Affiliations 

  • 1 School of Physics, Universiti Sains Malaysia, 11800 Penang, Malaysia
  • 2 School of Physics, Universiti Sains Malaysia, 11800 Penang, Malaysia. Electronic address: fairuz_omar@usm.my
  • 3 Malaysian Institute of Pharmaceuticals and Nutraceuticals, National Institute of Biotechnology Malaysia, Ministry of Energy, Science, Technology, Environment and Climate Change, 11700 Penang, Malaysia; Advanced Medical and Dental Institute, Universiti Sains Malaysia, Bertam, 13200, Pulau Pinang, Malaysia
PMID: 31216502 DOI: 10.1016/j.saa.2019.117241

Abstract

Cancer is increasing in incidence and the leading cause of death worldwide. Controlling and reducing cancer requires early detection and technique to accurately detect and quantify predictive biomarkers. Optical spectroscopy has shown promising non-destructive ability to display distinctive spectral characteristics between cancerous and normal tissues from different part of human organ. Nonetheless, not many information is available on spectroscopic properties of cancer cell lines. In this research, the visible-near infrared (VIS-NIR) absorbance spectroscopy measurement of cultured cervical cancer (HeLa) and prostate cancer cells (DU145) lines has been performed to develop spectral signature of cancer cells and to generate algorithm to quantify cancer cells. Spectroscopic measurement on mouse skin fibroblast (L929) was also taken for comparative purposes. In visible region, the raw cells' spectra do not produce any noticeable peak absorbance that provides information on color because the medium used for cells is colorless and transparent. NIR wavelength between 950 and 975 nm exhibit significant peak due to water absorbance by the medium. Development of spectral signature for the cells through the application of regression technique significantly enhances the diverse characteristics between L929, HeLa and DU145. The application of multiple linear regression allows high measurement accuracy of the cells with coefficient of determination above 0.94.

* Title and MeSH Headings from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.