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pmid:33935718

Transcriptomic and microRNA Expression Profiles Identify Biomarkers for Predicting Neo-Chemoradiotherapy Response in Esophageal Squamous Cell Carcinomas (ESCC).

Jian Wang · Pengyi Yu · Judong Luo · Zhiqiang Sun · Jingping Yu · Jianlin Wang

Frontiers in pharmacology · 2021 doi:10.3389/fphar.2021.626972

Paper

complete

Experiment

complete

Data

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Analysis

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Execution

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:33935718
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title
Transcriptomic and microRNA Expression Profiles Identify Biomarkers for Predicting Neo-Chemoradiotherapy Response in Esophageal Squamous Cell Carcinomas (ESCC).
doi
10.3389/fphar.2021.626972
pmid
33935718
authors array · 6 items
[0]
Jian Wang
[1]
Pengyi Yu
[2]
Judong Luo
[3]
Zhiqiang Sun
[4]
Jingping Yu
[5]
Jianlin Wang
journal
Frontiers in pharmacology
year
2021
abstract
Neo-chemoradiotherapy (nCRT) before surgery is a standard treatment for locally advanced esophageal cancers. However, the treatment outcome of nCRT varied with different patients. This study aimed to identify potential biomarkers for prediction of nCRT-response in patients with esophageal squamous cell carcinoma (ESCC). Microarray datasets of nCRT responder and non-responder samples (access number GSE45670 and GSE59974) of patients with ESCC were downloaded from Gene Expression Omnibus (GEO) database. The mRNA expression profiles of cancer biopsies from four ESCC patients were analyzed before and after nCRT. Differentially expressed genes (DEGs) and miRNAs were screened between nCRT responder and non-responder ESCC samples. Functional enrichment analysis was conducted for these DEGs followed by construction of protein-protein interaction (PPI) network and miRNA-mRNA regulatory network. Finally, univariate survival analysis was performed to identify candidate biomarkers with prognostic values in ESCC. We identified numerous DEGs and differentially expressed miRNAs from nCRT responder group. GO and KEGG analysis showed that the dysregulated genes were mainly involved in biological processes and pathways, including "response to stimulus", "cellular response to organic substance", "regulation of signal transduction", "AGE-RAGE signaling pathway in diabetic complications", and "steroid hormone biosynthesis". After integration of PPI network and miRNA-mRNA network analysis, we found eight genes, TNF, AKR1C1, AKR1C2, ICAM1, GPR68, GNB4, SERPINE1 and MMP12, could be candidate genes associated with disease progression. Univariate cox regression analysis showed that there was no significant correlation between dysregulated miRNAs (such as hsa-miR-34b-3p, hsa-miR-127-5p, hsa-miR-144-3p, and hsa-miR-486-5p, et al.) and overall survival of ESCC patients. Moreover, abnormal expression of MMP12 was significantly correlated with pathological degree, TNM stage, lymph nodes metastasis, and overall survival of ESCC patients (p < 0.05). Taken together, our study identified that MMP12 might be a useful tumor biomarker and therapeutic target for ESCC.
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number can be found below: https://www.ncbi.nlm.nih.gov/,GSE137867.
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sections[16] "Data Availability Statement" paragraph 2
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number can be found below: https://www.ncbi.nlm.nih.gov/,GSE137867.
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Tissue samples of 4 patients with esophageal cancer before and after radiotherapy
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Expression data from esophageal squamous cell carcinomas and normal esophageal epithelia
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The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession number can be found below: https://www.ncbi.nlm.nih.gov/,GSE137867.
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MiRNA expression arrays from esophageal squamous cell carcinomas with different neoadjuvant chemoradiotherapy response
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2026-11-01T15:39:54Z
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Twenty five DEGs were identified from two mRNA profiles (GSE45670 dataset and GSE137867 dataset), including 17 upregulated genes and 8 down-regulated genes in the ESCC responder groups compared with control non-responder groups.
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Screening DEGs From nCRT Responders of ESCCs
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TABLE 1
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Twenty five DEGs were identified from two mRNA profiles (GSE45670 dataset and GSE137867 dataset), including 17 upregulated genes and 8 down-regulated genes in the ESCC responder groups compared with control non-responder groups.
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ANO4, BMP2, DTNB, GADD45A, GAS1, GNB4, GPR68, ICAM1, IL24, MAN1A1, MMP12, NRBF2, SERPINE1, SLC31A2, SNX10, TNF, TNNT1
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Fifety nine differential expressed miRNAs were identified from miRNA profiles (GSE59974 dataset), including 44 upregulated genes and 15 down-regulated genes in the ESCC responder groups compared with control groups.
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Screening DEGs From nCRT Responders of ESCCs
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TABLE 2
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Fifety nine differential expressed miRNAs were identified from miRNA profiles (GSE59974 dataset), including 44 upregulated genes and 15 down-regulated genes in the ESCC responder groups compared with control groups.
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Gene Ontology analysis of differentially expressed genes associated with ESCC (Top ten biological process terms).
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11
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GO and KEGG Analysis for These Candidate Genes
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Gene Ontology analysis of differentially expressed genes associated with ESCC (Top ten biological process terms).
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[0]
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[1]
Description
[2]
Count
[3]
p value
[4]
FDR
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[0]
BP
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[2]
6
[3]
2.80e−06
[4]
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[4]
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12
[3]
6.06e−06
[4]
0.001658521
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BP
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[3]
7.33e−06
[4]
0.001658521
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7.44e−06
[4]
0.001658521
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BP
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GO:0009966∼regulation_of_signal_transduction
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11
[3]
1.32e−05
[4]
0.002048231
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BP
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4
[3]
1.46e−05
[4]
0.002048231
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BP
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6
[3]
1.46−-05
[4]
0.002048231
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[4]
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KEGG pathway analysis of differentially expressed genes in ESCC.
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GO and KEGG Analysis for These Candidate Genes
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KEGG pathway analysis of differentially expressed genes in ESCC.
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KEGG
[1]
hsa04933∼AGE-RAGE_signaling_pathway_in_diabetic_complications Homo_sapiens_(human)
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3
[3]
5.23e−04
[4]
0.058021807
[5]
ICAM1/SERPINE1/TNF
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hsa05143∼African_trypanosomiasis Homo_sapiens_(human)
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2
[3]
1.63e−03
[4]
0.08638883
[5]
ICAM1/TNF
[3] array · 6 items
[0]
KEGG
[1]
hsa05144∼Malaria Homo_sapiens_(human)
[2]
2
[3]
2.85e−03
[4]
0.08638883
[5]
ICAM1/TNF
[4] array · 6 items
[0]
KEGG
[1]
hsa05169∼Epstein-Barr_virus_infection Homo_sapiens_(human)
[2]
3
[3]
3.91e−03
[4]
0.08638883
[5]
GADD45A/ICAM1/TNF
[5] array · 6 items
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KEGG
[1]
hsa00140∼Steroid_hormone_biosynthesis Homo_sapiens_(human)
[2]
2
[3]
4.24e−03
[4]
0.08638883
[5]
AKR1C1/AKR1C2
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2
[3]
4.67e−03
[4]
0.08638883
[5]
BMP2/GADD45A
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2
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6.06e−03
[4]
0.095935394
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GADD45A/SERPINE1
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2
[3]
9.54e−03
[4]
0.095935394
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ICAM1/TNF
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KEGG
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hsa04350∼TGF-beta_signaling_pathway Homo_sapiens_(human)
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2
[3]
0.01
[4]
0.095935394
[5]
BMP2/TNF
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hsa04713∼Circadian_entrainment Homo_sapiens_(human)
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2
[3]
0.01
[4]
0.095935394
[5]
GNB4/PER2
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Protein-protein interaction network analysis for differential expressed genes in ESCC samples based on connectivity degrees evaluation.
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PPI Network Analysis and Prediction of miRNA-Gene Interactions
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Protein-protein interaction network analysis for differential expressed genes in ESCC samples based on connectivity degrees evaluation.
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“Univariate cox regression analysis and survival analysis were performed to identify crucial genes and miRNAs related to ESCC survival based on the TCGA datasets.”
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h esophageal squamous cell carcinoma (ESCC). Microarray datasets of nCRT responder and non-responder
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. Data normalization was performed for these microarray data. We extracted the gene expression value
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However, the treatment outcome of nCRT varied with different patients. This study aimed to identify potential biomarkers for prediction of nCRT-response in patients with esophageal squamous cell carcinoma (ESCC). Microarray datasets of nCRT responder and non-responder samples (access number GSE45670 and GSE59974) of patients with ESCC were downloaded from Gene Expression Omnibus (GEO) database. The mRNA expression profiles of cancer biopsies from four ESCC patients were analyzed before and after nCRT. Differentially expressed genes (DEGs) and miRNAs were screened between nCRT responder and non-responder ESCC samples. Functional enrichment analysis was conducted for these DEGs followed by construction of protein-protein interaction (PPI) network and miRNA-mRNA regulatory network. Finally, univariate survival analysis was performed to identify candidate biomarkers with prognostic values in ESCC. We identified numerous DEGs and differentially expressed miRNAs from nCRT responder group. GO and KEGG analysis showed that the dysregulated genes were mainly involved in biological processes and pathways, including \"response to stimulus\", \"cellular response to organic substance\", \"regulation of signal transduction\", \"AGE-RAGE signaling pathway in diabetic complications\", and \"steroid hormone biosynthesis\". After integration of PPI network and miRNA-mRNA network analysis, we found eight genes, TNF, AKR1C1, AKR1C2, ICAM1, GPR68, GNB4, SERPINE1 and MMP12, could be candidate genes associated with disease progression. Univariate cox regression analysis showed that there was no significant correlation between dysregulated miRNAs (such as hsa-miR-34b-3p, hsa-miR-127-5p, hsa-miR-144-3p, and hsa-miR-486-5p, et al.) and overall survival of ESCC patients. Moreover, abnormal expression of MMP12 was significantly correlated with pathological degree, TNM stage, lymph nodes metastasis, and overall survival of ESCC patients (p < 0.05). 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down-regulated genes in the ESCC responder groups compared with control non-responder groups.", "rows": [["DEGs", "Gene names"], ["Up-regulated", "ANO4, BMP2, DTNB, GADD45A, GAS1, GNB4, GPR68, ICAM1, IL24, MAN1A1, MMP12, NRBF2, SERPINE1, SLC31A2, SNX10, TNF, TNNT1"], ["Down-regulated", "AKR1C1, AKR1C2, PCTP, PER2, RAB40B, TLE2, ZDHHC11, ZNF703"]], "row_count": 3, "column_count": 2, "numeric_cells": 2, "header_rows": 1, "locator": "section[10]/table-wrap[1]#T1"}}, {"id": "asset:table:pmid:33935718:2", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:5c86181d73c70acd71498ef13e00de5384c98f18a3714c0d4622314cb5c9e212", "bytes": 1348, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[10]/table-wrap[2]#T2", "version": null, "note": "Fifety nine differential expressed miRNAs were identified from miRNA profiles (GSE59974 dataset), including 44 upregulated genes and 15 down-regulated genes in the ESCC responder groups compared with control groups.", "structure": {"pmcid": "PMC8082678", "section_index": 10, "section_title": "Screening DEGs From nCRT Responders of ESCCs", "row_count": 3, "column_count": 2}, "table": {"label": "TABLE 2", "caption": "Fifety nine differential expressed miRNAs were identified from miRNA profiles (GSE59974 dataset), including 44 upregulated genes and 15 down-regulated genes in the ESCC responder groups compared with control groups.", "rows": [["miRNAs", "Gene names"], ["Up-regulated", "hsa-miR-106b-3p, hsa-miR-122-5p, hsa-miR-1252, hsa-miR-127-5p, hsa-miR-1295a, hsa-miR-1343, hsa-miR-137, hsa-miR-155-3p, hsa-miR-18a-3p, hsa-miR-195-3p, hsa-miR-196a-5p, hsa-miR-206, hsa-miR-222-5p, hsa-miR-299-3p, hsa-miR-3144-5p, hsa-miR-323b-5p, hsa-miR-330-3p, hsa-miR-34b-3p, hsa-miR-3617-5p, hsa-miR-363-5p, hsa-miR-373-3p, hsa-miR-3975, hsa-miR-3978, hsa-miR-424-5p, hsa-miR-4448, hsa-miR-4528, hsa-miR-4645-3p, hsa-miR-4670-5p, hsa-miR-4704-5p, hsa-miR-4709-3p, hsa-miR-4715-5p, hsa-miR-4717-5p, hsa-miR-4773, hsa-miR-4774-5p, hsa-miR-4789-5p, hsa-miR-4798-5p, hsa-miR-503-5p, hsa-miR-504, hsa-miR-5189, hsa-miR-539-3p, hsa-miR-5579-3p, hsa-miR-637, hsa-miR-7-5p, hsa-miR-924"], ["Down-regulated", "hsa-miR-138-1-3p, hsa-miR-144-3p, hsa-miR-144-5p, hsa-miR-192-3p, hsa-miR-3145-5p, hsa-miR-3972, hsa-miR-486-5p, hsa-miR-489, hsa-miR-499a-5p, hsa-miR-550b-2-5p, hsa-miR-551b-3p, hsa-miR-5585-5p, hsa-miR-5690, hsa-miR-640, hsa-miR-675-3p"]], "row_count": 3, "column_count": 2, "numeric_cells": 2, "header_rows": 1, "locator": "section[10]/table-wrap[2]#T2"}}, {"id": "asset:table:pmid:33935718:3", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:c15ee0835ecc8627718c6e8c2cf850f00f434c3882780c498290980344156829", "bytes": 1184, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[1]#T3", "version": null, "note": "Gene Ontology analysis of differentially expressed genes associated with ESCC (Top ten biological process terms).", "structure": {"pmcid": "PMC8082678", "section_index": 11, "section_title": "GO and KEGG Analysis for These Candidate Genes", "row_count": 11, "column_count": 5}, "table": {"label": "TABLE 3", "caption": "Gene Ontology analysis of differentially expressed genes associated with ESCC (Top ten biological process terms).", "rows": [["Category", "Description", "Count", "p value", "FDR"], ["BP", "GO:0071396∼cellular_response_to_lipid", "6", "2.80e−06", "0.001617666"], ["BP", "GO:0050896∼response_to_stimulus", "18", "2.84e−06", "0.001617666"], ["BP", "GO:0071395∼cellular_response_to_jasmonic_acid_stimulus", "2", "3.63e−06", "0.001617666"], ["BP", "GO:0023051∼regulation_of_signaling", "12", "6.06e−06", "0.001658521"], ["BP", "GO:0010033∼response_to_organic_substance", "11", "7.33e−06", "0.001658521"], ["BP", "GO:0071310∼cellular_response_to_organic_substance", "10", "7.44e−06", "0.001658521"], ["BP", "GO:0009966∼regulation_of_signal_transduction", "11", "1.32e−05", "0.002048231"], ["BP", "GO:0071222∼cellular_response_to_lipopolysaccharide", "4", "1.46e−05", "0.002048231"], ["BP", "GO:0030155∼regulation_of_cell_adhesion", "6", "1.46−-05", "0.002048231"], ["BP", "GO:2000351∼regulation_of_endothelial_cell_apoptotic_process", "3", "1.54e−05", "0.002048231"]], "row_count": 11, "column_count": 5, "numeric_cells": 40, "header_rows": 1, "locator": "section[11]/table-wrap[1]#T3"}}, {"id": "asset:table:pmid:33935718:4", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:404b99413d5c49e10984051479f524323e97e0524ae23f033762c5b2ad3d3162", "bytes": 1401, "access": "open", "state": "verified", "reader": "read_table", "reader_status": "available", "identifier": "section[11]/table-wrap[2]#T4", "version": null, "note": "KEGG pathway analysis of differentially expressed genes in ESCC.", "structure": {"pmcid": "PMC8082678", "section_index": 11, "section_title": "GO and KEGG Analysis for These Candidate Genes", "row_count": 11, "column_count": 6}, "table": {"label": "TABLE 4", "caption": "KEGG pathway analysis of differentially expressed genes in ESCC.", "rows": [["Category", "Description", "Count", "p value", "FDR", "Genes"], ["KEGG", "hsa04933∼AGE-RAGE_signaling_pathway_in_diabetic_complications Homo_sapiens_(human)", "3", "5.23e−04", "0.058021807", "ICAM1/SERPINE1/TNF"], ["KEGG", "hsa05143∼African_trypanosomiasis Homo_sapiens_(human)", "2", "1.63e−03", "0.08638883", "ICAM1/TNF"], ["KEGG", "hsa05144∼Malaria Homo_sapiens_(human)", "2", "2.85e−03", "0.08638883", "ICAM1/TNF"], ["KEGG", "hsa05169∼Epstein-Barr_virus_infection Homo_sapiens_(human)", "3", "3.91e−03", "0.08638883", "GADD45A/ICAM1/TNF"], ["KEGG", "hsa00140∼Steroid_hormone_biosynthesis Homo_sapiens_(human)", "2", "4.24e−03", "0.08638883", "AKR1C1/AKR1C2"], ["KEGG", "hsa05217∼Basal_cell_carcinoma Homo_sapiens_(human)", "2", "4.67e−03", "0.08638883", "BMP2/GADD45A"], ["KEGG", "hsa04115∼p53_signaling_pathway Homo_sapiens_(human)", "2", "6.06e−03", "0.095935394", "GADD45A/SERPINE1"], ["KEGG", "hsa05323∼Rheumatoid_arthritis Homo_sapiens_(human)", "2", "9.54e−03", "0.095935394", "ICAM1/TNF"], ["KEGG", "hsa04350∼TGF-beta_signaling_pathway Homo_sapiens_(human)", "2", "0.01", "0.095935394", "BMP2/TNF"], ["KEGG", "hsa04713∼Circadian_entrainment Homo_sapiens_(human)", "2", "0.01", "0.095935394", "GNB4/PER2"]], "row_count": 11, "column_count": 6, "numeric_cells": 43, "header_rows": 1, "locator": "section[11]/table-wrap[2]#T4"}}, {"id": "asset:table:pmid:33935718:5", "role": "table", "format": "jats-table", "media_type": "application/vnd.jats.table+json", "uri": null, "sha256": "sha256:2958abfdc62fc9f125a1ec3c3dfe93dd40677d83884cefd8d4df2840efa17c73", "bytes": 415, "access": "open", "state": "verified", "reader": "read_table", "reader_status": 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