%0 Journal Article %A Joana Carlevaro-Fita %A Andrés Lanzós %A Lars Feuerbach %A Chen Hong %A David Mas-Ponte %A PCAWG Working Group %A Roderic Guigó %A Jakob Skou Pedersen %A Rory Johnson %T Unique genomic features and deeply-conserved functions of long non-coding RNAs in the Cancer LncRNA Census (CLC) %D 2017 %R 10.1101/152769 %J bioRxiv %P 152769 %X Long non-coding RNAs (lncRNAs) that drive tumorigenesis are a growing focus of cancer genomics studies. To facilitate further discovery, we have created the “Cancer LncRNA Census” (CLC), a manually-curated and strictly-defined compilation of lncRNAs with causative roles in cancer. CLC has two principle applications: first, as a resource for training and benchmarking de novo identification methods; and second, as a dataset for studying the fundamental properties of these genes.CLC Version 1 comprises 122 lncRNAs implicated in 31 distinct cancers. LncRNAs are included based on functional or genetic evidence for different causative roles in cancer progression. All belong to the GENCODE reference annotation, to facilitate integration across projects and datasets. For each entry, the evidence type, biological activity (oncogene or tumour suppressor), source reference and cancer type are recorded. CLC genes are significantly enriched amongst de novo predicted driver genes from PCAWG. CLC genes are distinguished from other lncRNAs by a series of features consistent with biological function, including gene length, expression and sequence conservation of both exons and promoters. We identify a trend for CLC genes to be co-localised with known protein-coding cancer genes along the human genome. Finally, by integrating data from transposon-mutagenesis functional screens, we show that mouse orthologues of CLC genes tend also to be cancer driver genes.Thus CLC represents a valuable resource for research into long non-coding RNAs in cancer. Their evolutionary and genomic properties have implications for understanding disease mechanisms and point to conserved functions across ~80 million years of evolution. %U https://www.biorxiv.org/content/biorxiv/early/2017/06/29/152769.full.pdf