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pmid:32284764

Down-regulated Solute Carrier Family 4 Member 4 Predicts Poor Progression in Colorectal Cancer.

Hong Yang · Yao Lu · Weilan Lan · Bin Huang · Jiumao Lin

Journal of Cancer · 2020 doi:10.7150/jca.36696

Paper

complete

Experiment

complete

Data

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Analysis

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pmid:32284764
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2026-11-01T15:40:59Z
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title
Down-regulated Solute Carrier Family 4 Member 4 Predicts Poor Progression in Colorectal Cancer.
doi
10.7150/jca.36696
pmid
32284764
authors array · 5 items
[0]
Hong Yang
[1]
Yao Lu
[2]
Weilan Lan
[3]
Bin Huang
[4]
Jiumao Lin
journal
Journal of Cancer
year
2020
abstract
Aim: To identify potential key candidate genes, whose expression and clinical significance was further assessed in colorectal cancer (CRC). Methods: Three original microarray datasets (GSE41328, GSE22598, and GSE23878) from NCBI-GEO were used to analyze differentially expressed genes (DEGs) in CRC. Online database analyses through Oncomine and GEIPA were performed to evaluate SLC4A4 expression and explore the prognostic merit of SLC4A4 expression, which was further confirmed by analyses from QPCR based cDNA array and IHC based tissue microarray (TMA). STRING website was used to explore the interaction between SLC4A4 with other DEGs based on the protein-protein interaction (PPI) networks. Results: Analysis of three original microarray datasets from GEO identified 82 shared, differentially expressed genes (28 upregulated and 54 down-regulated) in CRC tissues. Online analyses from Oncomine and GEIPA revealed lower SLC4A4 mRNA expression in CRC tissues compared to adjacent normal tissues, which were further confirmed by QPCR based cDNA array and IHC based TMA analyses on both mRNA and protein levels. Survival analyses through GEIPA and from TMA demonstrated that low SLC4A4 expression is correlated with worse overall survival among patients with CRC. Survival analysis from Kaplan-meier plotter demonstrated that low SLC4A4 expression is significantly associated with poor progression (including relapse-free survival, overall survival, distant metastasis-free survival, post-progression survival) of patients with breast cancer, lung cancer, gastric cancer, and ovarian cancer. PPI analysis found that SLC4A4 is highly correlated with various genes, including SLC9A3, SLC26A6, ENSG00000214921, SLC26A4, SLC9A3R1, and SLC9A1. Conclusion: The mRNA and protein levels of SLC4A4 were decreased in CRC tissues, and low expression of SLC4A4 significantly correlated with shorter survival of CRC patients and poorer progression of patients with breast cancer, lung cancer, gastric cancer and ovarian cancer, suggesting potential role of SLC4A4 on tumor suppression and prognostic prediction in multiple malignancies including CRC.
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Differentially expressed genes (DEGs) were identified using the classical t-test, and statistically significant DEGs were defined with P < 0.01 and [logFC] > 2 as the cutoff criteria.
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Differentially expressed genes (DEGs) were identified using the classical t-test, and statistically significant DEGs were defined with P < 0.01 and [logFC] > 2 as the cutoff criteria.
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The microarray data in GSE22598 included 17 pairs of cancer and non-cancerous tissues from CRC patients (Submission date: December 04, 2011) 13.
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The microarray data in GSE22598 included 17 pairs of cancer and non-cancerous tissues from CRC patients (Submission date: December 04, 2011) 13.
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Clinical significance of UNC5B Expression in Colorectal Cancer
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Genome Wide Expression Analysis of Middle Eastern Colorectal Cancer Reveals FOXM1 as a Novel Target for Cancer Therapy
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Oncomine Analysis of SLC4A4 mRNA Expression in Colorectal Cancer.
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Candidate gene SLC4A4 mRNA expression analysis thorough Oncomine
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Oncomine Analysis of SLC4A4 mRNA Expression in Colorectal Cancer.
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82 differentially expressed genes (DEGs) were identified from three profile datasets, including 28 up-regulated genes and 54 down-regulated genes in the colorectal cancer tissues, compared to normal tissues.
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Identification of differentially expressed genes in CRC
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82 differentially expressed genes (DEGs) were identified from three profile datasets, including 28 up-regulated genes and 54 down-regulated genes in the colorectal cancer tissues, compared to normal tissues.
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Correlation between SLCA4A expression and clinicopathological characteristics
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Lower SLC4A4 expression associated with shorter survival of CRC patients
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Correlation between SLCA4A expression and clinicopathological characteristics
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[0]
> 65
[1]
54 (55.7%)
[2]
12 (72.0%)
[3]
42 (41.9%)
[5] array · 5 items
[0]
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[2]
[3]
[4]
[6] array · 5 items
[0]
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[1]
53 (54.6%)
[2]
11 (68.8%)
[3]
42 (41.9%)
[4]
0.219
[7] array · 4 items
[0]
Female
[1]
44 (45.4%)
[2]
5 (31.2%)
[3]
39 (48.1%)
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[0]
Pathology stage
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[2]
[3]
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[0]
Ⅰ
[1]
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[2]
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[3]
0 (0%)
[4]
0.751
[10] array · 4 items
[0]
Ⅱ
[1]
51 (52.6%)
[2]
9 (56.3%)
[3]
42 (41.9%)
[11] array · 4 items
[0]
Ⅲ
[1]
46 (47.4%)
[2]
7 (43.7%)
[3]
39 (48.1%)
[12] array · 5 items
[0]
Tumor size
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[2]
[3]
[4]
[13] array · 5 items
[0]
≤ 5 cm
[1]
50 (51.5%)
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10 (62.5%)
[3]
40 (49.4%)
[4]
0.343
[14] array · 4 items
[0]
>5 cm
[1]
47 (48.5%)
[2]
6 (37.5%)
[3]
41 (50.6%)
[15] array · 5 items
[0]
T stage
[1]
[2]
[3]
[4]
[16] array · 5 items
[0]
T1
[1]
1 (1.0%)
[2]
0 (0%)
[3]
1 (1.2%)
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0.852
[17] array · 4 items
[0]
T2
[1]
5 (5.2%)
[2]
0 (0%)
[3]
5 (6.2%)
[18] array · 4 items
[0]
T3
[1]
74 (76.3%)
[2]
14 (87.5%)
[3]
60 (74.1%)
[19] array · 4 items
[0]
T4
[1]
17 (17.5%)
[2]
2 (12.5%)
[3]
15 (18.5%)
[20] array · 5 items
[0]
N stage
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[2]
[3]
[4]
[21] array · 5 items
[0]
N0
[1]
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9 (56.3%)
[3]
48 (59.3%)
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0.872
[22] array · 4 items
[0]
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[1]
29 (29.9%)
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6 (37.5%)
[3]
23 (28.4%)
[23] array · 4 items
[0]
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[1]
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1 (6.2%)
[3]
10 (12.3%)
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M stage
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[2]
[3]
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[0]
M0
[1]
94 (96.9%)
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15 (93.8%)
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79 (97.5%)
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0.430
[26] array · 4 items
[0]
M1
[1]
3 (3.1%)
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1 (6.2%)
[3]
2 (2.5%)
locator
section[14]/table-wrap[1]#T3
gaps array · 6 items
[0]
asset:data:geo:GSE22598 not downloaded
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asset:data:geo:GSE22598 licence not read
[2]
asset:data:geo:GSE23878 not downloaded
[3]
asset:data:geo:GSE23878 licence not read
[4]
asset:data:geo:GSE41328 not downloaded
[5]
asset:data:geo:GSE41328 licence not read
analysis object · 4 fields
state
partial
methods array · 4 items
[0] object · 10 fields
id
method-1
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survival_analysis
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kaplan_meier
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Survival analysis
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[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
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0.7
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method-2
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survival_analysis
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Survival analysis
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[0]
logrank_test
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time_to_event_with_censoring
evidence object · 3 fields
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0.8
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high
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log rank
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method-3
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network_analysis
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[0]
build_graph
[1]
centrality_scores
[2]
pathway_enrich
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edge_list
evidence object · 3 fields
score
0.7
band
medium
quote
protein-protein interaction
[3] object · 10 fields
id
method-4
family
null
specific
null
label
Classical t-test
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
Differentially expressed genes (DEGs) were identified using the classical t-test, and statistically significant DEGs were defined with P < 0.01 and [logFC] > 2 as the cutoff criteria.
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
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assay_families array · 9 items
[0]
meta_analysis
[1]
machine_learning
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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 · 3 items
[0]
GSE22598
[1]
GSE23878
[2]
GSE41328
resolved_accessions array · 3 items
[0]
GSE22598
[1]
GSE23878
[2]
GSE41328
statements array · 1 item
[0]
The microarray data in GSE22598 included 17 pairs of cancer and non-cancerous tissues from CRC patients (Submission date: December 04, 2011) 13.
basis
The paper names GSE22598, GSE23878, GSE41328 in NCBI-Gene Expression Omnibus (NCBI-GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read.
can_run object · 3 fields
dsl_operations array · 1 item
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survival_km
assets array · 5 items
[0]
source:pmid:32284764
[1]
data:geo:GSE22598
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asset:table:pmid:32284764:1
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asset:table:pmid:32284764:2
[4]
asset:table:pmid:32284764:3
steps array · 1 item
[0]
run_analysis
must_build object · 5 fields
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readers array · 0 items
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[0]
data:geo:GSE22598
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review object · 5 fields
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partial
machine_critique object · 5 fields
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extraction_review
reader object · 5 fields
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MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:19:19Z
independence
single_reader
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verbatim
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null
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3
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extraction
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minimax
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review.independent_reader
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review.machine_critique
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review.human_critique
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not_run
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null
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execution.not_run
provenance object · 7 fields
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pmid:32284764
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paper
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pmid:32284764
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source:pmid:32284764
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manuscript
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PMID 32284764 full text
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data:geo:GSE22598
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dataset
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GEO GSE22598
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[0] object · 4 fields
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activity-reading-sci-2026-11-01
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classification
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pmid:32284764
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paper
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pmid:32284764
[1] object · 3 fields
id
source:pmid:32284764
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manuscript
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PMID 32284764 full text
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id
data:geo:GSE22598
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dataset
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GEO GSE22598
agent
agent:corpus-assay-engine
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id
activity-read-32284764
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extraction
used array · 1 item
[0]
source:pmid:32284764
agent
agent:minimax-reader
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id
activity-resolve-GSE22598
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accession_resolution
used array · 1 item
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data:geo:GSE22598
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agent:corpus-assay-engine
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Corpus assay engine
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agent:minimax-reader
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MiniMax literature reader
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dsl_catalogue_fingerprint
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lineage object · 4 fields
parent_id
pmid:32284764
parent_hash
sha256:51496082c74c7d745ae2f3b72350340080995c4c91496111b3f5fd094b2324e0
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null
gaps array · 11 items
[0]
asset:data:geo:GSE22598 licence not read
[1]
asset:data:geo:GSE22598 not downloaded
[2]
asset:data:geo:GSE23878 licence not read
[3]
asset:data:geo:GSE23878 not downloaded
[4]
asset:data:geo:GSE41328 licence not read
[5]
asset:data:geo:GSE41328 not downloaded
[6]
execution.not_run
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[0] object · 11 fields
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data_generation
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microarray
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99e1195c7d6f
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support_state
partial
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99e1195c7d6f
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0.99
evidence array · 3 items
[0]
rectal cancer (CRC). Methods: Three original microarray datasets (GSE41328, GSE22598, and GSE23878)
[1]
m QPCR based cDNA array and IHC based tissue microarray (TMA). STRING website was used to explore th
[2]
etworks. Results: Analysis of three original microarray datasets from GEO identified 82 shared, diff
order_basis
paper_text_order:215
id
assay:1
[1] object · 11 fields
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data_generation
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99e1195c7d6f
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99e1195c7d6f
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which was further confirmed by analyses from QPCR based cDNA array and IHC based tissue microa
[1]
mal tissues, which were further confirmed by QPCR based cDNA array and IHC based TMA analyses
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paper_text_order:548
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assay:2
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data_generation
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99e1195c7d6f
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99e1195c7d6f
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d by analyses from QPCR based cDNA array and IHC based tissue microarray (TMA). STRING websit
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rther confirmed by QPCR based cDNA array and IHC based TMA analyses on both mRNA and protein
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paper_text_order:574
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assay:3
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f2132e96ae6c7a4e
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survival_km
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:32284764", "kind": "science-record", "revision": 8, "content_hash": "sha256:3961968b8ebe9fa77e5e32e52c1d9bc33a2bd7bb13dc0ab884660d73c9446b8d", "created_at": "2026-11-01T15:40:59Z", "updated_at": "2026-11-01T22:01:29Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Down-regulated Solute Carrier Family 4 Member 4 Predicts Poor Progression in Colorectal Cancer.", "doi": "10.7150/jca.36696", "pmid": "32284764", "authors": ["Hong Yang", "Yao Lu", "Weilan Lan", "Bin Huang", "Jiumao Lin"], "journal": "Journal of Cancer", "year": 2020, "abstract": "Aim: To identify potential key candidate genes, whose expression and clinical significance was further assessed in colorectal cancer (CRC). Methods: Three original microarray datasets (GSE41328, GSE22598, and GSE23878) from NCBI-GEO were used to analyze differentially expressed genes (DEGs) in CRC. Online database analyses through Oncomine and GEIPA were performed to evaluate SLC4A4 expression and explore the prognostic merit of SLC4A4 expression, which was further confirmed by analyses from QPCR based cDNA array and IHC based tissue microarray (TMA). STRING website was used to explore the interaction between SLC4A4 with other DEGs based on the protein-protein interaction (PPI) networks. Results: Analysis of three original microarray datasets from GEO identified 82 shared, differentially expressed genes (28 upregulated and 54 down-regulated) in CRC tissues. Online analyses from Oncomine and GEIPA revealed lower SLC4A4 mRNA expression in CRC tissues compared to adjacent normal tissues, which were further confirmed by QPCR based cDNA array and IHC based TMA analyses on both mRNA and protein levels. Survival analyses through GEIPA and from TMA demonstrated that low SLC4A4 expression is correlated with worse overall survival among patients with CRC. Survival analysis from Kaplan-meier plotter demonstrated that low SLC4A4 expression is significantly associated with poor progression (including relapse-free survival, overall survival, distant metastasis-free survival, post-progression survival) of patients with breast cancer, lung cancer, gastric cancer, and ovarian cancer. PPI analysis found that SLC4A4 is highly correlated with various genes, including SLC9A3, SLC26A6, ENSG00000214921, SLC26A4, SLC9A3R1, and SLC9A1. Conclusion: The mRNA and protein levels of SLC4A4 were decreased in CRC tissues, and low expression of SLC4A4 significantly correlated with shorter survival of CRC patients and poorer progression of patients with breast cancer, lung cancer, gastric cancer and ovarian cancer, suggesting potential role of SLC4A4 on tumor suppression and prognostic prediction in multiple malignancies including CRC.", "claims": [{"id": "claim-method", "statement": "Differentially expressed genes (DEGs) were identified using the classical t-test, and statistically significant DEGs were defined with P < 0.01 and [logFC] > 2 as the cutoff criteria.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32284764", "locator": "sections[3] \"Microarray data information and DEGs identification\" paragraph 3", "quote": "Differentially expressed genes (DEGs) were identified using the classical t-test, and statistically significant DEGs were defined with P < 0.01 and [logFC] > 2 as the cutoff criteria."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The microarray data in GSE22598 included 17 pairs of cancer and non-cancerous tissues from CRC patients (Submission date: December 04, 2011) 13.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:32284764", "locator": "sections[3] \"Microarray data information and DEGs identification\" paragraph 2", "quote": "The microarray data in GSE22598 included 17 pairs of cancer and non-cancerous tissues from CRC patients (Submission date: December 04, 2011) 13."}], "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:32284764"], "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:GSE22598"], "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:GSE22598"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:32284764", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.7150/jca.36696", "sha256": 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Methods: Three original microarray datasets (GSE41328, GSE22598, and GSE23878)", "m QPCR based cDNA array and IHC based tissue microarray (TMA). STRING website was used to explore th", "etworks. 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