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Ribosomal proteins: mutant phenotypes by the numbers and associated gene expression changes.

ABSTRACT: Ribosomal proteins are highly conserved, many universally so among organisms. All ribosomal proteins are structural parts of the same molecular machine, the ribosome. However, when ribosomal proteins are mutated individually, they often lead to distinct and intriguing phenotypes, including specific human pathologies. This review is an attempt to collect and analyse all the reported phenotypes of each ribosomal protein mutant in several eukaryotes (Saccharomyces cerevisiae, Caenorhabditis elegans, Drosophila melanogaster, Danio rerio, Mus musculus, Homo sapiens). These phenotypes were processed with unbiased computational approaches to reveal associations between different phenotypes and the contributions of individual ribosomal protein genes. An overview of gene expression changes in ribosomal protein mutants, with emphasis on ribosome profiling studies, is also presented. The available data point to patterns that may account for most of the observed phenotypes. The information presented here may also inform future studies about the molecular basis of the phenotypes that arise from mutations in ribosomal proteins.

SUBMITTER: Polymenis M

PROVIDER: S-EPMC7479938 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Ribosomal proteins: mutant phenotypes by the numbers and associated gene expression changes.

Polymenis Michael M

Open biology 20200819 8

Ribosomal proteins are highly conserved, many universally so among organisms. All ribosomal proteins are structural parts of the same molecular machine, the ribosome. However, when ribosomal proteins are mutated individually, they often lead to distinct and intriguing phenotypes, including specific human pathologies. This review is an attempt to collect and analyse all the reported phenotypes of each ribosomal protein mutant in several eukaryotes (<i>Saccharomyces cerevisiae</i>, <i>Caenorhabdit ...[more]

PMID: 32810425

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Project description:BACKGROUND:A better understanding of the development of metastatic disease and the identification of molecular markers for cancer spread would be useful for the design of improved treatment strategies. This study was conducted to identify gene expressions associated with metastatic phenotypes of locally advanced cervical carcinomas and investigate whether gains or losses of these genes could play a role in regulation of the transcripts. Gene expressions and copy number changes were determined in primary tumors from 29 patients with and 19 without diagnosed lymph node metastases by use of cDNA and genomic microarray techniques, respectively. RESULTS:Thirty-one genes that differed in expression between the node positive and negative tumors were identified. Expressions of eight of these genes (MRPL11, CKS2, PDK2, MRPS23, MSN, TBX3, KLF3, LSM3) correlated with progression free survival in univariate analysis and were therefore more strongly associated with metastatic phenotypes than the others. Immunohistochemistry data of CKS2 and MSN showed similar relationships to survival. The prognostic genes clustered into two groups, suggesting two major metastatic phenotypes. One group was associated with rapid proliferation, oxidative phosphorylation, invasiveness, and tumor size (MRPS23, MRPL11, CKS2, LSM3, TBX3, MSN) and another with hypoxia tolerance, anaerobic metabolism, and high lactate content (PDK2, KLF3). Multivariate analysis identified tumor volume and PDK2 expression as independent prognostic variables. Gene copy number changes of the differentially expressed genes were not frequent, but correlated with the expression level for seven genes, including MRPS23, MSN, and LSM3. CONCLUSION:Gene expressions associated with known metastatic phenotypes of cervical cancers were identified. Our findings may indicate molecular mechanisms underlying development of these phenotypes and be useful as markers of cancer spread. Gains or losses of the genes may be involved in development of the metastatic phenotypes in some cases, but other mechanisms for transcriptional regulation are probably important in the majority of tumors.

Dataset Information

Ribosomal proteins: mutant phenotypes by the numbers and associated gene expression changes.

Publications

Ribosomal proteins: mutant phenotypes by the numbers and associated gene expression changes.

Similar Datasets

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