SWATH-MS Analysis of FFPE Tissues Identifies Stathmin as a Potential Marker of Endometrial Cancer in Patients Exposed to Tamoxifen.

A specific form of endometrial cancer (EC) can develop in breast cancer patients previously treated with tamoxifen (ET), an antagonist of estrogen receptor (ER) that inhibits proliferation of ER positive breast cancer. ET tumors have a different phenotype than endometrial tumors, which typically develop de novo without previous exposure to tamoxifen (EN). Here we aimed to identify specific protein markers that could serve as specific molecular targets in either phenotype. A set of total 45 formalin-fixed paraffin-embedded (FFPE) endometrial tumor tissues and adjacent myometrium tissue samples were analyzed using LC-MS/MS in SWATH-MS mode. We found that calcyphosin (CAPS) levels were elevated in EN tumors compared to ET tumors. The higher CAPS level in EC tissue invading to myometrium supports its relationship to EC aggressiveness. Further, stathmin (STMN1) levels were found significantly elevated in ET versus EN tumors and significantly associated with patient survival. This finding connects elevated levels of this cell cycle regulating, proliferation-associated protein with tamoxifen exposure. In summary, using SWATH-MS we show that CAPS and STMN1 should be recognized as clinicopathologically different EC markers of which STMN1 is specifically connected with a previous tamoxifen exposition.

Breast Cancer Classification Based on Proteotypes Obtained by SWATH Mass Spectrometry.

Accurate classification of breast tumors is vital for patient management decisions and enables more precise cancer treatment. Here, we present a quantitative proteotyping approach based on sequential windowed acquisition of all theoretical fragment ion spectra (SWATH) mass spectrometry and establish key proteins for breast tumor classification. The study is based on 96 tissue samples representing five conventional breast cancer subtypes. SWATH proteotype patterns largely recapitulate these subtypes; however, they also reveal varying heterogeneity within the conventional subtypes, with triple negative tumors being the most heterogeneous. Proteins that contribute most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2 and are associated with estrogen receptor (ER) status, tumor grade status, and HER2 status. Although these three key proteins exhibit high levels of correlation with transcript levels (R > 0.67), general correlation did not exceed R = 0.29, indicating the value of protein-level measurements of disease-regulated genes. Overall, this study highlights how cancer tissue proteotyping can lead to more accurate patient stratification.