Summary 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.

Accurate breast cancer classification is vital for patient management decisions, and better tumour classification is expected to enable more precise and eventually personalized treatment to improve patient outcomes. Here, we present a novel quantitative proteotyping approach based on SWATH mass spectrometry and establish key proteins for breast tumour classification derived from proteotype data. The study was based on 96 tissue samples representing five breast cancer subtypes according to conventional classification. Correlation of SWATH proteotype patterns indicated groups that largely recapitulate these subtypes. However, 2 the proteotype-based classification also revealed varying degrees of heterogeneity within the conventional subtypes, with triple negative tumours being the most heterogeneous. Proteins that contributed most strongly to the proteotype-based classification include INPP4B, CDK1, and ERBB2, which are associated with oestrogen receptor status, tumour grade, and HER2 status, respectively. While these three key proteins exhibited high levels of correlation between protein and transcript levels (R>0.67), general correlation did not exceed R=0.29, indicating the value of protein-level measurements of biomarkers and disease-regulated genes. Overall, our data shows how large-scale protein-level measurements by next-generation proteomics can lead to improved patient stratification for precision medicine.

Targeted mass spectrometry-based proteomics approaches enable the simultaneous and reproducible quantification of multiple protein analytes across numerous conditions in biology and clinical studies. These approaches involve e.g. selected reaction monitoring (SRM) typically conducted on a triple quadrupole mass spectrometer, its high-resolution variant named pseudo-SRM (p-SRM), carried out in a quadrupole coupled with an TOF analyzer (qTOF), and "sequential window acquisition of all theoretical spectra" (SWATH). Here we compared these methods in terms of signal-to-noise ratio (S/N), coefficient of variance (CV), fold change (FC), limit of detection and quantitation (LOD, LOQ). We have shown the highest S/N for p-SRM mode, followed by SRM and SWATH, demonstrating a trade-off between sensitivity and level of multiplexing for SRM, p-SRM, and SWATH. SRM was more sensitive than p-SRM based on determining their LOD and LOQ. Although SWATH has the worst S/N, it enables peptide multiplexing with post-acquisition definition of the targets, leading to better proteome coverage. FC between breast tumors of different clinical-pathological characteristics were highly correlated (R >0.97) across three methods and consistent with the previous study on 96 tumor tissues. Our technical note presented here, therefore, confirmed that outputs of all the three methods were biologically relevant and highly applicable to cancer research.

Biological treatment of many cancers currently targets membrane bound receptors located on a cell surface. To identify novel membrane proteins associated with migration and metastasis of breast cancer cells, a more migrating subpopulation of MDA‐MB‐231 breast cancer cell line is selected and characterized. A high‐resolution quantitative mass spectrometry with SILAC labeling is applied to analyze their surfaceome and it is compared with that of parental MDA‐MB‐231 cells. Among 824 identified proteins (FDR < 0.01), 128 differentially abundant cell surface proteins with at least one transmembrane domain are found. Of these, i) desmocollin‐1 (DSC1) is validated as a protein connected with lymph node status of luminal A breast cancer, tumor grade, and Her‐2 status by immunohistochemistry in the set of 96 primary breast tumors, and ii) catechol‐O‐methyltransferase is successfully verified as a protein associated with lymph node metastasis of triple negative breast cancer as well as with tumor grade by targeted data extraction from the SWATH‐MS data of the same set of tissues. The findings indicate importance of both proteins for breast cancer development and metastasis and highlight the potential of biomarker validation strategy via targeted data extraction from SWATH‐MS datasets.

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.