Tumour mutations in long noncoding RNAs enhance cell fitness

Autor: Dominik F. Meise, Lia Mela, Marianna Kruithof-de Julio, Kyriakos Schwarz, Hugo Guillen-Ramirez, Lusine Hovhannisyan, Yitzhak Zimmer, Eugenio Zoni, Núria Bosch-Guiteras, Sunandini Ramnarayanan, Bernard Merlin, Taisia Polidori, Isabel Büchi, Corina Wenger, Giulia Basile, Andrés Lanzós, Matúš Medo, Adrienne Vancura, Finn McCluggage, Michaela Medová, Archa H. Fox, Roberta Esposito, Sandra Zwyssig, Rory Johnson, Deborah Stroka
Rok vydání: 2022
Předmět:
Popis: Long noncoding RNAs (lncRNAs) can act as tumour suppressors or oncogenes to repress/promote tumour cell proliferation via RNA-dependent mechanisms. Recently, genome sequencing has identified elevated densities of tumour somatic single nucleotide variants (SNVs) in lncRNA genes. However, this has been attributed to phenotypically-neutral “passenger” processes, and the existence of positively-selected fitness-altering “driver” SNVs acting via lncRNAs has not been addressed. We developed and used ExInAtor2, an improved driver-discovery pipeline, to map pancancer and cancer-specific mutated lncRNAs across an extensive cohort of 2583 primary and 3527 metastatic tumours. The 54 resulting lncRNAs are mostly linked to cancer for the first time. Their significance is supported by a range of clinical and genomic evidence, and display oncogenic potential when experimentally expressed in matched tumour models. Our results revealed a striking SNV hotspot in the iconic NEAT1 oncogene, which was ascribed by previous studies to passenger processes. To directly evaluate the functional significance of NEAT1 SNVs, we used in cellulo mutagenesis to introduce tumour-like mutations in the gene and observed a consequent increase in cell proliferation in both transformed and normal backgrounds. Mechanistic analyses revealed that SNVs alter NEAT1 ribonucleoprotein assembly and boost subnuclear paraspeckles. This is the first experimental evidence that mutated lncRNAs can contribute to the pathological fitness of tumour cells.
Databáze: OpenAIRE