Background: Cell proliferation is a hallmark of cancer and depends on complex signaling networks that are chiefly supported by protein kinase activities. Therapeutic strategies have been used to target specific kinases but new methods are required to identify combined targets and improve treatment. Here, we propose a small interfering RNA genetic screen and an integrative approach to identify kinase networks involved in the proliferation of cancer cells.
Results: The functional siRNA screen of 714 kinases in HeLa cells identified 91 kinases implicated in the regulation of cell growth, most of them never being reported in previous whole-genome siRNA screens. Based on gene ontology annotations, we have further discriminated between two classes of kinases that, when suppressed, result in alterations of the mitotic index and provoke cell-cycle arrest. Extinguished kinases that lead to a low mitotic index mostly include kinases implicated in cytosolic signaling. In contrast, extinguished kinases that result in a high mitotic index mostly include kinases implicated in cell division. By mapping hit kinases in the PhosphPOINT phosphoprotein database, we generated scale-free networks consisting of 449 and 661 protein-protein interactions for kinases from low MI and high MI groups, respectively. Further analyses of the kinase interactomes revealed specific modules such as FER- and CRKL-containing modules that connect three members of the epidermal growth factor receptor (EGFR) family, suggesting a tight control of the mitogenic EGF-dependent pathway. Based on experimental studies, we confirm the involvement of these two kinases in the regulation of tumor cell growth.
Conclusion: Based on a combined approach of large kinome-wide siRNA screens and ontology annotations, our study identifies for the first time two kinase groups differentially implicated in the control of cell proliferation. We further demonstrate that integrative analysis of the kinase interactome provides key information which can be used to facilitate or optimize target design for new therapeutic strategies. The complete list of protein-protein interactions from the two functional kinase groups will provide a useful database for future investigations.