4.5 Article

Discrimination analysis of human lung cancer cells associated with histological type and malignancy using Raman spectroscopy

Journal

JOURNAL OF BIOMEDICAL OPTICS
Volume 15, Issue 1, Pages -

Publisher

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS
DOI: 10.1117/1.3316296

Keywords

Raman spectroscopy; lung cancer; single cell; cancer; diagnosis; cytochrome c

Funding

  1. Japan Society for the Promotion of Science (JSPS)
  2. SENTAN
  3. Japan Science and Technology Agency (JST)

Ask authors/readers for more resources

The Raman spectroscopic technique enables the observation of intracellular molecules without fixation or labeling procedures in situ. Raman spectroscopy is a promising technology for diagnosing cancers-especially lung cancer, one of the most common cancers in humans-and other diseases. The purpose of this study was to find an effective marker for the identification of cancer cells and their malignancy using Raman spectroscopy. We demonstrate a classification of cultured human lung cancer cells using Raman spectroscopy, principal component analysis (PCA), and linear discrimination analysis (LDA). Raman spectra of single, normal lung cells, along with four cancer cells with different pathological types, were successfully obtained with an excitation laser at 532 nm. The strong appearance of bands due to cytochrome c (cyt-c) indicates that spectra are resonant and enhanced via the Q-band near 550 nm with excitation light. The PCA loading plot suggests a large contribution of cyt-c in discriminating normal cells from cancer cells. The PCA results reflect the nature of the original cancer, such as its histological type and malignancy. The five cells were successfully discriminated by the LDA. (C) 2010 Society of Photo-Optical Instrumentation Engineers. [DOI: 10.1117/1.3316296]

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.5
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available