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The Cinderella story of metabolic profiling: does metabolomics get to go to the functional genomics ball?

To date most global approaches to functional genomics have centred on genomics, transcriptomics and proteomics. However, since a number of high-profile publications, interest in metabolomics, the global profiling of metabolites in a cell, tissue or organism, has been rapidly increasing. A range of analytical techniques, including 1H NMR spectroscopy, gas chromatography-mass spectrometry (GC-MS), liquid chromatography-mass spectrometry (LC-MS), Fourier Transform mass spectrometry (FT-MS), high performance liquid chromatography (HPLC) and electrochemical array (EC-array), are required in order to maximize the number of metabolites that can be identified in a matrix. Applications have included phenotyping of yeast, mice and plants, understanding drug toxicity in pharmaceutical drug safety assessment, monitoring tumour treatment regimes and disease diagnosis in human populations. These successes are likely to be built on as other analytical and bioinformatic approaches are developed to fully exploit the information obtained in metabolic profiles. To assist in this process, databases of metabolomic data will be necessary to allow the passage of information between laboratories. In this prospective review, the capabilities of metabolomics in the field of medicine will be assessed in an attempt to predict the impact this 'Cinderella approach' will have at the 'functional genomic ball'.

Animals↗

SELDI-TOF-MS of saliva: methodology and pre-treatment effects.

Interest in saliva as a diagnostic fluid for monitoring general health and for early diagnosis of disease has increased in the last few years. In particular, efforts have focused on the generation of protein maps of saliva using advanced proteomics technology. Surface-enhanced laser-desorption/ionization time-of-flight mass spectrometry (SELDI-TOF-MS) is a novel high throughput and extremely sensitive proteomic approach that allows protein expression profiling of large sets of complex biological specimens. In this study, large scale profiling of salivary proteins and peptides, ranging from 2 to 100kDa was demonstrated using SELDI-TOF-MS. Various methodological aspects and pre-analytical variables were analysed with respect to their effects on saliva SELDI-TOF-MS profiling. Results show that chip surface type and sample type (unstimulated versus stimulated) critically affect the amount and composition of detected salivary proteins. Factors that influenced normal saliva protein profiling were matrix composition, sample dilution and binding buffer properties. Delayed processing time experiments show certain new peptides evolving 3h post-saliva donation, and quantitative analyses indicate relative intensity of other proteins and peptides changing with time. The addition of protease inhibitors partly counteracted the destabilization of certain protein/peptide mass spectra over time suggesting that some proteins in saliva are subject to digestion by intrinsic salivary proteases. SELDI-TOF-MS profiles also changed by varying storage time and storage temperature whereas centrifugation speed and freeze-thaw cycles had minimal impact. In conclusion, SELDI-TOF-MS offers a high throughput platform for saliva protein and peptide profiling, however, (pre-)analytical conditions must be taken into account for valid interpretation of the acquired data.

Biomarkers↗

Detection and identification of heat shock protein 10 as a biomarker in colorectal cancer by protein profiling.

Although colorectal cancer is one of the best-characterized tumors with regard to the multistep progression, it remains one of the most frequent and deadly neoplasms. For a better understanding of the molecular mechanisms behind the process of tumorigenesis and tumor progression, changes in protein expression between microdissected normal and tumorous colonic epithelium were analyzed. Cryostat sections from colorectal tumors, adenoma tissue, and adjacent normal mucosa were laser-microdissected and analyzed using ProteinChip Arrays. The derived MS profiles exhibited numerous statistical differences. One peak showing significantly high expression in the tumor was purified by reverse-phase chromatography and SDS-PAGE. The protein band of interest was passively eluted from the gel and identified as heat shock protein 10 (HSP 10) by tryptic digestion, peptide mapping, and MS/MS analysis. This tumor marker was further characterized by immunohistochemistry. Analysis of HSP 10-positive tissue by ProteinChip technology confirmed the identity of this protein. This work demonstrates that biomarker in colorectal cancer can be detected, identified, and assessed by a proteomic approach comprising tissue microdissection, protein profiling, and immunological techniques. In our experience, histological defined microdissected tissue areas should be used to identify proteins that might be responsible for tumorigenesis.

Biomarkers, Tumor↗

Proteomics: the next revolution in laboratory medicine?

BACKGROUND: The identification of specific genetic alterations and protein profiles associated with disease offers a unique opportunity to develop proteomics-based assays for early diagnosis. By identifying proteins in serum/plasma, a minimally invasive tool is used to assess the presence of disease and to monitor response to treatment and/or disease progression. The potential clinical applications of this tool are broad-based, including the diagnosis not only of cancer but also cardiovascular and neuromuscular diseases, organ transplantation associated conditions, and infertility. METHODS: A number of competing chromatographic techniques have been proposed for overcoming the complexity and labor-intensive manipulations associated with the traditional technique for proteomic analysis, which is based on two-dimensional gel electrophoretic techniques. However, mass spectrometry has now assumed a central role in most proteomic workflows, and several combinations of ionization sources, analyzers and fragmentations devices have been described and developed. RESULTS: Thanks to proteomic applications in the diagnosis of cancer, several research groups have identified proteomic patterns associated with ovarian, prostatic, colorectal and other cancers. While the sensitivity and specificity of these patterns are highly satisfactory, there are still some open questions concerning the standardization, reproducibility, and inter-laboratory agreement of these data. CONCLUSIONS: Proteomics, and, in particular, serum mass spectroscopic proteomic pattern diagnostics, is a rapid expanding field of research. The plasma proteoma has an important position at the intersection between genes and diseases, and clinical laboratories must adapt to a new era of tests based on proteomics and genomics. In the future, mass spectrometry will become an essential tool in the clinical laboratory.

Biomarkers, Tumor↗

Proteomic analysis of rat plasma by two-dimensional liquid chromatography and matrix-assisted laser desorption ionization time-of-flight mass spectrometry.

The proteomic analysis of plasma and serum samples represents a formidable challenge due to the presence of a few highly abundant proteins such as albumin and immunoglobulins. Detection of low abundance protein biomarkers therefore requires either the specific depletion of high abundance proteins using immunoaffinity columns and/or optimized protein fractionation methods based on charge, size or hydrophobicity. Here we describe a two-dimensional (2D) liquid chromatography separation method for the fractionation of rat plasma. In the first dimension proteins were separated by chromatofocusing according to their isoelectric point (pI). In the second dimension, proteins were further fractionated by non-porous, reversed-phase chromatography according to their hydrophobicity. The data from both separations was displayed as a 2D protein expression map of pI versus retention time (relative hydrophobicity). Both separations were carried out on the ProteomeLab PF 2D system (Beckman Coulter), an instrument platform that provides a high degree of automation and real-time monitoring of the separation process. The reproducibility of the first-dimension separation was evaluated in terms of pH gradient formation. The second-dimension separation was evaluated in terms of peak retention times on the reversed-phase column. We found in four consecutive chromatofocusing separations that the pH gradient differed by less than 0.2 pH units at any time during the elution step. Second dimension retention times of peaks from identical pI fractions differed by less than 7 s in six consecutive separations. Each 2D separation generated a total of 540 fractions which were analyzed by matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF MS). We detected approximately 275 peptides and proteins with molecular masses ranging from 3 to 225 kDa. Most fractions were found to contain multiple low and high molecular weight proteins. Differential display of 2D protein expression maps from retinol-sufficient and -deficient rat plasma samples identified a fraction with several proteins that appeared to be down-regulated in the vitamin A-deficient animal. Quantitative proteomic analysis of complex samples such as plasma is still a difficult task. We discuss the potential of this approach for biomarker discovery and address the experimental challenges that remain.

Animals↗

Two-dimensional database of a Burkitt lymphoma cell line (DG 75) proteins: protein pattern changes following treatment with 5'-azycytidine.

Hypermethylation is an important mechanism for repression of tumor gene suppressor in cancer. The drug 5'-azacytidine (AZC) has been used as demethylating agent to induce the expression of previously silencing genes. In the present work, we attempted to determine, using proteomics, the changes in protein expression profiles following a treatment of an Epstein Barr virus (EBV)-negative Burkitt lymphoma (BL) cell line DG 75. The effects of the treatment in terms of cell viability and growth were first examined. The following observations were made: AZC treatment led to (i) a decrease in cell growth with an arrest of the cell at G0/G1 phase of the cell cycle, (ii) the expression of p16, a tumor-suppressor gene whose expression was dependent on its promoter demethylation. Proteomic study evidenced that AZC treatment affected protein expression in two different ways. Twenty-one polypeptides were down-expressed, while 14 showed an increased expression. Some of the upregulated proteins appeared related to the energy metabolism, to organization of cytoskeletal structures, and to cell viability and protein synthesis. We also established a reference map for proteins in DG 75 cell line, comprising 74 different polypeptides corresponding to 67 proteins. This map will be accessible via Internet as a resource for proteome analyses of B-cells. Taken together, the results presented here highlight new insights into lymphoma cell gene regulations following a treatment of lymphoma cells with AZC and illustrate a use of proteomics to evidence the direct and indirect effects of a drug and the pathways it possibly regulates.

Antimetabolites, Antineoplastic↗

The molecular scanner: concept and developments.

Approaches aimed at deciphering the proteome have illustrated the need for relatively complex and highly sensitive methodologies. The major elements of proteome analysis, such as powerful protein separation and enzymatic processing, mass spectrometry and dedicated bioinformatics have been assembled in the development of the molecular scanner. This highly flexible and data-rich approach has combined the power of electrophoretic protein separation, the simultaneous digestion and transfer of proteins through an enzymatic membrane, the immediate use of the MALDI mass spectrometer to scan a collecting membrane, and the development of dedicated bioinformatics tools to perform protein identification and molecular imaging of the proteome. Clinical applications of the molecular scanner have also started to be developed for disease diagnosis in biological material.

Animals↗

Profiling stage-dependent changes of protein expression in Caenorhabditis elegans by mass spectrometric proteome analysis leads to the identification of stage-specific marker proteins.

Proteome maps obtained by synchronization of the wild-type Caenorhabditis elegans development reflected stage-dependent molecular differences and revealed dynamic cytoskeletal processes during ontogenesis. Distinct protein spots that may function as molecular markers for the corresponding developmental stages were mass spectrometrically identified. The amount of the Cu(2+)- Zn(2+) superoxide dismutase (CE23550) and an aspartyl proteinase (CE21681) was highest in the first larval stage (L1) and decreased during the ontogenesis from the first larval stage to the adult. Tropomyosin III (CE29059) was prominently present in the first and second larval stage (L1/L2). Abundances of actin 1 or 4 (CE12358 or CE13148) and tropomyosin I (CE28782) were particularly high in multiple spots in the third larval stage (L3). Interestingly, the amount of DIM-1 protein (CE27706), reflected by two spots, was the lowest in this stage. A particular splicing factor (CE31089) was detected only in the fourth larval stage (L4), whereas a spot with high abundance representing the cuticle collagen (CE02272) was only found highly expressed in adult animals (A). In addition, a Ca(2+)-binding protein (CE12368) and one protein spot which has not yet been identified, both reached their maximal spot intensities in the adult stage (A). Moreover, the ASP-1, CCT-5, GPD-1, GPD-2, HSP-6, HSP-16.2, IFB-2, LEC-2, LIN-53, LMN-1, MDH-1, NUD-1, RPA-0, RSP-12, SOD-1, TBB-1, TBB-2, TMY-1, UNC-60, and VIT-2 proteins for which mutants are available and two still unidentified protein spots which were present in all developmental stages, have been reproducibly localized in proteome maps of distinct ontogenesis states.

Animals↗

Spatial Proteomics of the Human Atherosclerotic Microenvironment Reveals Heterogeneity in Intraplaque Proteomes and Extracellular Matrix Remodeling.

Plaque heterogeneity underlies the propensity of atherosclerotic lesions to rupture and trigger cardiovascular events. Most proteomic studies examine bulk changes, obscuring key spatial differences in protein abundance. We report a high-resolution spatial proteomics workflow exploring the molecular landscape of human plaques and a murine myocardium. By combining laser capture microdissection with high-sensitivity ion-mobility mass spectrometry, spatial profiling of cellular and extracellular matrix (ECM) proteomes was achieved. Over 2700 proteins were detected from 50,000 μm2 areas, revealing substantial intraplaque heterogeneity across distinct regions (lipid-rich, media, shoulder, necrotic core, intima) and distance from the artery lumen. Inverse correlations between proteases (cathepsin B) and core structural ECM proteins (perlecan, HSPG2) indicated active ECM remodeling. Analysis of media layers indicated distinct protein signatures associated with smooth muscle contraction and cell-cell communication. Blood coagulation signatures, including platelet degranulation and fibrin formation, were enriched at the intima. Inflammatory (clusters of differentiation 4/68, CD4/CD68; vascular cell adhesion molecule 1, VCAM1) and vascular damage markers (tenascin-C, TNC) were enriched in shoulder regions. The necrotic core was dominated by blood proteins, consistent with intraplaque hemorrhage. This workflow resolves proteomic changes over ∼200 μm distances, providing unprecedented insights into plaque morphology and offers a powerful tool for elucidating plaque biology.

Humans↗

Activity-based probes that target diverse cysteine protease families.

Proteases are one of the largest and best-characterized families of enzymes in the human proteome. Unfortunately, the understanding of protease function in the context of complex proteolytic cascades remains in its infancy. One major reason for this gap in understanding is the lack of technologies that allow direct assessment of protease activity. We report here an optimized solid-phase synthesis protocol that allows rapid generation of activity-based probes (ABPs) targeting a range of cysteine protease families. These reagents selectively form covalent bonds with the active-site thiol of a cysteine protease, allowing direct biochemical profiling of protease activities in complex proteomes. We present a number of probes containing either a single amino acid or an extended peptide sequence that target caspases, legumains, gingipains and cathepsins. Biochemical studies using these reagents highlight their overall utility and provide insight into the biochemical functions of members of these protease families.

Animals↗

Synapse proteomics of multiprotein complexes: en route from genes to nervous system diseases.

Proteomic experiments have produced a draft profile of the overall molecular composition of the mammalian neuronal synapse. It appears that synapses have over 1000 protein components and the mapping of their interactions, organization and functions will lead to a global view of the role of synapses in physiology and disease. A major functional subcomponent of the synaptic machinery is a multiprotein complex of glutamate receptors and adhesion proteins with associated adaptor and signalling enzymes totally 185 proteins known as the N-methyl-d-aspartate receptor complex/MAGUK associated signalling complex (NRC/MASC). Here, we review the proteomic studies and functions of NRC/MASC and specifically report on the role of its component genes in human diseases. Using a systematic literature search protocol, we identified reports of mutations or polymorphisms in 47 genes associated with 183 disorders, of which 54 were nervous system disorders. A similar number of genes are important in mouse synaptic plasticity and behaviour, where the NRC/MASC acts as a signalling complex with multiple functions provided by its individual protein components and their interactions. The individual gene mutations suggest not only an important role for the NRC/MASC in human diseases but that these diseases may be functionally connected by their common link to the NRC/MASC. The NRC/MASC is a rich source of genetic variation and provides a platform for understanding relationships of disease phenotype amenable to systematic studies such as the Genes to Cognition research consortium (www.genes2cognition.org) that links human and mouse genetics with proteomic studies.

Humans↗

OMICS-driven biomarker discovery in nutrition and health.

While traditional nutrition research has dealt with providing nutrients to nourish populations, it nowadays focuses on improving health of individuals through diet. Modern nutritional research is aiming at health promotion and disease prevention and on performance improvement. As a consequence of these ambitious objectives, the disciplines "nutrigenetics" and "nutrigenomics" have evolved. Nutrigenetics asks the question how individual genetic disposition, manifesting as single nucleotide polymorphisms, copy-number polymorphisms and epigenetic phenomena, affects susceptibility to diet. Nutrigenomics addresses the inverse relationship, that is how diet influences gene transcription, protein expression and metabolism. A major methodological challenge and first pre-requisite of nutrigenomics is integrating genomics (gene analysis), transcriptomics (gene expression analysis), proteomics (protein expression analysis) and metabonomics (metabolite profiling) to define a "healthy" phenotype. The long-term deliverable of nutrigenomics is personalised nutrition for maintenance of individual health and prevention of disease. Transcriptomics serves to put proteomic and metabolomic markers into a larger biological perspective and is suitable for a first "round of discovery" in regulatory networks. Metabonomics is a diagnostic tool for metabolic classification of individuals. The great asset of this platform is the quantitative, non-invasive analysis of easily accessible human body fluids like urine, blood and saliva. This feature also holds true to some extent for proteomics, with the constraint that proteomics is more complex in terms of absolute number, chemical properties and dynamic range of compounds present. Apart from addressing the most complex "-ome", proteomics represents the only platform that delivers not only markers for disposition and efficacy but also targets of intervention. The Omics disciplines applied in the context of nutrition and health have the potential to deliver biomarkers for health and comfort, reveal early indicators for disease disposition, assist in differentiating dietary responders from non-responders, and, last but not least, discover bioactive, beneficial food components. This paper reviews the state-of-the-art of the three Omics platforms, discusses their implication in nutrigenomics and elaborates on applications in nutrition and health such as digestive health, allergy, diabetes and obesity, nutritional intervention and nutrient bioavailability. Proteomic developments, applications and potential in the field of nutrition have been specifically addressed in another review issued by our group.

Animals↗

Development of a multiplexed microcapillary liquid chromatography system for high-throughput proteome analysis.

Comprehensive proteome analysis requires the identification (and quantification) of the proteins in samples consisting of thousands of proteins spanning a range of abundance of several orders of magnitude. The currency of proteome analysis by mass spectrometry is the peptides generated by protein proteolysis. The high sample complexity of such samples requires a large separation capacity, which is commonly achieved by fractionation of the mixture followed by further serial separations of each fraction. The sample throughput of proteome analysis is therefore limited by the need to sequentially process large numbers of samples. We have developed a novel four-plexed microcapillary liquid chromatography system for automated, high-throughput separation of complex peptide samples. The system supports the concurrent separation of four different samples by directing identically split solvent-gradient flows into four microcapillary C18 columns. The simple design of the system achieves multiplexed separation without the need for extra solvent pumps. Peak resolution, reproducibility, and parallel separating capacity of the system were investigated using standard peptides. The applicability of the system to high-throughput protein expression profiling was demonstrated in qualitative and quantitative analyses of protein expression in S. cerevisiae grown on two different carbon sources using the isotope-coded affinity tag (ICAT) reagent and matrix-assisted desorption/ionization quadrupole time-of-flight mass spectrometry.

Chromatography, High Pressure Liquid↗

Human IL-34 Deficiency Primes Microglia Toward Alzheimer's Disease-Associated States.

BACKGROUND: Genome-wide association studies (GWAS), with independent replication in large European consortia, have identified a common nonsense variant in IL-34 (Y213X) as a genetic risk factor for late-onset Alzheimer's disease (AD). However, the biological consequences of this IL-34 mutation in humans, its prevalence in the population, and the mechanisms by which IL-34-Y213X alters microglial homeostasis, cerebrospinal fluid (CSF) proteomic networks, and amyloid pathology remain poorly understood. METHODS: We combined human genetics, cerebrospinal fluid (CSF) and serum proteomics, transcriptomics, large-scale phenome-wide association analyses, and preclinical experimental models to define the impact of human IL-34 deficiency. IL-34 concentrations were first quantified in CSF and serum from deeply phenotyped AD cohorts stratified by the common IL-34-Y213X nonsense variant. IL-34 levels and IL-34-Y213X status were then integrated with unbiased CSF proteomic networks and AD biomarkers. Transcriptomic profiling of purified microglia from IL-34 knockout mice was performed to assess disease-associated microglial programs. Using APP/PS1 mice lacking IL-34, we examined the effects of IL-34 deficiency on microglial survival, tiling, and plaque encapsulation. Finally, we performed postmortem analyses of temporal cortex from AD patients carrying IL-34-Y213X to assess microglial density, spatial organization, and plaque-associated responses. FINDINGS: IL-34-Y213X was a strong, dose-dependent loss-of-function (LOF) allele that reduced IL-34 levels by up to 2.5 standard deviations in CSF and serum and was common in multiple populations. IL-34 deficiency reshaped CSF proteomic networks, downregulating axon guidance and microglial support modules while upregulating inflammatory and extracellular matrix signatures, and showed pleiotropic associations with neurological, inflammatory, and metabolic traits. Transcriptomic analysis of sorted microglia from healthy 9-month-old IL-34KO compare to wild-type mice revealed a profound pro-inflammatory and disease-associated microglial transcriptional program enriched for disease-associated microglia (DAM) signatures, inflammatory pathways, and AD risk genes including APOE, CLU, and CASS4. In APP/PS1 mice, genetic IL-34 deletion selectively depleted homeostatic gray-matter microglia, disrupted microglial tiling, and impaired plaque encapsulation, resulting in altered amyloid structure and enhancing neuritic injury. Concordantly, AD patients homozygous for IL-34-Y213X displayed markedly reduced cortical microglial density and increased microglial spatial dispersion, indicating a breakdown of the microglial network organization in the human brain. INTERPRETATION: A common human IL-34 LOF variant creates a naturally occurring model of IL-34 deficiency that links microglial survival, CSF network signatures, and amyloid pathology in both mice and humans. Importantly, IL-34 deficiency alone is sufficient to induce inflammatory, AD-associated microglial states beyond simply reducing microglial number. These findings identify IL-34/CSF1R signaling as a critical determinant of microglial resilience and a potential upstream pathway linking human genetic variation to AD susceptibility, highlighting IL-34-dependent pathways as promising targets for disease modification. FUNDING: This work was supported by grants from the Spanish Ministerio de Ciencia, Innovación y Universidades/FEDER/UE (PID2024-157400OB-I00) and FORTALECE program (FORT23/00008; Instituto de Salud Carlos III, Spain) to RRL and JLV, ISCIII of Spain co-financed by FEDER funds (European Union) through grants PI24/00308 (JV) and CIBERNED collaborative grant 2022/01 to JV, PID2023-147125OB-I00 and CEX2023-001386-S (Severo Ochoa Programme) to SMTBC. A.R. is supported by STAR Award. University of Texas System. Tx, United States, The South Texas ADRC. National Institute of Aging. National Institutes of Health. USA. (P30AG066546), the Keith M. Orme and Pat Vigeon Orme Endowed Chair in Alzheimer's and Neurodegenerative Diseases (2024-2025) and Patricia Ruth Frederick Distinguished Chair for Precision Therapeutics in Alzheimer's and Neurodegenerative Diseases (2025-2028). AR is also supported by the Agency for Innovation and Entrepreneurship (VLAIO) grant N° PR067/21 for the HARPONE project and the ADAPTED project the EU/EFPIA Innovative Medicines Initiative Joint Undertaking Grant N° 115975 and CIBERNED (ISCIII).

Journal Article↗

Recent advances and novel strategies in vaccine development.

This review is intended to cover some recent advances in identification of vaccine candidates and in methods of delivery of vaccine antigens. Sequencing of bacterial genomes has led to rapid utilization of the predicted open reading frames to identify potential candidates for evaluation and, with improvements in proteomics combined with microanalytical sequencing techniques, to identify expressed proteins. Expression of vaccine antigens in human food sources has been greatly improved, opening the possibility of orally delivered subunit vaccines, as has the ability to modify the immune response with cytokines and chemokines. These techniques are slowly making their way to human studies and show great promise for future human use.

Antigens, Bacterial↗

Mass spectrometry-based study of the plasma proteome in a mouse intestinal tumor model.

Early detection of cancer can greatly improve prognosis. Identification of proteins or peptides in the circulation, at different stages of cancer, would greatly enhance treatment decisions. Mass spectrometry (MS) is emerging as a powerful tool to identify proteins from complex mixtures such as plasma that may help identify novel sets of markers that may be associated with the presence of tumors. To examine this feature we have used a genetically modified mouse model, Apc(Min), which develops intestinal tumors with 100% penetrance. Utilizing liquid chromatography-tandem mass spectrometry (LC-MS/MS), we identified total plasma proteome (TPP) and plasma glycoproteome (PGP) profiles in tumor-bearing mice. Principal component analysis (PCA) and agglomerative hierarchial clustering analysis revealed that these protein profiles can be used to distinguish between tumor-bearing Apc(Min) and wild-type control mice. Leave-one-out cross-validation analysis established that global TPP and global PGP profiles can be used to correctly predict tumor-bearing animals in 17/19 (89%) and 19/19 (100%) of cases, respectively. Furthermore, leave-one-out cross-validation analysis confirmed that the significant differentially expressed proteins from both the TPP and the PGP were able to correctly predict tumor-bearing animals in 19/19 (100%) of cases. A subset of these proteins was independently validated by antibody microarrays using detection by two color rolling circle amplification (TC-RCA). Analysis of the significant differentially expressed proteins indicated that some might derive from the stroma or the host response. These studies suggest that mass spectrometry-based approaches to examine the plasma proteome may prove to be a valuable method for determining the presence of intestinal tumors.

Animals↗

Mining microarray expression data by literature profiling.

BACKGROUND: The rapidly expanding fields of genomics and proteomics have prompted the development of computational methods for managing, analyzing and visualizing expression data derived from microarray screening. Nevertheless, the lack of efficient techniques for assessing the biological implications of gene-expression data remains an important obstacle in exploiting this information. RESULTS: To address this need, we have developed a mining technique based on the analysis of literature profiles generated by extracting the frequencies of certain terms from thousands of abstracts stored in the Medline literature database. Terms are then filtered on the basis of both repetitive occurrence and co-occurrence among multiple gene entries. Finally, clustering analysis is performed on the retained frequency values, shaping a coherent picture of the functional relationship among large and heterogeneous lists of genes. Such data treatment also provides information on the nature and pertinence of the associations that were formed. CONCLUSIONS: The analysis of patterns of term occurrence in abstracts constitutes a means of exploring the biological significance of large and heterogeneous lists of genes. This approach should contribute to optimizing the exploitation of microarray technologies by providing investigators with an interface between complex expression data and large literature resources.

Cluster Analysis↗