Back to Search Start Over

Invited Article: Molecular biomarkers characterization for human brain glioma grading using visible resonance Raman spectroscopy

Authors :
Yan Zhou
Cheng-hui Liu
Binlin Wu
Chunyuan Zhang
Xinguang Yu
Gangge Cheng
Hong Chen
Shenglin Li
Qijun Liang
Mingqian Zhang
Ke Zhu
Lingyan Shi
Robert R. Alfano
Source :
APL Photonics, Vol 3, Iss 12, Pp 120802-120802-6 (2018)
Publication Year :
2018
Publisher :
AIP Publishing LLC, 2018.

Abstract

The accurate identification of the human brain tumor boundary and the complete resection of the tumor are two essential factors for the removal of the glioma tumor in brain surgery. We present a visible resonance Raman (VRR) spectroscopy technique for differentiating the brain tumor margin and glioma grading. Eighty-seven VRR spectra from twenty-one human brain specimens of four types of brain tissues, including the control, glioma grade II, III, and IV tissues, were observed. This study focuses on observing the characteristics of new biomarkers and their changes in the four types of brain tissue. We found that two new RR peaks at 1129 cm−1 and 1338 cm−1 associated with molecular vibrational bonds in four types of brain tissues are significantly different in peak intensities of VRR spectra. These two resonance enhanced peaks may arise from lactic acid/phosphatidic acid and adenosine triphosphate (ATP)/nicotinamide adenine dinucleotide, respectively. We found that lactic acid and ATP concentrations vary with glioma gratings. The higher the grade of malignancy, the more the increase in lactic acid and ATP concentrations. These two RR peaks may be considered as new molecular biomarkers and used to evaluate glioma grades and identify the margin of gliomas from the control tissues. The metabolic process of lactic acid and ATP in glioma cells based on the VRR spectral changes may reveal the Warburg hypothesis.

Details

Language :
English
ISSN :
23780967
Volume :
3
Issue :
12
Database :
Directory of Open Access Journals
Journal :
APL Photonics
Publication Type :
Academic Journal
Accession number :
edsdoj.f9351b68bec64be7af03c825331983f0
Document Type :
article
Full Text :
https://doi.org/10.1063/1.5036637