Proteomics of High-Grade Serous Ovarian Cancer Models Identifies Cancer-Associated Fibroblast Markers Associated with Clinical Outcomes.
Meinusha GovindarajanVladimir IgnatchenkoLaurie AillesThomas KislingerPublished in: Biomolecules (2022)
The tumor microenvironment has recently emerged as a critical component of high-grade serous ovarian cancer (HGSC) disease progression. Specifically, cancer-associated fibroblasts (CAFs) have been recognized as key players in various pro-oncogenic processes. Here, we use mass-spectrometry (MS) to characterize the proteomes of HGSC patient-derived CAFs and compare them to those of the epithelial component of HGSC to gain a deeper understanding into their tumor-promoting phenotype. We integrate our data with primary tissue data to define a proteomic signature of HGSC CAFs and uncover multiple novel CAF proteins that are prognostic in an independent HGSC patient cohort. Our data represent the first MS-based global proteomic characterization of CAFs in HGSC and further highlights the clinical significance of HGSC CAFs.
Keyphrases
- high grade
- mass spectrometry
- low grade
- electronic health record
- liquid chromatography
- big data
- multiple sclerosis
- ms ms
- label free
- gas chromatography
- high performance liquid chromatography
- high resolution
- genome wide
- capillary electrophoresis
- gene expression
- data analysis
- artificial intelligence
- machine learning
- extracellular matrix
- anti inflammatory