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MALDI-TOF-MS Analysis Identifies Ovarian Cancer Patterns

By LabMedica International staff writers
Posted on 18 Jul 2017
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Image: A scanning electron micrograph (SEM) of ovarian cancer cells (Photo courtesy of SPL).
Image: A scanning electron micrograph (SEM) of ovarian cancer cells (Photo courtesy of SPL).
Ovarian cancer (OC) is one of the leading causes of death among all gynecological malignancies and as there are no early specific symptoms, OC is diagnosed in advanced clinical stages in more than 70% cases when, despite appropriate treatment, five-year survival rate drops to 30%.

Early diagnosis improves treatment outcomes and also dramatically reduces mortality rate. However, adequate diagnostic methods are lacking and therefore novel technologies that would allow early detection of OC that are urgently needed. To broaden the knowledge on the pathological processes that occur during ovarian cancer tumorigenesis, protein-peptide profiling has been proposed.

Scientists at the Poznan University of Medical Sciences (Poznań, Poland) collected blood samples were from 89 patients operated in their Gynecologic Oncology Department on the day before surgery, between August 2014 and December 2015. Based on histopathological result the patients were divided into two groups: 44 with OC, including borderline ovarian tumors, and 45 with no pathology of the ovaries, the control group.

Serum samples were pretreated using solid-phase extraction method and eluents were mixed with a matrix solution was spotted onto the MALDI target and left to crystallize at room temperature. The Bruker Daltonics UltrafleXtreme MALDI-TOF/TOF mass spectrometer was used to perform mass spectrometry (MS) analyses in the linear positive mode. Two markers additional marker CA124 and HE4, were measured in the OC group with an electrochemiluminescence immunoassay.

A classification model with the most discriminative factors was identified using chemometric algorithms and the results were verified by external validation on an independent test set of samples. The investigators reported that the main outcome of their study was an identification of potential OC biomarkers by applying liquid chromatography coupled with tandem mass spectrometry. Application of this novel strategy enabled the identification of four potential OC serum biomarkers: complement C3, kininogen-1, inter-alpha-trypsin inhibitor heavy chain H4, and transthyretin.

The authors concluded that proteomic profiling of serum samples based on the solid phase extraction enrichment technology coupled with MALDI-TOF MS demonstrated differences in the serum protein expression in patients with OC compared with the healthy control group. The study was published on June 30, 2017, in the journal BMC Cancer.

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