Targeting CDK to Prevent and Treat Retinoblastoma and other Cancers
type: CreativeWork
description: Pharmaceutical investment in cell cycle inhibitors has been immense, yet the efficacy in treating established tumors is poor in most cases. Considering that tumor cells co-opt the cell cycle to grow, it is unclear why most cell cycle inhibitors, like CDK inhibitors, have failed to pass Phase II clinical trials. Since expansion of premalignant cells is critical for tumor establishment, we wondered whether CDK inhibitors would be more effective in prevention than treatment. To examine this, we leveraged pharmaceutical and genetic strategies to demonstrate that initiated retinal cells and nascent retinoblastoma tumors are exquisitely sensitive to CDK inhibition in vivo. To uncover what factors predict CDK inhibitor sensitivity, we generated a transcriptional signature, which reports real-time activity of CDK2 (a potent target of most CDK inhibitors). Surprisingly, we found that CDK2 activity does not predict CDK2 inhibitor sensitivity. Instead, drug sensitivity is predicted by a subset of Protein Processing networks (e.g. translation, mRNA stability, splicing, and protein targeting). Through mining publically available datasets, we unravel a novel co-regulatory/co-dependent relationship between CDK2 activity and Protein Processing networks. Leveraging Protein Processing networks, we define which cancers may be best suited for CDK inhibition in the clinic (e.g. diffuse B-cell Lymphoma). Overall, we offer two strategies to bolster the clinical translation of CDK inhibitors and gain further insight into how cancer cells rewire their cell cycle machinery in order to bypass therapy.
abstract: Pharmaceutical investment in cell cycle inhibitors has been immense, yet the efficacy in treating established tumors is poor in most cases. Considering that tumor cells co-opt the cell cycle to grow, it is unclear why most cell cycle inhibitors, like CDK inhibitors, have failed to pass Phase II clinical trials. Since expansion of premalignant cells is critical for tumor establishment, we wondered whether CDK inhibitors would be more effective in prevention than treatment. To examine this, we leveraged pharmaceutical and genetic strategies to demonstrate that initiated retinal cells and nascent retinoblastoma tumors are exquisitely sensitive to CDK inhibition in vivo. To uncover what factors predict CDK inhibitor sensitivity, we generated a transcriptional signature, which reports real-time activity of CDK2 (a potent target of most CDK inhibitors). Surprisingly, we found that CDK2 activity does not predict CDK2 inhibitor sensitivity. Instead, drug sensitivity is predicted by a subset of Protein Processing networks (e.g. translation, mRNA stability, splicing, and protein targeting). Through mining publically available datasets, we unravel a novel co-regulatory/co-dependent relationship between CDK2 activity and Protein Processing networks. Leveraging Protein Processing networks, we define which cancers may be best suited for CDK inhibition in the clinic (e.g. diffuse B-cell Lymphoma). Overall, we offer two strategies to bolster the clinical translation of CDK inhibitors and gain further insight into how cancer cells rewire their cell cycle machinery in order to bypass therapy.
author: McCurdy, Sean R.
date published: 2016-06
date modified: 2026-07-27T21:28:02Z
provider: University of Toronto
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of Toronto

PropertyValue
property ID: Handle
value: http://hdl.handle.net/1807/89255