4.6 Article

A three-long non-coding RNA-expression-based risk score system can better predict both overall and recurrence-free survival in patients with small hepatocellular carcinoma

Journal

AGING-US
Volume 10, Issue 7, Pages 1627-1639

Publisher

IMPACT JOURNALS LLC
DOI: 10.18632/aging.101497

Keywords

small hepatocellular carcinoma; long non-coding RNA; risk score; prognosis

Funding

  1. National Science Foundation of China [81773128, 81472247]
  2. Natural Science Basic Research Plan in Shaanxi Province of China [2017JM8039]
  3. Project of Youth Star in Science and Technology of Shaanxi Province [2018KJXX-022]
  4. Fundamental Research Fund for the Central Universities [2016qngz05]
  5. Clinical Research Award of the First Affiliated Hospital of Xi'an Jiaotong University [XJTU1AF-CRF-2015-011, XJTU1AF-CRF-2015-003]

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Growing evidence indicates that long non-coding RNAs (lncRNAs) may be potential biomarkers and therapeutic targets for many disease conditions, including cancer. In this study, we constructed a risk score system of three lncRNAs (LOC101927051, LINC00667 and NSUN5P2) for predicting the prognosis of small hepatocellular carcinoma (sHCC) (maximum tumor diameter <= 5 cm). The prognostic value of this sHCC risk model was confirmed in TCGA HCC samples (TNM stage I and II). Stratified survival analysis revealed that the suitable patient groups of the sHCC lncRNA-signature included HBV-infected and cirrhotic patients with better physical conditions yet lower levels of albumin and higher levels of alpha-fetoprotein preoperatively. Besides, Asian patients with no family history of HCC or history of alcohol consumption can be predicted more precisely. Molecular functional analysis indicated that PYK2 pathway was significantly enriched in the high-risk patients. Pathway enrichment analysis indicated that the two lncRNAs (LINC00667 and NSUN5P2) associated with poor prognosis were closely related to cell cycle. The nomogram based on the lncRNA-signature for RFS prediction in sHCC patients exhibited good performance in recurrence risk stratification. In conclusion, we identified a novel three-lncRNA-expression-based risk model for predicting the prognosis of sHCC.

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