Ribosome Biogenesis and cell cycle regulation: Effect of RNA Polymerase III inhibition

In cycling cells positive stimuli like nutrient, growth factors and mitogens increase ribosome biogenesis rate and protein synthesis to ensure both growth and proliferation. In contrast, under stress situation, proliferating cells negatively modulate ribosome production to reduce protein synthesis and block cell cycle progression. The main strategy used by cycling cell to coordinate cell proliferation and ribosome biogenesis is to share regulatory elements, which participate directly in ribosome production and in cell cycle regulation. In fact, there is evidence that stimulation or inhibition of cell proliferation exerts direct effect on activity of the RNA polymerases controlling the ribosome biogenesis, while several alterations in normal ribosome biogenesis cause changes of the expression and the activity of the tumor suppressor p53, the main effector of cell cycle progression inhibition. The available data on the cross-talk between ribosome biogenesis and cell proliferation have been until now obtained in experimental model in which changes in ribosome biogenesis were obtained either by reducing the activity of the RNA polymerase I or by down-regulating the expression of the ribosomal proteins. The molecular pathways involved in the relationship between the effect of the inhibition of RNA polymerase III (Pol III) activity and cell cycle progression have been not yet investigated. In eukaryotes, RNA Polymerase III is responsible for transcription of factors involved both in ribosome assembly (5S rRNA) and rRNA processing (RNAse P and MRP).Thus, the aim of this study is characterize the effects of the down-regulation of RNA Polymerase III activity, or the specific depletion of 5S rRNA. The results that will be obtained might lead to a deeper understanding of the molecular pathway that controls the coordination between ribosome biogenesis and cell cycle, and might give useful information about the possibility to target RNA Polymerase III for cancer treatment.

Research of predictive biomarkers to anti-CD22 antibody-drug conjugate treatment in B-cell acute lymphoblastic leukemia

Background: The treatment of B-cell acute lymphoblastic leukemia (B-ALL) has been enriched by novel agents targeting surface markers CD19 and CD22. Inotuzumab ozogamicin (INO) is a CD22-calicheamicin conjugated monoclonal antibody approved in the setting of relapse/refractory (R/R) B-ALL able to induce a high rate of deep responses, not durable over time. Aims: This study aims to identify predictive biomarkers to INO treatment in B- ALL by flow cytometric analysis of CD22 expression and gene expression profile. Materials and methods: Firstly, the impact on patient outcome in 30 R/R B-ALL patients of baseline CD22 expression in terms of CD22 blast percentage and CD22 fluorescent intensity (CD22-FI) was explored. Secondly, baseline gene expression profile of 18 R/R B-ALL patient samples was analyzed. For statistical analysis of differentially expressed genes (DEGs) patients were divided in non-responders (NR), defined as either INO-refractory or with duration of response (DoR) < 3 months, and responders (R). Gene expression results were analyzed with Ingenuity pathway analysis (IPA). Results: In our patient set higher CD22-FI, defined as higher quartiles (Q2-Q4), correlated with better patient outcome in terms of CR rate, OS and DoR, compared to lower CD22-FI (Q1). CD22 blast percentage was less able to discriminate patients’ outcome, although a trend for better outcome in patients with CD22 ≥ 90% could be appreciated. Concerning gene expression profile, 32 genes with corrected p value <0.05 and absolute FC ≥2 were differentially expressed in NR as compared to R. IPA upstream regulator and regulator effect analysis individuated the inhibition of tumor suppressor HIPK2 as causal upstream condition of the downregulation of 6 DEGs. Conclusions: CD22-FI integrates CD22-percentage on leukemic blasts for a more comprehensive target pre-treatment evaluation. Moreover, a unique pattern of gene expression signature based on HIPK2 downregulation was identified, providing important insights in mechanisms of resistance to INO.