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pmid:33614483

Identification and Validation of an Autophagy-Related lncRNA Signature for Patients With Breast Cancer.

Ruyue Zhang · Qingwen Zhu · Detao Yin · Zhe Yang · Jinxiu Guo · Jingmin Zhang · Yubing Zhou · Jane J Yu

Frontiers in oncology · 2020 doi:10.3389/fonc.2020.597569

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Experiment

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Data

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Analysis

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title
Identification and Validation of an Autophagy-Related lncRNA Signature for Patients With Breast Cancer.
doi
10.3389/fonc.2020.597569
pmid
33614483
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Ruyue Zhang
[1]
Qingwen Zhu
[2]
Detao Yin
[3]
Zhe Yang
[4]
Jinxiu Guo
[5]
Jingmin Zhang
[6]
Yubing Zhou
[7]
Jane J Yu
journal
Frontiers in oncology
year
2020
abstract
BACKGROUND: Autophagy is a "self-feeding" phenomenon of cells, which is crucial in mammalian development. Long non-coding RNA (lncRNA) is a new regulatory factor for cell autophagy, which can regulate the process of autophagy to affect tumor progression. However, poor attention has been paid to the roles of autophagy-related lncRNAs in breast cancer. OBJECTIVE: This study aimed to construct an autophagy-related lncRNA signature that can effectively predict the prognosis of breast cancer patients and explore the potential functions of these lncRNAs. METHODS: The RNA sequencing (RNA-Seq) data of breast cancer patients was collected from The Cancer Genome Atlas (TCGA) database and the GSE20685 database. Multivariate Cox analysis was implemented to produce an autophagy-related lncRNA signature in the TCGA cohort. The signature was then validated in the GSE20685 cohort. The receiver operator characteristic (ROC) curve was performed to evaluate the predictive ability of the signature. Gene set enrichment analysis (GSEA) was used to explore the potential functions based on the signature. Finally, the study developed a nomogram and internal verification based on the autophagy-related lncRNAs. RESULTS: A signature composed of 9 autophagy-related lncRNAs was determined as a prognostic model, and 1,109 breast cancer patients were divided into high-risk group and low-risk group based on median risk score of the signature. Further analysis demonstrated that the over survival (OS) of breast cancer patients in the high-risk group was poorer than that in the low-risk group based on the prognostic signature. The area under the curve (AUC) of ROC curve verified the sensitivity and specificity of this signature. Additionally, we confirmed the signature is an independent factor and found it may be correlated to the progression of breast cancer. GSEA showed gene sets were notably enriched in carcinogenic activation pathways and autophagy-related pathways. The qRT-PCR identified 5 lncRNAs with significantly differential expression in breast cancer cells based on the 9 lncRNAs of the prognostic model, and the results were consistent with the tissues. CONCLUSION: In summary, our signature has potential predictive value in the prognosis of breast cancer and these autophagy-related lncRNAs may play significant roles in the diagnosis and treatment of breast cancer.
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Stepwise multivariable cox proportional hazards regression analysis were carried out to identify the optimal prognostic lncRNAs among the 25 candidate lncRNAs.
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sections[12] "Identification of an Autophagy-Related lncRNA Signature in Breast Cancer" paragraph 2
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Stepwise multivariable cox proportional hazards regression analysis were carried out to identify the optimal prognostic lncRNAs among the 25 candidate lncRNAs.
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Publicly available datasets were analyzed in this study. This data can be found here: https://www.cancergenome.nih.gov/, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20685, http://www.autophagy.lu/.
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sections[19] "Data Availability Statement" paragraph 2
quote
Publicly available datasets were analyzed in this study. This data can be found here: https://www.cancergenome.nih.gov/, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20685, http://www.autophagy.lu/.
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Gene set enrichment analysis based on the signature of 9 autophagy-related lncRNAs.
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Gene set enrichment analysis based on the signature of 9 autophagy-related lncRNAs.
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tags=52%, list=17%, signal=63%
[14] array · 9 items
[0]
renal_cell_carcinoma
[1]
70.000
[2]
0.435
[3]
1.643
[4]
0.023
[5]
0.170
[6]
0.575
[7]
5850.000
[8]
tags=37%, list=11%, signal=41%
[15] array · 9 items
[0]
progesterone_mediated_oocyte_maturation
[1]
85.000
[2]
0.434
[3]
1.621
[4]
0.026
[5]
0.173
[6]
0.611
[7]
4505.000
[8]
tags=33%, list=8%, signal=36%
[16] array · 9 items
[0]
starch_and_sucrose_metabolism
[1]
52.000
[2]
0.468
[3]
1.568
[4]
0.028
[5]
0.202
[6]
0.684
[7]
9541.000
[8]
tags=44%, list=17%, signal=53%
[17] array · 9 items
[0]
protein_export
[1]
24.000
[2]
0.643
[3]
1.687
[4]
0.029
[5]
0.137
[6]
0.514
[7]
4379.000
[8]
tags=50%, list=8%, signal=54%
[18] array · 9 items
[0]
dorso_ventral_axis_formation
[1]
24.000
[2]
0.549
[3]
1.717
[4]
0.029
[5]
0.122
[6]
0.473
[7]
5696.000
[8]
tags=42%, list=10%, signal=46%
[19] array · 9 items
[0]
epithelial_cell_signaling_in_helicobacter_pylori_infection
[1]
68.000
[2]
0.416
[3]
1.538
[4]
0.035
[5]
0.209
[6]
0.728
[7]
3970.000
[8]
tags=29%, list=7%, signal=32%
[20] array · 9 items
[0]
arrhythmogenic_right_ventricular_cardiomyopathy_arvc
[1]
74.000
[2]
0.450
[3]
1.596
[4]
0.038
[5]
0.180
[6]
0.651
[7]
6112.000
[8]
tags=35%, list=11%, signal=39%
[21] array · 9 items
[0]
long_term_potentiation
[1]
70.000
[2]
0.387
[3]
1.557
[4]
0.040
[5]
0.197
[6]
0.697
[7]
6344.000
[8]
tags=31%, list=11%, signal=35%
[22] array · 9 items
[0]
ecm_receptor_interaction
[1]
84.000
[2]
0.536
[3]
1.726
[4]
0.040
[5]
0.122
[6]
0.454
[7]
4669.000
[8]
tags=36%, list=8%, signal=39%
[23] array · 9 items
[0]
focal_adhesion
[1]
199.000
[2]
0.433
[3]
1.610
[4]
0.046
[5]
0.175
[6]
0.628
[7]
6112.000
[8]
tags=36%, list=11%, signal=41%
[24] array · 9 items
[0]
prostate_cancer
[1]
89.000
[2]
0.405
[3]
1.534
[4]
0.046
[5]
0.206
[6]
0.730
[7]
4558.000
[8]
tags=33%, list=8%, signal=35%
[25] array · 9 items
[0]
amino_sugar_and_nucleotide_sugar_metabolism
[1]
43
[2]
0.476
[3]
1.568
[4]
0.047
[5]
0.194
[6]
0.684
[7]
5323
[8]
tags=37%, list=10%, signal=41%
locator
section[15]/table-wrap[1]#T6
[3] object · 16 fields
id
asset:table:pmid:33614483:2
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table
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jats-table
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application/vnd.jats.table+json
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null
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sha256:104c602cdff0537fe33aa99baaf309df25dde831b22c2466749f58f21464994b
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693
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read_table
reader_status
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section[8]/table-wrap[1]#T1
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note
Primer sequences for RT-PCR analysis.
structure object · 5 fields
pmcid
PMC7892971
section_index
8
section_title
LncRNAs Validation Using qRT-PCR
row_count
11
column_count
2
table object · 8 fields
label
Table 1
caption
Primer sequences for RT-PCR analysis.
rows array · 11 items
[0] array · 2 items
[0]
[1]
Primer sequences
[1] array · 2 items
[0]
USP30-AS1-F
[1]
5’-TGAAACCGTCTCCTCCGCTACC-3’
[2] array · 2 items
[0]
USP30-AS1-R
[1]
5’-TGTCCTGCGGTCTACGTTCCC-3’
[3] array · 2 items
[0]
TFAP2A-AS1-F
[1]
5’-CTTGACAGCTCCAGGGGTTA-3’
[4] array · 2 items
[0]
TFAP2A-AS1-R
[1]
5’-TCTAGACTTGCAGGCACACA-3’
[5] array · 2 items
[0]
MAPT-AS1-F
[1]
5’-AGATGCACCTGCAGCCC-3’
[6] array · 2 items
[0]
MAPT-AS1-R
[1]
5’-CCCGTCCTTGTTCTGACTCC-3’
[7] array · 2 items
[0]
LINC01087-F
[1]
5’-CCACCAACCTCACCCACTCAAAG-3’
[8] array · 2 items
[0]
LINC01087-R
[1]
5’-TCCTCACGCCTCTGCTCCATC-3’
[9] array · 2 items
[0]
GAPDH-F
[1]
5’-CAGGAGGCATTGCTGATGAT-3’
[10] array · 2 items
[0]
GAPDH-R
[1]
5’-GAAGGCTGGGGCTCATTT-3’
locator
section[8]/table-wrap[1]#T1
[4] object · 16 fields
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asset:table:pmid:33614483:3
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table
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jats-table
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application/vnd.jats.table+json
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sha256:44bcd7bfb1678b72c97033363503b59e01e92b4269452394351e4718f6c96e5e
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2727
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section[12]/table-wrap[1]#T2
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note
Correlation between autophagy genes and lncRNAs in breast cancer.
structure object · 5 fields
pmcid
PMC7892971
section_index
12
section_title
Identification of an Autophagy-Related lncRNA Signature in Breast Cancer
row_count
62
column_count
4
table object · 8 fields
label
Table 2
caption
Correlation between autophagy genes and lncRNAs in breast cancer.
rows array · 62 items
[0] array · 4 items
[0]
Autophagy genes
[1]
lncRNAs
[2]
Correlation
[3]
P value
[1] array · 4 items
[0]
ARSA
[1]
KMT2E-AS1
[2]
0.38
[3]
7.24E-40
[2] array · 4 items
[0]
ARSB
[1]
KMT2E-AS1
[2]
-0.33
[3]
2.06E-30
[3] array · 4 items
[0]
ATF6
[1]
KMT2E-AS1
[2]
-0.31
[3]
2.37E-26
[4] array · 4 items
[0]
ATG16L2
[1]
KMT2E-AS1
[2]
0.30
[3]
9.31E-25
[5] array · 4 items
[0]
ATG4B
[1]
KMT2E-AS1
[2]
0.50
[3]
2.12E-72
[6] array · 4 items
[0]
ATG4D
[1]
KMT2E-AS1
[2]
0.30
[3]
4.97E-25
[7] array · 4 items
[0]
BAX
[1]
KMT2E-AS1
[2]
0.46
[3]
2.74E-60
[8] array · 4 items
[0]
BNIP1
[1]
KMT2E-AS1
[2]
0.31
[3]
3.85E-26
[9] array · 4 items
[0]
CANX
[1]
KMT2E-AS1
[2]
-0.32
[3]
1.44E-27
[10] array · 4 items
[0]
CAPN10
[1]
KMT2E-AS1
[2]
0.51
[3]
2.75E-75
[11] array · 4 items
[0]
CLN3
[1]
KMT2E-AS1
[2]
0.35
[3]
5.52E-33
[12] array · 4 items
[0]
DDIT3
[1]
KMT2E-AS1
[2]
0.30
[3]
1.24E-24
[13] array · 4 items
[0]
HSPA8
[1]
KMT2E-AS1
[2]
-0.30
[3]
3.95E-25
[14] array · 4 items
[0]
ITGB1
[1]
KMT2E-AS1
[2]
-0.43
[3]
1.63E-51
[15] array · 4 items
[0]
MAP2K7
[1]
KMT2E-AS1
[2]
0.32
[3]
2.21E-27
[16] array · 4 items
[0]
MAPK1
[1]
KMT2E-AS1
[2]
-0.33
[3]
4.61E-29
[17] array · 4 items
[0]
MLST8
[1]
KMT2E-AS1
[2]
0.36
[3]
2.58E-35
[18] array · 4 items
[0]
NCKAP1
[1]
KMT2E-AS1
[2]
-0.40
[3]
1.48E-43
[19] array · 4 items
[0]
PELP1
[1]
KMT2E-AS1
[2]
0.37
[3]
2.15E-36
[20] array · 4 items
[0]
PEX14
[1]
KMT2E-AS1
[2]
0.35
[3]
8.71E-33
[21] array · 4 items
[0]
PIK3R4
[1]
KMT2E-AS1
[2]
-0.33
[3]
4.89E-30
[22] array · 4 items
[0]
RAB24
[1]
KMT2E-AS1
[2]
0.50
[3]
6.73E-72
[23] array · 4 items
[0]
RB1
[1]
KMT2E-AS1
[2]
-0.37
[3]
1.37E-37
[24] array · 4 items
[0]
SH3GLB1
[1]
KMT2E-AS1
[2]
-0.33
[3]
8.19E-29
[25] array · 4 items
[0]
STK11
[1]
KMT2E-AS1
[2]
0.38
[3]
6.93E-39
[26] array · 4 items
[0]
WDR45
[1]
KMT2E-AS1
[2]
0.42
[3]
6.34E-49
[27] array · 4 items
[0]
APOL1
[1]
USP30-AS1
[2]
0.65
[3]
2.41E-136
[28] array · 4 items
[0]
BAK1
[1]
USP30-AS1
[2]
0.36
[3]
3.89E-35
[29] array · 4 items
[0]
BAX
[1]
USP30-AS1
[2]
0.30
[3]
5.64E-25
[30] array · 4 items
[0]
CASP1
[1]
USP30-AS1
[2]
0.63
[3]
4.65E-122
[31] array · 4 items
[0]
CASP4
[1]
USP30-AS1
[2]
0.51
[3]
7.21E-74
[32] array · 4 items
[0]
CCR2
[1]
USP30-AS1
[2]
0.51
[3]
4.73E-74
[33] array · 4 items
[0]
CFLAR
[1]
USP30-AS1
[2]
0.37
[3]
2.25E-36
[34] array · 4 items
[0]
FAS
[1]
USP30-AS1
[2]
0.42
[3]
4.41E-48
[35] array · 4 items
[0]
IKBKE
[1]
USP30-AS1
[2]
0.44
[3]
7.15E-55
[36] array · 4 items
[0]
NLRC4
[1]
USP30-AS1
[2]
0.31
[3]
1.82E-26
[37] array · 4 items
[0]
PRKCQ
[1]
USP30-AS1
[2]
0.48
[3]
6.54E-66
[38] array · 4 items
[0]
RGS19
[1]
USP30-AS1
[2]
0.41
[3]
7.33E-46
[39] array · 4 items
[0]
EGFR
[1]
ST7-AS1
[2]
0.38
[3]
4.60E-39
[40] array · 4 items
[0]
ATF4
[1]
VPS9D1-AS1
[2]
0.33
[3]
8.33E-29
[41] array · 4 items
[0]
ATG12
[1]
VPS9D1-AS1
[2]
-0.33
[3]
1.00E-28
[42] array · 4 items
[0]
BID
[1]
VPS9D1-AS1
[2]
0.37
[3]
1.14E-37
[43] array · 4 items
[0]
BIRC5
[1]
VPS9D1-AS1
[2]
0.32
[3]
1.29E-28
[44] array · 4 items
[0]
CD46
[1]
VPS9D1-AS1
[2]
-0.33
[3]
5.24E-30
[45] array · 4 items
[0]
CDKN2A
[1]
VPS9D1-AS1
[2]
0.33
[3]
3.76E-30
[46] array · 4 items
[0]
GAPDH
[1]
VPS9D1-AS1
[2]
0.36
[3]
7.50E-36
[47] array · 4 items
[0]
MYC
[1]
VPS9D1-AS1
[2]
0.45
[3]
1.57E-56
[48] array · 4 items
[0]
RHEB
[1]
VPS9D1-AS1
[2]
0.32
[3]
1.27E-28
[49] array · 4 items
[0]
ZFYVE1
[1]
VPS9D1-AS1
[2]
-0.36
[3]
4.51E-35
[50] array · 4 items
[0]
ATG16L2
[1]
TFAP2A-AS1
[2]
0.34
[3]
4.47E-31
[51] array · 4 items
[0]
BIRC6
[1]
TFAP2A-AS1
[2]
0.36
[3]
2.32E-35
[52] array · 4 items
[0]
TSC1
[1]
TFAP2A-AS1
[2]
0.40
[3]
5.96E-45
[53] array · 4 items
[0]
WDFY3
[1]
TFAP2A-AS1
[2]
0.35
[3]
3.17E-34
[54] array · 4 items
[0]
KIF5B
[1]
OTUD6B-AS1
[2]
0.31
[3]
1.60E-26
[55] array · 4 items
[0]
MAPK1
[1]
OTUD6B-AS1
[2]
0.33
[3]
5.57E-30
[56] array · 4 items
[0]
RB1CC1
[1]
OTUD6B-AS1
[2]
0.59
[3]
1.86E-104
[57] array · 4 items
[0]
CAPN2
[1]
HOXB-AS1
[2]
0.32
[3]
1.41E-28
[58] array · 4 items
[0]
ATG2B
[1]
LINC01087
[2]
0.31
[3]
2.52E-25
[59] array · 4 items
[0]
BIRC6
[1]
LINC01087
[2]
0.34
[3]
4.44E-32
[60] array · 4 items
[0]
WDFY3
[1]
LINC01087
[2]
0.40
[3]
6.65E-44
[61] array · 4 items
[0]
STK11
[1]
MAPT-AS1
[2]
0.32
[3]
4.11E-27
locator
section[12]/table-wrap[1]#T2
[5] object · 16 fields
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asset:table:pmid:33614483:4
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table
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jats-table
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application/vnd.jats.table+json
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null
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sha256:8dbdf9d622e60c3ee5d2ab8cae03dd7fefbbda76f6977e3965836d480350bdef
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831
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section[12]/table-wrap[2]#T3
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null
note
The 9 autophagy-related lncRNAs significantly associated with OS in the training set.
structure object · 5 fields
pmcid
PMC7892971
section_index
12
section_title
Identification of an Autophagy-Related lncRNA Signature in Breast Cancer
row_count
10
column_count
6
table object · 8 fields
label
Table 3
caption
The 9 autophagy-related lncRNAs significantly associated with OS in the training set.
rows array · 10 items
[0] array · 6 items
[0]
LncRNAs
[1]
β
[2]
HR
[3]
Lower 95%CI
[4]
Upper 95%CI
[5]
P-value
[1] array · 6 items
[0]
KMT2E-AS1
[1]
0.2520
[2]
1.2866
[3]
0.9278
[4]
1.7840
[5]
0.1308
[2] array · 6 items
[0]
USP30-AS1
[1]
-0.4604
[2]
0.6310
[3]
0.4794
[4]
0.8305
[5]
0.0010
[3] array · 6 items
[0]
ST7-AS1
[1]
-0.5304
[2]
0.5884
[3]
0.3985
[4]
0.8687
[5]
0.0076
[4] array · 6 items
[0]
VPS9D1-AS1
[1]
-0.2505
[2]
0.7784
[3]
0.6457
[4]
0.9383
[5]
0.0086
[5] array · 6 items
[0]
TFAP2A-AS1
[1]
-0.5438
[2]
0.5805
[3]
0.3770
[4]
0.8940
[5]
0.0136
[6] array · 6 items
[0]
OTUD6B-AS1
[1]
0.2797
[2]
1.3227
[3]
0.9840
[4]
1.7779
[5]
0.0638
[7] array · 6 items
[0]
HOXB-AS1
[1]
-0.1847
[2]
0.8314
[3]
0.6605
[4]
1.0464
[5]
0.1157
[8] array · 6 items
[0]
LINC01087
[1]
-0.0873
[2]
0.9164
[3]
0.8188
[4]
1.0257
[5]
0.1290
[9] array · 6 items
[0]
MAPT-AS1
[1]
-0.4423
[2]
0.6426
[3]
0.4955
[4]
0.8334
[5]
0.0009
locator
section[12]/table-wrap[2]#T3
[6] object · 16 fields
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asset:table:pmid:33614483:5
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table
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jats-table
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application/vnd.jats.table+json
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null
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sha256:2b0cb4af9885c5c2af4b4214d7f78f3ab93857440a29864dee9f6ca83cc18147
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1331
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read_table
reader_status
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section[13]/table-wrap[1]#T4
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note
Predictive values of related clinical features and risk score in the training dataset and the testing dataset.
structure object · 5 fields
pmcid
PMC7892971
section_index
13
section_title
Validation of Prognostic Performance of the Autophagy-Related lncRNA Signature in Breast Cancer
row_count
16
column_count
7
table object · 8 fields
label
Table 4
caption
Predictive values of related clinical features and risk score in the training dataset and the testing dataset.
rows array · 16 items
[0] array · 3 items
[0]
Variables
[1]
Univariate analysis
[2]
Multivariate analysis
[1] array · 6 items
[0]
HR
[1]
95% CI
[2]
P-value
[3]
HR
[4]
95% CI
[5]
P-value
[2] array · 7 items
[0]
Training dataset
[1]
[2]
[3]
[4]
[5]
[6]
[3] array · 7 items
[0]
age
[1]
1.035
[2]
1.022–1.049
[3]
<0.001
[4]
1.035
[5]
1.020–1.050
[6]
<0.001
[4] array · 7 items
[0]
gender
[1]
0.830
[2]
0.116–5.943
[3]
0.853
[4]
0.645
[5]
0.089–4.672
[6]
0.664
[5] array · 7 items
[0]
stage
[1]
2.205
[2]
1.756–2.768
[3]
<0.001
[4]
1.461
[5]
0.880–2.427
[6]
0.143
[6] array · 7 items
[0]
T
[1]
1.461
[2]
1.196–1.785
[3]
<0.001
[4]
1.070
[5]
0.796–1.438
[6]
0.654
[7] array · 7 items
[0]
M
[1]
4.935
[2]
2.944–8.273
[3]
<0.001
[4]
1.908
[5]
0.843–4.318
[6]
0.121
[8] array · 7 items
[0]
N
[1]
1.620
[2]
1.364–1.923
[3]
<0.001
[4]
1.294
[5]
0.971–1.724
[6]
0.079
[9] array · 7 items
[0]
risk score
[1]
1.794
[2]
1.556–2.069
[3]
<0.001
[4]
1.787
[5]
1.525–2.093
[6]
<0.001
[10] array · 7 items
[0]
Testing dataset
[1]
[2]
[3]
[4]
[5]
[6]
[11] array · 7 items
[0]
age
[1]
0.992
[2]
0.971–1.014
[3]
0.483
[4]
0.996
[5]
0.974–1.018
[6]
0.697
[12] array · 7 items
[0]
T
[1]
1.863
[2]
1.440–2.412
[3]
<0.001
[4]
1.288
[5]
0.891–1.860
[6]
0.178
[13] array · 7 items
[0]
M
[1]
5.204
[2]
2.391–11.326
[3]
<0.001
[4]
1.202
[5]
0.421–3.436
[6]
0.731
[14] array · 7 items
[0]
N
[1]
1.757
[2]
1.448–2.134
[3]
<0.001
[4]
1.633
[5]
1.317–2.026
[6]
<0.001
[15] array · 7 items
[0]
risk score
[1]
1.215
[2]
1.105–1.336
[3]
<0.001
[4]
1.210
[5]
1.083–1.351
[6]
0.001
locator
section[13]/table-wrap[1]#T4
[7] object · 16 fields
id
asset:table:pmid:33614483:6
role
table
format
jats-table
media_type
application/vnd.jats.table+json
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null
sha256
sha256:5f6456fd338391d2f0168af8110422fa2241d614df4c0b857404eb702f8114ed
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863
access
open
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verified
reader
read_table
reader_status
available
identifier
section[14]/table-wrap[1]#T5
version
null
note
Clinical impact of risk score signature for the TCGA cohort.
structure object · 5 fields
pmcid
PMC7892971
section_index
14
section_title
Clinical Value of the Prognostic Signature in Patients With Breast Cancer
row_count
20
column_count
6
table object · 8 fields
label
Table 5
caption
Clinical impact of risk score signature for the TCGA cohort.
rows array · 20 items
[0] array · 3 items
[0]
Clinical Features
[1]
n
[2]
Risk Score
[1] array · 4 items
[0]
Mean
[1]
SD
[2]
t
[3]
P
[2] array · 6 items
[0]
Age
[1]
[2]
[3]
[4]
[5]
[3] array · 6 items
[0]
<=65 >65
[1]
665
[2]
1.270
[3]
0.857
[4]
-2.673
[5]
0.008
[4] array · 3 items
[0]
243
[1]
1.452
[2]
0.932
[5] array · 6 items
[0]
Gender
[1]
[2]
[3]
[4]
[5]
[6] array · 6 items
[0]
Female Male
[1]
897
[2]
1.319
[3]
0.882
[4]
0.314
[5]
0.700
[7] array · 3 items
[0]
11
[1]
1.238
[2]
0.853
[8] array · 6 items
[0]
Stage
[1]
[2]
[3]
[4]
[5]
[9] array · 6 items
[0]
I-II III-IV
[1]
691
[2]
1.277
[3]
0.862
[4]
-2.443
[5]
0.000
[10] array · 3 items
[0]
217
[1]
1.451
[2]
0.929
[11] array · 6 items
[0]
T
[1]
[2]
[3]
[4]
[5]
[12] array · 6 items
[0]
T1-2 T3-4
[1]
774
[2]
1.304
[3]
0.870
[4]
-1.169
[5]
0.161
[13] array · 3 items
[0]
134
[1]
1.405
[2]
0.938
[14] array · 6 items
[0]
M
[1]
[2]
[3]
[4]
[5]
[15] array · 6 items
[0]
M0 M1
[1]
891
[2]
1.310
[3]
0.881
[4]
-2.325
[5]
0.186
[16] array · 3 items
[0]
17
[1]
1.746
[2]
0.763
[17] array · 6 items
[0]
N
[1]
[2]
[3]
[4]
[5]
[18] array · 6 items
[0]
N0 N1-3
[1]
449
[2]
1.265
[3]
0.867
[4]
-1.799
[5]
0.013
[19] array · 3 items
[0]
459
[1]
1.370
[2]
0.892
locator
section[14]/table-wrap[1]#T5
[8] object · 16 fields
id
asset:table:pmid:33614483:7
role
table
format
jats-table
media_type
application/vnd.jats.table+json
uri
null
sha256
sha256:3a1fbcccf55cd87096d1e1c3e88b60d0529650f1bae24c530ea9a7b234205509
bytes
3421
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read_table
reader_status
available
identifier
section[15]/table-wrap[1]#T6
version
null
note
Gene set enrichment analysis based on the signature of 9 autophagy-related lncRNAs.
structure object · 5 fields
pmcid
PMC7892971
section_index
15
section_title
Gene Set Enrichment Analysis
row_count
26
column_count
9
table object · 8 fields
label
Table 6
caption
Gene set enrichment analysis based on the signature of 9 autophagy-related lncRNAs.
rows array · 26 items
[0] array · 9 items
[0]
Name
[1]
Size
[2]
ES
[3]
NES
[4]
NOM P-val
[5]
FDRq-val
[6]
FWERP-val
[7]
Rank at max
[8]
Leading edge
[1] array · 9 items
[0]
oocyte_meiosis
[1]
112.000
[2]
0.536
[3]
2.039
[4]
0.000
[5]
0.047
[6]
0.066
[7]
4649.000
[8]
tags=39%, list=8%, signal=43%
[2] array · 9 items
[0]
vibrio_cholerae_infection
[1]
54.000
[2]
0.570
[3]
1.956
[4]
0.002
[5]
0.087
[6]
0.150
[7]
8855.000
[8]
tags=52%, list=16%, signal=62%
[3] array · 9 items
[0]
gap_junction
[1]
90.000
[2]
0.449
[3]
1.760
[4]
0.002
[5]
0.138
[6]
0.414
[7]
6344.000
[8]
tags=39%, list=11%, signal=44%
[4] array · 9 items
[0]
citrate_cycle_tca_cycle
[1]
31.000
[2]
0.718
[3]
2.040
[4]
0.006
[5]
0.095
[6]
0.066
[7]
4597.000
[8]
tags=55%, list=8%, signal=60%
[5] array · 9 items
[0]
pathogenic_escherichia_coli_infection
[1]
56.000
[2]
0.546
[3]
1.789
[4]
0.006
[5]
0.217
[6]
0.363
[7]
6053.000
[8]
tags=43%, list=11%, signal=48%
[6] array · 9 items
[0]
o_glycan_biosynthesis
[1]
30.000
[2]
0.534
[3]
1.758
[4]
0.010
[5]
0.127
[6]
0.417
[7]
7284.000
[8]
tags=50%, list=13%, signal=58%
[7] array · 9 items
[0]
steroid_biosynthesis
[1]
17.000
[2]
0.700
[3]
1.776
[4]
0.011
[5]
0.151
[6]
0.384
[7]
2995.000
[8]
tags=53%, list=5%, signal=56%
[8] array · 9 items
[0]
tgf_beta_signaling_pathway
[1]
85.000
[2]
0.469
[3]
1.752
[4]
0.012
[5]
0.112
[6]
0.427
[7]
3973.000
[8]
tags=31%, list=7%, signal=33%
[9] array · 9 items
[0]
glycolysis_gluconeogenesis
[1]
62.000
[2]
0.488
[3]
1.771
[4]
0.013
[5]
0.140
[6]
0.396
[7]
5471.000
[8]
tags=34%, list=10%, signal=38%
[10] array · 9 items
[0]
terpenoid_backbone_biosynthesis
[1]
15.000
[2]
0.705
[3]
1.786
[4]
0.015
[5]
0.186
[6]
0.368
[7]
5030.000
[8]
tags=40%, list=9%, signal=44%
[11] array · 9 items
[0]
n_glycan_biosynthesis
[1]
46.000
[2]
0.548
[3]
1.783
[4]
0.016
[5]
0.163
[6]
0.371
[7]
4408.000
[8]
tags=39%, list=8%, signal=42%
[12] array · 9 items
[0]
regulation_of_actin_cytoskeleton
[1]
213.000
[2]
0.401
[3]
1.643
[4]
0.016
[5]
0.161
[6]
0.576
[7]
6127.000
[8]
tags=35%, list=11%, signal=39%
[13] array · 9 items
[0]
adherens_junction
[1]
73.000
[2]
0.497
[3]
1.836
[4]
0.017
[5]
0.192
[6]
0.291
[7]
9394.000
[8]
tags=52%, list=17%, signal=63%
[14] array · 9 items
[0]
renal_cell_carcinoma
[1]
70.000
[2]
0.435
[3]
1.643
[4]
0.023
[5]
0.170
[6]
0.575
[7]
5850.000
[8]
tags=37%, list=11%, signal=41%
[15] array · 9 items
[0]
progesterone_mediated_oocyte_maturation
[1]
85.000
[2]
0.434
[3]
1.621
[4]
0.026
[5]
0.173
[6]
0.611
[7]
4505.000
[8]
tags=33%, list=8%, signal=36%
[16] array · 9 items
[0]
starch_and_sucrose_metabolism
[1]
52.000
[2]
0.468
[3]
1.568
[4]
0.028
[5]
0.202
[6]
0.684
[7]
9541.000
[8]
tags=44%, list=17%, signal=53%
[17] array · 9 items
[0]
protein_export
[1]
24.000
[2]
0.643
[3]
1.687
[4]
0.029
[5]
0.137
[6]
0.514
[7]
4379.000
[8]
tags=50%, list=8%, signal=54%
[18] array · 9 items
[0]
dorso_ventral_axis_formation
[1]
24.000
[2]
0.549
[3]
1.717
[4]
0.029
[5]
0.122
[6]
0.473
[7]
5696.000
[8]
tags=42%, list=10%, signal=46%
[19] array · 9 items
[0]
epithelial_cell_signaling_in_helicobacter_pylori_infection
[1]
68.000
[2]
0.416
[3]
1.538
[4]
0.035
[5]
0.209
[6]
0.728
[7]
3970.000
[8]
tags=29%, list=7%, signal=32%
[20] array · 9 items
[0]
arrhythmogenic_right_ventricular_cardiomyopathy_arvc
[1]
74.000
[2]
0.450
[3]
1.596
[4]
0.038
[5]
0.180
[6]
0.651
[7]
6112.000
[8]
tags=35%, list=11%, signal=39%
[21] array · 9 items
[0]
long_term_potentiation
[1]
70.000
[2]
0.387
[3]
1.557
[4]
0.040
[5]
0.197
[6]
0.697
[7]
6344.000
[8]
tags=31%, list=11%, signal=35%
[22] array · 9 items
[0]
ecm_receptor_interaction
[1]
84.000
[2]
0.536
[3]
1.726
[4]
0.040
[5]
0.122
[6]
0.454
[7]
4669.000
[8]
tags=36%, list=8%, signal=39%
[23] array · 9 items
[0]
focal_adhesion
[1]
199.000
[2]
0.433
[3]
1.610
[4]
0.046
[5]
0.175
[6]
0.628
[7]
6112.000
[8]
tags=36%, list=11%, signal=41%
[24] array · 9 items
[0]
prostate_cancer
[1]
89.000
[2]
0.405
[3]
1.534
[4]
0.046
[5]
0.206
[6]
0.730
[7]
4558.000
[8]
tags=33%, list=8%, signal=35%
[25] array · 9 items
[0]
amino_sugar_and_nucleotide_sugar_metabolism
[1]
43
[2]
0.476
[3]
1.568
[4]
0.047
[5]
0.194
[6]
0.684
[7]
5323
[8]
tags=37%, list=10%, signal=41%
locator
section[15]/table-wrap[1]#T6
gaps array · 2 items
[0]
asset:data:geo:GSE20685 not downloaded
[1]
asset:data:geo:GSE20685 licence not read
analysis object · 4 fields
state
complete
methods array · 4 items
[0] object · 10 fields
id
method-1
family
survival_analysis
specific
cox_proportional_hazards
label
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
1
band
verbatim
quote
Stepwise multivariable cox proportional hazards regression analysis were carried out to identify the optimal prognostic lncRNAs among the 25 candidate lncRNAs.
[1] object · 10 fields
id
method-2
family
survival_analysis
specific
kaplan_meier
label
Survival analysis
dsl_operations array · 1 item
[0]
survival_km
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
band
high
quote
Kaplan Meier
[2] object · 10 fields
id
method-3
family
differential_expression
specific
limma_voom
label
Differential expression analysis
dsl_operations array · 3 items
[0]
normalise_counts
[1]
differential_expression_fit
[2]
fdr_bh
missing_operations array · 0 items
parameters object · 2 fields
fold_change
ncRNAs in view of |log2 fold change (FC)|≥1 and false disco
fdr_threshold
fold change (FC)|≥1 and false discovery rate (FDR)<0
data_shapes array · 1 item
[0]
count_matrix_with_condition
evidence object · 3 fields
score
0.8
band
high
quote
Limma
[3] object · 10 fields
id
method-4
family
diagnostic_evaluation
specific
roc
label
Diagnostic test evaluation
dsl_operations array · 6 items
[0]
confusion_counts
[1]
roc_curve
[2]
sensitivity_specificity
[3]
solve_confusion_matrix
[4]
classification_metrics
[5]
published_precision_envelope
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
reference_standard_and_test
evidence object · 3 fields
score
0.7
band
medium
quote
ROC curve
targets array · 0 items
gaps array · 0 items
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
[0]
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]
GSE20685
resolved_accessions array · 1 item
[0]
GSE20685
statements array · 1 item
[0]
Publicly available datasets were analyzed in this study. This data can be found here: https://www.cancergenome.nih.gov/, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20685, http://www.autophagy.lu/.
basis
The paper names GSE20685 in Gene Expression Omnibus (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 · 9 items
[0]
source:pmid:33614483
[1]
data:geo:GSE20685
[2]
asset:table:pmid:33614483:1
[3]
asset:table:pmid:33614483:2
[4]
asset:table:pmid:33614483:3
[5]
asset:table:pmid:33614483:4
[6]
asset:table:pmid:33614483:5
[7]
asset:table:pmid:33614483:6
[8]
asset:table:pmid:33614483:7
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:GSE20685
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
2026-10-31T18:27:12Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
3
usage object · 3 fields
prompt_tokens
23805
completion_tokens
1787
cached_tokens
784
stages array · 1 item
[0] object · 4 fields
id
extraction
state
complete
reader
MiniMax-M3.1-Flash
provider
minimax
gaps array · 3 items
[0]
review.independent_reader
[1]
review.machine_critique
[2]
review.human_critique
execution object · 5 fields
state
absent
status
not_run
mode
null
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gaps array · 1 item
[0]
execution.not_run
provenance object · 7 fields
entities array · 3 items
[0] object · 3 fields
id
pmid:33614483
type
paper
label
pmid:33614483
[1] object · 3 fields
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source:pmid:33614483
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manuscript
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PMID 33614483 full text
[2] object · 3 fields
id
data:geo:GSE20685
type
dataset
label
GEO GSE20685
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[0] object · 4 fields
id
activity-reading-sci-2026-11-01
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classification
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[0] object · 3 fields
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pmid:33614483
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paper
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pmid:33614483
[1] object · 3 fields
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source:pmid:33614483
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manuscript
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PMID 33614483 full text
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id
data:geo:GSE20685
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dataset
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GEO GSE20685
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agent:corpus-assay-engine
[1] object · 4 fields
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activity-read-33614483
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extraction
used array · 1 item
[0]
source:pmid:33614483
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE20685
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accession_resolution
used array · 1 item
[0]
data:geo:GSE20685
agent
agent:corpus-assay-engine
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[0] object · 3 fields
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agent:corpus-assay-engine
type
software
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Corpus assay engine
[1] object · 3 fields
id
agent:minimax-reader
type
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:33614483
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sha256:60336ff03af912536659c67a47677d0dc3a4f7dd9cdb25cc034f04a6ab03e32c
fork_of
null
gaps array · 6 items
[0]
asset:data:geo:GSE20685 licence not read
[1]
asset:data:geo:GSE20685 not downloaded
[2]
execution.not_run
[3]
review.human_critique
[4]
review.independent_reader
[5]
review.machine_critique
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[0] object · 11 fields
role
data_generation
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rna_seq
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99e1195c7d6f
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partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 2 items
[0]
these lncRNAs. METHODS: The RNA sequencing (RNA-Seq) data of breast cancer patients was collecte
[1]
ial functions of these lncRNAs. METHODS: The RNA sequencing (RNA-Seq) data of breast cancer patients was
order_basis
paper_text_order:627
id
assay:1
[1] object · 11 fields
role
data_generation
definition_id
cell_culture
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99e1195c7d6f
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support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.77
evidence array · 1 item
[0]
ast cells (HBL-100) and breast cancer cells (MCF-7 and T-47D) were purchased from the Cell Bank
order_basis
paper_text_order:2536
id
assay:2
[2] object · 11 fields
role
analysis
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survival_analysis
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f2132e96ae6c7a4e
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cox_ph
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supported
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dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
Stepwise multivariable cox proportional hazards regression analysis were carried out to identify the optimal prognostic lncRNAs among the 25 candidate lncRNAs.
order_basis
consumes_earlier_output
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assay:3
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33614483", "kind": "science-record", "revision": 7, "content_hash": "sha256:356fb138f2a285e8310ba64b4bd7c4dea700d98fb78b03b40f61259f0afa898a", "created_at": "2026-11-01T15:41:26Z", "updated_at": "2026-11-01T22:03:10Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of an Autophagy-Related lncRNA Signature for Patients With Breast Cancer.", "doi": "10.3389/fonc.2020.597569", "pmid": "33614483", "authors": ["Ruyue Zhang", "Qingwen Zhu", "Detao Yin", "Zhe Yang", "Jinxiu Guo", "Jingmin Zhang", "Yubing Zhou", "Jane J Yu"], "journal": "Frontiers in oncology", "year": 2020, "abstract": "BACKGROUND: Autophagy is a \"self-feeding\" phenomenon of cells, which is crucial in mammalian development. Long non-coding RNA (lncRNA) is a new regulatory factor for cell autophagy, which can regulate the process of autophagy to affect tumor progression. However, poor attention has been paid to the roles of autophagy-related lncRNAs in breast cancer.\nOBJECTIVE: This study aimed to construct an autophagy-related lncRNA signature that can effectively predict the prognosis of breast cancer patients and explore the potential functions of these lncRNAs.\nMETHODS: The RNA sequencing (RNA-Seq) data of breast cancer patients was collected from The Cancer Genome Atlas (TCGA) database and the GSE20685 database. Multivariate Cox analysis was implemented to produce an autophagy-related lncRNA signature in the TCGA cohort. The signature was then validated in the GSE20685 cohort. The receiver operator characteristic (ROC) curve was performed to evaluate the predictive ability of the signature. Gene set enrichment analysis (GSEA) was used to explore the potential functions based on the signature. Finally, the study developed a nomogram and internal verification based on the autophagy-related lncRNAs.\nRESULTS: A signature composed of 9 autophagy-related lncRNAs was determined as a prognostic model, and 1,109 breast cancer patients were divided into high-risk group and low-risk group based on median risk score of the signature. Further analysis demonstrated that the over survival (OS) of breast cancer patients in the high-risk group was poorer than that in the low-risk group based on the prognostic signature. The area under the curve (AUC) of ROC curve verified the sensitivity and specificity of this signature. Additionally, we confirmed the signature is an independent factor and found it may be correlated to the progression of breast cancer. GSEA showed gene sets were notably enriched in carcinogenic activation pathways and autophagy-related pathways. The qRT-PCR identified 5 lncRNAs with significantly differential expression in breast cancer cells based on the 9 lncRNAs of the prognostic model, and the results were consistent with the tissues.\nCONCLUSION: In summary, our signature has potential predictive value in the prognosis of breast cancer and these autophagy-related lncRNAs may play significant roles in the diagnosis and treatment of breast cancer.", "claims": [{"id": "claim-method", "statement": "Stepwise multivariable cox proportional hazards regression analysis were carried out to identify the optimal prognostic lncRNAs among the 25 candidate lncRNAs.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33614483", "locator": "sections[12] \"Identification of an Autophagy-Related lncRNA Signature in Breast Cancer\" paragraph 2", "quote": "Stepwise multivariable cox proportional hazards regression analysis were carried out to identify the optimal prognostic lncRNAs among the 25 candidate lncRNAs."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Publicly available datasets were analyzed in this study. This data can be found here: https://www.cancergenome.nih.gov/, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20685, http://www.autophagy.lu/.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33614483", "locator": "sections[19] \"Data Availability Statement\" paragraph 2", "quote": "Publicly available datasets were analyzed in this study. This data can be found here: https://www.cancergenome.nih.gov/, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20685, http://www.autophagy.lu/."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": null, "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:33614483"], "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. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE20685"], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE20685"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33614483", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fonc.2020.597569", "sha256": "sha256:9007b18b6c433cff0897cafff8e48d5162a51ba3892e163684eadb0724c55efc", "bytes": 32356, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fonc.2020.597569", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC7892971", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE20685", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20685", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE20685", "version": null, "note": "Publicly available datasets were analyzed in this study. 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"", ""], ["I-II III-IV", "691", "1.277", "0.862", "-2.443", "0.000"], ["217", "1.451", "0.929"], ["T", "", "", "", "", ""], ["T1-2 T3-4", "774", "1.304", "0.870", "-1.169", "0.161"], ["134", "1.405", "0.938"], ["M", "", "", "", "", ""], ["M0 M1", "891", "1.310", "0.881", "-2.325", "0.186"], ["17", "1.746", "0.763"], ["N", "", "", "", "", ""], ["N0 N1-3", "449", "1.265", "0.867", "-1.799", "0.013"], ["459", "1.370", "0.892"]], "row_count": 20, "column_count": 6, "numeric_cells": 51, "header_rows": 2, "locator": "section[14]/table-wrap[1]#T5"}}, {"id": "asset:table:pmid:33614483:7", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:3a1fbcccf55cd87096d1e1c3e88b60d0529650f1bae24c530ea9a7b234205509", "bytes": 3421, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[15]/table-wrap[1]#T6", "version": null, "note": "Gene set enrichment analysis based on the signature of 9 autophagy-related lncRNAs.", "structure": {"pmcid": "PMC7892971", "section_index": 15, "section_title": "Gene Set Enrichment Analysis", "row_count": 26, "column_count": 9}, "table": {"label": "Table 6", "caption": "Gene set enrichment analysis based on the signature of 9 autophagy-related lncRNAs.", "rows": [["Name", "Size", "ES", "NES", "NOM P-val", "FDRq-val", "FWERP-val", "Rank at max", "Leading edge"], ["oocyte_meiosis", "112.000", "0.536", "2.039", "0.000", "0.047", "0.066", "4649.000", "tags=39%, list=8%, signal=43%"], ["vibrio_cholerae_infection", "54.000", "0.570", "1.956", "0.002", "0.087", "0.150", "8855.000", "tags=52%, list=16%, signal=62%"], ["gap_junction", "90.000", "0.449", "1.760", "0.002", "0.138", "0.414", "6344.000", "tags=39%, list=11%, signal=44%"], ["citrate_cycle_tca_cycle", "31.000", "0.718", "2.040", "0.006", "0.095", "0.066", "4597.000", "tags=55%, list=8%, signal=60%"], ["pathogenic_escherichia_coli_infection", "56.000", "0.546", "1.789", 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The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R1", "reachable": true, "accessions": ["GSE20685"], "resolved_accessions": ["GSE20685"], "statements": ["Publicly available datasets were analyzed in this study. This data can be found here: https://www.cancergenome.nih.gov/, https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE20685, http://www.autophagy.lu/."], "basis": "The paper names GSE20685 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. 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