Title |
Phenotypic Plasticity, Bet-Hedging, and Androgen Independence in Prostate Cancer: Role of Non-Genetic Heterogeneity
|
---|---|
Published in |
Frontiers in oncology, March 2018
|
DOI | 10.3389/fonc.2018.00050 |
Pubmed ID | |
Authors |
Mohit Kumar Jolly, Prakash Kulkarni, Keith Weninger, John Orban, Herbert Levine |
Abstract |
It is well known that genetic mutations can drive drug resistance and lead to tumor relapse. Here, we focus on alternate mechanisms-those without mutations, such as phenotypic plasticity and stochastic cell-to-cell variability that can also evade drug attacks by giving rise to drug-tolerant persisters. The phenomenon of persistence has been well-studied in bacteria and has also recently garnered attention in cancer. We draw a parallel between bacterial persistence and resistance against androgen deprivation therapy in prostate cancer (PCa), the primary standard care for metastatic disease. We illustrate how phenotypic plasticity and consequent mutation-independent or non-genetic heterogeneity possibly driven by protein conformational dynamics can stochastically give rise to androgen independence in PCa, and suggest that dynamic phenotypic plasticity should be considered in devising therapeutic dosing strategies designed to treat and manage PCa. |
X Demographics
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Switzerland | 1 | 9% |
United States | 1 | 9% |
Unknown | 9 | 82% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 9 | 82% |
Scientists | 2 | 18% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 110 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 25 | 23% |
Student > Ph. D. Student | 22 | 20% |
Student > Bachelor | 10 | 9% |
Student > Master | 7 | 6% |
Student > Doctoral Student | 5 | 5% |
Other | 13 | 12% |
Unknown | 28 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 33 | 30% |
Agricultural and Biological Sciences | 13 | 12% |
Medicine and Dentistry | 7 | 6% |
Engineering | 5 | 5% |
Immunology and Microbiology | 4 | 4% |
Other | 15 | 14% |
Unknown | 33 | 30% |