Abstract B01: Gene expression network--based identification of drugs targeting advanced ovarian cancer

Conference Paper


  • Abstract Ovarian cancer remains the deadliest of gynecologic malignancies. A major challenge in ovarian cancer treatment is that it is often diagnosed at stages when the cancer has already formed metastases throughout the peritoneum. While chemotherapy shows efficacy on the original tumor, the metastatic legions are often resistant to traditional chemotherapy regimens. Thus, the development of new therapy that targets metastatic ovarian cancer is necessary. Three-dimensional culture systems of ovarian spheroids are used to model the growth of ovarian cancer at these later stages. Thus, to target advanced ovarian cancer, we focused on identifying drugs that specifically target ovarian spheroids in the laboratory, hypothesizing that these drugs would target the metastatic legions in ovarian cancer patients. To do this, we identified genes that were modulated in ovarian cancer cell lines when grown in 3D culture, developing a 3D gene signature. Using this gene signature, we queried the Connectivity Map from the Broad Institute for drugs that induced the opposite gene expression patterns as the 3D signature we identified, hypothesizing that these drugs could potentially target signaling pathways activated in ovarian spheroids. From this approach, securinine was identified as a molecule that inhibits the 3D growth of ovarian cancer cells. To understand the mechanism of action of securinine, we analyzed genes modulated by securinine treatment. Pathway analysis identified Signal Transducer and Activator of Transcription 3 (STAT3) as being a transcription factor that is inhibited by securinine. STAT3 is a latent transcription factor that is activated upon tyrosine phosphorylation. Once activated, STAT3 regulates the expression of many genes involved in survival, growth, and metastasis. STAT3 has been found to be active in ovarian cancer, and we have demonstrated that the STAT3 signaling pathway is activated and necessary in ovarian cancer spheroids. While we have found that securinine does not inhibit STAT3 tyrosine phosphorylation, securinine inhibits the expression of a STAT3 responsive reporter and STAT3 target genes, verifying that securinine inhibits STAT3 activity. Computational analysis has found that the STAT3 gene signature is enhanced in cisplatin-resistant ovarian cancer spheroids and that genes inhibited by securinine are upregulated in these cells. This raises the possibility that targeting STAT3 with securinine will be beneficial in the treatment of cisplatin-resistant ovarian cancer. Thus, using gene expression signatures of 3D growth has identified securinine as an inhibitor that targets signaling pathways activated in ovarian cancer spheroids, identifying a potential drug for the treatment of advanced-stage ovarian cancer. Citation Format: Sarah R. Walker, Zachary T. Giaccone, David A. Frank. Gene expression network--based identification of drugs targeting advanced ovarian cancer. [abstract]. In: Proceedings of the AACR Conference: Addressing Critical Questions in Ovarian Cancer Research and Treatment; Oct 1-4, 2017; Pittsburgh, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(15_Suppl):Abstract nr B01.
  • Authors

  • Walker, Sarah
  • Giaccone, Zachary T
  • Frank, David A
  • Status

    Publication Date

  • August 1, 2018
  • Has Subject Area

    Published In

    Digital Object Identifier (doi)

    Start Page

  • B01
  • End Page

  • B01
  • Volume

  • 24
  • Issue

  • 15_Supplement