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pmid:33457427

Inflammation Is Associated with Worse Outcome in the Whole Cohort but with Better Outcome in Triple-Negative Subtype of Breast Cancer Patients.

Masanori Oshi · Stephanie Newman · Yoshihisa Tokumaru · Li Yan · Ryusei Matsuyama · Itaru Endo · Kazuaki Takabe

Journal of immunology research · 2020 doi:10.1155/2020/5618786

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title
Inflammation Is Associated with Worse Outcome in the Whole Cohort but with Better Outcome in Triple-Negative Subtype of Breast Cancer Patients.
doi
10.1155/2020/5618786
pmid
33457427
authors array · 7 items
[0]
Masanori Oshi
[1]
Stephanie Newman
[2]
Yoshihisa Tokumaru
[3]
Li Yan
[4]
Ryusei Matsuyama
[5]
Itaru Endo
[6]
Kazuaki Takabe
journal
Journal of immunology research
year
2020
abstract
Inflammation has been linked with cancer, but whether it is part of the problem or part of the solution remains to be a matter of debate in breast cancer. Our group and others have demonstrated that inflammation aggravates cancer progression; however, some claim that inflammation may support immune cell infiltration and suppress cancer. We defined the gene set variation analysis of the Molecular Signatures Database Hallmark inflammatory response gene set as the inflammatory pathway score and analyzed 3632 tumors in total from 4 breast cancer cohorts (METABRIC, TCGA, GSE25066, and GSE21094). In the whole breast cancer cohort, high-score tumors were associated with aggressive clinical characteristics, such as worse disease specific survival, higher Nottingham histological grade, and younger age. Inflammatory score was significantly higher in triple-negative (TNBC) as well as basal and normal subtypes compared with the other subtypes, which suggest that the detrimental effect of high level of inflammation may be because it includes a more aggressive subtype. On the contrary, high score within TNBC was significantly associated with better survival. TNBC with high score enriched not only IFN-α, IFN-γ response, IL-2/STAT5 signaling, Allograft rejection, Complement, p53 pathway, Reactive Oxygen, and Apoptosis but also TNF-α signaling, IL6-JAK-STAT signaling, TGF-β signaling, Coagulation, Angiogenesis, EMT, KRAS signaling, and PI3K-AKT-MTOR signaling gene sets. High score was associated with mainly favorable anticancerous immune cell infiltration as well as Leukocyte fraction, TIL regional fraction, Lymphocyte infiltration, IFN-γ response, TGF-β response, and cytolytic activity scores. Although the inflammatory pathway score was not associated with neoadjuvant treatment response, it associated with expressions of immune checkpoint molecules. In conclusion, inflammation was associated with worse outcome in the whole breast cancer cohort, but with better outcome in TNBC, which was associated with favorable anticancerous immune response and immune cell infiltrations.
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We used log-rank test and Kaplan-Meier method to examine the associations with disease free survival (DFS), disease specific survival (DSS), overall survival (OS), and the inflammatory pathway score.
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We used log-rank test and Kaplan-Meier method to examine the associations with disease free survival (DFS), disease specific survival (DSS), overall survival (OS), and the inflammatory pathway score.
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sample_count
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null
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platform
6986;8490;570
taxon
Homo sapiens
title
Genomic profiling in Down syndrome pediatric acute lymphoblastic leukemia
resolution_checked_at
2026-11-01T15:39:54Z
resolution_check
identifier_resolution_only_no_download_no_licence_read
downloaded
false
licence_read
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[3] object · 15 fields
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data:geo:GSE25066
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geo-series
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sha256
null
bytes
null
access
open
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resolved
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null
reader_status
reader_required
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version
null
note
All data relevant to the study are included in the article.
structure object · 15 fields
repository
GEO
access_route
GEO accession URL
access_statement_verbatim
All data relevant to the study are included in the article.
access_statement_kind
data_availability_statement
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[123]
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[421]
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[422]
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[423]
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[427]
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[428]
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GSM615828
sample_count
508
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null
group_sizes_basis
null
platform
96
taxon
Homo sapiens
title
Genomic predictor of response and survival following neoadjuvant taxane-anthracycline chemotherapy in breast cancer
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 · 6 items
[0]
asset:data:geo:GSE20194 not downloaded
[1]
asset:data:geo:GSE20194 licence not read
[2]
asset:data:geo:GSE21094 not downloaded
[3]
asset:data:geo:GSE21094 licence not read
[4]
asset:data:geo:GSE25066 not downloaded
[5]
asset:data:geo:GSE25066 licence not read
analysis object · 4 fields
state
partial
methods array · 3 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
1
band
verbatim
quote
We used log-rank test and Kaplan-Meier method to examine the associations with disease free survival (DFS), disease specific survival (DSS), overall survival (OS), and the inflammatory pathway score.
[1] object · 10 fields
id
method-2
family
group_comparison
specific
anova
label
Group comparison
dsl_operations array · 4 items
[0]
group_summary
[1]
welch_t
[2]
bootstrap_mean_difference
[3]
group_comparison_anova
missing_operations array · 0 items
parameters object · 0 fields
data_shapes array · 1 item
[0]
two_or_more_groups_continuous
evidence object · 3 fields
score
0.8
band
high
quote
ANOVA
[2] object · 10 fields
id
method-3
family
survival_analysis
specific
log_rank_test
label
Survival analysis
dsl_operations array · 1 item
[0]
logrank_test
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
Log-rank
targets array · 0 items
gaps array · 1 item
[0]
method.reader_differs_from_extractor
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 · 3 items
[0]
GSE20194
[1]
GSE25066
[2]
GSE21094
resolved_accessions array · 3 items
[0]
GSE20194
[1]
GSE25066
[2]
GSE21094
statements array · 1 item
[0]
All data relevant to the study are included in the article.
basis
The paper names GSE20194, GSE25066, GSE21094 in Gene Expression Omnibus (GEO) repository of the US National Institutes of Health 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:33457427
[1]
data:geo:GSE20194
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:GSE20194
gaps array · 0 items
review object · 5 fields
state
partial
machine_critique object · 5 fields
kind
extraction_review
reader object · 5 fields
model
MiniMax-M3.1-Flash
provider
minimax
provider_family
minimax
read_at
2026-10-31T18:26:29Z
independence
single_reader
evidence_check object · 2 fields
method
verbatim
availability
verbatim
calls
3
usage object · 3 fields
prompt_tokens
36175
completion_tokens
1894
cached_tokens
12288
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
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We used log-rank test and Kaplan-Meier method to examine the associations with disease free survival (DFS), disease specific survival (DSS), overall survival (OS), and the inflammatory pathway score.
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Complete file
{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:33457427", "kind": "science-record", "revision": 8, "content_hash": "sha256:d3f48e2b7b230cf49bad5731404017c362abe06b4e2149a5dca0dc4504ef60d8", "created_at": "2026-11-01T15:41:23Z", "updated_at": "2026-11-01T22:45:59Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Inflammation Is Associated with Worse Outcome in the Whole Cohort but with Better Outcome in Triple-Negative Subtype of Breast Cancer Patients.", "doi": "10.1155/2020/5618786", "pmid": "33457427", "authors": ["Masanori Oshi", "Stephanie Newman", "Yoshihisa Tokumaru", "Li Yan", "Ryusei Matsuyama", "Itaru Endo", "Kazuaki Takabe"], "journal": "Journal of immunology research", "year": 2020, "abstract": "Inflammation has been linked with cancer, but whether it is part of the problem or part of the solution remains to be a matter of debate in breast cancer. Our group and others have demonstrated that inflammation aggravates cancer progression; however, some claim that inflammation may support immune cell infiltration and suppress cancer. We defined the gene set variation analysis of the Molecular Signatures Database Hallmark inflammatory response gene set as the inflammatory pathway score and analyzed 3632 tumors in total from 4 breast cancer cohorts (METABRIC, TCGA, GSE25066, and GSE21094). In the whole breast cancer cohort, high-score tumors were associated with aggressive clinical characteristics, such as worse disease specific survival, higher Nottingham histological grade, and younger age. Inflammatory score was significantly higher in triple-negative (TNBC) as well as basal and normal subtypes compared with the other subtypes, which suggest that the detrimental effect of high level of inflammation may be because it includes a more aggressive subtype. On the contrary, high score within TNBC was significantly associated with better survival. TNBC with high score enriched not only IFN-α, IFN-γ response, IL-2/STAT5 signaling, Allograft rejection, Complement, p53 pathway, Reactive Oxygen, and Apoptosis but also TNF-α signaling, IL6-JAK-STAT signaling, TGF-β signaling, Coagulation, Angiogenesis, EMT, KRAS signaling, and PI3K-AKT-MTOR signaling gene sets. High score was associated with mainly favorable anticancerous immune cell infiltration as well as Leukocyte fraction, TIL regional fraction, Lymphocyte infiltration, IFN-γ response, TGF-β response, and cytolytic activity scores. Although the inflammatory pathway score was not associated with neoadjuvant treatment response, it associated with expressions of immune checkpoint molecules. In conclusion, inflammation was associated with worse outcome in the whole breast cancer cohort, but with better outcome in TNBC, which was associated with favorable anticancerous immune response and immune cell infiltrations.", "claims": [{"id": "claim-method", "statement": "We used log-rank test and Kaplan-Meier method to examine the associations with disease free survival (DFS), disease specific survival (DSS), overall survival (OS), and the inflammatory pathway score.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:33457427", "locator": "sections[5] \"2.3. 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This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": ["data:geo:GSE20194"], "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:GSE20194"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:33457427", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1155/2020/5618786", "sha256": 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