Expression levels of NONO, a nuclear protein primarily involved in paraspeckles function, are associated with several deregulated molecular pathways and poor clinical outcome in multiple myeloma

Abstract

Purpose: The NONO protein belongs to the multifunctional family of proteins that can bind DNA, RNA and proteins. It is located in the nucleus of most mammalian cells and can affect almost every step of gene regulation. Dysregulation of NONO has been found in many types of cancer; however, data regarding its expression and relevance in Multiple Myeloma (MM) are virtually absent.

Methods: We took advantage of a large cohort of MM patients enrolled in the Multiple Myeloma Research Foundation CoMMpass study to elucidate better the clinical and biological relevance of NONO expression in the context of the MM genomic landscape and transcriptome.

Results: NONO is overexpressed in pathological samples compared to normal controls. In addition, higher NONO expression levels are significant independent prognostic markers of worse clinical outcome in MM. Our results indicate that NONO deregulation may play a pathogenetic role in MM by affecting cell cycle, DNA repair mechanisms, and influencing translation by regulating ribosome biogenesis and assembly. Furthermore, our data suggest NONO involvement in the metabolic reprogramming of glucose metabolism from respiration to aerobic glycolysis, a phenomenon known as the 'Warburg Effect' that supports rapid cancer cell growth, survival, and invasion.

Conclusion: These findings strongly support the need of future investigations for the understanding of the mechanisms of deregulation and the biological role and activity of NONO in MM.

Keywords: Multiple myeloma; NONO; Therapeutic target; Warburg effect.

Fig. 1

a NONO expression in hematological tumors. Boxplot of NONO mRNA expression in 27 MM, 5 lymphoma, and 6 leukemia cell lines based on the quantitative real-time PCR (qRT-PCR) approach described in Supplementary Data. The histogram details NONO expression in each cell line, including: one diffuse large B-cell lymphoma (OCILY7), two mantle cell lymphomas (MAVER and MINO), two Burkitt lymphomas (SULTAN and NAMALWA), one chronic lymphatic leukemia (MEC1), one acute myeloid leukemia (U937), three T-cell acute lymphoblastic leukemia (CEM, MOLT4, and JURKAT), and one B-cell acute lymphoblastic leukemia (697). b WB of NONO in indicated HMCLs. GAPDH protein expression was included for protein loading normalization. Densitometric analysis of immunoreactive bands is reported in the histogram below. c Pearson correlation between NONO mRNA and protein expression levels. d Confocal microscopy results of NEAT1 specific RNA-FISH and NONO IF in AMO-1 cells (scale bar 5 μm)

Fig. 2

a Kaplan-Meier survival curves in the CoMMpass global dataset including 767 MM. MM cases were stratified in high and low NONO expression groups, accordingly to the median expression level across the dataset. Log-rank test p-value measuring the global difference between survival curves and number of samples at risk in each group across time are reported. b Kaplan-Meier survival curves in 653 MM with expression, molecular and clinical data available. Log-rank test p-value measuring the global difference between survival curves and the number of samples at risk in each group across time are reported. Log-rank test p-values of pairwise comparisons are also reported; significant adjusted p-values by BH correction (< 0.05) are in red-bold. Median OS and PFS is indicated for each curves

Fig. 3

Forest plot of cox regression multivariate analysis considering all features with adjusted p-value < 0.05 in univariate analysis with regards to OS (a) and PFS (b) in 497 BM-1 MM cases. Hazard Ratio, 95% Confidence Interval and Log-rank p-value are indicated in the plot for each variable. Significant p-value: * ≤ 0.05; ** ≤ 0.01; *** ≤ 0.001; **** ≤ 0.0001

Fig. 4

a Enrichment plots of selected GSEA gene sets significantly modulated in NONO IV versus I quartile. Normalized Enrichment Score (NES) and nominal p-value are reported for each plot. b Selected GSEA gene sets related to oxidative phosphorylation significantly downregulated in NONO IV versus I quartile. c NONO and LDHA Spearman’s correlation in the CoMMpass global dataset including 774 MM cases