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pmid:34222240

CBX4 Provides an Alternate Mode of Colon Cancer Development via Potential Influences on Circadian Rhythm and Immune Infiltration.

Wangzhi Wei · Wei Zhao · Yu Zhang

Frontiers in cell and developmental biology · 2021 doi:10.3389/fcell.2021.669254

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Experiment

complete

Data

partial

Analysis

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pmid:34222240
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title
CBX4 Provides an Alternate Mode of Colon Cancer Development via Potential Influences on Circadian Rhythm and Immune Infiltration.
doi
10.3389/fcell.2021.669254
pmid
34222240
authors array · 3 items
[0]
Wangzhi Wei
[1]
Wei Zhao
[2]
Yu Zhang
journal
Frontiers in cell and developmental biology
year
2021
abstract
The circadian machinery is critical for the normal physiological functions and cellular processes. Circadian rhythm disruption has been associated with immune suppression which leads to higher cancer risk, suggesting a putative tumor protective role of circadian clock homeostasis. CBX4, as an epigenetic regulator, has been explored for its involvement in tumorigenesis. However, little is known about the correlation between CBX4 and circadian rhythm disruption in colon cancer as well as the potential impact on the tumor immunity. A significant upregulation of CBX4 was identified in the TCGA colon adenocarcinoma (COAD) samples when compared with the normal controls (p < 0.001). This differential expression was confirmed at the protein level using colon adenocarcinoma tissue array (p < 0.01). CBX4 was up-regulated in the recurred/progressed colon cancer cases compared with the disease-free samples (p < 0.01), suggesting CBX4 as a potential predictor for poor prognosis. With regard to nodular metastasis, CBX4 was found to be associated with early onset of metastatic diseases but not late progression. The circadian rhythm is orchestrated by the alternating activation and suppression of the CLOCK/ARNTL-driven positive loop and the PER/CRY-controlled negative loop. In COAD, CBX4 was negatively correlated with CLOCK (p < 0.001), and positively correlated with PER1 (p < 0.001), PER3 (p < 0.01), and CRY2 (p < 0.001) as well as NR1D1 (p < 0.001), a critical negative regulator of the circadian clock. These interactions consistently impacted on patient survival based on the colorectal cancer cohorts GSE17536 and GSE14333 of PrognoScan. CBX4 showed significant negative correlations with infiltrating B cells (p < 0.05) and CD4+ T cells (p < 0.01), and positive correlations with myeloid derived suppressor cells (MDSCs) (p < 0.05) and cancer associated fibroblast (CAFs) (p < 0.001), as well as a low immunoscore. Moreover, CBX4 displayed significant correlations with diverse immune metagenes. PER1 and PER3, consistent with their coordinated expression with CBX4, also had strong correlations with these gene representatives in COAD, suggesting a potential interaction of CBX4 with the circadian machinery. Our studies implicate that CBX4 may contribute to colon cancer development via potential influence on circadian rhythm and immune infiltration. These findings provide new insights into deciphering the function of CBX4, and may contribute to the development of new targeting strategies.
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For each optimal cutpoint, patients are dichotomized and survival difference between high and low expression groups is calculated by log-rank test.
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sections[7] "PrognoScan Survival Analysis" paragraph 2
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For each optimal cutpoint, patients are dichotomized and survival difference between high and low expression groups is calculated by log-rank test.
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The datasets presented in this study are available in online repositories. These data were derived from the following publicly available resources: 1.TIMER: https://cistrome.shinyapps.io/timer/,2.UALCAN: Ualcan.path.uab.edu/analysis3.STRING: https://string-db.org/cgi/input?sessionId=bnvX D8cMolD6&input_page_active_form=multiple_identifiers4.cBioportal: https://www.cbioportal.org/5.GEPIA: http://gepia.cancer-pku.cn6.PrognoScan: http://dna00.bio.kyutech.ac.jp/PrognoScan/7.ESTIMATE: http:// bioinformatics.mdanderson.org/estimate/.
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sections[18] "Data Availability Statement" paragraphs 1-3
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The datasets presented in this study are available in online repositories. These data were derived from the following publicly available resources: 1.TIMER: https://cistrome.shinyapps.io/timer/,2.UALCAN: Ualcan.path.uab.edu/analysis3.STRING: https://string-db.org/cgi/input?sessionId=bnvX D8cMolD6&input_page_active_form=multiple_identifiers4.cBioportal: https://www.cbioportal.org/5.GEPIA: http://gepia.cancer-pku.cn6.PrognoScan: http://dna00.bio.kyutech.ac.jp/PrognoScan/7.ESTIMATE: http:// bioinformatics.mdanderson.org/estimate/.
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[147]
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[150]
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[176]
GSM437269
sample_count
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null
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null
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570
taxon
Homo sapiens
title
Metastasis Gene Expression Profile Predicts Recurrence and Death in Colon Cancer Patients (Moffitt Samples)
resolution_checked_at
2026-11-01T15:39:54Z
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identifier_resolution_only_no_download_no_licence_read
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Correlations between CBX4 and gene representatives of various functional cell subsets in COAD determined by TIMER2.0.
structure object · 5 fields
pmcid
PMC8253160
section_index
10
section_title
Statistical Analyses
row_count
31
column_count
4
table object · 8 fields
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TABLE 1
caption
Correlations between CBX4 and gene representatives of various functional cell subsets in COAD determined by TIMER2.0.
rows array · 31 items
[0] array · 2 items
[0]
[1]
Colon adenocarcinoma (COAD)
[1] array · 2 items
[0]
[1]
[2] array · 3 items
[0]
Cell type
[1]
Gene marker
[2]
CBX4 Correlation (TIMER 2.0)
[3] array · 1 item
[0]
[4] array · 4 items
[0]
[1]
[2]
Purity-adjusted partial
[3]
P Value
[5] array · 4 items
[0]
[1]
[2]
spearman’s rho value
[3]
[6] array · 4 items
[0]
T cell exhaustion
[1]
PD-1(PDCD1)
[2]
0.152
[3]
**
[7] array · 4 items
[0]
[1]
CTLA4
[2]
0.093
[3]
0.062
[8] array · 4 items
[0]
[1]
LAG3
[2]
0.138
[3]
**
[9] array · 4 items
[0]
[1]
TIM-3 (HAVCR2)
[2]
0.066
[3]
0.182
[10] array · 4 items
[0]
Regulatory T cells
[1]
FOXP3
[2]
0.127
[3]
*
[11] array · 4 items
[0]
[1]
TGFβ (TGFB1)
[2]
0.225
[3]
***
[12] array · 4 items
[0]
[1]
L1CAM
[2]
0.469
[3]
***
[13] array · 4 items
[0]
[1]
PTGIR
[2]
0.238
[3]
***
[14] array · 4 items
[0]
[1]
ITGA4
[2]
0.016
[3]
0.743
[15] array · 4 items
[0]
Th1 cells
[1]
T-bet (TBX21)
[2]
0.119
[3]
*
[16] array · 4 items
[0]
[1]
STAT1
[2]
0.197
[3]
***
[17] array · 4 items
[0]
[1]
STAT4
[2]
0.02
[3]
0.687
[18] array · 4 items
[0]
[1]
IFN-γ (IFNG)
[2]
0.076
[3]
0.126
[19] array · 4 items
[0]
Th2 cells
[1]
GATA3
[2]
0.197
[3]
***
[20] array · 4 items
[0]
[1]
STAT6
[2]
0.253
[3]
***
[21] array · 4 items
[0]
Th17 cells
[1]
IL-6R
[2]
0.203
[3]
***
[22] array · 4 items
[0]
[1]
STAT3
[2]
0.221
[3]
***
[23] array · 4 items
[0]
[1]
RORγt (RORC)
[2]
-0.035
[3]
0.479
[24] array · 4 items
[0]
[1]
IL-17A
[2]
-0.071
[3]
0.154
[25] array · 4 items
[0]
Macrophage
[1]
CD68
[2]
0.174
[3]
***
[26] array · 4 items
[0]
MDSC
[1]
CD11b (ITGAM)
[2]
0.139
[3]
**
[27] array · 4 items
[0]
[1]
IL-4R
[2]
0.286
[3]
***
[28] array · 4 items
[0]
[1]
CD33
[2]
−0.006
[3]
0.902
[29] array · 4 items
[0]
[1]
CD14
[2]
0.126
[3]
*
[30] array · 4 items
[0]
[1]
S100A9
[2]
−0.007
[3]
0.881
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section[10]/table-wrap[1]#T1
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section[10]/table-wrap[2]#T3
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Correlations between PER1, PER3, and gene representatives of various functional cell subsets in COAD determined by TIMER2.0.
structure object · 5 fields
pmcid
PMC8253160
section_index
10
section_title
Statistical Analyses
row_count
30
column_count
6
table object · 8 fields
label
TABLE 3
caption
Correlations between PER1, PER3, and gene representatives of various functional cell subsets in COAD determined by TIMER2.0.
rows array · 30 items
[0] array · 2 items
[0]
[1]
Colon Adenocarcinoma (COAD)
[1] array · 2 items
[0]
[1]
[2] array · 4 items
[0]
Cell type
[1]
Gene marker
[2]
PER1
[3]
PER3
[3] array · 4 items
[0]
[1]
[2]
[3]
[4] array · 6 items
[0]
[1]
[2]
spearman’s rho
[3]
P Value
[4]
spearman’s rho
[5]
P Value
[5] array · 6 items
[0]
T cell exhaustion
[1]
PD-1(PDCD1)
[2]
0.272
[3]
***
[4]
0.246
[5]
***
[6] array · 6 items
[0]
[1]
CTLA4
[2]
0.305
[3]
***
[4]
0.259
[5]
***
[7] array · 6 items
[0]
[1]
LAG3
[2]
0.309
[3]
***
[4]
0.257
[5]
***
[8] array · 6 items
[0]
[1]
TIM-3 (HAVCR2)
[2]
0.258
[3]
***
[4]
0.255
[5]
***
[9] array · 6 items
[0]
Regulatory T cells
[1]
FOXP3
[2]
0.269
[3]
***
[4]
0.286
[5]
***
[10] array · 6 items
[0]
[1]
TGFβ (TGFB1)
[2]
0.34
[3]
***
[4]
0.231
[5]
***
[11] array · 6 items
[0]
[1]
L1CAM
[2]
0.189
[3]
***
[4]
0.147
[5]
**
[12] array · 6 items
[0]
[1]
PTGIR
[2]
0.315
[3]
***
[4]
0.214
[5]
***
[13] array · 6 items
[0]
[1]
ITGA4
[2]
0.205
[3]
***
[4]
0.342
[5]
***
[14] array · 6 items
[0]
Th1 cells
[1]
T-bet (TBX21)
[2]
0.303
[3]
***
[4]
0.287
[5]
***
[15] array · 6 items
[0]
[1]
STAT1
[2]
0.308
[3]
***
[4]
0.351
[5]
***
[16] array · 6 items
[0]
[1]
STAT4
[2]
0.224
[3]
***
[4]
0.305
[5]
***
[17] array · 6 items
[0]
[1]
IFN-γ (IFNG)
[2]
0.122
[3]
*
[4]
0.209
[5]
***
[18] array · 6 items
[0]
Th2 cells
[1]
GATA3
[2]
0.245
[3]
***
[4]
0.282
[5]
***
[19] array · 6 items
[0]
[1]
STAT6
[2]
0.195
[3]
***
[4]
0.229
[5]
***
[20] array · 6 items
[0]
Th17 cells
[1]
IL-6R
[2]
0.209
[3]
***
[4]
0.395
[5]
***
[21] array · 6 items
[0]
[1]
STAT3
[2]
0.282
[3]
***
[4]
0.406
[5]
***
[22] array · 6 items
[0]
[1]
RORγt (RORC)
[2]
−0.087
[3]
0.08
[4]
0.145
[5]
**
[23] array · 6 items
[0]
[1]
IL-17A
[2]
−0.231
[3]
***
[4]
−0.072
[5]
0.15
[24] array · 6 items
[0]
Macrophage
[1]
CD68
[2]
0.254
[3]
***
[4]
0.277
[5]
***
[25] array · 6 items
[0]
MDSC
[1]
CD11b (ITGAM)
[2]
0.232
[3]
***
[4]
0.244
[5]
***
[26] array · 6 items
[0]
[1]
IL-4R
[2]
0.413
[3]
***
[4]
0.354
[5]
***
[27] array · 6 items
[0]
[1]
CD33
[2]
0.146
[3]
**
[4]
0.223
[5]
***
[28] array · 6 items
[0]
[1]
CD14
[2]
0.239
[3]
***
[4]
0.228
[5]
***
[29] array · 6 items
[0]
[1]
S100A9
[2]
0.01
[3]
0.834
[4]
−0.031
[5]
0.539
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section[10]/table-wrap[2]#T3
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Correlations between CBX4 and gene representatives of various functional cell subsets in COAD determined by GEPIA.
structure object · 5 fields
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PMC8253160
section_index
15
section_title
CBX4 Impacts Immunophenotype in Colon Cancer
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20
column_count
9
table object · 8 fields
label
TABLE 2
caption
Correlations between CBX4 and gene representatives of various functional cell subsets in COAD determined by GEPIA.
rows array · 20 items
[0] array · 2 items
[0]
Immune markers
[1]
CBX4 Correlation (GEPIA)
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[0]
[1]
[2] array · 3 items
[0]
[1]
COAD Tumor
[2]
COAD Normal
[3] array · 3 items
[0]
[1]
[2]
[4] array · 9 items
[0]
[1]
Spearman’s
[2]
p value
[3]
Pearson’s
[4]
p value
[5]
Spearman’s
[6]
p value
[7]
Pearson’s
[8]
p value
[5] array · 9 items
[0]
PD-1(PDCD1)
[1]
0.17
[2]
**
[3]
0.17
[4]
**
[5]
0.28
[6]
0.079
[7]
0.38
[8]
0.015
[6] array · 9 items
[0]
LAG3
[1]
0.15
[2]
*
[3]
0.21
[4]
***
[5]
0.15
[6]
0.34
[7]
0.19
[8]
0.24
[7] array · 9 items
[0]
FOXP3
[1]
0.12
[2]
*
[3]
0.12
[4]
*
[5]
0.2
[6]
0.21
[7]
0.27
[8]
0.089
[8] array · 9 items
[0]
TGFβ (TGFB1)
[1]
0.27
[2]
***
[3]
0.33
[4]
***
[5]
0.65
[6]
***
[7]
0.71
[8]
***
[9] array · 9 items
[0]
L1CAM
[1]
0.44
[2]
***
[3]
0.32
[4]
***
[5]
0.15
[6]
0.37
[7]
0.24
[8]
0.14
[10] array · 9 items
[0]
PTGIR
[1]
0.25
[2]
***
[3]
0.14
[4]
*
[5]
0.16
[6]
0.32
[7]
0.25
[8]
0.11
[11] array · 9 items
[0]
T-bet (TBX21)
[1]
0.15
[2]
*
[3]
0.15
[4]
*
[5]
0.16
[6]
0.32
[7]
0.2
[8]
0.2
[12] array · 9 items
[0]
STAT1
[1]
0.24
[2]
***
[3]
0.3
[4]
***
[5]
0.096
[6]
0.55
[7]
−0.09
[8]
0.58
[13] array · 9 items
[0]
GATA3
[1]
0.19
[2]
**
[3]
0.15
[4]
*
[5]
0.36
[6]
*
[7]
0.41
[8]
**
[14] array · 9 items
[0]
STAT6
[1]
0.23
[2]
***
[3]
0.19
[4]
**
[5]
0.42
[6]
**
[7]
0.44
[8]
**
[15] array · 9 items
[0]
IL-6R
[1]
0.22
[2]
***
[3]
0.13
[4]
*
[5]
−0.22
[6]
0.18
[7]
−0.16
[8]
0.33
[16] array · 9 items
[0]
STAT3
[1]
0.27
[2]
***
[3]
0.25
[4]
***
[5]
0.37
[6]
*
[7]
0.25
[8]
0.11
[17] array · 9 items
[0]
CD68
[1]
0.18
[2]
**
[3]
0.22
[4]
***
[5]
0.097
[6]
0.55
[7]
0.068
[8]
0.67
[18] array · 9 items
[0]
CD11b (ITGAM)
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0.2
[2]
***
[3]
0.13
[4]
*
[5]
0.51
[6]
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[7]
0.4
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[0]
IL-4R
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0.27
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0.21
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0.2
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0.2
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0.064
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section[15]/table-wrap[1]#T2
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[0]
asset:data:geo:GSE14333 not downloaded
[1]
asset:data:geo:GSE14333 licence not read
[2]
asset:data:geo:GSE17536 not downloaded
[3]
asset:data:geo:GSE17536 licence not read
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complete
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[0] object · 10 fields
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method-1
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survival_analysis
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[0]
logrank_test
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[0]
time_to_event_with_censoring
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1
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verbatim
quote
For each optimal cutpoint, patients are dichotomized and survival difference between high and low expression groups is calculated by log-rank test.
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gaps array · 0 items
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complete
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[0] object · 6 fields
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capability:computational_analysis
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[0]
meta_analysis
[1]
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[8]
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Automated Assays Laravel application and simulated adapters
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readiness object · 8 fields
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method object · 5 fields
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[0]
logrank_test
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The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: log_rank_test.
capability object · 4 fields
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capability:computational_analysis
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The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here.
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[0]
GSE17536
[1]
GSE14333
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[0]
GSE17536
[1]
GSE14333
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[0]
The datasets presented in this study are available in online repositories. These data were derived from the following publicly available resources: 1.TIMER: https://cistrome.shinyapps.io/timer/,2.UALCAN: Ualcan.path.uab.edu/analysis3.STRING: https://string-db.org/cgi/input?sessionId=bnvX D8cMolD6&input_page_active_form=multiple_identifiers4.cBioportal: https://www.cbioportal.org/5.GEPIA: http://gepia.cancer-pku.cn6.PrognoScan: http://dna00.bio.kyutech.ac.jp/PrognoScan/7.ESTIMATE: http:// bioinformatics.mdanderson.org/estimate/.
basis
The paper names GSE17536, GSE14333 in PrognoScan and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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[0]
logrank_test
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source:pmid:34222240
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[4]
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[0]
run_analysis
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[0]
data:geo:GSE14333
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extraction_review
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MiniMax-M3.1-Flash
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minimax
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minimax
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2026-10-31T18:32:08Z
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single_reader
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verbatim
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45208
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For each optimal cutpoint, patients are dichotomized and survival difference between high and low expression groups is calculated by log-rank test.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:34222240", "kind": "science-record", "revision": 6, "content_hash": "sha256:94a29da3d6dbd65691a91143721ae529d9e3157a4e7016edf4ef79b4a5b88ebe", "created_at": "2026-11-01T15:41:42Z", "updated_at": "2026-11-01T21:25:41Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "CBX4 Provides an Alternate Mode of Colon Cancer Development via Potential Influences on Circadian Rhythm and Immune Infiltration.", "doi": "10.3389/fcell.2021.669254", "pmid": "34222240", "authors": ["Wangzhi Wei", "Wei Zhao", "Yu Zhang"], "journal": "Frontiers in cell and developmental biology", "year": 2021, "abstract": "The circadian machinery is critical for the normal physiological functions and cellular processes. Circadian rhythm disruption has been associated with immune suppression which leads to higher cancer risk, suggesting a putative tumor protective role of circadian clock homeostasis. CBX4, as an epigenetic regulator, has been explored for its involvement in tumorigenesis. However, little is known about the correlation between CBX4 and circadian rhythm disruption in colon cancer as well as the potential impact on the tumor immunity. A significant upregulation of CBX4 was identified in the TCGA colon adenocarcinoma (COAD) samples when compared with the normal controls (p < 0.001). This differential expression was confirmed at the protein level using colon adenocarcinoma tissue array (p < 0.01). CBX4 was up-regulated in the recurred/progressed colon cancer cases compared with the disease-free samples (p < 0.01), suggesting CBX4 as a potential predictor for poor prognosis. With regard to nodular metastasis, CBX4 was found to be associated with early onset of metastatic diseases but not late progression. The circadian rhythm is orchestrated by the alternating activation and suppression of the CLOCK/ARNTL-driven positive loop and the PER/CRY-controlled negative loop. In COAD, CBX4 was negatively correlated with CLOCK (p < 0.001), and positively correlated with PER1 (p < 0.001), PER3 (p < 0.01), and CRY2 (p < 0.001) as well as NR1D1 (p < 0.001), a critical negative regulator of the circadian clock. These interactions consistently impacted on patient survival based on the colorectal cancer cohorts GSE17536 and GSE14333 of PrognoScan. CBX4 showed significant negative correlations with infiltrating B cells (p < 0.05) and CD4+ T cells (p < 0.01), and positive correlations with myeloid derived suppressor cells (MDSCs) (p < 0.05) and cancer associated fibroblast (CAFs) (p < 0.001), as well as a low immunoscore. Moreover, CBX4 displayed significant correlations with diverse immune metagenes. PER1 and PER3, consistent with their coordinated expression with CBX4, also had strong correlations with these gene representatives in COAD, suggesting a potential interaction of CBX4 with the circadian machinery. Our studies implicate that CBX4 may contribute to colon cancer development via potential influence on circadian rhythm and immune infiltration. These findings provide new insights into deciphering the function of CBX4, and may contribute to the development of new targeting strategies.", "claims": [{"id": "claim-method", "statement": "For each optimal cutpoint, patients are dichotomized and survival difference between high and low expression groups is calculated by log-rank test.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34222240", "locator": "sections[7] \"PrognoScan Survival Analysis\" paragraph 2", "quote": "For each optimal cutpoint, patients are dichotomized and survival difference between high and low expression groups is calculated by log-rank test."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The datasets presented in this study are available in online repositories. These data were derived from the following publicly available resources:\n1.TIMER: https://cistrome.shinyapps.io/timer/,2.UALCAN: Ualcan.path.uab.edu/analysis3.STRING: https://string-db.org/cgi/input?sessionId=bnvX D8cMolD6&input_page_active_form=multiple_identifiers4.cBioportal: https://www.cbioportal.org/5.GEPIA: http://gepia.cancer-pku.cn6.PrognoScan: http://dna00.bio.kyutech.ac.jp/PrognoScan/7.ESTIMATE: http:// bioinformatics.mdanderson.org/estimate/.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:34222240", "locator": "sections[18] \"Data Availability Statement\" paragraphs 1-3", "quote": "The datasets presented in this study are available in online repositories. These data were derived from the following publicly available resources:\n1.TIMER: https://cistrome.shinyapps.io/timer/,2.UALCAN: Ualcan.path.uab.edu/analysis3.STRING: https://string-db.org/cgi/input?sessionId=bnvX D8cMolD6&input_page_active_form=multiple_identifiers4.cBioportal: https://www.cbioportal.org/5.GEPIA: http://gepia.cancer-pku.cn6.PrognoScan: http://dna00.bio.kyutech.ac.jp/PrognoScan/7.ESTIMATE: http:// bioinformatics.mdanderson.org/estimate/."}], "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:34222240"], "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:GSE14333"], "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:GSE14333"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:34222240", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fcell.2021.669254", "sha256": "sha256:e2401c46a7a75c65cd1940d70aea2784d36a7f81ff4ed2524a471b29e6725b01", "bytes": 57324, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fcell.2021.669254", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC8253160", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE14333", "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=GSE14333", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE14333", "version": null, "note": "The datasets presented in this study are available in online repositories. 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