Direct mass spectrometry approach for the express identification of tumor tissue from breast cancer patients

Alisa Olegovna Tokareva, Vitaliy Viktorovich Chagovets, Zhihao Wang, Valeriy Vitalievich Rodionov, Vlada Vladimirovna Kometova, Maria Valerievna Rodionova, Alexey Sergeevich Kononikhin, Nataliia Leonidovna Starodubtseva, Konstantin Chingin, Vladimir Evgenievich Frankevich, Huanwen Chen, Gennadiy Tikhonovich Sukhikh

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

Objective. The development of analytical approach based on direct mass spectrometry analysis for the rapid identification and differentiation between tumor and healthy breast tissue. Subjects and methods. The case-control study included 25 patients with invasive breast cancer. Each sample of tumor and healthy tissue from each patient was divided into two parts. One part was used for pathomorphological examination. Another part was investigated by direct mass spectrometry analysis to obtain molecular profile. The mass spectrometric data were processed by the OPLS-DA multivariate analysis. Results. The normal and tumor breast tissues were differentiated by OPLS-DA analysis of the mass spectrometric data. Lipids of 4 different classes contributed in classification: diacylglycerol DG 34:1, monoacylglycerols MG 18:1, MG O-14:1, phosphatidylcholines LPC 16:0, PC 32:0, PC 32:1, PC 34:0, PC 34:1, PC 34:2, PC 36:3, PC 38:3, PC 38:4, sphingomyelin SM 32:1. Conclusions. Direct mass spectrometry tissue analysis allows differentiation between tumor and healthy breast tissues based on characteristic patterns of lipid ion signals in the mass spectrum. Besides their diagnostic value, these characteristic patterns can also be used for the mechanistic study of tumor pathogenesis.

Original languageEnglish
Pages (from-to)119-125
Number of pages7
JournalAkusherstvo i Ginekologiya (Russian Federation)
Issue number4
DOIs
Publication statusPublished - 2017
Externally publishedYes

Keywords

  • Breast cancer
  • Direct mass spectrometry
  • Lipidomics
  • Phosphatidylcholine

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