# Delineating the dystopian nature of the cell cycle in cancer

> **NIH NIH R01** · ROSWELL PARK CANCER INSTITUTE CORP · 2022 · $549,360

## Abstract

ABSTRACT: In the classical mammalian cell cycle model, CDK and cyclin complexes are responsible for
driving specific events in a sequential fashion. Mitogenic or oncogenic signals drive the activation of CDK4/6
complexes that initiate cell cycle progression. These complexes promote RB phosphorylation that leads to the
expression of a highly conserved cadre of genes that are required for progression through the remainder of the
cell cycle. The concept put forward by this model is that cell cycle control is linear and highly predictable.
However, recent findings related to the inter-dependencies of CDK/cyclins illustrate the need for better
understanding the cell cycle repertoires that are operable in tumors. In preliminary data using unbiased and
targeted approaches we have interrogated the extent to which the “utopian” simple version of the cell cycle
breaks-down. This work indicates that in cancer models there are multiple different cell cycle modes, which
have significance for tumorigenic proliferation and therapeutic interventions. Here we will take an integrated
approach to fundamentally understand “dystopian” cell cycle states (Aim 1) and define mechanisms of collateral
therapeutic resistance and new vulnerabilities (Aim 2) which associate with non-canonical cell cycle states.

## Key facts

- **NIH application ID:** 10355878
- **Project number:** 1R01CA267647-01
- **Recipient organization:** ROSWELL PARK CANCER INSTITUTE CORP
- **Principal Investigator:** Erik Knudsen
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $549,360
- **Award type:** 1
- **Project period:** 2022-06-03 → 2027-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10355878

## Citation

> US National Institutes of Health, RePORTER application 10355878, Delineating the dystopian nature of the cell cycle in cancer (1R01CA267647-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10355878. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*