The coding region of GSTP1 gene is preceded by a large CpG-rich region that is frequently affected by methylation. In many cancer types, GSTP1 is affected by hypermethylation and, as a consequence, it has a low expression. The aim of this review is to give an overview on GSTP1 methylation studies with a special focus on liquid biopsy, thus to summarize methods, results, sample types, different diseases, to have a complete information regarding this promising epigenetic biomarker. We used all the most valuable scientific search engines (PubMed, Medline, Scopus and Web of Science) searching the following keywords: GSTP1, methylation, cancer, urine, serum, plasma and blood. GSTP1 is a largely investigated tissue biomarker in several malignancies such as prostate, breast, lung and hepatocellular carcinoma with good performances especially for diagnostic purposes. As a liquid biopsy biomarker, it has been mainly investigated in prostate cancer (PCa) where it showed a high specificity but a low sensitivity; thus, it is recommended in combination with other biomarkers. Despite the large number of published papers and the promising results, GSTP1 has not yet entered the clinical practice even for PCa diagnosis. For this reason, further large and prospective studies are needed to validate this assay.
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http://dx.doi.org/10.1515/cclm-2017-0703 | DOI Listing |
Gene
March 2025
State University of Londrina (UEL), Department of General Biology, Center of Biological Sciences, Londrina, PR 86057-970, Brazil. Electronic address:
Background: Alteration in DNA repair and metabolism genes can affect the maintenance of DNA integrity or xenobiotics metabolism, potentially leading to DNA damage accumulation. The present study investigated the association between polymorphisms in Glutathione S-Transferase Pi 1 (GSTP1, rs1695) and O-6-Methylguanine-DNA Methyltransferase (MGMT, rs2308321) genes with urothelial bladder cancer (UBC) susceptibility and prognosis. Furthermore, the methylation patterns of the promoter region of these genes were analyzed in tumor and non-tumor bladder tissues, besides MGMT gene expression in tumor samples.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Unité Organisation Nucléaire et Oncogenèse, INSERM U993, Institut Pasteur, Université Paris Cité, 75015 Paris, France.
Hepatoblastoma is the most common primary liver malignancy in children, with metabolic reprogramming playing a critical role in its progression due to the liver's intrinsic metabolic functions. Enhanced glycolysis, glutaminolysis, and fatty acid synthesis have been implicated in hepatoblastoma cell proliferation and survival. In this study, we screened for altered overexpression of metabolic enzymes in hepatoblastoma tumors at tissue and single-cell levels, establishing and validating a hepatoblastoma tumor expression metabolic score using machine learning.
View Article and Find Full Text PDFPLoS One
December 2024
School of Mathematics and Statistics, University College Dublin, Dublin, Ireland.
Identifying differentially methylated cytosine-guanine dinucleotide (CpG) sites between benign and tumour samples can assist in understanding disease. However, differential analysis of bounded DNA methylation data often requires data transformation, reducing biological interpretability. To address this, a family of beta mixture models (BMMs) is proposed that (i) objectively infers methylation state thresholds and (ii) identifies differentially methylated CpG sites (DMCs) given untransformed, beta-valued methylation data.
View Article and Find Full Text PDFMol Syst Biol
December 2024
Genomic Epidemiology branch, International Agency for Research on Cancer/World Health Organization (IARC/WHO), Lyon, 69366, France.
Biological mechanisms related to cancer development can leave distinct molecular fingerprints in tumours. By leveraging multi-omics and epidemiological information, we can unveil relationships between carcinogenesis processes that would otherwise remain hidden. Our integrative analysis of DNA methylome, transcriptome, and somatic mutation profiles of kidney tumours linked ageing, epithelial-mesenchymal transition (EMT), and xenobiotic metabolism to kidney carcinogenesis.
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