Functional Enrichment Analysis of Deregulated Long Non-Coding RNAs in Cancer Based on their Genomic Neighbors


Olgun G., Tastan O.

11th ACM International Conference on Bioinformatics, Computational Biology and Health Informatics, BCB 2020, Virtual, Online, United States Of America, 21 - 24 September 2020 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1145/3388440.3412454
  • City: Virtual, Online
  • Country: United States Of America
  • Keywords: enrichment analysis, lncRNA lncRNA functions, pan cancer
  • Hacettepe University Affiliated: No

Abstract

The dysregulation of long non-coding RNAs' (lncRNAs) expressions has been implicated in cancer. Since most of the lncRNAs' are not functionally characterized well, investigating the set of perturbed lncRNAs are is challenging. Existing methods that inspect lncRNAs functionally rely on the co-expressed coding genes, which are far better characterized functionally. LncRNAs can be known to act as transcriptional regulators; they may activate or repress the neighborhood's coding genes on the genome. Based on this, in this work, we aim to analyze the deregulated lncRNAs in cancer by taking into account their ability to regulate nearby loci on the genome. We perform functional analysis on differentially expressed lncRNAs for 28 different cancers considering their adjacent coding genes. We identify that some deregulated lncRNAs are cancer-specific, but a substantial number of lncRNAs are shared across cancers. Next, we assess the similarities of the cancer types based on the functional enrichment of the deregulated lncRNA sets. We find some cancers are very similar in the functions and biological processes related to the deregulated lncRNAs. We observe that some of the cancers for which we find similarity can be linked through primary, metastatic site relations. We investigate the similarity of enriched functional terms for the deregulated lncRNAs and the mRNAs. We further assess the enriched functions' similarity to the functions and processes that the known cancer driver genes take place. We believe that our methodology help to understand the impact of the lncRNAs in cancer functionally.