LASSO-based screening for potential prognostic biomarkers associated with glioblastoma.

Background: Glioblastoma is the most common malignancy of the neuroepithelium, yet existing research on this tumor is limited. LASSO is an algorithm of selected feature coefficients by which genes associated with glioblastoma prognosis can be obtained. Methods: Glioblastoma-related data were selected from the Cancer Genome Atlas (TCGA) database, and information was obtained for 158 samples, including 153 cancer samples and five samples of paracancerous tissue. In addition, 2,642 normal samples were selected from the Genotype-Tissue Expression (GTEx) database. Whole-gene bulk survival analysis and differential expression analysis were performed on glioblastoma genes, and their intersections were taken. Finally, we determined which genes are associated with glioma prognosis. The STRING database was used to analyze the interaction network between genes, and the MCODE plugin under Cytoscape was used to identify the highest-scoring clusters. LASSO prognostic analysis was performed to identify the key genes. Gene expression validation allowed us to obtain genes with significant expression differences in glioblastoma cancer samples and paracancer samples, and glioblastoma independent prognostic factors could be derived by univariate and multivariate Cox analyses. GO functional enrichment analysis was performed, and the expression of the screened genes was detected using qRT-PCR. Results: Whole-gene bulk survival analysis of glioblastoma genes yielded 607 genes associated with glioblastoma prognosis, differential expression analysis yielded 8,801 genes, and the intersection of prognostic genes with differentially expressed genes (DEG) yielded 323 intersecting genes. PPI analysis of the intersecting genes revealed that the genes were significantly enriched in functions such as the formation of a pool of free 40S subunits and placenta development, and the highest-scoring clusters were obtained using the MCODE plug-in. Eight genes associated with glioblastoma prognosis were identified based on LASSO analysis: RPS10, RPS11, RPS19, RSL24D1, RPL39L, EIF3E, NUDT5, and RPF1. All eight genes were found to be highly expressed in the tumor by gene expression verification, and univariate and multivariate Cox analyses were performed on these eight genes to identify RPL39L and NUDT5 as two independent prognostic factors associated with glioblastoma. Both RPL39L and NUDT5 were highly expressed in glioblastoma cells. Conclusion: Two independent prognostic factors in glioblastoma, RPL39L and NUDT5, were identified.

Deletion of ribosomal paralogs Rpl39 and Rpl39l compromises cell proliferation via protein synthesis and mitochondrial activity.

Accumulating evidences suggest that the composition and functional roles of ribosomes are heterogeneous in cells, partly due to the temporal-spatial expression of paralogous ribosomal proteins (RPs), of which functional relationships remain largely unexplored. In mouse, the X chromosome-linked RPL39 and its male germline specific paralog RPL39L are thought to express mutually exclusively due to the meiotic sex chromosome inactivation, hinders the understanding of their functional relationships. In the present study, we investigated the expression and functional relations of Rpl39 and Rpl39l in a proliferative mouse cell line, in which both genes are expressed simultaneously, with the expression level of Rpl39 higher than that of Rpl39l. Disruption of Rpl39 via CRISPR/Cas9 method caused decreased cell proliferation, nascent protein synthesis and altered mitochondrial functions, whereas double mutations of Rpl39 and Rpl39l augmented these phenotypes, suggesting that both RPs contribute to the cellular physiology. Consistently, overexpression of Rpl39, Rpl39l or an alanine mutant of RPL39, rescued cell proliferation similarly in Rpl39-/-::Rpl39l-/- dual gene null cells. Deletion of Rpl39l induced compensatory expression of Rpl39, rendering the deleterious effects of Rpl39l mutation. Supporting this, Rpl39l mutation was more detrimental to cells under a low serum condition, under which the compensatory expression of Rpl39 was inhibited. Moreover, the low serum condition induced expression of both genes, suggesting that they possess stress responsive roles. Taken together, these data indicate that both RPL39 and RPL39L influence cell proliferation via protein synthesis and mitochondrial functions, suggesting a link between protein translation and cellular metabolism through these ribosomal protein paralogs.

RPL39L is an example of a recently evolved ribosomal protein paralog that shows highly specific tissue expression patterns and is upregulated in ESCs and HCC tumors.

Ribosomal proteins (RPs) have been shown to be able to impart selectivity on the translating ribosome implicating them in gene expression control. Many ribosomal proteins are highly conserved and recently a number of ribosomal protein paralogs have been described in mammals. We examined the expression pattern of RPs in differentiating mouse Embryonic Stem Cells (ESCs), paying particular attention to the RP paralogs. We find the RP paralog Rpl39l is highly expressed in ESC and its expression strongly correlates with hepatocellular carcinoma tumor (HCC) samples with high tumor grading and alpha-fetoprotein level giving it diagnostic potential. We further screen the expression pattern of all RPs and their paralogs across 22 different tissues. We find that the more recently evolved RP paralogs show a much greater level of tissue-specific expression. We propose that these RP paralogs evolved more recently to provide a greater level of gene expression control to higher eukaryotes.