Oncogene or tumor suppressor? Long noncoding RNAs role in patient's prognosis varies depending on disease type

Yingbo Huang, Alexander Ling, Siddhika Pareek, R. Stephanie Huang

Research output: Contribution to journalArticlepeer-review

11 Scopus citations

Abstract

Functional studies of long noncoding RNAs (lncRNAs) are often performed in the context of only a single cancer type. However, the tissue-specific expression patterns of lncRNAs raise the question of whether lncRNA associations identified in one cancer type are relevant to other cancer types. Here, we examine the relationships between the expression levels of 50 cancer-related lncRNAs and survival data from 24 types of cancer in The Cancer Genome Atlas (TCGA) with the goal of identifying prognosis related lncRNAs. Our results suggest that high expression levels of certain lncRNAs are consistently associated with worse/better survival in a number of cancers, while other lncRNAs have different prognostic roles in different types of cancer. Our analysis also identifies 20 novel unadjusted associations that have not been reported before. In addition, in low-grade glioma (LGG), prognostic-related lncRNAs are identified after conditioning on known clinical biomarker and common therapy, revealing that 2 lncRNAs, FOXP4-AS1, and NEAT1, are associated with temozolomide response—a standard-of-care in LGG. Pathway analysis suggests NF-kB/STAT3 signaling pathway enrichment in LGG patients with high NEAT1 expression and DNA repair/myc gene set enrichment in LGG patients with high expression of FOXP4-AS1. Our work demonstrates the context dependency of lncRNAs across cancer types and highlights a number of lncRNAs as potential novel cancer prognosis markers.

Original languageEnglish (US)
Pages (from-to)98-110
Number of pages13
JournalTranslational Research
Volume230
DOIs
StatePublished - Apr 2021

Bibliographical note

Publisher Copyright:
© 2020 Elsevier Inc.

Keywords

  • Long noncoding RNA
  • TCGA
  • cancer prognosis marker
  • low-grade glioma
  • pharmacogenomic

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