Program Official

Principal Investigator

Jennifer Kehlet
Barton
Awardee Organization

University Of Arizona
United States

Fiscal Year
2016
Activity Code
R01
Project End Date

Validating a mouse model of ovarian cancer for early detection through imaging

Despite advances in treatment strategies, ovarian cancer remains the deadliest gynecological malignancy and the 5th largest cancer killer in women. Located deep in the body, with few early symptoms and no effective screening technique, ovarian cancer has remained stubbornly difficult to understand, much less effectively combat. Ovarian cancer is almost always discovered at an advanced stage. Therefore, women at high risk for ovarian cancer are usually counseled to have a prophylactic oophorectomy, which can reduce risk of death from cancer but comes with associated morbidity and may reduce life span. The key to reducing the mortality from ovarian cancer is to develop an effective early detection technique. The investigators have shown that high resolution optical imaging, including optical coherence tomography (OCT) fluorescence imaging (FI), and multiphoton microscopy (MPM) can differentiate normal from advanced stage cancer in humans and mouse models. However, imaging biomarkers of early stage cancer are not yet known. Developing imaging markers is highly impractical in women due to the low number of early stage cancers detected, and the inability to follow cancer development over time. A relevant, validated mouse model of early stage high grade serous carcinoma (HGSC) is needed to develop imaging biomarkers that could be translated to an early detection system for women. Specific Aim 1: Validate a model for early stage ovarian cancer. The MISIIR-TAg mouse develops spontaneous bilateral HGSC. Because most women who develop ovarian cancer are post-menopausal, we will augment this transgenic model with administration of 4-vinylcyclohexene diepoxide (VCD), which induces selective follicular atresia and mimics menopause. At very early time points in cancer development, we will examine ovarian/fallopian tube morphology, gene expression, and cell surface marker expression, creating a roadmap of changes that occur during early OC. We will compare our findings on gene expression to those seen in women by comparison to published gene atlases and curated data sets, as well as validating select cell surface markers in mouse and human tissue microarrays. Specific Aim 2. Develop imaging biomarkers of early stage ovarian cancer. Using the validated mouse model, we will obtain in vivo optical images and develop qualitative and quantitative optical image features of ovaries and fallopian tubes that identify cancer at the earliest time points. We will follow mice over time, and test sensitivity and specificity of these in vivo image markers for single and multiple modalities to determine the earliest time point that cancer can reliably be detected. Additionally, we will develop contrast agents targeted to overexpressed cell surface markers, for potential increase in sensitivity. At the end of this project, we will have the information necessary to develop a viable optical imaging method for early detection of HGSC, which has the potential to dramatically reduce mortality from this disease.

Publications

  • Sawyer TW, Chandra S, Rice PFS, Koevary JW, Barton JK. Three-dimensional texture analysis of optical coherence tomography images of ovarian tissue. Physics in medicine and biology. 2018 Dec 4;63(23):235020. PMID: 30511664
  • Hoyer PB, Rice PF, Howard CC, Koevary JW, Dominguez Cooks JP, Hutchens GV, Chambers SK, Craig ZR, Connolly DC, Barton JK. Comparison of Reproductive Function in Female TgMISIIR-TAg Transgenic and Wildtype C57BL/6 Mice. Comparative medicine. 2019 Feb 1;69(1):16-21. Epub 2018 Dec 27. PMID: 30591091
  • Sawyer TW, Rice PFS, Sawyer DM, Koevary JW, Barton JK. Evaluation of segmentation algorithms for optical coherence tomography images of ovarian tissue. Journal of medical imaging (Bellingham, Wash.). 2019 Jan;6(1):014002. Epub 2019 Jan 29. PMID: 30746391
  • Kleinschmidt EG, Miller NLG, Ozmadenci D, Tancioni I, Osterman CD, Barrie AM, Taylor KN, Ye A, Jiang S, Connolly DC, Stupack DG, Schlaepfer DD. Rgnef promotes ovarian tumor progression and confers protection from oxidative stress. Oncogene. 2019 Sep;38(36):6323-6337. Epub 2019 Jul 15. PMID: 31308489
  • Sawyer TW, Koevary JW, Rice FPS, Howard CC, Austin OJ, Connolly DC, Cai KQ, Barton JK. Quantification of multiphoton and fluorescence images of reproductive tissues from a mouse ovarian cancer model shows promise for early disease detection. Journal of biomedical optics. 2019 Sep;24(9):1-16. PMID: 31571434
  • Sawyer TW, Koevary JW, Howard CC, Austin OJ, Rice PFS, Hutchens GV, Chambers SK, Connolly DC, Barton JK. Fluorescence and Multiphoton Imaging for Tissue Characterization of a Model of Postmenopausal Ovarian Cancer. Lasers in surgery and medicine. 2020 Dec;52(10):993-1009. Epub 2020 Apr 20. PMID: 32311117
  • Diaz Osterman CJ, Ozmadenci D, Kleinschmidt EG, Taylor KN, Barrie AM, Jiang S, Bean LM, Sulzmaier FJ, Jean C, Tancioni I, Anderson K, Uryu S, Cordasco EA, Li J, Chen XL, Fu G, Ojalill M, Rappu P, Heino J, Mark AM, Xu G, Fisch KM, Kolev VN, Weaver DT, Pachter JA, Győrffy B, McHale MT, Connolly DC, Molinolo A, Stupack DG, Schlaepfer DD. FAK activity sustains intrinsic and acquired ovarian cancer resistance to platinum chemotherapy. eLife. 2019 Sep 3;8. PMID: 31478830