Stefani N. Thomas

Global Proteomic Determination of the Poly-Pharmacological Effects of PARP Inhibitors Following Treatment of High-Grade Serous Ovarian Cancer Cells

High-grade serous ovarian cancer (HGSOC) is the most commonly diagnosed ovarian cancer subtype. Approximately half of all patients diagnosed with HGSOC are deficient in homologous recombination (HR), harbor BRCA1/2 mutations, and are treated with poly (ADP-ribose) polymerase (PARP) inhibitors (PARPis). FDA-approved PARPis Olaparib, Niraparib, and Rucaparib all contribute to adverse effects in patients due to their poly-pharmacological properties. This feature necessitates investigation of global protein responses to PARPi treatment beyond DNA repair in the context of BRCA mutational status and HR deficiency. We sought to determine the landscape of differential PARPi-induced proteomes in HGSOC cells exhibiting different BRCA1/2 mutational statuses. Here, we applied immunofluorescence microscopy to detect γH2AX, Rad51, and geminin foci as markers of DNA damage and repair upon treatment of HGSOC cells with IC50 doses of PARPis. Global proteome perturbations upon PARPi treatment were measured using quantitative mass spectrometry-based proteomics. The proteomic data highlighted cell line effects, masking high-dose PARPi treatment response. Interrogation of PARPi response within biological pathways identified through gene set enrichment analysis (GSEA) revealed significant changes to proteins involved in Epithelial–Mesenchymal Transition (EMT), E2F targets, and cholesterol homeostasis. Our study establishes proteomic evidence supporting the poly-pharmacological characteristics of Niraparib, Olaparib, and Rucaparib in HGSOC cells.

Evaluation of Serum Proteome Sample Preparation Methods to Support Clinical Proteomics Applications

Serum contains several proteins that are associated with disease-related processes. Mass spectrometry (MS)-based proteomics approaches greatly facilitate serum protein biomarker development. However, the serum proteome complexity presents a technical challenge for the accurate, sensitive, and reproducible quantification of proteins by MS. Thus, efficient sample preparation methods are of critical importance for serum proteome analyses. In this study, we evaluated the technical performance of two serum proteome sample preparation methods using sera from patients with high-grade serous ovarian cancer and patients with benign nongynecological conditions with a goal of providing insight into their compatibility with clinical proteomics workflows. One method entailed the use of immobilized trypsin (SMART Digest Trypsin) with RapiGest SF, an acid-labile surfactant designed to enhance the in-solution enzymatic digestion of proteins. The other method incorporated a commercially available sample preparation kit, iST-BCT, which contains standardized reagents. Significantly higher protein sequence coverage, albeit with lower digestion efficiency, was obtained with the immobilized trypsin + RapiGest SF workflow, whereas the iST-BCT workflow was quicker and had marginally better reproducibility. Protein relative abundance analysis revealed that the serum proteomes clustered primarily by the sample processing workflow and secondarily by disease state. We conducted a time course study to determine whether differences in the relative abundance of diagnostic high-grade serous ovarian cancer serum protein biomarker candidates were biased according to the duration of enzymatic digestion. Our results highlight the importance of optimizing enzymatic digestion kinetics according to the peptide targets of interest while considering the sensitivity of the downstream analytical method utilized in clinical proteomics workflows designed to measure biomarkers.

Novel proteomic technologies to address gaps in pre-clinical ovarian cancer biomarker discovery efforts

An estimated 20,000 women in the United States will receive a diagnosis of ovarian cancer in 2023. Late-stage diagnosis is associated with poor prognosis. There is a need for novel diagnostic biomarkers for ovarian cancer to improve early-stage detection and novel prognostic biomarkers to improve patient treatment. This review provides an overview of the clinicopathological features of ovarian cancer and the currently available biomarkers and treatment options. Two affinity-based platforms using proximity extension assays (Olink) and DNA aptamers (SomaLogic) are described in the context of highly reproducible and sensitive multiplexed assays for biomarker discovery. Recent developments in ion mobility spectrometry are presented as novel techniques to apply to the biomarker discovery pipeline. Examples are provided of how these aforementioned methods are being applied to biomarker discovery efforts in various diseases, including ovarian cancer. Translating novel ovarian cancer biomarkers from candidates in the discovery phase to

Proteomic Analysis of ARID1A-Deficient Ovarian Clear Cell Carcinoma Cells Reveals Differential Mitochondria ETC Subunit Abundances and Targetable Mitochondrial Pathways

ARID1A-deficient ovarian clear cell carcinoma is a highly lethal gynecologic cancer that depends heavily on mitochondrial respiration. Our biochemical and proteomic analyses reveal that ARID1A knockout cells exhibit marked upregulation of specific subunits within mitochondrial electron transport chain (ETC) Complexes I, III, and IV. However, this upregulation does not directly translate into increased sensitivity to broad-spectrum inhibitors targeting these complexes. These findings suggest that broad-spectrum mitochondrial inhibitors may not be effective therapeutic options for ARID1A-deficient cancers. Instead, the selective inhibition of specific ETC subunits may offer a more promising approach to exploit the metabolic vulnerabilities of ARID1A-deficient cells.

Proteomic Analysis Reveals Low-Dose PARP Inhibitor-Induced Differential Protein Expression in BRCA1-Mutated High-Grade Serous Ovarian Cancer Cells

High-grade serous ovarian cancer (HGSOC) is the most common form of ovarian cancer diagnosed in patients worldwide. Patients with

Quantitative Mass Spectrometry-Based Proteomics for Biomarker Development in Ovarian Cancer

Ovarian cancer is the most lethal gynecologic malignancy among women. Approximately 70–80% of patients with advanced ovarian cancer experience relapse within five years and develop platinum-resistance. The short life expectancy of patients with platinum-resistant or platinum-refractory disease underscores the need to develop new and more effective treatment strategies. Early detection is a critical step in mitigating the risk of disease progression from early to an advanced stage disease, and protein biomarkers have an integral role in this process. The best biological diagnostic tool for ovarian cancer will likely be a combination of biomarkers. Targeted proteomics methods, including mass spectrometry-based approaches, have emerged as robust methods that can address the chasm between initial biomarker discovery and the successful verification and validation of these biomarkers enabling their clinical translation due to the robust sensitivity, specificity, and reproducibility of these versatile methods. In this review, we provide background information on the fundamental principles of biomarkers and the need for improved treatment strategies in ovarian cancer. We also provide insight into the ways in which mass spectrometry-based targeted proteomics approaches can provide greatly needed solutions to many of the challenges related to ovarian cancer biomarker development.