A novel isolation method for cancer prognostic factors via the p53 pathway by a combination of in vitro and in silico analyses.

Identifying new therapeutic target genes affecting the survival of patients with cancer is crucial for the development of new cancer therapies. Here, we developed a novel technology combining in vitro short hairpin RNA (shRNA) library screening and in silico analysis of the tumor transcriptome to identify prognostic factors via the p53 tumor-suppressor pathway. For initial screening, we screened 5,000 genes through selection of shRNAs in p53 wild-type tumor cells that altered sensitivity to the p53 activator actinomycin D (ActD) to identify p53 regulatory genes; shRNAs targeting 322 genes were obtained. Among these 322 genes, seven were prognostic factor candidates whose high expression increased ActD sensitivity while prolonging the survival period in patients with the p53 wild-type genotype. Conversely, we identified 33 genes as prognostic factor candidates among ActD-resistant genes related to a shortened survival period only in p53 wild-type tumors. These 40 genes had biological functions such as apoptosis, drug response, cell cycle checkpoint, and cell proliferation. The 40 genes selected by this method contained many known genes related to the p53 pathway and prognosis in patients with cancer. In summary, we developed an efficient screening method to identify p53-dependent prognostic factors with in vitro experimental data and database analysis.