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Hereditary and genetic factors account for only about 5-10% of breast cancer cases. More than 50% are not attributable to any known cause. There is a significant gap, therefore, in understanding breast cancer etiology, said authors of a review in the .

The study of metabolomics -- defined as the study of small molecules, also known as metabolites, within cells, biofluids, tissues, and organisms -- may help fill that gap, said Sabina Rinaldi, PhD, of the International Agency for Research on Cancer in Lyon, France, and colleagues. Several circulating metabolic biomarkers have already been linked to breast cancer risk, such as sex steroids and insulin-like growth factors, but this is only the tip of an iceberg that researchers are beginning to investigate more deeply.

"Metabolomics may prove to be an important tool for the identification of new risk factors or mechanisms linking risk factors to breast cancer development," Rinaldi and colleagues wrote. "However, various challenges still need to be addressed before results can be translated into clinical applications and, ultimately, can be translated into public health recommendations."

Rinaldi and colleagues were not available for an interview. The following responses were taken from their paper.

What is the metabolome exactly?

The metabolome can be considered as the total set of metabolites in human tissues or biofluids and represents the most downstream expression of the phenotype. Metabolic phenotypes differ between individuals, but intra-individual variation can also be observed over time, according to endogenous parameters and exogenous exposures (age, body mass index, diet, or other environmental factors).

Metabolomics uses advanced analytical chemistry techniques to enable the high-throughput characterization of metabolites in cells, organs, tissues, or biofluids.

What does research suggest about the relationship of amino acids with breast cancer risk?

Amino acids have important functions in promoting cancer development. Changes in amino acid metabolism have been reported in breast cancer, where targeting non-essential amino acids offers potential new therapeutic opportunities.

In the prospective metabolomics studies reviewed [in the article], amino acids were commonly measured, and several were associated with breast cancer risk years before diagnosis such as leucine, valine, lysine, arginine, phenylalanine, asparagine, proline, and glutamine, a main amino acid to support energy production and tumor growth under hypoxia.

Arginine has been both positively and inversely associated with breast cancer risk. This amino acid participates in cellular growth and proliferation and has immunomodulatory properties. High concentrations of arginine in patients with breast cancer are associated with better outcomes of immune checkpoint therapy.

Branched chain amino acids -- in particular leucine and valine -- were also associated with breast cancer risk. Asparagine bioavailability has been linked to breast cancer progression. Various other amino acids including lysine, proline, or phenylalanine have been associated with breast cancer risk in prospective studies.

This suggests that early changes in the overall amino acid metabolism (rather than single compound) could provide a suitable environment for future tumor development. Understanding the interplay among different amino acids may be very important for prevention and treatment for breast cancer.

Other studies have explored the relationship between lipids and breast cancer risk. Any interesting findings here?

Despite the complexity in the comparison of data from large-scale studies published so far, various lipid classes have been associated with breast cancer risk, in line with alterations of lipid metabolism observed in patients and within tumors.

Choline and ethanolamine glycerophospholipids showed mostly inverse associations with breast cancer risk. These lipids are important components of cell membranes. Although less consistent, lysoPCs [lysophosphatidylcholines] were also generally inversely associated with breast cancer risk and have important signaling functions.

Acylcarnitines also seem to play a role, although directions of associations with breast cancer risk were not consistent across specific acylcarnitines.

What kind of research will be needed to develop clinical applications in this field?

If associations are confirmed, the above mentioned classes of metabolites may provide interesting perspectives in the context of etiology, risk prediction models, and risk-reducing interventions for breast cancer. Recent studies have shown the importance of integrating hormone measurements and sex steroid concentrations into clinical risk prediction models to improve breast cancer risk stratification.

Metabolomics may prove to be an important tool for the identification of new risk factors or mechanisms linking risk factors to breast cancer development. However, various challenges still need to be addressed before results can be translated into clinical applications and, ultimately, can be translated into public health recommendations.

Studies of larger sample size and with precise information on menopausal status, breast cancer subtypes, and repeated samples are needed. The development of specific assays targeting the new molecules of interest are warranted to facilitate replication of findings and quantify levels of associations. Replication and extension of findings to other populations with different genetic backgrounds and different lifestyle patterns may also help interpret findings.

Read the review here.