Investigator

Andrew K. Godwin

University Of Kansas

AKGAndrew K. Godwin
Papers(6)
Defining the Ovarian …Targeting progesteron…Lineage specific extr…Dual targeting of Aur…Ovarian tumor cells g…Selective targeting o…
Institutions(1)
University Of Kansas

Papers

Defining the Ovarian Cancer Precancerous Landscape through Modeling Fallopian Tube Epithelium Reprogramming Driven by Extracellular Vesicles

Abstract Serous tubal intraepithelial carcinomas (lesions) in the human fallopian tube epithelium (hFTE) are theorized to give rise to high-grade serous ovarian cancers. Small extracellular vesicles (sEV) are known to mediate key signaling in both normal and cancerous tissues, but few ex vivo systems exist for studying the impact of sEV on hFTE tissue. In this study, we present a microfluidic tissue culture platform with combined spatial transcriptomic and proteomic readouts that allows us to profile dual responses in tissue exposed to sEV “messages”—capturing both short-term transcriptomic shifts in the tissue and long-term changes in protein cargo of secreted EVs (the “reply”). Using spatial transcriptomics, we show that the short-term 1-day exposure to ovarian cancer–derived sEVs alters expression of 68 transcripts in secretory cells, the progenitor of high-grade serous ovarian cancer, notably upregulating immune-related mRNA, including CXCL family chemokines, VCAM1, and pro-inflammatory mediators (NFKB1, IL1B, and IFNA7/17). Additionally, we observed that the long-term 14-day exposure to sEVs alters the expression of seven transcripts and 25 EV cargo proteins of fallopian tube–derived EVs (“secondary release EVs”) following stimulus from cancer EVs. Together, tissue transcriptomics and tissue-derived EV proteomics indicate that ovarian cancer–derived sEVs rewire target cell signaling to modify the tubal immune landscape. This study provides insights into the early molecular changes associated with the pathogenesis of ovarian cancer in its tissue of origin, providing a platform to study EV–tissue interactions and identify how sEVs drive cell signaling reprogramming in hFTE. Significance: We model the fallopian tube preneoplastic landscape using a microfluidic platform to study EV-induced stress and show that cancer EVs promote immune signaling changes representing the earliest stages of ovarian cancer pathogenesis.

Lineage specific extracellular vesicle-associated protein biomarkers for the early detection of high grade serous ovarian cancer

Abstract High grade serous ovarian carcinoma (HGSOC) accounts for ~ 70% of ovarian cancer cases. Non-invasive, highly specific blood-based tests for pre-symptomatic screening in women are crucial to reducing the mortality associated with this disease. Since most HGSOCs typically arise from the fallopian tubes (FT), our biomarker search focused on proteins found on the surface of extracellular vesicles (EVs) released by both FT and HGSOC tissue explants and representative cell lines. Using mass spectrometry, 985 EV proteins (exo-proteins) were identified that comprised the FT/HGSOC EV core proteome. Transmembrane exo-proteins were prioritized because these could serve as antigens for capture and/or detection. With a nano-engineered microfluidic platform, six newly discovered exo-proteins (ACSL4, IGSF8, ITGA2, ITGA5, ITGB3, MYOF) plus a known HGSOC associated protein, FOLR1 exhibited classification performance ranging from 85 to 98% in a case–control study using plasma samples representative of early (including stage IA/B) and late stage (stage III) HGSOCs. Furthermore, by a linear combination of IGSF8 and ITGA5 based on logistic regression analysis, we achieved a sensitivity of 80% with 99.8% specificity and a positive predictive value of 13.8%. Importantly, these exo-proteins also can accurately discriminate between ovarian and 12 types of cancers commonly diagnosed in women. Our studies demonstrate that these lineage-associated exo-biomarkers can detect ovarian cancer with high specificity and sensitivity early and potentially while localized to the FT when patient outcomes are more favorable.

Dual targeting of Aurora Kinase A and poly (ADP-ribose) polymerase as a therapeutic option for patients with ovarian cancer: preclinical evaluations

Epithelial ovarian cancers (EOCs) are often diagnosed at an advanced stage, leading to poor survival outcomes despite chemotherapeutic and surgical advances. Precision oncology strategies have been developed to treat EOCs characterized by BRCA1 and BRCA2 inactivation with consequent homologous recombination (HR) repair defects. HR deficiency enhances tumor sensitivity to poly (ADP-ribose) polymerase (PARP) inhibitors (PARPis), approved for EOCs as maintenance therapy, although they have been discontinued as recurrent EOC monotherapy. However, combination treatment with PARPis may be a viable alternate strategy for EOCs. Moreover, EOC patients with wild-type BRCA are ineligible for PARPs, necessitating novel approaches. We previously discovered that inhibiting Aurora kinase A (AURKA) downregulates PARP and BRCA1/2 expression in EOCs and may constitute a viable approach for EOCs. Herein, we evaluated combined PARPi olaparib with the selective AURKA inhibitor (AURKAi) VIC-1911 in six different patient-derived xenograft (PDX) EOC models, including two with mutant BRCA1, two with mutant BRCA2, one with mutant BRCA1/2, and one with wild-type BRCA1/2. We found that combined olaparib + VIC-1911 treatment reduced tumor volumes and weights by up 90% in some PDX models, with synergistic effect compared to olaparib and VIC-1911 monotherapy. Additionally, combined olaparib + VIC-1911 treatment improved survival of mice harboring both mutant BRCA1 and wild-type BRCA1/2 PDXs. Generally, mice tolerated the drug combinations well during treatment, though loss of body weight was observed at higher drug dosages and with intensive treatment regimens. Our studies indicate a synergistic benefit from combined PARPi and AURKAi in mutant and wild-type BRCA EOC tumors.

23Works
6Papers
Breast NeoplasmsOvarian NeoplasmsPrognosisBiomarkers, TumorTriple Negative Breast NeoplasmsCell Line, TumorGenetic Predisposition to DiseaseCarcinoma, Ovarian Epithelial