Identification of a Selective G1-Phase Benzimidazolone Inhibitor by a Senescence-Targeted Virtual Screen Using Artificial Neural Networks

Alan E Bilsland,Angelo Pugliese,Yu Liu,John Revie,Sharon Burns,Carol Mccormick,Claire J Cairney,Justin Bower,Martin Drysdale,Masashi Narita,Mahito Sadaie,W Nicol Keith

doi:10.1016/j.neo.2015.08.009

Abstract

Cellular senescence is a barrier to tumorigenesis in normal cells, and tumor cells undergo senescence responses to genotoxic stimuli, which is a potential target phenotype for cancer therapy. However, in this setting, mixed-mode responses are common with apoptosis the dominant effect. Hence, more selective senescence inducers are required. Here we report a machine learning–based in silico screen to identify potential senescence agonists. We built profiles of differentially affected biological process networks from expression data obtained under induced telomere dysfunction conditions in colorectal cancer cells and matched these to a panel of 17 protein targets with confirmatory screening data in PubChem. We trained a neural network using 3517 compounds identified as active or inactive against these targets. The resulting classification model was used to screen a virtual library of ~2M lead-like compounds. One hundred and forty-seven virtual hits were acquired for validation in growth inhibition and senescence-associated β-galactosidase assays. Among the found hits, a benzimidazolone compound, CB-20903630, had low micromolar IC50 for growth inhibition of HCT116 cells and selectively induced senescence-associated β-galactosidase activity in the entire treated cell population without cytotoxicity or apoptosis induction. Growth suppression was mediated by G1 blockade involving increased p21 expression and suppressed cyclin B1, CDK1, and CDC25C. In addition, the compound inhibited growth of multicellular spheroids and caused severe retardation of population kinetics in long-term treatments. Preliminary structure-activity and structure clustering analyses are reported, and expression analysis of CB-20903630 against other cell cycle suppressor compounds suggested a PI3K/AKT-inhibitor–like profile in normal cells, with different pathways affected in cancer cells.

Highlights

Cellular senescence in normal cells is an irreversible cell cycle arrest which is involved in cellular aging and tissue maintenance, and which is induced by critically shortened telomeres at the end of replicative lifespan
To identify pathways associated with telomere dysfunction and senescence, we performed expression profiling and pathway analysis [27,28,29] on HCT116 colorectal cancer cells infected with Ad-hTR-mut or treated in long-term culture with telomerase inhibitor GRN163L [30,31]
The most significant enrichments of differentially expressed genes in response to telomere targeting agents were on networks involved in DNA damage, cell cycle, and protein folding

Summary

Introduction

Cellular senescence in normal cells is an irreversible cell cycle arrest which is involved in cellular aging and tissue maintenance, and which is induced by critically shortened telomeres at the end of replicative lifespan. Oxidative damage and oncogene activation accelerate both telomere shortening and senescence induction [1]. Senescence is considered to be a barrier to tumorigenesis which cancer cells must bypass to acquire a transformed phenotype [2,3]. Many cancer cells retain the capacity to undergo senescence-like growth arrest in response to agents including chemotherapeutics and ionizing radiation in addition to many targeted agents [4]. Despite inactivation of some key pathways, many tumor cells retain the ability to exit the cell cycle under appropriate treatments. Latent senescence signaling may persist in tumors [5]

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Conclusion