Investigating proteogenomic divergence in patient-derived xenograft models of ovarian cancer.

Within ovarian cancer research, patient-derived xenograft (PDX) models recapitulate histologic features and genomic aberrations found in original tumors. However, conflicting data from published studies have demonstrated significant transcriptional differences between PDXs and original tumors, challenging the fidelity of these models. We employed a quantitative mass spectrometry-based proteomic approach coupled with generation of patient-specific databases using RNA-seq data to investigate the proteogenomic landscape of serially-passaged PDX models established from two patients with distinct subtypes of ovarian cancer.

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.

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 -mutated HGSOC have benefited from targeted treatments such as poly(ADP-ribose) polymerase inhibitors (PARPi). Despite the initial success of PARPi-based ovarian cancer treatment regimens, approximately 70% of patients with ovarian cancer relapse and the 5-year survival rate remains at 30%.