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pmid:26492393

Cancer Specific Long Noncoding RNAs Show Differential Expression Patterns and Competing Endogenous RNA Potential in Hepatocellular Carcinoma.

Jian Zhang · Dahua Fan · Zhixiang Jian · George G Chen · Paul B S Lai

PloS one · 2015 doi:10.1371/journal.pone.0141042

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Experiment

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Data

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:26492393
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science-record
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sha256:94e0eb3544d6771d8ee0be3dc2c8f7734b2ad4975807351e76436028d1ce5945
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2026-11-01T15:40:13Z
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2026-11-01T21:20:15Z
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title
Cancer Specific Long Noncoding RNAs Show Differential Expression Patterns and Competing Endogenous RNA Potential in Hepatocellular Carcinoma.
doi
10.1371/journal.pone.0141042
pmid
26492393
authors array · 5 items
[0]
Jian Zhang
[1]
Dahua Fan
[2]
Zhixiang Jian
[3]
George G Chen
[4]
Paul B S Lai
journal
PloS one
year
2015
abstract
Long noncoding RNAs (lncRNAs) regulate gene expression by acting with microRNAs (miRNAs). However, the roles of cancer specific lncRNA and its related competitive endogenous RNAs (ceRNA) network in hepatocellular cell carcinoma (HCC) are not fully understood. The lncRNA profiles in 372 HCC patients, including 372 tumor and 48 adjacent non-tumor liver tissues, from The Cancer Genome Atlas (TCGA) and NCBI GEO omnibus (GSE65485) were analyzed. Cancer specific lncRNAs (or HCC related lncRNAs) were identified and correlated with clinical features. Based on bioinformatics generated from miRcode, starBase, and miRTarBase, we constructed an lncRNA-miRNA-mRNA network (ceRNA network) in HCC. We found 177 cancer specific lncRNAs in HCC (fold change ≥ 1.5, P < 0.01), 41 of them were also discriminatively expressed with gender, race, tumor grade, AJCC tumor stage, and AJCC TNM staging system. Six lncRNAs (CECR7, LINC00346, MAPKAPK5-AS1, LOC338651, FLJ90757, and LOC283663) were found to be significantly associated with overall survival (OS, log-rank P < 0.05). Collectively, our results showed the lncRNA expression patterns and a complex ceRNA network in HCC, and identified a complex cancer specific ceRNA network, which includes 14 lncRNAs and 17 miRNAs in HCC.
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Differences among groups were evaluated by two-sample t test and the significance level was set as 0.001 as default to control the false discovery rate (FDR).
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Differences among groups were evaluated by two-sample t test and the significance level was set as 0.001 as default to control the false discovery rate (FDR).
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All relevant data are within the paper and its Supporting Information files.
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sections[16] "Data Availability" paragraph 2
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All relevant data are within the paper and its Supporting Information files.
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Using TCGA and GEO RNA-sequencing data analyzed with BRB-ArrayTools and R, the study identified 177 cancer-specific lncRNAs in HCC, with six significantly associated with overall survival (log-rank P < 0.05).
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sections[0] "Abstract" paragraph 1
quote
The lncRNA profiles in 372 HCC patients, including 372 tumor and 48 adjacent non-tumor liver tissues, from The Cancer Genome Atlas (TCGA) and NCBI GEO omnibus (GSE65485) were analyzed.
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quote
Based on bioinformatics generated from miRcode, starBase, and miRTarBase, we constructed an lncRNA-miRNA-mRNA network (ceRNA network) in HCC.
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sections[0] "Abstract" paragraph 1
quote
We found 177 cancer specific lncRNAs in HCC (fold change ≥ 1.5, P < 0.01), 41 of them were also discriminatively expressed with gender, race, tumor grade, AJCC tumor stage, and AJCC TNM staging system.
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sections[0] "Abstract" paragraph 1
quote
Six lncRNAs (CECR7, LINC00346, MAPKAPK5-AS1, LOC338651, FLJ90757, and LOC283663) were found to be significantly associated with overall survival (OS, log-rank P < 0.05).
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sections[6] "Statistical analysis" paragraph 2
quote
The statistical analyses were performed by BRB-ArrayTools or R language [19].
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Using TCGA and GEO RNA-sequencing data analyzed with BRB-ArrayTools and R, the study identified 177 cancer-specific lncRNAs in HCC, with six significantly associated with overall survival (log-rank P < 0.05).
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Next Generation Sequencing Identification of HBV-MLL4 integration and its molecular basis in Chinese hepatocellular carcinoma
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Twenty eight cancer specific lncRNAs in ceRNA network construction.This table showed 28 cancer specific lncRNAs for ceRNA network construction with absolute fold change ≥ 3.0, P < 0.01 and included in GENCODE.
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Cancer specific lncRNAs in HCC
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Table 1
caption
Twenty eight cancer specific lncRNAs in ceRNA network construction.This table showed 28 cancer specific lncRNAs for ceRNA network construction with absolute fold change ≥ 3.0, P < 0.01 and included in GENCODE.
rows array · 29 items
[0] array · 5 items
[0]
LncRNA
[1]
Gene ID
[2]
Chromosome
[3]
Expression change (T vs. N)
[4]
Data set
[1] array · 5 items
[0]
ASMTL-AS1
[1]
ENSG00000236017
[2]
chrX
[3]
Up-regulation
[4]
TCGA
[2] array · 5 items
[0]
CDKN2B-AS1
[1]
ENSG00000240498
[2]
chr9
[3]
Up-regulation
[4]
TCGA + GEO
[3] array · 5 items
[0]
CECR7
[1]
ENSG00000237438
[2]
chr22
[3]
Up-regulation
[4]
TCGA
[4] array · 5 items
[0]
FLVCR1-AS1
[1]
ENSG00000198468
[2]
chr1
[3]
Up-regulation
[4]
TCGA
[5] array · 5 items
[0]
FOXD2-AS1
[1]
ENSG00000237424
[2]
chr1
[3]
Up-regulation
[4]
TCGA
[6] array · 5 items
[0]
GAS5
[1]
ENSG00000234741
[2]
chr1
[3]
Up-regulation
[4]
TCGA
[7] array · 5 items
[0]
IGF2BP2-AS1
[1]
ENSG00000163915
[2]
chr3
[3]
Up-regulation
[4]
TCGA
[8] array · 5 items
[0]
LINC00152
[1]
ENSG00000222041
[2]
chr2
[3]
Up-regulation
[4]
TCGA
[9] array · 5 items
[0]
LINC00176
[1]
ENSG00000196421
[2]
chr20
[3]
Up-regulation
[4]
TCGA
[10] array · 5 items
[0]
LINC00488
[1]
ENSG00000214381
[2]
chr3
[3]
Up-regulation
[4]
TCGA
[11] array · 5 items
[0]
LINC00685
[1]
ENSG00000226179
[2]
chrX
[3]
Up-regulation
[4]
TCGA
[12] array · 5 items
[0]
PVT1
[1]
ENSG00000249859
[2]
chr8
[3]
Up-regulation
[4]
TCGA + GEO
[13] array · 5 items
[0]
RUSC1-AS1
[1]
ENSG00000225855
[2]
chr1
[3]
Up-regulation
[4]
TCGA
[14] array · 5 items
[0]
SNHG1
[1]
ENSG00000255717
[2]
chr11
[3]
Up-regulation
[4]
TCGA
[15] array · 5 items
[0]
SNHG3
[1]
ENSG00000242125
[2]
chr1
[3]
Up-regulation
[4]
TCGA + GEO
[16] array · 5 items
[0]
SNHG4
[1]
ENSG00000281398
[2]
chr5
[3]
Up-regulation
[4]
TCGA + GEO
[17] array · 5 items
[0]
TSPEAR-AS2
[1]
ENSG00000182912
[2]
chr21
[3]
Up-regulation
[4]
TCGA
[18] array · 5 items
[0]
ZNF252P-AS1
[1]
ENSG00000255559
[2]
chr8
[3]
Up-regulation
[4]
TCGA
[19] array · 5 items
[0]
DIO3OS
[1]
ENSG00000258498
[2]
chr14
[3]
Down-regulation
[4]
GEO
[20] array · 5 items
[0]
FAM99A
[1]
ENSG00000205866
[2]
chr11
[3]
Down-regulation
[4]
TCGA + GEO
[21] array · 5 items
[0]
FAM99B
[1]
ENSG00000205865
[2]
chr11
[3]
Down-regulation
[4]
TCGA
[22] array · 5 items
[0]
H19
[1]
ENSG00000130600
[2]
chr11
[3]
Down-regulation
[4]
TCGA
[23] array · 5 items
[0]
HAND2-AS1
[1]
ENSG00000237125
[2]
chr4
[3]
Down-regulation
[4]
TCGA
[24] array · 5 items
[0]
HAR1A
[1]
ENSG00000225978
[2]
chr20
[3]
Down-regulation
[4]
TCGA
[25] array · 5 items
[0]
LINC00238
[1]
ENSG00000196553
[2]
chr14
[3]
Down-regulation
[4]
TCGA
[26] array · 5 items
[0]
LINC01554
[1]
ENSG00000236882
[2]
chr5
[3]
Down-regulation
[4]
TCGA
[27] array · 5 items
[0]
PWRN1
[1]
ENSG00000259905
[2]
chr15
[3]
Down-regulation
[4]
GEO
[28] array · 5 items
[0]
UCA1
[1]
ENSG00000214049
[2]
chr19
[3]
Down-regulation
[4]
TCGA
locator
section[8]/table-wrap[1]#pone.0141042.t001
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The correlations between cancer specific lncRNAs and clinical features.This table showed 41 cancer specific lncRNA which were also differentially expressed in clinical feature comparisons.
structure object · 5 fields
pmcid
PMC4619599
section_index
9
section_title
The correlations between cancer specific lncRNAs and clinical features
row_count
10
column_count
3
table object · 8 fields
label
Table 2
caption
The correlations between cancer specific lncRNAs and clinical features.This table showed 41 cancer specific lncRNA which were also differentially expressed in clinical feature comparisons.
rows array · 10 items
[0] array · 3 items
[0]
Comparisons
[1]
Down-regulated
[2]
Up-regulated
[1] array · 3 items
[0]
Gender (Female vs. Male)
[1]
LOC643837, LINC00526, FAM223B, MIR99AHG, LINC01554, TTTY15
[2]
H19, LINC00092, MIR600HG, LOC645676, COLCA1, LOC723809
[2] array · 3 items
[0]
Race (White vs. Asian)
[1]
GAS5, SNHG7, LOC100128191, SNHG1, HCG18
[2]
HCG11, LINC00242, GLIDR, LINC00261, LINC00638, LINC00574
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[0]
Tumor grade (G3 + G4 vs. G1 + G2)
[1]
LOC255167, FAM99A, LINC00574, LOC399959, A1BG-AS1, LINC00526, LINC00261, MIR22HG, LOC643837
[2]
MALAT1, SNHG12, HCG18, SNHG20, ZFAS1, LOC440944, SNHG7, LOC100128191, MCM3AP-AS1, SNHG1, KCNQ1OT1, DSCR9, GAS5, LOC92659
[4] array · 3 items
[0]
AJCC TNM staging system (T3 + T4 vs. T1 + T2)
[1]
LOC255167, LINC01554, LINC01558, A1BG-AS1
[2]
MCM3AP-AS1
[5] array · 3 items
[0]
AJCC pathological stage (III + IV vs. I + II)
[1]
LOC255167, LINC01554, LINC01558, A1BG-AS1
[2]
UCA1
[6] array · 3 items
[0]
Vascular invasion (No vs. Yes)
[1]
MAPKAPK5-AS1, HNF1A-AS1, DSCR9
[2]
FAM99A
[7] array · 3 items
[0]
New tumor event (Yes vs. No)
[1]
MIR22HG
[2]
[8] array · 3 items
[0]
Tumor status (With tumor vs. Tumor free)
[1]
MIR22HG
[2]
[9] array · 3 items
[0]
Age at diagnosis (≥ 61 vs. < 61)
[1]
[2]
LINC01554, LINC00526, LOC255167
locator
section[9]/table-wrap[1]#pone.0141042.t002
[4] object · 16 fields
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note
Putative miRNAs that may target cancer specific lncRNAs by MREs.miR-199A-1 and miR-199A-2 were regards as a single miRNA in our study
structure object · 5 fields
pmcid
PMC4619599
section_index
10
section_title
miRNA targeting lncRNAs predicted by miRcode and starBase
row_count
16
column_count
2
table object · 8 fields
label
Table 3
caption
Putative miRNAs that may target cancer specific lncRNAs by MREs.miR-199A-1 and miR-199A-2 were regards as a single miRNA in our study
rows array · 16 items
[0] array · 2 items
[0]
lncRNA
[1]
miRNAs
[1] array · 2 items
[0]
LINC00176
[1]
miR-424, miR-184, miR-214, miR-93
[2] array · 2 items
[0]
PVT1
[1]
miR-195, miR-424, miR-183, miR-199A-1/2, miR-214, miR-383, miR-93
[3] array · 2 items
[0]
LINC00488
[1]
miR-139
[4] array · 2 items
[0]
RUSC1-AS1
[1]
miR-10B, miR-135A-1, miR-139, miR-182, miR-199A-1/2, miR-214, miR-96
[5] array · 2 items
[0]
FLVCR1-AS1
[1]
miR-375
[6] array · 2 items
[0]
GAS5
[1]
miR-10B, miR-139, miR-182, miR-490, miR-93, miR-96
[7] array · 2 items
[0]
UCA1
[1]
miR-214, miR-383
[8] array · 2 items
[0]
SNHG1
[1]
miR-182, miR-195, miR-383, miR-424
[9] array · 2 items
[0]
SNHG3
[1]
miR-135A-1, miR-139, miR-182
[10] array · 2 items
[0]
CDKN2B-AS1
[1]
miR-10B
[11] array · 2 items
[0]
LINC00152
[1]
miR-376C
[12] array · 2 items
[0]
CECR7
[1]
miR-199A-1/2, miR-214
[13] array · 2 items
[0]
DIO3OS
[1]
miR-10B, miR-139, miR-199A-1/2, miR-214, miR-34C
[14] array · 2 items
[0]
H19
[1]
miR-93
[15] array · 2 items
[0]
LINC00238
[1]
miR-33B, miR-375
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section[10]/table-wrap[1]#pone.0141042.t003
[5] object · 16 fields
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read_table
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identifier
section[11]/table-wrap[1]#pone.0141042.t004
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null
note
Validation of miRNA targets.
structure object · 5 fields
pmcid
PMC4619599
section_index
11
section_title
miRNA targets predicted by miRTarBase
row_count
18
column_count
2
table object · 8 fields
label
Table 4
caption
Validation of miRNA targets.
rows array · 18 items
[0] array · 2 items
[0]
miRNA
[1]
mRNAs targeted by miRNAs
[1] array · 2 items
[0]
miR-10B
[1]
PPARA, NF1, CDKN2A, HOXD10, KLF4, NCOR2, CDKN1A, TFAP2C, BCL2L11
[2] array · 2 items
[0]
miR-135A-1
[1]
JAK2, NR3C2, APC, MYC
[3] array · 2 items
[0]
miR-139
[1]
FOS
[4] array · 2 items
[0]
miR-182
[1]
CDKN1A, FOXO1, MITF, FOXO3, RARG, ADCY6, CLOCK, TSC22D3, CYLD, BCL2, CCND2, PDCD4, RECK, EP300, FGF9, NTM
[5] array · 2 items
[0]
miR-183
[1]
SRSF2, PDCD4, AKAP12, FOXO1, ITGB1, KIF2A, BTRC, EZR, IDH2
[6] array · 2 items
[0]
miR-184
[1]
AKT2, INPPL1, NFATC2
[7] array · 2 items
[0]
miR-195
[1]
WEE1, E2F3, CDK6, BCL2, CCND1, RUNX2, RAF1, CCL4, BCL2L11, MECP2, CCND3, TBCCD1, VEGFA, SKI, KRT7, SLC2A3, CAB39, BCL2L2
[8] array · 2 items
[0]
miR-199A-1/2
[1]
CD44, IKBKB, MET, HIF1A, SMARCA2, SMARCA2, MAPK1, DDR1, MAP3K11, FUT4, CAV2, EZH2, CCNL1, MAPK9, AKT1, MAPK8, MAPK14, LIF, JUNB, MED6, MECP2, ETS2, EDN1, TMEM54, SIRT1
[9] array · 2 items
[0]
miR-214
[1]
PTEN, MAP2K3, MAPK8, PLXNB1, EZH2, POU4F2, GALNT7, XBP1, DAPK1, SRGAP1, TWIST1, BCL2L2, ING4, FLOT1, MAP2K5, HSPD1, AHSA1, CPNE7, RASA1, YWHAQ, ARL2, AP3B1
[10] array · 2 items
[0]
miR-33B
[1]
BCL2, ABCA1
[11] array · 2 items
[0]
miR-34C
[1]
MET, CDK4, NOTCH1, BCL2, E2F3, MYB, CAV1, CCNE2, MYCN, NOTCH4, ULBP2, MYC, SRSF2, SOX2, NANOG
[12] array · 2 items
[0]
miR-375
[1]
ELAVL4, YWHAZ, TIMM8A, PDK1, YAP1, MTDH, RASD1, YY1AP1, RHOA, KCNQ2, MTPN, USP1, JAK2, C1QBP, PLAG1, BCL2L11, RAB10, PARP1, CAB39, DLG4, ITGB1, SETD8, CASP3, CDC42, EIF2AK2, BCL2, NCAM1, LEPROTL1
[13] array · 2 items
[0]
miR-376C
[1]
ACVR1C, IGF1R
[14] array · 2 items
[0]
miR-383
[1]
DIO1, IRF1, VEGFA
[15] array · 2 items
[0]
miR-424
[1]
HIF1A, CUL2, SPI1, PLAG1, CCNE1, CCND3, CDK6, CCND1, MAP2K1, WEE1, NFIA, LGALS3, MYB, SIAH1, CCNF, CDC14A, CDC25A, CHEK1, KIF23, ATF6, ANLN, FGFR1, PIAS1, ITPR1
[16] array · 2 items
[0]
miR-93
[1]
CDKN1A, E2F1, ITGB8, TUSC2, TP53INP1, KAT2B, PTEN, LATS2, MAPK9, VEGFA
[17] array · 2 items
[0]
miR-96
[1]
CDKN1A, KRAS, FOXO1, FOXO3, ADCY6, REV1, RAD51, MITF, HTR1B, PRMT5
locator
section[11]/table-wrap[1]#pone.0141042.t004
[6] object · 16 fields
id
asset:table:pmid:26492393:5
role
table
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jats-table
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application/vnd.jats.table+json
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null
sha256
sha256:28d168fcd752bbad079ce473bddfd753ca780dce429f52f5b2bef77fbc054513
bytes
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open
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verified
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read_table
reader_status
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identifier
section[12]/table-wrap[1]#pone.0141042.t005
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null
note
Top 15 KEEG pathways enriched by the coding genes involved in ceRNA network (P < 0.0001).The P value was corrected for multiple hypothesis testing using the Benjamini-Hochberg method (Please also refer to S3 Table)
structure object · 5 fields
pmcid
PMC4619599
section_index
12
section_title
ceRNA network construction and KEEG pathway analysis
row_count
18
column_count
3
table object · 8 fields
label
Table 5
caption
Top 15 KEEG pathways enriched by the coding genes involved in ceRNA network (P < 0.0001).The P value was corrected for multiple hypothesis testing using the Benjamini-Hochberg method (Please also refer to S3 Table)
rows array · 18 items
[0] array · 3 items
[0]
[1]
KEEG pathways
[2]
No. of Genes
[1] array · 3 items
[0]
Cancer related
[1]
[2]
[2] array · 3 items
[0]
[1]
Pathways in cancer
[2]
41
[3] array · 2 items
[0]
Pancreatic cancer
[1]
19
[4] array · 2 items
[0]
Melanoma
[1]
19
[5] array · 2 items
[0]
Prostate cancer
[1]
19
[6] array · 2 items
[0]
Chronic myeloid leukemia
[1]
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[7] array · 2 items
[0]
Colorectal cancer
[1]
16
[8] array · 2 items
[0]
Glioma
[1]
15
[9] array · 2 items
[0]
Small cell lung cancer
[1]
15
[10] array · 2 items
[0]
Bladder cancer
[1]
13
[11] array · 2 items
[0]
Non-small cell lung cancer
[1]
13
[12] array · 3 items
[0]
Non-cancer related
[1]
[2]
[13] array · 3 items
[0]
[1]
MAPK signaling pathway
[2]
22
[14] array · 2 items
[0]
Focal adhesion
[1]
21
[15] array · 2 items
[0]
Cell cycle
[1]
19
[16] array · 2 items
[0]
Neurotrophin signaling pathway
[1]
18
[17] array · 2 items
[0]
T cell receptor signaling pathway
[1]
14
locator
section[12]/table-wrap[1]#pone.0141042.t005
gaps array · 2 items
[0]
asset:data:geo:GSE65485 not downloaded
[1]
asset:data:geo:GSE65485 licence not read
analysis object · 4 fields
state
partial
methods array · 3 items
[0] object · 10 fields
id
method-1
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survival_analysis
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cox_proportional_hazards
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Survival analysis
dsl_operations array · 1 item
[0]
cox_ph
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.8
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Cox proportional hazards
[1] object · 10 fields
id
method-2
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survival_analysis
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log_rank_test
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Survival analysis
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[0]
logrank_test
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
time_to_event_with_censoring
evidence object · 3 fields
score
0.7
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log-rank
[2] object · 10 fields
id
method-3
family
null
specific
null
label
two-sample t test
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missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
Differences among groups were evaluated by two-sample t test and the significance level was set as 0.001 as default to control the false discovery rate (FDR).
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gaps array · 1 item
[0]
method.reader_named_unmapped
capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
Computational analysis platform
assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
[2]
survival_analysis
[3]
statistical_regression
[4]
pca
[5]
molecular_docking
[6]
network_analysis
[7]
differential_expression
[8]
gwas
candidate
Automated Assays Laravel application and simulated adapters
gaps array · 0 items
readiness object · 8 fields
state
complete
tier
R1
blocked_on
nothing:replicable_now
axes object · 3 fields
method object · 5 fields
tier
R1
expressible
true
required_operations array · 1 item
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cox_ph
missing_operations array · 0 items
basis
The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards.
capability object · 4 fields
tier
R1
capability_id
capability:computational_analysis
availability_state
owned
basis
The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
data object · 6 fields
tier
R1
reachable
true
accessions array · 1 item
[0]
GSE65485
resolved_accessions array · 1 item
[0]
GSE65485
statements array · 1 item
[0]
All relevant data are within the paper and its Supporting Information files.
basis
The paper names GSE65485 in NCBI GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
[0]
cox_ph
assets array · 7 items
[0]
source:pmid:26492393
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data:geo:GSE65485
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asset:table:pmid:26492393:1
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asset:table:pmid:26492393:2
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asset:table:pmid:26492393:3
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asset:table:pmid:26492393:4
[6]
asset:table:pmid:26492393:5
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
dsl_operations array · 0 items
converters array · 0 items
readers array · 0 items
capabilities array · 0 items
data_gaps array · 1 item
[0]
data:geo:GSE65485
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:26:08Z
independence
same_provider
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
8
usage object · 3 fields
prompt_tokens
65984
completion_tokens
4342
cached_tokens
17152
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
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MiniMax-M3.1-Flash
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minimax
gaps array · 3 items
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review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
runs array · 0 items
gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:26492393
type
paper
label
pmid:26492393
[1] object · 3 fields
id
source:pmid:26492393
type
manuscript
label
PMID 26492393 full text
[2] object · 3 fields
id
data:geo:GSE65485
type
dataset
label
GEO GSE65485
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
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[0] object · 3 fields
id
pmid:26492393
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paper
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pmid:26492393
[1] object · 3 fields
id
source:pmid:26492393
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manuscript
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PMID 26492393 full text
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id
data:geo:GSE65485
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dataset
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GEO GSE65485
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-26492393
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extraction
used array · 1 item
[0]
source:pmid:26492393
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE65485
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accession_resolution
used array · 1 item
[0]
data:geo:GSE65485
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
type
software
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Corpus assay engine
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id
agent:minimax-reader
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software
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MiniMax literature reader
source_run_id
reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
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ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:26492393
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sha256:83ba63fd1c87cde1531a5d2549715cf3d737750f336996f2826f893e5888f96c
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null
gaps array · 7 items
[0]
asset:data:geo:GSE65485 licence not read
[1]
asset:data:geo:GSE65485 not downloaded
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execution.not_run
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method.reader_named_unmapped
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review.human_critique
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review.independent_reader
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review.machine_critique
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role
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f2132e96ae6c7a4e
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cox_ph
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dsl_catalogue
f2132e96ae6c7a4e
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Cox proportional hazards
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analysis_only
id
assay:1
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:26492393", "kind": "science-record", "revision": 6, "content_hash": "sha256:94e0eb3544d6771d8ee0be3dc2c8f7734b2ad4975807351e76436028d1ce5945", "created_at": "2026-11-01T15:40:13Z", "updated_at": "2026-11-01T21:20:15Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Cancer Specific Long Noncoding RNAs Show Differential Expression Patterns and Competing Endogenous RNA Potential in Hepatocellular Carcinoma.", "doi": "10.1371/journal.pone.0141042", "pmid": "26492393", "authors": ["Jian Zhang", "Dahua Fan", "Zhixiang Jian", "George G Chen", "Paul B S Lai"], "journal": "PloS one", "year": 2015, "abstract": "Long noncoding RNAs (lncRNAs) regulate gene expression by acting with microRNAs (miRNAs). However, the roles of cancer specific lncRNA and its related competitive endogenous RNAs (ceRNA) network in hepatocellular cell carcinoma (HCC) are not fully understood. The lncRNA profiles in 372 HCC patients, including 372 tumor and 48 adjacent non-tumor liver tissues, from The Cancer Genome Atlas (TCGA) and NCBI GEO omnibus (GSE65485) were analyzed. Cancer specific lncRNAs (or HCC related lncRNAs) were identified and correlated with clinical features. Based on bioinformatics generated from miRcode, starBase, and miRTarBase, we constructed an lncRNA-miRNA-mRNA network (ceRNA network) in HCC. We found 177 cancer specific lncRNAs in HCC (fold change ≥ 1.5, P < 0.01), 41 of them were also discriminatively expressed with gender, race, tumor grade, AJCC tumor stage, and AJCC TNM staging system. Six lncRNAs (CECR7, LINC00346, MAPKAPK5-AS1, LOC338651, FLJ90757, and LOC283663) were found to be significantly associated with overall survival (OS, log-rank P < 0.05). Collectively, our results showed the lncRNA expression patterns and a complex ceRNA network in HCC, and identified a complex cancer specific ceRNA network, which includes 14 lncRNAs and 17 miRNAs in HCC.", "claims": [{"id": "claim-method", "statement": "Differences among groups were evaluated by two-sample t test and the significance level was set as 0.001 as default to control the false discovery rate (FDR).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:26492393", "locator": "sections[6] \"Statistical analysis\" paragraph 2", "quote": "Differences among groups were evaluated by two-sample t test and the significance level was set as 0.001 as default to control the false discovery rate (FDR)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All relevant data are within the paper and its Supporting Information files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:26492393", "locator": "sections[16] \"Data Availability\" paragraph 2", "quote": "All relevant data are within the paper and its Supporting Information files."}], "state": "complete"}, {"id": "claim-target-result", "statement": "Using TCGA and GEO RNA-sequencing data analyzed with BRB-ArrayTools and R, the study identified 177 cancer-specific lncRNAs in HCC, with six significantly associated with overall survival (log-rank P < 0.05).", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:26492393", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "The lncRNA profiles in 372 HCC patients, including 372 tumor and 48 adjacent non-tumor liver tissues, from The Cancer Genome Atlas (TCGA) and NCBI GEO omnibus (GSE65485) were analyzed."}, {"asset": "source:pmid:26492393", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Based on bioinformatics generated from miRcode, starBase, and miRTarBase, we constructed an lncRNA-miRNA-mRNA network (ceRNA network) in HCC."}, {"asset": "source:pmid:26492393", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "We found 177 cancer specific lncRNAs in HCC (fold change ≥ 1.5, P < 0.01), 41 of them were also discriminatively expressed with gender, race, tumor grade, AJCC tumor stage, and AJCC TNM staging system."}, {"asset": "source:pmid:26492393", "locator": "sections[0] \"Abstract\" paragraph 1", "quote": "Six lncRNAs (CECR7, LINC00346, MAPKAPK5-AS1, LOC338651, FLJ90757, and LOC283663) were found to be significantly associated with overall survival (OS, log-rank P < 0.05)."}, {"asset": "source:pmid:26492393", "locator": "sections[6] \"Statistical analysis\" paragraph 2", "quote": "The statistical analyses were performed by BRB-ArrayTools or R language [19]."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "Using TCGA and GEO RNA-sequencing data analyzed with BRB-ArrayTools and R, the study identified 177 cancer-specific lncRNAs in HCC, with six significantly associated with overall survival (log-rank P < 0.05).", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:26492393"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "complete", "blocked_on": null, "description": "The GEO series accession resolves and its sample accessions are listed. 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"group_sizes": null, "group_sizes_basis": null, "platform": "11154", "taxon": "Homo sapiens", "title": "Next Generation Sequencing Identification of HBV-MLL4 integration and its molecular basis in Chinese hepatocellular carcinoma", "resolution_checked_at": "2026-11-01T15:39:55Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}, {"id": "asset:table:pmid:26492393:1", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:89613f39a391bcc13013aaaeef13a04f903101ee58d20026e2ada034d48b0361", "bytes": 2198, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[8]/table-wrap[1]#pone.0141042.t001", "version": null, "note": "Twenty eight cancer specific lncRNAs in ceRNA network construction.This table showed 28 cancer specific lncRNAs for ceRNA network construction with absolute fold change ≥ 3.0, P < 0.01 and included in GENCODE.", "structure": {"pmcid": "PMC4619599", "section_index": 8, "section_title": "Cancer specific lncRNAs in HCC", "row_count": 29, "column_count": 5}, "table": {"label": "Table 1", "caption": "Twenty eight cancer specific lncRNAs in ceRNA network construction.This table showed 28 cancer specific lncRNAs for ceRNA network construction with absolute fold change ≥ 3.0, P < 0.01 and included in GENCODE.", "rows": [["LncRNA", "Gene ID", "Chromosome", "Expression change (T vs. N)", "Data set"], ["ASMTL-AS1", "ENSG00000236017", "chrX", "Up-regulation", "TCGA"], ["CDKN2B-AS1", "ENSG00000240498", "chr9", "Up-regulation", "TCGA + GEO"], ["CECR7", "ENSG00000237438", "chr22", "Up-regulation", "TCGA"], ["FLVCR1-AS1", "ENSG00000198468", "chr1", "Up-regulation", "TCGA"], ["FOXD2-AS1", "ENSG00000237424", "chr1", "Up-regulation", "TCGA"], ["GAS5", "ENSG00000234741", "chr1", "Up-regulation", "TCGA"], ["IGF2BP2-AS1", "ENSG00000163915", "chr3", "Up-regulation", "TCGA"], ["LINC00152", "ENSG00000222041", "chr2", "Up-regulation", "TCGA"], ["LINC00176", "ENSG00000196421", "chr20", "Up-regulation", "TCGA"], ["LINC00488", "ENSG00000214381", "chr3", "Up-regulation", "TCGA"], ["LINC00685", "ENSG00000226179", "chrX", "Up-regulation", "TCGA"], ["PVT1", "ENSG00000249859", "chr8", "Up-regulation", "TCGA + GEO"], ["RUSC1-AS1", "ENSG00000225855", "chr1", "Up-regulation", "TCGA"], ["SNHG1", "ENSG00000255717", "chr11", "Up-regulation", "TCGA"], ["SNHG3", "ENSG00000242125", "chr1", "Up-regulation", "TCGA + GEO"], ["SNHG4", "ENSG00000281398", "chr5", "Up-regulation", "TCGA + GEO"], ["TSPEAR-AS2", "ENSG00000182912", "chr21", "Up-regulation", "TCGA"], ["ZNF252P-AS1", "ENSG00000255559", "chr8", "Up-regulation", "TCGA"], ["DIO3OS", "ENSG00000258498", "chr14", "Down-regulation", "GEO"], ["FAM99A", "ENSG00000205866", "chr11", "Down-regulation", "TCGA + GEO"], ["FAM99B", "ENSG00000205865", "chr11", "Down-regulation", "TCGA"], ["H19", "ENSG00000130600", "chr11", "Down-regulation", "TCGA"], ["HAND2-AS1", "ENSG00000237125", "chr4", "Down-regulation", "TCGA"], ["HAR1A", "ENSG00000225978", "chr20", "Down-regulation", "TCGA"], ["LINC00238", "ENSG00000196553", "chr14", "Down-regulation", "TCGA"], ["LINC01554", "ENSG00000236882", "chr5", "Down-regulation", "TCGA"], ["PWRN1", "ENSG00000259905", "chr15", "Down-regulation", "GEO"], ["UCA1", "ENSG00000214049", "chr19", "Down-regulation", "TCGA"]], "row_count": 29, "column_count": 5, "numeric_cells": 50, "header_rows": 1, "locator": "section[8]/table-wrap[1]#pone.0141042.t001"}}, {"id": "asset:table:pmid:26492393:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:c337b58f5565e801b5e8cd93dfccded0c8e05a64599f3c21820a1bad09cdd0f2", "bytes": 1394, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[9]/table-wrap[1]#pone.0141042.t002", "version": null, "note": "The correlations between cancer specific lncRNAs and clinical features.This table showed 41 cancer specific lncRNA which were also differentially expressed in clinical feature comparisons.", "structure": {"pmcid": "PMC4619599", "section_index": 9, "section_title": "The correlations between cancer specific lncRNAs and clinical features", "row_count": 10, "column_count": 3}, "table": {"label": "Table 2", "caption": "The correlations between cancer specific lncRNAs and clinical features.This table showed 41 cancer specific lncRNA which were also differentially expressed in clinical feature comparisons.", "rows": [["Comparisons", "Down-regulated", "Up-regulated"], ["Gender (Female vs. Male)", "LOC643837, LINC00526, FAM223B, MIR99AHG, LINC01554, TTTY15", "H19, LINC00092, MIR600HG, LOC645676, COLCA1, LOC723809"], ["Race (White vs. Asian)", "GAS5, SNHG7, LOC100128191, SNHG1, HCG18", "HCG11, LINC00242, GLIDR, LINC00261, LINC00638, LINC00574"], ["Tumor grade (G3 + G4 vs. G1 + G2)", "LOC255167, FAM99A, LINC00574, LOC399959, A1BG-AS1, LINC00526, LINC00261, MIR22HG, LOC643837", "MALAT1, SNHG12, HCG18, SNHG20, ZFAS1, LOC440944, SNHG7, LOC100128191, MCM3AP-AS1, SNHG1, KCNQ1OT1, DSCR9, GAS5, LOC92659"], ["AJCC TNM staging system (T3 + T4 vs. T1 + T2)", "LOC255167, LINC01554, LINC01558, A1BG-AS1", "MCM3AP-AS1"], ["AJCC pathological stage (III + IV vs. I + II)", "LOC255167, LINC01554, LINC01558, A1BG-AS1", "UCA1"], ["Vascular invasion (No vs. Yes)", "MAPKAPK5-AS1, HNF1A-AS1, DSCR9", "FAM99A"], ["New tumor event (Yes vs. No)", "MIR22HG", ""], ["Tumor status (With tumor vs. Tumor free)", "MIR22HG", ""], ["Age at diagnosis (≥ 61 vs. < 61)", "", "LINC01554, LINC00526, LOC255167"]], "row_count": 10, "column_count": 3, "numeric_cells": 13, "header_rows": 1, "locator": "section[9]/table-wrap[1]#pone.0141042.t002"}}, {"id": "asset:table:pmid:26492393:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:7097a7f0cc6780f3226e983e4739144683a9961af609b7ceb7d47e4754130c67", "bytes": 952, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[1]#pone.0141042.t003", "version": null, "note": "Putative miRNAs that may target cancer specific lncRNAs by MREs.miR-199A-1 and miR-199A-2 were regards as a single miRNA in our study", "structure": {"pmcid": "PMC4619599", "section_index": 10, "section_title": "miRNA targeting lncRNAs predicted by miRcode and starBase", "row_count": 16, "column_count": 2}, "table": {"label": "Table 3", "caption": "Putative miRNAs that may target cancer specific lncRNAs by MREs.miR-199A-1 and miR-199A-2 were regards as a single miRNA in our study", "rows": [["lncRNA", "miRNAs"], ["LINC00176", "miR-424, miR-184, miR-214, miR-93"], ["PVT1", "miR-195, miR-424, miR-183, miR-199A-1/2, miR-214, miR-383, miR-93"], ["LINC00488", "miR-139"], ["RUSC1-AS1", "miR-10B, miR-135A-1, miR-139, miR-182, miR-199A-1/2, miR-214, miR-96"], ["FLVCR1-AS1", "miR-375"], ["GAS5", "miR-10B, miR-139, miR-182, miR-490, miR-93, miR-96"], ["UCA1", "miR-214, miR-383"], ["SNHG1", "miR-182, miR-195, miR-383, miR-424"], ["SNHG3", "miR-135A-1, miR-139, miR-182"], ["CDKN2B-AS1", "miR-10B"], ["LINC00152", "miR-376C"], ["CECR7", "miR-199A-1/2, miR-214"], ["DIO3OS", "miR-10B, miR-139, miR-199A-1/2, miR-214, miR-34C"], ["H19", "miR-93"], ["LINC00238", "miR-33B, miR-375"]], "row_count": 16, "column_count": 2, "numeric_cells": 20, "header_rows": 1, "locator": "section[10]/table-wrap[1]#pone.0141042.t003"}}, {"id": "asset:table:pmid:26492393:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:5609bef77b85e8006513772958f7dcebda860db19d4377260fe69b19253a69f9", "bytes": 1829, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#pone.0141042.t004", "version": null, "note": "Validation of miRNA targets.", "structure": {"pmcid": "PMC4619599", "section_index": 11, "section_title": "miRNA targets predicted by miRTarBase", "row_count": 18, "column_count": 2}, "table": {"label": "Table 4", "caption": "Validation of miRNA targets.", "rows": [["miRNA", "mRNAs targeted by miRNAs"], ["miR-10B", "PPARA, NF1, CDKN2A, HOXD10, KLF4, NCOR2, CDKN1A, TFAP2C, BCL2L11"], ["miR-135A-1", "JAK2, NR3C2, APC, MYC"], ["miR-139", "FOS"], ["miR-182", "CDKN1A, FOXO1, MITF, FOXO3, RARG, ADCY6, CLOCK, TSC22D3, CYLD, BCL2, CCND2, PDCD4, RECK, EP300, FGF9, NTM"], ["miR-183", "SRSF2, PDCD4, AKAP12, FOXO1, ITGB1, KIF2A, BTRC, EZR, IDH2"], ["miR-184", "AKT2, INPPL1, NFATC2"], ["miR-195", "WEE1, E2F3, CDK6, BCL2, CCND1, RUNX2, RAF1, CCL4, BCL2L11, MECP2, CCND3, TBCCD1, VEGFA, SKI, KRT7, SLC2A3, CAB39, BCL2L2"], ["miR-199A-1/2", "CD44, IKBKB, MET, HIF1A, SMARCA2, SMARCA2, MAPK1, DDR1, MAP3K11, FUT4, CAV2, EZH2, CCNL1, MAPK9, AKT1, MAPK8, MAPK14, LIF, JUNB, MED6, MECP2, ETS2, EDN1, TMEM54, SIRT1"], ["miR-214", "PTEN, MAP2K3, MAPK8, PLXNB1, EZH2, POU4F2, GALNT7, XBP1, DAPK1, SRGAP1, TWIST1, BCL2L2, ING4, FLOT1, MAP2K5, HSPD1, AHSA1, CPNE7, RASA1, YWHAQ, ARL2, AP3B1"], ["miR-33B", "BCL2, ABCA1"], ["miR-34C", "MET, CDK4, NOTCH1, BCL2, E2F3, MYB, CAV1, CCNE2, MYCN, NOTCH4, ULBP2, MYC, SRSF2, SOX2, NANOG"], ["miR-375", "ELAVL4, YWHAZ, TIMM8A, PDK1, YAP1, MTDH, RASD1, YY1AP1, RHOA, KCNQ2, MTPN, USP1, JAK2, C1QBP, PLAG1, BCL2L11, RAB10, PARP1, CAB39, DLG4, ITGB1, SETD8, CASP3, CDC42, EIF2AK2, BCL2, NCAM1, LEPROTL1"], ["miR-376C", "ACVR1C, IGF1R"], ["miR-383", "DIO1, IRF1, VEGFA"], ["miR-424", "HIF1A, CUL2, SPI1, PLAG1, CCNE1, CCND3, CDK6, CCND1, MAP2K1, WEE1, NFIA, LGALS3, MYB, SIAH1, CCNF, CDC14A, CDC25A, CHEK1, KIF23, ATF6, ANLN, FGFR1, PIAS1, ITPR1"], ["miR-93", "CDKN1A, E2F1, ITGB8, TUSC2, TP53INP1, KAT2B, PTEN, LATS2, MAPK9, VEGFA"], ["miR-96", "CDKN1A, KRAS, FOXO1, FOXO3, ADCY6, REV1, RAD51, MITF, HTR1B, PRMT5"]], "row_count": 18, "column_count": 2, "numeric_cells": 26, "header_rows": 1, "locator": "section[11]/table-wrap[1]#pone.0141042.t004"}}, {"id": "asset:table:pmid:26492393:5", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:28d168fcd752bbad079ce473bddfd753ca780dce429f52f5b2bef77fbc054513", "bytes": 900, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[12]/table-wrap[1]#pone.0141042.t005", "version": null, "note": "Top 15 KEEG pathways enriched by the coding genes involved in ceRNA network (P < 0.0001).The P value was corrected for multiple hypothesis testing using the Benjamini-Hochberg method (Please also refer to S3 Table)", "structure": {"pmcid": "PMC4619599", "section_index": 12, "section_title": "ceRNA network construction and KEEG pathway analysis", "row_count": 18, "column_count": 3}, "table": {"label": "Table 5", "caption": "Top 15 KEEG pathways enriched by the coding genes involved in ceRNA network (P < 0.0001).The P value was corrected for multiple hypothesis testing using the Benjamini-Hochberg method (Please also refer to S3 Table)", "rows": [["", "KEEG pathways", "No. of Genes"], ["Cancer related", "", ""], ["", "Pathways in cancer", "41"], ["Pancreatic cancer", "19"], ["Melanoma", "19"], ["Prostate cancer", "19"], ["Chronic myeloid leukemia", "16"], ["Colorectal cancer", "16"], ["Glioma", "15"], ["Small cell lung cancer", "15"], ["Bladder cancer", "13"], ["Non-small cell lung cancer", "13"], ["Non-cancer related", "", ""], ["", "MAPK signaling pathway", "22"], ["Focal adhesion", "21"], ["Cell cycle", "19"], ["Neurotrophin signaling pathway", "18"], ["T cell receptor signaling pathway", "14"]], "row_count": 18, "column_count": 3, "numeric_cells": 15, "header_rows": 1, "locator": "section[12]/table-wrap[1]#pone.0141042.t005"}}], "gaps": ["asset:data:geo:GSE65485 not downloaded", "asset:data:geo:GSE65485 licence not read"]}, "analysis": {"state": 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