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PubMed2026

Proteomic and phosphoproteomic profiles of time-dependent dynamic changes in LPS-induced macrophage polarization.

The temporal proteomic and phosphoproteomic reprogramming during early M1 macrophage polarization (0-6 h) remains poorly understood. We performed time-resolved proteomic and phosphoproteomic analyses of LPS-stimulated RAW264.7 macrophages at seven time points within 6 h. Time-clustering of differentially expressed molecules revealed two patterns: initial change with partial recovery, and sustained dysregulation. Upregulated proteins and phosphorylation sites were enriched in the Rho GTPase signaling pathway, T-cell receptor signaling pathway, NF-κB cascade, osteoclast differentiation pathway, and antiviral immune pathway. Downregulated pathways were associated with cell cycle regulation, chromatin remodeling, RNA metabolism, and mRNA processing, indicating resource reallocation to prioritize acute inflammatory responses. Kinase-substrate network analysis confirmed the mitogen-activated protein kinase (MAPK), cyclin-dependent kinase (CDK), protein kinase B (AKT), and ribosomal S6 kinase (RSK) families as core upstream phosphorylation regulators. Integrated analysis revealed synergistic and antagonistic relationships between proteomic and phosphoproteomic changes. This study provides a temporal molecular atlas of M1 polarization, delineating inflammatory signaling dynamics and offering a basis for therapeutic target discovery in inflammatory diseases. SIGNIFICANCE: Macrophage M1 polarization is a central event in innate immune defense against pathogenic invasion, yet its dysregulation is a pivotal driver of the onset and progression of a broad spectrum of inflammation-associated disorders, spanning autoimmune diseases, infectious conditions and inflammatory bone diseases, making the dissection of its molecular regulatory mechanisms an urgent research priority in immunology and translational medicine. Dynamic molecular events within 0-6 h after LPS stimulation are critical for initiating and shaping M1 inflammatory activation, yet systematic time-resolved proteomic and phosphoproteomic profiling remains insufficient.In this study, we comprehensively characterized temporal proteome and phosphoproteome changes at seven consecutive time points during macrophage polarization, clarified two distinct dynamic molecular patterns, identified core signaling pathways and key kinase regulators involved in inflammatory reprogramming, and uncovered the leading role of post-translational phosphorylation modifications in initiating polarization. This work delineates the time-series molecular atlas of early macrophage activation, provides novel insights into the temporal regulatory mechanism of inflammatory signaling networks, and lays a solid experimental foundation for exploring new intervention targets and regulatory nodes in clinical translational research.

Lipopolysaccharides↗
PubMed2024

Combining Data Independent Acquisition With Spike-In SILAC (DIA-SiS) Improves Proteome Coverage and Quantification.

Data-independent acquisition (DIA) is increasingly preferred over data-dependent acquisition due to its higher throughput and fewer missing values. Whereas data-dependent acquisition often uses stable isotope labeling to improve quantification, DIA mostly relies on label-free approaches. Efforts to integrate DIA with isotope labeling include chemical methods like mass differential tags for relative and absolute quantification and dimethyl labeling, which, while effective, complicate sample preparation. Stable isotope labeling by amino acids in cell culture (SILAC) achieves high labeling efficiency through the metabolic incorporation of heavy labels into proteins in vivo. However, the need for metabolic incorporation limits the direct use in clinical scenarios and certain high-throughput experiments. Spike-in SILAC (SiS) methods use an externally generated heavy sample as an internal reference, enabling SILAC-based quantification even for samples that cannot be directly labeled. Here, we combine DIA-SiS, leveraging the robust quantification of SILAC without the complexities associated with chemical labeling. We developed DIA-SiS and rigorously assessed its performance with mixed-species benchmark samples on bulk and single cell-like amount level. We demonstrate that DIA-SiS substantially improves proteome coverage and quantification compared to label-free approaches and reduces incorrectly quantified proteins. Additionally, DIA-SiS proves effective in analyzing proteins in low-input formalin-fixed paraffin-embedded tissue sections. DIA-SiS combines the precision of stable isotope-based quantification with the simplicity of label-free sample preparation, facilitating simple, accurate, and comprehensive proteome profiling.

Isotope Labeling↗
PubMed2004

Mechanism of immune response during immunotherapy.

Tumor immunology embraces an extensive array of biological phenomena that include interactions between neoplastic cells and the innate and adaptive immune response. Among immune cells, T cells have taken the center stage because they can be easily demonstrated to specifically recognize autologous cancer cells. However, their role is limited and other components of the immune response are likely necessary for the completion of cancer rejection. Metastatic melanoma and renal cell carcinoma (RCC) are malignancies strongly predisposed to regress in response to the systemic administration of high-dose interleukin (IL)-2. Several clinical Studies in extensive cohorts of patients have shown that this treatment can induce complete or partial clinical regressions of metastatic disease in 15 to 20% of patients who receive this treatment. Although IL-2 has direct pluri-potent effects on cells with immune and inflammatory function, it remains unexplained which cell subset is implicated in mediating tumor regression. In a quest to characterize the mechanism of action of IL-2 during the course of immunotherapy, we have investigated the early changes in transcriptional profiles of circulating mononuclear cells and microenvironment of melanoma metastases following high dose IL-2 administration (720,000 IU/kg) by serial sampling of blood cells and tumors in the form of fine needle aspirate (FNA). Furthermore, studies are currently ongoing to characterize the proteomic profiling of RCC patients undergoing the same treatment using protein arrays (manuscript in preparation). The predominant activation of genes related to inflammation and activation of mononuclear phagocytes lead us to further characterize this cell subset in the context of stimulation with a panel of soluble factors potentially present in the circulation and tumor microenvironment.

Antibody Formation↗
PubMed2004

Sperm proteome mapping of a patient who experienced failed fertilization at IVF reveals altered expression of at least 20 proteins compared with fertile donors: case report.

The aim of this study was to compare the sperm protein expression profile (proteome map) from a patient who experienced failed fertilization at IVF with fertile controls. One patient and three fertile donor sperm samples were characterized using two-dimensional electrophoresis. Differences in protein expression were established using gel analysis software before attempted protein identification. Gel analysis of the fertile donor proteome maps revealed excellent reproducibility as well as very low intra-donor and inter-donor variability in the presence of protein spots. In the patient samples, we have noted 20 consistent differences in protein expression (six spots missing, three additional spots, four less abundant, seven more abundant) compared with the controls. Two proteins that were more intense in the patient have been conclusively identified as secretory actin-binding protein and outer dense fibre protein 2/2. In conclusion proteome variation between different fertile donors was very low. In contrast, the patient proteome exhibited 20 differences compared with controls, which we believe is an underestimate. These proteins merit further investigation to determine whether failed fertilization at IVF might be caused by abnormalities in their expression. This case report represents a proof of principle that proteomics may be useful to study defects in sperm function.

Case-Control Studies↗
PubMed2006

Role of proteomics in translational research in cervical cancer.

Cervical cancer is one of the leading causes of cancer morbidity and mortality in women worldwide. More than 98% of cases are related to a human papillomavirus (HPV) infection. Infection with specific subtypes of HPV has been strongly implicated in cervical carcinogenesis. The identification and functional verification of host proteins associated with HPV E6 and E7 oncoproteins may provide useful information for understanding cervical carcinogenesis and the development of cervical cancer-specific markers. In addition, proteomic profiling of altered proteins by anticancer drugs on cervical cancer cells may contribute to providing the fundamental resources for investigation of disease-specific target proteins, elucidation of the novel mechanisms of action and development of new drugs. The advent of proteomics has provided the hope of discovering novel biological markers for use in the screening, early diagnosis and prediction of response to therapy. This review describes the studies where profiles of protein expression in cervical cancer have been generated.

Antineoplastic Agents↗
PubMed2025

Relationships between childhood adversity, resilience, and inflammatory profiles in Taiwanese young adults.

Psychological resilience is the capacity to withstand and bounce back from stressors, trauma, and negative life events, such as childhood adverse experiences (ACEs). Yet, little is known about the biological mechanisms by which resilience mitigates the psychological effects of ACEs. We aimed to identify differentially expressed proteins (DEPs) that reflect the combined effects of early life stress and psychological resilience by using an inflammatory proteomics panel. Three different resilience and ACE questionnaires were employed to classify participants into four groups according to high vs. low levels of resilience and ACEs. Forty-five age-matched and sex-matched participants were selected for proteomics profiling with Olink's 92-protein inflammatory panel. Of these, only 32 passed quality control filtering for analysis. Results showed that CD274 emerged as a protein hub in resilient profiles, while CXCL5 was central to ACE-related profiles. Network co-expression analysis revealed group-specific protein rewiring, suggesting dysregulated inflammation in individuals with high ACE. In contrast, high-resilience profiles showed stronger immune checkpoint co-expression, indicating more effective inflammatory resolution as a key trait of resilience. These findings suggest that resilience maintains an adaptive immune network architecture that may be leveraged to promote resilience after early adversity.

Humans↗
PubMed2004

Chemical probes and tandem mass spectrometry: a strategy for the quantitative analysis of proteomes and subproteomes.

Quantitative proteome profiling using mass spectrometry and stable isotope dilution is being widely applied for the functional analysis of biological systems and for the detection of clinical, diagnostic or prognostic marker proteins. Because of the enormous complexity of proteomes, their comprehensive analysis is unlikely to be routinely achieved in the near future. However, in recent years, significant progress has been achieved focusing quantitative proteomic analyses on specific protein classes or subproteomes that are rich in biologically or clinically important information. Such projects typically combine the use of chemical probes that are specific for a targeted group of proteins and may contain stable isotope signatures for accurate quantification with automated tandem mass spectrometry and bioinformatics tools for data analysis. In this review, we summarize technical and conceptual advances in quantitative subproteome profiling based on tandem mass spectrometry and chemical probes.

Amino Acids↗
PubMed2002

Genomics to fluxomics and physiomics - pathway engineering.

Developments in microanalytical methods are enabling quantitative measurement of multiple metabolic fluxes and, in conjunction with transcript and proteomic profiling, are revolutionizing the ability of researchers to manipulate metabolism through pathway engineering in a variety of species. We review recent literature on the advances in genomics, proteomics, fluxomics and computational modeling focused on metabolic pathway engineering applications.

Bacteria↗
PubMed2006

Contribution of genomics and proteomics in understanding the role of modifying factors in Parkinson's disease.

Parkinson's disease (PD) is a complex neurological disorder, characterized by selective degeneration of nigrostriatal dopaminergic neurons. It is a multi-factorial disease, contributed by a combination of age, genetic and environmental factors. Etiology of sporadic PD and mechanism underlying selective loss of dopaminergic neurons has not yet been clearly understood. Recent developments in genomics and proteomics have revolutionized the research on PD at genetic level. Differential gene expression patterns (DNA biochip technology), age-dependent complex genetic patterns (SNP genotyping), and protein expression profiles (proteomics) of PD patients have started providing the specific and rigorous molecular explanation and role of modifying factors in PD. Genomics and proteomics are further expected to help in developing biomarkers for diagnosis of early onset PD and also to develop valuable and potential therapeutic strategies for its treatment. In this review, we have discussed the progress made by genomics and proteomics, in understanding the role of modifying factors in PD.

Animals↗
PubMed2006

A systems approach to model metastatic progression.

Proteomic profiling of human disease has seen much early activity with the accessibility of the newest generation of high-throughput platforms and technologies. Nevertheless, the nature of the dynamic physiologic milieu and high dimensionality of the data has complicated major diagnostic and prognostic breakthroughs. Our recent article in Cancer Cell delineates an integrative model for culling a molecular signature of metastatic progression in prostate cancer from proteomic and transcriptomic analyses and shows its facility as a predictor of prognosis. The study leveraged direct proteomic analysis of tumor tissue extracts, differential feature selection characterizing the proteomic alterations of prostate cancer subclasses, and integration with public and study-derived genomic data to construct a multiplex gene signature representing progression of indolent cancer to aggressive disease. This further predicted clinical outcome in a variety of solid tumors. This review describes the context of the work, the framework for the analysis itself, and a look forward to the promise of this systems approach to human disease.

Computational Biology↗
PubMed2026

Comprehensive multi-post-translational modifications profiling reveals age-associated remodeling in skeletal muscle.

Sarcopenia, characterized by the progressive loss of skeletal muscle mass and function, is a major hallmark of aging. Post-translational modifications (PTMs) play essential roles in regulating protein activity and cellular homeostasis; however, how multiple PTMs are remodeled during skeletal muscle aging remains incompletely characterized. Here, we performed comprehensive multi-layered proteomic profiling of skeletal muscle from young (3-month-old) and aged (24-month-old) mice, systematically quantifying the global proteome together with five major PTMs: acetylation, phosphorylation, N-glycosylation, O-glycosylation, and ubiquitination. In total, we identified 5 337 proteins and mapped thousands of PTM sites, generating an integrated atlas of age-associated proteomic and PTM remodeling in skeletal muscle. Pathway enrichment analyses revealed distinct modification-specific patterns: acetylation and phosphorylation were predominantly associated with metabolic and mitochondrial-related pathways; N-glycosylation was enriched in immune- and secretory pathway-related processes; O-glycosylation was associated with muscle contraction-related pathways; and ubiquitination was preferentially linked to cytoskeletal organization in muscle cells. Correlation analyses further uncovered diverse association patterns among different PTMs across protein- and modification-level datasets. Phosphorylation and ubiquitination exhibited consistent positive associations, whereas acetylation and ubiquitination showed both inverse and concordant co-variation patterns across subsets of proteins. Phosphorylation and O-glycosylation displayed heterogeneous association patterns across different proteins, and acetylation and phosphorylation demonstrated positive correlations with distinct age-associated directional changes across protein subsets. Together, these results provide a comprehensive, multi-dimensional view of age-associated remodeling of the skeletal muscle proteome and multiple PTM layers, offering a valuable resource for understanding molecular alterations accompanying muscle aging and sarcopenia.

Animals↗
PubMed2004

Proteomic signature of human cancer cells.

We assessed proteomic profiles as biomarkers for monitoring cell phenotypes. Protein expression profiles were obtained by fluorescence two-dimensional difference gel electrophoresis (2-D-DIGE), in which quantitative ability is improved by labeling proteins with fluorescent dyes prior to electrophoresis. Integrated protein spot intensities were analyzed by a statistical approach. The proteomic data of two groups of cell lines: (1) adenocarcinoma (AC) cell lines derived from lung, pancreas and colon tissues and (2) lung cancer cell lines with different histological backgrounds, including AC, squamous cell carcinoma and small cell carcinoma, were assessed on the basis of prior biological information. Hierarchical clustering analysis and principal component analysis were used to divide the cell lines into subgroups on the basis of similarities between their protein expression profiles. The majority of cell lines were grouped according to their organ of origin or histological background. A machine-learning algorithm selected 32 protein spots that were responsible for the classification. The results indicate that proteomic data generated by 2-D-DIGE can provide a signature of essential cell phenotypes, suggesting that it might be possible to apply this technique to developing tumor markers that could identify the organ of origin of metastatic tumors and contribute to the differential diagnosis of lung cancer.

Cell Line, Tumor↗
PubMed2001

Two-dimensional gel electrophoresis: a powerful method to elucidate cellular responses to toxic compounds.

Humans are exposed to a variety of environmental toxicants and combinations thereof, and a large number of interacting factors contribute to an individual's risk for disease. Therefore, new strategies in toxicological research are needed for efficient screening of environmental hazards on complex living systems. The rapidly expanding field of proteomics relies heavily upon the use of two-dimensional gel electrophoresis (2-DE) of protein samples. 2-DE is a key separation technique in proteome analysis due to its advantage of simultaneous separation of thousands of proteins at a time, excellent reproducibility, and ability to exhibit post-translational modifications. Therefore, 2-D proteome analysis is becoming a popular method of choice to detect differentially expressed proteins between proteome profiles after exposure to toxicants. The goal of this study was to examine the response of pancreas carcinoma cells to increasing concentrations of the cytotoxic agent daunorubicin (DRC). The proteomic investigation revealed a number of proteins that were up-regulated by DRC treatment, some in a dose-dependent manner. However, these changes were not seen by reverse transcriptase-polymerase chain reaction. The determination of proteome changes following exposure to xenobiotics will aid our understanding of the mechanisms of their toxicity as well as providing the possibility for the establishment of biomarkers that can be used in risk assessment as well as for the identification of individual susceptibility factors.

Adenocarcinoma↗
PubMed2026

Cross-tissue immune profiling of APOE ε4 reveals early dysregulation in Alzheimer's disease.

INTRODUCTION: Apolipoprotein E (APOE) ε4 is the strongest genetic risk factor for late-onset Alzheimer's disease (AD), but its contribution to disease pathogenesis remains incompletely understood. METHODS: Here, we integrate proteomic profiling of plasma (n = 9028), cerebrospinal fluid (n = 1099), dorsolateral prefrontal cortex (n = 720), and superior temporal gyrus (n = 105) to define the immune phenotype associated with APOE ε4. RESULTS: We identify a conserved, allele dose-dependent pro-inflammatory immune protein signature across peripheral and central tissues independent of AD diagnosis. This signature also emerges in patient-derived cortical organoids prior to amyloid beta and tau pathology, supporting a genotype-driven mechanism. Cross-tissue comparisons reveal shared innate and antiviral responses alongside tissue-specific immune signaling. Notably, a 12-week medical ketogenic diet partially reversed the APOE ε4 immune signature. DISCUSSION: These findings position immune dysregulation as an early and tractable driver of AD risk in APOE ε4 carriers with direct implications for targeted prevention strategies.

Humans↗
PubMed2006

Proteomic analysis of injured spinal cord tissue proteins using 2-DE and MALDI-TOF MS.

Spinal cord injury (SCI) induces a progressive pathophysiology affecting cell survival and neurological integrity via complex and evolving molecular cascades whose interrelationships are not fully understood. Acute injury to the spinal cord undergoes sequential pathological change including hemorrhage, edema, axonal and neuronal necrosis, and demyelination. In the present study, we aimed to establish the proteomic profiles and characterization of the total protein expressed in traumatic injured spinal cord tissue by using 2-DE and matrix assisted laser desorption/ionization-TOF MS (MALDI-TOF MS). We performed proteomic analysis using 2-DE and MS to describe total proteins and differential proteins expression between normal and traumatic injured spinal cord tissues. The study discovered 947 total proteins and analyzed 219 and 270 proteins from normal and injured tissue, respectively. After 24 h of traumatic damage induction, the injured spinal cord tissue up-regulated over 39 proteins including neurofilament light chain, annexin 5, heat shock protein, tubulin beta, peripherin, glial fibrillary acidic protein delta, peroxiredoxin 2, and apolipoprotein A. Twenty-one proteins showed reduction. The majority of the modulated proteins belonged to the 13 functional categories. Proteins that were identified with neural functional category in injured tissue were considered most likely to be involved in wound healing response coupled with neurogenesis and gliogenesis.

Animals↗
PubMed2005

Advances in clinical cancer proteomics: SELDI-ToF-mass spectrometry and biomarker discovery.

For most cancers, survival rates depend on the early detection of the disease. So far, no biomarkers exist to cope with this difficult task. New proteomic technologies have brought the hope of discovering novel early cancer-specific biomarkers in complex biological samples and/or of the setting up of new clinically relevant test systems. Novel mass spectrometry-(MS) based technologies in particular, such as surface-enhanced laser desorption/ionisation time of flight (SELDI-ToF-MS), have shown promising results in the recent literature. Here, proteomic profiles of control and disease states are compared to find biomarkers for diagnosis. This paper aims to address the authors' own work and that of other groups in clinical cancer proteomics based on SELDI-ToF-MS. Shortcomings and hopes for the future are discussed.

Biomarkers, Tumor↗
PubMed2026

Epithelial-Mesenchymal Transition Shapes the Lipotoxic Response of Colon Cancer Cells to Palmitic Acid.

Saturated fatty acids such as palmitic acid (PA) can induce lipotoxic stress, whereas monounsaturated fatty acids like oleic acid (OA) often promote adaptive responses through lipid droplets (LDs) formation. Here, we reveal that epithelial-mesenchymal transition (EMT) profoundly influences the lipotoxic response of colorectal cancer cells. Using the epithelial-like HCT15 and mesenchymal-like HCT116 cell lines, we combined proteomic, metabolic, and imaging analyses to elucidate how EMT status determines lipid storage capacity and resistance to PA-induced toxicity. A basal proteomic profiling highlighted a striking divergence in metabolic changes: HCT15 cells displayed enhanced glycolysis and reduced expression of LDs biogenesis proteins, while HCT116 cells exhibited oxidative metabolism and a "lipid-rich" proteomic signature enriched in PLIN2, GPAT3, and DGAT1. Functionally, PA triggered massive cytotoxicity and failed to induce LDs in HCT15 cells, correlating with DGAT1/2 downregulation and suppressed triacylglycerol synthesis. In contrast, HCT116 cells showed modest LDs accumulation, preserved mitochondrial function, and strong resistance to lipotoxic stress. OA treatment restored LDs formation and cell viability in both models, underscoring the protective role of unsaturated fatty acids. Notably, forced EMT induction in HCT15 cells by PMA markedly enhanced LDs accumulation and reduced PA-induced death, confirming that EMT confers metabolic plasticity and lipid-buffering capacity. These findings demonstrate that EMT status modulates differential lipid handling and stress adaptation in colon cancer cells, linking mesenchymal transition to enhanced LDs biogenesis and survival under lipotoxic conditions. Data are available via ProteomeXchange with identifier PXD071641.

Humans↗
PubMed2006

Proteomic analysis of differential protein expression in early process of pancreatic regeneration in pancreatectomized rats.

AIM: A broad-range proteomic approach was applied to investigate the complexity of the mechanisms involved in pancreatic regeneration for identification of new targets of diabetes treatment and potential markers of pancreatic stem cells. METHODS: A regeneration pancreatic model was induced by 90% partial pancreatectomy (Px) in rats. Changes in the protein expression in regenerating rat pancreas on the third day after Px, as compared with rats that received sham surgery, were analyzed by using 2-D gel electrophoresis (2-DE), mass spectrometry (MS), and mass fingerprinting. RESULTS: 2-DE revealed 91 spots with at least 1.5-fold increases in expression at 3 d after pancreatectomy and 53 differentially expressed proteins that were identified by peptide mass fingerprinting (PMF). These included cell growth-related, lipid and energy metabolism-related, protein and amino acid metabolism-related proteins, and signal transduction proteins. Vimentin, CK8, L-plastin, hnRNP A2/B1, and AGAT are associated with embryogenesis and cell differentiation, and may be new potential pancreatic stem cells markers. CONCLUSION: The proteome profiling technique provided a broad-based and effective approach for the rapid assimilation and identification of adaptive protein changes during pancreas regeneration induced by pancreatectomy. Our data clarify the global proteome during the pancreatic proliferation and differentiation processes, which is important for better understanding of pancreatic regeneration and for discovering of protein biomarkers for pancreatic stem cells.

Amidinotransferases↗