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At least 271 records · Page 15Linked to original sources

Clinical proteomics in inborn errors of metabolism: from biomarker discovery to implementation.

INTRODUCTION: Inborn errors of metabolism (IEMs) are rare, heterogeneous disorders traditionally diagnosed through genetic testing, enzyme assays, and metabolite measurements. However, these tools often do not fully explain phenotypic variability, organ involvement, disease progression, or treatment response. Clinical proteomics provides a complementary functional layer by capturing changes in protein abundance, proteoforms, post-translational modifications (PTM), and biological pathways, offering insights beyond genotype- and metabolite-based approaches. AREAS COVERED: This review examines the role of high-resolution mass spectrometry and computational proteomics in biomarker discovery and clinical decision-making for IEMs. It focuses on their contribution to diagnosis, variant interpretation, patient stratification, and treatment monitoring. Disease-specific applications are discussed, with the strongest evidence in lysosomal storage disorders, mitochondrial diseases, congenital disorders of glycosylation, and selected neurodegenerative or renal metabolic conditions. The literature search was performed in PubMed, Scopus, Web of Science, and Google Scholar, covering peer-reviewed articles available up to 2026, with emphasis on methodological advances and translational applications in clinical proteomics for IEMs. EXPERT OPINION: Proteomics will not replace established diagnostic tools, but it can help address clinically actionable questions in selected contexts. Translation into clinical practice will require standardized workflows, multicenter validation, clinically anchored endpoints, and integration with other omics approaches.

Humans↗

Molecular epidemiology of p53 protein mutations in workers exposed to vinyl chloride.

The production of mutations in cellular tumor suppressor genes such as p53 is involved in the development of many human cancers. These mutations result in the expression of mutant forms of the encoded p53 protein which can potentially serve as a biomarker for this carcinogenic process. Workers exposed to vinyl chloride who are at risk for the development of the sentinel neoplasm angiosarcoma of the liver represent a model population for the study of such a mutant p53 biomarker, since vinyl chloride is known to cause specific p53 mutations in persons with angiosarcoma of the liver. To determine the relation between vinyl chloride exposure and this p53 biomarker, the authors examined serum samples collected between 1987 and 1992 from a cohort of 225 French vinyl chloride workers and 111 unexposed controls (matched according to age, sex, race, smoking, and alcohol drinking) for the presence of mutant p53 protein, using an enzyme-linked immunosorbent assay. Stratification of the exposed workers by quartile of vinyl chloride exposure (in estimated ppm-years) yielded a statistically significant trend of increasing odds ratios for p53 biomarker seropositivity with increasing exposure. These results suggest that this serum biomarker for mutant p53 protein is related to vinyl chloride exposure and may be an early indicator of carcinogenic risk in exposed individuals.

Adult↗

Risk stratification of acute pulmonary embolism.

Acute pulmonary embolism (PE) is a potentially life-threatening condition, with an overall 3-month mortality rate of 15% and with right ventricular failure as the most common cause of early death. Risk stratification facilitates identification of high-risk patients and may be helpful in guiding the initial and long-term management. In patients with massive PE and hemodynamic instability, rapid risk assessment is paramount and bedside echocardiography and multislice chest computed tomography (CT) are useful for identifying patients who may benefit from thrombolysis or embolectomy. Cardiac biomarkers, including troponin and the natriuretic peptides, are sensitive markers of right ventricular function. Low levels of troponin, B-type natriuretic peptide (BNP), and NT-terminal proBNP are all highly sensitive assays for identifying patients with an uneventful clinical course. Multislice chest CT is not only useful to diagnose or exclude PE; it also is useful for risk assessment. A right-to-left ventricular dimension ratio > 0.9 on the reconstructed CT four-chamber view identifies patients at increased risk of early death. This article focuses on risk stratification tools, including the clinical examination, electrocardiography, echocardiography, cardiac biomarkers, and chest CT.

Biomarkers↗

Emerging noninvasive biochemical measures to predict cardiovascular risk.

New predictors of cardiovascular events are needed to improve the accuracy of risk stratification. Such predictors should be easily measurable in the population and potentially modifiable. This review reports on new biomarkers that are closely linked to the pathogenic mechanisms underlying the progression of the atherosclerotic plaque leading to rupture and thrombosis that ultimately precipitate acute clinical events, such as stroke and myocardial infarction. These risk factors have been associated with subclinical or clinical cardiovascular disease in large populations and include markers of lipoprotein and lipid metabolism, vitamin B12 metabolism, fibrinolysis, coagulation, inflammation, infection, endothelial dysfunction, the angiotensin system, and oxidative stress. For other key processes of atherosclerosis and cardiac disease, such as apoptosis or programmed cell death, there are currently no markers that can be measured noninvasively. Atherosclerosis is a multifactorial condition and possibly only a subset of factors are the main determinants of disease in a given patient. A better definition of the cardiovascular risk profile will help to better target primary and secondary prevention. Further epidemiological studies are needed to characterize the actual predictive and clinical value of these new emerging cardiovascular biomarkers.

Biomarkers↗

Molecular screening of cancer: the future is here.

The remarkable growth in our knowledge of the biology of cancer is leading to the identification of previously elusive pathways and networks involved in cancer causation. The development of technologies has played a pivotal role in furthering this understanding and appreciation of the complexity of tumorigenesis, and is advancing efforts to fully grasp the biology and exploit the knowledge for improvements in cancer detection, prevention, and therapy. The future of molecular screening, i.e. detection of risk or cancer via molecular determinants, has never been so close to a reality. Molecular assays employed in cancer detection and therapy are likely to revolutionize cancer treatment through individual-based diagnosis and treatment, i.e. personalized medicine. A number of detection techniques, such as the detection of aberrant DNA and RNA, the presence of auto-antibodies in serum or plasma, and protein profiling, are already in limited use for patient stratification for clinical trials and for predicting drug response.

Autoantibodies↗

Molecular genetics of pediatric central nervous system tumors.

Recent advances in molecular biology have enhanced our understanding of the pathogenesis of brain tumors, particularly in children. The use of molecular diagnostic tools is quickly becoming a standard component in the diagnosis and classification of brain tumors in children, in addition to providing insight leading to treatment stratification and improved outcome prediction. All new protocols involving treatments for brain tumors in children include studies of biomarkers and biologic correlates as a means to identify new targets for therapeutics and possible intervention strategies.

Astrocytoma↗

Identification of biomarkers and potential therapeutic targets for pancreatic cancer by proteomic analysis in two prospective cohorts.

Pancreatic cancer (PC) is the deadliest malignancy due to late diagnosis. Aberrant alterations in the blood proteome might serve as biomarkers to facilitate early detection of PC. We designed a nested case-control study of incident PC based on a prospective cohort of 38,295 elderly Chinese participants with &#x223c;5.7 years' follow-up. Forty matched case-control pairs passed the quality controls for the proximity extension assay of 1,463 serum proteins. With a lenient threshold of p&#xa0;<&#xa0;0.005, we discovered regenerating family member 1A (REG1A), REG1B, tumor necrosis factor (TNF), and phospholipase A2 group IB (PLA2G1B) in association with incident PC, among which the two REG1 proteins were replicated using the UK Biobank Pharma Proteomics Project, with effect sizes increasing steadily as diagnosis time approaches the baseline. Mendelian randomization analysis further supported the potential causal effects of REG1 proteins on PC. Taken together, circulating REG1A and REG1B are promising biomarkers and potential therapeutic targets for the early detection and prevention of PC.

Humans↗

Troponin: an important prognostic marker and risk-stratification tool in non-ST-segment elevation acute coronary syndromes.

Over the past decade, there has been a progressive evolution of cardiac marker testing in patients with acute coronary syndromes (ACS). This has not only resulted in a dramatic shift in how we view the diagnosis of myocardial infarction (MI), but it has also extended the role of cardiac marker testing into risk stratification and guidance of treatment decisions. By the year 2000, the development of highly sensitive and cardiac-specific troponin assays had resulted in a consensus change in the definition of MI, placing increased emphasis on cardiac-marker testing with troponins as the new gold standard. Furthermore, and perhaps more importantly, the role of the troponins as superior markers of subsequent cardiac risk in ACS patients became firmly established. Most recently, the supportive role of these markers in identifying patients with ACS who may derive particular benefit from potent anti-thrombotic and anti-platelet therapy or early invasive treatment strategies has been demonstrated. This paper will review the evolution of these important roles of troponin testing for risk stratification in ACS.

Biomarkers↗

Quantitative real-time RT-PCR of disseminated tumor cells in combination with immunomagnetic cell enrichment.

Detection of disseminated tumor cells in the blood circulation is important in assessing tumor progression. The objective of this examination was to develop a highly specific and sensitive quantitative realtime reverse transcriptase-polymerase chain reaction (qRT-PCR) assay for the detection of relevant tumor-associated transcripts in patients' blood. The qRT-PCR assays detect the human epidermal growth factor receptor 2 (HER2) and CK20 transcripts of two tumor cells spiked into 5 mL of blood after an immunomagnetic tumor cell enrichment. Furthermore, the HER2 assay is only specific when enrichment is included. This procedure is a useful alternative to fluorescence in situ hybridization and immunocytochemistry for gene alteration analysis in human tumors. The analysis of the studied molecular markers of tumor cells in blood may be useful in the detection of disseminated tumor cells as well as for monitoring treatment response, early detection of relapse, and for stratification of patients with carcinoma.

Biomarkers, Tumor↗

[Contemporary view on the plasma natriuretic peptide assessment in the clinical practice].

Plasma natriuretic peptide assessment became a part of the routine clinical practice because of the laboratory methods development. After a brief historical overview of natriuretic peptides discovery, the article focuses on the brain natriuretic peptide (BNP). BNP plays an important role in the pathophysiology of many diseases of cardiovascular system due to its effects on the circulation (natriuresis, diuresis, inhibition of renin-angiotensin system, etc). The authors describe process of BNP synthesis, factors leading to its release into circulation. The main emphasis is done on the clinical significance of BNP and NT-proBNP assessment for the-diagnosis in cardiovascular diseases, risk stratification and monitoring of the treatment.

Biomarkers↗

Targeting RELA and STAT3 regulates TNFRSF10A-mediated apoptosis in a novel apoptosis-based prognostic model for clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal malignancy and remains a major cause of cancer-related mortality worldwide. Although advances in surgery, targeted therapy, and immunotherapy have improved outcomes for patients, reliable biomarkers for predicting prognosis remain limited. Therefore, robust gene-based prognostic models are urgently needed to improve risk stratification and guide individualized treatment strategies. METHODS: We developed a novel prognostic model integrating apoptosis and immune - related genes (AIRGs) to predict overall survival (OS) in patients with ccRCC. RESULT: Using Gene Set Enrichment Analysis (GSEA) combined with least absolute shrinkage and selection operator (LASSO) Cox regression, we identified 7 key prognostic genes, namely, CCR4, TNFRSF10A, TEK, TGFA, CD14, IFITM1, and SEMA3G, that collectively demonstrated strong predictive performance in TCGA cohort with c-index&#x2009;=&#x2009;0.711. Functional enrichment analyses revealed that apoptosis, immune regulation, and multiple oncogenic signaling pathways were significantly associated with the risk score, highlighting the critical role of the tumor microenvironment in ccRCC progression. Transcription factor binding analysis based on the JASPAR database suggested that RELA and STAT3 with scores of 0.829 and 0.951, respectively are potential upstream regulators within the prognostic network, particularly influencing TNFRSF10A expression. External validation using the International Cancer Genome Consortium (ICGC) dataset confirmed the robustness of the prognostic model with c-index&#x2009;=&#x2009;0.612 Furthermore, in vitro experiments demonstrated that RELA and STAT3 regulate TNFRSF10A-mediated apoptotic signaling in ccRCC cells, providing mechanistic support for the bioinformatic findings. CONCLUSION: This study establishes a biologically informed and clinically relevant prognostic framework for ccRCC. Our findings highlight the therapeutic potential of targeting the RELA/STAT3-TNFRSF10A axis and contribute to the advancement of precision medicine in ccRCC.

Humans↗

Kynurenine metabolism-related gene signature for prognostic stratification in hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) remains a major global health burden with high mortality rates and limited therapeutic options. The identification of reliable biomarkers for early diagnosis and prognosis prediction is urgently needed. Kynurenine metabolism, a critical pathway in immune regulation and tumor progression, has been implicated in various cancers. However, its prognostic value in HCC has not been fully elucidated. This study aimed to develop a prognostic risk model based on kynurenine metabolism-related genes (KMRGs) for HCC patients. METHODS: Transcriptomic and clinical data of HCC patients were retrieved from The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) databases. A prognostic risk model was established using least absolute shrinkage and selection operator (LASSO) and Cox regression analyses. Survival analysis and functional enrichment analysis were conducted to validate the predictive performance of the model and to investigate the underlying mechanisms. ALDH8A1 was ultimately identified as a target gene based on survival analysis, and its impact on tumor cell migration was assessed using the HCC cell line. RESULTS: A prognostic model based on seven KMRGs was established. The high-risk group exhibited significantly worse overall survival compared to the low-risk group. Functional enrichment analysis in high-risk patients highlighted significant enrichment in core biological processes, including spliceosome assembly and ribonucleoprotein complex biogenesis. Furthermore, a nomogram integrating the risk score and clinical pathological features was developed, demonstrating moderate predictive performance for HCC prognosis. CONCLUSIONS: This study successfully constructed a prognostic risk model based on seven KMRGs, providing a valuable tool for predicting clinical outcomes in HCC patients. These findings highlight the potential role of kynurenine metabolism in HCC progression and offer new insights for future therapeutic strategies.

ALDH8A1↗

Biomarker-guided selection of intravesical therapy in high-risk non-muscle invasive bladder cancer: A contemporary review.

High-risk non-muscle invasive bladder cancer poses therapeutic challenges, with significant rates of recurrence and progression with standard intravesical bacillus Calmette-Gu&#xe9;rin (BCG) therapy. Current surveillance strategies lack accurate risk stratification models to predict individual treatment response and personalized treatment options. Simultaneously, there are no well-validated alternatives to replace the current gold-standard approach based on clinical and pathologic features. This review examines emerging biomarkers and advanced technologies with the potential to enhance patient selection and personalize intravesical therapy in HR-NMIBC. Artificial intelligence(AI)-driven histopathologic tools, such as the computer histological AI biomarker, have demonstrated the ability to identify non-responders to standard therapy using whole-slide digital pathology images. In parallel, radiomics-enhanced imaging has shown promise in assessing tumor biology and immune microenvironment features predictive of BCG responsiveness. Liquid biopsy, especially urine tumor DNA analysis, is now available in the arsenal to detect minimal residual disease, stratify recurrence risk, and predict treatment response even before clinical or radiographic evidence of recurrence. Tissue-based genomic profiling has also revealed molecular alterations associated with treatment resistance, though additional validation is needed. Together, these next-generation biomarkers may represent a pivotal shift toward precision oncology in bladder cancer and their incorporation into NMIBC future clinical guidelines is both anticipated and necessary.

BCG-unresponsive disease↗

Transcriptomic profiling across stages of non-muscle-invasive bladder cancer identifies fibroblast activation protein-alpha as a stromal biomarker associated with progression.

BACKGROUND: T1 non-muscle-invasive bladder cancer (NMIBC) represents a biologically aggressive subgroup with substantial heterogeneity in recurrence and progression risk. Current clinicopathological risk stratification tools lack sufficient precision to identify patients at the highest risk of progression to muscle-invasive bladder cancer (MIBC). OBJECTIVE: To characterize transcriptomic differences between T1 and&#x2009;<&#x2009;T1 (Ta/Tis) NMIBC and to explore the association of fibroblast activation protein-&#x3b1; (FAP) gene expression with disease progression. METHODS: Transcriptomic profiling was performed on formalin-fixed paraffin-embedded (FFPE) tumor tissue from 66 patients with primary, treatment-na&#xef;ve NMIBC and 5 patients with T2 disease (included for exploratory comparisons). Analyses included differential gene expression, gene set enrichment analysis (GSEA), molecular subtyping, immune cell deconvolution, and evaluation of FAP expression in relation to recurrence and progression. External validation of FAP was conducted in three independent NMIBC cohorts. RESULTS: T1 tumors demonstrated a distinct transcriptomic profile compared with&#x2009;<&#x2009;T1 tumors, characterized by enrichment of cell cycle-related and metabolic pathways and a higher prevalence of aggressive molecular subtypes. Despite these molecular differences, no statistically significant differences in recurrence-free, progression-free, cancer-specific, and overall survival were observed, likely reflecting limited event numbers. Among recurrent tumors, early recurrences (&#x2264;&#x2009;24&#xa0;months) were associated with epithelial-mesenchymal transition signatures. FAP expression increased with tumor stage (p&#x2009;=&#x2009;0.0005) and was associated with progression (p&#x2009;=&#x2009;0.002) and mortality (p&#x2009;=&#x2009;0.01). Patients with tumors in the highest quartile of FAP expression had worse progression-free survival. This association was consistently observed in three external NMIBC cohorts. CONCLUSIONS: T1 NMIBC exhibits distinct transcriptomic features suggestive of increased biological aggressiveness. Elevated FAP expression is reproducibly associated with progression risk across multiple cohorts, supporting its potential role as a biomarker of aggressive disease. Given the limited number of progression events, these findings should be considered hypothesis-generating and warrant prospective validation before clinical implementation.

Humans↗