Kinase and phosphatase overexpression drives tumorigenesis and drug resistance.,We previously developed a mass-cytometry-based single-cell proteomics approach that enables quantitative assessment of overexpression effects on cell signaling.,Here, we applied this approach in a human kinome- and phosphatome-wide study to assess how 649 individually overexpressed proteins modulated cancer-related signaling in HEK293T cells in an abundance-dependent manner.,Based on these data, we expanded the functional classification of human kinases and phosphatases and showed that the overexpression effects include non-catalytic roles.,We detected 208 previously unreported signaling relationships.,The signaling dynamics analysis indicated that the overexpression of ERK-specific phosphatases sustains proliferative signaling.,This suggests a phosphatase-driven mechanism of cancer progression.,Moreover, our analysis revealed a drug-resistant mechanism through which overexpression of tyrosine kinases, including SRC, FES, YES1, and BLK, induced MEK-independent ERK activation in melanoma A375 cells.,These proteins could predict drug sensitivity to BRAF-MEK concurrent inhibition in cells carrying BRAF mutations.,•Human kinome- and phosphatome-wide screen of overexpression-altered signaling network•Classification of the kinome and phosphatome based on abundance-dependent effects•Phosphatase overexpression sustains MAPK-ERK signaling by halting negative feedback•SRC, FES, YES1, and BLK lead to drug resistance in BRAF-MEK combined inhibition,Human kinome- and phosphatome-wide screen of overexpression-altered signaling network,Classification of the kinome and phosphatome based on abundance-dependent effects,Phosphatase overexpression sustains MAPK-ERK signaling by halting negative feedback,SRC, FES, YES1, and BLK lead to drug resistance in BRAF-MEK combined inhibition,Lun et al. perform mass-cytometry-based single-cell analysis to study how the expression levels of 649 kinases and phosphatases affect the intracellular signaling network.,They expand the functional classification of the kinome and phosphatome based on abundance-dependent effects and identify novel signaling mechanisms underlying overexpression-driven diseases and drug resistance.
Single-cell RNA-seq's (scRNA-seq) unprecedented cellular resolution at a genome-wide scale enables us to address questions about cellular heterogeneity that are inaccessible using methods that average over bulk tissue extracts.,However, scRNA-seq data sets also present additional challenges such as high transcript dropout rates, stochastic transcription events, and complex population substructures.,Here, we present a single-cell RNA-seq analysis and klustering evaluation (SAKE), a robust method for scRNA-seq analysis that provides quantitative statistical metrics at each step of the analysis pipeline.,Comparing SAKE to multiple single-cell analysis methods shows that most methods perform similarly across a wide range of cellular contexts, with SAKE outperforming these methods in the case of large complex populations.,We next applied the SAKE algorithms to identify drug-resistant cellular populations as human melanoma cells respond to targeted BRAF inhibitors (BRAFi).,Single-cell RNA-seq data from both the Fluidigm C1 and 10x Genomics platforms were analyzed with SAKE to dissect this problem at multiple scales.,Data from both platforms indicate that BRAF inhibitor-resistant cells can emerge from rare populations already present before drug application, with SAKE identifying both novel and known markers of resistance.,These experimentally validated markers of BRAFi resistance share overlap with previous analyses in different melanoma cell lines, demonstrating the generality of these findings and highlighting the utility of single-cell analysis to elucidate mechanisms of BRAFi resistance.