Fourier transform infrared spectroscopic studies of T-cell lymphoma, B-cell lymphoid and myeloid leukaemia cell lines

This paper presents Fourier transform infrared (FT-IR) spectroscopy to characterise spectral differences that distinguish cells derived from human T-cell lymphoma, B-cell lymphoid, and myeloid leukaemia cell lines. This methodology is based on spectral measurements of major cellular biochemical cons...

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Bibliographic Details
Published in:Analyst (London) 2009-04, Vol.134 (4), p.763-768
Main Authors: BABRAH, Jaspreet, MCCARTHY, Keith, LUSH, Richard John, RYE, Adam David, BESSANT, Conrad, STONE, Nicholas
Format: Article
Language:English
Subjects:
Analytical chemistry
Cell Line, Tumor
Chemistry
Diagnosis, Differential
Exact sciences and technology
Humans
Leukemia, Myeloid - diagnosis
Lymphoma, B-Cell - diagnosis
Lymphoma, T-Cell - diagnosis
Multivariate Analysis
Neoplasm Proteins - analysis
Sensitivity and Specificity
Spectrometric and optical methods
Spectroscopy, Fourier Transform Infrared - methods
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Summary:This paper presents Fourier transform infrared (FT-IR) spectroscopy to characterise spectral differences that distinguish cells derived from human T-cell lymphoma, B-cell lymphoid, and myeloid leukaemia cell lines. This methodology is based on spectral measurements of major cellular biochemical constituents and multivariate spectral processing. Major spectral differences were observed in the 1800-900 cm(-1) 'fingerprint' spectral region. Bands in the averaged spectra for each cell line were assigned to major biochemical constituents including: proteins, lipids, carbohydrates and nucleic acids. Multivariate statistical analysis of the spectra was carried out to develop a classification model to discriminate the five cell types. The results show that FT-IR spectroscopy displays high sensitivity and specificity when discriminating between T-cell lymphoma, B-cell lymphoid, and myeloid leukaemia cells based on intrinsic biomolecular signatures. FT-IR spectroscopy in combination with multivariate statistical analysis provides an important insight into T-cell lymphoma, B-cell lymphoid, and myeloid leukaemia cell line identification. In conclusion, this paper demonstrates a potential for this technique to be used in developing a clinical tool for the detection and identification of haematological malignancies.
ISSN:0003-2654
1364-5528
DOI:10.1039/b807967f