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At least 19 recordsLinked to original sources
PubMed2026

Machine learning-enabled multi-omics discovery of prognostic biomarkers and signaling targets in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains difficult to subtype using single omics layers. We conducted an exploratory investigation integrating reverse-phase protein array (RPPA) and DNA methylation data from the cancer genome atlas (TCGA)- pancreatic adenocarcinoma (PAAD) to assess the feasibility of multi-omics subtyping, alongside a supervised machine learning analysis of a small gene expression omnibus (GEO) transcriptomic cohort (n = 26) to identify candidate diagnostic genes. RPPA-based K-means clustering suggested a weak, possible two-subtype structure (silhouette ≈ 0.16) that remained unassociated with overall survival (log-rank p = 0.113) and lacked independent prognostic value. An independently performed similarity network fusion (SNF) analysis integrating RPPA and methylation data showed low concordance with RPPA-derived subtypes (Adjusted Rand Index (ARI) = 0.014), indicating limited convergence between molecular modalities. Supervised machine learning analysis of the GEO cohort using a fully nested leave-one-out cross-validation pipeline achieved a mean (area under the curve) AUC of 0.896 across four classifiers and identified four-fold-stable candidate genes (ESCO2, COL17A1, BCL2L14, and SOWAHB). However, this gene panel demonstrated limited external validity across two independent PDAC cohorts (log-rank p = 0.438 for both GSE62452 and GSE28735), indicating limited generalizability despite robust internal performance. Collectively, these findings provide limited evidence for a robust, prognostically significant multi-omics subtype or a validated diagnostic gene signature; instead, this study serves as a hypothesis-generating resource and highlights the importance of rigorous cross-validation and independent external validation in small-sample transcriptomic biomarker discovery.

Humans↗
PubMed2026

A nonlinear multi-omics data integration and classification model based on pathway self-attention and graph convolutional networks.

The abundance of omics data has significantly advanced the development of multi-omics data integration techniques. Non-linear embedding approaches for data integration have gradually become the mainstream in multi-omics research, as these approaches can substantially improve cancer analysis by enhancing the quality of the embeddings. However, current multi-omics data integration methods are typically confined to omics measurements, neglecting domain-specific prior knowledge encompassing biological pathways. In this study, we proposed a multi-omics integrated classification model, PathTransGCN, based on pathway self-attention and graph convolutional networks (GCN). The model integrated biological pathway information into multi-omics data analysis with the aim of enhancing the accuracy of cancer classification. Multi-omics data for breast cancer (BRCA), non-small cell lung cancer (NSCLC), and low-grade glioma (LGG) were obtained from The Cancer Genome Atlas (TCGA) and UCSC Xena databases. These data included gene mutations, DNA methylation, copy number variations, and gene expression, and were used to assess the model's generalizability across different cancers. First, PathTransGCN employed a pathway self-attention module to learn latent representations of samples across different pathways, thereby obtaining multi-omics integration vectors. Concurrently, a patient similarity network (PSN) was constructed using the similarity network fusion (SNF) approach. Second, the integrated vectors and the PSN were jointly fed into a GCN for end-to-end training, enabling precise classification of cancer subtypes. Through multi-omics data analysis of the BRCA dataset, PathTransGCN outperformed several popular algorithms (such as MoGCN and DeePathNet) in the five-class classification of cancer subtypes, achieving an accuracy rate of 87.6% and an F1 score of 86.4%. Moreover, the model demonstrated robust generalization capabilities across both NSCLC and LGG datasets, while effectively identifying key disease-associated biomarkers at the pathway level. Experimental results demonstrate that PathTransGCN exhibits outstanding performance in integrating omics data and delivering interpretable classification outcomes, presenting significant potential for clinical applications.

Humans↗
PubMed2025

miss-SNF: a multimodal patient similarity network integration approach to handle completely missing data sources.

MOTIVATION: Precision medicine leverages patient-specific multimodal data to improve prevention, diagnosis, prognosis, and treatment of diseases. Advancing precision medicine requires the non-trivial integration of complex, heterogeneous, and potentially high-dimensional data sources, such as multi-omics and clinical data. In the literature, several approaches have been proposed to manage missing data, but are usually limited to the recovery of subsets of features for a subset of patients. A largely overlooked problem is the integration of multiple sources of data when one or more of them are completely missing for a subset of patients, a relatively common condition in clinical practice. RESULTS: We propose miss-Similarity Network Fusion (miss-SNF), a novel general-purpose data integration approach designed to manage completely missing data in the context of patient similarity networks. miss-SNF integrates incomplete unimodal patient similarity networks by leveraging a non-linear message-passing strategy borrowed from the SNF algorithm. miss-SNF is able to recover missing patient similarities and is "task agnostic", in the sense that can integrate partial data for both unsupervised and supervised prediction tasks. Experimental analyses on nine cancer datasets from The Cancer Genome Atlas (TCGA) demonstrate that miss-SNF achieves state-of-the-art results in recovering similarities and in identifying patients subgroups enriched in clinically relevant variables and having differential survival. Moreover, amputation experiments show that miss-SNF supervised prediction of cancer clinical outcomes and Alzheimer's disease diagnosis with completely missing data achieves results comparable to those obtained when all the data are available. AVAILABILITY AND IMPLEMENTATION: miss-SNF code, implemented in R, is available at https://github.com/AnacletoLAB/missSNF.

Humans↗
PubMed1989

Organization of oligodendroglial membrane sheets: II. Galactocerebroside:antibody interactions signal changes in cytoskeleton and myelin basic protein.

Antibodies to galactocerebroside (GalC) cause patching of this surface glycolipid over internal domains of myelin basic protein (MBP), which are demarcated by a network of microtubules. The patching occurs whether or not second antibody is present, but the process is accelerated by the presence of second antibody. GalC patching results in disruption of microtubules in the lacy networks in oligodendroglial membrane sheets and in the eventual fusion of MBP domains, similar to the effects of colchicine (Dyer and Benjamins, 1989). Antibodies to GalC also disrupt F-actin in the lacy networks. Since colchicine does not alter the distribution of F-actin, anti-GalC is causing F-actin redistribution by a mechanism other than microtubule depolymerization. Extended exposure to anti-GalC results in coalescence of surface GalC patches concomitant with fusion of internal MBP domains. When anti-GalC is applied to induce GalC patching in cells previously treated with cytoskeletal inhibitors, patching is altered. After colchicine treatment, GalC surface staining is granular; i.e., patching is totally disorganized. Following cytochalasin B treatment, most membrane sheets display a few very large patches rather than the normal multiple, small patches. These GalC surface patterns are similar to the MBP distributions following the respective drug treatments (Dyer and Benjamins, 1989). Thus, the pattern of GalC distribution in the presence of antibody always reflects the organization of the underlying MBP domains; in turn, the organization of the MBP domains is determined by the lacy networks of microtubules in the oligodendroglial membrane sheets.

Animals↗
PubMed2002

Clathrin and plant endocytosis.

Endocytosis requires the coordinated interaction of a plethora of cytosolic and membrane proteins. In mammalian cells, clathrin plays a crucial role in this process as a scaffolding protein underlying the invaginating plasma membrane and surrounding the primary endocytic vesicle. Despite great similarities at the morphological level, the cargo of endocytic clathrin-coated vesicles in plant cells remains to be elucidated. Thus, the role of endocytosis in the plant cell is difficult to ascertain. This review will present important discoveries on putative endosomal compartments and on the functions of plasma membrane-derived plant clathrin-coated vesicles, but will also emphasize the striking similarities of the clathrin-, network- and vesicle fusion-machineries between plant and animal cells.

Clathrin↗
PubMed1985

An investigation of the structural changes occurring in a cetostearyl alcohol/cetrimide/water gel after prolonged low temperature (4 degrees C) storage.

Structural changes in a ternary gel prepared using the mixed emulsifier system of cetrimide and cetostearyl alcohol after prolonged low temperature (4 degrees C) storage have been studied using freeze-etch transmission electron microscopy and other techniques. The system changed from an opaque smooth gel of high viscosity, low conductivity and low free water, to a pearlescent milky lotion of low viscosity, high conductivity and high free water. Subsequent equilibration of the thinned system to room temperature (25 degrees C) over 48 h produced an opaque granular gel of similar consistency, but slightly higher conductivity and higher free water than the initial sample. Microscopical examination by both differential interference contrast and freeze-etch electron microscopy showed the system changed from one consisting of a liquid crystalline network localized around cetostearyl alcohol particles, to a system consisting of large waxy plates coexisting with some residual liquid crystalline network. A supportive mechanism for the thinning of the ternary gel at prolonged low temperature storage has been inferred by comparing data with that produced by other workers studying the fusion of phospholipid membranes considered to be morphologically similar to the liquid crystalline network observed in this ternary gel.

Cetrimonium↗
PubMed2006

Identifying metabolic enzymes with multiple types of association evidence.

BACKGROUND: Existing large-scale metabolic models of sequenced organisms commonly include enzymatic functions which can not be attributed to any gene in that organism. Existing computational strategies for identifying such missing genes rely primarily on sequence homology to known enzyme-encoding genes. RESULTS: We present a novel method for identifying genes encoding for a specific metabolic function based on a local structure of metabolic network and multiple types of functional association evidence, including clustering of genes on the chromosome, similarity of phylogenetic profiles, gene expression, protein fusion events and others. Using E. coli and S. cerevisiae metabolic networks, we illustrate predictive ability of each individual type of association evidence and show that significantly better predictions can be obtained based on the combination of all data. In this way our method is able to predict 60% of enzyme-encoding genes of E. coli metabolism within the top 10 (out of 3551) candidates for their enzymatic function, and as a top candidate within 43% of the cases. CONCLUSION: We illustrate that a combination of genome context and other functional association evidence is effective in predicting genes encoding metabolic enzymes. Our approach does not rely on direct sequence homology to known enzyme-encoding genes, and can be used in conjunction with traditional homology-based metabolic reconstruction methods. The method can also be used to target orphan metabolic activities.

Energy Metabolism↗
PubMed2006

Network metrics reveal differences in social organization between two fission-fusion species, Grevy's zebra and onager.

For species in which group membership frequently changes, it has been a challenge to characterize variation in individual interactions and social structure. Quantifying this variation is necessary to test hypotheses about ecological determinants of social patterns and to make predictions about how group dynamics affect the development of cooperative relationships and transmission processes. Network models have recently become popular for analyzing individual contacts within a population context. We use network metrics to compare populations of Grevy's zebra (Equus grevyi) and onagers (Equus hemionus khur). These closely related equids, previously described as having the same social system, inhabit environments differing in the distribution of food, water, and predators. Grevy's zebra and onagers are one example of many sets of coarsely similar fission-fusion species and populations, observed elsewhere in other ungulates, primates, and cetaceans. Our analysis of the population association networks reveals contrasts consistent with their distinctive environments. Grevy's zebra individuals are more selective in their association choices. Grevy's zebra form stable cliques, while onager associations are more fluid. We find evidence that females associate assortatively by reproductive state in Grevy's zebra but not in onagers. The current approach demonstrates the utility of network metrics for identifying fine-grained variation among individuals and populations in association patterns. From our analysis, we can make testable predictions about behavioral mechanisms underlying social structure and its effects on transmission processes.

Analysis of Variance↗
PubMed2004

Comprehensive de novo structure prediction in a systems-biology context for the archaea Halobacterium sp. NRC-1.

BACKGROUND: Large fractions of all fully sequenced genomes code for proteins of unknown function. Annotating these proteins of unknown function remains a critical bottleneck for systems biology and is crucial to understanding the biological relevance of genome-wide changes in mRNA and protein expression, protein-protein and protein-DNA interactions. The work reported here demonstrates that de novo structure prediction is now a viable option for providing general function information for many proteins of unknown function. RESULTS: We have used Rosetta de novo structure prediction to predict three-dimensional structures for 1,185 proteins and protein domains (<150 residues in length) found in Halobacterium NRC-1, a widely studied halophilic archaeon. Predicted structures were searched against the Protein Data Bank to identify fold similarities and extrapolate putative functions. They were analyzed in the context of a predicted association network composed of several sources of functional associations such as: predicted protein interactions, predicted operons, phylogenetic profile similarity and domain fusion. To illustrate this approach, we highlight three cases where our combined procedure has provided novel insights into our understanding of chemotaxis, possible prophage remnants in Halobacterium NRC-1 and archaeal transcriptional regulators. CONCLUSIONS: Simultaneous analysis of the association network, coordinated mRNA level changes in microarray experiments and genome-wide structure prediction has allowed us to glean significant biological insights into the roles of several Halobacterium NRC-1 proteins of previously unknown function, and significantly reduce the number of proteins encoded in the genome of this haloarchaeon for which no annotation is available.

Archaeal Proteins↗
PubMed2001

A what-and-where fusion neural network for recognition and tracking of multiple radar emitters.

A neural network recognition and tracking system is proposed for classification of radar pulses in autonomous Electronic Support Measure systems. Radar type information is considered with position-specific information from active emitters in a scene. Type-specific parameters of the input pulse stream are fed to a neural network classifier trained on samples of data collected in the field. Meanwhile, a clustering algorithm is used to separate pulses from different emitters according to position-specific parameters of the input pulse stream. Classifier responses corresponding to different emitters are separated into tracks, or trajectories, one per active emitter, allowing for more accurate identification of radar types based on multiple views of emitter data along each emitter trajectory. Such a What-and-Where fusion strategy is motivated by a similar subdivision of labor in the brain. The fuzzy ARTMAP neural network is used to classify streams of pulses according to radar type using their functional parameters. Simulation results obtained with a radar pulse data set indicate that fuzzy ARTMAP compares favorably to several other approaches when performance is measured in terms of accuracy and computational complexity. Incorporation into fuzzy ARTMAP of negative match tracking (from ARTMAP-IC) facilitated convergence during training with this data set. Other modifications improved classification of data that include missing input pattern components and missing training classes. Fuzzy ARTMAP was combined with a bank of Kalman filters to group pulses transmitted from different emitters based on their position-specific parameters, and with a module to accumulate evidence from fuzzy ARTMAP responses corresponding to the track defined for each emitter. Simulation results demonstrate that the system provides a high level of performance on complex, incomplete and overlapping radar data.

Algorithms↗
PubMed2003

Registration and fusion of retinal images--an evaluation study.

We present the results of a study on the application of registration and pixel-level fusion techniques to retinal images. The images are of different modalities (color, fluorescein angiogram), different resolutions, and taken at different times (from a few minutes during an angiography examination to several years between two examinations). We propose a new registration method based on global point mapping with blood vessel bifurcations as control points and a search for control point matches that uses local structural information of the retinal network. Three transformation types (similarity, affine, and second-order polynomial) are evaluated on each image pair. Fourteen pixel-level fusion techniques have been tested and classified according to their qualitative and quantitative performance. Four quantitative fusion performance criteria are used to evaluate the gain obtained with the grayscale fusion.

Algorithms↗
PubMed1997

Functional expression of olfactory-adrenergic receptor chimeras and intracellular retention of heterologously expressed olfactory receptors.

Replacing the G-protein-coupling domains of the beta 2-adrenergic receptor with homologous domains of putative olfactory receptors produced chimeric receptors which were able to stimulate pigment dispersion in Xenopus melanophores, a G-protein-mediated pathway. A multiple replacement chimera containing the second, third and C-terminal cytoplasmic domains of receptor OR5 elevated cyclic adenosine 3':5'-monophosphate (cAMP) and suppressed production of inositol phosphates. Co-expression of G alpha olf did not alter the strength of response of this chimera. A novel rat olfactory receptor cDNA (U131) was isolated and sequenced. Expression of U131 and OR5 constructs containing an N-terminal epitope-tag or C-terminal fusion to green fluorescent protein occurred in an intracellular network but not in the plasma membrane of heterologous cells. Similarly treated beta 2-adrenergic receptors were functional and were observed in the plasma membrane and the intracellular network. These results demonstrate that the putative cytoplasmic domains of olfactory receptors are capable of functional interaction with heterologous G-proteins of the G alpha s subtype. Instead, the absence of these receptors from the plasma membrane of heterologous cells appears to explain our inability to determine if odorants can activate the olfactory receptor clones. We hypothesize that the olfactory receptors have requirements for maturation and targeting to the plasma membrane that are different from most other G-protein-coupled receptors.

Adenylyl Cyclases↗
PubMed2005

Characterization of the TGN exit signal of the human mannose 6-phosphate uncovering enzyme.

The human mannose 6-phosphate uncovering enzyme participates in the uncovering of the mannose 6-phosphate recognition tag on lysosomal enzymes, a process that facilitates recognition of those enzymes by mannose 6-phosphate receptors to ensure delivery to lysosomes. Uncovering enzyme has been identified on the trans-Golgi network at steady state. It has been shown to traffic to the plasma membrane from where it is rapidly internalized via endosomal structures, the process being mediated by a tyrosine-based internalization motif, Y488HPL, in its cytoplasmic tail. Using immunogold electron microscopy a GFP-uncovering enzyme fusion construct was found to be colocalized with the cation-dependent mannose 6-phosphate receptor in regions of the trans-Golgi network, suggesting that uncovering enzyme might follow a similar pathway of exit from the trans-Golgi network as that of the cation-dependent mannose 6-phosphate receptor. In this study, we identified the signal sequence in the cytoplasmic tail of uncovering enzyme responsible for its exit from the trans-Golgi network. Using GFP fusion constructs of the transmembrane and cytoplasmic domains of uncovering enzyme, we could show, by automated analysis of confocal immunofluorescence images, that residues Q492EMN in the cytoplasmic tail of uncovering enzyme are involved in its exit from the trans-Golgi network. Detailed characterization of the exit signal revealed that residue Q492 is the most important to the exit function while M494 and N495 also contribute. The cytoplasmic tail of the uncovering enzyme does not possess any of the known canonical signal sequences for interaction with Golgi-associated gamma ear-containing adaptor proteins. The identification of a trans-Golgi network exit signal in its cytoplasmic tail elucidates the trafficking pathway of uncovering enzyme, a crucial player in the process of lysosomal biogenesis.

Gene Expression Regulation, Enzymologic↗
PubMed2003

Autocrine growth factor signaling by insulin-like growth factor-II mediates MyoD-stimulated myocyte maturation.

Skeletal muscle differentiation, maturation, and regeneration are regulated by interactions between intrinsic genetic programs controlled by myogenic transcription factors, including members of the MyoD and MEF2 families, and environmental cues mediated by hormones and growth factors. Insulin-like growth factors (IGFs) also play key roles in muscle development, and in the maintenance and repair of mature muscle, but their mechanisms of interaction with other muscle regulatory networks remain undefined. To evaluate the potential interplay between MyoD and IGF signaling pathways, we have studied muscle differentiation in C3H 10T1/2 fibroblasts acutely converted to myoblasts by quantitative infection with a recombinant adenovirus encoding mouse MyoD. In these cells, IGF-II gene and protein expression are induced as early events in differentiation, and the IGF-I receptor and downstream signaling molecules, including Akt, are rapidly activated. Interference with IGF-II production by a tetracycline-inhibited adenovirus expressing an IGF-II cDNA in the antisense orientation reversibly inhibited both production of muscle-specific structural proteins and myocyte fusion to form multinucleated myotubes. Similar results were achieved with a tetracycline-inhibited adenovirus expressing dominant-negative Akt. Our observations identify a robust autocrine amplification network in which MyoD enhances the later steps in muscle differentiation by induction of a locally acting growth factor.

Adenoviridae↗
PubMed1999

[Role of vesicle fusion mechanism and cell adhesion molecules in growth cone elongation and synaptogenesis].

Growth cones have been regarded to play central roles in forming complex neural network through target tract selection and target cell recognition. We have found that the vesicle fusion molecular system in growth cones is similar to that in synapses. The cleavage of SNAP25, a protein involved in neurotransmitter release in synapse, resulted in inhibition of neurite elongation. Inversely the overexpression of VAMP2/synaptobrevin, another protein involved in neurotransmitter release in synapse, in PC12 cells resulted in promotion of neurite elongation. We have recently isolated a novel components at cadherin-based cell-cell adherens junctions, named neurabin I, neurabin II, and afadin. Neurabin I is specifically expressed in nervous tissues and localized at synapses. Afadin is uviquitously expressed in various tissues and highly concentrated at cell-cell adherens junctions of small intestine epithelial cells, cardiac muscles, synapses. We have identified the transmembrane protein binding to afadin, and named it nectin, which belongs to immunoglobulin superfamily. Nectin, afadin, neurabin I, and neurabin II may be key molecules to find out various unknown guidance cues which can induce regenerating growth cones to repair the functional neuronal connections in central nervous system after injury.

Animals↗
PubMed2005

Functional divergence of Kaposi's sarcoma-associated herpesvirus and related gamma-2 herpesvirus thymidine kinases: novel cytoplasmic phosphoproteins that alter cellular morphology and disrupt adhesion.

The nucleoside kinase encoded by Kaposi's sarcoma-associated herpesvirus (KSHV) is a relatively inefficient enzyme with substrate specificity for thymidine alone, unlike alphaherpesvirus thymidine kinases (TKs). Similar to all gammaherpesvirus TKs, KSHV TK is composed of two distinct domains, a conserved C-terminal kinase and a novel and uncharacterized N terminus. Ectopic expression of KSHV TK in adherent cells induced striking morphological changes and anchorage independence although cells survived, a property shared with the related rhadinovirus TKs of rhesus monkey rhadinovirus and herpesvirus saimiri. To determine whether KSHV TK served alternate functions relevant to the rhadinovirus life cycle and to reveal the contribution of the N terminus, an enhanced green fluorescent protein-tagged fusion protein and serial mutants were generated for investigation of intracellular localization and cell biology. Analysis of truncation mutants showed that a proline-rich region located within the N terminus cooperated with the conserved C-terminal kinase to tether KSHV TK to a reticular network in the cytoplasm and to induce morphological change. Fusion of the KSHV N terminus to herpes simplex virus type 1 TK, a nucleus-localized enzyme, similarly resulted in cytoplasmic redistribution of the chimeric protein but did not alter cell shape or adhesion. Unlike other human herpesvirus TKs, KSHV TKs and related rhadinovirus TKs are constitutively tyrosine phosphorylated; a KSHV TK mutant that was hypophosphorylated failed to detach and grow in suspension. Loss of adhesion may enhance terminal differentiation, viral replication, and egress at the cellular level and at the organism level may facilitate detachment and distant migration of KSHV-replicating cells within body fluids--promoting oropharyngeal transmission and perhaps contributing to the multifocal lesions that characterize KS.

Cell Adhesion↗
PubMed1979

Normal and pseudorabies virus infected primary nerve cell cultures in scanning electron microscopy.

Primary cell cultures from the central nervous system of the embryonic rat were inoculated with pseudorabies virus. Their morphological changes were studied by phase contrast microscopy and by scanning as well as by transmission electron microscopy. Uninfected cultures display two distinct cell layers in scanning electron microscopy: a flat continuous monolayer supports a heterogeneous population of individual, presumably neural cells, which emit processes of different number and size. The latter cells form contacts by a dense network of fibres. Infectious virus is propagated in these nerve cell cultures with similar effectivity as in other cultures. The infectoin leads to fusion and death of the cells. By the time the cytopathic effect is visible, nearly all cells, including those of neuronal and those of nonneuronal appearance, are studded with ample amounts of virus-sized particles. The particles represent viruses as demonstrated by transmission electron microscopy or by treatment with a hyperimmune serum directed against pseudorabies virus structural components. Hyperimmune serum leads to clustering of the particles at the cell surface. The amount of virus particles per surface unit was about 10 times higher on neural cells as compared to primary rabbit kidney cells. The concentration of infectious particles in the supernatant, however was approximately the same. The system described appears to be useful for the study of acute virus effects on neural tissue under strictly controlled conditions.

Animals↗
PubMed2000

In vitro formation of the endoplasmic reticulum occurs independently of microtubules by a controlled fusion reaction.

We have established an in vitro system for the formation of the endoplasmic reticulum (ER). Starting from small membrane vesicles prepared from Xenopus laevis eggs, an elaborate network of membrane tubules is formed in the presence of cytosol. In the absence of cytosol, the vesicles only fuse to form large spheres. Network formation requires a ubiquitous cytosolic protein and nucleoside triphosphates, is sensitive to N-ethylmaleimide and high cytosolic Ca(2+) concentrations, and proceeds via an intermediate stage in which vesicles appear to be clustered. Microtubules are not required for membrane tubule and network formation. Formation of the ER network shares significant similarities with formation of the nuclear envelope. Our results suggest that the ER network forms in a process in which cytosolic factors modify and regulate a basic reaction of membrane vesicle fusion.

Actins↗