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PubMed2006

A genome-wide approach to identify genetic loci with a signature of natural selection in the Irish population.

BACKGROUND: In this study we present a single population test (Ewens-Waterson) applied in a genomic context to investigate the presence of recent positive selection in the Irish population. The Irish population is an interesting focus for the investigation of recent selection since several lines of evidence suggest that it may have a relatively undisturbed genetic heritage. RESULTS: We first identified outlier single nucleotide polymorphisms (SNPs), from previously published genome-wide data, with high FST branch specification in a European-American population. Eight of these were chosen for further analysis. Evidence for selective history was assessed using the Ewens-Watterson's statistic calculated using Irish genotypes of microsatellites flanking the eight outlier SNPs. Evidence suggestive of selection was detected in three of these by comparison with a population-specific genome-wide empirical distribution of the Ewens-Watterson's statistic. CONCLUSION: The cystic fibrosis gene, a disease that has a world maximum frequency in Ireland, was among the genes showing evidence of selection. In addition to the demonstrated utility in detecting a signature of natural selection, this approach has the particular advantage of speed. It also illustrates concordance between results drawn from alternative methods implemented in different populations.

Cystic Fibrosis Transmembrane Conductance Regulato↗
PubMed2025

Developing a disease-specific accessible transcriptional signature as a biomarker for ataxia with oculomotor apraxia type 2.

BACKGROUND: Genetic ataxias are clinically heterogenous neurodegenerative conditions often involving rare or private mutations and it is often difficult to assign pathogenicity to rare gene variants solely based on DNA sequencing. An effective functional assay from an easy-to-obtain biospecimen would aid this assessment and be of high clinical value. SETX encodes a ubiquitous DNA/RNA helicase crucial for resolving R-loops and maintaining genome stability. Loss-of-function mutations cause a recessive disorder, Ataxia with Oculomotor Apraxia Type 2 (AOA2). METHODS: Here we utilize Weighted Gene Co-expression Network Analysis (WGCNA) from patient blood to construct an AOA2-specific transcriptomic signature as a biomarker to evaluate SETX variants in patients clinically suspected of having AOA2. RESULTS: WGCNA from peripheral blood RNA of 11 AOA2 patients from 7 families initially identified a single gene module that was modestly effective in distinguishing individuals with AOA2 from controls (sensitivity 73%, specificity 97%) and was able to robustly differentiate AOA2 patients from those with genetically distinct, yet phenotypically similar, neurological disorders (sensitivity 100%, specificity 100%). An independent derivation of the transcriptional biomarker identified a dual module model that was able to better distinguish individuals with AOA2 from controls (sensitivity 100%, specificity 97%). As validation, we examined a second cohort of 21 patients from 13 families and demonstrate that this dual module transcriptional biomarker could discriminate patients clinically suspected of AOA2 from controls (57%, 95%CI: 34%-78%). Overall, the transcriptional biomarker was able to separate AOA2 subjects (n = 32) from controls (n = 35) with 72% sensitivity and 97% specificity. Notably, this transcriptomic biomarker enabled verification of the first pathogenic SETX mutation found in a non-canonical transcript, expanding the spectrum of mutations that contribute to AOA2. CONCLUSIONS: Our study identified a transcriptional biomarker that was able to differentiate AOA2 from controls and from other related neurological disorders, consequently expanding the spectrum of known pathogenic mutations. This proof-of-concept study illustrates that transcriptional biomarkers may be used to validate variants of uncertain significance in known genetic diseases.

Humans↗
PubMed2025

Molecular signatures of adaptive introgression and selection in contact zones of closely related pine species (Pinus genus).

BACKGROUND: Natural hybridization plays a key role in shaping genetic diversity, local adaptation, and the dynamics of speciation through interspecific gene flow. Hybrid zones serve as valuable natural systems for studying these processes. In this research, we used genotypic data at thousands of nuclear SNPs to investigate genomic outcomes of hybridization and selection across three contact zones of closely related pine species including Scots pine (Pinus sylvestris L.) and dwarf mountain pine (P. mugo T.). Reference allopatric stands of parental species were used to assess introgression dynamics. RESULTS: Individuals from the hybrid zones showed distinct genetic ancestry patterns and were assigned to groups including putative pure species, first-generation hybrids, and advanced backcrosses. Genotypes of the majority of hybrids were shifted towards P. mugo ancestry. Most outlier loci were shared across all sympatric populations, although some were specific to individual contact zones. The identified outliers were mainly associated with regulatory biological processes related to phosphorylation, proteolysis, and transmembrane transport. Signatures of local adaptation varied in different genetic classes in contact zones and they were strongest in pure P. sylvestris and hybrids with a majority of P. sylvestris ancestry. The pattern suggests that it may be driven by adaptation to peat bog habitats situated outside the species’ core ecological niche. CONCLUSIONS: Our findings indicate strong selective pressure acting on multiple genes in groups of hybrids and pure Pinus sylvestris individuals across all studied hybrid zones. In contrast, the weaker signal of selection observed in individuals with P. mugo ancestry suggests that relict populations of this species, which historically spread across postglacial peat bogs, were pre-adapted to such environments. While several outlier loci were shared across different contact zones, others were unique for one of them, indicating that local environmental pressures and adaptive introgression shape the genomic composition of the populations. These results highlight the role of hybridization in generating adaptive diversity and emphasize the evolutionary significance of hybrid zones in pines.

Hybridization, Genetic↗
PubMed2026

Epigenetic and immunological alterations in umbilical cord blood of overweight/obese women with gestational diabetes mellitus: insights into DNA methylation signatures and immune cell dysregulation.

BACKGROUND: Gestational diabetes mellitus (GDM) is a common pregnancy complication associated with adverse maternal and neonatal outcomes. Epigenetic modifications may reflect intrauterine metabolic exposure and contribute to immune and metabolic alterations. This study aimed to explore DNA methylation profiles in umbilical cord blood from overweight and obese women with and without GDM. METHODS: Umbilical cord blood samples from 30 overweight/obese pregnant women (with and without GDM) were analyzed using the Illumina 850&#xa0;K methylation array to identify differentially methylated positions (DMPs) and regions (DMRs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to assess the functional relevance of methylation changes. Immune cell composition was estimated using deconvolution analysis and further examined in an independent single-cell RNA sequencing (scRNA-seq) cohort. Lasso regression was applied to identify CpG sites associated with GDM status and construct a preliminary methylation-based classification model. RESULTS: A total of 23,331 hypermethylated and 29,501 hypomethylated DMPs were identified between women with and without GDM, with hypomethylation predominating. Enrichment analyses indicated associations with neurodevelopmental pathways, metabolic processes, immune regulation, and epigenetic modification. Immune deconvolution analysis suggested reduced proportions of CD4+ T cells (p&#x2009;<&#x2009;0.05) and a trend toward decreased NK cells in the GDM group, alongside increased CD8+ T cells and neutrophils. Seven CpG sites were selected for model construction and demonstrated strong discriminatory performance within this cohort. CONCLUSION: This exploratory study identifies distinct cord blood DNA methylation patterns associated with GDM in overweight/obese pregnancies. The findings suggest potential links between epigenetic alterations and immune cell composition in GDM-exposed offspring. The identified CpG signature warrants further validation in larger, prospective cohorts to determine its clinical applicability.

Humans↗
PubMed2025

Evaluation of a biomarker for amyotrophic lateral sclerosis derived from a hypomethylated DNA signature of human motor neurons.

Amyotrophic lateral sclerosis (ALS) lacks a specific biomarker, but is defined by relatively selective toxicity to motor neurons (MN). As others have highlighted, this offers an opportunity to develop a sensitive and specific biomarker based on detection of DNA released from dying MN within accessible biofluids. Here we have performed whole genome bisulfite sequencing (WGBS) of iPSC-derived MN from neurologically normal individuals. By comparing MN methylation with an atlas of tissue methylation we have derived a MN-specific signature of hypomethylated genomic regions, which accords with genes important for MN function. Through simulation we have optimised the selection of regions for biomarker detection in plasma and CSF cell-free DNA (cfDNA). However, we show that MN-derived DNA is not detectable via WGBS in plasma cfDNA. In support of our experimental finding, we show theoretically that the relative sparsity of lower MN sets a limit on the proportion of plasma cfDNA derived from MN which is below the threshold for detection via WGBS. Our findings are important for the ongoing development of ALS biomarkers. The MN-specific hypomethylated genomic regions we have derived could be usefully combined with more sensitive detection methods and perhaps with study of CSF instead of plasma. Indeed we demonstrate that neuronal-derived DNA is detectable in CSF. Our work is relevant for all diseases featuring death of rare cell-types.

Humans↗
PubMed2026

LLPS-based classification and a novel prognostic signature reveal NRF1 as a therapeutic target in pancreatic cancer.

BACKGROUND: Aberrant liquid-liquid phase separation (LLPS) can alter biomolecular condensate functions and may influence pancreatic tumorigenesis and progression, but the specific role of LLPS regulators in prognosis and the tumor immune microenvironment (TIME) in pancreatic ductal adenocarcinoma (PDAC) remains unclear. METHODS: We integrated transcriptome data of LLPS regulator-related differentially expressed genes (DEGs; n&#x2009;=&#x2009;298) in a cohort of 176 PDAC patients from TCGA. Three LLPS regulator subtypes (LS1-LS3) were identified through multi-omics analyses, and a prognostic LLPS subtype-related risk model (LRRPC) was developed and validated. Chromatin immunoprecipitation confirmed NRF1 binding to promoters of key risk genes, and in vitro and in vivo experiments assessed the effects of NRF1 targeting on tumor growth. RESULTS: The three LLPS regulator subtypes exhibited significant differences in prognosis, clinical features, genomic alterations, TIME patterns and predicted immunotherapy response. The LRRPC signature predicted prognosis and immunotherapy efficacy across cohorts and was associated with tumor biomarkers and immune infiltration. Nuclear Respiratory Factor 1 (NRF1) directly regulated hub genes such as FAM83A, RHOV and ITGB6, promoting PDAC cell proliferation, while its inhibition induced apoptosis and reduced tumor growth. CONCLUSIONS: This study proposes an LLPS-based stratification framework for PDAC, and the LRRPC model provides an LLPS subtype-related risk score that may assist personalized prognostic assessment and immunotherapy stratification. NRF1 emerges as a promising therapeutic candidate whose targeting can inhibit tumor progression in PDAC experimental models and warrants further evaluation.

Immunotherapy↗
PubMed2025

Altered immune signatures in breast cancer lymph nodes with metastases revealed by spatial proteome analyses.

BACKGROUND: Metastasis to lymph nodes is strongly associated with reduced survival in breast cancer patients. To increase the understanding on how lymph node metastasis impairs the local immune response in affected lymph nodes, we here studied spatial proteomic changes of critical lymph node immune populations in uninvolved lymph nodes (UnLN) and paired lymph nodes with metastases (LNM) from five breast cancer patients. METHODS: The proteome was analyzed for cortical lymphocyte compartments, subcapsular sinus (SCS) and medullary sinus (MS) CD169+ macrophages, using the Digital Spatial Profiling (DSP) platform from NanoString. RESULTS: Our results identified a stable proteome of SCS CD169+ macrophages in LNM, with the exception for downregulation of the anti-apoptotic protein Bcl-xL and FAP&#x3b1;, but a clear reduction in numbers of SCS CD169+ macrophages in LNM. In contrast, the proteome of MS CD169+ macrophages, B-cell compartments and interfollicular T-cells showed altered immune signatures in LNM, indicating that the decline in SCS CD169+ macrophages coincide with a malfunction in the local, anti-tumor immune responses. CONCLUSIONS: The findings from our study support the notion that metastasis to lymph nodes in breast cancer patients modifies local immune responses. These changes may contribute to explain unsuccessful therapeutic responses, and thereby worsened prognosis, for breast cancer patients with LNM.

Breast Neoplasms↗
PubMed2025

Proteomic signatures and predictive modeling of cadmium-associated anxiety in middle-aged and elderly populations: an environmental exposure association study.

BACKGROUND: Emerging evidence implicates environmental contaminants such as cadmium (Cd) as modifiable risk factors for anxiety. Despite growing recognition of heavy metal toxicity in neuropsychiatric disorders, the molecular mechanisms linking environmental exposure to anxiety pathogenesis remain poorly understood. METHODS: Based on the established cohort of individuals with cognitive impairment in cadmium-contaminated areas, this cross-sectional association study enrolled 50 middle-aged and elderly hospitalized patients from these regions, adhering to the STROBE guidelines. Blood concentrations of cadmium (Cd), lead (Pb), and mercury (Hg) were analyzed in relation to anxiety severity assessed via the Hamilton Anxiety Rating Scale (HAMA). Plasma proteomic profiling was performed using data-independent acquisition (DIA) quantitative technology with an LC-MS/MS platform (timsTOF Pro, Bruker Daltonics), systematically characterizing 2,531 proteins across all samples. Machine learning techniques, specifically XGBoost and LASSO, were employed to identify biomarkers that were subsequently validated through mediation analysis and animal experiments, allowing for the screening of key protein signatures. Finally, clinical variables were integrated to construct a comprehensive model, which was then thoroughly evaluated. RESULTS: Anxious individuals exhibited significantly higher blood Cd levels than controls (&#x3b2;&#x2009;=&#x2009;0.50, 95% CI: 0.07-0.93, p&#x2009;<&#x2009;0.01), with anxiety positively correlating with depression (r&#x2009;=&#x2009;0.62, p&#x2009;=&#x2009;0.003) and inversely with ApoE3 genotype prevalence. Proteomics identified 120 differentially expressed proteins in anxious patients, enriched in oxidative phosphorylation and neurodegenerative pathways. CCDC126 emerged as a cadmium-associated biomarker, validated in rat models exposed to Cd. Combining CCDC126, blood Cd, Pb, and hypertension, a clinical prediction model achieved robust discrimination (AUC&#x2009;=&#x2009;0.80, validation cohort). CONCLUSIONS: This first integrative environmental-proteomic study highlights cadmium's synergistic role in anxiety pathophysiology and psychiatric comorbidity. The predictive model offers translatable potential for early risk stratification, while CCDC126 provides mechanistic insights for targeted interventions in populations exposed to environmental pollutants.

Cadmium↗
PubMed2026

Transcriptome-based epigenetic screening identifies DNA hypermethylation signatures as prognostic biomarkers in oral squamous cell carcinoma.

Promoter DNA hypermethylation is a key epigenetic mechanism of gene silencing in cancer, yet the DNA hypermethylome of oral squamous cell carcinoma (OSCC) and its prognostic relevance remain poorly characterized. Here, we systematically identified and validated novel hypermethylated genes with prognostic significance in OSCC using a genome-wide discovery and multi-platform validation strategy. Candidate genes were first identified by pharmacologic demethylation combined with RNA sequencing across OSCC cell lines, then validated by quantitative RT-PCR, methylation-specific PCR, and bisulfite sequencing in OSCC cell lines, normal oral mucosa, and primary OSCC tumors, with independent confirmation in the TCGA-HNSC dataset. Immunohistochemistry confirmed protein-level silencing, and Kaplan-Meier survival analysis assessed prognostic significance across both cohorts. This pipeline identified five candidate genes, GPX3, ANG, CTGF, GPRC5B, and BAMBI, exhibiting cancer-specific promoter hypermethylation associated with transcriptional and protein silencing in OSCC. Validation in oral cavity tumor samples extracted from the TCGA-HNSC dataset confirmed tumor-specific hypermethylation and revealed significant inverse correlations between methylation and expression for GPX3, GPRC5B, and CTGF. Notably, CTGF hypermethylation was independently associated with poor overall survival in both cohorts (institutional cohort, p=0.03; oral tumor subset from TCGA-HNSC, p=0.01), and a combined ANG+CTGF methylation signature showed superior and reproducible prognostic performance across both platforms. Pathway analysis linked these genes to epithelial-mesenchymal transition and interferon response signaling. This study establishes the first validated DNA methylation biomarker panel for OSCC prognosis, identifying CTGF hypermethylation as a robust prognostic driver with translational potential for clinical risk stratification.

Humans↗
PubMed2006

Mining the mouse transcriptome of receptive endometrium reveals distinct molecular signatures for the luminal and glandular epithelium.

Epithelia coat most tissues where they sense and respond to the environment and participate in innate immune responses. In the adult mouse uterus, columnar epithelium lines the central lumen and the glands that penetrate the underlying stroma. A nidatory surge of estrogen causes differentiation of the luminal epithelium to the receptive state that permits blastocyst attachment and allows subsequent implantation. Here, using laser-capture microdissection to isolate the luminal and glandular epithelia separately, we have profiled gene expression 2 h before embryo attachment to determine whether there are unique roles for these two epithelial structures in this process. Although most genes were expressed in both compartments, there was greater expression of 153 and 118 genes in the lumen and glands, respectively. In the luminal epithelium, there is enrichment in lipid, metal-ion binding, and carbohydrate-metabolizing enzymes, whereas in the glands, immune response genes are emphasized. In situ hybridization to uterine sections obtained from mice during the preimplantation period validated these data and indicated an array of previously undocumented genes expressed with unique patterns in these epithelia. The data show that each epithelial compartment has a distinct molecular signature and that they act differentially and synergistically to permit blastocyst implantation.

Animals↗
PubMed2025

Tumor Signatures of Physical Fitness: Insights from a Preclinical Model.

PURPOSE: Cardiorespiratory fitness (CRF) and muscle strength are associated with cancer risk/mortality in adults. However, there is yet no evidence for pediatric tumors. This study investigated the association of CRF and muscle strength with several tumor-related phenotypes in an aggressive childhood malignancy, high-risk neuroblastoma. METHODS: Twelve mice-bearing orthotopic high-risk neuroblastomas were studied. CRF and muscle strength were assessed using treadmill and grip strength testing, respectively. The following tumor-related outcomes were studied: survival, clinical severity, tumor weight/volume, metastasis, and intratumor immune infiltrates. In addition, tumor samples underwent quantitative proteomic analysis via liquid chromatography-tandem mass spectrometry. Spearman correlations (or logistic regression) were performed between CRF/muscle strength and the abovementioned variables. Proteins that were significantly correlated with CRF or muscle strength were mapped into protein-protein interaction (PPI) networks using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. RESULTS: CRF was inversely correlated with clinical severity score ( r = -0.657, P = 0.020). Of 6840 identified tumor proteins, 76 correlated significantly with CRF (19 positively, 57 negatively), whereas 194 correlated with muscle strength (97 positively, 97 negatively). Proteins correlated with CRF were primarily involved in metabolic and structural pathways, including angiotensinogen and elastin. In turn, muscle strength-associated proteins were more abundant and included keratin family proteins (e.g., keratin, type I cytoskeletal 14, and type II cytoskeletal 5), proteins involved in cell adhesion (e.g., desmoglein-1-alpha), and translational regulators (e.g., eukaryotic initiation factor 4A). Network analysis revealed significant enrichment in structural organization and cellular adhesion pathways. CONCLUSIONS: Besides the association of CRF with clinical severity of the tumor, distinct novel tumor proteomic signatures associated with CRF and muscle strength were identified, highlighting potential mechanisms linking physical fitness with childhood cancer biology.

Muscle Strength↗
PubMed2004

Exploiting quartz spectral signature for the detection of cloud-affected satellite infrared observations over African desert areas.

It is shown that IMG (interferometric monitoring of greenhouse gases) spectra recorded over African and Arabian deserts clearly contain the fingerprint of quartz-rich soils. We illustrate how this spectral signature can be exploited to devise a suitable cloud-detection scheme to identify which infrared observations are affected by clouds. As a by-product, the scheme also allows one to identify the most likely underlying emitting surface type and provides a suitable first guess for the surface emissivity to be used, e.g., for the retrieval of geophysical parameters from high-spectral-resolution infrared radiance from space. The analysis has focused on African deserts because of their intrinsic relevance to numerical weather prediction and Earth's climate. Desert areas, like oceans, are poorly covered by the world meteorological radiosonde network and therefore are geographical regions for which the global coverage capability of satellites soundings is expected to provide better initializations for numerical weather prediction than are now available. Application of the cloud-detection scheme to IMG spectra has been considered, which demonstrates the good performance of the method.

Journal Article↗
PubMed2005

Three Prochlorococcus cyanophage genomes: signature features and ecological interpretations.

The oceanic cyanobacteria Prochlorococcus are globally important, ecologically diverse primary producers. It is thought that their viruses (phages) mediate population sizes and affect the evolutionary trajectories of their hosts. Here we present an analysis of genomes from three Prochlorococcus phages: a podovirus and two myoviruses. The morphology, overall genome features, and gene content of these phages suggest that they are quite similar to T7-like (P-SSP7) and T4-like (P-SSM2 and P-SSM4) phages. Using the existing phage taxonomic framework as a guideline, we examined genome sequences to establish "core" genes for each phage group. We found the podovirus contained 15 of 26 core T7-like genes and the two myoviruses contained 43 and 42 of 75 core T4-like genes. In addition to these core genes, each genome contains a significant number of "cyanobacterial" genes, i.e., genes with significant best BLAST hits to genes found in cyanobacteria. Some of these, we speculate, represent "signature" cyanophage genes. For example, all three phage genomes contain photosynthetic genes (psbA, hliP) that are thought to help maintain host photosynthetic activity during infection, as well as an aldolase family gene (talC) that could facilitate alternative routes of carbon metabolism during infection. The podovirus genome also contains an integrase gene (int) and other features that suggest it is capable of integrating into its host. If indeed it is, this would be unprecedented among cultured T7-like phages or marine cyanophages and would have significant evolutionary and ecological implications for phage and host. Further, both myoviruses contain phosphate-inducible genes (phoH and pstS) that are likely to be important for phage and host responses to phosphate stress, a commonly limiting nutrient in marine systems. Thus, these marine cyanophages appear to be variations of two well-known phages-T7 and T4-but contain genes that, if functional, reflect adaptations for infection of photosynthetic hosts in low-nutrient oceanic environments.

Bacteriophage T7↗
PubMed2006

Genetic signature of anthropogenic population collapse in orang-utans.

Great ape populations are undergoing a dramatic decline, which is predicted to result in their extinction in the wild from entire regions in the near future. Recent findings have particularly focused on African apes, and have implicated multiple factors contributing to this decline, such as deforestation, hunting, and disease. Less well-publicised, but equally dramatic, has been the decline in orang-utans, whose distribution is limited to parts of Sumatra and Borneo. Using the largest-ever genetic sample from wild orang-utan populations, we show strong evidence for a recent demographic collapse in North Eastern Borneo and demonstrate that this signature is independent of the mutation and demographic models used. This is the first demonstration that genetic data can detect and quantify the effect of recent, human-induced deforestation and habitat fragmentation on an endangered species. Because current demographic collapses are usually confounded by ancient events, this suggests a much more dramatic decline than demographic data alone and emphasises the need for major conservation efforts.

Animals↗
PubMed2005

Comparative signature-tagged mutagenesis identifies Pseudomonas factors conferring resistance to the pulmonary collectin SP-A.

The pulmonary collectin, surfactant protein A (SP-A), is a broad spectrum opsonin with microbicidal membrane permeabilization properties that plays a role in the innate immune response of the lung. However, the factors that govern SP-A's microbial specificity and the mechanisms by which it mediates membrane permeabilization and opsonization are not fully understood. In an effort to identify bacterial factors that confer susceptibility or resistance to SP-A, we used comparative signature-tagged mutagenesis to screen a library of 1,680 Pseudomonas aeruginosa mutants for evidence of differential pulmonary clearance in SP-A-sufficient (SP-A) and SP-A-deficient (SP-A) mice. Two SP-A-sensitive P. aeruginosa mutants harboring transposon insertions in genes required for salicylate biosynthesis (pch) and phosphoenolpyruvate-protein-phosphotransferase (ptsP) were recovered. The mutants were indistinguishable from the parental wild-type PA01 with regard to opsonization by SP-A, but they exhibited increased susceptibility to SP-A-mediated membrane permeabilization. These results suggest that bacterial gene functions that are required to maintain membrane integrity play crucial roles in resistance of P. aeruginosa to the permeabilizing effects of SP-A.

Journal Article↗
PubMed2003

Comprehensive proteomic profiling identifies serum proteomic signatures for detection of hepatocellular carcinoma and its subtypes.

BACKGROUND: Detection of hepatocellular carcinoma (HCC) in patients with chronic liver disease (CLD) is difficult. We investigated the use of comprehensive proteomic profiling of sera to differentiate HCC from CLD. METHODS: Proteomes in sera from 20 CLD patients with alpha-fetoprotein (AFP) <500 microg/L (control group) and 38 HCC patients (disease group) were profiled by anion-exchange fractionation (first dimension), two types (IMAC3 copper and WCX2) of ProteinChip Arrays (second dimension), and time-of-flight mass spectrometry (third dimension). Bioinformatic tests were used to identify tumor-specific proteomic features and to estimate the values of the tumor-specific proteomic features in the diagnosis of HCC. Cross-validation was performed, and we also validated the models with pooled sera from the control and disease groups, serum from a CLD patient with AFP >500 microg/L, and postoperative sera from two HCC patients. RESULTS: Among 2384 common serum proteomic features, 250 were significantly different between the HCC and CLD cases. Two-way hierarchical clustering differentiated HCC and CLD cases. Most HCC cases with advanced disease were clustered together and formed two subgroups that contained significantly more cases with lymph node invasion or distant metastasis. For differentiation of HCC and CLD by an artificial network (ANN), the area under the ROC curve was 0.91 (95% confidence interval, 0.82-1.01; P <0.0005) for all cases and 0.954 (95% confidence interval, 0.881-1.027; P <0.0005) for cases with nondiagnostic serum AFP (<500 microg/L). At a specificity of 90%, the sensitivity was 92%. Both cluster analysis and ANN correctly classified the pooled serum samples, the CLD serum sample with increased AFP, and the HCC patient in complete remission. CONCLUSION: Tumor-specific proteomic signatures may be useful for detection and classification of hepatocellular cancers.

Carcinoma, Hepatocellular↗
PubMed2003

Detection of cystic fibrosis mutations by peptide mass signature genotyping.

BACKGROUND: The diversity of genetic mutations and polymorphisms calls for the development of practical detection methods capable of assessing more than one patient/one nucleotide position per analysis. METHODS: We developed a new method, based on peptide mass signature genotyping (PMSG), for the detection of DNA mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Exons of the gene were amplified, cloned, and expressed in Escherichia coli as peptide fusions, in natural as well as unnatural reading frames. Peptide analytes were purified by immobilized metal affinity chromatography and analyzed by matrix-assisted, laser desorption/ionization time-of-flight mass spectrometry. Synthetic and natural DNA samples with the 25 mutations recommended for CFTR carrier screening (Grody et al. Genet Med 2001;3:149-54) were assessed using the PMSG test for the CFTR gene. RESULTS: Peptide analytes ranged from 6278 to 17 454 Da and varied 30-fold in expression; highly expressing peptides were observed by electron microscopy to accumulate as inclusion bodies. Peptides were reliably recovered from whole-cell lysates by a simple purification method. CFTR mutations caused detectable changes in resulting mass spectrometric profiles, which were >95% reliably detected in blinded testing of replicate synthetic heterozygous DNA samples. Mutation detection was possible with both sample pooling and multiplexing. The PMSG CFTR test was used to determine compound heterozygous mutations in DNA samples from cystic fibrosis patients, which were confirmed by direct DNA sequencing. CONCLUSIONS: The PMSG test of the CFTR gene demonstrates unique capabilities for determining the sequence status of a DNA target by sensitively monitoring the mass of peptides, natural or unnatural, generated from that target.

Cloning, Molecular↗
PubMed2005

High-resolution serum proteomic profiling of Alzheimer disease samples reveals disease-specific, carrier-protein-bound mass signatures.

BACKGROUND: Researchers typically search for disease markers using a "targeted" approach in which a hypothesis about the disease mechanism is tested and experimental results either confirm or disprove the involvement of a particular gene or protein in the disease. Recently, there has been interest in developing disease diagnostics based on unbiased quantification of differences in global patterns of protein and peptide masses, typically in blood from individuals with and without disease. We combined a suite of methods and technologies, including novel sample preparation based on carrier-protein capture and biomarker enrichment, high-resolution mass spectrometry, a unique cohort of well-characterized persons with and without Alzheimer disease (AD), and powerful bioinformatic analysis, that add statistical and procedural robustness to biomarker discovery from blood. METHODS: Carrier-protein-bound peptides were isolated from serum samples by affinity chromatography, and peptide mass spectra were acquired by a matrix-assisted laser desorption/ionization (MALDI) orthogonal time-of-flight (O-TOF) mass spectrometer capable of collecting data over a broad mass range (100 to >300,000 Da) in a single acquisition. Discriminatory analysis of mass spectra was used to process and analyze the raw mass spectral data. RESULTS: Coupled with the biomarker enrichment protocol, the high-resolution MALDI O-TOF mass spectra provided informative, reproducible peptide signatures. The raw mass spectra were analyzed and used to build discriminant disease models that were challenged with blinded samples for classification. CONCLUSIONS: Carrier-protein enrichment of disease biomarkers coupled with high-resolution mass spectrometry and discriminant pattern analysis is a powerful technology for diagnostics and population screening. The mass fingerprint model successfully classified blinded AD patient and control samples with high sensitivity and specificity.

Alzheimer Disease↗