Clinical applications of breast cancer metabolomics using high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS 1H MRS): systematic scoping review

• Published in: Metabolomics 2019-11, Vol.15 (11), p.148-12, Article 148
• Main Authors: Bitencourt, Almir G. V., Goldberg, Johanna, Pinker, Katja, Thakur, Sunitha B.
• Format: Article
• Language: English
• Subjects: Biochemistry; Biomedical and Life Sciences; Biomedicine; Biopsy; Breast cancer; Breast Neoplasms - diagnosis; Breast Neoplasms - metabolism; Cell Biology; Developmental Biology; Diagnosis; Female; Humans; Life Sciences; Magnetic resonance spectroscopy; Medical prognosis; Metabolism; Metabolomics; Molecular Medicine; Patients; Prognosis; Proteomics; Proton Magnetic Resonance Spectroscopy; Review Article; Spectrum analysis; Statistical analysis; Therapeutic applications
• ISSN: 1573-3882; 1573-3890
• DOI: 10.1007/s11306-019-1611-5

Introduction Breast cancer is a heterogeneous disease with different prognoses and responses to systemic treatment depending on its molecular characteristics, which makes it imperative to develop new biomarkers for an individualized diagnosis and personalized oncological treatment. Ex vivo high-resolution magic angle spinning proton magnetic resonance spectroscopy (HRMAS 1H MRS) is the most common technique for metabolic quantification in human surgical and biopsy tissue specimens. Objective To perform a review of the current available literature on the clinical applications of HRMAS 1H MRS metabolic analysis in tissue samples of breast cancer patients. Methods This systematic scoping review included original research papers published in the English language in peer-reviewed journals. Study selection was performed independently by two reviewers and preferred reporting items for systematic reviews and meta-analyses (PRISMA) guidelines were followed. Results The literature search returned 159 studies and 26 papers were included as part of this systematic review. There was considerable variation regarding tissue type, aims, and statistical analysis methods across the different studies. To facilitate the interpretation of the results, the included studies were grouped according to their aims or main outcomes into: feasibility and tumor diagnosis (n = 6); tumor heterogeneity (n = 2); correlation with proteomics/transcriptomics (n = 3); correlation with prognostic factors (n = 11); and response evaluation to NAC (n = 4). Conclusion There is a lot of potential in including metabolic information of breast cancer tissue obtained with HRMAS 1H MRS. To date, studies show that metabolic concentrations quantified by this technique can be related to the diagnosis, prognosis, and treatment response in breast cancer patients.