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PubMed1980

A molecular approach to the identification and individualization of human and animal cells in culture: isozyme and allozyme genetic signatures.

The electrophoretic resolution of a group of genetically monomorphic gene-enzyme systems that are developmentally and biologically ubiquitous has been used to provide a species-specific and type-specific biochemical characterization of various cultured cells. The relative mobilities of gene-enzyme systems representing nine distinct gene products from cell cultures of 25 species from Drosophila to man are presented. These isoenzymes effectively discriminate interspecies cell-to-cell contamination and almost invariably serve to identify the contaminating species. The resolution of eight polymorphic gene-enzyme systems in human cell cultures provides a virtually unique allozyme genetic signature as a monitor of intraspecies cellular contamination. The genetic signatures of 47 commonly used human cells are presented. Included in the test were seven putative HeLa (human cervical carcinoma) contaminants each of which expressed a signature identical with that of HeLa. The probability that an unrelated human cell line will have a signature identical to a typed cell is computed for each line from the genotypic frequencies at each locus in a population of cultured human cells. The gene frequencies of this cell population are comparable to the same frequencies in natural human populations. The most common human signature has a frequency (and therefore a probability) of 0.02. The majority of the 17,010 possible signatures are far less probable. A calculation of the theoretical incidence of chance matching of signatures within test groups of two or more individuals is presented. The probability of a chance match between any two randomly selected individuals is 0.004 and among five randomly selected individuals is 0.034. The allozyme genetic signature represents a definitive monitor of cell identity and is presented as a standard of cell and tissue identification for a variety of biological studies.

Animals↗

PubMed2003

Impact of electronic signature on radiology report turnaround time.

The purpose of this study was to measure the impact of electronic signature on report turnaround time. The Radiology Information System (RIS) database was interrogated to obtain a file containing all examinations recorded within a one-month period. Two sectors were specifically studied: abdominal ultrasound and chest radiography. Each of these sectors had one reader per day. The periods studied were October 2001 (before implementation of electronic signature) and February 2002 (3 months after electronic signature implementation). For the abdominal ultrasound examinations, the median time from transcription to final signature decreased from 11 days to 3 days with the introduction of electronic signature ( P < 0.001). For the chest radiographs, the median time from transcription to final signature decreased from 10 days to 5 days with the introduction of electronic signature ( P < 0.001). Electronic signature significantly shortens the time interval between transcription and finalization of radiology reports.

Efficiency, Organizational↗

PubMed1994

Design and use of signature primers to detect carry-over of amplified material.

Signature primer pairs designed for use with the polymerase chain reaction have been developed which can determine if a positive result originated from the intended target nucleic acid or from so-called "carry-over" contamination of previously amplified DNA. The 3' ends of each signature primer, SK339/341, SSK110/111, and SSK58/59 contain a viral specific sequence complementary to regions of either HIV-1, HTLV-I and II respectively. The 5' ends of each primer contain a non-human, non-viral (NHNV) signature sequence including restriction endonuclease sites for subsequent cloning. A fourth set of primers, SK338/340, consist solely of these NHNV sequences and are designed to anneal to any product previously amplified by the viral-specific signature primers. These primers were tested against their corresponding positive and negative DNA targets, to determine their specificity and sensitivity. As expected, the viral-specific signature primers detected the retroviral infected samples while no detectable amplification occurred in negative DNA controls. Primers SK338/340 did not amplify any viral positive or negative template DNA's. Samples spiked with amplified material generated from the viral-specific signature primers could be specifically amplified by the NHNV primers SK338/340. Primers SK338/340 were determined to be more sensitive than the viral-specific signature primers, ensuring the detection of extremely low amounts of carryover. This strategy may be useful in developing other retroviral or non-retroviral primers with a built-in signature sequence that can differentiate false positives from true positives in a subsequent confirmatory test.

Artifacts↗

PubMed2004

Virulence signatures: microarray-based approaches to discovery and analysis.

Rapid, accurate, and sensitive detection of biothreat agents requires a broad-spectrum assay capable of discriminating between closely related microbial or viral pathogens. Moreover, in cases where a biological agent release has been identified, forensic analysis demands detailed genetic signature data for accurate strain identification and attribution. To date, nucleic acid sequences have provided the most robust and phylogentically illuminating signature information. Nucleic acid signature sequences are not often linked to genomic or extrachromosomal determinants of virulence, a link that would further facilitate discrimination between pathogens and closely related species. Inextricably coupling genetic determinants of virulence with highly informative nucleic acid signatures would provide a robust means of identifying human, livestock, and agricultural pathogens. By means of example, we present here an overview of two general applications of microarray-based methods for: (1) the identification of candidate virulence factors; and (2) the analysis of genetic polymorphisms that are coupled to Bacillus anthracis virulence factors using an accurate, low cost solid-phase mini-sequencing assay. We show that microarray-based analysis of gene expression can identify potential virulence associated genes for use as candidate signature targets, and, further, that microarray-based single nucleotide polymorphism assays provide a robust platform for the detection and identification of signature sequences in a manner independent of the genetic background in which the signature is embedded. We discuss the strategy as a general approach or pipeline for the discovery of virulence-linked nucleic acid signatures for biothreat agents.

Bacillus anthracis↗

PubMed2005

The spectrum of genomic signatures: from dinucleotides to chaos game representation.

In the post genomic era, access to complete genome sequence data for numerous diverse species has opened multiple avenues for examining and comparing primary DNA sequence organization of entire genomes. Previously, the concept of a genomic signature was introduced with the observation of species-type specific Dinucleotide Relative Abundance Profiles (DRAPs); dinucleotides were identified as the subsequences with the greatest bias in representation in a majority of genomes. Herein, we demonstrate that DRAP is one particular genomic signature contained within a broader spectrum of signatures. Within this spectrum, an alternative genomic signature, Chaos Game Representation (CGR), provides a unique visualization of patterns in sequence organization. A genomic signature is associated with a particular integer order or subsequence length that represents a measure of the resolution or granularity in the analysis of primary DNA sequence organization. We quantitatively explore the organizational information provided by genomic signatures of different orders through different distance measures, including a novel Image Distance. The Image Distance and other existing distance measures are evaluated by comparing the phylogenetic trees they generate for 26 complete mitochondrial genomes from a diversity of species. The phylogenetic tree generated by the Image Distance is compatible with the known relatedness of species. Quantitative evaluation of the spectrum of genomic signatures may be used to ultimately gain insight into the determinants and biological relevance of the genome signatures.

Base Sequence↗

PubMed2026

Seqwin: ultrafast identification of signature sequences in microbial genomes.

MOTIVATION: Polymerase chain reaction (PCR) enables rapid, cost-effective diagnostics but requires prior identification of genomic regions that allow sensitive and specific detection of target microbial groups, herein referred to as microbial signature sequences. We introduce Seqwin, an open-source framework designed to automate microbial genome signature discovery. Tens of thousands of microbial genomes are now available for a single species, limiting the application of existing manual and automated approaches for identifying signatures. Modern approaches that are capable of leveraging all available microbial genomes will ensure sensitive and accurate DNA signature identification and enable robust pathogen detection for clinical, environmental, and public health applications. RESULTS: Seqwin builds weighted pan-genome minimizer graphs and uses a traversal algorithm to identify signature sequences that occur frequently in target genomes but remain rare in non-targets. Unlike earlier tools that depend on strict presence or absence of sequences, Seqwin accommodates natural sequence variation and scales to very large genome collections. When applied to genomes from C. difficile, M. tuberculosis, and S. enterica, Seqwin recovered more high-quality signatures than alternative methods with lower computational burden. Seqwin's analysis of nearly 15 000 S. enterica genomes yielded over 200 candidate signatures in three minutes. Seqwin provides an open-source solution for the long-standing need for scalable microbial signature discovery and diagnostic assay design. AVAILABILITY AND IMPLEMENTATION: Seqwin is available on GitHub (https://github.com/treangenlab/Seqwin) and can be installed via Bioconda (https://bioconda.github.io/recipes/seqwin/README.html). Benchmarking datasets, outputs, and scripts are available on Zenodo (https://doi.org/10.5281/zenodo.19874011).

Software↗

PubMed2005

Identification of a molecular signature of sarcopenia.

Investigating the molecular mechanisms underlying sarcopenia in humans with the use of microarrays has been complicated by low sample size and the variability inherent in human gene expression profiles. We have conducted a study using Affymetrix GeneChips to identify a molecular signature of aged skeletal muscle. The molecular signature was defined as the set of expressed genes that best distinguished the vastus lateralis muscle of young (n = 10) and older (n = 12) male subjects, when a k-nearest neighbor supervised classification method was used in conjunction with a signal-to-noise ratio gene selection method and a holdout cross-validation procedure. The age-specific expression signature was comprised of 45 genes; 27 were upregulated and 18 were downregulated. This signature also correctly classified 75% of the muscle samples from young and older subjects published by an independent laboratory, based on their expression profiles. The signature revealed increased expression of several genes involved in mediating cellular responses to inflammation and apoptosis, including complement component C1QA, Galectin-1, C/EBP-beta, and FOXO3A, among others. The increased expressions of genes that regulate pre-mRNA splicing, localization, and modification of RNA comprise markers of the aging signature. Downregulated genes in the signature were the glutamine transporter SLC38A1, a TRAF-6 inhibitory zinc finger protein, and membrane-bound transcription factor protease S2P, among others. The sarcopenia signature developed here will be useful as a molecular model to judge the effectiveness of exercise and other therapeutic treatments aimed at ameliorating the effects of muscle loss associated with aging.

Adult↗

PubMed2004

Prognostic meta-signature of breast cancer developed by two-stage mixture modeling of microarray data.

BACKGROUND: An increasing number of studies have profiled tumor specimens using distinct microarray platforms and analysis techniques. With the accumulating amount of microarray data, one of the most intriguing yet challenging tasks is to develop robust statistical models to integrate the findings. RESULTS: By applying a two-stage Bayesian mixture modeling strategy, we were able to assimilate and analyze four independent microarray studies to derive an inter-study validated "meta-signature" associated with breast cancer prognosis. Combining multiple studies (n = 305 samples) on a common probability scale, we developed a 90-gene meta-signature, which strongly associated with survival in breast cancer patients. Given the set of independent studies using different microarray platforms which included spotted cDNAs, Affymetrix GeneChip, and inkjet oligonucleotides, the individually identified classifiers yielded gene sets predictive of survival in each study cohort. The study-specific gene signatures, however, had minimal overlap with each other, and performed poorly in pairwise cross-validation. The meta-signature, on the other hand, accommodated such heterogeneity and achieved comparable or better prognostic performance when compared with the individual signatures. Further by comparing to a global standardization method, the mixture model based data transformation demonstrated superior properties for data integration and provided solid basis for building classifiers at the second stage. Functional annotation revealed that genes involved in cell cycle and signal transduction activities were over-represented in the meta-signature. CONCLUSION: The mixture modeling approach unifies disparate gene expression data on a common probability scale allowing for robust, inter-study validated prognostic signatures to be obtained. With the emerging utility of microarrays for cancer prognosis, it will be important to establish paradigms to meta-analyze disparate gene expression data for prognostic signatures of potential clinical use.

Bayes Theorem↗

PubMed2000

Key residues approach to the definition of protein families and analysis of sparse family signatures.

We extend the concept of the motif as a tool for characterizing protein families and explore the feasibility of a sparse "motif" that is the length of the protein sequence itself. The type of motif discussed is a sparse family signature consisting of a set of N key residue positions (A1, A2...AN) preceded by gaps (G) thus G1A1G2A2. ...GNAN. Both a residue and gap can be variable. A signature is matched to a protein sequence and scored using a dynamic programming algorithm which permits variability in gap distance and residue type. Generating a signature involves identifying residues associated with points of contact in interactions between secondary structure elements. A raw signature consists of a set of positions with potential key structural roles sampled from a sequence alignment constructed with reference to this contact data. Raw signatures are refined by sampling different gap-residue pairs until the specificity of a signature for the family cannot be further improved. We summarize signatures for nine families of protein of diverse fold and function and present results of scans against the OWL protein sequence database. The implications of such signatures are discussed.

Algorithms↗

PubMed2005

Compliance update--valid types of signatures in this modern era.

Proper signatures in the medical record is an area of concern because they are included in the Office of Inspector General (OIG) Compliance Guidance as a potential risk area effecting physician practices. One of the four areas identified by OIG is timely, accurate and complete documentation, which includes "date and legible identity of the observer." Federal auditors deny claims and require refunds if signatures are omitted from documentation of services. The vision of the current President is for all Americans to have Electronic Health Records (EHR) within a decade; this implies a growing use of electronic signatures. What constitutes a valid signature, and what regulations affect the use and type of signature? Businesses require signatures on many forms and documents. However, what if a check is not signed; can it be cashed? If a contract is not signed, is it binding? Similarly, if the medical record is not signed, will it withstand scrutiny in court? What is the significance of a signature? How important is it to authenticate or sign a report? To authenticate means to verify that the message/report comes from its stated source; therefore the author stands behind the documentation as written. The type of signature that is acceptable is variable, depending on the facility and the form payer requires.

Documentation↗

PubMed2026

Prognostic value and immune landscape implications of using a novel homologous recombination repair pathway signature in prostate cancer: A retrospective cohort study.

ObjectiveAlthough the homologous recombination repair (HRR) pathway plays a critical role in the treatment of prostate cancer, its prognostic value remains incompletely understood. This study aimed to identify HRR pathway-related biomarkers with clinical utility for prognosis prediction and treatment guidance.MethodsWe analyzed genomic data from The Cancer Genome Atlas and Chinese patients with prostate cancer in a retrospective cohort study using a comprehensive multiomics approach to characterize a novel HRR-related prognostic signature and its immune implications.ResultsIn the Chinese cohort, 25.6% of the patients exhibited homologous recombination deficiency scores >42, whereas 27.3% carried ≥1 HRR gene mutation. We established a prognostic HRR signature (homologous recombination deficiency score >32, HRR gene mutations, and Signature 3) associated with poor outcomes. Compared with The Cancer Genome Atlas data, the Chinese cohort demonstrated a higher prevalence of HRR signature. Patients with HRR signatures demonstrated significantly increased genomic instability markers, including segment number, alteration burden, aneuploidy score, and intratumor heterogeneity. The HRR signature was associated with higher neoantigen load but reduced T cell receptor (TCR) evenness. Immunologically, HRR-positive tumors were associated with computationally inferred immune profiles suggestive of reduced immune activity, characterized by depletion of T-helper 17 cell; downregulation of TLR4/PDCD1LG2 expression; and upregulation of ARG1, IFNG, KIR2DL3, and CXCL9. However, these findings are descriptive and require experimental validation.ConclusionOur findings identify a clinically relevant HRR signature that warrants investigation as a potential predictive biomarker for prostate cancer prognosis and treatment response. This biomarker provides new insights for personalized therapy and may help optimize patient outcomes.

Humans↗

PubMed2025

An anti-androgen resistance-related gene signature acts as a prognostic marker and increases enzalutamide efficacy via PLK1 inhibition in prostate cancer.

BACKGROUND: Anti-androgen resistance remains a major clinical challenge in the treatment of prostate cancer (PCa), leading to disease progression and treatment failure. Despite extensive research on resistance mechanisms, a reliable prognostic model for predicting patient outcomes and guiding therapeutic strategies is still lacking. This study aimed to develop a novel gene signature related to anti-androgen resistance and evaluate its prognostic and therapeutic implications. METHODS: Anti-androgen resistance-related differentially expressed genes (ARRDEGs) were identified through transcriptomic analysis of enzalutamide- and dual enzalutamide abiraterone-resistant PCa cell lines from the GEO database. Functional enrichment analysis was performed to determine the biological roles of these genes. A prognostic gene signature was developed using univariate Cox regression, LASSO, and multivariate Cox regression models. The model was validated in independent PCa cohorts from The Cancer Genome Atlas (TCGA). Additionally, we assessed the correlation between the signature, immune infiltration, immune checkpoint expression, and drug sensitivity. The efficacy of PLK1 inhibition combined with enzalutamide was further explored using in vitro and in vivo experiments. RESULTS: We identified 304 ARRDEGs, from which three key genes (LMNB1, SSPO, and PLK1) were selected to construct a prognostic signature. This gene signature effectively stratified PCa patients into high- and low-risk groups, with the high-risk group exhibiting shorter recurrence-free survival and distinct immune characteristics. High-risk patients demonstrated elevated immune checkpoint expression (B7H3, CTLA-4, B7-1, and TIGIT), increased M2 macrophage infiltration, and enhanced sensitivity to chemotherapy and targeted therapy. Mechanistically, PLK1 inhibition potentiated the antitumor effect of enzalutamide by downregulating SLC7A11 and inducing ferroptosis, providing a potential therapeutic strategy to overcome anti-androgen resistance. CONCLUSION: We established a novel ARRDEGs-based prognostic signature that predicts PCa progression and response to chemotherapy and targeted therapy. The integration of this signature with immune profiling and drug sensitivity analysis provides a valuable tool for precision oncology in PCa. Our findings highlight the potential of PLK1 inhibition as a therapeutic strategy to enhance enzalutamide efficacy and overcome resistance.

Humans↗

PubMed2007

Determination of community structure through deconvolution of PLFA-FAME signature of mixed population.

Phospholipid fatty acids (PLFAs) as biomarkers are well established in the literature. A general method based on least square approximation (LSA) was developed for the estimation of community structure from the PLFA signature of a mixed population where biomarker PLFA signatures of the component species were known. Fatty acid methyl ester (FAME) standards were used as species analogs and mixture of the standards as representative of the mixed population. The PLFA/FAME signatures were analyzed by gas chromatographic separation, followed by detection in flame ionization detector (GC-FID). The PLFAs in the signature were quantified as relative weight percent of the total PLFA. The PLFA signatures were analyzed by the models to predict community structure of the mixture. The LSA model results were compared with the existing "functional group" approach. Both successfully predicted community structure of mixed population containing completely unrelated species with uncommon PLFAs. For slightest intersection in PLFA signatures of component species, the LSA model produced better results. This was mainly due to inability of the "functional group" approach to distinguish the relative amounts of the common PLFA coming from more than one species. The performance of the LSA model was influenced by errors in the chromatographic analyses. Suppression (or enhancement) of a component's PLFA signature in chromatographic analysis of the mixture, led to underestimation (or overestimation) of the component's proportion in the mixture by the model. In mixtures of closely related species with common PLFAs, the errors in the common components were adjusted across the species by the model.

Bacteria↗

PubMed1998

Context-specific use suggests that bottlenose dolphin signature whistles are cohesion calls.

Studies on captive bottlenose dolphins, Tursiops truncatus, have shown that each individual produces a stereotyped, individually specific signature whistle; however, no study has demonstrated clear context-dependent usage of these whistles. Thus, the hypothesis that signature whistles are used to maintain group cohesion remains untested. To investigate whether signature whistles are used only in contexts that would require a mechanism to maintain group cohesion, we examined whistle type usage in a group of four captive bottlenose dolphins in two contexts. Individuals were recorded while they were separate from the group and while they all swam in the same pool. Separations occurred spontaneously when one animal swam into another pool. No partitions were used and no aggressive interactions between dolphins preceded separations. Calling animals were identified by an amplitude comparison of the same sound recorded in the two pools. Each dolphin primarily produced one stereotyped signature whistle when it was separated from the group. Similarly the remaining group in the other pool also used primarily their signature whistles if one animal was in a separate pool. If all animals swam in the same pool almost only nonsignature whistles were used. Signature whistle copying was rare and did not initiate reunions or specific vocal responses. The results strongly support the hypothesis that signature whistles are used to maintain group cohesion. Copyright 1998 The Association for the Study of Animal Behaviour.

Journal Article↗

PubMed2005

ArrayVigil: a methodology for statistical comparison of gene signatures using segregated-one-tailed (SOT) Wilcoxon's signed-rank test.

Due to versatile diagnostic and prognostic fidelity molecular signatures or fingerprints are anticipated as the most powerful tools for cancer management in the near future. Notwithstanding the experimental advancements in microarray technology, methods for analyzing either whole arrays or gene signatures have not been firmly established. Recently, an algorithm, ArraySolver has been reported by Khan for two-group comparison of microarray gene expression data using two-tailed Wilcoxon signed-rank test. Most of the molecular signatures are composed of two sets of genes (hybrid signatures) wherein up-regulation of one set and down-regulation of the other set collectively define the purpose of a gene signature. Since the direction of a selected gene's expression (positive or negative) with respect to a particular disease condition is known, application of one-tailed statistics could be a more relevant choice. A novel method, ArrayVigil, is described for comparing hybrid signatures using segregated-one-tailed (SOT) Wilcoxon signed-rank test and the results compared with integrated-two-tailed (ITT) procedures (SPSS and ArraySolver). ArrayVigil resulted in lower P values than those obtained from ITT statistics while comparing real data from four signatures.

Algorithms↗

PubMed2005

Gene expression signatures for colorectal cancer microsatellite status and HNPCC.

The majority of microsatellite instable (MSI) colorectal cancers are sporadic, but a subset belongs to the syndrome hereditary non-polyposis colorectal cancer (HNPCC). Microsatellite instability is caused by dysfunction of the mismatch repair (MMR) system that leads to a mutator phenotype, and MSI is correlated to prognosis and response to chemotherapy. Gene expression signatures as predictive markers are being developed for many cancers, and the identification of a signature for MMR deficiency would be of interest both clinically and biologically. To address this issue, we profiled the gene expression of 101 stage II and III colorectal cancers (34 MSI, 67 microsatellite stable (MSS)) using high-density oligonucleotide microarrays. From these data, we constructed a nine-gene signature capable of separating the mismatch repair proficient and deficient tumours. Subsequently, we demonstrated the robustness of the signature by transferring it to a real-time RT-PCR platform. Using this platform, the signature was validated on an independent test set consisting of 47 tumours (10 MSI, 37 MSS), of which 45 were correctly classified. In a second step, we constructed a signature capable of separating MMR-deficient tumours into sporadic MSI and HNPCC cases, and validated this by a mathematical cross-validation approach. The demonstration that this two-step classification approach can identify MSI as well as HNPCC cases merits further gene expression studies to identify prognostic signatures.

Adenocarcinoma↗

PubMed2002

A gene-expression signature as a predictor of survival in breast cancer.

BACKGROUND: A more accurate means of prognostication in breast cancer will improve the selection of patients for adjuvant systemic therapy. METHODS: Using microarray analysis to evaluate our previously established 70-gene prognosis profile, we classified a series of 295 consecutive patients with primary breast carcinomas as having a gene-expression signature associated with either a poor prognosis or a good prognosis. All patients had stage I or II breast cancer and were younger than 53 years old; 151 had lymph-node-negative disease, and 144 had lymph-node-positive disease. We evaluated the predictive power of the prognosis profile using univariable and multivariable statistical analyses. RESULTS: Among the 295 patients, 180 had a poor-prognosis signature and 115 had a good-prognosis signature, and the mean (+/-SE) overall 10-year survival rates were 54.6+/-4.4 percent and 94.5+/-2.6 percent, respectively. At 10 years, the probability of remaining free of distant metastases was 50.6+/-4.5 percent in the group with a poor-prognosis signature and 85.2+/-4.3 percent in the group with a good-prognosis signature. The estimated hazard ratio for distant metastases in the group with a poor-prognosis signature, as compared with the group with the good-prognosis signature, was 5.1 (95 percent confidence interval, 2.9 to 9.0; P<0.001). This ratio remained significant when the groups were analyzed according to lymph-node status. Multivariable Cox regression analysis showed that the prognosis profile was a strong independent factor in predicting disease outcome. CONCLUSIONS: The gene-expression profile we studied is a more powerful predictor of the outcome of disease in young patients with breast cancer than standard systems based on clinical and histologic criteria.

Adult↗

PubMed2005

Robustness, scalability, and integration of a wound-response gene expression signature in predicting breast cancer survival.

Based on the hypothesis that features of the molecular program of normal wound healing might play an important role in cancer metastasis, we previously identified consistent features in the transcriptional response of normal fibroblasts to serum, and used this "wound-response signature" to reveal links between wound healing and cancer progression in a variety of common epithelial tumors. Here, in a consecutive series of 295 early breast cancer patients, we show that both overall survival and distant metastasis-free survival are markedly diminished in patients whose tumors expressed this wound-response signature compared to tumors that did not express this signature. A gene expression centroid of the wound-response signature provides a basis for prospectively assigning a prognostic score that can be scaled to suit different clinical purposes. The wound-response signature improves risk stratification independently of known clinico-pathologic risk factors and previously established prognostic signatures based on unsupervised hierarchical clustering ("molecular subtypes") or supervised predictors of metastasis ("70-gene prognosis signature").

Breast Neoplasms↗