AI Article Synopsis
- Breast cancer (BC) is the most common cancer among women, and while adjuvant chemotherapy is used post-surgery to target hidden cancer cells, tracking its effectiveness is difficult.
- This study utilized proton nuclear magnetic resonance (NMR) to analyze serum samples from 61 BC patients and 51 healthy individuals pre- and post-chemotherapy, identifying key metabolites affected by the treatment.
- Four metabolites (lactate, pyruvate, 1-methylhistidine, and formate) were found to accurately predict chemotherapy success, with a high sensitivity (98.36%) and specificity (91.30%), offering a promising non-invasive approach for monitoring treatment efficacy in breast cancer patients.
Article Abstract
Background: Breast cancer (BC) has the highest incidence rate among female malignant tumors. Adjuvant chemotherapy is commonly used to reduce micrometastasis in postoperative patients. However, monitoring the efficacy of chemotherapy in BC is a major challenge in clinical practice. In this study, H nuclear magnetic resonance (NMR) metabonomics was performed to explore the serum metabolic characteristics of BC patients before and after adjuvant chemotherapy.
Methods: In this study, we collected serum samples from 51 healthy controls and 61 BC patients before and after chemotherapy for H NMR metabolomic analysis, and tested the performance of each metabolite and combination segment by the receiver operating characteristic (ROC) curves.
Results: Nine metabolites, namely glutamine, citrate, creatine, glycerophosphatidylcholine/phosphatidylcholine, glycine, 1-methylhistidine, lactate, pyruvate and formate had significant changes in BC patients before chemotherapy compared with healthy controls. Lactate, pyruvate, 1-methylhistidine and formate were found to be inversely regulated by chemotherapy. ROC analysis showed that a combination of the four metabolites had good prediction for chemotherapy efficacy with area under the curve of 0.958, sensitivity of 98.36% and specificity of 91.30%. There was no significant correlation between chemotherapy-related metabolites and clinical indicators of cancer patients, indicating that they can be used to evaluate the chemotherapy efficacy of patients with different clinical indicators.
Conclusions: Effectively, dynamic and non-invasive metabolic markers for the evaluation of the efficacy of chemotherapy were identified in this study.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11231764 | PMC |
| http://dx.doi.org/10.21037/tcr-23-2352 | DOI Listing |
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