations that were unique and fundamental to the archaeal "design fabric." Genomic protein signature analysis methods may be extended to characterize the evolution of any phylogenetically defined lineage. The complete set of protein clusters for the archaeal genomic signature is presented as supplementary material (see the PNAS web site, www.pnas.org).

Archaeal Proteins↗
PubMed2006

Expression profiling analysis of the CD5+ diffuse large B-cell lymphoma subgroup: development of a CD5 signature.

Diffuse large B-cell lymphoma (DLBCL) accounts for 30% of non-Hodgkin's lymphomas and is known to comprise heterogeneous groups. We previously reported that CD5+ DLBCL is a clinically distinct subgroup of these tumors that is associated with poor prognosis. In our current study, we have used gene expression profiling technology in an attempt to identify new markers and to further characterize the biological features of CD5+ DLBCL. Candidate genes, which showed the greatest difference in expression between 22 CD5+ and 26 CD5- DLBCL cases, were selected from our screening and subjected to clustering analysis. This resulted in identification of a specific mRNA profile (a CD5 signature) for CD5+ DLBCL. The CD5 signature included downregulated extracellular matrix genes such as POSTN, SPARC, COL1A1, COL3A1, CTSK, MMP9 and LAMB3, and comprised upregulated genes including TRPM4. We tested this CD5 signature for its potential use as a relevant marker for CD5+ DLBCL and found that it did indeed recognize this subgroup. The tumors identified by the CD5 signature contained most of the CD5+ DLBCL cases and some CD5- DLBCL cases. Moreover, the subgroup of cases with this CD5 signature showed a poorer prognosis. The subsequent application of the CD5 signature to the analysis of an independent series of DLBCL microarray data resulted in identification of a subgroup of DLBCL cases with a similar clinical outcome, further suggesting that the CD5 signature can be used as a clinically relevant marker of this disease.

Biomarkers, Tumor↗
PubMed2004

Autoimmunity gene expression portrait: specific signature that intersects or differentiates between multiple sclerosis and systemic lupus erythematosus.

Autoimmune diseases are either tissue-specific like multiple sclerosis (MS) or multisystemic like systemic lupus erythematosus (SLE), although clinically both exhibit common features. To gain insight into the properties of the genes involved in each disease we have investigated the gene expression signature of peripheral blood mononuclear cells (PBMC) in MS and SLE in comparison to healthy subjects. Total RNA was purified, hybridized to Genechip array and analysed in 36 subjects (13 relapsing-remitting MS patients, five SLE patients and 18 age-matched healthy subjects that served as controls). Additional blood samples from 15 relapsing-remitting MS patients, 8 SLE patients and 10 healthy subjects were used for confirmation of microarray gene expression findings by ELISA and RT-PCR. MS and SLE patients demonstrated a common gene expression autoimmune signature of 541 genes which differentiated them from healthy subjects. The autoimmune signature included genes that encode proteins involved in apoptosis, cell cycle, inflammation and regulation of matrix metalloproteinase pathways. Specifically, decreased TIMP1 gene expression in the autoimmunity signature suggests increased MMP activity in target tissues as a result of the lack of feedback mechanism. An additional different disease specific signature identified the gene expression pattern for MS (1031 genes), mainly associated with over-expression of adhesion molecules and down-expression of heat shock proteins; the SLE specific signature (1146 genes) mainly involved DNA damage/repair pathways that result in production of nuclear autoantibodies. These results provide insights into the genetic pathways underlying autoimmune diseases, and identify specific disease-associated signatures that may enable targetted disease-related specific therapies to be developed.

Adult↗
PubMed2005

Gene signatures of progression and metastasis in renal cell cancer.

PURPOSE: To address the progression, metastasis, and clinical heterogeneity of renal cell cancer (RCC). EXPERIMENTAL DESIGN: Transcriptional profiling with oligonucleotide microarrays (22,283 genes) was done on 49 RCC tumors, 20 non-RCC renal tumors, and 23 normal kidney samples. Samples were clustered based on gene expression profiles and specific gene sets for each renal tumor type were identified. Gene expression was correlated to disease progression and a metastasis gene signature was derived. RESULTS: Gene signatures were identified for each tumor type with 100% accuracy. Differentially expressed genes during early tumor formation and tumor progression to metastatic RCC were found. Subsets of these genes code for secreted proteins and membrane receptors and are both potential therapeutic or diagnostic targets. A gene pattern ("metastatic signature") derived from primary tumor was very accurate in classifying tumors with and without metastases at the time of surgery. A previously described "global" metastatic signature derived by another group from various non-RCC tumors was validated in RCC. CONCLUSION: Unlike previous studies, we describe highly accurate and externally validated gene signatures for RCC subtypes and other renal tumors. Interestingly, the gene expression of primary tumors provides us information about the metastatic status in the respective patients and has the potential, if prospectively validated, to enrich the armamentarium of diagnostic tests in RCC. We validated in RCC, for the first time, a previously described metastatic signature and further showed the feasibility of applying a gene signature across different microarray platforms. Transcriptional profiling allows a better appreciation of the molecular and clinical heterogeneity in RCC.

Adult↗
PubMed2006

Independent confirmation of a prognostic gene-expression signature in adult acute myeloid leukemia with a normal karyotype: a Cancer and Leukemia Group B study.

Patients with acute myeloid leukemia (AML) and normal karyotype are classified in an intermediate-risk group, albeit this subset is heterogeneous for clinical outcome. A recent complementary DNA microarray study identified a gene-expression signature that--when used to cluster normal karyotype patients--separated them into 2 prognostically relevant subgroups. We sought the first independent validation of the prognostic value of this signature. Using oligonucleotide microarrays to measure gene expression in samples from uniformly treated adults with karyotypically normal AML, we performed cluster analysis based on the previously identified signature. We also developed a well-defined classification rule using the signature to predict outcome for individual patients. Cluster analysis confirmed the prognostic utility of the signature: patient clusters differed in overall (P = .001) and disease-free (P = .001) survival. The signature-based classifier identified groups with differences in overall (P = .02) and disease-free (P = .05) survival. A strong association of the outcome classifier with the prognostically adverse FLT3 internal tandem duplication (FLT3 ITD) potentially explained the prognostic significance of the signature. However, in the subgroup of patients without FLT3 ITD there was a moderate difference in survival for the classifier-derived groups. Our analysis confirms the applicability of the gene-expression profiling strategy for outcome prediction in cytogenetically normal AML.

Acute Disease↗
PubMed2005

Predictors of primary breast cancers responsiveness to preoperative epirubicin/cyclophosphamide-based chemotherapy: translation of microarray data into clinically useful predictive signatures.

BACKGROUND: Our goal was to identify gene signatures predictive of response to preoperative systemic chemotherapy (PST) with epirubicin/cyclophosphamide (EC) in patients with primary breast cancer. METHODS: Needle biopsies were obtained pre-treatment from 83 patients with breast cancer and mRNA was profiled on Affymetrix HG-U133A arrays. Response ranged from pathologically confirmed complete remission (pCR), to partial remission (PR), to stable or progressive disease, "No Change" (NC). A primary analysis was performed in breast tissue samples from 56 patients and 5 normal healthy individuals as a training cohort for predictive marker identification. Gene signatures identifying individuals most likely to respond completely to PST-EC were extracted by combining several statistical methods and filtering criteria. In order to optimize prediction of non responding tumors Student's t-test and Wilcoxon test were also applied. An independent cohort of 27 patients was used to challenge the predictive signatures. A k-Nearest neighbor algorithm as well as two independent linear partial least squares determinant analysis (PLS-DA) models based on the training cohort were selected for classification of the test samples. The average specificity of these predictions was greater than 74% for pCR, 100% for PR and greater than 62% for NC. All three classification models could identify all pCR cases. RESULTS: The differential expression of 59 genes in the training and the test cohort demonstrated capability to predict response to PST-EC treatment. Based on the training cohort a classifier was constructed following a decision tree. First, a transcriptional profile capable to distinguish cancerous from normal tissue was identified. Then, a "favorable outcome signature" (31 genes) and a "poor outcome signature" (26 genes) were extracted from the cancer specific signatures. This stepwise implementation could predict pCR and distinguish between NC and PR in a subsequent set of patients. Both PLS-DA models were implemented to discriminate all three response classes in one step. CONCLUSION: In this study signatures were identified capable to predict clinical outcome in an independent set of primary breast cancer patients undergoing PST-EC.

Journal Article↗
PubMed2006

Dissection of a metastatic gene expression signature into distinct components.

BACKGROUND: Metastasis, the process whereby cancer cells spread, is in part caused by an incompletely understood interplay between cancer cells and the surrounding stroma. Gene expression studies typically analyze samples containing tumor cells and stroma. Samples with less than 50% tumor cells are generally excluded, thereby reducing the number of patients that can benefit from clinically relevant signatures. RESULTS: For a head-neck squamous cell carcinoma (HNSCC) primary tumor expression signature that predicts the presence of lymph node metastasis, we first show that reduced proportions of tumor cells results in decreased predictive accuracy. To determine the influence of stroma on the predictive signature and to investigate the interaction between tumor cells and the surrounding microenvironment, we used laser capture microdissection to divide the metastatic signature into six distinct components based on tumor versus stroma expression and on association with the metastatic phenotype. A strikingly skewed distribution of metastasis associated genes is revealed. CONCLUSION: Dissection of predictive signatures into different components has implications for design of expression signatures and for our understanding of the metastatic process. Compared to primary tumors that have not formed metastases, primary HNSCC tumors that have metastasized are characterized by predominant down-regulation of tumor cell specific genes and exclusive up-regulation of stromal cell specific genes. The skewed distribution agrees with poor signature performance on samples that contain less than 50% tumor cells. Methods for reducing tumor composition bias that lead to greater predictive accuracy and an increase in the types of samples that can be included are presented.

Carcinoma, Squamous Cell↗
PubMed1995

Pattern recognition of amino acid signatures in retinal neurons.

Pattern recognition of amino acid signals partitions the cells of the goldfish retina into nine statistically unique biochemical theme classes and permits a first-order chemical mapping of virtually all cellular space. Photoreceptors, bipolar cells, and ganglion cells display a set of unique, nominally glutamatergic type E1, E1+E2, and E4 signatures, respectively. All horizontal cells are assignable to a GABAergic gamma 2 class or a non-GABAergic class with a glutamate-rich E3 signature. The amacrine cell layer is largely a mixture of (1) a taurine-dominated T1 Müller's cell signature and (2) GABAergic gamma 1, glycinergic G1, and dual glycinergic/GABAergic G gamma 1 amacrine cell signatures. Several major conclusions emerge from this work. (1) Glutamatergic, GABAergic, and glycinergic neural signatures and glial signatures account for over 99% of the cellular space in the retina. (2) All known neurons in the goldfish retina are associated with a set of conventional nonpeptide neurotransmitters. (3) Multiple forms of metabolic profiles are associated with a single nominal neurotransmitter category. (4) Glutamate and aspartate contents exhibit overlapping distributions and are not adequate univariate probes for identifying cell classes. (5) Signatures can serve as quantitative measures of cell state.

Amino Acids↗
PubMed2025

Glioma mutational signatures associated with haloalkane exposure are enriched in firefighters.

BACKGROUND: Glioma is the most common malignant primary brain tumor and is associated with significant morbidity and mortality. Modifiable risk factors remain unidentified. New advances in exposure assessment, genomic analyses, and statistical techniques permit more accurate evaluation of glioma risk associated with exogenous occupational or environmental exposures. METHODS: By using whole-exome sequencing data from matched germline and glioma tumor samples, the authors compared tumor mutational signatures for 17 persons with glioma and a documented occupational history of firefighting with those of 18 persons with glioma without an occupational history of firefighting. All 35 individuals were participants in the University of California, San Francisco Adult Glioma Study. RESULTS: There was a positive correlation among firefighters between the median number of sample variants attributable to single-base substitution signature 42, a single-base substitution mutational signature associated with haloalkane exposure (from the Catalogue of Somatic Mutational Signatures in Cancer) and firefighting years (p = .04; R2 = 0.29). Among nonfirefighters, the individuals with the highest number of median variants attributable to single-base substitution signature 42 also had occupations that possibly exposed them to haloalkanes, such as painting and being a mechanic. CONCLUSIONS: In summary, the authors identified gliomas that had mutational signatures associated with haloalkane exposure that were enriched in firefighters and other occupations.

Humans↗
PubMed2024

Construction of an immunogenic cell death-related LncRNA signature to predict the prognosis of patients with lung adenocarcinoma.

BACKGROUND: Lung adenocarcinoma (LUAD) is one of the most common malignant diseases worldwide. This study aimed to construct an immunogenic cell death (ICD)-related long non-coding RNA (lncRNA) signature to effectively predict the prognosis of LUAD. METHODS: The RNA-sequencing and clinical data of LUAD were downloaded from The Cancer Genome Atlas (TCGA). Least absolute shrinkage and selection operator (LASSO) and stepwise multivariate Cox proportional hazard regression analysis were utilized to construct lncRNA signature. Then, the reliability of the signature was evaluated in the training, validation and whole cohorts. The differences in the immune landscape and drug sensitivity between the low- and high-risk groups were analyzed. Finally, the expression level of the selected ICD-related lncRNAs in LUAD cell lines via reverse transcription quantitative PCR (RT-qPCR). CCK-8 and transwell assays were performed to study biological function of AC245014.3. RESULTS: A signature consisting of 5 ICD-related lncRNAs was constructed. Kaplan Meier (K-M) survival analysis showed shorter overall survival (OS) in high-risk group. The receiver operating characteristic (ROC) curves and Multivariate Cox regression analysis showed the signature was good predictive and independent prognostic factor in LUAD. Moreover, the high-risk group had a lower level of antitumor immunity and was less sensitive to some chemotherapeutics and targeted drugs. Finally, the expression level of selected ICD-related lncRNAs was validated in LUAD cell lines by RT-qPCR. Knockdown of AC245014.3 significantly suppressed LUAD proliferation, migration and invasion. CONCLUSIONS: In this study, an ICD-related lncRNA signature was constructed, which could accurately predict the prognosis of LUAD patients and guide clinical treatment.

Humans↗
PubMed2004

Verifiable threshold signature schemes against conspiracy attack.

In this study, the author has designed new verifiable (t,n) threshold untraceable signature schemes. The proposed schemes have the following properties:(1) Verification: The shadows of the secret distributed by the trusted center can be verified by all of the participants;(2) Security: Even if the number of the dishonest member is over the value of the threshold, they cannot get the system secret parameters, such as the group secret key, and forge other member's individual signature;(3) Efficient verification: The verifier can verify the group signature easily and the verification time of the group signature is equivalent to that of an individual signature; (4) Untraceability: The signers of the group signature cannot be traced.

Algorithms↗
PubMed2003

[Does the digital signature of the DICOM standard meet the requirements of German law?].

The DICOM standard offers the possibilities to generate electronic signatures, valid according to German laws. This enhances the reliability of the correlation between image and patient data. However, only so called qualified electronic signatures--conveniently issued by an accredited supplier--are permissible and not rejectable as evidence in German jurisdiction and are completely equivalent to the handwritten signatures. These qualified electronic signatures can be executed only by individuals, whereas the former are not applicable to technical apparatus like image generating modalities. In consequence, a modality is able to provide its pictures with a "common or advanced signature" solely. This limits the use of the digital signature of the DICOM standard for further applications, e.g. the verifiability within the teleradiology.

Algorithms↗
PubMed2006

Neural signatures: multiple coding in spiking-bursting cells.

Recent experiments have revealed the existence of neural signatures in the activity of individual cells of the pyloric central pattern generator (CPG) of crustacean. The neural signatures consist of cell-specific spike timings in the bursting activity of the neurons. The role of these intraburst neural fingerprints is still unclear. It has been reported previously that some muscles can reflect small changes in the spike timings of the neurons that innervate them. However, it is unclear to what extent neural signatures contribute to the command message that the muscles receive from the motoneurons. It is also unknown whether the signatures have any functional meaning for the neurons that belong to the same CPG or to other interconnected CPGs. In this paper, we use realistic neural models to study the ability of single cells and small circuits to recognize individual neural signatures. We show that model cells and circuits can respond distinctly to the incoming neural fingerprints in addition to the properties of the slow depolarizing waves. Our results suggest that neural signatures can be a general mechanism of spiking-bursting cells to implement multicoding.

Action Potentials↗
PubMed2005

Chiral signatures of PCB#s 95 and 149 in indoor air, grass, duplicate diets and human faeces.

Chiral signatures of PCB#s 95 and 149 are reported for indoor air, grass, omnivorous and vegan duplicate human diet homogenates, and human faeces. Comparison of chiral signatures of both congeners in grass with those reported previously for outdoor air (measured at a height of 1.5 m) and soil at the same location suggest that volatilisation of PCBs present in soil may exert a significant influence on concentrations in grass. Duplicate diet homogenates display racemic signatures for both congeners. Alongside the racemic signatures in both outdoor and indoor air, this implies that human intake via diet and inhalation is racemic, and that the previously observed variation between individuals in the extent of enantioselective degradation in human liver samples indicates possible inter-individual variation in ability to metabolise PCBs. Chiral signatures of PCB# 95 in the 10 human faecal samples analysed indicate 8 to be racemic, but 2 to display an excess of the 2nd eluting enantiomer. This is consistent with the excess of the 1st eluting enantiomer reported elsewhere for human liver samples, as it implies enantioselective excretion of the 2nd eluting enantiomer. However, the racemic residues for PCB# 95 in the majority of faecal samples are a possible indication that enantioselective interaction of chiral PCBs with cytochrome P450 occurs slowly. The racemic or near-racemic signatures observed for PCB# 95 and 149 in indoor air match closely those in outdoor air, but differ from those in soil, adding to the weight of evidence that ventilation of indoor air is a far more significant contributor to outdoor air concentrations than volatilisation of PCBs from soil.

Air Pollutants↗
PubMed2025

TSC angiofibroma and ungual fibroma have different mutation signatures, with recurrent mutations in KMT2C.

PURPOSE: Tuberous sclerosis complex (TSC) is an autosomal dominant tumor suppressor syndrome characterized by tumors affecting multiple tissues, including skin, due to inactivating TSC1/TSC2 variants. Genome-wide profiling of somatic mutations in a unique collection of angiofibroma (FAF) and ungual fibroma (UF) TSC skin tumors was performed. METHODS: Genome sequencing was performed on 9 samples, comprising 4 FAF and 5 UF, along with 6 matched normal samples from 6 individuals with TSC. RESULTS: TSC-FAF and TSC-UF skin tumors have different mutation signatures, with a predominance of UV-related single-nucleotide variant (SNV; SBS7a and SBS7b) and dinucleotide variant (DNV; DBS1) signatures in FAF, and aging-related SNV (SBS1 and SBS5) signatures in UF. We also identified a novel DNV signature for TSC-UF, with frequent TG>CA and TT>GG substitutions. Furthermore, 3 inactivating somatic mutations in KMT2C were observed in 2 of 4 TSC-FAF and 5 mutations in other cancer genes. CONCLUSION: The distinct SNV mutation signatures seen in TSC-FAF and UF indicate that they develop through distinct pathogenic mechanisms, UV-induced mutagenesis in FAF, and aging-related mutagenesis in UF. The mechanism of the novel DNV signature in UFs merits further investigation. Our observation on the occurrence of KMT2C mutations suggests that KMT2C inactivation contributes to the pathogenesis of TSC-FAF.

Humans↗
PubMed1997

The temporal evolution of MRI tissue signatures after transient middle cerebral artery occlusion in rat.

We have developed a multiparameter magnetic resonance imaging (MRI) cluster analysis model of acute ischemic stroke using T2 relaxation times and the diffusion coefficient of water (ADCw). To test the ability of this model to predict cerebral infarction, male Wistar rats (n = 7) were subjected to 2 h of transient middle cerebral artery (MCA) occlusion, and diffusion and T2 weighted MRI were performed on these rats before, during and up to 7 days after MCA occlusion. MRI tissue signatures, specified by values of ADCw and T2 were assigned to tissue histopathology. Significant correlations were obtained between MRI signatures at different time points and histopathologic measurements of lesion area obtained at 1 week. In addition, we compared the temporal evolution of MRI tissue signatures to a separate population of animals at which histological data were obtained at select times of reperfusion. A significant shift (p < or = 0.05) within signatures reflecting tissue histopathology was demonstrated as the ischemic lesion evolved over time. Our data suggest, that the MRI signatures are associated with the degree of ischemic cell damage. Thus, the tissue signature model may provide a noninvasive means to monitor the evolution of ischemic cell damage and to predict final outcome of ischemic cell damage.

Animals↗
PubMedDate not supplied

A critical evaluation of two methods of signature analysis.

The assessment of signature disguise, where an individual attempts to disguise their own signature on a document with the intent of later disclaiming it (so-called 'view to deny' signatures), is a problem faced by many document examiners. This study evaluates a method known as the angle value test and another experimental method involving angle measurements to determine if either of them can reliably establish whether a questioned signature is disguised or has been written by another person. By using 29 sets of normal and disguised signatures, both methods of analysis were shown to be unreliable techniques for identifying the author of a particular signature.

Journal Article↗
PubMedDate not supplied

Enrichment of ligands for the serotonin receptor using the Shape Signatures approach.

Shape Signatures, a new 3-dimensional molecular comparison method, has been adapted to rank ligands of the serotonin receptors. A set of 825 agonists and 400 antagonists together with approximately 10,000 randomly chosen compounds from the NCI database were used in this study. Both 1D and 2D Shape Signature databases were created, and enrichment studies were carried out. Results from these studies reveal that the 1D Shape Signature approach is highly efficient in separating agonists from a mixture of molecules which includes compounds randomly selected from the NCI database taken as inactives. It is also equally effective at separating agonists and antagonists from a pool of active ligands for the serotonin receptor. Parallel enrichment studies using 2D shape signatures showed high selectivity with more restricted coverage due to the high specificity of 2D signatures. The influence of conformational variation of the shape signature on enrichment was explored by docking a subset of ligands into the crystal structure of serotonin N-acetyltransferase. Enrichment studies on the resulting "docked" conformations produced only slightly improved results compared with the CORINA-generated conformations.

Computer Simulation↗