RESUMEN
Resistance to therapy commonly develops in patients with high-grade serous ovarian carcinoma (HGSC) and triple-negative breast cancer (TNBC), urging the search for improved therapeutic combinations and their predictive biomarkers. Starting from a CRISPR knockout screen, we identified that loss of RB1 in TNBC or HGSC cells generates a synthetic lethal dependency on casein kinase 2 (CK2) for surviving the treatment with replication-perturbing therapeutics such as carboplatin, gemcitabine, or PARP inhibitors. CK2 inhibition in RB1-deficient cells resulted in the degradation of another RB family cell cycle regulator, p130, which led to S phase accumulation, micronuclei formation, and accelerated PARP inhibition-induced aneuploidy and mitotic cell death. CK2 inhibition was also effective in primary patient-derived cells. It selectively prevented the regrowth of RB1-deficient patient HGSC organoids after treatment with carboplatin or niraparib. As about 25% of HGSCs and 40% of TNBCs have lost RB1 expression, CK2 inhibition is a promising approach to overcome resistance to standard therapeutics in large strata of patients.
Asunto(s)
Quinasa de la Caseína II , Proteínas de Unión a Retinoblastoma , Humanos , Quinasa de la Caseína II/antagonistas & inhibidores , Quinasa de la Caseína II/metabolismo , Quinasa de la Caseína II/genética , Proteínas de Unión a Retinoblastoma/metabolismo , Proteínas de Unión a Retinoblastoma/genética , Femenino , Línea Celular Tumoral , Neoplasias de la Mama Triple Negativas/tratamiento farmacológico , Neoplasias de la Mama Triple Negativas/genética , Neoplasias de la Mama Triple Negativas/patología , Neoplasias de la Mama Triple Negativas/metabolismo , Neoplasias Ováricas/tratamiento farmacológico , Neoplasias Ováricas/genética , Neoplasias Ováricas/patología , Neoplasias Ováricas/metabolismo , Ubiquitina-Proteína Ligasas/metabolismo , Ubiquitina-Proteína Ligasas/genética , Carboplatino/farmacología , Mutaciones Letales Sintéticas , Replicación del ADN/efectos de los fármacos , Resistencia a Antineoplásicos/genética , Resistencia a Antineoplásicos/efectos de los fármacos , Inhibidores de Poli(ADP-Ribosa) Polimerasas/farmacología , Antineoplásicos/farmacologíaRESUMEN
Dasatinib is a multitargeted kinase inhibitor used for treatment of chronic myeloid leukemia and acute lymphoblastic leukemia. Unfortunately, treatment of cancer patients with some kinase inhibitors has been associated with cardiotoxicity. Cancer treatment with dasatinib has been reported to be associated with cardiotoxic side effects such as left ventricular dysfunction, heart failure, pericardial effusion and pulmonary hypertension. Here we aimed to investigate the molecular mechanisms underlying the cardiotoxicity of dasatinib. We found that among the resident cardiac cell types, cardiomyocytes were most sensitive to dasatinib-induced cell death. Exposure of cardiomyocytes to dasatinib attenuated the activity of extracellular signal-regulated kinase (ERK), which is a downstream target of dasatinib target kinase c-Src. Similar to dasatinib, c-Src depletion in cardiomyocytes compromised cardiomyocyte viability. Overexpression of dasatinib-resistant mutant of c-Src rescued the toxicity of dasatinib on cardiomyocytes, whereas forced expression of wild type c-Src did not have protective effect. Collectively, our results show that c-Src is a key target of dasatinib mediating the toxicity of dasatinib to cardiomyocytes. These findings may influence future drug design and suggest closer monitoring of patients treated with agents targeting c-Src for possible adverse cardiac effects.
RESUMEN
Background Small molecule kinase inhibitors (KIs) are a class of agents currently used for treatment of various cancers. Unfortunately, treatment of cancer patients with some of the KIs is associated with cardiotoxicity, and there is an unmet need for methods to predict their cardiotoxicity. Here, we utilized a novel computational method to identify protein kinases crucial for cardiomyocyte viability. Methods and Results One hundred forty KIs were screened for their toxicity in cultured neonatal cardiomyocytes. The kinase targets of KIs were determined based on integrated data from binding assays. The key kinases mediating the toxicity of KIs to cardiomyocytes were identified by using a novel machine learning method for target deconvolution that combines the information from the toxicity screen and from the kinase profiling assays. The top kinases identified by the model were phosphoinositide 3-kinase catalytic subunit alpha, mammalian target of rapamycin, and insulin-like growth factor 1 receptor. Knockdown of the individual kinases in cardiomyocytes confirmed their role in regulating cardiomyocyte viability. Conclusions Combining the data from analysis of KI toxicity on cardiomyocytes and KI target profiling provides a novel method to predict cardiomyocyte toxicity of KIs.