A preliminary study of amino acid metabolomics using LC-MS/MS to predict the che-motherapeutic response of patients with advanced breast cancer / 中国肿瘤临床
Chinese Journal of Clinical Oncology
; (24): 1253-1257, 2017.
Article
en Zh
| WPRIM
| ID: wpr-706741
Biblioteca responsable:
WPRO
ABSTRACT
Objective:To investigate the value of amino acid metabolomics in evaluating chemotherapeutic response of patients with ad-vanced breast cancer, the changes in the levels of 32 amino acids in the circulating serum of patients before (baseline) and after the first cycle (prognosis) of chemotherapy were tested. Methods:Seventy-three advanced breast cancer patients with local recurrence and distant metastasis admitted at the Liaoning Cancer Hospital from March 2015 to October 2016 were enrolled. Peripheral blood samples (2 mL) were collected before and after the first cycles of chemotherapy from each patient. Thirty-two amino acids in the se-rum were tested using the ultra-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). Patients were catego-rized into the improvement or deterioration groups, based on the first imaging test after 2-4 cycles of chemotherapy. The changes in amino acids levels were analyzed in different prognosis groups. Results:The levels of the 32 amino acids ranged 3-180000 pmol/L. Compared to their baseline levels, both glycine and L-glutamine increased in the improvement group, but decreased in the deteriora-tion group. Sarcosine was significantly reduced in the improvement group, while differences in its levels were not obvious in the deteri-oration group. L-threonine, taurine, iminodiacetic acid, and L-glutamic acid were increased in both groups. Conclusion:Changes in the serum levels of glycine, sarcosine, and the other amino acids before and after the first cycles of chemotherapy can predict chemothera-peutic response in patients with advanced breast cancer. Amino acid metabolomics may become a potential biomarker for predicting the efficacy of chemotherapy earlier than that of imaging tests, and thereby help improve therapeutic strategies for advanced breast cancer.
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Base de datos:
WPRIM
Tipo de estudio:
Prognostic_studies
Idioma:
Zh
Revista:
Chinese Journal of Clinical Oncology
Año:
2017
Tipo del documento:
Article