Ligation-Mediated Polymerase Chain Reaction Detection of 8-Oxo-7,8-Dihydro-2′-Deoxyguanosine and 5-Hydroxycytosine at the Codon 176 of the p53 Gene of Hepatitis C-Associated Hepatocellular Carcinoma Patients

Abstract

Molecular mechanisms underlying Hepatitis C virus (HCV)-associated hepatocellular carcinoma (HCC) pathogenesis are still unclear. Therefore, we analyzed the levels of 8-oxo-7,8-dihydro-2′-deoxyguanosine (8-oxodG) and other oxidative lesions at codon 176 of the p53 gene, as well as the generation of 3-(2-deoxy-β-d-erythro-pentafuranosyl)pyrimido[1,2-α]purin-10(3H)-one deoxyguanosine (M1dG), in a cohort of HCV-related HCC patients from Italy. Detection of 8-oxodG and 5-hydroxycytosine (5-OHC) was performed by ligation mediated-polymerase chain reaction assay, whereas the levels of M1dG were measured by chromatography and mass-spectrometry. Results indicated a significant 130% excess of 8-oxodG at –TGC– position of p53 codon 176 in HCV-HCC cases as compared to controls, after correction for age and gender, whereas a not significant increment of 5-OHC at –TGC– position was found. Then, regression models showed an 87% significant excess of M1dG in HCV-HCC cases relative to controls. Our study provides evidence that increased adduct binding does not occur randomly on the sequence of the p53 gene but at specific sequence context in HCV-HCC patients. By-products of lipid peroxidation could also yield a role in HCV-HCC development. Results emphasize the importance of active oxygen species in inducing nucleotide lesions at a p53 mutational hotspot in HCV-HCC patients living in geographical areas without dietary exposure to aflatoxin B1.

Artificial Intelligence Predictive Models of Response to Cytotoxic Chemotherapy Alone or Combined to Targeted Therapy for Metastatic Colorectal Cancer Patients: A Systematic Review and Meta-Analysis

“…Artificial intelligence (AI), a field of computer science that mimics human intelligent behavior and performs tasks that commonly require human intervention, has gained interest in the field of cancer research for its problem solving, decision making and pattern recognition abilities [ 16 ]. Machine learning (ML) and deep learning (DL), two subsets of AI, have emerged as important tools that could effectively improve the field of molecular cancer characterization, from epidemiology [ 17 ], to diagnosis, prognosis and patient classification [ 18 ], with higher performance than traditional approaches [ 19 , 20 , 21 , 22 , 23 , 24 ]. Accumulating evidence suggests that radiomics can be used to study tumor heterogeneity and to predict therapy in CRC [ 25 ].…”

Cruciferous Vegetable Intake and Bulky DNA Damage within Non-Smokers and Former Smokers in the Gen-Air Study (EPIC Cohort)

“…DNA damage, unless fully repaired, can lead to mutations, including in oncogenes and tumor suppressors, initiating the process of carcinogenesis [5]. Moreover, we provide evidence that the generation of DNA damage at a single nucleotide resolution causes characteristic signatures at the site of mutations along the TP53 sequence, indicating a causal relationship between DNA damage and cancer [13,14].…”

Traffic-Related Air Pollution and Ground-Level Ozone Associated Global DNA Hypomethylation and Bulky DNA Adduct Formation

“…They are considered to be a reliable biomarker of carcinogen exposure [7,8] and cancer risk [9,10]. Recently, we indicated that the generation of DNA damage at single nucleotide resolution causes characteristic signatures at the site of mutations along the sequence of the tumor suppressor gene TP53 (TP53), indicating a causal relationship between DNA damage and human cancer [11,12]. In addition to genotoxic effects, air pollution can cause various epigenetic alterations, as on the levels of DNA methylation and non-coding RNA transcripts [1], important regulators for gene transcription [13].…”