Project description:Bulk and single-cell RNA sequencing do not provide full characterization of tissue spatial diversity in cancer samples, and currently available in situ techniques (multiplex immunohistochemistry, imaging mass cytometry) allow for only limited analysis of a small number of targets. The current study represents the first comprehensive approach to spatial transcriptomics of high-grade serous ovarian carcinoma using intact tumor tissue. We selected a small cohort of patients with highly annotated high-grade serous ovarian carcinoma, categorized them by response to neoadjuvant chemotherapy (poor or excellent), and analyzed pre-treatment tumor tissue specimens. Our study uncovered extensive differences in tumor composition between the poor responders and excellent responders to chemotherapy, related to cell cluster organization and localization. This in-depth characterization of high-grade serous ovarian carcinoma tumor tissue from poor and excellent responders showed that spatial interactions between cell clusters may influence chemo-responsiveness more than cluster composition alone.
Project description:Sequential Window Acquisition of All Theoretical Mass Spectra (SWATH-MS) is a DIA method whose use in proteomic studies has increased considerably within the past five years. SWATH-MS acquires a complete and permanent digital record for all the detectable MS/MS spectra of a sample using DIA. After their generation, the SWATH-MS maps can be used for iterative analyses of candidate proteins. As with any analytical methodology that has potential widespread use, several studies have been conducted to optimize and evaluate the performance of SWATH-MS. The present dataset was acquired from 103 tissue samples of high-grade serous ovarian carcinoma collected and processed in the context of the CPTAC initiative and analyzed via bottom-up SWATH mass spectrometry.