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pmid:28472085

Transcriptomic immunologic signature associated with favorable clinical outcome in basal-like breast tumors.

Sandra Martínez-Canales · Francisco Cifuentes · Miguel López De Rodas Gregorio · Leticia Serrano-Oviedo · Eva María Galán-Moya · Eitan Amir · Atanasio Pandiella · Balázs Győrffy · Alberto Ocaña

PloS one · 2017 doi:10.1371/journal.pone.0175128

Paper

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Experiment

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Data

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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:28472085
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2026-11-01T15:40:25Z
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2026-11-01T21:20:54Z
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title
Transcriptomic immunologic signature associated with favorable clinical outcome in basal-like breast tumors.
doi
10.1371/journal.pone.0175128
pmid
28472085
authors array · 9 items
[0]
Sandra Martínez-Canales
[1]
Francisco Cifuentes
[2]
Miguel López De Rodas Gregorio
[3]
Leticia Serrano-Oviedo
[4]
Eva María Galán-Moya
[5]
Eitan Amir
[6]
Atanasio Pandiella
[7]
Balázs Győrffy
[8]
Alberto Ocaña
journal
PloS one
year
2017
abstract
BACKGROUND: Most patients with early stage triple negative breast cancer (TNBC) receive adjuvant chemotherapy. Activation of the immune system is associated with tumor response and may help identify TNBC with favorable outcome. METHODS: Gene expression data were obtained from the GEO Dataset GDS2250/GSE3744. Affymetrix CEL files were downloaded and analyzed with Affymetrix Transcriptome Analysis Console 3.0. Functional genomics was implemented with David Bioinformatics Resources 6.8. Data contained at Oncomine were used to identify genes upregulated in basal-like cancer compared to normal breast tissue. Data contained at cBioportal were used to assess for molecular alterations. The KMPlotter online tool, METABRIC and GSE25066 datasets were used to associate gene signatures with clinical outcome. RESULTS: 1564 upregulated genes were identified as differentially expressed between normal and basal-like tumors. Of these, 16 genes associated with immune function were linked with clinical outcome. HLA-C, HLA-F, HLA-G and TIGIT were associated with both improved relapse-free survival (RFS) and overall survival (OS). The combination of HLA-F/TIGIT and HLA-C/HLA-F/TIGIT showed the most favorable outcome (HR for RFS 0.44, p<0.001; HR for OS 0.22, p<0.001; and HR for RFS 0.46, p<0.001; HR for OS 0.15, p<0.001; respectively). The association of HLA-C/HLA-F with outcome was confirmed using the METABRIC and GSE25066 datasets. No copy number alterations of these genes were identified. CONCLUSION: We describe a gene signature associated with immune function and favorable outcome in basal-like breast cancer. Incorporation of this signature in prospective studies may help to stratify risk of early stage TNBC.
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The KM Plotter Online Tool was used to analyze the relationship between the gene expression and patient clinical outcome in breast cancer (http://www.kmplot.com); this public database allowed us to investigate overall survival (OS) and relapse-free survival (RFS) [11].
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sections[4] "Outcome analyses" paragraph 2
quote
The KM Plotter Online Tool was used to analyze the relationship between the gene expression and patient clinical outcome in breast cancer (http://www.kmplot.com); this public database allowed us to investigate overall survival (OS) and relapse-free survival (RFS) [11].
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sections[13] "Data Availability" paragraph 2
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All relevant data are within the paper and its Supporting Information files.
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An in silico survival analysis using KM Plotter, with confirmation in the METABRIC and GSE25066 datasets, found that HLA-F/TIGIT and HLA-C/HLA-F/TIGIT signatures were associated with the most favorable relapse-free and overall survival in basal-like breast cancer.
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The combination of HLA-F/TIGIT and HLA-C/HLA-F/TIGIT showed the most favorable outcome (HR for RFS 0.44, p<0.001; HR for OS 0.22, p<0.001; and HR for RFS 0.46, p<0.001; HR for OS 0.15, p<0.001; respectively).
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sections[0] "Abstract" paragraph 3
quote
The combination of HLA-F/TIGIT and HLA-C/HLA-F/TIGIT showed the most favorable outcome (HR for RFS 0.44, p<0.001; HR for OS 0.22, p<0.001; and HR for RFS 0.46, p<0.001; HR for OS 0.15, p<0.001; respectively).
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sections[4] "Outcome analyses" paragraph 2
quote
The KM Plotter Online Tool was used to analyze the relationship between the gene expression and patient clinical outcome in breast cancer (http://www.kmplot.com); this public database allowed us to investigate overall survival (OS) and relapse-free survival (RFS) [11].
[2] object · 3 fields
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source:pmid:28472085
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sections[4] "Outcome analyses" paragraph 3
quote
We also confirmed the results using two additional datasets: METABRIC [13] and the GSE25066 dataset [14].
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An in silico survival analysis using KM Plotter, with confirmation in the METABRIC and GSE25066 datasets, found that HLA-F/TIGIT and HLA-C/HLA-F/TIGIT signatures were associated with the most favorable relapse-free and overall survival in basal-like breast cancer.
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GSM615828
sample_count
508
group_sizes
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
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[2] object · 16 fields
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List of the identified immunologic-related genes associated with RFS and OS in basal like breast cancer.
structure object · 5 fields
pmcid
PMC5417488
section_index
9
section_title
Gene set combinations for HLA-C, HLA-F, HLA-G and TIGIT
row_count
13
column_count
6
table object · 8 fields
label
Table 1
caption
List of the identified immunologic-related genes associated with RFS and OS in basal like breast cancer.
rows array · 13 items
[0] array · 3 items
[0]
Probe Set
[1]
Gene name
[2]
Basal Like
[1] array · 2 items
[0]
Relapse Free Survival
[1]
Overall Survival
[2] array · 4 items
[0]
HR (Hazard Ratio)
[1]
Logrank P-value
[2]
HR (Hazard Ratio)
[3]
Logrank P-value
[3] array · 6 items
[0]
217072_at
[1]
CD300A, CD300a molecule
[2]
0,74 (0,57–0,96)
[3]
0,023
[4]
-
[5]
>0,05
[4] array · 6 items
[0]
211893_x_at
[1]
CD6, CD6 molecule
[2]
0,53 (0,4–0,69)
[3]
2,20E-06
[4]
-
[5]
>0,05
[5] array · 6 items
[0]
222859_s_at
[1]
DAPP1, dual adaptor of phosphotyrosine and 3-phosphoinositides
[2]
0,5 (0,35–0,7)
[3]
5,50E-05
[4]
-
[5]
>0,05
[6] array · 6 items
[0]
211799_x_at
[1]
HLA-C, major histocompatibility complex, class I, C
[2]
0,59 (0,45–0,77)
[3]
9,90E-05
[4]
0,38 (0,21–0,71)
[5]
0,0014
[7] array · 6 items
[0]
221875_x_at
[1]
HLA-F, major histocompatibility complex, class I, F
[2]
0,53 (0,41–0,7)
[3]
2,80E-06
[4]
0,35 (0,19–0,63)
[5]
0,00032
[8] array · 6 items
[0]
211528_x_at
[1]
HLA-G, major histocompatibility complex, class I, G
[2]
0,6 (0,46–0,79)
[3]
0,00017
[4]
0,42 (0,23–0,75)
[5]
0,0028
[9] array · 6 items
[0]
239021_at
[1]
TLR6, toll-like receptor 6
[2]
0,67 (0,48–0,95)
[3]
0,023
[4]
-
[5]
>0,05
[10] array · 6 items
[0]
210340_s_at
[1]
CSF2RA, colony stimulating factor 2 receptor, alpha, low-affinity (granulocyte-macrophage)
[2]
0,59 (0,45–0,76)
[3]
6,80E-05
[4]
-
[5]
>0,05
[11] array · 6 items
[0]
240070_at
[1]
TIGIT, T cell immunoreceptor with Ig and ITIM domains
[2]
0,36 (0,25–0,52)
[3]
8,30E-09
[4]
0,37 (0,16–0,84)
[5]
0,014
[12] array · 6 items
[0]
1564684_at
[1]
BTN2A2, butyrophilin, subfamily 2, member A2
[2]
0,55 (0,39–0,78)
[3]
0,00072
[4]
-
[5]
>0,05
locator
section[9]/table-wrap[1]#pone.0175128.t001
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asset:table:pmid:28472085:2
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version
null
note
List of gene combinations associated with favorable outcome in basal like cancer using the KM plotter online tool, as described in material and methods.
structure object · 5 fields
pmcid
PMC5417488
section_index
9
section_title
Gene set combinations for HLA-C, HLA-F, HLA-G and TIGIT
row_count
13
column_count
7
table object · 8 fields
label
Table 2
caption
List of gene combinations associated with favorable outcome in basal like cancer using the KM plotter online tool, as described in material and methods.
rows array · 13 items
[0] array · 3 items
[0]
Gene combinations
[1]
Relapse Free Survival
[2]
Overall Survival
[1] array · 6 items
[0]
HR (Hazard Ratio)
[1]
Logrank P- value
[2]
N (patients)
[3]
HR (Hazard Ratio)
[4]
Logrank P- value
[5]
N (patients)
[2] array · 7 items
[0]
HLA-C, HLA-F, HLA-G, TIGIT
[1]
0,54 (0,38–0,77)
[2]
0.00047
[3]
339
[4]
0,2 (0,08–0,54)
[5]
0,00036
[6]
132
[3] array · 7 items
[0]
HLA-C, HLA-F, HLA-G
[1]
0,55 (0,42–0,72)
[2]
7,8E-06
[3]
580
[4]
0,38 (0,21–0,7)
[5]
0,0011
[6]
204
[4] array · 7 items
[0]
HLA-C, HLA-F, TIGIT
[1]
0,46 (0,32–0,65)
[2]
7,5E-06
[3]
339
[4]
0,15 (0,05–0,44)
[5]
6,2E-05
[6]
132
[5] array · 7 items
[0]
HLA-C, HLA-G, TIGIT
[1]
0,56 (0,4–0,79)
[2]
0,00081
[3]
339
[4]
0,15 (0,05–0,44)
[5]
6,7E-05
[6]
132
[6] array · 7 items
[0]
HLA-F, HLA-G, TIGIT
[1]
0,5 (0,35–0,71)
[2]
7,8E-05
[3]
339
[4]
0,25 (0,1–0,62)
[5]
0,0012
[6]
132
[7] array · 7 items
[0]
HLA-C, HLA-F
[1]
0,51 (0,39–0,67)
[2]
6,2E-07
[3]
580
[4]
0,31 (0,16–0,58)
[5]
0,00011
[6]
204
[8] array · 7 items
[0]
HLA-C, HLA-G
[1]
0,62 (0,47–0,8)
[2]
0,00029
[3]
580
[4]
0,39 (0,21–0,71)
[5]
0,0014
[6]
204
[9] array · 7 items
[0]
HLA-C, TIGIT
[1]
0,58 (0,41–0,81)
[2]
0,0015
[3]
339
[4]
0,21 (0,08–0,57)
[5]
0,00063
[6]
132
[10] array · 7 items
[0]
HLA-F, HLA-G
[1]
0,57 (0,44–0,75)
[2]
3,5E-05
[3]
580
[4]
0,42 (0,23–0,76)
[5]
0,0029
[6]
204
[11] array · 7 items
[0]
HLA-F, TIGIT
[1]
0,44 (0,31–0,63)
[2]
3E-06
[3]
339
[4]
0,22 (0,09–0,55)
[5]
0,00037
[6]
132
[12] array · 7 items
[0]
HLA-G, TIGIT
[1]
0,57 (0,4–0,81)
[2]
0,0013
[3]
339
[4]
0,19 (0,07–0,51)
[5]
2E-04
[6]
132
locator
section[9]/table-wrap[2]#pone.0175128.t002
gaps array · 2 items
[0]
asset:data:geo:GSE25066 not downloaded
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asset:data:geo:GSE25066 licence not read
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state
complete
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[0] object · 10 fields
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method-1
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survival_analysis
specific
kaplan_meier
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Survival analysis
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survival_km
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time_to_event_with_censoring
evidence object · 3 fields
score
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band
verbatim
quote
The KM Plotter Online Tool was used to analyze the relationship between the gene expression and patient clinical outcome in breast cancer (http://www.kmplot.com); this public database allowed us to investigate overall survival (OS) and relapse-free survival (RFS) [11].
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[0] object · 8 fields
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target-published-estimate
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claim-target-result
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survival_km
unit
p-value
tolerance
null
state
complete
note
The threshold the paper applied to its own result, as the paper states it. A run that reproduces the effect is judged against this threshold.
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capability object · 3 fields
state
complete
requirements array · 1 item
[0] object · 6 fields
capability_id
capability:computational_analysis
label
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assay_families array · 9 items
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meta_analysis
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machine_learning
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survival_analysis
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statistical_regression
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pca
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molecular_docking
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differential_expression
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gwas
candidate
Automated Assays Laravel application and simulated adapters
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complete
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blocked_on
nothing:replicable_now
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method object · 5 fields
tier
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survival_km
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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 · 2 items
[0]
GDS2250/GSE3744
[1]
GSE25066
resolved_accessions array · 1 item
[0]
GSE25066
statements array · 1 item
[0]
All relevant data are within the paper and its Supporting Information files.
basis
The paper names GSE25066 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read.
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survival_km
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source:pmid:28472085
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data:geo:GSE25066
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asset:table:pmid:28472085:1
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run_analysis
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data:geo:GSE25066
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partial
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MiniMax-M3.1-Flash
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minimax
provider_family
minimax
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availability
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extraction
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source:pmid:28472085
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PMID 28472085 full text
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data:geo:GSE25066
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GEO GSE25066
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source:pmid:28472085
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PMID 28472085 full text
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agent:corpus-assay-engine
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agent:minimax-reader
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[0]
The KM Plotter Online Tool was used to analyze the relationship between the gene expression and patient clinical outcome in breast cancer (http://www.kmplot.com); this public database allowed us to investigate overall survival (OS) and relapse-free survival (RFS) [11].
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{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:28472085", "kind": "science-record", "revision": 4, "content_hash": "sha256:0ec9737a354faf06704ee18303c5ca9d82f0a301b15248d08a3dff0fb176bbe6", "created_at": "2026-11-01T15:40:25Z", "updated_at": "2026-11-01T21:20:54Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Transcriptomic immunologic signature associated with favorable clinical outcome in basal-like breast tumors.", "doi": "10.1371/journal.pone.0175128", "pmid": "28472085", "authors": ["Sandra Martínez-Canales", "Francisco Cifuentes", "Miguel López De Rodas Gregorio", "Leticia Serrano-Oviedo", "Eva María Galán-Moya", "Eitan Amir", "Atanasio Pandiella", "Balázs Győrffy", "Alberto Ocaña"], "journal": "PloS one", "year": 2017, "abstract": "BACKGROUND: Most patients with early stage triple negative breast cancer (TNBC) receive adjuvant chemotherapy. Activation of the immune system is associated with tumor response and may help identify TNBC with favorable outcome.\nMETHODS: Gene expression data were obtained from the GEO Dataset GDS2250/GSE3744. Affymetrix CEL files were downloaded and analyzed with Affymetrix Transcriptome Analysis Console 3.0. Functional genomics was implemented with David Bioinformatics Resources 6.8. Data contained at Oncomine were used to identify genes upregulated in basal-like cancer compared to normal breast tissue. Data contained at cBioportal were used to assess for molecular alterations. The KMPlotter online tool, METABRIC and GSE25066 datasets were used to associate gene signatures with clinical outcome.\nRESULTS: 1564 upregulated genes were identified as differentially expressed between normal and basal-like tumors. Of these, 16 genes associated with immune function were linked with clinical outcome. HLA-C, HLA-F, HLA-G and TIGIT were associated with both improved relapse-free survival (RFS) and overall survival (OS). The combination of HLA-F/TIGIT and HLA-C/HLA-F/TIGIT showed the most favorable outcome (HR for RFS 0.44, p<0.001; HR for OS 0.22, p<0.001; and HR for RFS 0.46, p<0.001; HR for OS 0.15, p<0.001; respectively). The association of HLA-C/HLA-F with outcome was confirmed using the METABRIC and GSE25066 datasets. No copy number alterations of these genes were identified.\nCONCLUSION: We describe a gene signature associated with immune function and favorable outcome in basal-like breast cancer. Incorporation of this signature in prospective studies may help to stratify risk of early stage TNBC.", "claims": [{"id": "claim-method", "statement": "The KM Plotter Online Tool was used to analyze the relationship between the gene expression and patient clinical outcome in breast cancer (http://www.kmplot.com); this public database allowed us to investigate overall survival (OS) and relapse-free survival (RFS) [11].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28472085", "locator": "sections[4] \"Outcome analyses\" paragraph 2", "quote": "The KM Plotter Online Tool was used to analyze the relationship between the gene expression and patient clinical outcome in breast cancer (http://www.kmplot.com); this public database allowed us to investigate overall survival (OS) and relapse-free survival (RFS) [11]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "All relevant data are within the paper and its Supporting Information files.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28472085", "locator": "sections[13] \"Data Availability\" paragraph 2", "quote": "All relevant data are within the paper and its Supporting Information files."}], "state": "complete"}, {"id": "claim-target-result", "statement": "An in silico survival analysis using KM Plotter, with confirmation in the METABRIC and GSE25066 datasets, found that HLA-F/TIGIT and HLA-C/HLA-F/TIGIT signatures were associated with the most favorable relapse-free and overall survival in basal-like breast cancer.", "kind": "quantitative", "target": {"value": 0.001, "unit": "p-value", "tolerance": null, "source": "The combination of HLA-F/TIGIT and HLA-C/HLA-F/TIGIT showed the most favorable outcome (HR for RFS 0.44, p<0.001; HR for OS 0.22, p<0.001; and HR for RFS 0.46, p<0.001; HR for OS 0.15, p<0.001; respectively)."}, "evidence": [{"asset": "source:pmid:28472085", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The combination of HLA-F/TIGIT and HLA-C/HLA-F/TIGIT showed the most favorable outcome (HR for RFS 0.44, p<0.001; HR for OS 0.22, p<0.001; and HR for RFS 0.46, p<0.001; HR for OS 0.15, p<0.001; respectively)."}, {"asset": "source:pmid:28472085", "locator": "sections[4] \"Outcome analyses\" paragraph 2", "quote": "The KM Plotter Online Tool was used to analyze the relationship between the gene expression and patient clinical outcome in breast cancer (http://www.kmplot.com); this public database allowed us to investigate overall survival (OS) and relapse-free survival (RFS) [11]."}, {"asset": "source:pmid:28472085", "locator": "sections[4] \"Outcome analyses\" paragraph 3", "quote": "We also confirmed the results using two additional datasets: METABRIC [13] and the GSE25066 dataset [14]."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "An in silico survival analysis using KM Plotter, with confirmation in the METABRIC and GSE25066 datasets, found that HLA-F/TIGIT and HLA-C/HLA-F/TIGIT signatures were associated with the most favorable relapse-free and overall survival in basal-like breast cancer.", "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:28472085"], "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. 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immunologic-related genes associated with RFS and OS in basal like breast cancer.", "rows": [["Probe Set", "Gene name", "Basal Like"], ["Relapse Free Survival", "Overall Survival"], ["HR (Hazard Ratio)", "Logrank P-value", "HR (Hazard Ratio)", "Logrank P-value"], ["217072_at", "CD300A, CD300a molecule", "0,74 (0,57–0,96)", "0,023", "-", ">0,05"], ["211893_x_at", "CD6, CD6 molecule", "0,53 (0,4–0,69)", "2,20E-06", "-", ">0,05"], ["222859_s_at", "DAPP1, dual adaptor of phosphotyrosine and 3-phosphoinositides", "0,5 (0,35–0,7)", "5,50E-05", "-", ">0,05"], ["211799_x_at", "HLA-C, major histocompatibility complex, class I, C", "0,59 (0,45–0,77)", "9,90E-05", "0,38 (0,21–0,71)", "0,0014"], ["221875_x_at", "HLA-F, major histocompatibility complex, class I, F", "0,53 (0,41–0,7)", "2,80E-06", "0,35 (0,19–0,63)", "0,00032"], ["211528_x_at", "HLA-G, major histocompatibility complex, class I, G", "0,6 (0,46–0,79)", "0,00017", "0,42 (0,23–0,75)", "0,0028"], ["239021_at", "TLR6, toll-like receptor 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"List of gene combinations associated with favorable outcome in basal like cancer using the KM plotter online tool, as described in material and methods.", "structure": {"pmcid": "PMC5417488", "section_index": 9, "section_title": "Gene set combinations for HLA-C, HLA-F, HLA-G and TIGIT", "row_count": 13, "column_count": 7}, "table": {"label": "Table 2", "caption": "List of gene combinations associated with favorable outcome in basal like cancer using the KM plotter online tool, as described in material and methods.", "rows": [["Gene combinations", "Relapse Free Survival", "Overall Survival"], ["HR (Hazard Ratio)", "Logrank P- value", "N (patients)", "HR (Hazard Ratio)", "Logrank P- value", "N (patients)"], ["HLA-C, HLA-F, HLA-G, TIGIT", "0,54 (0,38–0,77)", "0.00047", "339", "0,2 (0,08–0,54)", "0,00036", "132"], ["HLA-C, HLA-F, HLA-G", "0,55 (0,42–0,72)", "7,8E-06", "580", "0,38 (0,21–0,7)", "0,0011", "204"], ["HLA-C, HLA-F, TIGIT", "0,46 (0,32–0,65)", "7,5E-06", "339", "0,15 (0,05–0,44)", "6,2E-05", "132"], ["HLA-C, HLA-G, TIGIT", "0,56 (0,4–0,79)", "0,00081", "339", "0,15 (0,05–0,44)", "6,7E-05", "132"], ["HLA-F, HLA-G, TIGIT", "0,5 (0,35–0,71)", "7,8E-05", "339", "0,25 (0,1–0,62)", "0,0012", "132"], ["HLA-C, HLA-F", "0,51 (0,39–0,67)", "6,2E-07", "580", "0,31 (0,16–0,58)", "0,00011", "204"], ["HLA-C, HLA-G", "0,62 (0,47–0,8)", "0,00029", "580", "0,39 (0,21–0,71)", "0,0014", "204"], ["HLA-C, TIGIT", "0,58 (0,41–0,81)", "0,0015", "339", "0,21 (0,08–0,57)", "0,00063", "132"], ["HLA-F, HLA-G", "0,57 (0,44–0,75)", "3,5E-05", "580", "0,42 (0,23–0,76)", "0,0029", "204"], ["HLA-F, TIGIT", "0,44 (0,31–0,63)", "3E-06", "339", "0,22 (0,09–0,55)", "0,00037", "132"], ["HLA-G, TIGIT", "0,57 (0,4–0,81)", "0,0013", "339", "0,19 (0,07–0,51)", "2E-04", "132"]], "row_count": 13, "column_count": 7, "numeric_cells": 66, "header_rows": 2, "locator": "section[9]/table-wrap[2]#pone.0175128.t002"}}], "gaps": ["asset:data:geo:GSE25066 not downloaded", "asset:data:geo:GSE25066 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A run that reproduces the effect is judged against this threshold."}], "gaps": []}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "complete", "tier": "R1", "blocking_axis": "none", "blocked_on": "nothing:replicable_now", "axes": {"method": {"tier": "R1", "expressible": true, "required_operations": ["survival_km"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: kaplan_meier."}, "capability": {"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": {"tier": "R1", "reachable": true, "accessions": ["GDS2250/GSE3744", "GSE25066"], "resolved_accessions": ["GSE25066"], "statements": ["All relevant data are within the paper and its Supporting Information files."], "basis": "The paper names GSE25066 in GEO and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["survival_km"], "assets": ["source:pmid:28472085", "data:geo:GSE25066", "asset:table:pmid:28472085:1", "asset:table:pmid:28472085:2"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE25066"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:31:02Z", "independence": "same_provider"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 8, "usage": {"prompt_tokens": 46215, "completion_tokens": 5327, "cached_tokens": 2096}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:28472085", "type": "paper", "label": "pmid:28472085"}, {"id": "source:pmid:28472085", "type": "manuscript", "label": "PMID 28472085 full text"}, {"id": "data:geo:GSE25066", "type": "dataset", "label": "GEO GSE25066"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:28472085", "type": "paper", "label": "pmid:28472085"}, {"id": "source:pmid:28472085", "type": "manuscript", "label": "PMID 28472085 full text"}, {"id": "data:geo:GSE25066", "type": "dataset", "label": "GEO GSE25066"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-28472085", "type": "extraction", "used": ["source:pmid:28472085"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE25066", "type": "accession_resolution", "used": ["data:geo:GSE25066"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"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": {"parent_id": "pmid:28472085", "parent_hash": "sha256:038ae17b5f2eea9733b4126d088dd15456589d28d6f53850012b34609a328971", "fork_of": null, "generation": 3}, "gaps": ["asset:data:geo:GSE25066 licence not read", "asset:data:geo:GSE25066 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": 1.0, "evidence": ["The KM Plotter Online Tool was used to analyze the relationship between the gene expression and patient clinical outcome in breast cancer (http://www.kmplot.com); this public database allowed us to investigate overall survival (OS) and relapse-free survival (RFS) [11]."], "order_basis": "analysis_only", "id": "assay:1"}]}