4.6 Article

Differentially Expressed lncRNAs in Gastric Cancer Patients: A Potential Biomarker for Gastric Cancer Prognosis

Journal

JOURNAL OF CANCER
Volume 8, Issue 13, Pages 2575-2586

Publisher

IVYSPRING INT PUBL
DOI: 10.7150/jca.19980

Keywords

gastric cancer; lncRNA; prognosis; survival; ssGSEA; nomogram

Categories

Funding

  1. National Natural Science Foundation of China [81421001, 81320108024, 31371420, 81530072, 81402347, 31371273]
  2. Program for Professor of Special Appointment (2015 Youth Eastern Scholar) at Shanghai Institutions of Higher Learning [QD2015003]
  3. Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support [20161309]
  4. Chenxing Project of Shanghai Jiao-Tong University
  5. National Natural Science Foundation of China [81421001, 81320108024, 31371420, 81530072, 81402347, 31371273]
  6. Program for Professor of Special Appointment (2015 Youth Eastern Scholar) at Shanghai Institutions of Higher Learning [QD2015003]
  7. Shanghai Municipal Education Commission-Gaofeng Clinical Medicine Grant Support [20161309]
  8. Chenxing Project of Shanghai Jiao-Tong University

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Current studies indicate that long non-coding RNAs (lncRNAs) are frequently aberrantly expressed in cancers and implicated with prognosis in gastric cancer (GC). We intended to generate a multi-lncRNA signature to improve prognostic prediction of GC. By analyzing ten paired GC and adjacent normal mucosa tissues, 339 differentially expressed lncRNAs were identified as the candidate prognostic biomarkers in GC. Then we used LASSO Cox regression method to build a 12-lncRNA signature and validated it in another independent GEO dataset. An innovative 12-lncRNA signature was established, and it was significantly associated with the disease free survival (DFS) in the training dataset. By applying the 12-lncRNA signature, the training cohort patients could be categorized into high-risk or low-risk subgroup with significantly different DFS (HR = 4.52, 95%CI= 2.49-8.20, P < 0.0001). Similar results were obtained in another independent GEO dataset (HR=1.58, 95%CI=1.05 -2.38, P=0.0270). Further analysis showed that the prognostic value of this 12-lncRNA signature was independent of AJCC stage and postoperative chemotherapy. Receiver operating characteristic (ROC) analysis showed that the area under receiver operating characteristic curve (AUC) of combined model reached 0.869. Additionally, a well-performed nomogram was constructed for clinicians. Moreover, single-sample gene-set enrichment analysis (ssGSEA) showed that a group of pathways related to drug resistance and cancer metastasis significantly enriched in the high risk patients. A useful innovative 12-lncRNA signature was established for prognostic evaluation of GC. It might complement clinicopathological features and facilitate personalized management of GC.

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