Title: | Fingerprinting breast cancer vs. normal mammary cells by mass spectrometric analysis of volatiles |
Author(s): | He J; Sinues PM; Hollmen M; Li X; Detmar M; Zenobi R; |
Address: | "1] State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100050, P.R. China [2] ETH Zurich, Department of Chemistry and Applied Biosciences, CH-8093 Zurich, Switzerland. ETH Zurich, Department of Chemistry and Applied Biosciences, CH-8093 Zurich, Switzerland. ETH Zurich, Institute of Pharmaceutical Sciences, CH-8093 Zurich, Switzerland" |
ISSN/ISBN: | 2045-2322 (Electronic) 2045-2322 (Linking) |
Abstract: | "There is increasing interest in the development of noninvasive diagnostic methods for early cancer detection, to improve the survival rate and quality of life of cancer patients. Identification of volatile metabolic compounds may provide an approach for noninvasive early diagnosis of malignant diseases. Here we analyzed the volatile metabolic signature of human breast cancer cell lines versus normal human mammary cells. Volatile compounds in the headspace of conditioned culture medium were directly fingerprinted by secondary electrospray ionization-mass spectrometry. The mass spectra were subsequently treated statistically to identify discriminating features between normal vs. cancerous cell types. We were able to classify different samples by using feature selection followed by principal component analysis (PCA). Additionally, high-resolution mass spectrometry allowed us to propose their chemical structures for some of the most discriminating molecules. We conclude that cancerous cells can release a characteristic odor whose constituents may be used as disease markers" |
Keywords: | "Breast/*metabolism Breast Neoplasms/*diagnosis/metabolism Cells, Cultured Female Humans Principal Component Analysis Spectrometry, Mass, Electrospray Ionization/*methods Volatile Organic Compounds/*analysis;" |
Notes: | "MedlineHe, Jingjing Sinues, Pablo Martinez-Lozano Hollmen, Maija Li, Xue Detmar, Michael Zenobi, Renato eng Research Support, Non-U.S. Gov't England 2014/06/07 Sci Rep. 2014 Jun 6; 4:5196. doi: 10.1038/srep05196" |