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. 2017 Oct 19;8(55):94769-94779.
doi: 10.18632/oncotarget.21930. eCollection 2017 Nov 7.

Systematic identification of long non-coding RNAs with cancer-testis expression patterns in 14 cancer types

Na Qin  1   2   3 , Cheng Wang  1   2   3   4 , Qun Lu  2   3 , Zijian Ma  2   3 , Juncheng Dai  1   2   3 , Hongxia Ma  1   2   3 , Guangfu Jin  1   2   3 , Hongbing Shen  1   2   3 , Zhibin Hu  1   2   3
Affiliations

Systematic identification of long non-coding RNAs with cancer-testis expression patterns in 14 cancer types

Na Qin et al. Oncotarget. .

Abstract

Cancer-testis (CT) genes are a group of genes that are potential targets of immunotherapy and candidate epi-drivers participating in the development of cancers. Previous studies mainly focused on protein-coding genes, neglecting long non-coding RNAs with the same expression patterns. In this study, we performed a systematic investigation of cancer-testis long non-coding RNAs (CT-lncRNAs) with multiple independent open-access databases.We identified 1,325 extremely highly expressed CT-lncRNAs (EECT-lncRNAs) in 14 cancer types. Functional annotation revealed that CT-lncRNAs reactivated in cancers could promote genome instability and the malignant potential of cancers. We observed a mutually exclusive pattern of EECT-lncRNA activation and mutation in known oncogenes, suggesting their potential role as drivers of cancer that complement known mut-driver genes. Additionally, we provided evidence that testis-specific regulatory elements and promoter hypo-methylation may be EECT-lncRNA activation mechanisms, and EECT-lncRNAs may regulate CT gene reactivation. Taken together, our study puts forth a new hypothesis in the research field of CT genes, whereby CT-lncRNAs/EECT-lncRNAs play important roles in the progression and maintenance of tumorigenesis, expanding candidate CT epi-driver genes from coding genes to non-coding RNAs.

Keywords: cancer-testis gene; genomic instability; long non-coding RNA; lung adenocarcinoma.

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Conflict of interest statement

CONFLICTS OF INTEREST The authors have declared that no conflict of interest exists.

Figures

Figure 1
Figure 1. Classification of CT-lncRNAs, EECT-lncRNAs and TS-lncRNAs
The bar plot represents the proportion of lncRNAs per sub-category. The error bar represents the ER confidence interval.
Figure 2
Figure 2. Statistically significantly enriched pathways of lung adenocarcinoma specific CT-lncRNAs
Figure 3
Figure 3. The association between SMG mutation ratio and the number of activated EECT-lncRNAs
(A) Negative correlation between the mutation ratio of SMGs and the number of activated EECT-lncRNAs. (B) The total of number of activated EECT-lncRNAs is significantly higher in lung adenocarcinoma samples without clear activating oncogene mutational alterations. (C) Mutually exclusive pattern of EECT-lncRNA activation and oncogene mutations in lung adenocarcinoma samples.
Figure 4
Figure 4. Enrichment analysis of testis-specific regulatory elements
Figure 5
Figure 5. Negative correlation between the average promoter methylation level of EECT-lncRNAs and the number of activated EECT-lncRNAs
See this image and copyright information in PMC

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