Fat profile: breast cancer biomarkers laid bare

Multivariate assessment

A multivariate statistical analysis of gas-chromatograph-mass spectrometry data has allowed one team to identify possible biomarkers for breast cancer simply from free fatty acid profiles. Such biomarkers might be useful in identifying breast cancer before patients show any symptoms and so allow interventions to be carried out well before any screening program would otherwise highlight a problem.

Breast cancer incidence is approximately 116 in every 100,000 women, according to Cancer Research UK. It comprises almost 23 percent of all cancers (excluding non-melanoma skin cancers) in women and accounts for around half a million deaths worldwide annually, around 14% of cancer deaths. Finding biomarkers for early prediction of the development of breast cancer is therefore a matter of urgency if those statistics are to be reduced.

Now, Wuwen Lv of Harbin University of Commence, and Tongshu Yang of The Affiliated Tumor Hospital of Harbin Medical University, Harbin Medical University, both in Harbin, People's Republic of China, have investigated the free fatty acid (FFA) metabolic profiles in order to identify putative biomarkers for distinguishing between breast cancer patients, those with benign problems and entirely healthy controls.

High-throughput profiling

"With the development of many high-throughput measurement technologies, there have been many studies regarding the diagnosis of breast cancer using high-throughput methods of analysis, such as genomics, proteomics and metabolomics," the team says. Their focus has been on the latter as it can provide what they refer to as a "dynamic portrait" of a patient's metabolic status.

Metabolomics has often used nuclear magnetic resonance (NMR) spectroscopy and high-performance liquid chromatography/mass spectrometry (HPLC-MS) as well as GC-MS. The team points out that this latter technique has proven very useful and has been widely applied to identify and quantify metabolites because it is very sensitive has good peak resolution and offers high reproducibility . It has been particularly successful in profiling plasma fatty acid metabolites.

As such, the team recruited 114 subjects and divided them into those three groups appropriately. They then used GC-MS to obtain the requisite data and applied multivariate statistical analysis to elucidate any patterns. The researchers found that concentrations of three saturated fatty acids (C14:0, C16:0 and C18:0) as well as three unsaturated fatty acids (C18:2, C18:3 and C20:5) were very different in the group with breast cancer compared to the benign and the control groups. The team has thus identified palmitic acid (C16:0), stearic acid (C18:0), linoleic acid (C18:2) and total FFA as likely biomarkers for the disease. They suggest that such significant changes in the fatty acid profile of the patients must reflect important underlying metabolic changes, given that metabolites are the end products of gene expression and environmental influences along the various biochemical pathways. However, the actual metabolic changes remain unknown at this point in the research project.

Other researchers have measured fatty acid profiles in serum and tissue of breast cancer patients but previously detailed analysis has not been carried out to reveal the distinctions between the profile of breast cancer patients and others. The team suggests that such a statistical analysis, as they have carried out could become a powerful tool in elucidating the mechanisms of the disease, screening patients in order to identify the presence of novel biomarkers and in monitoring the patient response during any course of pharmacological treatment.

Taking precautions

There is, of course, a caveat in this study in that the patient sample was rather small at just 114 women of whom only a third were identified as actually having breast cancer. The team emphasises that, "Care must be exercised in the extrapolation of our findings to larger populations of breast cancer individuals." They suggest that the work must now be validated with an entirely independent group of women in order to demonstrate that the putative biomarkers their analysis reveals might be universal among breast cancer patients. Follow-up studies, should they be able to successfully reproduce the results, might also shed new light on the underlying metabolic changes alluded to by the team.