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pmid:38477438

Exploring the molecular mechanisms network of breast cancer by multi-omics analysis.

Asia-Pacific journal of clinical oncology · 2025 doi:10.1111/ajco.14052

Paper

partial

Experiment

partial

Data

partial

Analysis

absent

Execution

absent

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Record details sci_version · id · kind · revision · content_hash · schema · created_at · updated_at · generator
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pmid:38477438
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science-record
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2026-11-01T10:25:48Z
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2026-11-01T10:25:48Z
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sep_to_sci_v1
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paper object · 10 fields
state
partial
title
Exploring the molecular mechanisms network of breast cancer by multi-omics analysis.
doi
10.1111/ajco.14052
pmid
38477438
authors
null
journal
Asia-Pacific journal of clinical oncology
year
2025
abstract
null
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[0] object · 6 fields
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claim-1
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the headline numerical result the paper states for its main finding
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quantitative
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complete
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4
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hub genes
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null
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source:pmid:38477438
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13 genes that significantly impacted patient prognosis were found when we performed a survival study on these 50 genes. Then, we conducted survival analysis on the transcriptional data of BRCA in TCGA, and ultimately determined four hub genes that maintained consistent survival effects in both data sets (Figure 2C,D).
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abstract
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partial
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the headline numerical result the paper states for its main finding
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read_published_estimate
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1
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Read the published estimate and its interval from the source
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other
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complete
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null
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The number a replication must land on, and the sentence it came from.
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source:pmid:38477438
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[0]
the published estimate, its unit and its interval
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Obtain the source data behind the published result
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The published result cannot be recomputed without the data the paper analysed.
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[0]
the source data with its provenance
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no owned computational capability is bound to this experiment
description
Re-run the paper's analysis on the source data and produce the registered result. | SEP input not carried into the asset list: materials:the source data behind the published result in pmid:38477438
parameters object · 0 fields
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outputs array · 1 item
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the registered result
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step:obtain_source_data blocked on data:not_downloaded
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step:run_analysis blocked on no owned computational capability is bound to this experiment
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step:run_analysis input 'materials:the source data behind the published result in pmid:38477438' does not resolve to a declared asset
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Source read by the package builder: full_text.
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asset:source:pmid:38477438 not verified
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null
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source:pmid:38477438
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read_published_estimate
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xml
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{"parent_value":4,"unit":"hub genes","evidence":"13 genes that significantly impacted patient prognosis were found when we performed a survival study on these 50 genes. Then, we conducted survival analysis on the transcriptional data of BRCA in TCGA, and ultimately determined four hub genes that maintained consistent survival effects in both data sets (Figure 2C,D).","target_result":"The paper reports that four hub genes maintained consistent survival effects in both the GSE20685 and TCGA datasets.","number_stated":true}
reading object · 6 fields
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13 genes that significantly impacted patient prognosis were found when we performed a survival study on these 50 genes. Then, we conducted survival analysis on the transcriptional data of BRCA in TCGA, and ultimately determined four hub genes that maintained consistent survival effects in both data sets (Figure 2C,D).
target_result
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raw_response
<think>We need answer JSON only. Need interpret target: headline numerical result paper states for main finding. Main finding four hub genes? Registered target says "the headline numerical result the paper states for its main finding". Likely number = four, unit perhaps "hub genes" or "genes"? Need exact contiguous quote contains number and attribution. Text: "We found six modules..." but main finding ultimately four hub genes. Abstract: "Four hub genes were identified based on..." Exact number word not numeral? User asks numerical result, value paper states, unit paper prints. parent_value number 4, unit maybe "hub genes". Evidence exact contiguous quotation. "Four hub genes were identified based on the Weighted Gene Co‐expression Network Analysis." That supports 4 hub genes, but target wording "headline numerical result ... main finding" perhaps yes. They emphasize exact contiguous quotation contains number. Number spelled "Four", does that count? likely yes. Unit "hub genes" (paper prints). Could also evidence "These findings pinpoint four crucial genes in BC progression..." unit genes. Need single result. Let's scrutinize. User says registered target "the headline numerical result the paper itself states for its main finding." They want numerical result replication must reproduce. Main finding likely four hub genes. Headline number 4, unit "hub genes". The exact quote perhaps must include a number (word accepted?) Evidence "Four hub genes were identified based on the Weighted Gene Co‐expression Network Analysis." Contiguous exact. target_result likely "Four hub genes were identified." Or perhaps target_result should describe "Four hub genes identified..." Number stated true. Could unit be "hub genes" exactly. parent_value 4. JSON valid, preserving special hyphen not relevant. Evidence exact quote. Need no markdown.</think> {"parent_value":4,"unit":"hub genes","evidence":"Four hub genes were identified based on the Weighted Gene Co‐expression Network Analysis.","target_result":"Four hub genes were identified.","number_stated":true}
reading object · 6 fields
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4
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hub genes
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Four hub genes were identified based on the Weighted Gene Co‐expression Network Analysis.
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Four hub genes were identified.
number_stated
true
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chars 533-622 of source sha256 18218b95e4529026df9f273a22b69b580ad5fc25e2d0bc08a7a273173fd91050
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agreement
false
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minimax
Four hub genes associated with breast cancer prognosis were identified: SERPINB5, Keratin 14 (KRT14), melanoma-inhibiting activity (MIA), and Secreted Frizzled-Related Protein 1 (SFRP1).
minimax_alt
The study identified four breast-cancer hub genes with consistent survival effects in the GSE20685 and TCGA data sets: SERPINB5, KRT14, MIA, and SFRP1.
decisive
false
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[0]
Weighted Gene Co-expression Network Analysis (WGCNA)
[1]
hierarchical clustering analysis
[2]
module conservation analysis
[3]
principal component analysis
[4]
gene ontology (GO) analysis
[5]
Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis
[6]
survival analysis
[7]
co-expression analysis
[8]
immune infiltration analysis
[9]
pan-cancer analysis
[10]
chemosensitivity prediction
[11]
gene set variation analysis (GSVA)
[12]
mutational-profile analysis
minimax_alt array · 12 items
[0]
Weighted Gene Co‐expression Network Analysis (WGCNA)
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hierarchical clustering using weighted correlation
[2]
module conservation analysis
[3]
principal-component-based module analysis
[4]
survival analysis (specific statistical test not stated)
[5]
Gene Ontology and KEGG functional enrichment analysis
[6]
co‐expression analysis
[7]
TIMER-based immune infiltration analysis
[8]
pan-cancer gene-expression analysis
[9]
pRRophetic chemosensitivity prediction using regression and 10‐fold cross‐validation
[10]
gene set variation analysis (GSVA)
[11]
tumor mutational burden and microsatellite instability association analysis
decisive
false
statistical_method object · 3 fields
minimax
Weighted Gene Co-expression Network Analysis (WGCNA)
minimax_alt
Weighted Gene Co‐expression Network Analysis (WGCNA)
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true
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decisive_fields
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null
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null
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null
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step:run_analysis input 'materials:the source data behind the published result in pmid:38477438' does not resolve to a declared asset
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targets
Complete file
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Then, we conducted survival analysis on the transcriptional data of BRCA in TCGA, and ultimately determined four hub genes that maintained consistent survival effects in both data sets (Figure 2C,D).\",\"target_result\":\"The paper reports that four hub genes maintained consistent survival effects in both the GSE20685 and TCGA datasets.\",\"number_stated\":true}", "reading": {"parent_value": 4, "unit": "hub genes", "evidence": "13 genes that significantly impacted patient prognosis were found when we performed a survival study on these 50 genes. Then, we conducted survival analysis on the transcriptional data of BRCA in TCGA, and ultimately determined four hub genes that maintained consistent survival effects in both data sets (Figure 2C,D).", "target_result": "The paper reports that four hub genes maintained consistent survival effects in both the GSE20685 and TCGA datasets.", "number_stated": true, "source_locator": "chars 6901-7220 of source sha256 18218b95e4529026df9f273a22b69b580ad5fc25e2d0bc08a7a273173fd91050"}, "recorded_at": "2026-10-31T15:19:16.688692+00:00"}, {"provider": "minimax_alt", "model": "MiniMax-M3", "prompt_version": "replication-target-v2", "prompt_hash": "3996adb3dfa60a5da5d40e3897827d1e3ee68701c9e8a8ae74315bd010cff470", "source_hash": "18218b95e4529026df9f273a22b69b580ad5fc25e2d0bc08a7a273173fd91050", "raw_response": "<think>We need answer JSON only. Need interpret target: headline numerical result paper states for main finding. Main finding four hub genes? Registered target says \"the headline numerical result the paper states for its main finding\". Likely number = four, unit perhaps \"hub genes\" or \"genes\"? Need exact contiguous quote contains number and attribution. Text: \"We found six modules...\" but main finding ultimately four hub genes. Abstract: \"Four hub genes were identified based on...\" Exact number word not numeral? User asks numerical result, value paper states, unit paper prints. parent_value number 4, unit maybe \"hub genes\". Evidence exact contiguous quotation. \"Four hub genes were identified based on the Weighted Gene Co‐expression Network Analysis.\" That supports 4 hub genes, but target wording \"headline numerical result ... main finding\" perhaps yes. They emphasize exact contiguous quotation contains number. Number spelled \"Four\", does that count? likely yes. Unit \"hub genes\" (paper prints). Could also evidence \"These findings pinpoint four crucial genes in BC progression...\" unit genes. Need single result.\n\nLet's scrutinize. User says registered target \"the headline numerical result the paper itself states for its main finding.\" They want numerical result replication must reproduce. Main finding likely four hub genes. Headline number 4, unit \"hub genes\". The exact quote perhaps must include a number (word accepted?) Evidence \"Four hub genes were identified based on the Weighted Gene Co‐expression Network Analysis.\" Contiguous exact. target_result likely \"Four hub genes were identified.\" Or perhaps target_result should describe \"Four hub genes identified...\" Number stated true.\n\nCould unit be \"hub genes\" exactly. parent_value 4. JSON valid, preserving special hyphen not relevant. Evidence exact quote. Need no markdown.</think>\n\n{\"parent_value\":4,\"unit\":\"hub genes\",\"evidence\":\"Four hub genes were identified based on the Weighted Gene Co‐expression Network Analysis.\",\"target_result\":\"Four hub genes were identified.\",\"number_stated\":true}", "reading": {"parent_value": 4, "unit": "hub genes", "evidence": "Four hub genes were identified based on the Weighted Gene Co‐expression Network Analysis.", "target_result": "Four hub genes were identified.", "number_stated": true, "source_locator": "chars 533-622 of source sha256 18218b95e4529026df9f273a22b69b580ad5fc25e2d0bc08a7a273173fd91050"}, "recorded_at": "2026-10-31T15:19:18.705705+00:00"}], "agreement": false, "disagreements": {"target_result": {"minimax": "Four hub genes associated with breast cancer prognosis were identified: SERPINB5, Keratin 14 (KRT14), melanoma-inhibiting activity (MIA), and Secreted Frizzled-Related Protein 1 (SFRP1).", "minimax_alt": "The study identified four breast-cancer hub genes with consistent survival effects in the GSE20685 and TCGA data sets: SERPINB5, KRT14, MIA, and SFRP1.", "decisive": false}, "analysis_methods": {"minimax": ["Weighted Gene Co-expression Network Analysis (WGCNA)", "hierarchical clustering analysis", "module conservation analysis", "principal component analysis", "gene ontology (GO) analysis", "Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis", "survival analysis", "co-expression analysis", "immune infiltration analysis", "pan-cancer analysis", "chemosensitivity prediction", "gene set variation analysis (GSVA)", "mutational-profile analysis"], "minimax_alt": ["Weighted Gene Co‐expression Network Analysis (WGCNA)", "hierarchical clustering using weighted correlation", "module conservation analysis", "principal-component-based module analysis", "survival analysis (specific statistical test not stated)", "Gene Ontology and KEGG functional enrichment analysis", "co‐expression analysis", "TIMER-based immune infiltration analysis", "pan-cancer gene-expression analysis", "pRRophetic chemosensitivity prediction using regression and 10‐fold cross‐validation", "gene set variation analysis (GSVA)", "tumor mutational burden and microsatellite instability association analysis"], "decisive": false}, "statistical_method": {"minimax": "Weighted Gene Co-expression Network Analysis (WGCNA)", "minimax_alt": "Weighted Gene Co‐expression Network Analysis (WGCNA)", "decisive": true}}, "agreement_basis": {"policy": "decisive_fields", "decisive_fields": ["work_type", "number_stated", "parent_value", "unit"]}, "blinded": true}, "human_critique": {"status": "not_run", "reviewer": null, "signed_at": null, "conflict_checked": false, "commentary": null}, "stages": [{"key": "target_materials", "status": "pending", "reason": null, "evidence": null}, {"key": "independent_readings", "status": "blocked", "reason": "The independent readings are incomplete or disagree; the source evidence must resolve the difference.", "evidence": {"provider_errors": []}}, {"key": "source_resolution", "status": "pending", "reason": null, "evidence": null}, {"key": "protocol_reconstruction", "status": "pending", "reason": null, "evidence": null}, {"key": "control_execution", "status": "pending", "reason": null, "evidence": null}, {"key": "control_comparison", "status": "pending", "reason": null, "evidence": null}, {"key": "publication", "status": "pending", "reason": null, "evidence": null}], "gaps": ["review.human_critique", "review.machine_critique.blocked"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "package:096fda2433c9c837c2d51e43ee93d44529a476e14bce7944327b0f990355cca9", "type": "sep_package", "label": "SEP v1 package for pmid:38477438"}], "activities": [{"id": "activity:conversion:pmid:38477438", "type": "conversion", "used": ["package:096fda2433c9c837c2d51e43ee93d44529a476e14bce7944327b0f990355cca9"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:minimax", "type": "model", "label": "minimax"}, {"id": "agent:minimax_alt", "type": "model", "label": "minimax_alt"}, {"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}], "source_run_id": "run-20261023T122449232913", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "3e070471-483b-464a-842f-a420964861eb", "parent_hash": "096fda2433c9c837c2d51e43ee93d44529a476e14bce7944327b0f990355cca9", "fork_of": null, "generation": 1}, "gaps": ["abstract", "asset:source:pmid:38477438 not verified", "authors", "capability", "corpus_record_absent", "execution.not_run", "method", "review.human_critique", "review.machine_critique.blocked", "step:obtain_source_data blocked on data:not_downloaded", "step:run_analysis blocked on no owned computational capability is bound to this experiment", "step:run_analysis input 'materials:the source data behind the published result in pmid:38477438' does not resolve to a declared asset", "targets"]}