A dynamical framework for complex fractional killing

• Published in: Scientific reports Vol. 7; no. 1; pp. 8002 - 12
• Main Authors: Ballweg, Richard, Paek, Andrew L., Zhang, Tongli
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 14.08.2017; Nature Publishing Group; Nature Portfolio
• Subjects: 631/114/2397; 631/553/2393; 631/553/2699; 631/553/2703; 631/67/70; Animals; Antineoplastic Agents - pharmacology; Apoptosis; Apoptosis - drug effects; Cancer; Cell death; Cell fate; Chemotherapy; Drug resistance; Drug Resistance, Neoplasm; Genotypes; Humanities and Social Sciences; Humans; Models, Theoretical; multidisciplinary; p53 Protein; Science; Science (multidisciplinary); Tumor cells; Tumor Suppressor Protein p53 - genetics; Tumor Suppressor Protein p53 - metabolism
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-017-07422-2

When chemotherapy drugs are applied to tumor cells with the same or similar genotypes, some cells are killed, while others survive. This fractional killing contributes to drug resistance in cancer. Through an incoherent feedforward loop, chemotherapy drugs not only activate p53 to induce cell death, but also promote the expression of apoptosis inhibitors which inhibit cell death. Consequently, cells in which p53 is activated early undergo apoptosis while cells in which p53 is activated late survive. The incoherent feedforward loop and the essential role of p53 activation timing makes fractional killing a complex dynamical challenge, which is hard to understand with intuition alone. To better understand this process, we have constructed a representative model by integrating the control of apoptosis with the relevant signaling pathways. After the model was trained to recapture the observed properties of fractional killing, it was analyzed with nonlinear dynamical tools. The analysis suggested a simple dynamical framework for fractional killing, which predicts that cell fate can be altered in three possible ways: alteration of bifurcation geometry, alteration of cell trajectories, or both. These predicted categories can explain existing strategies known to combat fractional killing and facilitate the design of novel strategies.