Tumor suppressor p53 plays an important role in mediating growth inhibition upon telomere dysfunction. Here, we show that loss of the p53 target gene cyclin-dependent kinase inhibitor 1A (CDKN1A, also known as p21(WAF1/CIP1)) increases apoptosis induction following telomerase inhibition in a variety of cancer cell lines and mouse xenografts. This effect is highly specific to p21, as loss of other checkpoint proteins and CDK inhibitors did not affect apoptosis. In telomerase, inhibited cell loss of p21 leads to E2F1- and p53-mediated transcriptional activation of p53-upregulated modulator of apoptosis, resulting in increased apoptosis. Combined genetic or pharmacological inhibition of telomerase and p21 synergistically suppresses tumor growth. Furthermore, we demonstrate that simultaneous inhibition of telomerase and p21 also suppresses growth of tumors containing mutant p53 following pharmacological restoration of p53 activity. Collectively, our results establish that inactivation of p21 leads to increased apoptosis upon telomerase inhibition and thus identify a genetic vulnerability that can be exploited to treat many human cancers containing either wild-type or mutant p53.

The move from reading to writing the human genome offers new opportunities to improve human health. The United States National Institutes of Health (NIH) Somatic Cell Genome Editing (SCGE) Consortium aims to accelerate the development of safer and more-effective methods to edit the genomes of disease-relevant somatic cells in patients, even in tissues that are difficult to reach. Here we discuss the consortium's plans to develop and benchmark approaches to induce and measure genome modifications, and to define downstream functional consequences of genome editing within human cells. Central to this effort is a rigorous and innovative approach that requires validation of the technology through third-party testing in small and large animals. New genome editors, delivery technologies and methods for tracking edited cells in vivo, as well as newly developed animal models and human biological systems, will be assembled-along with validated datasets-into an SCGE Toolkit, which will be disseminated widely to the biomedical research community. We visualize this toolkit-and the knowledge generated by its applications-as a means to accelerate the clinical development of new therapies for a wide range of conditions.