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pmid:35223987

CGN Correlates With the Prognosis and Tumor Immune Microenvironment in Clear Cell Renal Cell Carcinoma.

Zijian Tian · Lingfeng Meng · Xin Wang · Tongxiang Diao · Maolin Hu · Miao Wang · Yaqun Zhang · Ming Liu · Jianye Wang

Frontiers in molecular biosciences · 2022 doi:10.3389/fmolb.2022.758974

Paper

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Experiment

complete

Data

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Analysis

partial

Execution

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title
CGN Correlates With the Prognosis and Tumor Immune Microenvironment in Clear Cell Renal Cell Carcinoma.
doi
10.3389/fmolb.2022.758974
pmid
35223987
authors array · 9 items
[0]
Zijian Tian
[1]
Lingfeng Meng
[2]
Xin Wang
[3]
Tongxiang Diao
[4]
Maolin Hu
[5]
Miao Wang
[6]
Yaqun Zhang
[7]
Ming Liu
[8]
Jianye Wang
journal
Frontiers in molecular biosciences
year
2022
abstract
This study aimed to screen and verify the important prognostic genes related to clear cell renal cell carcinoma (ccRCC) and further analyze their relationship with the immune microenvironment. Gene expression profiles from the TCGA-KIRC, GSE46699, GSE36895, and GSE16449 datasets were utilized to explore differentially co-expressed genes in ccRCC. We screened 124 differentially co-expressed genes using a weighted gene co-expression network and differential gene expression analyses. Univariate and multivariate Cox survival analyses revealed that the expressions of genes CGN, FECH, UCHL1, and WT1 were independently related to the overall survival of ccRCC patients. Kaplan-Meier survival analysis was performed, and CGN was found to have the strongest correlation with the prognosis of ccRCC patients and was consequently selected for further analyses and experimental verification. The results showed that NK cell activation, resting dendritic cells, resting monocytes, and resting mast cells were positively correlated with CGN expression; CD4+ memory activated T cells, regulatory T cells, and M0 macrophages were negatively correlated with CGN expression. Finally, using western blotting and reverse transcription polymerase chain reaction, we verified that the CGN protein level was down-regulated in ccRCC samples, which was consistent with the mRNA levels. CGN was thus identified as diagnosis and prognosis biomarker for ccRCC and is related to the immune microenvironment.
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Weighted gene co-expression network analysis (WGCNA) is a systems biology method that delineates gene association patterns between different samples and can be used to identify highly coordinated gene sets.
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Weighted gene co-expression network analysis (WGCNA) is a systems biology method that delineates gene association patterns between different samples and can be used to identify highly coordinated gene sets.
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CGN was thus identified as diagnosis and prognosis biomarker for ccRCC and is related to the immune microenvironment.
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CGN was thus identified as diagnosis and prognosis biomarker for ccRCC and is related to the immune microenvironment.
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CGN was thus identified as diagnosis and prognosis biomarker for ccRCC and is related to the immune microenvironment.
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Molecular Stratification of Clear Cell Renal Cell Carcinoma Reveals Distinct Subtypes and Survival Patterns
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GSM342
[243]
GSM343
[244]
GSM344
[245]
GSM345
[246]
GSM346
[247]
GSM347
[248]
GSM348
[249]
GSM349
[250]
GSM350
[251]
GSM351
[252]
GSM352
[253]
GSM353
[254]
GSM354
[255]
GSM355
[256]
GSM356
[257]
GSM357
[258]
GSM358
[259]
GSM359
[260]
GSM360
[261]
GSM361
[262]
GSM362
[263]
GSM363
[264]
GSM364
[265]
GSM365
[266]
GSM366
[267]
GSM367
[268]
GSM368
[269]
GSM369
[270]
GSM370
[271]
GSM371
[272]
GSM372
[273]
GSM373
[274]
GSM374
[275]
GSM375
[276]
GSM376
[277]
GSM377
[278]
GSM378
[279]
GSM379
[280]
GSM380
[281]
GSM381
[282]
GSM382
[283]
GSM383
[284]
GSM384
[285]
GSM385
[286]
GSM386
[287]
GSM387
[288]
GSM388
[289]
GSM389
[290]
GSM390
[291]
GSM391
[292]
GSM392
[293]
GSM393
[294]
GSM394
[295]
GSM395
[296]
GSM396
[297]
GSM397
[298]
GSM398
[299]
GSM399
[300]
GSM400
[301]
GSM401
[302]
GSM402
[303]
GSM403
[304]
GSM404
[305]
GSM405
[306]
GSM406
[307]
GSM407
[308]
GSM408
[309]
GSM409
[310]
GSM410
[311]
GSM411
[312]
GSM412
[313]
GSM413
[314]
GSM414
[315]
GSM415
[316]
GSM416
[317]
GSM417
[318]
GSM418
[319]
GSM419
[320]
GSM420
[321]
GSM421
[322]
GSM422
[323]
GSM81
[324]
GSM82
[325]
GSM83
[326]
GSM84
[327]
GSM85
[328]
GSM86
[329]
GSM87
[330]
GSM88
[331]
GSM89
[332]
GSM90
[333]
GSM91
[334]
GSM92
[335]
GSM93
[336]
GSM94
[337]
GSM95
[338]
GSM96
[339]
GSM97
[340]
GSM98
[341]
GSM99
sample_count
342
group_sizes
null
group_sizes_basis
null
platform
10;9
taxon
Homo sapiens
title
Renal Cell Carcinoma Differential Expression
resolution_checked_at
2026-11-01T18:06:43Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[5] object · 15 fields
id
data:geo:GSE36895
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=GSE36895
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE36895
version
null
note
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
access_statement_kind
data_availability_statement
sample_accessions array · 76 items
[0]
GSM904985
[1]
GSM904986
[2]
GSM904988
[3]
GSM904989
[4]
GSM904990
[5]
GSM904991
[6]
GSM904992
[7]
GSM904994
[8]
GSM904995
[9]
GSM904996
[10]
GSM904998
[11]
GSM904999
[12]
GSM905000
[13]
GSM905002
[14]
GSM905003
[15]
GSM905004
[16]
GSM905006
[17]
GSM905007
[18]
GSM905008
[19]
GSM905009
[20]
GSM905011
[21]
GSM905012
[22]
GSM905013
[23]
GSM905014
[24]
GSM905016
[25]
GSM905017
[26]
GSM905018
[27]
GSM905020
[28]
GSM905021
[29]
GSM905022
[30]
GSM905023
[31]
GSM905024
[32]
GSM905025
[33]
GSM905026
[34]
GSM905027
[35]
GSM905028
[36]
GSM905029
[37]
GSM905030
[38]
GSM905031
[39]
GSM905032
[40]
GSM905033
[41]
GSM905034
[42]
GSM905035
[43]
GSM905036
[44]
GSM905037
[45]
GSM905038
[46]
GSM905039
[47]
GSM905040
[48]
GSM905041
[49]
GSM905042
[50]
GSM905043
[51]
GSM905044
[52]
GSM905045
[53]
GSM905046
[54]
GSM905047
[55]
GSM905048
[56]
GSM905049
[57]
GSM905050
[58]
GSM905051
[59]
GSM905052
[60]
GSM905053
[61]
GSM905054
[62]
GSM905055
[63]
GSM905056
[64]
GSM905057
[65]
GSM905058
[66]
GSM905059
[67]
GSM905060
[68]
GSM905061
[69]
GSM905062
[70]
GSM905063
[71]
GSM905064
[72]
GSM905065
[73]
GSM905066
[74]
GSM905067
[75]
GSM905068
sample_count
76
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Molecular Genetic Classification of clear-cell Renal Cell Carcinoma (ccRCC) based on the Gene Expression Profiling of Tumors and Tumorgrafts deficient for BAP1 or PBRM1
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
[6] object · 15 fields
id
data:geo:GSE46699
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=GSE46699
sha256
null
bytes
null
access
open
state
resolved
reader
null
reader_status
reader_required
identifier
GSE46699
version
null
note
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
access_statement_kind
data_availability_statement
sample_accessions array · 130 items
[0]
GSM1134764
[1]
GSM1134765
[2]
GSM1134766
[3]
GSM1134767
[4]
GSM1134768
[5]
GSM1134769
[6]
GSM1134770
[7]
GSM1134771
[8]
GSM1134772
[9]
GSM1134773
[10]
GSM1134774
[11]
GSM1134775
[12]
GSM1134776
[13]
GSM1134777
[14]
GSM1134778
[15]
GSM1134779
[16]
GSM1134780
[17]
GSM1134781
[18]
GSM1134782
[19]
GSM1134783
[20]
GSM1134784
[21]
GSM1134785
[22]
GSM1134786
[23]
GSM1134787
[24]
GSM1134788
[25]
GSM1134789
[26]
GSM1134790
[27]
GSM1134791
[28]
GSM1134792
[29]
GSM1134793
[30]
GSM1134794
[31]
GSM1134795
[32]
GSM1134796
[33]
GSM1134797
[34]
GSM1134798
[35]
GSM1134799
[36]
GSM1134800
[37]
GSM1134801
[38]
GSM1134802
[39]
GSM1134803
[40]
GSM1134804
[41]
GSM1134805
[42]
GSM1134806
[43]
GSM1134807
[44]
GSM1134808
[45]
GSM1134809
[46]
GSM1134810
[47]
GSM1134811
[48]
GSM1134812
[49]
GSM1134813
[50]
GSM1134814
[51]
GSM1134815
[52]
GSM1134816
[53]
GSM1134817
[54]
GSM1134818
[55]
GSM1134819
[56]
GSM1134820
[57]
GSM1134821
[58]
GSM1134822
[59]
GSM1134823
[60]
GSM1134824
[61]
GSM1134825
[62]
GSM1134826
[63]
GSM1134827
[64]
GSM1134828
[65]
GSM1134829
[66]
GSM1134830
[67]
GSM1134831
[68]
GSM1134832
[69]
GSM1134833
[70]
GSM1134834
[71]
GSM1134835
[72]
GSM1134836
[73]
GSM1134837
[74]
GSM1134838
[75]
GSM1134839
[76]
GSM1134840
[77]
GSM1134841
[78]
GSM1134842
[79]
GSM1134843
[80]
GSM1134844
[81]
GSM1134845
[82]
GSM1134846
[83]
GSM1134847
[84]
GSM1134848
[85]
GSM1134849
[86]
GSM1134850
[87]
GSM1134851
[88]
GSM1134852
[89]
GSM1134853
[90]
GSM1134854
[91]
GSM1134855
[92]
GSM1134856
[93]
GSM1134857
[94]
GSM1134858
[95]
GSM1134859
[96]
GSM1134860
[97]
GSM1134861
[98]
GSM1134862
[99]
GSM1134863
[100]
GSM1134864
[101]
GSM1134865
[102]
GSM1134866
[103]
GSM1134867
[104]
GSM1134868
[105]
GSM1134869
[106]
GSM1134870
[107]
GSM1134871
[108]
GSM1134872
[109]
GSM1134873
[110]
GSM1134874
[111]
GSM1134875
[112]
GSM1134876
[113]
GSM1134877
[114]
GSM1134878
[115]
GSM1134879
[116]
GSM1134880
[117]
GSM1134881
[118]
GSM1134882
[119]
GSM1134883
[120]
GSM1134884
[121]
GSM1134885
[122]
GSM1134886
[123]
GSM1134887
[124]
GSM1134888
[125]
GSM1134889
[126]
GSM1304420
[127]
GSM1304421
[128]
GSM1304422
[129]
GSM1304423
sample_count
130
group_sizes
null
group_sizes_basis
null
platform
570
taxon
Homo sapiens
title
Smoking and Obesity Related Molecular Alterations in Clear Cell Renal Cell Carcinoma
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
false
gaps array · 12 items
[0]
asset:data:geo:GSE16449 not downloaded
[1]
asset:data:geo:GSE16449 licence not read
[2]
asset:data:geo:GSE22541 not downloaded
[3]
asset:data:geo:GSE22541 licence not read
[4]
asset:data:geo:GSE29609 not downloaded
[5]
asset:data:geo:GSE29609 licence not read
[6]
asset:data:geo:GSE3 not downloaded
[7]
asset:data:geo:GSE3 licence not read
[8]
asset:data:geo:GSE36895 not downloaded
[9]
asset:data:geo:GSE36895 licence not read
[10]
asset:data:geo:GSE46699 not downloaded
[11]
asset:data:geo:GSE46699 licence not read
analysis object · 4 fields
state
partial
methods array · 4 items
[0] object · 10 fields
id
method-1
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
0.7
band
medium
quote
Kaplan-Meier
[1] object · 10 fields
id
method-2
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
0.8
band
high
quote
Cox regression
[2] object · 10 fields
id
method-3
family
correlation_analysis
specific
pearson
label
Correlation analysis
dsl_operations array · 1 item
[0]
pearson_r
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
paired_numeric_columns
evidence object · 3 fields
score
0.8
band
high
quote
Pearson correlation
[3] object · 10 fields
id
method-4
family
null
specific
null
label
Weighted gene co-expression network analysis (WGCNA)
dsl_operations array · 0 items
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 0 items
evidence object · 3 fields
score
1
band
verbatim
quote
Weighted gene co-expression network analysis (WGCNA) is a systems biology method that delineates gene association patterns between different samples and can be used to identify highly coordinated gene sets.
targets array · 0 items
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
[0]
survival_km
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: kaplan_meier.
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 · 6 items
[0]
GSE46699
[1]
GSE36895
[2]
GSE16449
[3]
GSE3
[4]
GSE22541
[5]
GSE29609
resolved_accessions array · 6 items
[0]
GSE46699
[1]
GSE36895
[2]
GSE16449
[3]
GSE3
[4]
GSE22541
[5]
GSE29609
statements array · 1 item
[0]
The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number(s) can be found in the article/Supplementary Material.
basis
The paper names GSE46699, GSE36895, GSE16449, GSE3, GSE22541, GSE29609 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]
survival_km
assets array · 2 items
[0]
source:pmid:35223987
[1]
data:geo:GSE16449
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:GSE16449
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
2026-11-01T17:36:09Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
5
usage object · 3 fields
prompt_tokens
9801
completion_tokens
2255
cached_tokens
128
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
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:35223987
type
paper
label
pmid:35223987
[1] object · 3 fields
id
source:pmid:35223987
type
manuscript
label
PMID 35223987 full text
[2] object · 3 fields
id
data:geo:GSE16449
type
dataset
label
GEO GSE16449
activities array · 3 items
[0] object · 4 fields
id
activity-reading-sci-2026-11-01
type
classification
used array · 3 items
[0] object · 3 fields
id
pmid:35223987
type
paper
label
pmid:35223987
[1] object · 3 fields
id
source:pmid:35223987
type
manuscript
label
PMID 35223987 full text
[2] object · 3 fields
id
data:geo:GSE16449
type
dataset
label
GEO GSE16449
agent
agent:corpus-assay-engine
[1] object · 4 fields
id
activity-read-35223987
type
extraction
used array · 1 item
[0]
source:pmid:35223987
agent
agent:minimax-reader
[2] object · 4 fields
id
activity-resolve-GSE16449
type
accession_resolution
used array · 1 item
[0]
data:geo:GSE16449
agent
agent:corpus-assay-engine
agents array · 2 items
[0] object · 3 fields
id
agent:corpus-assay-engine
type
software
label
Corpus assay engine
[1] object · 3 fields
id
agent:minimax-reader
type
software
label
MiniMax literature reader
source_run_id
reading-sci-2026-11-01
dsl_catalogue_fingerprint
343fb30756ba6ec3
capability_table_fingerprint
2cb3e42f047d2ecf
snapshot_id
ba34b49490d9bfaf
lineage object · 4 fields
parent_id
pmid:35223987
parent_hash
sha256:0c0d18b558ba1bf6e654098a6346a13dc03306a8fdd44576f57d56ebafe5ef0b
fork_of
null
gaps array · 17 items
[0]
asset:data:geo:GSE16449 licence not read
[1]
asset:data:geo:GSE16449 not downloaded
[2]
asset:data:geo:GSE22541 licence not read
[3]
asset:data:geo:GSE22541 not downloaded
[4]
asset:data:geo:GSE29609 licence not read
[5]
asset:data:geo:GSE29609 not downloaded
[6]
asset:data:geo:GSE3 licence not read
[7]
asset:data:geo:GSE3 not downloaded
[8]
asset:data:geo:GSE36895 licence not read
[9]
asset:data:geo:GSE36895 not downloaded
[10]
asset:data:geo:GSE46699 licence not read
[11]
asset:data:geo:GSE46699 not downloaded
[12]
execution.not_run
[13]
method.reader_named_unmapped
[14]
review.human_critique
[15]
review.independent_reader
[16]
review.machine_critique
assays array · 5 items
[0] object · 11 fields
role
data_generation
definition_id
western_blot
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.99
evidence array · 3 items
[0]
rrelated with CGN expression. Finally, using western blotting and reverse transcription polymerase chain r
[1]
ption polymerase chain reaction (RT-PCR) and western blotting (WB) were performed on the fresh ccRCC sampl
[2]
sues. (D) Expressed CGN protein confirmed by western blot analysis in normal and tumor tissues. Supple
order_basis
paper_text_order:1239
id
assay:1
[1] object · 11 fields
role
data_generation
definition_id
rna_seq
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.93
evidence array · 1 item
[0]
Methods Data and Sample Collection RNA sequencing data of 72 normal renal samples and 539 ccRC
order_basis
paper_text_order:1591
id
assay:2
[2] object · 11 fields
role
data_generation
definition_id
microarray
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.93
evidence array · 1 item
[0]
) database (https://cancerg enome.nih.gov/). Microarray data sets (GSE46699 (63 normal renal and 67
order_basis
paper_text_order:1802
id
assay:3
[3] object · 11 fields
role
data_generation
definition_version
99e1195c7d6f
required_operations array · 0 items
support_state
partial
source_hashes object · 1 field
assay_lexicon
99e1195c7d6f
confidence
0.93
evidence array · 1 item
[0]
ormal tissues (p < 0.001; Figure 8D). (A, B) Immunohistochemistry of the CGN gene in normal and tumor tissues
order_basis
paper_text_order:7232
id
assay:4
[4] object · 11 fields
role
analysis
definition_id
survival_analysis
definition_version
f2132e96ae6c7a4e
required_operations array · 1 item
[0]
survival_km
support_state
supported
source_hashes object · 1 field
dsl_catalogue
f2132e96ae6c7a4e
evidence array · 1 item
[0]
Kaplan-Meier
order_basis
consumes_earlier_output
id
assay:5
Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:35223987", "kind": "science-record", "revision": 4, "content_hash": "sha256:c6a5dc4ed6ee9dc11814a1b223e14e6caca6085e85bea8158fd65604115ab642", "created_at": "2026-11-01T17:36:59Z", "updated_at": "2026-11-01T21:27:20Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "CGN Correlates With the Prognosis and Tumor Immune Microenvironment in Clear Cell Renal Cell Carcinoma.", "doi": "10.3389/fmolb.2022.758974", "pmid": "35223987", "authors": ["Zijian Tian", "Lingfeng Meng", "Xin Wang", "Tongxiang Diao", "Maolin Hu", "Miao Wang", "Yaqun Zhang", "Ming Liu", "Jianye Wang"], "journal": "Frontiers in molecular biosciences", "year": 2022, "abstract": "This study aimed to screen and verify the important prognostic genes related to clear cell renal cell carcinoma (ccRCC) and further analyze their relationship with the immune microenvironment. Gene expression profiles from the TCGA-KIRC, GSE46699, GSE36895, and GSE16449 datasets were utilized to explore differentially co-expressed genes in ccRCC. We screened 124 differentially co-expressed genes using a weighted gene co-expression network and differential gene expression analyses. Univariate and multivariate Cox survival analyses revealed that the expressions of genes CGN, FECH, UCHL1, and WT1 were independently related to the overall survival of ccRCC patients. Kaplan-Meier survival analysis was performed, and CGN was found to have the strongest correlation with the prognosis of ccRCC patients and was consequently selected for further analyses and experimental verification. The results showed that NK cell activation, resting dendritic cells, resting monocytes, and resting mast cells were positively correlated with CGN expression; CD4+ memory activated T cells, regulatory T cells, and M0 macrophages were negatively correlated with CGN expression. Finally, using western blotting and reverse transcription polymerase chain reaction, we verified that the CGN protein level was down-regulated in ccRCC samples, which was consistent with the mRNA levels. CGN was thus identified as diagnosis and prognosis biomarker for ccRCC and is related to the immune microenvironment.", "claims": [{"id": "claim-method", "statement": "Weighted gene co-expression network analysis (WGCNA) is a systems biology method that delineates gene association patterns between different samples and can be used to identify highly coordinated gene sets.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:35223987", "locator": "sections[1] \"Introduction\" paragraph 3", "quote": "Weighted gene co-expression network analysis (WGCNA) is a systems biology method that delineates gene association patterns between different samples and can be used to identify highly coordinated gene sets."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study can be found in online repositories. 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Finally, using western blotting and reverse transcription polymerase chain r", "ption polymerase chain reaction (RT-PCR) and western blotting (WB) were performed on the fresh ccRCC sampl", "sues. (D) Expressed CGN protein confirmed by western blot analysis in normal and tumor tissues. 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Microarray data sets (GSE46699 (63 normal renal and 67"], "order_basis": "paper_text_order:1802", "id": "assay:3"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["ormal tissues (p < 0.001; Figure 8D). (A, B) Immunohistochemistry of the CGN gene in normal and tumor tissues"], "order_basis": "paper_text_order:7232", "id": "assay:4"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["survival_km"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 0.7, "evidence": ["Kaplan-Meier"], "order_basis": "consumes_earlier_output", "id": "assay:5"}]}