An early investigative serum Raman spectroscopy study of meningioma

• Published in: Analyst (London) 2018-04, Vol.143 (8), p.1916-1923
• Main Authors: Mehta, Kanika, Atak, Apurva, Sahu, Aditi, Srivastava, Sanjeeva, C, Murali Krishna
• Format: Article
• Language: English
• Subjects: Amino acids; Brain; Carotene; Central nervous system; Deoxyribonucleic acid; Diagnosis; Discriminant Analysis; DNA; Humans; Lipids; Meningeal Neoplasms - blood; Meningeal Neoplasms - diagnosis; Meningioma - blood; Meningioma - diagnosis; Principal Component Analysis; Principal components analysis; Proteins; Raman spectroscopy; Screening; Spectrum analysis; Spectrum Analysis, Raman
• ISSN: 0003-2654; 1364-5528
• DOI: 10.1039/c8an00224j

Meningiomas represent one of the most frequently reported non-glial, primary brain and central nervous system (CNS) tumors. Meningiomas often display a spectrum of anomalous locations and morphological attributes, deterring their timely diagnosis. Majority of them are sporadic in nature and thus the present-day screening strategies, including radiological investigations, often result in misdiagnosis due to their aberrant and equivocal radiological facets. Therefore, it is pertinent to explore less invasive and patient-friendly biofluids such as serum for their screening and diagnostics. The utility of serum Raman spectroscopy in diagnosis and therapeutic monitoring of cancers has been reported in the literature. In the present study, for the first time, to the best of our knowledge, we have explored Raman spectroscopy to classify the sera of meningioma and control subjects. For this exploration, 35 samples each of meningioma and control subjects were accrued and the spectra revealed variance in the levels of DNA, proteins, lipids, amino acids and β-carotene, i.e. , a relatively higher protein, DNA and lipid content in meningioma. Subsequent Principal Component Analysis (PCA) and Principal Component-Linear Discriminant Analysis (PC-LDA) followed by Leave-One-Out Cross-Validation (LOOCV) and limited independent test data, in a patient-wise approach, yielded a classification efficiency of 92% and 80% for healthy and meningioma, respectively. Additionally, in the analogous analysis between healthy and different grades of meningioma, similar results were obtained. These results indicate the potential of Raman spectroscopy in differentiating meningioma. As present methods suffer from known limitations, with the prospective validation on a larger cohort, serum Raman spectroscopy could be an adjuvant/alternative approach in the clinical management of meningioma. Serum Raman spectroscopy is explored to classify meningiomas, which are the most frequently reported non-malignant brain and CNS tumors and are often misdiagnosed. We find the technique can be prospectively extended to the screening of high-risk populations and for therapeutic monitoring.