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Identification of a five-lncRNA signature for the diagnosis and prognosis of gastric cancer

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Tumor Biology

Abstract

Gastric cancer (GC) is one of the most aggressive malignancies and has a poor prognosis. Identifying novel diagnostic and prognostic markers is of great importance for the management and treatment of GC. Long non-coding RNAs (lncRNAs), which are involved in multiple processes during the development and progression of cancer, may act as potential biomarkers of GC. Here, by performing data mining using four microarray data sets of GC downloaded from the Gene Expression Omnibus (GEO) database with different classifiers and risk score analyses, we identified a five-lncRNA signature (AK001094, AK024171, AK093735, BC003519 and NR_003573) displaying both diagnostic and prognostic values for GC. The results of the Kaplan-Meier survival analysis and log-rank test showed that the risk score based on this five-lncRNA signature was closely associated with overall survival time (p = 0.0001). Further analysis revealed that the risk score is an independent predictor of prognosis. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) analysis of 30 pairs of GC tissue samples confirmed that the five lncRNAs were dysregulated in GC, and receiver operating characteristic (ROC) curves showed the high diagnostic ability of combining the five lncRNAs, with an area under the curve (AUC) of 0.95 ± 0.025. The five lncRNAs involved in several cancer-related pathways were identified using gene set enrichment analysis (GSEA). These findings indicate that the five-lncRNA signature may have a good clinical applicability for determining the diagnosis and predicting the prognosis of GC.

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Acknowledgments

This study was financially supported by grants from the National Natural Science Foundation of China (Nos. 91529302, 81572798 and 81272749), the Key Projects in the National Science & Technology Pillar Program of China (No. 2014BAI09B03), the Science and Technology Fund of Shanghai Jiao Tong University School of Medicine (No. 13XJ10011) and the Shanghai Jiao Tong University Medical Engineering Cross Research Fund (No. YG2014MS59).

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Authors and Affiliations

  1. Shanghai Key Laboratory of Gastric Neoplasms, Department of Surgery, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China

    Zhi-yuan Fan, Wentao Liu, Chao Yan, Zheng-lun Zhu, Wei Xu, Jian-fang Li, Liping Su, Chen Li, Zheng-gang Zhu, Bingya Liu & Min Yan

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  1. Zhi-yuan Fan
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  2. Wentao Liu
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Correspondence to Bingya Liu or Min Yan.

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Zhi-yuan Fan and Wentao Liu are contributed equally to this work

Electronic supplementary material

Table S1

The 208 common lncRNAs in the list. (XLS 35 kb)

Table S2

The re-annotated lncRNAs listed in the 2 mRNA platforms. (XLSX 218 kb)

Table S3

Weight value of the 35 lncRNAs in the 3 linear classifiers in the training set. (XLSX 14 kb)

Table S4

Detailed results of the reclassification of the samples using different classifiers in the training set. (XLSX 21 kb)

Table S5

Detailed results of the reclassification of the samples using different classifiers in the test data sets. (XLSX 37 kb)

Table S6

Variable and relative importance of the 30 lncRNAs using the random survival forest algorithm. (XLSX 12 kb)

Table S7

Detailed information of differentially expressed genes between the low-risk and high-risk groups. (XLSX 488 kb)

Table S8

GSEA results of each of the 5 lncRNAs. (XLSX 145 kb)

Fig. S1

ROC curves of the 5-lncRNA signature in diagnosing GC in GSE63089. (DOCX 129 kb)

Fig. S2

ROC curves of the 5-lncRNA signature in diagnosing GC in GSE27342. (DOCX 131 kb)

Fig. S3

ROC curves of the 5-lncRNA signature in diagnosing GC in GSE50710. (DOCX 132 kb)

Fig. S4

Melting curves of qRT-PCR for AK001094, AK024171, AK093735, BC003519 and NR_003573 and GAPDH. (a) Melting curves of qRT-PCR for AK001094. (GIF 178 kb)

High resolution image (TIFF 2327 kb)

Figure S4

(b) Melting curves of qRT-PCR for AK024171.(GIF 220 kb)

High resolution image (TIFF 2874 kb)

Figure S4

(c) Melting curves of qRT-PCR for AK093735. (GIF 233 kb)

High resolution image (TIFF 2933 kb)

Figure S4

(d) Melting curves of qRT-PCR for BC003519. (GIF 200 kb)

High resolution image (TIFF 2584 kb)

Figure S4

(e) Melting curves of qRT-PCR for NR_003573. (GIF 204 kb)

High resolution image (TIFF 2642 kb)

ESM 5

(f) Melting curves of qRT-PCR for GAPDH. (GIF 221 kb)

High resolution image (TIFF 2797 kb)

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Fan, Zy., Liu, W., Yan, C. et al. Identification of a five-lncRNA signature for the diagnosis and prognosis of gastric cancer. Tumor Biol. 37, 13265–13277 (2016). https://doi.org/10.1007/s13277-016-5185-9

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  • DOI: https://doi.org/10.1007/s13277-016-5185-9

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