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通过传统的预后方法,鉴定出一种与早期乳腺癌患者微转移疾病存在相关的血清可检测代谢组学特征,这些患者存在疾病复发的不同风险。

Identification of a serum-detectable metabolomic fingerprint potentially correlated with the presence of micrometastatic disease in early breast cancer patients at varying risks of disease relapse by traditional prognostic methods.

机构信息

Department of Oncology, "Sandro Pitigliani" Medical Oncology Unit, Hospital of Prato, Istituto Toscano Tumori, Prato.

Magnetic Resonance Center (CERM), University of Florence, Sesto Fiorentino; FiorGen Foundation, Sesto Fiorentino, Italy.

出版信息

Ann Oncol. 2011 Jun;22(6):1295-1301. doi: 10.1093/annonc/mdq606. Epub 2011 Jan 3.

Abstract

BACKGROUND

Prognostic tools in early breast cancer are inadequate. The evolving field of metabolomics may allow more accurate identification of patients with residual micrometastases.

PATIENTS AND METHODS

Forty-four early breast cancer patients with pre- and postoperative serum samples had metabolomic assessment by nuclear magnetic resonance. Fifty-one metastatic patients served as control. Differential clustering was identified and used to calculate individual early patient 'metabolomic risk', calculated as inverse distance of each early patient from the metastatic cluster barycenter. Metabolomic risk was compared with Adjuvantionline 10-year mortality assessment.

RESULTS

Innate serum metabolomic differences exist between early and metastatic patients. Preoperative patients were identified with 75% sensitivity, 69% specificity and 72% predictive accuracy. Comparison with Adjuvantionline revealed discordance. Of 21 patients assessed as high risk by Adjuvantionline, 10 (48%) and 6 (29%) were at high risk by metabolomics in pre- and postoperative settings, respectively. Of 23 low-risk patients by Adjuvantionline, 11 (48%) preoperative and 20 (87%) postoperative patients were at low risk by metabolomics.

CONCLUSIONS

This study identifies metabolomic discrimination between early and metastatic breast cancer. Micrometastatic disease may account for metabolomic misclassification of some early patients as metastatic. Metabolomics identifies more patients as low relapse risk compared with Adjuvantionline. Further exploration of this metabolomic fingerprint is warranted.

摘要

背景

早期乳腺癌的预后工具不足。代谢组学这一新兴领域可能能够更准确地识别出仍有微转移的患者。

患者与方法

44 例早期乳腺癌患者在术前和术后均有血清样本进行了核磁共振代谢组学评估。51 例转移性患者作为对照。通过差异聚类确定并计算了每个早期患者的个体“代谢组学风险”,即每个早期患者距转移性聚类质心的逆距离。将代谢组学风险与 Adjuvantionline 10 年死亡率评估进行比较。

结果

早期和转移性患者的血清代谢组学存在先天差异。术前患者的敏感性为 75%,特异性为 69%,预测准确率为 72%。与 Adjuvantionline 比较存在差异。在 Adjuvantionline 评估为高风险的 21 例患者中,代谢组学在术前和术后分别有 10 例(48%)和 6 例(29%)为高风险。在 Adjuvantionline 评估为低风险的 23 例患者中,代谢组学在术前有 11 例(48%)和术后有 20 例(87%)为低风险。

结论

本研究确定了早期和转移性乳腺癌之间的代谢组学差异。一些早期患者被误诊为转移性,可能是由于微转移病代谢组学分类错误。与 Adjuvantionline 相比,代谢组学可识别出更多低复发风险的患者。需要进一步探索这种代谢组指纹图谱。

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