Data mining analysis of the PP2A cell cycle axis in mesothelioma patients.
Raffaella PippaSilvia BoffoMaria D OderoAntonio GiordanoPublished in: Journal of cellular physiology (2019)
Mesothelioma is an aggressive tumor that affects thousands of people every year. The therapeutic options for patients are limited; hence, a better understanding of mesothelioma biology is crucial to improve patient survival. To find new molecular targets and therapeutic strategies related to the protein phosphatase 2A (PP2A) network, we analyzed the gene expression of known PP2A inhibitors in mesothelioma patient samples. Our analysis disclosed a general overexpression of all PP2A-negative regulators in mesothelioma patients. Moreover, the expression of ANP32E and CIP2A genes, increased in 16% and 11% of cases, positively correlates with the ones of all the other PP2A regulators and the ones of the main cyclins and CDKs, suggesting the existence of a feed-forward loop that might contribute to the mesothelioma progression via PP2A inactivation. Overall, our study indicates the existence of a strategic and targetable axis between PP2A inhibitors (ANP32E and CIP2A) and cell cycle regulators (cyclin B2/CDK1) and provides a valuable rationale for using a personalized combinational therapy approach to improve mesothelioma patient survival.
Keyphrases
- cell cycle
- gene expression
- end stage renal disease
- ejection fraction
- cell proliferation
- chronic kidney disease
- prognostic factors
- poor prognosis
- stem cells
- machine learning
- long non coding rna
- small molecule
- deep learning
- amino acid
- electronic health record
- patient reported
- cell therapy
- artificial intelligence
- protein protein
- bioinformatics analysis