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A long non-coding RNA-based signature predicts early recurrence in hepatocellular carcinoma.
He, Shuai; Li, Jin-Feng; Tian, Hao; Sang, Ye; Yang, Xiao-Jing; Guo, Gui-Xin; Yang, Jin-E.
Afiliação
  • He S; MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Li JF; MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Tian H; MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Sang Y; MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Yang XJ; MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Guo GX; National Supercomputer Center in Guangzhou, School of Data and Computer Science, Sun Yat-sen University, Guangzhou, Guangdong, China.
  • Yang JE; MOE Key Laboratory of Gene Function and Regulation, School of Life Sciences, Sun Yat-sen University, Guangzhou, Guangdong, China.
Cancer Biomark ; 34(2): 309-318, 2022.
Article em En | MEDLINE | ID: mdl-34957996
ABSTRACT

BACKGROUND:

Early recurrence is the main obstacle for long-term survival of hepatocellular carcinoma (HCC) patients after curative resection.

OBJECTIVE:

We aimed to develop a long non-coding RNA (lncRNA) based signature to predict early recurrence.

METHODS:

Using bioinformatics analysis and quantitative reverse transcription PCR (RT-qPCR), we screened for lncRNA candidates that were abnormally expressed in HCC. The expression levels of candidate lncRNAs were analyzed in HCC tissues from 160 patients who underwent curative resection, and a risk model for the prediction of recurrence within 1 year (early recurrence) of HCC patients was constructed with linear support vector machine (SVM).

RESULTS:

An lncRNA-based classifier (Clnc), which contained nine differentially expressed lncRNAs including AF339810, AK026286, BC020899, HEIH, HULC, MALAT1, PVT1, uc003fpg, and ZFAS1 was constructed. In the test set, this classifier reliably predicted early recurrence (AUC, 0.675; sensitivity, 72.0%; specificity, 63.1%) with an odds ratio of 4.390 (95% CI, 2.120-9.090). Clnc showed higher accuracy than traditional clinical features, including tumor size, portal vein tumor thrombus (PVTT) in predicting early recurrence (AUC, 0.675 vs 0.523 vs 0.541), and had much higher sensitivity than Barcelona Clinical Liver Cancer (BCLC; 72.0% vs 50.0%), albeit their AUCs were comparable (0.675 vs 0.678). Moreover, combining Clnc with BCLC significantly increased the AUC, compared with Clnc or BCLC alone in predicting early recurrence (all P< 0.05). Finally, logistic and Cox regression analyses suggested that Clnc was an independent prognostic factor and associated with the early recurrence and recurrence-free survival of HCC patients after resection, respectively (all P= 0.001).

CONCLUSIONS:

Our lncRNA-based classifier Clnc can predict early recurrence of patients undergoing surgical resection of HCC.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Hepatocelular / RNA Longo não Codificante / Neoplasias Hepáticas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Cancer Biomark Assunto da revista: BIOQUIMICA / NEOPLASIAS Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Carcinoma Hepatocelular / RNA Longo não Codificante / Neoplasias Hepáticas Tipo de estudo: Prognostic_studies / Risk_factors_studies Limite: Humans Idioma: En Revista: Cancer Biomark Assunto da revista: BIOQUIMICA / NEOPLASIAS Ano de publicação: 2022 Tipo de documento: Article País de afiliação: China