Metabolomics unravels subtype-specific characteristics related to neoadjuvant therapy response in breast cancer patients

Zapater-Moros, Andrea; Díaz-Beltrán, Leticia; Gámez‐Pozo, Angelo; Trilla-Fuertes, Lucía; Lumbreras-Herrera, María Isabel; López-Camacho, Elena; González-Olmedo, Carmen; Espinosa, Enrique; Zamora, Pilar; Sánchez‐Rovira, Pedro; Vara, Juan Ángel Fresno

doi:10.1007/s11306-023-02024-8

Cited by 3 publications

(2 citation statements)

References 35 publications

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“…This molecular pattern could be defined as the metabolomic signature or potential biomarker profile to be detected and analysed in liquid biopsies for early diagnosis of the disease. Several studies have already explored the possibility of using metabolite panels as biomarkers for early diagnosis, tumor characterization and clinical outcome prediction [14][15][16]. Hence, human body fluids such as saliva, urine, serum and plasma have been re-discovered as an excellent source of potential biological markers and, therefore, are analyzed to discover a metabolic profile that may reflect the systemic dysregulation in BC patients' metabolisms.…”

Section: Introductionmentioning

confidence: 99%

Assessment of Untargeted Metabolomics by Hydrophilic Interaction Liquid Chromatography−Mass Spectrometry to Define Breast Cancer Liquid Biopsy-Based Biomarkers in Plasma Samples

González Olmedo,

Díaz Beltrán,

Madrid García

et al. 2024

IJMS

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An early diagnosis of cancer is fundamental not only in regard to reducing its mortality rate but also in terms of counteracting the progression of the tumor in the initial stages. Breast cancer (BC) is the most common tumor pathology in women and the second deathliest cancer worldwide, although its survival rate is increasing thanks to improvements in screening programs. However, the most common techniques to detect a breast tumor tend to be time-consuming, unspecific or invasive. Herein, the use of untargeted hydrophilic interaction liquid chromatography−mass spectrometry analysis appears as an analytical technique with potential use for the early detection of biomarkers in liquid biopsies from BC patients. In this research, plasma samples from 134 BC patients were compared with 136 from healthy controls (HC), and multivariate statistical analyses showed a clear separation between four BC phenotypes (LA, LB, HER2, and TN) and the HC group. As a result, we identified two candidate biomarkers that discriminated between the groups under study with a VIP > 1 and an AUC of 0.958. Thus, targeting the specific aberrant metabolic pathways in future studies may allow for better molecular stratification or early detection of the disease.

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Section: Introductionmentioning

confidence: 99%

Assessment of Untargeted Metabolomics by Hydrophilic Interaction Liquid Chromatography−Mass Spectrometry to Define Breast Cancer Liquid Biopsy-Based Biomarkers in Plasma Samples

González Olmedo,

Díaz Beltrán,

Madrid García

et al. 2024

IJMS

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“…Jobard et al identified nine metabolites to differentiate between metastatic and early breast cancer, although a separation of breast cancer phenotypes based on metabolomics is still controversial [ 14 , 15 ]. Several metabolomic studies of plasma/serum breast cancer have been performed, mainly aimed at distinguishing between the subtypes of breast cancer [ 16 ], metastatic breast cancer [ 8 , 14 , 17 , 18 , 19 , 20 ], recurrence [ 21 , 22 ], response to neoadjuvant chemotherapy [ 23 , 24 ], etc. An important part of the metabolomic profile, which makes it possible to discriminate between BC patients and healthy controls, is represented by amino acids.…”

Section: Introductionmentioning

confidence: 99%

The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review

Bel’skaya,

Gundyrev,

Solomatin

2023

CIMB

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This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10–15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.

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Metabolomic Profiling of Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy for Predicting Disease-Free and Overall Survival

Talarico,

Derchain,

da Silva

et al. 2024

IJMS

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Breast cancer (BC) remains a significant global health concern, with neoadjuvant chemotherapy (NACT) offering preoperative benefits like tumor downstaging and treatment response assessment. However, identifying factors influencing post-NACT treatment response and survival outcomes is challenging. Metabolomic approaches offer promising insights into understanding these outcomes. This study analyzed the serum of 80 BC patients before and after NACT, followed for up to five years, correlating with disease-free survival (DFS) and overall survival (OS). Using untargeted nuclear magnetic resonance (NMR) spectroscopy and a novel statistical model that avoids collinearity issues, we identified metabolic changes associated with survival outcomes. Four metabolites (histidine, lactate, serine, and taurine) were significantly associated with DFS. We developed a metabolite-related survival score (MRSS) from these metabolites, stratifying patients into low- and high-risk relapse groups, independent of classical prognostic factors. High-risk patients had a hazard ratio (HR) for DFS of 3.42 (95% CI 1.51–7.74; p = 0.003) after adjustment for disease stage and age. A similar trend was observed for OS (HR of 3.34, 95% CI 1.64–6.80; p < 0.001). Multivariate Cox proportional hazards analysis confirmed the independent prognostic value of the MRSS. Our findings suggest the potential of metabolomic data, alongside traditional markers, in guiding personalized treatment decisions and risk stratification in BC patients undergoing NACT. This study provides a methodological framework for leveraging metabolomics in survival analyses.

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Metabolomics unravels subtype-specific characteristics related to neoadjuvant therapy response in breast cancer patients

Cited by 3 publications

References 35 publications

Assessment of Untargeted Metabolomics by Hydrophilic Interaction Liquid Chromatography−Mass Spectrometry to Define Breast Cancer Liquid Biopsy-Based Biomarkers in Plasma Samples

Assessment of Untargeted Metabolomics by Hydrophilic Interaction Liquid Chromatography−Mass Spectrometry to Define Breast Cancer Liquid Biopsy-Based Biomarkers in Plasma Samples

The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review

Metabolomic Profiling of Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy for Predicting Disease-Free and Overall Survival

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