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. 2021 Apr 28;79(1):61.
doi: 10.1186/s13690-021-00588-2.

Identification of a prognostic long noncoding RNA signature in lung squamous cell carcinoma: a population-based study with a mean follow-up of 3.5 years

Rongjiong Zheng  1 , Mengdi Zheng  1 , Mingming Wang  1 , Feijie Lu  2 , Meiling Hu  3
Affiliations

Identification of a prognostic long noncoding RNA signature in lung squamous cell carcinoma: a population-based study with a mean follow-up of 3.5 years

Rongjiong Zheng et al. Arch Public Health. .

Abstract

Background: Lung squamous cell carcinoma (LSCC) is a form of cancer that is associated with high rates of relapse, poor responsiveness to therapy, and a relatively poor prognosis. The relationship between long non-coding RNA (lncRNA) expression and LSCC patient prognosis remains to be established.

Methods: In the present study, we discovered that lncRNAs were differentially expressed in LSCC tumor tissues relative to normal control tissues, and we explored the prognostic relevance of these lncRNA expression patterns using data from the Cancer Genome Atlas (TCGA).

Results: These multidimensional data were analyzed in order to identify lncRNA signatures that were associated with LSCC patient survival outcomes. Kaplan-Meier survival curves revealed prognostic capabilities for three of these lncRNAs (LINC02555, APCDD1L-DT and OTX2-AS1). A Cox regression analysis revealed this three-lncRNA signature to be significantly associated with patient survival. Further GO and KEGG analyses revealed that the predicted target genes of these three lncRNAs were also potentially involved in cancer-associated pathways.

Conclusions: Together these results thus indicate that this novel three-lncRNA signature can be used to predict LSCC patient prognosis.

Keywords: LncRNAs; Lung squamous cell carcinoma; Survival.

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Conflict of interest statement

No competing interests exist.

Figures

Fig. 1
Fig. 1
Volcano plot of differentially expressed lncRNAs. Red and green dots represent upregulated and downregulated lncRNAs, respectively: a population-based study with a mean follow-up of 3.5 years
Fig. 2
Fig. 2
Forest plot for the association between three lncRNAs and risk value (a) Univariable Cox regression model (b) Multivariable Cox regression model: adjusted for age, gender and the stage: a population-based study with a mean follow-up of 3.5 years
Fig. 3
Fig. 3
Kaplan-Meier method and log-rank test revealed that three lncRNAs were associated with OS in patients with LSCC. The patients were divided into low and high expression levels group according to the median value. a APCDD1L-DT b LINC02555 and (C) OTX2-AS1: a population-based study with a mean follow-up of 3.5 years
Fig. 4
Fig. 4
(a) Kaplan-Meier estimates of the survival outcomes for patients using the three-lncRNA signature, and (b) Receiver operating characteristic analysis of risk factors for survival prediction: a population-based study with a mean follow-up of 3.5 years
Fig. 5
Fig. 5
(a) The Gene Ontology and (b) Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses, and (c) PPI networks: a population-based study with a mean follow-up of 3.5 years
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