Long non-coding RNA LCAL62 / LINC00261 is associated with lung adenocarcinoma prognosis

Ha X Dang; Nicole M White; Emily B Rozycki; Brooke M Felsheim; Mark A Watson; Ramaswamy Govindan; Jingqin Luo; Christopher A Maher

doi:10.1016/j.heliyon.2020.e03521

Long non-coding RNA LCAL62 / LINC00261 is associated with lung adenocarcinoma prognosis

Heliyon. 2020 Mar 5;6(3):e03521. doi: 10.1016/j.heliyon.2020.e03521. eCollection 2020 Mar.

Authors

Ha X Dang^{1

2

3}, Nicole M White^{1

3}, Emily B Rozycki¹, Brooke M Felsheim¹, Mark A Watson^{3

4}, Ramaswamy Govindan^{1

3}, Jingqin Luo^{3

5}, Christopher A Maher^{1

2

3

6}

Affiliations

¹ Department of Internal Medicine, Washington University School of Medicine, St. Louis, MO, USA.
² McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.
³ Alvin J. Siteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA.
⁴ Department of Pathology and Immunology, Washington University School of Medicine, St Louis, MO, USA.
⁵ Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA.
⁶ Department of Biomedical Engineering, Washington University School of Medicine, St. Louis, MO, USA.

Abstract

Background: More than half of non-small cell lung cancer (NSCLC) patients present with metastatic disease at initial diagnosis with an estimated five-year survival rate of ~5%. Despite advances in understanding primary lung cancer oncogenesis metastatic disease remains poorly characterized. Recent studies demonstrate important roles of long non-coding RNAs (lncRNAs) in tumor physiology and as prognostic markers. Therefore, we present the first transcriptome analysis to identify lncRNAs altered in metastatic lung adenocarcinoma leading to the discovery and characterization of the lncRNA LCAL62 as a prognostic biomarker.

Patients and methods: RNA-Seq, microarray, nanoString expression, and clinical data from 1,116 LUAD patients across six independent cohorts and 83 LUAD cell lines were used to discover and evaluate the survival association of metastasis associated lncRNAs. Coexpression and gene set enrichment analyses were used to establish gene regulatory networks and implicate metastasis associated lncRNAs in specific biological processes.

Results: Our integrative analysis discovered LCAL62 as the most down-regulated lncRNA in metastasis. Further low LCAL62 expression promoted aggressive phenotypes and regulated genes associated with metastasis (such as metastasis repressor FOXA2). Low LCAL62 expression corresponded to poor overall patient survival across five independent lung adenocarcinoma cohorts (n = 881) including our own nanoString validation cohort.

Conclusion: We discovered that LCAL62 was down-regulated in lung cancer progression to promote invasive phenotypes, and lower expression was significantly associated with poor patient outcome and aggressive lung adenocarcinoma.

Keywords: Bioinformatics; Biomarker; Cancer research; Cell biology; Computational biology; Genetics; Genomics; Long non-coding RNA; Lung cancer; Metastasis; Molecular biology; Oncology; Prognostic; Transcriptome.

Abstract

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