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The Hippo pathway effectors Yes-associated protein 1 (YAP) and its homolog TAZ are transcriptional coactivators that control gene expression by binding to TEA domain (TEAD) family transcription factors. The YAP/TAZ–TEAD complex is a key regulator of cancer-specific transcriptional programs, which promote tumor progression in diverse types of cancer, including breast cancer. Despite intensive efforts, the YAP/TAZ–TEAD complex in cancer has remained largely undruggable due to an incomplete mechanistic understanding. Here, we report that nuclear phosphoinositides function as cofactors that mediate the binding of YAP/TAZ to TEADs. The enzymatic products of phosphoinositide kinases PIPKIα and IPMK, including phosphatidylinositol 4,5-bisphosphate (PI(4,5)P₂) and phosphatidylinositol 3,4,5-trisphosphate (P(I3,4,5)P₃), bridge the binding of YAP/TAZ to TEAD. Inhibiting these kinases or the association of YAP/TAZ with PI(4,5)P₂and PI(3,4,5)P₃attenuates YAP/TAZ interaction with the TEADs, the expression of YAP/TAZ target genes, and breast cancer cell motility. Although we could not conclusively exclude the possibility that other enzymatic products of IPMK such as inositol phosphates play a role in the mechanism, our results point to a previously unrecognized role of nuclear phosphoinositide signaling in control of YAP/TAZ activity and implicate this pathway as a potential therapeutic target in YAP/TAZ-driven breast cancer.

 

Abstract Many measurements at the LHC require efficient identification of heavy-flavour jets, i.e. jets originating from bottom (b) or charm (c) quarks. An overview of the algorithms used to identify c jets is described and a novel method to calibrate them is presented. This new method adjusts the entire distributions of the outputs obtained when the algorithms are applied to jets of different flavours. It is based on an iterative approach exploiting three distinct control regions that are enriched with either b jets, c jets, or light-flavour and gluon jets. Results are presented in the form of correction factors evaluated using proton-proton collision data with an integrated luminosity of 41.5 fb -1 at  √s = 13 TeV, collected by the CMS experiment in 2017. The closure of the method is tested by applying the measured correction factors on simulated data sets and checking the agreement between the adjusted simulation and collision data. Furthermore, a validation is performed by testing the method on pseudodata, which emulate various mismodelling conditions. The calibrated results enable the use of the full distributions of heavy-flavour identification algorithm outputs, e.g. as inputs to machine-learning models. Thus, they are expected to increase the sensitivity of future physics analyses.