Research Papers:

A mathematical theory of the transcription repression (TR) therapy of cancer - whether and how it may work

Yuxin Chen, Haijun Wen and Chung-I Wu _

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Oncotarget. 2017; 8:38642-38649. https://doi.org/10.18632/oncotarget.16957

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Yuxin Chen1,*, Haijun Wen1,*, Chung-I Wu1,2,3

1State Key Laboratory of Bio-control, School of Life Science, Sun Yat-Sen University, Guangzhou, China

2Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing, China

3Department of Ecology and Evolution, University of Chicago, Chicago, Illinois, USA

*These authors contributed equally to this study and should be considered as co-first authors

Correspondence to:

Chung-I Wu, email: ciwu@uchicago.edu

Keywords: cancer therapy theory, transcription repression, transcription addiction, actinomycin D, evolution of cancer

Received: February 23, 2017     Accepted: March 29, 2017     Published: April 08, 2017


Transcription repression (TR) therapy of cancer has been widely discussed. Here, TR refers to global repression of transcription rather than specific targeting of cancer-causing genes such as MYC. TR drugs inhibit transcription by binding to the transcribed DNA or to RNA polymerase; for example, actinomycin D has been extensively used in research and therapy to shut down transcription globally [17]. As proliferating cells demand a high rate of transcription, restricting transcript production could be effective in slowing down cell proliferation. However, TR also deprives other less proliferative cells of new transcripts, thus leading to substantial toxicity [1, 8, 9]. We now develop a mathematical theory to exploit the greater demand for transcription in highly proliferating cells. A new strategy, referred to as the TRR (transcript repression-recovery) model, would insert a recovery phase to allow the more slowly proliferating cells to recover. It is most effective to have strong blocking for a short period (a few hours) followed by a longer recovery phase in each cell cycle. Hence, TRR can potentially achieve selective killing of cells based on their global transcription needs but precise fine-tuning is necessary.

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PII: 16957