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PubMed2005

Proteomics strategies for protein identification.

The information from genome sequencing provides new approaches for systems-wide understanding of protein networks and cellular function. DNA microarray technologies have advanced to the point where nearly complete monitoring of gene expression is feasible in several organisms. An equally important goal is to comprehensive survey cellular proteomes and profile protein changes under different cellular states. This presents a complex analytical problem, due to the chemical variability between proteins and peptides. Here, we discuss strategies to improve accuracy and sensitivity of peptide identification, distinguish represented protein isoforms, and quantify relative changes in protein abundance.

Computational Biology↗

PubMed2004

Molecular fingerprinting of dairy microbial ecosystems by use of temporal temperature and denaturing gradient gel electrophoresis.

Numerous microorganisms, including bacteria, yeasts, and molds, constitute the complex ecosystem present in milk and fermented dairy products. Our aim was to describe the bacterial ecosystem of various cheeses that differ by production technology and therefore by their bacterial content. For this purpose, we developed a rapid, semisystematic approach based on genetic profiling by temporal temperature gradient electrophoresis (TTGE) for bacteria with low-G+C-content genomes and denaturing gradient gel electrophoresis (DGGE) for those with medium- and high-G+C-content genomes. Bacteria in the unknown ecosystems were assigned an identity by comparison with a comprehensive bacterial reference database of approximately 150 species that included useful dairy microorganisms (lactic acid bacteria), spoilage bacteria (e.g., Pseudomonas and Enterobacteriaceae), and pathogenic bacteria (e.g., Listeria monocytogenes and Staphylococcus aureus). Our analyses provide a high resolution of bacteria comprising the ecosystems of different commercial cheeses and identify species that could not be discerned by conventional methods; at least two species, belonging to the Halomonas and Pseudoalteromonas genera, are identified for the first time in a dairy ecosystem. Our analyses also reveal a surprising difference in ecosystems of the cheese surface versus those of the interior; the aerobic surface bacteria are generally G+C rich and represent diverse species, while the cheese interior comprises fewer species that are generally low in G+C content. TTGE and DGGE have proven here to be powerful methods to rapidly identify a broad range of bacterial species within dairy products.

Animals↗

PubMed2006

Global gene expression profiling of dimethylnitrosamine-induced liver fibrosis: from pathological and biochemical data to microarray analysis.

The development of hepatocellular carcinoma (HCC) is generally preceded by cirrhosis, which occurs at the end stage of fibrosis. This is a common and potentially lethal problem of chronic liver disease in Asia. The development of microarrays permits us to monitor transcriptomes on a genome-wide scale; this has dramatically speeded up a comprehensive understanding of the disease process. Here we used dimethylnitrosamine (DMN), a nongenotoxic hepatotoxin, to induce rat necroinflammatory and hepatic fibrosis. During the 6-week time course, histopathological, biochemical, and quantitative RT-PCR analyses confirmed the incidence of necroinflammatory and hepatic fibrosis in this established rat model system. Using the Affymetrix microarray chip, 256 differentially expressed genes were identified from the liver injury samples. Hierarchical clustering of gene expression using a gene ontology database allowed the identification of several stage-specific characters and functionally related clusters that encode proteins related to metabolism, cell growth/maintenance, and response to external challenge. Among these genes, we classified 44 potential necroinflammatory-related genes and 62 potential fibrosis-related markers or drug targets based on histopathological scores. We also compared the results with other data on well-known markers and various other microarray datasets that are available. In conclusion, we believe that the molecular picture of necroinflammatory and hepatic fibrosis from this study may provide novel biological insights into the development of early liver damage molecular classifiers than can be used for basic research and in clinical applications. A public accessible website is available at http://LiverFibrosis.nchc.org.tw:8080/LF.

Animals↗

PubMed2004

Construction of representative transcript and protein sets of human, mouse, and rat as a platform for their transcriptome and proteome analysis.

The number of mammalian transcripts identified by full-length cDNA projects and genome sequencing projects is increasing remarkably. Clustering them into a strictly nonredundant and comprehensive set provides a platform for functional analysis of the transcriptome and proteome, but the quality of the clustering and predictive usefulness have previously required manual curation to identify truncated transcripts and inappropriate clustering of closely related sequences. A Representative Transcript and Protein Sets (RTPS) pipeline was previously designed to identify the nonredundant and comprehensive set of mouse transcripts based on clustering of a large mouse full-length cDNA set (FANTOM2). Here we propose an alternative method that is more robust, requires less manual curation, and is applicable to other organisms in addition to mouse. RTPSs of human, mouse, and rat have been produced by this method and used for validation. Their comprehensiveness and quality are discussed by comparison with other clustering approaches. The RTPSs are available at .

Animals↗

PubMed2003

Towards deciphering phloem: a transcriptome analysis of the phloem of Apium graveolens.

Events occurring in the phloem tissue are key to understanding a wide range of developmental and physiological processes in vascular plants. While a considerable amount of molecular information on phloem proteins has emerged in the past decade, a unified picture of the molecular mechanisms involved in phloem differentiation and function is still lacking. New models to increase our understanding of this complex tissue can be created by the development of global approaches such as genomic analysis. In order to obtain a comprehensive overview of the molecular biology of the phloem tissue, we developed a genomic approach using Apium graveolens as a model. cDNA libraries were constructed from mRNAs extracted from isolated phloem of petioles. Expression data obtained from the analysis of 989 expressed sequence tags (ESTs) and the transcript profile deduced from a cDNA macroarray of 1326 clones were combined to identify genes showing distinct expression patterns in the vascular tissues. Comparisons of expression profiles obtained from the phloem, xylem and storage parenchyma tissues uncovered tissue-specific differential expression patterns for given sets of genes. The major classes of mRNAs predominantly found in the phloem encode proteins related to phloem structure, metal homeostasis or distribution, stress responses and degradation or turnover of proteins. Of great interest for future studies are the genes we found to be specifically expressed in the phloem but for which the function is still unknown, and also those genes described in previous reports to be up or downregulated by specific interactions. From a broader prospective, our results also clearly demonstrate that cDNA macroarray technology can be used to identify the key genes involved in various physiological and developmental processes in the phloem.

Apium↗

PubMed2026

Genomic Profiling of Epidermal Growth Factor Receptor Mutation-Positive Non-Small Cell Lung Cancer after Progression on First-line Osimertinib: Phase II ORCHARD Study.

PURPOSE: Osimertinib is the standard of care for first-line treatment for epidermal growth factor receptor-mutated (EGFRm) non-small cell lung cancer (NSCLC). Understanding the tumor molecular profile of patients following progression on osimertinib could help inform optimal second-line treatment. PATIENTS AND METHODS: ORCHARD (NCT03944772), a phase II biomarker-directed study, enrolled patients with EGFRm NSCLC who progressed on first-line osimertinib to receive treatment based on their tumor molecular profile after progression. The study comprised three groups into which patients were allocated based on the molecular profile of their tumor, determined via next-generation sequencing (NGS) of a tumor biopsy. We report results from a prespecified, exploratory analysis of baseline tumor tissue and plasma samples to evaluate mechanisms of resistance to first-line osimertinib identified by tissue and plasma NGS. Agreement between tissue and plasma NGS data was also assessed. RESULTS: This study provided a comprehensive dataset exploring tissue (n = 400) and plasma (n = 191) genomics, enabling characterization of the histogenomic landscape after first-line osimertinib treatment. TP53 and MDM2/4 alterations were mutually exclusive and occurred in 86% of tumors. When combining tissue and plasma genomics, resistance alterations were detected in 87% of samples, with multiple resistance alterations in 46%. Alterations in the PI3K pathway, SOX2, and MYC were frequently detected in histologically transformed tumors. Additionally, differential patterns of co-occurring EGFR mutations in tumors with L858R versus exon 19 deletion were observed. CONCLUSIONS: This comprehensive analysis highlights potential heterogeneous resistance to first-line osimertinib treatment, providing a rationale for combining treatments with broad activity to improve patient outcomes. See related commentary by Gupta et al., p. 3718.

Humans↗

PubMed2004

Metabolomics: an emerging post-genomic tool for nutrition.

The post-genomic era has been driven by the development of technologies that allow the function of cells and whole organisms to be explored at the molecular level. Metabolomics is concerned with the measurement of global sets of low-molecular-weight metabolites. Metabolite profiles of body fluids or tissues can be regarded as important indicators of physiological or pathological states. Such profiles may provide a more comprehensive view of cellular control mechanisms in man and animals, and raise the possibility of identifying surrogate markers of disease. Metabolomic approaches use analytical techniques such as NMR spectroscopy and MS to measure populations of low-molecular-weight metabolites in biological samples. Advanced statistical and bioinformatic tools are then employed to maximise the recovery of information and interpret the large datasets that are generated. Metabolomics has already been used to study toxicological mechanisms and disease processes and offers enormous potential as a means of investigating the complex relationship between nutrition and metabolism. Examples include the metabolism of dietary substrates, drug-induced disturbances of lipid metabolites in type 2 diabetes mellitus and the therapeutic effects of vitamin supplementation in the treatment of chronic metabolic disorders.

Biomarkers↗

PubMed2026

Genome-Wide Identification and Colchicine-Responsive Expression Profiling of the Tubulins (TUA and TUB) Gene Family in Phoebe bournei.

Phoebe bournei is an economically and ecologically important woody species native to China. As a core component of colchicine-triggered polyploid breeding, the tubulin genes (TUA and TUB) have been identified and functionally analyzed in many plants, but not yet in P. bournei. Here, tubulin family members in P. bournei were identified through sequence alignment and subsequently characterized using comprehensive bioinformatic analyses. In particular, a total of six PbTUA and ten PbTUB members were identified and grouped into two and five subfamilies, respectively, according to phylogenetic relationships. Most tubulin proteins were small (414-522 aa) with predicted stability. Furthermore, 36 collinear gene pairs were identified, suggesting a possible contribution to the evolutionary expansion of this family. For different tissues, the expression levels of most tubulin genes were generally lower in leaves but higher in roots. Besides, treatment with 1.0% colchicine inhibited the expression of all 15 tubulin genes except PbTUB6. These results provide preliminary insights into tubulin genes associated with polyploid induction and supply candidate genes for future functional studies toward polyploid germplasm creation of P. bournei.

Phoebe bournei↗

PubMed2025

HallmarkGraph: a cancer hallmark informed graph neural network for classifying hierarchical tumor subtypes.

MOTIVATION: Accurate tumor subtype diagnosis is crucial for precision oncology, yet current methodologies face significant challenges. These include balancing model accuracy with interpretability and the high costs of generating multi-omics data in clinical settings. Moreover, there is a lack of validated models capable of classifying hierarchical tumor subtypes across a comprehensive pan-cancer cohort. RESULTS: We present a graph neural network, HallmarkGraph, the first biologically informed model developed to classify hierarchical tumor subtypes in human cancer. Inspired by cancer hallmarks, the model's architecture integrates transcriptome profiles and gene regulatory interactions to perform multi-label classification. We evaluate the model on a comprehensive pan-cancer cohort comprising 11 476 samples from 26 primary cancers with 405 subtypes up to eight levels. The model demonstrates exceptional performance, achieving 5-fold cross-validation accuracy between 85% and 99% for tumor subtypes labeled with increasing details of genomic information. It also shows good generalizability on a validation dataset of 887 samples, assessed using three metrics that consider tumor subtypes at individual, combined, and sample levels. Benchmarking and ablation experiments show that hallmark-based embeddings slightly influence model performance, while the integrated multilayer perceptron plays a significant role in determining classifier accuracy. Additionally, we use the SHAP method to link cancer hallmarks with genes, identifying key features that influence model decisions. Our findings present a biologically informed machine learning framework capable of tracking tumor transcriptomic trajectories and distinguishing inter- and intra-tumor heterogeneity in pan-cancer. This approach holds promise for enhancing cancer diagnostics. AVAILABILITY AND IMPLEMENTATION: HallmarkGraph is accessible at https://github.com/laixn/HallmarkGraph.

Humans↗

PubMed2006

In silico identification and comparative analysis of differentially expressed genes in human and mouse tissues.

BACKGROUND: Screening for differentially expressed genes on the genomic scale and comparative analysis of the expression profiles of orthologous genes between species to study gene function and regulation are becoming increasingly feasible. Expressed sequence tags (ESTs) are an excellent source of data for such studies using bioinformatic approaches because of the rich libraries and tremendous amount of data now available in the public domain. However, any large-scale EST-based bioinformatics analysis must deal with the heterogeneous, and often ambiguous, tissue and organ terms used to describe EST libraries. RESULTS: To deal with the issue of tissue source, in this work, we carefully screened and organized more than 8 million human and mouse ESTs into 157 human and 108 mouse tissue/organ categories, to which we applied an established statistic test using different thresholds of the p value to identify genes differentially expressed in different tissues. Further analysis of the tissue distribution and level of expression of human and mouse orthologous genes showed that tissue-specific orthologs tended to have more similar expression patterns than those lacking significant tissue specificity. On the other hand, a number of orthologs were found to have significant disparity in their expression profiles, hinting at novel functions, divergent regulation, or new ortholog relationships. CONCLUSION: Comprehensive statistics on the tissue-specific expression of human and mouse genes were obtained in this very large-scale, EST-based analysis. These statistical results have been organized into a database, freely accessible at our website http://gln.ibms.sinica.edu.tw/product/HMDEG/EST/index.php, for easy searching of human and mouse tissue-specific genes and for investigating gene expression profiles in the context of comparative genomics. Comparative analysis showed that, although highly tissue-specific genes tend to exhibit similar expression profiles in human and mouse, there are significant exceptions, indicating that orthologous genes, while sharing basic genomic properties, could result in distinct phenotypes.

Animals↗

PubMed2005

Application of microarray-based technology to neuroblastoma.

In the past decade, microarray technology has become a major tool for high-throughput comprehensive analysis of gene expression, genotyping and re-sequencing applications. High-throughput microarrays are used for expression profiling analyses with the aims of gene or pathway discovery, tumor subclassification or relapse risk assessment. The introduction of microarray CGH provides a powerful tool to precisely detect and quantify genomic aberrations and map these directly onto the human genome. This review summarizes the current status of the application of microarray technology to neuroblastoma research.

Humans↗

PubMed2005

Metabolomics in practice: emerging knowledge to guide future dietetic advice toward individualized health.

The profession of dietetics can take an increasingly prominent role in managing health and patient care as clinicians gain access to three new resources: detailed information about the metabolic status of healthy individual clients, metabolic knowledge about the relationships between metabolite abundances and health, and bioinformatics tools that link clients' metabolism to their present and future health status. The current use of single biomarkers as indicators of disease will be replaced by comprehensive profiling of individual metabolites linked to an understanding of health and human metabolism--the emerging science now known as metabolomics. Industrial and academic initiatives are currently developing the analytical and bioinformatic technologies needed to assemble the quantitative reference databases of metabolites as the metabolic analog of the human genome. With these in place, dietetics professionals will be able to assess both the current health status of individuals and predict their health trajectories. Another important role for dietetics professionals will be to assist in the development of the tools and their application in predicting how an individual's specific metabolic pattern can be changed by diet, drugs, and lifestyle, with the goal of improving health and preventing the development of chronic diseases.

Biomarkers↗

PubMed2026

An Integrative Morphological and Genomic Analysis With a Refined Fluorescence In Situ Hybridization (FISH) Threshold and Novel Kinase Fusions in a Large Asian Cohort of Spitzoid Neoplasms.

Differentiating atypical Spitz tumors (ASTs) from true Spitz melanomas (SMs) and conventional melanomas with spitzoid features (MSFs) remains a formidable diagnostic challenge. Because current molecular epidemiological data are overwhelmingly derived from Caucasian cohorts, the genomic landscape of Asian populations remains largely unexplored. To elucidate the molecular progression landscape and refine the diagnostic criteria, we performed a comprehensive multimodal analysis-integrating histomorphology, immunohistochemistry, multiprobe fluorescence in situ hybridization (FISH), and targeted RNA/DNA-based next-generation sequencing (NGS)-on a cohort of 140 spitzoid neoplasms. This cohort, comprising 126 ASTs, 8 SMs, and 6 MSFs, represents the largest Asian cohort to date. Malignant phenotype strongly correlated with lesional asymmetry, deep atypical mitoses, a sheet-like growth pattern, diffuse preferentially expressed antigen of melanoma positivity, and significant loss of p16 expression (64.3% in SM/MSF vs 9.5% in ASTs; P < .0001). Building upon the established melanoma FISH criteria, we optimized a prognostic threshold of ≥2 FISH abnormalities specifically tailored for spitzoid neoplasms. We demonstrated that isolated single chromosomal aberrations (particularly MYB loss) are relatively stable events that are frequent in indolent ASTs, whereas our refined ≥2 threshold yielded 100% sensitivity and 92.5% specificity for predicting regional lymph node metastasis/local recurrence. Molecularly, NGS identified mutually exclusive initiating driver alterations (comprising kinase fusions and HRAS mutations) in 89.9% of true Spitz neoplasms, a remarkably high prevalence suggesting a distinct genetic background in Asian populations. We also characterized 5 entirely novel kinase fusions (ZNF24::ROS1, PCBP1::ROS1, NUMA1::RET, CBWD1::ALK, and TPR::NTRK1). Furthermore, NGS definitively segregated true Spitz neoplasms from morphological mimics (MSF), which lacked fusions and were driven by canonical genomic alterations of the conventional melanoma pathway. Integrating these genomic landscapes validated a stepwise progression model. Although isolated kinase fusions drove indolent ASTs, malignant SM invariably harbored concurrent pathogenic secondary alterations, demonstrating a profound reliance on CDKN2A/B, TP53, and CDK4 aberrations. Ultimately, we propose an integrated diagnostic algorithm combining morphological evaluation, the refined FISH threshold, and comprehensive NGS profiling, providing a precise, evidence-based framework for pathway classification and clinical management of spitzoid neoplasms.

fluorescence in situ hybridization↗

PubMed2003

RIKEN mouse genome encyclopedia.

We have been working to establish the comprehensive mouse full-length cDNA collection and sequence database to cover as many genes as we can, named Riken mouse genome encyclopedia. Recently we are constructing higher-level annotation (Functional ANnoTation Of Mouse cDNA; FANTOM) not only with homology search based annotation but also with expression data profile, mapping information and protein-protein database. More than 1,000,000 clones prepared from 163 tissues were end-sequenced to classify into 159,789 clusters and 60,770 representative clones were fully sequenced. As a conclusion, the 60,770 sequences contained 33,409 unique. The next generation of life science is clearly based on all of the genome information and resources. Based on our cDNA clones we developed the additional system to explore gene function. We developed cDNA microarray system to print all of these cDNA clones, protein-protein interaction screening system, protein-DNA interaction screening system and so on. The integrated database of all the information is very useful not only for analysis of gene transcriptional network and for the connection of gene to phenotype to facilitate positional candidate approach. In this talk, the prospect of the application of these genome resourced should be discussed. More information is available at the web page: http://genome.gsc.riken.go.jp/.

Animals↗

PubMed2003

Microarrays and clinical dentistry.

BACKGROUND: The Human Genome Project, or HGP, has inspired a great deal of exciting biology recently by enabling the development of new technologies that will be essential for understanding the different types of abnormalities in diseases related to the oral cavity. LITERATURE REVIEWED: The authors review current literature pertaining to the advanced microarray technologies arising from the HGP and how they can contribute to dentistry. This technology has become a standard tool for monitoring activities of genes at both academic and pharmaceutical research institutions. RESULTS: With the availability of the DNA sequences for the entire human genome, attention now is focused on understanding various diseases at the genome level. Deciphering the molecular behavior of genetically encoded proteins is crucial to obtaining a more comprehensive picture of disease processes. Important progress has been made using microarrays, which have been shown to be effective in identifying gene expression patterns and variations that correlate with cellular development, physiology and function. Arrays can be used to classify tissue samples accurately based on molecular profiles and to select candidate genes related to a number of cancers, including oral cancer. This type of oral genetic approach will aid in the understanding of disease progression, thus improving diagnosis and treatment for patients. CLINICAL IMPLICATIONS: Microarrays hold much promise for the analysis of diseases in the oral cavity. As the technology evolves, dentists may see these tools as screening tests for better managing patients' dental care.

Anti-Bacterial Agents↗

PubMed2026

Comprehensive molecular profiling of advanced NSCLC in Greek patients:A prospective HeCOG study.

BACKGROUND: We report for the first time the molecular landscape and outcome associations from the prospective CLIMEDIN trial in Greece. METHODS: Two hundred patients with newly diagnosed advanced NSCLC (March 2022-October 2023) were enrolled and randomized to standard-of-care education versus additional automated, adverse-event-targeted digital interventions. Within this study baseline testing (EGFR, ALK, PD-L1) was performed in all; 165 tumors underwent comprehensive NGS (Oncomine Comprehensive Assay v3). Primary endpoint was improvement in AEs/QoL; secondary endpoints included ORR, PFS and OS. Associations between genomic alterations and outcomes were explored. RESULTS: Median age was 68 years; 75% male; 52% current smokers; adenocarcinoma 68.5%. Most received chemo-immunotherapy (66%). At data cut-off (December 2025; reverse-Kaplan-Meier median follow-up 36.3 months), median PFS was 9.6 months and median OS was 15.2 months. Across 200 tumors, 495 pathogenic variants (PVs) were identified in 83 genes. Exploratory outcome analyses showed longer OS in EGFR-mutant disease (preserved under parsimonious multivariable adjustment) and a formal KRAS × smoking interaction for OS (interaction P = 0.011). CONCLUSIONS: In this cohort, the molecular profile mirrors other Caucasian series, with clinically relevant enrichment patterns for EGFR and KRAS. ECOG performance status and first line treatment were the dominant prognostic factors in this cohort. A novel KRAS and smoking interaction for overall survival warrants prospective validation.

Aged↗

PubMed2001

Serial analysis of gene expression in Plasmodium falciparum reveals the global expression profile of erythrocytic stages and the presence of anti-sense transcripts in the malarial parasite.

Serial analysis of gene expression (SAGE) was applied to the malarial parasite Plasmodium falciparum to characterize the comprehensive transcriptional profile of erythrocytic stages. A SAGE library of approximately 8335 tags representing 4866 different genes was generated from 3D7 strain parasites. Basic local alignment search tool analysis of high abundance SAGE tags revealed that a majority (88%) corresponded to 3D7 sequence, and despite the low complexity of the genome, 70% of these highly abundant tags matched unique loci. Characterization of these suggested the major metabolic pathways that are used by the organism under normal culture conditions. Furthermore several tags expressed at high abundance (30% of tags matching to unique loci of the 3D7 genome) were derived from previously uncharacterized open reading frames, demonstrating the use of SAGE in genome annotation. The open platform "profiling" nature of SAGE also lead to the important discovery of a novel transcriptional phenomenon in the malarial pathogen: a significant number of highly abundant tags that were derived from annotated genes (17%) corresponded to antisense transcripts. These SAGE data were validated by two independent means, strand specific reverse transcription-polymerase chain reaction and Northern analysis, where antisense messages were detected in both asexual and sexual stages. This finding has implications for transcriptional regulation of Plasmodium gene expression.

Animals↗

PubMed2025

Multi-omic integration with human dorsal root ganglia proteomics highlights TNFα signalling as a relevant sexually dimorphic pathway.

The peripheral nervous system (PNS) plays a critical role in pathological conditions, including chronic pain disorders, that manifest differently in men and women. To investigate this sexual dimorphism at the molecular level, we integrated quantitative proteomic profiling of human dorsal root ganglia (hDRG) and peripheral nerve tissue into the expanding omics framework of the PNS. Using data-independent acquisition (DIA) mass spectrometry, we characterized a comprehensive proteomic profile, validating tissue-specific differences between the hDRG and peripheral nerve. Through multi-omic analyses and in vitro functional assays, we identified sex-specific molecular differences, with TNFα signalling emerging as a key sexually dimorphic pathway with higher prominence in men. Genetic evidence from genome-wide association studies further supports the functional relevance of TNFα signalling in the periphery, while clinical trial data and meta-analyses indicate a sex-dependent response to TNFα inhibitors. Collectively, these findings underscore a functionally sexual dimorphism in the PNS, with direct implications for sensory and pain-related clinical translation.

Humans↗