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1.
Eur J Cancer Prev ; 33(1): 73-btii, 2024 Jan 01.
Article in English | MEDLINE | ID: mdl-37401481

ABSTRACT

Glioblastoma is the most aggressive central nervous system primary tumor. Prognosis is poor, mainly due to the malignant characteristics of the tumor, such as high cell proliferation and invasiveness. CDH1 hypermethylation is linked to the invasive potential in various cancer types, but its importance is still unknown in glioblastoma. In this context, the methylation status of CDH1 was analyzed using MSP-PCR (Methylation-specific Polymerase Chain Reaction) in glioblastoma (n = 34) and normal glial tissue samples (n = 11). CDH1 hypermethylation was found in 39.4% (13/34) of the tumor samples and none of the normal glial tissue, suggesting a relation between CDH1 hypermethylation and glioblastoma ( P = 0.0195). Finally, this study showed unprecedented information that could contribute to clarifying the molecular pathways involved in the invasiveness and aggressiveness of this type of cancer.


Subject(s)
Glioblastoma , Humans , Glioblastoma/genetics , Promoter Regions, Genetic , DNA Methylation , Cadherins/genetics , Polymerase Chain Reaction , Prognosis , Antigens, CD/genetics
2.
Int J Mol Sci ; 24(10)2023 May 16.
Article in English | MEDLINE | ID: mdl-37240159

ABSTRACT

Glioblastoma (GB) is the most aggressive and frequent primary malignant tumor of the central nervous system and is associated with poor overall survival even after treatment. To better understand tumor biochemical alterations and broaden the potential targets of GB, this study aimed to evaluate differential plasma biomarkers between GB patients and healthy individuals using metabolomics analysis. Plasma samples from both groups were analyzed via untargeted metabolomics using direct injection with an electrospray ionization source and an LTQ mass spectrometer. GB biomarkers were selected via Partial Least Squares Discriminant and Fold-Change analyses and were identified using tandem mass spectrometry with in silico fragmentation, consultation of metabolomics databases, and a literature search. Seven GB biomarkers were identified, some of which were unprecedented biomarkers for GB, including arginylproline (m/z 294), 5-hydroxymethyluracil (m/z 143), and N-acylphosphatidylethanolamine (m/z 982). Notably, four other metabolites were identified. The roles of all seven metabolites in epigenetic modulation, energy metabolism, protein catabolism or folding processes, and signaling pathways that activate cell proliferation and invasion were elucidated. Overall, the findings of this study highlight new molecular targets to guide future investigations on GB. These molecular targets can also be further evaluated to derive their potential as biomedical analytical tools for peripheral blood samples.


Subject(s)
Glioblastoma , Humans , Metabolomics/methods , Biomarkers , Tandem Mass Spectrometry/methods , Least-Squares Analysis
3.
Int J Mol Sci ; 24(1)2022 Dec 26.
Article in English | MEDLINE | ID: mdl-36613836

ABSTRACT

Meningiomas (MGMs) are currently classified into grades I, II, and III. High-grade tumors are correlated with decreased survival rates and increased recurrence rates. The current grading classification is based on histological criteria and determined only after surgical tumor sampling. This study aimed to identify plasma metabolic alterations in meningiomas of different grades, which would aid surgeons in predefining the ideal surgical strategy. Plasma samples were collected from 51 patients with meningioma and classified into low-grade (LG) (grade I; n = 43), and high-grade (HG) samples (grade II, n = 5; grade III, n = 3). An untargeted metabolomic approach was used to analyze plasma metabolites. Statistical analyses were performed to select differential biomarkers among HG and LG groups. Metabolites were identified using tandem mass spectrometry along with database verification. Five and four differential biomarkers were identified for HG and LG meningiomas, respectively. To evaluate the potential of HG MGM metabolites to differentiate between HG and LG tumors, a receiving operating characteristic curve was constructed, which revealed an area under the curve of 95.7%. This indicates that the five HG MGM metabolites represent metabolic alterations that can differentiate between LG and HG meningiomas. These metabolites may indicate tumor grade even before the appearance of histological features.


Subject(s)
Meningeal Neoplasms , Meningioma , Humans , Meningioma/pathology , Meningeal Neoplasms/pathology , Neoplasm Grading , Retrospective Studies
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