BID expression determines the apoptotic fate of cancer cells after abrogation of the spindle assembly checkpoint by AURKB or TTK inhibitors.

BACKGROUND: Drugs targeting the spindle assembly checkpoint (SAC), such as inhibitors of Aurora kinase B (AURKB) and dual specific protein kinase TTK, are in different stages of clinical development. However, cell response to SAC abrogation is poorly understood and there are no markers for patient selection. METHODS: A panel of 53 tumor cell lines of different origins was used. The effects of drugs were analyzed by MTT and flow cytometry. Copy number status was determined by FISH and Q-PCR; mRNA expression by nCounter and RT-Q-PCR and protein expression by Western blotting. CRISPR-Cas9 technology was used for gene knock-out (KO) and a doxycycline-inducible pTRIPZ vector for ectopic expression. Finally, in vivo experiments were performed by implanting cultured cells or fragments of tumors into immunodeficient mice. RESULTS: Tumor cells and patient-derived xenografts (PDXs) sensitive to AURKB and TTK inhibitors consistently showed high expression levels of BH3-interacting domain death agonist (BID), while cell lines and PDXs with low BID were uniformly resistant. Gene silencing rendered BID-overexpressing cells insensitive to SAC abrogation while ectopic BID expression in BID-low cells significantly increased sensitivity. SAC abrogation induced activation of CASP-2, leading to cleavage of CASP-3 and extensive cell death only in presence of high levels of BID. Finally, a prevalence study revealed high BID mRNA in 6% of human solid tumors. CONCLUSIONS: The fate of tumor cells after SAC abrogation is driven by an AURKB/ CASP-2 signaling mechanism, regulated by BID levels. Our results pave the way to clinically explore SAC-targeting drugs in tumors with high BID expression.

Activating mutations cluster in the "molecular brake" regions of protein kinases and do not associate with conserved or catalytic residues.

Mutations leading to activation of proto-oncogenic protein kinases (PKs) are a type of drivers crucial for understanding tumorogenesis and as targets for antitumor drugs. However, bioinformatics tools so far developed to differentiate driver mutations, typically based on conservation considerations, systematically fail to recognize activating mutations in PKs. Here, we present the first comprehensive analysis of the 407 activating mutations described in the literature, which affect 41 PKs. Unexpectedly, we found that these mutations do not associate with conserved positions and do not directly affect ATP binding or catalytic residues. Instead, they cluster around three segments that have been demonstrated to act, in some PKs, as "molecular brakes" of the kinase activity. This finding led us to hypothesize that an auto inhibitory mechanism mediated by such "brakes" is present in all PKs and that the majority of activating mutations act by releasing it. Our results also demonstrate that activating mutations of PKs constitute a distinct group of drivers and that specific bioinformatics tools are needed to identify them in the numerous cancer sequencing projects currently underway. The clustering in three segments should represent the starting point of such tools, a hypothesis that we tested by identifying two somatic mutations in EPHA7 that might be functionally relevant.

Kin-Driver: a database of driver mutations in protein kinases.

Somatic mutations in protein kinases (PKs) are frequent driver events in many human tumors, while germ-line mutations are associated with hereditary diseases. Here we present Kin-driver, the first database that compiles driver mutations in PKs with experimental evidence demonstrating their functional role. Kin-driver is a manual expert-curated database that pays special attention to activating mutations (AMs) and can serve as a validation set to develop new generation tools focused on the prediction of gain-of-function driver mutations. It also offers an easy and intuitive environment to facilitate the visualization and analysis of mutations in PKs. Because all mutations are mapped onto a multiple sequence alignment, analogue positions between kinases can be identified and tentative new mutations can be proposed for studying by transferring annotation. Finally, our database can also be of use to clinical and translational laboratories, helping them to identify uncommon AMs that can correlate with response to new antitumor drugs. The website was developed using PHP and JavaScript, which are supported by all major browsers; the database was built using MySQL server. Kin-driver is available at: http://kin-driver.leloir.org.ar/