Bioanalysis Zone

Chromatography and Mass Spectrometry utilized to detect breast cancer earlier

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A study published in Rapid Communications in Mass Spectrometry, described the use of chromatography and mass spectrometry to identify and quantify lipids in breast cancer cells compared to healthy cells. After investigating 120 different lipids the team identified a specific pattern found only in the cancerous cells. The unique lipid biomarkers could have the potential to aid earlier diagnosis of breast cancer.

Early diagnosis of cancer is important to the prognosis: when diagnosed at the earliest stage the five-year survival rate is over 90% contrasted to 15% when the cancer is diagnosed later.

Researchers from the University of Pardubice (Pardubice, Czech Republic), Palacký University (Olomouc, Czech Republic), Masaryk Memorial Cancer Institute (Brno, Czech Republic) and Tomáš Baťa University (Zlín, Czech Republic) investigated using cell lipids as biomarkers for breast cancer.

The team based the study on previous research highlighting an association between cancer and increased production of saturated fatty acids – such as palmitic and stearic. Lipids were extracted from healthy and breast cancer cells from nine different types of breast cancer.

Researchers utilized hydrophilic interaction liquid chromatography / electrospray ionization mass spectrometry for lipid separation and gas chromatography mass spectrometry to determine the fatty acid character of the lipids.

In total 120 different lipids were investigated and the methods identified a specific pattern in the cancer cells.

Currently, breast cancer is detected by mammograms which screen for signs and changes in the breast. Researchers hope that screening for biomarkers could be an alternative test that doesn’t expose the individual to radiation.

Source: Cífková E, Lísa M, Hrstka R et al. Correlation of lipidomic composition of cell lines and tissues of breast cancer patients using hydrophilic interaction liquid chromatography/electrospray ionization mass spectrometry and multivariate data analysisRapid Communications in Mass Spectroscopy. 31(3), 253-263 (2017)

 

 

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