Forecasting individual breast cancer risk using plasma metabolomics and biocontours

Abstract

Breast cancer is a major cause of death for women. To improve treatment, current oncology research focuses on discovering and validating new biomarkers for early detection of cancer; so far with limited success. Metabolic profiling of plasma samples and auxiliary lifestyle information was combined by chemometric data fusion. It was possible to create a biocontour, which we define as a complex pattern of relevant biological and phenotypic information. While single markers or known risk factors have close to no predictive value, the developed biocontour provides a forecast which, several years before diagnosis, is on par with how well most current biomarkers can diagnose current cancer. Hence, while e.g. mammography can diagnose current cancer with a sensitivity and specificity of around 75 %, the currently developed biocontour can predict that there is an increased risk that breast cancer will develop in a subject 2–5 years after the sample is taken with sensitivity and specificity well above 80 %. The model was built on data obtained in 1993–1996 and tested on persons sampled a year later in 1997. Metabolic forecasting of cancer by biocontours opens new possibilities for early prediction of individual cancer risk and thus for efficient screening. This may provide new avenues for research into disease mechanisms.Electronic supplementary materialThe online version of this article (doi:10.1007/s11306-015-0793-8) contains supplementary material, which is available to authorized users.

Recent Advances in NMR-Based Metabolomics

“…An interesting epidemiological study demonstrated accurate prediction of breast cancer several years ahead of its clinical detection based on the combined analysis of serum NMR metabolic profiles and lifestyle variables, referred to as biocontours. 105 While mammography can diagnose current breast cancer with a sensitivity and specificity of ~75%, respectively, the new approach can predict the breast cancer risk 2–5 years ahead with sensitivity and specificity above 80%. This study was made using the samples from women enrolled in the Danish Diet, Cancer and Health cohort enrolled in the years 1993–1997.…”

“…Red curve: validation using independent data obtained in 1997. Reproduced from Bro, R.; Kamstrup-Nielsen, M. H.; Engelsen, S. B.; Savorani, F.; Rasmussen, M. A.; Hansen, L.; Olsen, A.; Tjønneland, A.; Dragsted, L. O. Metabolomics 2015, 11, 1376–1380 (ref 105). …”

Implications of Overdiagnosis: Impact on Screening Mammography Practices

“…54 Most recently, metabolic profiling of plasma samples and auxiliary lifestyle information has led to the development of so-called biocontours, which may forecast higher risk of breast cancer two-to-five years after the sample is taken, opening the possibility of timely prediction of individual cancer risk and thus more efficient screening. 55 On the other hand, clinical or pathologic markers that can reliably identify the subset of patients with DCIS at greatest risk of developing invasive breast cancers -a crucial population in the overdiagnosis and overtreatment debate -have yet to be identified. 56 As medical professionals, we must find better ways to communicate the benefits and risks of screening to patients.…”

Dietary phytochemicals and cancer chemoprevention: a review of the clinical evidence

“…Similar unique metabolic patterns have been identified in lung cancer [124] and oral squamous cell carcinoma pathways [125] as well. By incorporating a more integrative approach, Bro and colleagues recent created Biocontour [126], a novel risk assessment scale that combines metabolic profile analysis of plasma samples and relevant lifestyle information to predict cancer risk. With a sensitivity and specificity superior to traditional screening mammography, Biocontour was shown to predict individual diagnoses of breast cancer several years ahead of diagnosis [126].…”