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PubMed2025

Transcriptomics-based exploration of ubiquitination-related biomarkers and potential molecular mechanisms in laryngeal squamous cell carcinoma.

BACKGROUND: One of the most common and prevalent cancers is laryngeal squamous cell carcinoma (LSCC), which poses a great threat to the life and health of the patient. Nonetheless, it has been demonstrated that ubiquitination is crucial for the development and course of LSCC. Therefore, it is particularly important to identify biomarkers for ubiquitination-related genes (UbRGs) in LSCC. METHODS: Differentially expressed genes (DEGs) in the LSCC versus controls were obtained by differential expression analysis. Also, key modular genes associated with LSCC were obtained using weighted gene co-expression network analysis (WGCNA). Next, DEGs, key module genes, and UbRGs were taken to intersect to obtain candidate genes. And then machine algorithms were to screen potential biomarkers, further their diagnostic value were analyzed and validated. Then, therapeutic agents for biomarkers were predict. In addition, the regulatory networks of the biomarkers were mapped. The expression levels of biomarkers were detected in clinical samples using reverse transcription-quantitative PCR (RT-qPCR). RESULTS: A total of eight candidate genes were acquired by the overlap 1,911 DEGs, the key modular genes of WGCNA, and 1,393 UbRGs. A sum of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) were identified by two machine learning, then these four biomarkers were validated in GSE127165 and the expression trend was consistent with TCGA-LSCC, they were recorded as biomarkers. Moreover, the accuracy of the biomarkers in predicting clinical aspects of LSCC was confirmed by the receiver operating characteristic (ROC) curves. Subsequently, cancers such as malignant neoplasms, colorectal cancers, tumors, and primary malignant neoplasms were significantly associated with the biomarkers, which further suggests that these four biomarkers were strongly associated with cancer. Meanwhile, the drugs garcinol, cocaine, and triazolam, among others, used for LSCC treatment were predicted. Finally, transcription factors (TFs) (BRD4, MYC, AR, and CTCF) were predicted to regulate the biomarkers. RT-qPCR assays illustrated that the expression trends of KAT2B, LNX1 and NBEAL2 remained consistent with the dataset. CONCLUSION: The identification of four biomarkers (WDR54, KAT2B, NBEAL2 and LNX1) associated with UbRGs could ultimately serve as a predictive clinical diagnosis of LSCC and provide insight into the molecular mechanisms of LSCC.

Humans↗

PubMed2026

Proteomic Analysis Identifies Potential Biomarkers of ELOC -Mutated Renal Cell Carcinoma.

ELOC -mutated renal cell carcinoma (RCC) is a rare tumor with only ∼40 cases reported to date; it shares a molecular background with clear cell RCC (ccRCC) in terms of hypoxia-inducible factor-alpha (HIF-α) protein accumulation. ELOC -mutated RCC is characterized by prominent leiomyomatous stromal growth and a more indolent clinical course compared with ccRCC. In our previous study, whole-genome sequencing of 102 ccRCC cases identified 5 cases of ELOC -mutated RCC. In the present study, we conducted proteomic and immunohistochemical analyses on up to 13 Japanese ELOC -mutated RCCs, including 8 previously reported cases, to elucidate its distinct molecular mechanisms and identify biomarkers that may be useful in distinguishing ELOC -mutated RCC from ccRCC. Proteomic profiling revealed that molecules, including cytokeratin 7, scinderin (SCIN), and sortilin 1 (SORT1), were significantly overexpressed in ELOC -mutated RCC compared with ccRCC. Notably, SCIN and SORT1 emerged as novel potential diagnostic biomarkers for distinguishing ELOC -mutated RCC from ccRCC. The analysis further suggested that ELOC -mutated RCC relies more on oxidative phosphorylation and less on glycolysis than ccRCC. This metabolic shift may be linked to the relative depletion of NAD+ due to the low expression of NAPRT and QPRT. In addition, we observed geographic variation in the disease frequency among different cohorts, with a higher frequency in Japan. Our findings provide novel insights into the pathogenesis of ELOC -mutated RCC and highlight SCIN and SORT1 as potential supportive biomarkers.

Humans↗

PubMed2006

RCA-enhanced protein detection arrays.

There are many instances in which it is desirable to generate profiles of the relative abundance of a multiplicity of protein species. Examples include studies in embryonic development, immunobiology, drug responses, cancer biology, biomarkers, and so on. Microarray formats provide a convenient, high-throughput vehicle for generating such profiles, and the repertoire of proteins that can be measured is growing continuously as larger panels of specific antibodies become available. Here we describe methods for the use of antibody microarrays, whereby the detection of specifically bound antigens is enhanced by rolling circle amplification (RCA). RCA-enhanced protein detection on antibody microarrays provides a means for rapid protein profiling at high sensitivity. The set of RCA reagents remains unchanged for different microarray formats and compositions, and signal readout is performed using standard fluorescent dyes and scanners. The method is sensitive enough for the most challenging applications, such as the detection of low-abundance components of human serum.

Animals↗

PubMed2006

Profiling alternatively spliced mRNA isoforms for prostate cancer classification.

BACKGROUND: Prostate cancer is one of the leading causes of cancer illness and death among men in the United States and world wide. There is an urgent need to discover good biomarkers for early clinical diagnosis and treatment. Previously, we developed an exon-junction microarray-based assay and profiled 1532 mRNA splice isoforms from 364 potential prostate cancer related genes in 38 prostate tissues. Here, we investigate the advantage of using splice isoforms, which couple transcriptional and splicing regulation, for cancer classification. RESULTS: As many as 464 splice isoforms from more than 200 genes are differentially regulated in tumors at a false discovery rate (FDR) of 0.05. Remarkably, about 30% of genes have isoforms that are called significant but do not exhibit differential expression at the overall mRNA level. A support vector machine (SVM) classifier trained on 128 signature isoforms can correctly predict 92% of the cases, which outperforms the classifier using overall mRNA abundance by about 5%. It is also observed that the classification performance can be improved using multivariate variable selection methods, which take correlation among variables into account. CONCLUSION: These results demonstrate that profiling of splice isoforms is able to provide unique and important information which cannot be detected by conventional microarrays.

Algorithms↗

PubMed2025

Molecular profiling of exhaled breath condensate in respiratory diseases.

BACKGROUND: Respiratory disorders, , continue to pose a major global health burden. Their complexity and heterogeneity challenge accurate diagnosis, effective monitoring, and therapeutic decision-making. Exhaled breath condensate (EBC) provides a reliable, non-invasive means of sampling the molecular environment of the airways. AIM: This review presents the state-of-the-art in EBC-based omics approaches-particularly metabolomics and proteomics-to characterize molecular signatures associated with chronic respiratory (e.g. asthma, chronic obstructive pulmonary disease, and rhinitis) and infectious diseases (e.g. COVID-19). RESULTS: We critically examine findings from studies applying nuclear magnetic resonance (NMR), mass spectrometry (MS), and sensor-based technologies to analyze EBC across various respiratory conditions. NMR, valued for its reproducibility and minimal sample preparation, consistently discriminates among disease phenotypes, identifies distinct metabotypes, and monitors treatment response over time. MS-based approaches afford enhanced sensitivity and specificity, enabling detailed profiling of inflammatory mediators, such as lipid-derived eicosanoids and amino acid derivatives. Proteomic studies reveal protein-level alterations associated with inflammation and tissue remodeling. In COVID-19 and long COVID, metabolomic and volatile compound profiling distinguishes affected individuals from healthy controls suggesting clinical potential. However, inconsistent sample processing and lack of analytical standardization remain limiting factors. CONCLUSIONS: EBC profiling shows clear promise for improving diagnosis, monitoring, and stratification in respiratory medicine. Yet, translation into clinical practice is hindered by limited standardization and validation. Broader, longitudinal studies will be essential to establish robust molecular signatures across disease states. This review underscores the timely need to implement breathomics investigations to gain mechanistic insight into the underlying biology of respiratory diseases.

Humans↗

PubMed2005

Mass spectrometry-based expression profiling of clinical prostate cancer.

The maturation of MS technologies has provided a rich opportunity to interrogate protein expression patterns in normal and disease states by applying expression protein profiling methods. Major goals of this research strategy include the identification of protein biomarkers that demarcate normal and disease populations, and the identification of therapeutic biomarkers for the treatment of diseases such as cancer (Celis, J. E., and Gromov, P. (2003) Proteomics in translational cancer research: Toward an integrated approach. Cancer Cell 3, 9-151). Prostate cancer is one disease that would greatly benefit from implementing MS-based expression profiling methods because of the need to stratify the disease based on molecular markers. In this review, we will summarize the current MS-based methods to identify and validate biomarkers in human prostate cancer. Lastly, we propose a reverse proteomic approach implementing a quantitative MS research strategy to identify and quantify biomarkers implicated in prostate cancer development. With this approach, the absolute levels of prostate cancer biomarkers will be identified and quantified in normal and diseased samples by measuring the levels of native peptide biomarkers in relation to a chemically identical but isotopically labeled reference peptide. Ultimately, a centralized prostate cancer peptide biomarker expression database could function as a repository for the identification, quantification, and validation of protein biomarker(s) during prostate cancer progression in men.

Biomarkers, Tumor↗

PubMed2025

Demonstrating the potential of untargeted hair proteomics for personalized biomarkers in stress-associated disorders.

Biomarker research in psychopathology increasingly employs high-dimensional Omics approaches. Yet, proteomics based on human hair remain largely unexplored, despite its potential to efficiently capture stable biological signals accumulated over weeks to months. This study leveraged machine learning to investigate the potential of the hair proteome-all detectable peptides and proteins-as a biomarker source for stress-associated psychopathology. We analyzed protein profiles from hair segments of women with non-suicidal self-injury disorder and healthy controls (N = 68). Of 1114 identified proteins, 611 were sufficiently abundant for analyses. Partial Least Squares Discriminant Analysis achieved stable 84.4 % cross-validated accuracy for classification of clinical groups (p < .001), outperforming models based on data-derived clusters (60 %), stress-related proteins (73 %), and simulated hair cortisol from meta-analytic effect sizes (53-59 %). Predicted class probabilities strongly correlated with clinical symptoms and well-being (r > .60). Key predictive proteins were linked to pain perception, oxidative stress, and cholesterol homeostasis. Approximately 15 % of proteins differed significantly between groups, with the strongest candidates related to ribosomal function-an emerging target in depression. These findings establish hair proteomics as a promising, non-invasive biomarker source for psychiatric research with potential clinical applications in risk assessment and personalized interventions.

Humans↗

PubMed2006

Genomic profiling of hormone-naïve lymph node metastases in patients with prostate cancer.

The progression of organ-confined prostate cancer to metastatic cancer is inevitably fatal. Consequently, identification of structural changes in the genome and associated transcriptional responses that drive this progression is critical to understanding the disease process and the development of biomarkers and therapeutic targets. In this study, whole genome copy number changes in genomes of hormone-naïve lymph node metastases were profiled using array comparative genomic hybridization, and matched primaries were included for a subset. Matched primaries and lymph node metastases showed very similar copy number profiles that are distinct from primary tumors that fail to metastasize.

Biomarkers, Tumor↗

PubMed2005

Levels of PCDDs and PCDFs in Korean river sediments and their detection by biomarkers.

Polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) are a group of toxic halogenated aryl hydrocarbons inducing various physiological disorders against biological organisms. Here, we investigated their levels in sediment samples taken from 12 different rivers in Korea. The levels of PCDD/PCDFs in sediment samples were expressed as concentrations and international TEQ values. Among 17 PCDD/PCDFs selected as target compounds in this study, the 1,2,3,4,7,8-HxCDD and OCDD were found in all river sediments with significant variation in various congener profiles of PCDD/PCDFs in sediments. PCDD/PCDFs could be monitored by sensitive biomarkers using insect immune system. Out of 12 river sediment samples, the biomarkers reported four spots (up, middle, and down Singil sites and Ansan) as putative contamination areas. When comparing both chemical and biological monitoring results, two methods agreed three spots of Singil as contamination areas (above 10ppt levels) as well as six river sediment samples as relatively less-contaminated areas, but differed in the results in Ansan and Miho, probably due to relative non-specificity of biomarkers. Despite some disparity between bio- and chemical monitoring results, the biomarkers can be recommended as a device warning the contamination of dioxins in the environment because of a fast and inexpensive detection method.

Animals↗

PubMed2005

Reliability of human serum protein profiles generated with C8 magnetic beads assisted MALDI-TOF mass spectrometry.

Protein profiling with mass spectrometry is a promising approach for classification and identification of biomarkers; however, there is debate about measurement quality and reliability. Here, we present a pipeline for preprocessing, statistical data analysis and presentation. Serum samples of 16 healthy individuals are used to generate protein profiles with high-resolution MALDI-TOF after isolation of peptides with C8 magnetic beads. Analysis of variance was performed after binning, baseline correction and normalization of the mean spectra. Relative variations in the spectra are expressed as coefficient of variation, which depending on the respective preanalytical variation parameter investigated, was found to range between 0.15 and 0.67 in this study. With this novel method, the reproducibility of our protein profiling procedure could be quantified. We showed that circadian rhythm and the number of freeze-thaw cycles had relatively limited influence on serum protein profiles, whereas the period between collection and serum centrifugation had a more pronounced effect.

Carbon↗

PubMed2026

Integrative genetic and transcriptomic analyses prioritize CDC16 as a candidate marker for gastric cancer.

BackgroundGastric cancer (GC) remains a major cause of cancer-related mortality, and biomarkers for early detection are needed.MethodsStomach and blood expression quantitative trait loci were integrated with two GC genome-wide association studies using Mendelian randomization (MR), Bayesian colocalization, and summary-data-based MR/heterogeneity in dependent instruments (SMR/HEIDI) testing. Bulk and single-cell transcriptomic analyses characterized candidate expression and lesion-associated patterns. CDC16 protein expression was evaluated by immunohistochemistry in 53 paired GC and non-neoplastic tissues, followed by paired and exploratory receiver operating characteristic analyses.ResultsMR prioritized PILRB, CDC16, and GABPB1-AS1; SMR/HEIDI provided complementary support, while colocalization for CDC16 and GABPB1-AS1 was suggestive and model-dependent. Bulk-tissue CDC16 abundance was higher in GC, but the modest TCGA-STAD tumor-normal difference (log2FC = 0.210, FDR = 0.019) was attenuated after proliferation adjustment (log2FC = -0.002, FDR = 0.987), indicating close coupling with proliferative activity. Single-cell analysis localized CDC16 predominantly to epithelial populations, and the proportion of CDC16-detectable epithelial cells increased across lesion categories (ρ = 0.735; permutation P = 0.031). CDC16 H-scores were higher in GC than in paired non-neoplastic tissues (161.15 ± 45.11 vs 102.15 ± 54.50; P < 0.001), with higher cancer-tissue scores in 41 of 53 cases. Exploratory AUC was 0.794 (95% CI, 0.704-0.874; sensitivity, 66.0%; specificity, 79.2%).ConclusionsConvergent genetic, transcriptomic, and protein-level evidence prioritizes CDC16 as a GC-associated candidate tissue marker whose expression is closely linked to proliferative activity. Prospective validation in independent cohorts, including appropriate disease controls and blood-based evaluation, is warranted.

Stomach Neoplasms↗

PubMed2005

Microarray analysis identifies a death-from-cancer signature predicting therapy failure in patients with multiple types of cancer.

Activation in transformed cells of normal stem cells' self-renewal pathways might contribute to the survival life cycle of cancer stem cells and promote tumor progression. The BMI-1 oncogene-driven gene expression pathway is essential for the self-renewal of hematopoietic and neural stem cells. We applied a mouse/human comparative translational genomics approach to identify an 11-gene signature that consistently displays a stem cell-resembling expression profile in distant metastatic lesions as revealed by the analysis of metastases and primary tumors from a transgenic mouse model of prostate cancer and cancer patients. To further validate these results, we examined the prognostic power of the 11-gene signature in several independent therapy-outcome sets of clinical samples obtained from 1,153 cancer patients diagnosed with 11 different types of cancer, including 5 epithelial malignancies (prostate, breast, lung, ovarian, and bladder cancers) and 5 nonepithelial malignancies (lymphoma, mesothelioma, medulloblastoma, glioma, and acute myeloid leukemia). Kaplan-Meier analysis demonstrated that a stem cell-like expression profile of the 11-gene signature in primary tumors is a consistent powerful predictor of a short interval to disease recurrence, distant metastasis, and death after therapy in cancer patients diagnosed with 11 distinct types of cancer. These data suggest the presence of a conserved BMI-1-driven pathway, which is similarly engaged in both normal stem cells and a highly malignant subset of human cancers diagnosed in a wide range of organs and uniformly exhibiting a marked propensity toward metastatic dissemination as well as a high probability of unfavorable therapy outcome.

Animals↗

PubMed2005

Multiplexed analysis of biomarkers related to obesity and the metabolic syndrome in human plasma, using the Luminex-100 system.

BACKGROUND: The complex pathology of disease has sparked the development of novel protein expression profiling techniques that require validation in clinical settings. This study focuses on multiplexed analyses of adipocytokines and biomarkers linked to the metabolic syndrome, diabetes, and cardiovascular disease. METHODS: Multiplexed immunoassays using fluorescent microspheres and the Luminex-100 system were performed on plasma from 80 obese patients (40 with the metabolic syndrome) before and after 6-8 weeks of diet-induced weight loss. Leptin, insulin, C-peptide, monocyte chemoattractant protein-1 (MCP-1), eotaxin, interleukin-8 (IL-8), tumor necrosis factor-alpha (TNF-alpha), and IL-6 concentrations measured with multiplex panels from 3 different manufacturers were compared with results from commercial ELISAs. Detection limits and between- and within-run imprecision were determined for each analyte. Bland-Altman analysis was used to determine agreement between multiplexed immunoassays and ELISAs. RESULTS: Correlation between the Luminex multiplexed assays and ELISAs was good for leptin (Linco), insulin (Linco), MCP-1 (Biosource and Upstate), and eotaxin (Biosource) with correlation coefficients of 0.711-0.895; fair for eotaxin (Upstate) and C-peptide (Linco) with correlation coefficients of 0.496-0.582; and poor for TNF-alpha, IL-8, and IL-6 (Linco, Biosource, Upstate, and R&D) with correlation coefficients of -0.107 to 0.318. Within- and between-run imprecision values for the multiplex method were generally <15%. Relative changes in plasma leptin and insulin concentrations after diet-induced weight loss were similar whether assessed by multiplex assay or ELISA. CONCLUSION: Although this technology appears useful in clinical research studies, low assay sensitivity and poor correlations with conventional ELISA methods for some analytes with very low plasma concentrations should be considered when using the Luminex platform in clinical studies.

Adipose Tissue↗

PubMed2006

Biomarkers of response to preoperative chemoradiation in esophageal cancers.

To identify a panel of biomarkers that predicts response of esophageal cancers to preoperative chemoradiation, our group profiled the gene expression of pretreatment cancer biopsies from patients with esophageal cancer. Six (32%) of these patients had pathologic complete response. All cancers except one that achieved pathologic complete response (83%) clustered in one molecular type (type I), while cancers that achieved less than pathologic complete response with one exception clustered in another molecular type (type II). Activated NF-kappaB was significantly associated with aggressive pathology. These data indicate that expression analysis of a limited set of biomarkers selected from the list of genes that were differentially regulated between the two subtypes can increase predictive power, and suggest that esophageal cancer with activated NF-kappaB may result in poor treatment outcome.

Adenocarcinoma↗

PubMed2006

Proteomics in clinical interventions: achievements and limitations in biomarker development.

Development of toxicological and clinical biomarkers for disease diagnosis, quantification of toxicant/drug responses and rapid patient care are major concerns in modern biology. Even after human genome sequencing, identification of specific molecular signatures for unambiguous correlation with toxicity and clinical interventions is a challenging task. Differential protein expression patterns and protein-protein interaction studies have started unraveling rigorous molecular explanation of multi-factorial and toxicant borne diseases. Proteome profiling is extensively used to investigate etiology of diseases, develop predictive biomarkers for toxicity and therapeutic interventions and potential strategies for treatment of complex and toxicant mediated diseases. In this review, achievements and limitations of proteomics in developing predictive biomarkers for toxicological and clinical interventions have been discussed.

Animals↗

PubMed2005

MIP-1beta, a novel biomarker for in vitro sensitization test using human monocytic cell line.

In order to seek a novel biomarker for predicting skin sensitization, changes in the gene expression profile of THP-1 cells on exposure to 2,4-dinitrochlorobenzene (DNCB), p-phenylenediamine (pPD) and nickel sulfate (Ni) were assessed using oligo-DNA microarrays. While the change in gene expression varied depending on the sensitizers, up-regulation of MIP-1 beta mRNA expression was detected in both DNCB-treated and Ni-treated THP-1 cells. This finding was validated by RT-PCR and confirmed at the protein level by ELISA. Secretion of MIP-1 beta from THP-1 was detected after 24-h treatment with sensitizers such as DNCB, Ni, 2-mercaptobenzothiazole (2-MBT) and cobalt sulfate (Co), while pPD and non-sensitizers such as sodium dodecyl sulfate (SDS) and benzalkonium chloride (BC) had no effect. The use of both MIP-1 beta production and CD86 expression as criteria reduced the number of false-negatives, and the results were in good agreement with those of in vivo assays. MIP-1 beta may be useful as a novel biomarker in in vitro sensitization assay using THP-1 cells, either alone or in combination with known markers.

B7-2 Antigen↗

PubMed2002

Normal, benign, preneoplastic, and malignant prostate cells have distinct protein expression profiles resolved by surface enhanced laser desorption/ionization mass spectrometry.

PURPOSE: The objective of this study was to discover protein biomarkers that differentiate malignant from nonmalignant cell populations, especially early protein alterations that signal the initiation of a developing cancer. We hypothesized that Surface Enhanced Laser Desorption/Ionization-time of flight-mass spectrometry-assisted protein profiling could detect these protein alterations. EXPERIMENTAL DESIGN: Epithelial cell populations [benign prostatic hyperplasia (BPH), prostate intraepithelial neoplasia (PIN), and prostate cancer (PCA)] were procured from nine prostatectomy specimens using laser capture microdissection. Surface Enhanced Laser Desorption/Ionization-time of flight-mass spectrometry analysis was performed on cell lysates, and the relative intensity levels of each protein or peptide in the mass spectra was calculated and compared for each cell type. RESULTS: Several small molecular mass peptides or proteins (3000-5000 Da) were found in greater abundance in PIN and PCA cell lysates. Another peak, with an average mass of 5666 Da, was observed to be up-regulated in 86% of the BPH cell lysates. Higher levels of this same peak were found in only 22% of the PIN lysates and none of the PCA lysates. Expression differences were also found for intracellular levels of prostate-specific antigen, which were reduced in PIN and PCA cells when compared with matched normals. Although no single protein alteration was observed in all PIN/PCA samples, combining two or more of the markers was effective in distinguishing the benign cell types (normal/BPH) from diseased cell types (PIN/PCA). Logistic regression analysis using seven differentially expressed proteins resulted in a predictive equation that correctly distinguished the diseased lysates with a sensitivity and specificity of 93.3 and 93.8%, respectively. CONCLUSIONS: We have shown that the protein profiles from prostate cells with different disease states have discriminating differences. These differentially regulated proteins are potential markers for early detection and/or risk factors for development of prostate cancer. Studies are under way to identify these protein/peptides, with the goal of developing a diagnostic test for the early detection of prostate cancer.

Adult↗

PubMed2002

Application of genomics and proteomics for study of the integrated response to zinc exposure in a non-model fish species, the rainbow trout.

The advent of DNA array technology and proteomics has revolutionised biology by allowing global analysis of cellular events. So far, the benefits from these new techniques have primarily been realised for well-characterised species. These organisms are rarely the most relevant for environmental biology and ecotoxicology. Thus, there is a need to explore new ways to exploit transcriptomics and proteomics for non-model species. In the present study, rainbow trout (Oncorhynchus mykiss) were exposed to a sublethal concentration of waterborne zinc for up to 6 days. The response in gill tissue was investigated by differential screening of a heterologous cDNA array and by protein profiling using Surface Enhanced Laser Desorption/Ionisation (SELDI). The cDNA array, which was a high-density spotted library of cDNA from Fugu rubripes gill, revealed differentially expressed genes related to energy production, protein synthesis, paracellular integrity, and inflammatory response. SELDI analysis yielded seven proteins that were consistently present only in zinc-exposed gills, and four proteins unique to gills from control fish. A further 11 proteins were differentially regulated. Identification of these proteins by bioinformatics proved difficult in spite of detailed information on molecular mass, charge and zinc-binding affinity. It is concluded that these approaches are viable to non-model species although both have clear limitations.

Animals↗