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At least 289 records · Page 16Linked to original sources
PubMed2005

Structural signature of jamming in granular media.

Glasses are rigid, but flow when the temperature is increased. Similarly, granular materials are rigid, but become unjammed and flow if sufficient shear stress is applied. The rigid and flowing phases are strikingly different, yet measurements reveal that the structures of glass and liquid are virtually indistinguishable. It is therefore natural to ask whether there is a structural signature of the jammed granular state that distinguishes it from its flowing counterpart. Here we find evidence for such a signature, by measuring the contact-force distribution between particles during shearing. Because the forces are sensitive to minute variations in particle position, the distribution of forces can serve as a microscope with which to observe correlations in the positions of nearest neighbours. We find a qualitative change in the force distribution at the onset of jamming. If, as has been proposed, the jamming and glass transitions are related, our observation of a structural signature associated with jamming hints at the existence of a similar structural difference at the glass transition--presumably too subtle for conventional scattering techniques to uncover. Our measurements also provide a determination of a granular temperature that is the counterpart in granular systems to the glass-transition temperature in liquids.

Journal Article↗
PubMed2004

An oncogenic KRAS2 expression signature identified by cross-species gene-expression analysis.

Using advanced gene targeting methods, generating mouse models of cancer that accurately reproduce the genetic alterations present in human tumors is now relatively straightforward. The challenge is to determine to what extent such models faithfully mimic human disease with respect to the underlying molecular mechanisms that accompany tumor progression. Here we describe a method for comparing mouse models of cancer with human tumors using gene-expression profiling. We applied this method to the analysis of a model of Kras2-mediated lung cancer and found a good relationship to human lung adenocarcinoma, thereby validating the model. Furthermore, we found that whereas a gene-expression signature of KRAS2 activation was not identifiable when analyzing human tumors with known KRAS2 mutation status alone, integrating mouse and human data uncovered a gene-expression signature of KRAS2 mutation in human lung cancer. We confirmed the importance of this signature by gene-expression analysis of short hairpin RNA-mediated inhibition of oncogenic Kras2. These experiments identified both a pattern of gene expression indicative of KRAS2 mutation and potential effectors of oncogenic KRAS2 activity in human cancer. This approach provides a strategy for using genomic analysis of animal models to probe human disease.

Adenocarcinoma↗
PubMed2006

A signature of chromosomal instability inferred from gene expression profiles predicts clinical outcome in multiple human cancers.

We developed a computational method to characterize aneuploidy in tumor samples based on coordinated aberrations in expression of genes localized to each chromosomal region. We summarized the total level of chromosomal aberration in a given tumor in a univariate measure termed total functional aneuploidy. We identified a signature of chromosomal instability from specific genes whose expression was consistently correlated with total functional aneuploidy in several cancer types. Net overexpression of this signature was predictive of poor clinical outcome in 12 cancer data sets representing six cancer types. Also, the signature of chromosomal instability was higher in metastasis samples than in primary tumors and was able to stratify grade 1 and grade 2 breast tumors according to clinical outcome. These results provide a means to assess the potential role of chromosomal instability in determining malignant potential over a broad range of tumors.

Aneuploidy↗
PubMed2026

Early oligodendrocyte dysfunction signature in Alzheimer's disease: Insights from DNA methylomics and transcriptomics.

Much research into the aetiology of Alzheimer's disease (AD) has focused on neuronal cell types, while studies on the contribution of glial cells, particularly oligodendrocytes (OLGs), are only starting to emerge. Altered brain DNA methylation, an epigenetic modification that provides the interplay between genetics and environmental cues to tightly regulate gene expression, is well documented in AD. Yet, cell-type-specific investigations remain limited. Here, we examine the role of DNA methylation and OLGs in AD, and how such changes may impact gene expression. We performed weighted-gene correlation network analysis (WGCNA) on multiple brain omics AD datasets across species: human DNA methylation data from 4 brain regions, human brain single-nuclei RNA sequencing data and mouse brain RNA sequencing data. We compared AD-associated network modules enriched for OLG genes across AD brain regions, as well as with other neurodegenerative disease DNA methylation datasets. We identified a DNA methylation signature associated with AD, enriched for OLGs, and preserved across brain regions representing early and late AD pathology stages. Genes within this signature showed altered expression in AD OLGs, confirming cell-type specificity and relevance to AD. This OLG signature was also preserved in transgenic mice with early Aβ pathology and in other neurodegenerative diseases without Aβ pathology. We reveal a consistent pattern of OLG dysfunction spanning early to late stages of AD, across DNA methylation and gene expression. Our findings highlight OLG-associated DNA methylation changes as important in AD pathogenesis, and possibly in other neurodegenerative diseases, opening new avenues for therapeutic development.

Alzheimer Disease↗
PubMed2026

Cell-type signatures of Alzheimer's disease shared across population groups.

Genomic studies at single-cell resolution have identified several cell types associated with clinical and pathological traits in Alzheimer's disease1-9, but have not examined associations that are shared across populations. To bridge this gap, here we use single-nucleus RNA sequencing and assay for transposase-accessible chromatin with sequencing to profile cortical and subcortical regions in post-mortem brain-tissue samples from Latin, white (excluding Latin) and African American (excluding Latin) individuals. Using discrete and continuous dissections of molecular programs, we identify cell-type-specific clusters associated with Alzheimer's disease in a region-specific manner across all three population groups, including microglial (GPNMB+ and CD74+ subgroups), astrocytic (SERPINH1+, CD44+ and WIF1+ subgroups) and neuronal (SST+ GABAergic and superficial-layer glutamatergic) signatures. We also report continuous gene-expression factors in astrocytes and oligodendrocytes that are not captured by discrete cluster assignments, but which show strong associations with disease phenotypes; these factors are enriched for genes associated with annotated functions such as lipid processing and neurotransmitter reuptake. Finally, we find that molecular programs reveal six distinct subgroups of individuals with cognitive impairment that span all three populations, are not captured by neuropathology, and are instead distinguished by molecular signatures that are not universally present but are nonetheless associated with ante-mortem impairment. Overall, our study identifies key cell types and gene programs implicated in Alzheimer's disease that are shared across population groups, and underscores how representative sampling can capture both shared signatures and disease heterogeneity, thereby enabling better prioritization of key cell types for further investigation.

Female↗
PubMed2004

Pediatric acute lymphoblastic leukemia (ALL) gene expression signatures classify an independent cohort of adult ALL patients.

Recent reports support a possible future application of gene expression profiling for the diagnosis of leukemias. However, the robustness of subtype-specific gene expression signatures has to be proven on independent patient samples. Here, we present gene expression data of 34 adult acute lymphoblastic leukemia (ALL) patients (Affymetrix U133A microarrays). Support Vector Machines (SVMs) were applied to stratify our samples based on given gene lists reported to predict MLL, BCR-ABL, and T-ALL, as well as MLL and non-MLL gene rearrangement positive pediatric ALL. In addition, seven other B-precursor ALL cases not bearing t(9;22) or t(11q23)/MLL chromosomal aberrations were analyzed. Using top differentially expressed genes, hierarchical cluster and principal component analyses demonstrate that the genetically more heterogeneous B-precursor ALL samples intercalate with BCR-ABL-positive cases, but were clearly distinct from T-ALL and MLL profiles. Similar expression signatures were observed for both heterogeneous B-precursor ALL and for BCR-ABL-positive cases. As an unrelated laboratory, we demonstrate that gene signatures defined for childhood ALL were also capable of stratifying distinct subtypes in our cohort of adult ALL patients. As such, previously reported gene expression patterns identified by microarray technology are validated and confirmed on truly independent leukemia patient samples.

Adult↗
PubMed2006

Gene expression signatures associated with the resistance to imatinib.

Imatinib (imatinib mesylate, STI-571, Gleevec) is a selective BCR-ABL tyrosine kinase inhibitor that has been used as a highly effective chemoagent for treating chronic myelogenous leukemia. However, the initial response to imatinib is often followed by the recurrence of a resistant form of the disease, which is major obstacle to many therapeutic modalities. The aim of this study was to identify the gene expression signatures that confer resistance to imatinib. A series of four resistant K562 sublines was established with different imatinib dosage (200, 400, 600 and 800 nM) and analyzed using microarray technology. The transcripts of the genes showing universal or dose-dependent expression changes across the resistant sublines were identified. The gene sets associated with the imatinib-resistance were also identified using gene set enrichment analysis. In the resistant K562 sublines, the transcription- and apoptosis-related expression signatures were upregulated, whereas those related to the protein and energy metabolism were downregulated. Several genes identified in this study such as IGF1 and RAB11A have the potential to become surrogate markers useful in a clinical evaluation of imatinib-resistant patients without BCR-ABL mutation. The expression signatures identified in this study provide insights into the mechanism of imatinib-resistance and are expected to facilitate the development of an effective diagnostic and therapeutic strategy.

Antineoplastic Agents↗
PubMed2006

Identification of a molecular signature predictive of sensitivity to differentiation induction in acute myeloid leukemia.

Acute myeloid leukemia (AML) blasts are immature committed myeloid cells unable to spontaneously undergo terminal maturation, and characterized by heterogeneous sensitivity to natural differentiation inducers. Here, we show a molecular signature predicting the resistance or sensitivity of six myeloid cell lines to differentiation induced in vitro with retinoic acid or vitamin D. The identified signature was further validated by TaqMan assay for the prediction of response to an in vitro differentiation assay performed on 28 freshly isolated AML blast populations. The TaqMan assay successfully predicts the in vitro resistance or responsiveness of AML blasts to differentiation inducers. Furthermore, performing a meta-analysis of publicly available microarray data sets, we also show the accuracy of our prediction on known phenotypes and suggest that our signature could become useful for the identification of patients eligible for new therapeutic strategies.

Acute Disease↗
PubMed2004

Gene expression profiling of advanced ovarian cancer: characterization of a molecular signature involving fibroblast growth factor 2.

Epithelial ovarian cancer (EOC) is the gynecological disease with the highest death rate. We applied an automatic class discovery procedure based on gene expression profiling to stages III-IV tumors to search for molecular signatures associated with the biological properties and progression of EOC. Using a complementary DNA microarray containing 4451 cancer-related, sequence-verified features, we identified a subset of EOC characterized by the expression of numerous genes related to the extracellular matrix (ECM) and its remodeling, along with elements of the fibroblast growth factor 2 (FGF2) signaling pathway. A total of 10 genes were validated by quantitative real-time polymerase chain reaction, and coexpression of FGF2 and fibroblast growth factor receptor 4 in tumor cells was revealed by immunohistochemistry, confirming the reliability of gene expression by cDNA microarray. Since the functional relationships among these genes clearly suggested involvement of the identified molecular signature in processes related to epithelial-stromal interactions and/or epithelial-mesenchymal cellular plasticity, we applied supervised learning analysis on ovarian-derived cell lines showing distinct cellular phenotypes in culture. This procedure enabled construction of a gene classifier able to discriminate mesenchymal-like from epithelial-like cells. Genes overexpressed in mesenchymal-like cells proved to match the FGF2 signaling and ECM molecular signature, as identified by unsupervised class discovery on advanced tumor samples. In vitro functional analysis of the cell plasticity classifier was carried out using two isogenic and immortalized cell lines derived from ovarian surface epithelium and displaying mesenchymal and epithelial morphology, respectively. The results indicated the autocrine, but not intracrine stimulation of mesenchymal conversion and cohort/scatter migration of cells by FGF2, suggesting a central role for FGF2 signaling in the maintenance of cellular plasticity of ovary-derived cells throughout the carcinogenesis process. These findings raise mechanistic hypotheses on EOC pathogenesis and progression that might provide a rational underpinning for new therapeutic modalities.

Cell Line, Tumor↗
PubMedDate not supplied

Use of genomic signatures in therapeutics development in oncology and other diseases.

Pharmacogenomics is the science of determining how the benefits and adverse effects of a drug vary among a target population of patients based on genomic features of the patient's germ line and diseased tissue. By identifying those patients who are most likely to respond while eliminating serious adverse effects, the therapeutic index of a drug can be substantially increased. This may facilitate demonstrating the effectiveness of the drug and may avoid subsequent problems due to serious adverse events. Our objective here is to provide clinical trial designs and analysis strategies for the utilization of genomic signatures as classifiers for patient stratification or patient selection in therapeutics development. We review methods for the development of genomic signature classifiers of treatment outcome in high-dimensional settings, where the number of variables available for prediction far exceeds the number of cases. The split-sample and cross-validation methods for obtaining estimates of prediction accuracy in developmental studies are described. We present clinical trial designs for utilizing genomic signature classifiers in therapeutics development. The purpose of the classifier is to facilitate the identification of groups of patients with a high probability of benefiting from it and avoiding serious adverse events. We distinguish exploratory analysis during the development of the genomic classifier from prospective planning and rigorous testing of therapeutic hypotheses in studies that utilize the genomic classifier in therapeutics development. We discuss a variety of clinical trial designs including those utilizing specimen collection and assay prospectively for newly accrued patients and those involving a prospectively planned analysis of archived specimens from a previously conducted clinical trial. Our discussion of the development and use of classifiers of efficacy is mostly focused on applications in oncology using classifiers based on biomarkers measured in tumors. Some of the same considerations apply, however, to development of efficacy and safety classifiers in nononcologic diseases based on single-nucleotide germline polymorphisms.

Biomarkers↗
PubMed1997

Characterization of the human multidrug resistance protein containing mutations in the ATP-binding cassette signature region.

A number of mutants with single amino acid replacements were generated in the highly conserved ATP-binding cassette (ABC)-signature region (amino acids 531-543) of the N-terminal half of the human multidrug resistance (MDR1) protein. The cDNA variants were inserted into recombinant baculoviruses and the MDR1 proteins were expressed in Spodoptera frugiperda (Sf9) insect cells. The level of expression and membrane insertion of the MDR1 variants was examined by immunostaining, and MDR1 function was followed by measuring drug-stimulated ATPase activity. We found that two mutations, L531R and G534V, practically eliminated MDR1 expression; thus these amino acid replacements seem to inhibit the formation of a stable MDR1 protein structure. The MDR1 variants G534D and I541R were expressed at normal levels with normal membrane insertion, but showed a complete loss of drug-stimulated ATPase activity, while mutant R538M yielded full protein expression but with greatly decreased ATPase activity. Increasing the ATP concentration did not restore MDR1 ATPase activity in these variants. Some amino acid replacements in the ABC-signature region (K536I, K536R, I541T and R543S) affected neither the expression and membrane insertion nor the ATPase function of MDR1. We found no alteration in the drug-sensitivity of ATP cleavage in any of the MDR1 variants that had measurable ATPase activity. These observations suggest that the ABC-signature region is essential for MDR1 protein stability and function, but alterations in this region do not seem to modulate MDR1-drug interactions directly.

ATP Binding Cassette Transporter, Subfamily B, Mem↗
PubMed2004

Genesis of the strand-biased signature in somatic hypermutation of rearranged immunoglobulin variable genes.

The history and current development of the reverse transcriptase model of somatic hypermutation (RT-model) is reviewed with particular reference to the genesis of strand-biased mutation signatures in rearranged immunoglobulin variable genes (V(D)J). The recent disagreement in the field as to whether strand bias really exists or not has been critically analysed and the confusion traced to the putative presence, in some mutated V(D)J sequence collections, of polymerase chain reaction (PCR)-recombinant artefacts. Recent analysis of somatic hypermutation in xeroderma pigmentosum variant patients, by the group of PJ Gearhart and others, has established that the Y-family translesion DNA repair enzyme, DNA polymerase eta (eta), is responsible for the striking A-T targeted strand-bias mutation signature seen in all mouse and human collections of somatically mutated V(D)J sequences. This evidence, together with our own recent demonstration that human DNA polymerase eta is a reverse transcriptase, leads to the conclusion that the strand-biased A-T mutation signature is caused either by: (i) error-prone DNA-dependent DNA repair synthesis by pol-eta of single-strand nicks preferentially in the non-transcribed strand; and/or (ii) by error-prone cDNA synthesis of the transcribed strand by pol-eta using the pre-mRNA as the copying template, primed by the nicked transcribed DNA strand, followed by replacement of the original transcribed strand by cDNA. Analysis of the total mutation pattern also suggests that the major transitions observed in SHM (A-->G, C-->T and G-->A) can be explained by known RNA editing mechanisms active on pre-mRNA which are then written into cDNA during synthesis of the transcribed strand by error-prone cellular reverse transcriptases such as pol-eta.

Animals↗
PubMedDate not supplied

Turning Hox "signatures" into synapomorphies.

It has recently been shown that the three metazoan superphyla that are recognized on the basis of 18S rDNA phylogenies--ecdysozoans, lophotrochozoans, and deuterostomes--each have characteristic Hox genes. This observation has been taken further, and these "signature" Hox genes have been looked for in taxa of uncertain affinity such as the mesozoa, in order to link them to one of the three superphyla. Here I point out that, in the absence of an out-group, these so-called signature Hox genes are unpolarized characters and, as such, should not be used in this cladistic sense to determine phylogeny. Taking the example of the mesozoans, which have the Lox5 gene in common with the lophotrochozoans, I show that it is possible to polarize this character using paralogous Hox genes as proxy out-groups; however, due to the impossibility of reliable alignment outside the homeobox, only two residues of the Lox5 peptide are susceptible to this method. With this in mind, I find slim evidence for an association between mesozoans and lophotrochozoans. I demonstrate that the lophotrochozoan genes Lox2 and Lox4 would provide many more reliable residues that are truly indicative of lophotrochozoan affinity. Finally, I point out the potential problems in using unpolarized signatures to address the question of the position of the acoel flatworms.

Amino Acid Sequence↗
PubMed2005

A MicroRNA signature associated with prognosis and progression in chronic lymphocytic leukemia.

BACKGROUND: MicroRNA expression profiles can be used to distinguish normal B cells from malignant B cells in patients with chronic lymphocytic leukemia (CLL). We investigated whether microRNA profiles are associated with known prognostic factors in CLL. METHODS: We evaluated the microRNA expression profiles of 94 samples of CLL cells for which the level of expression of 70-kD zeta-associated protein (ZAP-70), the mutational status of the rearranged immunoglobulin heavy-chain variable-region (IgV(H) ) gene, and the time from diagnosis to initial treatment were known. We also investigated the genomic sequence of 42 microRNA genes to identify abnormalities. RESULTS: A unique microRNA expression signature composed of 13 genes (of 190 analyzed) differentiated cases of CLL with low levels of ZAP-70 expression from those with high levels and cases with unmutated IgV(H) from those with mutated IgV(H) . The same microRNA signature was also associated with the presence or absence of disease progression. We also identified a germ-line mutation in the miR-16-1-miR-15a primary precursor, which caused low levels of microRNA expression in vitro and in vivo and was associated with deletion of the normal allele. Germ-line or somatic mutations were found in 5 of 42 sequenced microRNAs in 11 of 75 patients with CLL, but no such mutations were found in 160 subjects without cancer (P<0.001). CONCLUSIONS: A unique microRNA signature is associated with prognostic factors and disease progression in CLL. Mutations in microRNA transcripts are common and may have functional importance.

Disease Progression↗
PubMed2007

A five-gene signature and clinical outcome in non-small-cell lung cancer.

BACKGROUND: Current staging methods are inadequate for predicting the outcome of treatment of non-small-cell lung cancer (NSCLC). We developed a five-gene signature that is closely associated with survival of patients with NSCLC. METHODS: We used computer-generated random numbers to assign 185 frozen specimens for microarray analysis, real-time reverse-transcriptase polymerase chain reaction (RT-PCR) analysis, or both. We studied gene expression in frozen specimens of lung-cancer tissue from 125 randomly selected patients who had undergone surgical resection of NSCLC and evaluated the association between the level of expression and survival. We used risk scores and decision-tree analysis to develop a gene-expression model for the prediction of the outcome of treatment of NSCLC. For validation, we used randomly assigned specimens from 60 other patients. RESULTS: Sixteen genes that correlated with survival among patients with NSCLC were identified by analyzing microarray data and risk scores. We selected five genes (DUSP6, MMD, STAT1, ERBB3, and LCK) for RT-PCR and decision-tree analysis. The five-gene signature was an independent predictor of relapse-free and overall survival. We validated the model with data from an independent cohort of 60 patients with NSCLC and with a set of published microarray data from 86 patients with NSCLC. CONCLUSIONS: Our five-gene signature is closely associated with relapse-free and overall survival among patients with NSCLC.

Aged↗
PubMed2004

Multidimensional signatures in antimicrobial peptides.

Conventional analyses distinguish between antimicrobial peptides by differences in amino acid sequence. Yet structural paradigms common to broader classes of these molecules have not been established. The current analyses examined the potential conservation of structural themes in antimicrobial peptides from evolutionarily diverse organisms. Using proteomics, an antimicrobial peptide signature was discovered to integrate stereospecific sequence patterns and a hallmark three-dimensional motif. This striking multidimensional signature is conserved among disulfide-containing antimicrobial peptides spanning biological kingdoms, and it transcends motifs previously limited to defined peptide subclasses. Experimental data validating this model enabled the identification of previously unrecognized antimicrobial activity in peptides of known identity. The multidimensional signature model provides a unifying structural theme in broad classes of antimicrobial peptides, will facilitate discovery of antimicrobial peptides as yet unknown, and offers insights into the evolution of molecular determinants in these and related host defense effector molecules.

Amino Acid Sequence↗
PubMed2005

Sequence signatures and the probabilistic identification of proteins in the Myc-Max-Mad network.

Accurate identification of specific groups of proteins by their amino acid sequence is an important goal in genome research. Here we combine information theory with fuzzy logic search procedures to identify sequence signatures or predictive motifs for members of the Myc-Max-Mad transcription factor network. Myc is a well known oncoprotein, and this family is involved in cell proliferation, apoptosis, and differentiation. We describe a small set of amino acid sites from the N-terminal portion of the basic helix-loop-helix (bHLH) domain that provide very accurate sequence signatures for the Myc-Max-Mad transcription factor network and three of its member proteins. A predictive motif involving 28 contiguous bHLH sequence elements found 337 network proteins in the GenBank NR database with no mismatches or misidentifications. This motif also identifies at least one previously unknown fungal protein with strong affinity to the Myc-Max-Mad network. Another motif found 96% of known Myc protein sequences with only a single mismatch, including sequences from genomes previously not thought to contain Myc proteins. The predictive motif for Myc is very similar to the ancestral sequence for the Myc group estimated from phylogenetic analyses. Based on available crystal structure studies, this motif is discussed in terms of its functional consequences. Our results provide insight into evolutionary diversification of DNA binding and dimerization in a well characterized family of regulatory proteins and provide a method of identifying signature motifs in protein families.

Amino Acid Sequence↗
PubMed2006

Hereditary family signature of facial expression.

Although facial expressions of emotion are universal, individual differences create a facial expression "signature" for each person; but, is there a unique family facial expression signature? Only a few family studies on the heredity of facial expressions have been performed, none of which compared the gestalt of movements in various emotional states; they compared only a few movements in one or two emotional states. No studies, to our knowledge, have compared movements of congenitally blind subjects with their relatives to our knowledge. Using two types of analyses, we show a correlation between movements of congenitally blind subjects with those of their relatives in think-concentrate, sadness, anger, disgust, joy, and surprise and provide evidence for a unique family facial expression signature. In the analysis "in-out family test," a particular movement was compared each time across subjects. Results show that the frequency of occurrence of a movement of a congenitally blind subject in his family is significantly higher than that outside of his family in think-concentrate, sadness, and anger. In the analysis "the classification test," in which congenitally blind subjects were classified to their families according to the gestalt of movements, results show 80% correct classification over the entire interview and 75% in anger. Analysis of the movements' frequencies in anger revealed a correlation between the movements' frequencies of congenitally blind individuals and those of their relatives. This study anticipates discovering genes that influence facial expressions, understanding their evolutionary significance, and elucidating repair mechanisms for syndromes lacking facial expression, such as autism.

Blindness↗