Serum activities of alanine- and aspartate aminotransferases (ALT and AST) are considered the "gold standard" biomarkers of hepatocyte injury in clinical practice and drug development. However, due to the expression of ALT and AST in myocytes, the diagnosis of hepatocellular injury in patients with underlying muscle diseases, including drug-induced muscle injury, is severely limited. Thus, we proposed glutamate dehydrogenase (GLDH) as a liver-specific alternative to serum ALT and AST. In fact, our exploratory studies showed that GLDH has comparable performance to ALT for detecting hepatocyte injury without interference from concomitant muscle injury. Here, we report the results of studies confirming the reference intervals in a healthy human population and the sensitivity and specificity of GLDH for the detection of hepatocyte injury in human subjects. In human subjects, we could not perform liver biopsies due to ethical reasons; we also confirmed the relationship of GLDH and histopathologic lesions using 32 model toxicants in rats. Furthermore, we have shown that injury to tissues that are known to express appreciable levels of GLDH does not affect serum GLDH measurements, indicating excellent liver specificity of serum GLDH. Finally, we observed faster elimination of GLDH than ALT in humans, indicating that decreasing GLDH values could be considered an early sign of recovery. This study provides comprehensive evidence of excellent sensitivity and liver specificity of GLDH for diagnosis of hepatocellular injury, including evaluation of reference intervals, which is essential for the interpretation of serum GLDH in human subjects.
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11775418 | PMC |
Front Oncol
January 2025
Hepatobiliary and Echinococcosis Surgery Department, Digestive and Vascular Surgery Center, First Affiliated Hospital of Xinjiang Medical University, Urumqi, China.
Background: Nanotechnology has increasingly been applied in the diagnosis and treatment of hepatocellular carcinoma (HCC) over the past two decades. This study aims to explore the utilization of nanotechnology in HCC through a bibliometric analysis, identifying key themes, trends, and contributions in this field.
Methods: The study utilized VOSviewer and CiteSpace software to perform a bibliometric analysis, evaluating scholarly contributions related to nanotechnology in HCC.
Biochem Biophys Rep
March 2025
Department of Biochemistry, North Eastern Hill University, Shillong, India.
Hepatocellular carcinoma (HCC) is the most fatal cancer that has affected both male and female populations globally. With poor diagnosis and patient survival rates, it has become a global need for scientists to come to the aid. The main objective of the study was to profile the miRNAs in the serum of Control and DEN-treated mice at different time intervals (4 Weeks, 8 Weeks, 12 Weeks, and 16 Weeks) and identify HCC-associated miRNA as putative early biomarkers along with the miRNA regulated candidate gene which may be involved in HCC.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Machine Learning, Moffitt Cancer Center, Tampa, FL, USA.
AI decision support systems can assist clinicians in planning adaptive treatment strategies that can dynamically react to individuals' cancer progression for effective personalized care. However, AI's imperfections can lead to suboptimal therapeutics if clinicians over or under rely on AI. To investigate such collaborative decision-making process, we conducted a Human-AI interaction study on response-adaptive radiotherapy for non-small cell lung cancer and hepatocellular carcinoma.
View Article and Find Full Text PDFInsights Imaging
January 2025
Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, China.
Objectives: To develop and validate radiomics and deep learning models based on contrast-enhanced MRI (CE-MRI) for differentiating dual-phenotype hepatocellular carcinoma (DPHCC) from HCC and intrahepatic cholangiocarcinoma (ICC).
Methods: Our study consisted of 381 patients from four centers with 138 HCCs, 122 DPHCCs, and 121 ICCs (244 for training and 62 for internal tests, centers 1 and 2; 75 for external tests, centers 3 and 4). Radiomics, deep transfer learning (DTL), and fusion models based on CE-MRI were established for differential diagnosis, respectively, and their diagnostic performances were compared using the confusion matrix and area under the receiver operating characteristic (ROC) curve (AUC).
Sci Rep
January 2025
Department of Laboratory Medicine, West China Hospital, Sichuan University, Chengdu, China.
Hepatocellular carcinoma (HCC) is the most prevalent form of liver cancer, and ranks among the most lethal malignancies globally, primarily due to its high rates of recurrence and metastasis. Despite the urgency, no reliable biomarkers currently exist for predicting tumor recurrence in HCC. Telomerase reverse transcriptase (TERT) promoter mutations (TERTpm) and cellular tumor antigen p53 mutations (TP53m) have been frequently documented in HCC, but their combined clinical significance remains undefined.
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