PROTEOMICS

Differential Proteomics of Large Extracellular Vesicles in Ovarian Cancer

ABSTRACT Diverse extracellular vesicles (EVs) are present in all body fluids; however, knowledge of large EVs (lEVs) remains limited. Molecular EV profiles vary depending on EV size and the physiological circulatory system, even within the same patient. In this study, we aimed to characterize the proteomic profile of IEVs in ovarian cancer patients and identify lEV‐protein biomarkers. We collected tissue, serum, and ascites from patients with high‐grade serous ovarian cancer and concurrently separated small EVs (sEVs) and lEVs through sequential multistep centrifugation. Proteomic analysis of tissues and EVs revealed distinct EV profiles in serum and ascites, identifying 11 lEV‐specific proteins in serum and 14 in ascites that were absent in sEV. Of these, seven serum‐specific and 10 ascites‐specific proteins were further analyzed using transcriptomic databases, revealing candidate diagnostic and prognostic lEV‐protein biomarkers. Our findings underscore the importance of size‐based EV separation, as particle size influences biosynthetic mechanisms, in identifying lEV‐specific proteins with potential diagnostic and prognostic values. Summary This study underscores the importance of distinguishing extracellular vesicle (EV) subtypes and considering body fluid specificity in biomarker discovery. By isolating EVs based on size and stepwise separation and analyzing their proteomic profiles in ovarian cancer, we identified potential large EV (lEV)‐specific biomarkers that reflect disease pathology. These findings provide a foundation for lEV‐protein–based liquid biopsy approaches that could enhance the accuracy of early detection and patient stratification. Further validation in clinical settings may pave the way for more precise and personalized ovarian cancer diagnostics.

Comparative Analysis of the Progesterone Receptor Interactome in the Human Ovarian Granulosa Cell Line KGN and Other Female Reproductive Cells

ABSTRACT The nuclear steroid hormone receptor progesterone receptor (PGR) is expressed in granulosa cells in the ovarian follicle in a tightly regulated pattern in response to the surge of luteinizing hormone (LH) that stimulates ovulation. PGR plays a critical role in mediating ovulation in response to LH, however, the mechanism for this is still unknown. We performed immunoprecipitation‐mass spectrometry using the KGN human granulosa cell line expressing the primary PGR isoforms PGR‐A or PGR‐B, to identify novel interacting proteins that regulate PGR function in these ovary‐specific target cells. Proteomic analysis revealed protein interactions with both PGR isoforms that were gained (e.g., transcriptional coactivators) or lost (e.g., chaperone proteins) in response to the PGR agonist R5020. Additionally, isoform‐specific interactions, including different families of transcriptional regulators, were identified. Comparison with published datasets of PGR‐interacting proteins in human breast cancer cell lines and decidualized endometrial stromal cells demonstrated a remarkable number of tissue‐specific interactions, shedding light on how PGR can maintain diverse functions in different tissues. In conclusion, we provide a comprehensive novel dataset of the PGR interactome in previously unstudied ovarian cells and offer new insights into ovary‐specific PGR transcriptional mechanisms.

The tumour‐derived extracellular vesicle proteome varies by endometrial cancer histology and is confounded by an obesogenic environment

AbstractEndometrial cancer, the most common gynaecological cancer worldwide, is closely linked to obesity and metabolic diseases, particularly in younger women. New circulating biomarkers have the potential to improve diagnosis and treatment selections, which could significantly improve outcomes. Our approach focuses on extracellular vesicle (EV) biomarker discovery by directly profiling the proteome of EVs enriched from frozen biobanked endometrial tumours. We analysed nine tissue samples to compare three clinical subgroups—low BMI (Body Mass Index) Endometrioid, high BMI Endometrioid, and Serous (any BMI)—identifying proteins related to histological subtype, BMI, and shared secreted proteins. Using collagenase digestion and size exclusion chromatography, we successfully enriched generous quantities of EVs (range 204.8–1291.0 µg protein: 1.38 × 1011–1.10 × 1012 particles), characterised by their size (∼150 nm), expression of EV markers (CD63/81), and proposed endometrial cancer markers (L1CAM, ANXA2). Mass spectrometry‐based proteomic profiling identified 2075 proteins present in at least one of the 18 samples. Compared to cell lysates, EVs were successfully depleted for mitochondrial and blood proteins and enriched for common EV markers and large secreted proteins. Further analysis highlighted significant differences in EV protein profiles between the high BMI subgroup and others, underlining the impact of comorbidities on the EV secretome. Interestingly, proteins differentially abundant in tissue subgroups were largely not also differential in matched EVs. This research identified secreted proteins known to be involved in endometrial cancer pathophysiology and proposed novel diagnostic biomarkers (EIF6, MUC16, PROM1, SLC26A2).

Proteomic profiling of ovarian clear cell carcinomas identifies prognostic biomarkers for chemotherapy

AbstractClear cell ovarian carcinoma (CCOC) is a relatively rare subtype of ovarian cancer (OC) with high degree of resistance to standard chemotherapy. Little is known about the underlying molecular mechanisms, and it remains a challenge to predict its prognosis after chemotherapy. Here, we first analyzed the proteome of 35 formalin‐fixed paraffin‐embedded (FFPE) CCOC tissue specimens from a cohort of 32 patients with CCOC (H1 cohort) and characterized 8697 proteins using data‐independent acquisition mass spectrometry (DIA‐MS). We then performed proteomic analysis of 28 fresh frozen (FF) CCOC tissue specimens from an independent cohort of 24 patients with CCOC (H2 cohort), leading to the identification of 9409 proteins with DIA‐MS. After bioinformatics analysis, we narrowed our focus to 15 proteins significantly correlated with the recurrence free survival (RFS) in both cohorts. These proteins are mainly involved in DNA damage response, extracellular matrix (ECM), and mitochondrial metabolism. Parallel reaction monitoring (PRM)‐MS was adopted to validate the prognostic potential of the 15 proteins in the H1 cohort and an independent confirmation cohort (H3 cohort). Interferon‐inducible transmembrane protein 1 (IFITM1) was observed as a robust prognostic marker for CCOC in both PRM data and immunohistochemistry (IHC) data. Taken together, this study presents a CCOC proteomic data resource and a single promising protein, IFITM1, which could potentially predict the recurrence and survival of CCOC.

Differential histone deacetylase inhibitor‐induced perturbations of the global proteome landscape in the setting of high‐grade serous ovarian cancer

AbstractHigh‐grade serous ovarian cancer (HGSOC) is the most lethal gynecologic malignancy in women. Its low survival rate is attributed to late detection, relapse, and drug resistance. The lack of effective second‐line therapeutics remains a significant challenge. There is an opportunity to incorporate the use of histone deacetylase inhibitors (HDACi) into HGSOC treatment. However, the mechanism and efficacy of HDACi in the context of BRCA‐1/2 mutation status is understudied. Therefore, we set out to elucidate how HDACi perturb the proteomic landscape within HGSOC cells. In this work, we used TMT labeling followed by data‐dependent acquisition LC‐MS/MS to quantitatively determine differences in the global proteomic landscape across HDACi‐treated CAOV3, OVCAR3, and COV318 (BRCA‐1/2 wildtype) HGSOC cells. We identified significant differences in the HDACi‐induced perturbations of global protein regulation across CAOV3, OVCAR3, and COV318 cells. The HDACi Vorinostat and Romidepsin were identified as being the least and most effective in inhibiting HDAC activity across the three cell lines, respectively. Our results provide a justification for the further investigation of the functional mechanisms associated with the differential efficacy of FDA‐approved HDACi within the context of HGSOC. This will enhance the efficacy of targeted HGSOC therapeutic treatment modalities that include HDACi.