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A competing endogenous RNA network identifies novel mRNA, miRNA and lncRNA markers for the prognosis of diabetic pancreatic cancer.

Abstract Pancreatic cancer (PaC) is highly associated with diabetes mellitus (DM). However, the mechanisms are insufficient. The study aimed to uncover the underlying regulatory mechanism on diabetic PaC and find novel biomarkers for the disease prognosis. Two RNA-sequencing (RNA-seq) datasets, GSE74629 and GSE15932, as well as relevant data in TCGA were utilized. After pretreatment, differentially expressed genes (DEGs) or miRNAs (DEMs) or lncRNAs (DELs) between diabetic PaC and non-diabetic PaC patients were identified, and further examined for their correlations with clinical information. Prognostic RNAs were selected using KM curve. Optimal gene set for classification of different samples were recognized by support vector machine. Protein-protein interaction (PPI) network was constructed for DEGs based on protein databases. Interactions among three kinds of RNAs were revealed in the 'lncRNA-miRNA-mRNA' competing endogenous RNA (ceRNA) network. A group of 32 feature genes were identified that could classify diabetic PaC from non-diabetic PaC, such as CCDC33, CTLA4 and MAP4K1. This classifier had a high accuracy on the prediction. Seven lncRNAs were tied up with prognosis of diabetic PaC, especially UCA1. In addition, crucial DEMs were selected, such as hsa-miR-214 (predicted targets: MAP4K1 and CCDC33) and hsa-miR-429 (predicted targets: CTLA4). Notably, interactions of 'HOTAIR-hsa-miR-214-CCDC33' and 'CECR7-hsa-miR-429-CTLA4' were highlighted in the ceRNA network. Several biomarkers were identified for diagnosis of diabetic PaC, such as HOTAIR, CECR7, UCA1, hsa-miR-214, hsa-miR-429, CCDC33 and CTLA4. 'HOTAIR-hsa-miR-214-CCDC33' and 'CECR7-hsa-miR-429-CTLA4' regulations might be two important mechanisms for the disease progression.
PMID
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Authors

Mayor MeshTerms
Keywords

Pancreatic cancer

competing endogenous RNA

diabetes mellitus

feature gene

lncRNA

Journal Title tumour biology : the journal of the international society for oncodevelopmental biology and medicine
Publication Year Start




PMID- 28639886
OWN - NLM
STAT- MEDLINE
DA  - 20170622
DCOM- 20170711
LR  - 20170713
IS  - 1423-0380 (Electronic)
IS  - 1010-4283 (Linking)
VI  - 39
IP  - 6
DP  - 2017 Jun
TI  - A competing endogenous RNA network identifies novel mRNA, miRNA and lncRNA
      markers for the prognosis of diabetic pancreatic cancer.
PG  - 1010428317707882
LID - 10.1177/1010428317707882 [doi]
AB  - Pancreatic cancer (PaC) is highly associated with diabetes mellitus (DM).
      However, the mechanisms are insufficient. The study aimed to uncover the
      underlying regulatory mechanism on diabetic PaC and find novel biomarkers for the
      disease prognosis. Two RNA-sequencing (RNA-seq) datasets, GSE74629 and GSE15932, 
      as well as relevant data in TCGA were utilized. After pretreatment,
      differentially expressed genes (DEGs) or miRNAs (DEMs) or lncRNAs (DELs) between 
      diabetic PaC and non-diabetic PaC patients were identified, and further examined 
      for their correlations with clinical information. Prognostic RNAs were selected
      using KM curve. Optimal gene set for classification of different samples were
      recognized by support vector machine. Protein-protein interaction (PPI) network
      was constructed for DEGs based on protein databases. Interactions among three
      kinds of RNAs were revealed in the 'lncRNA-miRNA-mRNA' competing endogenous RNA
      (ceRNA) network. A group of 32 feature genes were identified that could classify 
      diabetic PaC from non-diabetic PaC, such as CCDC33, CTLA4 and MAP4K1. This
      classifier had a high accuracy on the prediction. Seven lncRNAs were tied up with
      prognosis of diabetic PaC, especially UCA1. In addition, crucial DEMs were
      selected, such as hsa-miR-214 (predicted targets: MAP4K1 and CCDC33) and
      hsa-miR-429 (predicted targets: CTLA4). Notably, interactions of
      'HOTAIR-hsa-miR-214-CCDC33' and 'CECR7-hsa-miR-429-CTLA4' were highlighted in the
      ceRNA network. Several biomarkers were identified for diagnosis of diabetic PaC, 
      such as HOTAIR, CECR7, UCA1, hsa-miR-214, hsa-miR-429, CCDC33 and CTLA4.
      'HOTAIR-hsa-miR-214-CCDC33' and 'CECR7-hsa-miR-429-CTLA4' regulations might be
      two important mechanisms for the disease progression.
FAU - Yao, Kanyu
AU  - Yao K
AD  - 1 Department of Emergency Surgery, Affiliated Hospital of Inner Mongolia Medical 
      University, Hohhot, People's Republic of China.
FAU - Wang, Qi
AU  - Wang Q
AD  - 1 Department of Emergency Surgery, Affiliated Hospital of Inner Mongolia Medical 
      University, Hohhot, People's Republic of China.
FAU - Jia, Jianhua
AU  - Jia J
AD  - 2 The 253th Hospital of P.L.A., Hohhot, People's Republic of China.
FAU - Zhao, Haiping
AU  - Zhao H
AD  - 3 Department of Hepatobiliary Surgery, Affiliated Hospital of Inner Mongolia
      Medical University, Hohhot, People's Republic of China.
LA  - eng
PT  - Journal Article
PL  - United States
TA  - Tumour Biol
JT  - Tumour biology : the journal of the International Society for Oncodevelopmental
      Biology and Medicine
JID - 8409922
RN  - 0 (MicroRNAs)
RN  - 0 (Neoplasm Proteins)
RN  - 0 (RNA, Long Noncoding)
SB  - IM
MH  - Computational Biology
MH  - Diabetes Complications/*genetics/pathology
MH  - Diabetes Mellitus/genetics/pathology
MH  - Gene Expression Regulation, Neoplastic
MH  - Humans
MH  - MicroRNAs/*biosynthesis/genetics
MH  - Neoplasm Proteins/biosynthesis
MH  - Pancreatic Neoplasms/complications/*genetics/pathology
MH  - Protein Interaction Maps/genetics
MH  - RNA, Long Noncoding/*biosynthesis/genetics
OTO - NOTNLM
OT  - Pancreatic cancer
OT  - competing endogenous RNA
OT  - diabetes mellitus
OT  - feature gene
OT  - lncRNA
EDAT- 2017/06/24 06:00
MHDA- 2017/07/14 06:00
CRDT- 2017/06/23 06:00
AID - 10.1177/1010428317707882 [doi]
PST - ppublish
SO  - Tumour Biol. 2017 Jun;39(6):1010428317707882. doi: 10.1177/1010428317707882.