Mutation-Derived Long Noncoding RNA Signature Predicts Survival in Lung Adenocarcinoma

Longjun Yang; Guangran Guo; Xiangyang Yu; Yingsheng Wen; Yongbin Lin; Rusi Zhang; Dechang Zhao; Zirui Huang; Gongming Wang; Yan Yan; Xuewen Zhang; Dongtai Chen; Wei Xing; Weidong Wang; Weian Zeng; Lanjun Zhang

doi:10.3389/fonc.2022.780631

Mutation-Derived Long Noncoding RNA Signature Predicts Survival in Lung Adenocarcinoma

Front Oncol. 2022 Mar 15:12:780631. doi: 10.3389/fonc.2022.780631. eCollection 2022.

Authors

Longjun Yang^{1

2}, Guangran Guo^{1

2}, Xiangyang Yu³, Yingsheng Wen^{1

2}, Yongbin Lin^{1

2}, Rusi Zhang^{1

2}, Dechang Zhao^{1

2}, Zirui Huang^{1

2}, Gongming Wang^{1

2}, Yan Yan^{1

4}, Xuewen Zhang^{1

5}, Dongtai Chen^{1

5}, Wei Xing^{1

5}, Weidong Wang⁶, Weian Zeng^{1

5}, Lanjun Zhang^{1

2}

Affiliations

¹ State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China.
² Department of Thoracic Surgery, Sun Yat-sen University Cancer Center, Guangzhou, China.
³ Department of Thoracic Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital and Shenzhen Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Shenzhen, China.
⁴ Department of Anesthesiology, Huizhou Municipal Central Hospital, Huizhou, China.
⁵ Department of Anesthesiology, Sun Yat-sen University Cancer Center, Guangzhou, China.
⁶ Department of Thoracic Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.

Abstract

Background: Genomic instability is one of the representative features of cancer evolution. Recent research has revealed that long noncoding RNAs (lncRNAs) play a critical role in maintaining genomic instability. Our work proposed a gene signature (GILncSig) based on genomic instability-derived lncRNAs to probe the possibility of lncRNA signatures as an index of genomic instability, providing a potential new approach to identify genomic instability-related cancer biomarkers.

Methods: Lung adenocarcinoma (LUAD) gene expression data from an RNA-seq FPKM dataset, somatic mutation information and relevant clinical materials were downloaded from The Cancer Genome Atlas (TCGA). A prognostic model consisting of genomic instability-related lncRNAs was constructed, termed GILncSig, to calculate the risk score. We validated GILncSig using data from the Gene Expression Omnibus (GEO) database. In this study, we used R software for data analysis.

Results: Through univariate and multivariate Cox regression analyses, five genomic instability-associated lncRNAs (LINC01671, LINC01116, LINC01214, lncRNA PTCSC3, and LINC02555) were identified. We constructed a lncRNA signature (GILncSig) related to genomic instability. LUAD patients were classified into two risk groups by GILncSig. The results showed that the survival rate of LUAD patients in the low-risk group was higher than that of those in the high-risk group. Then, we verified GILncSig in the GEO database. GILncSig was associated with the genomic mutation rate of LUAD. We also used GILncSig to divide TP53 mutant-type patients and TP53 wild-type patients into two groups and performed prognostic analysis. The results suggested that compared with TP53 mutation status, GILncSig may have better prognostic significance.

Conclusions: By combining the lncRNA expression profiles associated with somatic mutations and the corresponding clinical characteristics of LUAD, a lncRNA signature (GILncSig) related to genomic instability was established.

Keywords: GILncSig; TCGA; TP53; genome instability; lung adenocarcinoma (LUAD).