Skip to main content

Table 4 Essential properties of the 11 records for the five miRNAs by data from GEO

From: A circRNA–miRNA–mRNA network identification for exploring underlying pathogenesis and therapy strategy of hepatocellular carcinoma

miRNA First author Year Region Data source Platform Number of case Expression (mean ± SD)
Cancer Normal Cancer Normal
hsa-miR-1303 Hou J 2010 China GSE21279 GPL9052 4 7 4.15 ± 1.206 2.49 ± 0.554
Sato F 2011 Japan GSE21362 GPL10312 59 61 1.59 ± 1.014 1.39 ± 1.042
Kim J 2012 South Korea GSE39678 GPL15852 16 8 11.00 ± 0.702 11.49 ± 0.364
Diaz G 2013 USA GSE40744 GPL14613 9 19 3.72 ± 0.774 2.78 ± 0.492
Villanueva A 2016 Spain GSE74618 GPL14613 230 10 1.88 ± 0.658 1.51 ± 0.263
TCGA 2017 USA TCGA none 21 5 0.35 ± 0.225 0.17 ± 0.100
Xie Z 2017 China GSE98269 GPL20712 3 3 5.07 ± 0.071 5.10 ± 0.115
hsa-miR-142-5p Li W 2008 China GSE10694 GPL6542 78 88 11.01 ± 0.605 11.19 ± 0.710
Su H 2008 China GSE12717 GPL7274 9 6 9.11 ± 1.406 9.09 ± 0.707
Burchard J 2010 USA GSE22058 GPL10457 96 96 0.95 ± 0.241 1.07 ± 0.135
Hou J 2010 China GSE21279 GPL9052 4 7 7.04 ± 1.190 7.77 ± 1.112
Sato F 2011 Japan GSE21362 GPL10312 59 61 7.06 ± 1.022 7.93 ± 0.577
Kim J 2012 South Korea GSE39678 GPL15852 16 8 11.10 ± 0.959 11.88 ± 0.182
Morita K 2013 Japan GSE41874 GPL7722 6 4 0.72 ± 0.412 1.34 ± 0.225
Diaz G 2013 USA GSE40744 GPL14613 9 19 1.96 ± 0.506 1.74 ± 0.224
Villanueva A 2016 Spain GSE74618 GPL14613 230 10 1.37 ± 0.206 1.36 ± 0.212
Xie Z 2017 China GSE98269 GPL20712 3 3 6.76 ± 0.733 6.88 ± 0.169
TCGA 2017 USA TCGA None 371 49 5.45 ± 1.264 6.86 ± 0.796
hsa-miR-877-5p Hou J 2010 China GSE21279 GPL9052 4 6 3.64 ± 1.753 2.19 ± 0.713
Sato F 2011 Japan GSE21362 GPL10312 59 61 2.17 ± 0.921 2.05 ± 0.961
Morita K 2013 Japan GSE41874 GPL7722 6 4 1.08 ± 0.313 1.06 ± 0.452
Diaz G 2013 USA GSE40744 GPL14613 9 19 5.36 ± 0.619 3.88 ± 0.797
Villanueva A 2016 Spain GSE74618 GPL14613 230 10 3.64 ± 0.741 3.42 ± 0.636
Xie Z 2017 China GSE98269 GPL20712 3 3 5.31 ± 0.073 5.12 ± 0.066
TCGA 2017 USA TCGA None 360 46 1.47 ± 0.807 0.73 ± 0.328
hsa-miR-583 Sato F 2011 Japan GSE21362 GPL10312 59 61 1.47 ± 0.722 1.46 ± 0.837
Morita K 2013 Japan GSE41874 GPL7722 6 4 0.91 ± 0.249 0.76 ± 0.293
Diaz G 2013 USA GSE40744 GPL14613 9 19 1.75 ± 0.247 1.77 ± 0.344
Villanueva A 2016 Spain GSE74618 GPL14613 230 10 1.43 ± 0.237 1.45 ± 0.294
Xie Z 2017 China GSE98269 GPL20712 3 3 5.07 ± 0.119 5.02 ± 0.020
hsa-miR-1276 Sato F 2011 Japan GSE21362 GPL10312 59 61 1.55 ± 0.810 1.72 ± 0.737
Diaz G 2013 USA GSE40744 GPL14613 9 19 1.9 ± 0.254 1.70 ± 0.209
Villanueva A 2016 Spain GSE74618 GPL14613 230 10 1.34 ± 0.164 1.38 ± 0.191
Xie Z 2017 China GSE98269 GPL20712 3 3 5.06 ± 0.049 5.06 ± 0.027
TCGA 2017 USA TCGA None 233 17 0.61 ± 0.380 0.36 ± 0.233
  1. TCGA The Cancer Genome Atlas, SD standard deviation
Back to article page

Journal of Translational Medicine

ISSN: 1479-5876

Contact us