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At least 217 records · Page 12Linked to original sources
PubMed2002

Barrett esophagus.

A number of publications have provided valuable insight into and data on the epidemiology, pathogenesis, diagnosis, risk factor evaluation, and treatment of patients with Barrett esophagus. Although the incidence of esophageal adenocarcinoma has rapidly increased over the past two decades, it is not clear whether there has been a parallel increase in the frequency of Barrett esophagus. The issue of surveillance endoscopy in patients with Barrett esophagus remains controversial; prospective data are still lacking. Bile reflux plays an important role in the pathogenesis of Barrett esophagus; however, this usually occurs in the presence of acid. Newer technology and techniques, including chromoendoscopy, magnification endoscopy, optical coherence tomography, and spectroscopy, have opened the field by providing a more accurate and "nonbiopsy" diagnosis of intestinal metaplasia and dysplasia. The field of biomarkers remains continues to expand and is providing insight into risk stratification of patients with Barrett esophagus. The exact role of acid suppression in patients with this premalignant disease remains controversial, and endoscopic therapies appear promising.

Journal Article↗
PubMed2026

Leveraging single-cell and spatial omics for brain tumour insights to improve therapeutic strategies.

Single-cell and spatial omics (SPOs) technologies have advanced how healthcare physicians characterise brain tumours by enabling detailed understanding of their cellular architecture, functional states, and microenvironmental dynamics. These approaches provide high-resolution detection of tumour heterogeneity and allow precise analysis of the brain tumour microenvironment. Their application has also led to the discovery of novel biomarkers used for early brain tumour detection, prognosis, and improved tumour stratification. Furthermore, integrative multi-omic analyses have revealed new therapeutic targets, clarified mechanisms of drug resistance, and uncovered molecular pathways underpinning treatment failure. By bridging cellular-level insights with spatial context, SPOs hold significant promise for advancing personalised diagnostics, predicting therapeutic response, and guiding the development of targeted interventions for brain tumours. Despite these advances, several limitations constrain the full translational potential of SPOs, including high experimental costs, substantial computational demands, lack of standardised protocols, and challenges in data integration and reproducibility. Addressing these barriers through scalable bioinformatic pipelines, consensus experimental frameworks, and cost-effective platforms remains critical for broadening accessibility and enabling clinical adoption.

Brain Neoplasms↗
PubMed2004

Molecular pathology in oncology--the AstraZeneca perspective.

Growth of the oncology portfolio remains of strategic importance to AstraZeneca, and the adoption of new technologies to allow us to enhance this portfolio is central to this strategy. With the move away from classical hormonal and cytotoxic therapies to the development of more targeted approaches for the treatment of cancer, an understanding of the molecular pathology of the disease state is becoming vital. Our understanding of the pathogenesis of cancer has increased dramatically over the last few decades and with the publication of the human genome and the resultant explosion in the field of genetics and genomics, AstraZeneca is turning its attention to using these new technologies to enhance the oncology R&D platform. In particular, the fields of pharmacogenetics and pharmacogenomics in relation to oncology have received much attention and this has been mirrored externally both within the pharmaceutical/biotechnology and academic sectors. Future products from the AstraZeneca oncology portfolio will increasingly rely on the use of genetics and genomics for patient identification and stratification, whilst these technologies will also provide a source of novel biomarkers and diagnostics that may allow us to streamline the R&D process and help us to better understand the biological basis of the diseases we are aiming to treat. The AstraZeneca perspective is, however, pragmatic enough to appreciate the practical challenges involved in applying pharmacogenetics and genomics not only for early drug development, but also in the organization of the healthcare infrastructure to undertake timely and complex laboratory investigations. Finally, validation of this approach will require carefully controlled clinical studies.

Drug Industry↗
PubMed2026

Integrated multi-omics profiling of amniotic fluid identifies predictive biomarkers for fetal growth restriction trajectories.

BACKGROUND: Fetal growth restriction (FGR) is a complex condition with highly heterogeneous clinical outcomes, making prenatal distinction between transient and persistent growth failure challenging. This study aims to identify amniotic fluid (AF) biomarkers capable of differentiating distinct FGR trajectories and characterizing persistent growth failure mechanisms. METHODS: Integrated proteomic and metabolomic profiling was performed on AF samples from transient FGR (n&#x2009;=&#x2009;11), persistent FGR (n&#x2009;=&#x2009;9), and healthy controls (n&#x2009;=&#x2009;13). Diagnostic and prognostic models were developed using multivariate analysis. Selected protein candidates were validated via ELISA in an independent cohort (n&#x2009;=&#x2009;69). RESULTS: Multi-omics analysis revealed distinct molecular signatures for FGR stratification. A two-protein diagnostic panel (PDGFA and phospho-STAT5A) achieved an AUC of 1.000 in the discovery stage and 0.780 in the external validation cohort. For prognostic assessment, a molecular signature including IREB2, HLA-C, and PLXNB2 accurately predicted persistent growth failure from transient recovery (AUC = 0.966). Cross-platform integration highlighted the mass spectrometry-derived WASHC2C as a central hub protein with a significant progressive increase across the control, transient, and persistent groups (p&#x2009;<&#x2009;0.001). CONCLUSIONS: This study establishes a multi-omics framework for prenatal FGR stratification. Our findings identify distinct molecular&#xa0;signatures reflecting&#xa0;the intrauterine environment and provide high-performance molecular tools for predicting divergent fetal growth trajectories to guide personalized clinical decision-making.

Humans↗
PubMed2026

Human papillomavirus viral load as promising surrogate biomarker of cervical cancer risk and clinical outcome.

INTRODUCTION: Persistent high-risk human papillomavirus (HR-HPV) causes cervical precancerous lesions and cancer. While molecular HPV DNA testing offers superior sensitivity over cytology as a primary screening method, its limited specificity leads to unnecessary follow-up procedures. Therefore, identifying surrogate biomarkers to distinguish transient infections from clinically relevant, persistent ones is essential for improving risk stratification. A comprehensive literature search across PubMed/MEDLINE, Embase, Scopus, and Web of Science databases up to December 2025 identified studies evaluating HR-HPV viral load in cervical lesion progression. AREAS COVERED: Oncogenic HPV viral load, the quantity of HPV genomes in a sample, is a promising biomarker. Levels correlated positively with HR-HPV persistence, increasing the risk of high-grade lesions and invasive cervical cancer. Furthermore, quantification provides prognostic information regarding disease severity, therapeutic response, and post-treatment recurrence. EXPERT OPINION: Recent standardization and validation of multiplex real-time PCR techniques supports integrating HPV viral load into clinical pratice. Incorporating viral load assessment into screening and management algorithms could significantly enhance diagnostic precision, enable personalized follow-up, and guide therapeutic decisions for women with HR-HPV-associated cervical disease. Refining these protocols will ultimately minimize over-treatment while ensuring rigorous monitoring for high-risk patients.

Humans↗
PubMed2026

[Effect of Cancer Antigen-125 Elimination Rate Constant K and BRCA Mutation Status on the Prognosis of Interval Debulking Surgery in Advanced High-Grade Serous Ovarian Cancer].

OBJECTIVE: To investigate the predictive value of the cancer antigen-125 elimination rate constant K (KELIM) for treatment response and prognosis in patients with advanced high-grade serous ovarian cancer (HGSOC) undergoing neoadjuvant chemotherapy followed by interval debulking surgery (NACT-IDS), and to analyze the combined prognostic significance of KELIM and the mutation status of breast cancer susceptibility gene (BRCA). METHODS: A total of 106 patients with advanced HGSOC who had undergone NACT-IDS were retrospectively enrolled. The KELIM values during neoadjuvant chemotherapy were calculated, and patients were divided into high- and low-KELIM groups using a cutoff value of 1.0. Clinicopathological characteristics, R0 resection rates, and platinum sensitivity rates were compared between the two groups. Logistic regression analysis was performed to identify predictive factors for R0 resection, while Kaplan-Meier survival analysis and Cox proportional hazards regression were performed to evaluate factors associated with progression-free survival (PFS). Furthermore, the patients were stratified according to both KELIM and BRCA status to assess the risk of platinum-resistant recurrence in each subgroup. RESULTS: The R0 resection rate was higher in the KELIM &#x2265; 1 group than in the KELIM < 1 group (77.1% vs 55.2%), and the difference was statistically significant (P = 0.024). Multivariate logistic regression analysis showed that KELIM was an independent predictor of R0 resection (odds ratio [OR] = 2.922, 95% CI: 1.112-7.678). Survival analysis demonstrated longer PFS in the KELIM &#x2265;1 group compared with that in the KELIM <1 group (33.0 months vs 18.0 months), and the difference was statistically significant (P < 0.001). Multivariate Cox regression analysis showed that KELIM &#x2265; 1 was associated with a reduced risk of disease progression (hazard ratio [HR] = 0.481, 95% CI: 0.280-0.826). Combined stratification analysis revealed that no platinum-resistant recurrence was observed in the subgroup with both KELIM &#x2265;1 and a BRCA-positive status (0/21). Compared with patients with KELIM <1 and a BRCA-negative status, this subgroup exhibited a lower risk of platinum-resistant recurrence (OR = 0.053, 95% CI: 0.003-0.932, P = 0.006). CONCLUSION: KELIM is an effective dynamic biomarker for predicting surgical outcomes and PFS in patients undergoing NACT-IDS. Combined stratification by KELIM and BRCA status allows more precise identification of the patient population with both KELIM &#x2265;1 and BRCA-positive status, who have an extremely low risk of platinum-resistant recurrence, thereby providing an important basis for individualized treatment and risk stratification management in patients with advanced HGSOC.

Humans↗
PubMed2005

Identifying novel endpoints for cystic fibrosis clinical trials.

Clinical and translational research in cystic fibrosis (CF) is hampered by a lack of biomarkers that can be used to identify promising new therapies. In particular, validated protein biomarkers are needed to evaluate emerging candidate anti-inflammatory and antimicrobial treatments. Noninvasively obtained biomarkers are especially desirable in children where repeatedly sampling the airway is difficult. To more quickly identify and validate candidate protein biomarkers, it will be essential to pursue a phased approach to biomarker development in a large, well-characterized CF patient population. New high-throughput technologies that can simultaneously examine the expression of thousands of genes and proteins are accelerating the discovery of potential biomarkers. It is hoped that individual biomarkers, or more likely a panel of validated markers, will predict clinical outcomes such as susceptibility to rapid disease progression or response to treatment and therefore, greatly improve stratification for future CF clinical trials.

Anti-Inflammatory Agents↗
PubMed2005

[The use of cardiac troponins (T or I) measurement in cardiology and various clinical settings].

Measurement of cardiac troponin I or T in serum (highly specific for the myocardium) have replaced classical markers, such as creatine kinase MB. Cardiac troponins are preferred markers because of their high specificity and sensitivity. This had led to modifications of the original World Health Organization criteria for acute myocardial infarction. Furthermore, the place of the troponins as superior markers of subsequent cardiac risk in acute coronary syndrome has now become firmly established, for both diagnostic and risk stratification purposes. The use of C-reactive protein and/or other inflammatory biomarkers may add independent information in this context. After non cardiac surgery, the total cardiospecificity of cardiac troponins explains why other biomarkers of necrosis should no longer be used. Recent studies suggest that any elevation of troponin in the postoperative period is indicative of increased risk of long-term cardiac complications. This prognostic value has been previously demonstrated in other clinical settings such as invasive coronary intervention (surgical myocardial revascularization and percutaneous coronary intervention) and after heart valve surgery. Increases of troponin indicate cardiac damage, whatever the mechanism (ischemic or not). Other causes of cardiac injury include: pulmonary embolism, myocarditis, pericarditis, congestive heart failure, septic shock, myocardial contusion. In most cases, elevation of troponins has been shown to be associated with a bad outcome.

Anesthesia Recovery Period↗
PubMed2025

Cardiac Troponins and Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis.

BACKGROUND: The extent to which high-sensitivity cardiac troponin can predict cardiovascular disease (CVD) is uncertain. OBJECTIVES: We aimed to quantify the potential advantage of adding information on cardiac troponins to conventional risk factors in the prevention of CVD. METHODS: We meta-analyzed individual-participant data from 15 cohorts, comprising 62,150 participants without prior CVD. We calculated HRs, measures of risk discrimination, and reclassification after adding cardiac troponin T (cTnT) or I (cTnI) to conventional risk factors. The primary outcome was first-onset CVD (ie, coronary heart disease or stroke). We then modeled the implications of initiating statin therapy using incidence rates from 2.1 million individuals from the United Kingdom. RESULTS: Among participants with cTnT or cTnI measurements, 8,133 and 3,749 incident CVD events occurred during a median follow-up of 11.8 and 9.8 years, respectively. HRs for CVD per 1-SD higher concentration were 1.31 (95%&#xa0;CI: 1.25-1.37) for cTnT and 1.26 (95%&#xa0;CI: 1.19-1.33) for cTnI. Addition of cTnT or cTnI to conventional risk factors was associated with C-index increases of 0.015 (95%&#xa0;CI: 0.012-0.018) and 0.012 (95%&#xa0;CI: 0.009-0.015) and continuous net reclassification improvements of 6% and 5% in cases and 22% and 17% in noncases. One additional CVD event would be prevented for every 408 and 473 individuals screened based on statin therapy in those whose CVD risk is reclassified from intermediate to high risk after cTnT or cTnI measurement, respectively. CONCLUSIONS: Measurement of cardiac troponin results in a modest improvement in the prediction of first-onset CVD that may translate into population health benefits if used at scale.

Humans↗
PubMed2005

Inactivation of p16, RUNX3, and HPP1 occurs early in Barrett's-associated neoplastic progression and predicts progression risk.

Patients with Barrett's esophagus (BE) are at increased risk of developing esophageal adenocarcinoma (EAC). Clinical neoplastic progression risk factors, such as age and the length of the esophageal BE segment, have been identified. However, improved molecular biomarkers predicting increased progression risk are needed for improved risk assessment and stratification. Using real-time quantitative methylation-specific PCR, we screened 10 genes (HPP1, RUNX3, RIZ1, CRBP1, 3-OST-2, APC, TIMP3, p16, MGMT, p14) for promoter hypermethylation in 77 EAC, 93 BE, and 64 normal esophagus (NE) specimens. A subset of genes manifesting significant differences in methylation frequencies between BE and EAC was then analysed in 20 dysplastic specimens. All 10 genes except p14 were frequently methylated in EACs, with RUNX3, HPP1, CRBP1, RIZ1, and OST-2 representing novel methylation targets in EAC and/or BE. p16, RUNX3, and HPP1 displayed increasing methylation frequencies in BE vs EAC. Furthermore, these increases in methylation occurred early, at the interface between BE and low-grade dysplasia (LGD). To demonstrate the silencing effect of hypermethylation, we selected the EAC cells BIC1, in which the HPP1 promoter is natively methylated, and subjected them to 5-aza-2'-deoxycytidine (Aza-C) treatment. Real-time RT-PCR indicated increased HPP1 mRNA levels after 3 days of Aza-C treatment, as well as decreased levels of methylated HPP1 DNA. Hypermethylation of a subset of six genes (APC, TIMP3, CRBP1, p16, RUNX3, and HPP1) was then tested in a retrospective longitudinal study of 99 BE and nine LGD specimens obtained from 53 BE patients undergoing surveillance endoscopy. Only high-grade dysplasia (HGD) or EAC were defined as progression end points. Two patient groups were compared: eight progressors (P) and 45 nonprogressors (NP), using Cox proportional hazards models to determine the relative progression risks of age, BE segment length, and methylation events. Multivariate analyses revealed that only hypermethylation of p16 (odds ratio (OR) 1.74, 95% confidence interval (CI) 1.33-2.20), RUNX3 (OR 1.80, 95% CI 1.08-2.81), and HPP1 (OR 1.77, 95% CI 1.06-2.81) were independently associated with an increased risk of progression, whereas age, BE segment length, and hypermethylation of TIMP3, APC, or CRBP1 were not independent risk factors. In combined analyses, risk was detectable up to, but not earlier than, 2 years preceding neoplastic progression. Hypermethylation of p16, RUNX3, and HPP1 in BE or LGD may represent independent risk factors for the progression of BE to HGD or EAC. These findings have implications regarding risk stratification, early EAC detection, and the appropriate endoscopic surveillance interval for patients with BE.

Adenocarcinoma↗
PubMed2002

Oesophageal disorders: future developments.

Elicitation of the characteristic symptom patterns remains the primary approach to the diagnosis of gastro-oesophageal reflux disease, and this may be enhanced by developments in the use of high-resolution endoscopy and oesophageal biopsy. For future therapy, proton pump inhibitors and anti-reflux surgery may compete with reversible acid pump blockers, reflux inhibitor drugs and diverse luminally delivered physical anti-reflux therapies. Short-segment Barrett's oesophagus is known to be highly prevalent, but its impact on the risk of adenocarcinoma remains poorly defined. Biomarkers for Barrett's oesophagus have been proposed to aid in the stratification of cancer risk, and cytology may assume more importance in the future. Endoscopic surveillance for Barrett's oesophagus is widely practised, but more data are needed to demonstrate cost-effectiveness and a positive impact on mortality. Animal and limited human studies suggest that chemoprevention may become an important strategy in reducing the risk of adenocarcinoma. The ablation of Barrett's epithelium results in a reversal of Barrett's epithelium, albeit with an uncertain long-term outcome.

Adenocarcinoma↗
PubMed2026

Pathomics-based machine learning models for predicting METTL5 expression and prognosis in lung adenocarcinoma.

BACKGROUND: METTL5, an N6-methyladenosine (m6A) RNA methyltransferase, has been implicated in tumor progression, but its prognostic value and non-invasive prediction in lung adenocarcinoma (LUAD) remain unclear. This study aimed to develop a pathomics-based machine learning model to predict METTL5 expression from histopathological images and evaluate its prognostic significance in LUAD. METHODS: A total of 327 LUAD patients from The Cancer Genome Atlas (TCGA) with matched hematoxylin and eosin (H&E) slides, transcriptomic, and clinical data were included and randomly divided into training and validation sets (7:3). Quantitative histopathological features were extracted using PyRadiomics. Feature selection was performed via maximum relevance minimum redundancy (mRMR) and recursive feature elimination (RFE), followed by construction of a Gradient Boosting Machine (GBM) model. A pathomics score (PS) was generated to assess prognostic relevance. Survival analyses, gene set variation analysis (GSVA), tumor mutational burden (TMB), immune infiltration analysis, and in vitro functional assays were conducted. RESULTS: METTL5 overexpression was independently associated with poor overall survival [hazard ratio (HR) =1.637, P=0.007]. The model achieved good predictive performance [area under the curve (AUC) =0.847 in the training set and 0.752 in the validation set]. High PS was significantly associated with worse survival and remained an independent prognostic factor (HR =1.563, P=0.03). Elevated PS correlated with altered metabolic pathways, increased TMB, and immune microenvironment changes. METTL5 knockdown reduced proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT) in A549 cells. CONCLUSIONS: The pathomics-based model accurately predicts METTL5 expression and provides prognostic stratification in LUAD, supporting its potential as a practical imaging-derived biomarker.

Methyltransferase-like 5↗
PubMed2026

A stratified urine-based molecular diagnostic and prognostic model for non-muscle-invasive bladder cancer management.

BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) is characterized by a high recurrence rate requiring lifelong cystoscopic surveillance. Existing urine-based molecular assays mainly rely on mutations or methylation, which fail to capture large-scale genomic instability. Copy number variation (CNV) profiling offers complementary information on tumor evolution and aggressiveness, but its application in urinary diagnosis remains limited. We aimed to integrate CNV and DNA methylation signals from urinary DNA to establish a noninvasive and biologically informed stratified diagnostic model for NMIBC recurrence surveillance and risk stratification. METHODS: Urine samples were prospectively collected from 91 patients (75 evaluable) between June 2021 and August 2023. Shallow whole-genome sequencing (sWGS) was used to detect CNVs at chromosomal arm and focal gene levels, while ONECUT2 promoter methylation was quantified by qPCR. Diagnostic and prognostic performance was evaluated by ROC analysis, Kaplan-Meier survival, and stratified recurrence assessment. RESULTS: We evaluated a stratified diagnostic model combining CNV and ONECUT2 methylation testing in a cohort of 79 patients. CNV analysis alone showed high specificity (0.923) for NMIBC diagnosis. A combined model, using CNV as an initial screen followed by ONECUT2 methylation testing in CNV-positive cases, achieved a sensitivity of 0.783, specificity of 0.981, and a negative predictive value (NPV) of 0.911. This approach reduced the number of required ONECUT2 tests by 35% and identified a high proportion of true-negative patients (98.1%), which may help reduce unnecessary cystoscopy procedures. The model also demonstrated significant prognostic value, with the molecularly defined high-risk group showing significantly shorter recurrence-free survival (RFS) than the low-risk group (median RFS: 4.33 months vs. not reached; p&#x2009;<&#x2009;0.001). Additional, in patients with initially negative cystoscopy after urine sample collection, the model demonstrated a predictive accuracy of 0.922 for recurrence, with molecular positivity observed a median of 9.6 months prior to clinical diagnosis. CONCLUSIONS: Integrating CNV and DNA methylation profiling from urinary DNA provides a powerful and noninvasive molecular framework for NMIBC surveillance. By combining early epigenetic changes with genomic instability signals, this approach enhances recurrence risk assessment and enables earlier detection compared with conventional cystoscopy. It offers a practical route toward personalized and adaptive post-treatment monitoring of NMIBC. TRIAL REGISTRATION: NCT04994197.

Humans↗
PubMedDate not supplied

Cardiac biomarkers in the new millennium.

Cardiac disease is the major cause of death in patients with end-stage renal disease (ESRD), accounting for about 45% of all deaths. In dialysis patients about 20% of cardiac deaths are attributed to acute myocardial infarction (AMI). The survival of dialysis patients after AMI is poor, with nearly three-quarters of patients dead at 2 years after AMI. The definition of AMI is based on symptoms, electrocardiography, and cardiac biomarkers. In the non-ESRD population, it has been recognized that sensitive markers of myocardial injury (cardiac troponin I and troponin T) define a group of patients who are increased risk for adverse cardiac outcomes and who are more likely to benefit from treatment. Elevated cardiac troponin levels in nonhospitalized ESRD patients without other evidence of ongoing myocardial ischemia may also prospectively identify a subgroup of ESRD patients at increased risk for death. This editorial is an overview of cardiac biomarkers (specifically troponin I and troponin T) in the management of acute coronary syndromes in ESRD patients. A potential role of cardiac troponin testing for risk stratification in the outpatient dialysis unit is also presented.

Biomarkers↗
PubMed2026

Cancer-associated fusion transcripts: mechanisms, functional roles, and clinical implications.

Fusion transcripts are hybrid RNA molecules generated through genomic rearrangements or RNA-level fusion mechanisms. They represent important molecular features of many cancers and can function as oncogenic drivers, diagnostic biomarkers, prognostic indicators, and therapeutic targets. Since the discovery of the BCR::ABL1 fusion in chronic myeloid leukemia, numerous cancer-associated fusion transcripts have been identified across hematologic malignancies and solid tumors. These fusion events encompass diverse biological mechanisms, including constitutively active kinases, aberrant transcription factors, epigenetic regulators, and non-coding fusion RNAs. This review summarizes current knowledge of the mechanisms underlying fusion transcript formation, including genomic rearrangement-dependent and rearrangement-independent processes, as well as fusion circular RNAs. The functional roles of fusion transcripts in cancer biology and their clinical relevance as diagnostic, prognostic, and predictive biomarkers are discussed. In addition, recent advances in fusion transcript detection and characterization are reviewed, including next-generation sequencing, long-read sequencing, single-cell approaches, artificial intelligence-assisted computational methods, and CRISPR/Cas9-mediated strategies for functional modeling and functional validation of fusion transcripts. Despite the rapid expansion of fusion transcript catalogs, the biological and clinical significance of most identified fusion events remains incompletely understood. Future progress will depend on integrating advanced sequencing technologies, artificial intelligence-assisted computational prioritization, and systematic functional validation to distinguish clinically actionable fusion transcripts from biologically neutral events. Such multidisciplinary approaches will be essential for translating fusion transcript research into precision oncology and improving cancer diagnosis, patient stratification, and targeted therapy.

Humans↗