Discovering and validating cancer genetic dependencies: approaches and pitfalls

Sequence-specific control of gene expression on a genome-wide scale is an important approach for understanding gene functions and for engineering genetic regulatory systems. We have recently described an RNA-based method, CRISPR interference (CRISPRi), for targeted silencing of transcription in bacteria and human cells. The CRISPRi system is derived from the Streptococcus pyogenes CRISPR (clustered regularly interspaced palindromic repeats) pathway, requiring only the coexpression of a catalytically inactive Cas9 protein and a customizable single guide RNA (sgRNA). The Cas9-sgRNA complex binds to DNA elements complementary to the sgRNA and causes a steric block that halts transcript elongation by RNA polymerase, resulting in the repression of the target gene. Here we provide a protocol for the design, construction and expression of customized sgRNAs for transcriptional repression of any gene of interest. We also provide details for testing the repression activity of CRISPRi using quantitative fluorescence assays and native elongating transcript sequencing. CRISPRi provides a simplified approach for rapid gene repression within 1-2 weeks. The method can also be adapted for high-throughput interrogation of genome-wide gene functions and genetic interactions, thus providing a complementary approach to RNA interference, which can be used in a wider variety of organisms.

SUMMARY Previous estimates of drug development success rates rely on relatively small samples from databases curated by the pharmaceutical industry and are subject to potential selection biases. Using a sample of 406 038 entries of clinical trial data for over 21 143 compounds from January 1, 2000 to October 31, 2015, we estimate aggregate clinical trial success rates and durations. We also compute disaggregated estimates across several trial features including disease type, clinical phase, industry or academic sponsor, biomarker presence, lead indication status, and time. In several cases, our results differ significantly in detail from widely cited statistics. For example, oncology has a 3.4% success rate in our sample vs. 5.1% in prior studies. However, after declining to 1.7% in 2012, this rate has improved to 2.5% and 8.3% in 2014 and 2015, respectively. In addition, trials that use biomarkers in patient-selection have higher overall success probabilities than trials without biomarkers.

Genetic robustness, or the ability of an organism to maintain fitness in the presence of mutations, can be achieved via protein feedback loops. Recent evidence suggests that organisms may also respond to mutations by upregulating related gene(s) independently of protein feedback loops, a phenomenon called transcriptional adaptation. However, the prevalence of transcriptional adaptation and its underlying molecular mechanisms are unknown. Here, by analyzing several models of transcriptional adaptation in zebrafish and mouse, we show a requirement for mRNA degradation. Alleles that fail to transcribe the mutated gene do not display transcriptional adaptation and exhibit more severe phenotypes than alleles displaying mutant mRNA decay. Transcriptome analysis reveals the upregulation of a substantial proportion of the genes that exhibit sequence similarity with the mutated gene’s mRNA, suggesting a sequence dependent mechanism. Besides implications for our understanding of disease-causing mutations, these findings will help design mutant alleles with minimal transcriptional adaptation-derived compensation.