Metabolomic analysis of plasma from breast tumour patients. A pilot study

Date Icon Publish Date
  • Carola Politi
    Department of Medical Sciences and Public Health, University of Cagliari, Italy.
  • Claudia Fattuoni
    Department of Chemical and Geological Sciences, University of Cagliari, Italy.
  • Alessandra Serra
    Department of Medical Sciences and Public Health, University of Cagliari, Italy.
  • Antonio Noto
    Department of Medical Sciences and Public Health, University of Cagliari, Italy.
  • Silvia Loi
    Department of Medical Sciences and Public Health, University of Cagliari, Italy.
  • Andrea Casanova
    Department of Mathematics and Informatics, University of Cagliari, Italy.
  • Gavino Faa
    Department of Medical Sciences and Public Health, University of Cagliari, Italy.
  • Alberto Ravarino
    Department of Medical Sciences and Public Health, University of Cagliari, Italy.
  • Luca Saba
    Department of Medical Sciences and Public Health, University of Cagliari, Italy.


Background: Patients at risk of breast cancer are submitted to mammography, resulting in a classification of the lesions following the Breast Imaging Reporting and Data System (BI-RADS®). Due to BI-RADS 3 classification problems and the great uncertainty of the possible evolution of this kind of tumours, the integration of mammographic imaging with other techniques and markers of pathology, as metabolic information, may be advisable.

Design and Methods: 
Our study aims to evaluate the possibility to quantify by gas chromatography-mass spectrometry (GC-MS) specific metabolites in the plasma of patients with mammograms classified from BI-RADS 3 to BI-RADS 5, to find similarities or differences in their metabolome. Samples from BI-RADS 3 to 5 patients were compared with samples from a healthy control group. This pilot project aimed at establishing the sensitivity of the metabolomic classification of blood samples of patients undergoing breast radiological analysis and to support a better classification of mammographic cases.

Results: Metabolomic analysis revealed a panel of metabolites more abundant in healthy controls, as 3-aminoisobutyric acid, cholesterol, cysteine, stearic, linoleic and palmitic fatty acids. The comparison between samples from BI-RADS 3 and BI-RADS 5 patients, revealed the importance of 4-hydroxyproline, found in higher amount in BI-RADS 3 subjects.

Although the low sample number did not allow the attainment of high validated statistical models, some interesting data were obtained, revealing the potential of metabolomics for an improvement in the classification of different mammographic lesions.


Dafni U, Tsourti Z, Alatsathianos I. Breast cancer statistics in the European Union: Incidence and survival across European countries. Breast Care 2019;14:344–352. DOI:

ACR BI-RADS® for Mammograpy–algorithm–blueberry Dx–RADS algorithms. Accessed: 05-Nov-2020. Available from:

Eberl MM, Fox CH, Edge SB, et al. BI-RADS classification for management of abnormal mammograms. J Am Board Fam Med 2006;19:161-4. DOI:

World Health Organization. Breast Tumours. WHO classification of tumours. Geneva: World Health Organization; 2019.

Pesce K, Orruma MB, Hadad C, et al. BI-RADS terminology for mammography reports: What residents need to know. RadioGraphics 2019;39:319-20. DOI:

Demetri-Lewis A, Slanetz PJ, Eisenberg RL. Breast calcifications: The focal group. Am J Roentgenol 2012;198:W325-43. DOI:

Yang L, Wang Y, Cai H, et al. Application of metabolomics in the diagnosis of breast cancer: a systematic review. J Cancer 2020;11:2540-51. DOI:

Barberini L, Noto A, Fattuoni C, et al. The metabolomic profile of lymphoma subtypes: A pilot study. Molecules 2019;24;2367. DOI:

Sumner LW, Amberg A, Barrett D, et al. Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI). Metabolomics 2007;3:211-21. DOI:

Barberini L, Noto A, Saba L, et al. Multivariate data validation for investigating primary HCMV infection in pregnancy. Data Brief 2016;9:220-30. DOI:

Chong J, Wishart DS, Xia J. Using metaboanalyst 4.0 for comprehensive and integrative metabolomics data analysis. Curr Protoc Bioinformatics 2019;68:e86. DOI:

Penco S, Rizzo S, Bozzini AC, et al. Stereotactic vacuum-assisted breast biopsy is not a therapeutic procedure even when all mammographically found calcifications are removed: analysis of 4,086 procedures. Am . Roentgenol 2010;195:1255-60. DOI:

Lazarus E, Mainiero MB, Schepps B, et al. BI-RADS lexicon for US and mammography: Interobserver variability and positive predictive value. Radiology 2006;239:385-91. DOI:

National Comprehensive Cancer Network [Internet]. Clinical practice guidelines in oncology. Accessed: 05-Nov-2020. Available from:

Singer CF, Balmaña J, Bürki N, et al. Genetic counselling and testing of susceptibility genes for therapeutic decision-making in breast cancer-a European consensus statement and expert recommendations. Eur J Cancer 2019;106:54-60. DOI:

Lourenco P, Mainiero MB, Lazarus E, et al. Stereotactic breast biopsy: Comparison of histologic underestimation rates with 11- and 9-gauge vacuum-assisted breast biopsy. Am J Roentgenol 2007;189:1164. DOI:

Hilvo M, de Santiago I, Gopalacharyulu P, et al. Accumulated metabolites of hydroxybutyric acid serve as diagnostic and prognostic biomarkers of ovarian high-grade serous carcinomas. Cancer Res 2016;76:796-804. DOI:

Cala MP, Aldana J, Medina J, et al. Multiplatform plasma metabolic and lipid fingerprinting of breast cancer: A pilot control case study in Colombian Hispanic women. PLoS One 2018;13:e0190958. DOI:

Díaz-Beltrán L, González-Olmedo C, Luque-Caro N, et al. Human plasma metabolomics for biomarker discovery: Targeting the molecular subtypes in breast cancer. Cancers 2021;13:147. DOI:

Cechowska-Pasko M, Pałka J, Wojtukiewicz MZ. Enhanced prolidase activity and decreased collagen content in breast cancer tissue. Int J Exp Path 2006;87:289-96. DOI:

Barberini L, Restivo A, Noto A, et al. A gas chromatography-mass spectrometry (GC-MS) metabolomic approach in human colorectal cancer (CRC): the emerging role of monosaccharides and amino acids. Ann Transl Med 2019;7:727. DOI:

Our most popular topics on Journal of Public Health Research

Leave a Reply

Your email address will not be published.