Liver phosphorylase b kinase (PhK) deficiency (glycogen storage disease type IX), one of the most common causes of glycogen storage disease, is caused by mutations in the PHKA2, PHKB, and PHKG2 genes. Presenting symptoms include hepatomegaly, ketotic hypoglycemia, and growth delay. Clinical severity varies widely. Autosomal recessive mutations in the PHKG2 gene, which cause about 10-15% of cases, have been associated with severe symptoms including increased risk of liver cirrhosis in childhood. We have summarized the molecular, biochemical, and clinical findings in five patients, age 5-16 years, diagnosed with liver PhK deficiency caused by PHKG2 gene mutations. We have identified five novel and two previously reported mutations in the PHKG2 gene in these five patients. Clinical severity was variable among these patients. Histopathological studies were performed for four of the patients on liver biopsy samples, all of which showed signs of fibrosis but not cirrhosis. One of the patients (aged 9 years) developed a liver adenoma which later resolved. All patients are currently doing well. Their clinical symptoms have improved with age and treatment. These cases add to the current knowledge of clinical variability in patients with PHKG2 mutations. Long term studies, involving follow-up of these patients into adulthood, are needed.
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http://dx.doi.org/10.1016/j.ymgme.2013.12.008 | DOI Listing |
Genomics
December 2024
Center for Reproductive Medicine, the Affiliated Qingyuan Hospital (Qingyuan People's Hospital), Guangzhou Medical University, Qingyuan, Guangdong 511518, China; Guangdong Engineering Technology Research Center of Urinary Continence and Reproductive Medicine, the Affiliated Qingyuan Hospital (Qingyuan People's Hospital), Guangzhou Medical University, Qingyuan, Guangdong 511518, China. Electronic address:
Background: Abnormal programmed cell death (PCD) plays a central role in spermatogenic dysfunction. However, the molecular mechanisms and biomarkers of PCD in patients with nonobstructive azoospermia (NOA) remain unclear.
Methods: The genetic conditions of NOA patients were analysed using bulk transcriptomic, single-cell transcriptomic, single nucleotide polymorphism (SNP), and clinical data from multiple centres.
NPJ Precis Oncol
August 2024
Department of Medical Imaging, Tongji Hospital, School of Medicine, Tongji University, Shanghai, 200065, China.
While ferroptosis shows promise in anti-cancer strategy, the molecular mechanisms behind this process remain poorly understood. Our research aims to highlight the regulation of radiotherapy-induced ferroptosis in non-small cell lung cancer (NSCLC) via the NRF2/PHKG2 axis-mediated mechanism. To identify ferroptosis-associated genes associated with radioresistance in NSCLC, this study employed high-throughput transcriptome sequencing and Lasso risk regression analysis.
View Article and Find Full Text PDFMol Cytogenet
May 2024
Hengyang Medical School, University of South China, Hengyang, 421000, China.
Arch Biochem Biophys
May 2023
Research Center of Basic Medicine, Jinan Central Hospital, Shandong University, Jinan, 250013, People's Republic of China; Research Center of Basic Medicine, Jinan Central Hospital, Shandong First Medical University, Jinan, 250013, People's Republic of China. Electronic address:
Ferroptosis is a newly discovered form of regulatory cell death induced by iron-dependent lipid peroxidation. Infection with Helicobacter pylori (H. pylori) is regarded as a high-risk factor for the development of gastric cancer (GC) and is associated with an increase in the levels of reactive oxygen species with activation of oncogenic signaling pathways.
View Article and Find Full Text PDFHeliyon
February 2023
Department of General Surgery, Linhai Hospital of Traditional Chinese Medicine, Linhai, 317000, Zhejiang, China.
Background: This study aimed to identify prognostic signatures to predict the prognosis of breast cancer (BRCA) patients based on a series of comprehensive analyses of gene expression data.
Methods: The RNA-sequencing expression data and corresponding BRCA patient clinical data were collected from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets. Firstly, the differently expressed genes (DEGs) related to prognosis between tumor tissues and normal tissues were ascertained by performing R package "limma".
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