PMID- 34866477
OWN - NLM
STAT- MEDLINE
DCOM- 20220210
LR  - 20220210
IS  - 1533-0338 (Electronic)
IS  - 1533-0346 (Print)
IS  - 1533-0338 (Linking)
VI  - 20
DP  - 2021 Jan-Dec
TI  - Identification of a Liver Progenitor Cell-Related Genes Signature Predicting 
      Overall Survival for Hepatocellular Carcinoma.
PG  - 15330338211041425
LID - 10.1177/15330338211041425 [doi]
LID - 15330338211041425
AB  - Background: Liver progenitor cells (LPCs) play significant roles in the 
      development and progression of hepatocellular carcinoma (HCC). However, no 
      studies on the value of LPC-related genes for evaluating HCC prognosis exist. We 
      developed a gene signature of LPC-related genes for prognostication in HCC. 
      Methods: To identify LPC-related genes, we analyzed mRNA expression arrays from a 
      dataset (GSE57812 & GSE 37071) containing LPCs, mature hepatocytes, and embryonic 
      stem cell samples. HCC RNA-Seq data from The Cancer Genome Atlas (TCGA) were used 
      to explore the differentially expressed genes (DEGs) related to prognosis through 
      DEG analysis and univariate Cox regression analysis. Lasso and multivariate Cox 
      regression analyses were performed to construct the LPC-related gene prognostic 
      model in the TCGA training dataset. This model was validated in the TCGA testing 
      set and an external dataset (International Cancer Genome Consortium [ICGC] 
      dataset). Finally, we investigated the relationship between this prognostic model 
      with tumor-node-metastasis stage, tumor grade, and vascular invasion of HCC. 
      Results: Overall, 1770 genes were identified as LPC-related genes, of which 92 
      genes were identified as DEGs in HCC tissues compared with normal tissues. 
      Furthermore, we randomly assigned patients from the TCGA dataset to the training 
      and testing cohorts. Twenty-six DEGs correlated with overall survival (OS) in the 
      univariate Cox regression analysis. Lasso and multivariate Cox regression 
      analyses were performed in the TCGA training set, and a 3-gene signature was 
      constructed to stratify patients into 2 risk groups: high-risk and low-risk. 
      Patients in the high-risk group had significantly lower OS than those in the 
      low-risk group. Receiver operating characteristic curve analysis confirmed the 
      signature's predictive capacity. Moreover, the risk score was confirmed to be an 
      independent predictor for patients with HCC. Conclusion: We demonstrated that the 
      LPC-related gene signature can be used for prognostication in HCC. Thus, 
      targeting LPCs may serve as a therapeutic alternative for HCC.
FAU - Li, Xiaoyong
AU  - Li X
AUID- ORCID: 0000-0001-7754-731X
AD  - 26468Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
FAU - Lin, Jiaqong
AU  - Lin J
AD  - School of Basic Medical Sciences, 70570Southern Medical University, Guangzhou, 
      China.
FAU - Pan, Yuguo
AU  - Pan Y
AD  - 26468Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
FAU - Cui, Peng
AU  - Cui P
AD  - 26468Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
FAU - Xia, Jintang
AU  - Xia J
AD  - 26468Third Affiliated Hospital of Guangzhou Medical University, Guangzhou, China.
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
PT  - Validation Study
PL  - United States
TA  - Technol Cancer Res Treat
JT  - Technology in cancer research & treatment
JID - 101140941
RN  - 0 (RNA, Messenger)
RN  - 0 (SPP1 protein, human)
RN  - 106441-73-0 (Osteopontin)
RN  - EC 2.1.1.43 (EZH2 protein, human)
RN  - EC 2.1.1.43 (Enhancer of Zeste Homolog 2 Protein)
RN  - EC 2.7.11.1 (PRKAA2 protein, human)
RN  - EC 2.7.11.31 (AMP-Activated Protein Kinases)
SB  - IM
MH  - AMP-Activated Protein Kinases/genetics
MH  - Adolescent
MH  - Adult
MH  - Aged
MH  - Aged, 80 and over
MH  - Carcinoma, Hepatocellular/*genetics/secondary
MH  - Databases, Genetic
MH  - Enhancer of Zeste Homolog 2 Protein/genetics
MH  - Female
MH  - Gene Expression Profiling
MH  - Humans
MH  - Liver Neoplasms/*genetics/pathology
MH  - Male
MH  - Middle Aged
MH  - Neoplasm Grading
MH  - Neoplasm Invasiveness/genetics
MH  - Neoplasm Staging
MH  - Oligonucleotide Array Sequence Analysis
MH  - Osteopontin/genetics
MH  - Prognosis
MH  - Proportional Hazards Models
MH  - RNA, Messenger/metabolism
MH  - ROC Curve
MH  - Retrospective Studies
MH  - Risk Assessment/methods
MH  - *Stem Cells
MH  - Survival Rate
MH  - *Transcriptome
MH  - Young Adult
PMC - PMC8652186
OTO - NOTNLM
OT  - LPC-related genes
OT  - bioinformation
OT  - hepatocellular carcinoma
OT  - mRNAs
OT  - prognostic signature
COIS- Declaration of Conflicting Interests: The authors declared no potential conflicts 
      of interest with respect to the research, authorship, and/or publication of this 
      article.
EDAT- 2021/12/07 06:00
MHDA- 2022/02/11 06:00
PMCR- 2021/12/06
CRDT- 2021/12/06 08:47
PHST- 2021/12/06 08:47 [entrez]
PHST- 2021/12/07 06:00 [pubmed]
PHST- 2022/02/11 06:00 [medline]
PHST- 2021/12/06 00:00 [pmc-release]
AID - 10.1177_15330338211041425 [pii]
AID - 10.1177/15330338211041425 [doi]
PST - ppublish
SO  - Technol Cancer Res Treat. 2021 Jan-Dec;20:15330338211041425. doi: 
      10.1177/15330338211041425.