KAP1 is a new non-genetic vulnerability of malignant pleural mesothelioma (MPM).
Eugenia LorenziniFederica TorricelliRaffaella ZamponiBenedetta DonatiVeronica ManicardiElisabetta SautaItalo Faria do ValleFrancesca ReggianiMila GugnoniGloria ManzottiValentina FragliassoEmanuele VitaleSimonetta PianaValentina SancisiAlessia CiarrocchiPublished in: NAR cancer (2022)
Malignant pleural mesothelioma (MPM) is a rare and incurable cancer, which incidence is increasing in many countries. MPM escapes the classical genetic model of cancer evolution, lacking a distinctive genetic fingerprint. Omics profiling revealed extensive heterogeneity failing to identify major vulnerabilities and restraining development of MPM-oriented therapies. Here, we performed a multilayered analysis based on a functional genome-wide CRISPR/Cas9 screening integrated with patients molecular and clinical data, to identify new non-genetic vulnerabilities of MPM. We identified a core of 18 functionally-related genes as essential for MPM cells. The chromatin reader KAP1 emerged as a dependency of MPM. We showed that KAP1 supports cell growth by orchestrating the expression of a G2/M-specific program, ensuring mitosis correct execution. Targeting KAP1 transcriptional function, by using CDK9 inhibitors resulted in a dramatic loss of MPM cells viability and shutdown of the KAP1-mediated program. Validation analysis on two independent MPM-patients sets, including a consecutive, retrospective cohort of 97 MPM, confirmed KAP1 as new non-genetic dependency of MPM and proved the association of its dependent gene program with reduced patients' survival probability. Overall these data: provided new insights into the biology of MPM delineating KAP1 and its target genes as building blocks of its clinical aggressiveness.
Keyphrases
- genome wide
- end stage renal disease
- newly diagnosed
- crispr cas
- dna methylation
- chronic kidney disease
- ejection fraction
- gene expression
- single cell
- induced apoptosis
- peritoneal dialysis
- poor prognosis
- prognostic factors
- quality improvement
- transcription factor
- machine learning
- cell proliferation
- cross sectional
- electronic health record
- patient reported outcomes
- big data
- cell cycle
- cell cycle arrest
- heat stress
- patient reported
- pi k akt
- data analysis
- deep learning
- binding protein