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Wu Y, Wang X, Zhang M, Wu D. Molecular Biomarkers and Recent Liquid Biopsy Testing Progress: A Review of the Application of Biosensors for the Diagnosis of Gliomas. Molecules 2023; 28:5660. [PMID: 37570630 PMCID: PMC10419986 DOI: 10.3390/molecules28155660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 07/19/2023] [Accepted: 07/24/2023] [Indexed: 08/13/2023] Open
Abstract
Gliomas are the most common primary central nervous system tumors, with a high mortality rate. Early and accurate diagnosis of gliomas is critical for successful treatment. Biosensors are significant in the detection of molecular biomarkers because they are simple to use, portable, and capable of real-time analysis. This review discusses several important molecular biomarkers as well as various biosensors designed for glioma diagnosis, such as electrochemical biosensors and optical biosensors. We present our perspectives on the existing challenges and hope that this review can promote the improvement of biosensors.
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Affiliation(s)
- Yuanbin Wu
- Department of Emergency Medicine, The Seventh Medical Center, Chinese PLA General Hospital, Beijing 100700, China;
| | - Xuning Wang
- Department of General Surgery, The Air Force Hospital of Northern Theater PLA, Shenyang 110042, China
| | - Meng Zhang
- Department of Neurosurgery, The Second Hospital of Southern Theater of Chinese Navy, Sanya 572000, China
| | - Dongdong Wu
- Department of Neurosurgery, The First Medical Centre, Chinese PLA General Hospital, Beijing 100853, China
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2
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Rafeeinia A, Asadikaram G, Moazed V, Darabi MK. Organochlorine pesticides may induce leukemia by methylation of CDKN2B and MGMT promoters and histone modifications. Gene 2023; 851:146976. [DOI: 10.1016/j.gene.2022.146976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/25/2022] [Accepted: 10/11/2022] [Indexed: 11/27/2022]
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Papanicolau-Sengos A, Aldape K. DNA Methylation Profiling: An Emerging Paradigm for Cancer Diagnosis. ANNUAL REVIEW OF PATHOLOGY-MECHANISMS OF DISEASE 2021; 17:295-321. [PMID: 34736341 DOI: 10.1146/annurev-pathol-042220-022304] [Citation(s) in RCA: 85] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Histomorphology has been a mainstay of cancer diagnosis in anatomic pathology for many years. DNA methylation profiling is an additional emerging tool that will serve as an adjunct to increase accuracy of pathological diagnosis. Genome-wide interrogation of DNA methylation signatures, in conjunction with machine learning methods, has allowed for the creation of clinical-grade classifiers, most prominently in central nervous system and soft tissue tumors. Tumor DNA methylation profiling has led to the identification of new entities and the consolidation of morphologically disparate cancers into biologically coherent entities, and it will progressively become mainstream in the future. In addition, DNA methylation patterns in circulating tumor DNA hold great promise for minimally invasive cancer detection and classification. Despite practical challenges that accompany any new technology, methylation profiling is here to stay and will become increasingly utilized as a cancer diagnostic tool across a range of tumor types. Expected final online publication date for the Annual Review of Pathology: Mechanisms of Disease, Volume 17 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
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Affiliation(s)
| | - Kenneth Aldape
- Laboratory of Pathology, National Cancer Institute, Bethesda, Maryland 20892, USA; ,
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Maurer GD, Tichy J, Harter PN, Nöth U, Weise L, Quick-Weller J, Deichmann R, Steinbach JP, Bähr O, Hattingen E. Matching Quantitative MRI Parameters with Histological Features of Treatment-Naïve IDH Wild-Type Glioma. Cancers (Basel) 2021; 13:cancers13164060. [PMID: 34439213 PMCID: PMC8392045 DOI: 10.3390/cancers13164060] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 08/05/2021] [Accepted: 08/10/2021] [Indexed: 11/16/2022] Open
Abstract
Quantitative MRI allows to probe tissue properties by measuring relaxation times and may thus detect subtle changes in tissue composition. In this work we analyzed different relaxation times (T1, T2, T2* and T2') and histological features in 321 samples that were acquired from 25 patients with newly diagnosed IDH wild-type glioma. Quantitative relaxation times before intravenous application of gadolinium-based contrast agent (GBCA), T1 relaxation time after GBCA as well as the relative difference between T1 relaxation times pre-to-post GBCA (T1rel) were compared with histopathologic features such as the presence of tumor cells, cell and vessel density, endogenous markers for hypoxia and cell proliferation. Image-guided stereotactic biopsy allowed for the attribution of each tissue specimen to its corresponding position in the respective relaxation time map. Compared to normal tissue, T1 and T2 relaxation times and T1rel were prolonged in samples containing tumor cells. The presence of vascular proliferates was associated with higher T1rel values. Immunopositivity for lactate dehydrogenase A (LDHA) involved slightly longer T1 relaxation times. However, low T2' values, suggesting high amounts of deoxyhemoglobin, were found in samples with elevated vessel densities, but not in samples with increased immunopositivity for LDHA. Taken together, some of our observations were consistent with previous findings but the correlation of quantitative MRI and histologic parameters did not confirm all our pathophysiology-based assumptions.
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Affiliation(s)
- Gabriele D. Maurer
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
- Correspondence:
| | - Julia Tichy
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
| | - Patrick N. Harter
- Institute of Neurology (Edinger Institute), Goethe University Hospital, 60528 Frankfurt am Main, Germany;
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz, 60590 Frankfurt am Main, Germany
- German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Frankfurt Cancer Institute (FCI), 60596 Frankfurt am Main, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, 60528 Frankfurt am Main, Germany; (U.N.); (R.D.)
| | - Lutz Weise
- Division of Neurosurgery, Dalhousie University Halifax, Halifax, NS B3H 4R2, Canada;
| | - Johanna Quick-Weller
- Department of Neurosurgery, Goethe University Hospital, 60528 Frankfurt am Main, Germany;
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, 60528 Frankfurt am Main, Germany; (U.N.); (R.D.)
| | - Joachim P. Steinbach
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
| | - Oliver Bähr
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
- Department of Neurology, Klinikum Aschaffenburg-Alzenau, 63739 Aschaffenburg, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, Goethe University Hospital, 60528 Frankfurt am Main, Germany;
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Du SZ, Chen C, Qin L, Tang XL. Bioinformatics analysis of immune infiltration in glioblastoma multiforme based on data using a methylation chip in the GEO database. Transl Cancer Res 2021; 10:1484-1491. [PMID: 35116473 PMCID: PMC8798202 DOI: 10.21037/tcr-21-74] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2020] [Accepted: 02/26/2021] [Indexed: 12/12/2022]
Abstract
Background Glioblastoma multiforme (GBM) is the most aggressive and malignant tumor of the central nervous system. The study was to obtain the data of immune cell infiltration based on the data of a methylation chip in the GEO, and to clarify its prognostic significance for GBM. Methods The methylation data of glioblastoma was obtained by using the Illumina human methylation 450k BeadChip. The corrected expression was obtained by using edge R. Limma was used to correct the expression amount of the samples, and EpiDISH was used to translate the methylation expression data, so that the expression amount was transformed into the expression matrix of immune cells. The immune cells were then co-expressed, and the proportion and correlation of related immune cells was determined. The results of the cells in each of two groups were analyzed by enrichment and PCA mapping to establish the relevant differences. Results The data of GBM patients were obtained from the methylation chip of the GEO database. Patients were divided into a long-term (SNU-LTS) (21 cases), and short-term survival group (SNU-STS) (12 cases). There were 73 genes with significant individual differences between the two groups (P<0.05). EpiDISH was used to translate the methylation expression data into the expression matrix of immune cells, which showed that the highest proportion of cells in groups were mono cells, while Gran cells and CD8T appeared in a very small number of samples. The positive correlation between mono and B cells was the strongest, while the negative correlation between mono and Gran cells was the strongest. A violin chart shows that there was no significant difference in the infiltration degree of six kinds of immune cells between the two groups. Principal component analysis (PCA) showed that there was individual difference between the two groups, but the overall consistency was high. Conclusions Data on tumor immune cell infiltration can be obtained by using a methylation chip in the GEO database. This not only extends the application abilities of methylation chips but provides obvious individual differences. The study of tumor immune infiltrating cells may pave the way for targeted therapy in the treatment of GBM.
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Affiliation(s)
- Song-Zhou Du
- Department of Neurosurgery, Jingzhou Hospital of Traditional Chinese Medicine, The Third Clinical Medical College, Yangtze University, Jingzhou, China
| | - Cheng Chen
- Department of Nuclear Medicine, Jingzhou Central Hospital, The Second Clinical Medical College, Yangtze University, Jingzhou, China
| | - Lu Qin
- Department of Thyroid Vascular Surgery, Jingzhou Central Hospital, The Second Clinical Medical College, Yangtze University, Jingzhou, China
| | - Xue-Lian Tang
- Department of Respiratory Medicine, Jingzhou Central Hospital, The Second Clinical Medical College, Yangtze University, Jingzhou, China
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Lehmann U, Stark H, Bartels S, Schlue J, Büsche G, Kreipe H. Genome-wide DNA methylation profiling is able to identify prefibrotic PMF cases at risk for progression to myelofibrosis. Clin Epigenetics 2021; 13:28. [PMID: 33541399 PMCID: PMC7860011 DOI: 10.1186/s13148-021-01010-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2020] [Accepted: 01/11/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Patients suffering from the BCR-ABL1-negative myeloproliferative disease prefibrotic primary myelofibrosis (pre-PMF) have a certain risk for progression to myelofibrosis. Accurate risk estimation for this fibrotic progression is of prognostic importance and clinically relevant. Commonly applied risk scores are based on clinical, cytogenetic, and genetic data but do not include epigenetic modifications. Therefore, we evaluated the assessment of genome-wide DNA methylation patterns for their ability to predict fibrotic progression in PMF patients. RESULTS For this purpose, the DNA methylation profile was analyzed genome-wide in a training set of 22 bone marrow trephines from patients with either fibrotic progression (n = 12) or stable disease over several years (n = 10) using the 850 k EPIC array from Illumina. The DNA methylation classifier constructed from this data set was validated in an independently measured test set of additional 11 bone marrow trephines (7 with stable disease, 4 with fibrotic progress). Hierarchical clustering of methylation β-values and linear discriminant classification yielded very good discrimination between both patient groups. By gene ontology analysis, the most differentially methylated CpG sites are primarily associated with genes involved in cell-cell and cell-matrix interactions. CONCLUSIONS In conclusion, we could show that genome-wide DNA methylation profiling of bone marrow trephines is feasible under routine diagnostic conditions and, more importantly, is able to predict fibrotic progression in pre-fibrotic primary myelofibrosis with high accuracy.
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Affiliation(s)
- Ulrich Lehmann
- Institute of Pathology, Medical School Hannover, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625, Hannover, Germany.
| | - Helge Stark
- Institute of Pathology, Medical School Hannover, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Stephan Bartels
- Institute of Pathology, Medical School Hannover, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Jerome Schlue
- Institute of Pathology, Medical School Hannover, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Guntram Büsche
- Institute of Pathology, Medical School Hannover, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
| | - Hans Kreipe
- Institute of Pathology, Medical School Hannover, Medizinische Hochschule Hannover, Carl-Neuberg-Str. 1, 30625, Hannover, Germany
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Lu VM, Shah AH, Eichberg DG, Luther EM, Shah SS, Komotar RJ, Ivan ME. Utilizing systematic reviews and meta-analyses effectively to evaluate brain tumor biomarkers. Biomark Med 2020; 14:817-820. [PMID: 32799644 DOI: 10.2217/bmm-2020-0209] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2020] [Accepted: 05/28/2020] [Indexed: 11/21/2022] Open
Affiliation(s)
- Victor M Lu
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
- Department of Neurologic Surgery, Mayo Clinic, Rochester, MN 55905, USA
| | - Ashish H Shah
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Daniel G Eichberg
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Evan M Luther
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Sumedh S Shah
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Ricardo J Komotar
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Michael E Ivan
- Department of Neurological Surgery, University of Miami Miller School of Medicine, Miami, FL 33136, USA
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