Abstract
Background
Among all types of renal cell cancer (RCC), clear cell renal cell cancer (ccRCC) is
the most common and aggressive one. Emerging evidence uncovers that long non-coding
RNAs (lncRNAs) are involved in genomic instability, which correlates to the clinical
outcomes of patients who suffer from various kinds of cancers.
Methods
We gathered expression profiles of transcriptome RNA and clinical information about
ccRCC from The Cancer Genome Atlas (TCGA) and The Gene Expression Omnibus (GEO) database.
The lncRNA expression profiles and somatic mutation data were combined to identify
genome instability-related lncRNAs (GILncRs) by significance analysis of T test. By
means of univariate and multivariate cox regression analyses, 3 GILncRs strongly associated
with patient prognosis were screened out to build a genomic instability-related risk
score (GIRS) model. We use R-version 4.0.4 to draw Kaplan-Meier plots and ROC curves
for survival prediction.
Results
The somatic mutation count was higher in genomic unstable group. PBRM1 showed lower
expression in genomic unstable group. Three lncRNAs such as LINC00460, AC156455.1,
LINC01606 were included in the GIRS model. Patients had poorer prognosis with higher
risk score of GIRS model. The somatic mutation count was higher in patients with higher
risk score while PBRM1 expression was lower. The GIRS model was independent from other
clinical factors. The GIRS model was superior to other 2 published lncRNA signatures
in survival prediction.
Keywords
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Article info
Publication history
Published online: February 23, 2022
Accepted:
February 18,
2022
Received in revised form:
February 17,
2022
Received:
June 15,
2021
Identification
Copyright
© 2022 Elsevier Inc. All rights reserved.
