Abstract
Metastasis is a crucial step of malignant progression and is the primary cause of death from endometrial cancer. However, clinicians presently face the challenge that conventional surgical-pathological variables, such as tumour size, depth of myometrial invasion, histological grade, lymphovascular space invasion or radiological imaging are unable to predict with accuracy if the primary tumour has metastasized. In the current retrospective study, we have used primary tumour samples of endometrial cancer patients diagnosed with (n = 16) and without (n = 27) lymph node metastasis to identify potential discriminators. Using peptide matrix assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI), we have identified m/z values which can classify 88% of all tumours correctly. The top discriminative m/z values were identified using a combination of in situ sequencing and LC-MS/MS from digested tumour samples. Two of the proteins identified, plectin and -Actin-2, were used for validation studies using LCMS/MS data independent analysis (DIA) and immunohistochemistry. In summary, MALDIMSI has the potential to identify discriminators of metastasis using primary tumour samples.
| Original language | English |
|---|---|
| Pages (from-to) | 1793-1801 |
| Number of pages | 9 |
| Journal | Proteomics |
| Volume | 16 |
| Issue number | 45637 |
| DOIs | |
| Publication status | Published - 2016 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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