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Kino S, Kanamori M, Shimoda Y, Niizuma K, Endo H, Matsuura Y. Distinguishing IDH mutation status in gliomas using FTIR-ATR spectra of peripheral blood plasma indicating clear traces of protein amyloid aggregation. BMC Cancer 2024; 24:222. [PMID: 38365669 PMCID: PMC10870484 DOI: 10.1186/s12885-024-11970-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/06/2024] [Indexed: 02/18/2024] Open
Abstract
BACKGROUND Glioma is a primary brain tumor and the assessment of its molecular profile in a minimally invasive manner is important in determining treatment strategies. Among the molecular abnormalities of gliomas, mutations in the isocitrate dehydrogenase (IDH) gene are strong predictors of treatment sensitivity and prognosis. In this study, we attempted to non-invasively diagnose glioma development and the presence of IDH mutations using multivariate analysis of the plasma mid-infrared absorption spectra for a comprehensive and sensitive view of changes in blood components associated with the disease and genetic mutations. These component changes are discussed in terms of absorption wavenumbers that contribute to differentiation. METHODS Plasma samples were collected at our institutes from 84 patients with glioma (13 oligodendrogliomas, 17 IDH-mutant astrocytoma, 7 IDH wild-type diffuse glioma, and 47 glioblastomas) before treatment initiation and 72 healthy participants. FTIR-ATR spectra were obtained for each plasma sample, and PLS discriminant analysis was performed using the absorbance of each wavenumber in the fingerprint region of biomolecules as the explanatory variable. This data was used to distinguish patients with glioma from healthy participants and diagnose the presence of IDH mutations. RESULTS The derived classification algorithm distinguished the patients with glioma from healthy participants with 83% accuracy (area under the curve (AUC) in receiver operating characteristic (ROC) = 0.908) and diagnosed the presence of IDH mutation with 75% accuracy (AUC = 0.752 in ROC) in cross-validation using 30% of the total test data. The characteristic changes in the absorption spectra suggest an increase in the ratio of β-sheet structures in the conformational composition of blood proteins of patients with glioma. Furthermore, these changes were more pronounced in patients with IDH-mutant gliomas. CONCLUSIONS The plasma infrared absorption spectra could be used to diagnose gliomas and the presence of IDH mutations in gliomas with a high degree of accuracy. The spectral shape of the protein absorption band showed that the ratio of β-sheet structures in blood proteins was significantly higher in patients with glioma than in healthy participants, and protein aggregation was a distinct feature in patients with glioma with IDH mutations.
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Affiliation(s)
- Saiko Kino
- Graduate School of Biomedical Engineering, Tohoku University, 6-6-05, Aza-Aoba, Aramaki, Aoba, Sendai City, 980-8579, Miyagi Prefecture, Japan
| | - Masayuki Kanamori
- Department of Neurosurgery, Tohoku University Graduate School of Medicine, 980-8574 Seiryo 1-1, Aoba, Sendai City, Miyagi Prefecture, Japan
| | - Yoshiteru Shimoda
- Department of Neurosurgery, Tohoku University Graduate School of Medicine, 980-8574 Seiryo 1-1, Aoba, Sendai City, Miyagi Prefecture, Japan
| | - Kuniyasu Niizuma
- Department of Neurosurgical Engineering and Translational Neuroscience, Graduate School of Biomedical Engineering, Tohoku University, Seiryo 2-1, Aoba, Sendai City, 980-8575, Miyagi Prefecture, Japan
- Department of Neurosurgical Engineering and Translational Neuroscience, Tohoku University Graduate School of Medicine, 980-8575 Seiryo 2-1, Aoba, Sendai City, Miyagi Prefecture, Japan
| | - Hidenori Endo
- Department of Neurosurgery, Tohoku University Graduate School of Medicine, 980-8574 Seiryo 1-1, Aoba, Sendai City, Miyagi Prefecture, Japan
| | - Yuji Matsuura
- Graduate School of Biomedical Engineering, Tohoku University, 6-6-05, Aza-Aoba, Aramaki, Aoba, Sendai City, 980-8579, Miyagi Prefecture, Japan.
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Martin FL. Translating Biospectroscopy Techniques to Clinical Settings: A New Paradigm in Point-of-Care Screening and/or Diagnostics. J Pers Med 2023; 13:1511. [PMID: 37888122 PMCID: PMC10608143 DOI: 10.3390/jpm13101511] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 10/11/2023] [Accepted: 10/18/2023] [Indexed: 10/28/2023] Open
Abstract
As healthcare tools increasingly move towards a more digital and computational format, there is an increasing need for sensor-based technologies that allow for rapid screening and/or diagnostics [...].
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Affiliation(s)
- Francis L Martin
- Department of Cellular Pathology, Blackpool Teaching Hospitals NHS Foundation Trust, Whinney Heys Road, Blackpool FY3 8NR, UK
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3
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Sala A, Cameron JM, Brennan PM, Crosbie EJ, Curran T, Gray E, Martin-Hirsch P, Palmer DS, Rehman IU, Rattray NJW, Baker MJ. Global serum profiling: an opportunity for earlier cancer detection. J Exp Clin Cancer Res 2023; 42:207. [PMID: 37580713 PMCID: PMC10426107 DOI: 10.1186/s13046-023-02786-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2023] [Accepted: 07/30/2023] [Indexed: 08/16/2023] Open
Abstract
The advances in cancer research achieved in the last 50 years have been remarkable and have provided a deeper knowledge of this disease in many of its conceptual and biochemical aspects. From viewing a tumor as a 'simple' aggregate of mutant cells and focusing on detecting key cell changes leading to the tumorigenesis, the understanding of cancer has broadened to consider it as a complex organ interacting with its close and far surroundings through tumor and non-tumor cells, metabolic mechanisms, and immune processes. Metabolism and the immune system have been linked to tumorigenesis and malignancy progression along with cancer-specific genetic mutations. However, most technologies developed to overcome the barriers to earlier detection are focused solely on genetic information. The concept of cancer as a complex organ has led to research on other analytical techniques, with the quest of finding a more sensitive and cost-effective comprehensive approach. Furthermore, artificial intelligence has gained broader consensus in the oncology community as a powerful tool with the potential to revolutionize cancer diagnosis for physicians. We herein explore the relevance of the concept of cancer as a complex organ interacting with the bodily surroundings, and focus on promising emerging technologies seeking to diagnose cancer earlier, such as liquid biopsies. We highlight the importance of a comprehensive approach to encompass all the tumor and non-tumor derived information salient to earlier cancer detection.
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Affiliation(s)
| | | | - Paul M Brennan
- Translational Neurosurgery, Department of Clinical Neurosciences, Royal Infirmary of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Emma J Crosbie
- Division of Cancer Sciences, School of Medical Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, M13 9PL, UK
- Division of Gynecology, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester, M13 9WL, UK
| | - Tom Curran
- Children's Mercy Research Institute, Children's Mercy Kansas City, Kansas City, MO, 64108, USA
| | - Ewan Gray
- Independent Health Economics Consultant, Edinburgh, UK
| | - Pierre Martin-Hirsch
- Gynecological Oncology, Clinical Research Facility, Lancashire Teaching Hospitals, Preston, PR2 9HT, UK
| | - David S Palmer
- Dxcover Limited, Glasgow, G1 1XW, UK
- Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, Glasgow, G1 1XL, UK
| | - Ihtesham U Rehman
- School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK
| | - Nicholas J W Rattray
- Strathclyde Institute of Pharmacy and Biomedical Sciences (SIPBS), University of Strathclyde, Glasgow, G4 0RE, UK
| | - Matthew J Baker
- Dxcover Limited, Glasgow, G1 1XW, UK.
- Department of Pure and Applied Chemistry, Thomas Graham Building, University of Strathclyde, Glasgow, G1 1XL, UK.
- School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston, PR1 2HE, UK.
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Antoniou G, Conn JJA, Smith BR, Brennan PM, Baker MJ, Palmer DS. Recurrent neural networks for time domain modelling of FTIR spectra: application to brain tumour detection. Analyst 2023; 148:1770-1776. [PMID: 36967685 DOI: 10.1039/d2an02041f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
A recurrent neural network trained on time domain data can accurately identify brain tumours from serum spectral data.
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Affiliation(s)
- Georgios Antoniou
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
| | - Justin J A Conn
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
| | - Benjamin R Smith
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
| | - Paul M Brennan
- Translational Neurosurgery, Centre for Clinical Brain Sciences, University of Edinburgh, Midlothian, Edinburgh EH4 2XU, UK
| | - Matthew J Baker
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
- School of Medicine, Faculty of Clinical and Biomedical Sciences, University of Central Lancashire, Preston PR1 2HE, UK
| | - David S Palmer
- Dxcover Limited, Suite RC534, Royal College Building, 204 George Street, Glasgow G1 1XW, UK
- Department of Pure and Applied Chemistry, University of Strathclyde, Glasgow G1 1XL, UK.
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Sala A, Cameron JM, Jenkins CA, Barr H, Christie L, Conn JJA, Evans TRJ, Harris DA, Palmer DS, Rinaldi C, Theakstone AG, Baker MJ. Liquid Biopsy for Pancreatic Cancer Detection Using Infrared Spectroscopy. Cancers (Basel) 2022; 14:3048. [PMID: 35804820 PMCID: PMC9264892 DOI: 10.3390/cancers14133048] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2022] [Revised: 06/16/2022] [Accepted: 06/20/2022] [Indexed: 12/04/2022] Open
Abstract
Pancreatic cancer claims over 460,000 victims per year. The carbohydrate antigen (CA) 19-9 test is the blood test used for pancreatic cancer's detection; however, its levels can be raised in symptomatic patients with other non-malignant diseases, or with other tumors in the surrounding area. Attenuated total reflection Fourier-transform infrared (ATR-FTIR) spectroscopy has demonstrated exceptional potential in cancer diagnostics, and its clinical implementation could represent a significant step towards early detection. This proof-of-concept study, investigating the use of ATR-FTIR spectroscopy on dried blood serum, focused on the discrimination of both cancer versus healthy control samples, and cancer versus symptomatic non-malignant control samples, as a novel liquid biopsy approach for pancreatic cancer diagnosis. Machine learning algorithms were applied, achieving results of up to 92% sensitivity and 88% specificity when discriminating between cancers (n = 100) and healthy controls (n = 100). An area under the curve (AUC) of 0.95 was obtained through receiver operating characteristic (ROC) analysis. Balanced sensitivity and specificity over 75%, with an AUC of 0.83, were achieved with cancers (n = 35) versus symptomatic controls (n = 35). Herein, we present these results as demonstration that our liquid biopsy approach could become a simple, minimally invasive, and reliable diagnostic test for pancreatic cancer detection.
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Affiliation(s)
- Alexandra Sala
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK; (A.S.); (L.C.); (D.S.P.)
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - James M. Cameron
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - Cerys A. Jenkins
- Swansea University Medical School, Swansea University, Swansea SA2 8PP, UK;
| | - Hugh Barr
- Gloucestershire Hospitals NHS Foundation Trust, Gloucester GL1 2EL, UK;
| | - Loren Christie
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK; (A.S.); (L.C.); (D.S.P.)
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - Justin J. A. Conn
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | | | - Dean A. Harris
- Singleton Hospital, Swansea Bay University Local Health Board, Swansea SA2 8QA, UK;
| | - David S. Palmer
- Department of Pure and Applied Chemistry, University of Strathclyde, Thomas Graham Building, Glasgow G1 1XL, UK; (A.S.); (L.C.); (D.S.P.)
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
| | - Christopher Rinaldi
- Department of Pure and Applied Chemistry, University of Strathclyde, The Technology and Innovation Centre, Glasgow G1 1RD, UK; (C.R.); (A.G.T.)
| | - Ashton G. Theakstone
- Department of Pure and Applied Chemistry, University of Strathclyde, The Technology and Innovation Centre, Glasgow G1 1RD, UK; (C.R.); (A.G.T.)
| | - Matthew J. Baker
- Dxcover Limited, Royal College Building, Glasgow G1 1XW, UK; (J.M.C.); (J.J.A.C.)
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Lilo T, Morais CL, Shenton C, Ray A, Gurusinghe N. Revising Fourier-transform infrared (FT-IR) and Raman spectroscopy towards brain cancer detection. Photodiagnosis Photodyn Ther 2022; 38:102785. [DOI: 10.1016/j.pdpdt.2022.102785] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2021] [Revised: 02/15/2022] [Accepted: 02/25/2022] [Indexed: 12/11/2022]
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Raman Spectroscopy and Machine Learning for IDH Genotyping of Unprocessed Glioma Biopsies. Cancers (Basel) 2021; 13:cancers13164196. [PMID: 34439355 PMCID: PMC8392399 DOI: 10.3390/cancers13164196] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Revised: 08/12/2021] [Accepted: 08/16/2021] [Indexed: 11/26/2022] Open
Abstract
Simple Summary Isocitrate dehydrogenase (IDH) mutation is one of the most important prognostic markers in glioma tumors. Raman spectroscopy (RS) is an optical technique with great potential in intraoperative molecular diagnosis and surgical guidance. We analyzed RS’s ability to detect the IDH mutation onto unprocessed glioma biopsies. A total of 2073 Raman spectra were extracted from 38 tumor specimens. From the 103 Raman shifts screened, we identified 52 shifts (related to lipids, collagen, DNA and cholesterol/phospholipids) with the highest performance in the distinction of the two groups. We described 18 shifts never used before for IDH detection with RS in fresh or frozen samples. We were able to distinguish between IDH-mutated and IDH-wild-type tumors with an accuracy and precision of 87%. RS showed optimal accuracy and precision in discriminating IDH-mutated glioma from IDH-wild-type tumors ex-vivo onto fresh surgical specimens. Abstract Isocitrate dehydrogenase (IDH) mutational status is pivotal in the management of gliomas. Patients with IDH-mutated (IDH-MUT) tumors have a better prognosis and benefit more from extended surgical resection than IDH wild-type (IDH-WT). Raman spectroscopy (RS) is a minimally invasive optical technique with great potential for intraoperative diagnosis. We evaluated the RS’s ability to characterize the IDH mutational status onto unprocessed glioma biopsies. We extracted 2073 Raman spectra from thirty-eight unprocessed samples. The classification performance was assessed using the eXtreme Gradient Boosted trees (XGB) and Support Vector Machine with Radial Basis Function kernel (RBF-SVM). Measured Raman spectra displayed differences between IDH-MUT and IDH-WT tumor tissue. From the 103 Raman shifts screened as input features, the cross-validation loop identified 52 shifts with the highest performance in the distinction of the two groups. Raman analysis showed differences in spectral features of lipids, collagen, DNA and cholesterol/phospholipids. We were able to distinguish between IDH-MUT and IDH-WT tumors with an accuracy and precision of 87%. RS is a valuable and accurate tool for characterizing the mutational status of IDH mutation in unprocessed glioma samples. This study improves RS knowledge for future personalized surgical strategy or in situ target therapies for glioma tumors.
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Goertzen N, Pappesch R, Fassunke J, Brüning T, Ko YD, Schmidt J, Großerueschkamp F, Buettner R, Gerwert K. Quantum Cascade Laser-Based Infrared Imaging as a Label-Free and Automated Approach to Determine Mutations in Lung Adenocarcinoma. THE AMERICAN JOURNAL OF PATHOLOGY 2021; 191:1269-1280. [PMID: 34004158 DOI: 10.1016/j.ajpath.2021.04.013] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/28/2021] [Revised: 04/09/2021] [Accepted: 04/22/2021] [Indexed: 12/28/2022]
Abstract
Therapeutic decisions in lung cancer critically depend on the determination of histologic types and oncogene mutations. Therefore, tumor samples are subjected to standard histologic and immunohistochemical analyses and examined for relevant mutations using comprehensive molecular diagnostics. In this study, an alternative diagnostic approach for automatic and label-free detection of mutations in lung adenocarcinoma tissue using quantum cascade laser-based infrared imaging is presented. For this purpose, a five-step supervised classification algorithm was developed, which was not only able to detect tissue types and tumor lesions, but also the tumor type and mutation status of adenocarcinomas. Tumor detection was verified on a data set of 214 patient samples with a specificity of 97% and a sensitivity of 95%. Furthermore, histology typing was verified on samples from 203 of the 214 patients with a specificity of 97% and a sensitivity of 94% for adenocarcinoma. The most frequently occurring mutations in adenocarcinoma (KRAS, EGFR, and TP53) were differentiated by this technique. Detection of mutations was verified in 60 patient samples from the data set with a sensitivity and specificity of 95% for each mutation. This demonstrates that quantum cascade laser infrared imaging can be used to analyze morphologic differences as well as molecular changes. Therefore, this single, one-step measurement provides comprehensive diagnostics of lung cancer histology types and most frequent mutations.
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Affiliation(s)
- Nina Goertzen
- Center for Protein Diagnostics, Biospectroscopy, Germany; Department of Biophysics, Faculty of Biology and Biotechnology, Ruhr University Bochum, Bochum, Germany
| | | | - Jana Fassunke
- Institut für Pathologie, Universitätsklinikum Köln, Germany
| | - Thomas Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum, Bochum, Germany
| | - Yon-Dschun Ko
- Department of Internal Medicine, Johanniter-Kliniken Bonn GmbH, Johanniter Krankenhaus, Bonn, Germany
| | - Joachim Schmidt
- Lung Cancer Center Bonn, Department of Thoracic Surgery, Helios Klinikum Bonn/Rhein-Sieg and Department of Surgery, Division of Thoracic Surgery, Universitätsklinikum Bonn, Germany
| | - Frederik Großerueschkamp
- Center for Protein Diagnostics, Biospectroscopy, Germany; Department of Biophysics, Faculty of Biology and Biotechnology, Ruhr University Bochum, Bochum, Germany
| | | | - Klaus Gerwert
- Center for Protein Diagnostics, Biospectroscopy, Germany; Department of Biophysics, Faculty of Biology and Biotechnology, Ruhr University Bochum, Bochum, Germany.
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Glioma biopsies Classification Using Raman Spectroscopy and Machine Learning Models on Fresh Tissue Samples. Cancers (Basel) 2021; 13:cancers13051073. [PMID: 33802369 PMCID: PMC7959285 DOI: 10.3390/cancers13051073] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2021] [Revised: 02/17/2021] [Accepted: 02/25/2021] [Indexed: 12/14/2022] Open
Abstract
Identifying tumor cells infiltrating normal-appearing brain tissue is critical to achieve a total glioma resection. Raman spectroscopy (RS) is an optical technique with potential for real-time glioma detection. Most RS reports are based on formalin-fixed or frozen samples, with only a few studies deployed on fresh untreated tissue. We aimed to probe RS on untreated brain biopsies exploring novel Raman bands useful in distinguishing glioma and normal brain tissue. Sixty-three fresh tissue biopsies were analyzed within few minutes after resection. A total of 3450 spectra were collected, with 1377 labelled as Healthy and 2073 as Tumor. Machine learning methods were used to classify spectra compared to the histo-pathological standard. The algorithms extracted information from 60 different Raman peaks identified as the most representative among 135 peaks screened. We were able to distinguish between tumor and healthy brain tissue with accuracy and precision of 83% and 82%, respectively. We identified 19 new Raman shifts with known biological significance. Raman spectroscopy was effective and accurate in discriminating glioma tissue from healthy brain ex-vivo in fresh samples. This study added new spectroscopic data that can contribute to further develop Raman Spectroscopy as an intraoperative tool for in-vivo glioma detection.
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Circular RNA circ_HN1 facilitates gastric cancer progression through modulation of the miR-302b-3p/ROCK2 axis. Mol Cell Biochem 2020; 476:199-212. [PMID: 32949310 DOI: 10.1007/s11010-020-03897-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 09/02/2020] [Indexed: 02/07/2023]
Abstract
Gastric cancer (GC) is a malignant tumor with high morbidity and mortality in the world. Circular RNA hsa_circHN1_005 (circ_HN1), also termed as hsa_circ_0045602, is reported as an oncogene in GC. However, the molecular mechanism of circ_HN1 in GC development has not been fully explored. Here, we surveyed the regulatory mechanism of circ_HN1 in GC progression. The levels of circ_HN1, miR-302b-3p, and rho-associated coiled-coil containing protein kinase 2 (ROCK2) mRNA were measured by quantitative real-time polymerase chain reaction (qRT-PCR). Cell proliferation, apoptosis, colony formation, cell cycle progresion, migration, and invasion were determined by using cell counting, flow cytometry, colony formation, or transwell assays. Protein levels were detected with Western blotting. The relationship between circ_HN1 or ROCK2 and miR-302b-3p was verified via dual luciferase reporter or RNA immunoprecipitation (RIP) assays. The role of circ_HN1 in vivo was confirmed by xenograft assay. We observed that circ_HN1 and ROCK2 were upregulated while miR-302b-3p was downregulated in GC tissues and cells. Circ_HN1 silencing slowed tumor growth in vivo and impeded cell proliferation migration, invasion, and facilitated cell apoptosis in GC cells in vitro. Circ_HN1 sponged miR-302b-3p to regulate ROCK2 expression. MiR-302b-3p inhibitor reversed circ_HN1 silencing-mediated influence on the malignant behaviors of GC cells. Furthermore, ROCK2 overexpression restored miR-302b-3p mimic-mediated impacts on cell malignant behaviors in GC cells. In conclusion, circ_HN1 exerted an oncogenic role in GC through upregulating ROCK2 via sponging miR-302b-3p, offering evidence that circ_HN1 is a potential target for GC therapy.
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