Genetic dependencies associated with transcription factor activities in human cancer cell lines [CROP-seq]

Transcription factors (TFs) are important mediators of aberrant transcriptional programs in cancer cells. In this study, we focused on TF activity (TFa) as a new biomarker for cell line-selective anti-proliferative effects, in that high TFa predicts sensitivity to loss-of-function of a given gene (i.e., genetic dependencies (GD)). Our linear regression-based framework identified 3,047 pan-cancer and 3,952 cancer-typespecific candidate TFa-GD associations from cell line data, which were then crossexamined for impact on survival in patient cohorts. One of the most prominent biomarkers was TEAD1 activity, whose associations with its predicted GDs were validated through experimental evidence as proof of concept. Overall, these TFa-GD associations represent an attractive resource for identifying innovative, biomarkerdriven hypotheses for drug discovery programs in oncology. We performed a pooled CRISPRko screen followed by single cell RNA sequencing (CROP-seq) on human SNU-761 cell line using a library containing 450 sgRNAs targeting 108 genes and non-targeting controls. Cells were processed on 10X Genomics platform using 5’ HT chemistry on Day 5 and Day 10 timepoints. Whole transcriptome, sgRNA and cell hashing libraries were prepared from each time point and submitted for next-generation sequencing.