Characterization of metastasis-specific macrophages in colorectal cancer for prognosis prediction and immunometabolic remodeling.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39487182", "kind": "science-record", "revision": 2, "content_hash": "sha256:2ff338589ae45cdc6688f68cbab53f0cb4d4335757c9e92add1ea12c4e8bf07b", "created_at": "2026-11-01T20:29:44Z", "updated_at": "2026-11-01T21:34:15Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Characterization of metastasis-specific macrophages in colorectal cancer for prognosis prediction and immunometabolic remodeling.", "doi": "10.1038/s41598-024-77248-2", "pmid": "39487182", "authors": ["Yang Hua", "Xiukun Ma", "Xinyu Zhao", "Xiaomeng Wei", "Xiaojing Mu", "XiPeng Zhang"], "journal": "Scientific reports", "year": 2024, "abstract": "This study develops a prognostic model to predict metastasis and prognosis in colorectal cancer liver metastases by identifying distinct macrophage subsets. Using scRNA-seq data from primary colorectal cancer and liver metastases, we dissected the cellular landscape to find unique macrophage subpopulations, particularly EEF1G + macrophages, which were prevalent in liver metastases. The study leveraged data from GSE231559, TCGA, and GEO databases to construct an 8-gene risk model named EMGS, based on the EEF1G + macrophage gene signature. Patients were divided into high-risk and low-risk groups using the median EMGS score, with the high-risk group showing significantly worse survival. This group also demonstrated upregulated pathways associated with tumor progression, such as epithelial-mesenchymal transition and angiogenesis, and downregulated metabolic pathways. Moreover, the high-risk group presented an immunosuppressive microenvironment, with a higher TIDE score indicating lower effectiveness of immunotherapy. The study identifies potential drugs targeting the high-risk group, suggesting therapeutic avenues to improve survival. Conclusively, the EMGS score identifies colorectal cancer patients at high risk of liver metastases, highlighting the role of specific macrophage subsets in tumor progression and providing a basis for personalized treatment strategies.", "claims": [{"id": "claim-method", "statement": "Subsequently, these genes were assessed using the least absolute shrinkage and selection operator (LASSO) method in Cox proportional hazards regression, employing the ‘glmnet’ package in R.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39487182", "locator": "sections[15] \"Construction and validation of the prognostic signature\" paragraph 2", "quote": "Subsequently, these genes were assessed using the least absolute shrinkage and selection operator (LASSO) method in Cox proportional hazards regression, employing the ‘glmnet’ package in R."}], "state": "complete"}, {"id": "claim-data-access", "statement": "We sourced the single-cell RNA-seq dataset from the Gene Expression Omnibus (GEO) database using the accession number GSE231559. The TCGA-COAD cohort dataset was obtained from The Cancer Genome Atlas (TCGA) portal, available at https://portal.gdc.cancer.gov/. For validation purposes, we also retrieved datasets GSE29621, GSE17536, and GSE39582 from the GEO database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39487182", "locator": "sections[25] \"Data availability\" paragraph 2", "quote": "We sourced the single-cell RNA-seq dataset from the Gene Expression Omnibus (GEO) database using the accession number GSE231559. The TCGA-COAD cohort dataset was obtained from The Cancer Genome Atlas (TCGA) portal, available at https://portal.gdc.cancer.gov/. For validation purposes, we also retrieved datasets GSE29621, GSE17536, and GSE39582 from the GEO database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "In the TCGA-COAD training set, the EMGS-high group demonstrated significantly higher mortality risk and lower overall survival rates (Fig. 4A, HR = 2.5, 95% CI: 1.77–3.54, P < 0.0001).", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "In the TCGA-COAD training set, the EMGS-high group demonstrated significantly higher mortality risk and lower overall survival rates (Fig. 4A, HR = 2.5, 95% CI: 1.77–3.54, P < 0.0001)."}, "evidence": [{"asset": "source:pmid:39487182", "locator": "sections[6] \"Performance of the EMGS Signature in training and validation cohorts\" paragraph 2", "quote": "In the TCGA-COAD training set, the EMGS-high group demonstrated significantly higher mortality risk and lower overall survival rates (Fig. 4A, HR = 2.5, 95% CI: 1.77–3.54, P < 0.0001)."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "In the TCGA-COAD training set, the EMGS-high group demonstrated significantly higher mortality risk and lower overall survival rates (Fig. 4A, HR = 2.5, 95% CI: 1.77–3.54, P < 0.0001).", "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:39487182"], "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:GSE17536"], "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:GSE17536"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39487182", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1038/s41598-024-77248-2", "sha256": "sha256:53bdd947e412ec266c1d32104053d560add16718934333390a60d216fbb12de2", "bytes": 49421, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1038/s41598-024-77248-2", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11530676", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE17536", "role": "raw", "format": "geo-series", "media_type": "application/vnd.ncbi.geo-series+json", "uri": "https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE17536", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE17536", "version": null, "note": "We sourced the single-cell RNA-seq dataset from the Gene Expression Omnibus (GEO) database using the accession number GSE231559. 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subtypes with distinct clinical, molecular and survival characteristics [Expression]", "resolution_checked_at": "2026-11-01T15:39:54Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE17536 not downloaded", "asset:data:geo:GSE17536 licence not read", "asset:data:geo:GSE178318 not downloaded", "asset:data:geo:GSE178318 licence not read", "asset:data:geo:GSE231559 not downloaded", "asset:data:geo:GSE231559 licence not read", "asset:data:geo:GSE29621 not downloaded", "asset:data:geo:GSE29621 licence not read", "asset:data:geo:GSE39582 not downloaded", "asset:data:geo:GSE39582 licence not read"]}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "family": "survival_analysis", "specific": "cox_proportional_hazards", "label": "Survival analysis", "dsl_operations": ["cox_ph"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 1.0, "band": "verbatim", "quote": "Subsequently, these genes were assessed using the least absolute shrinkage and selection operator (LASSO) method in Cox proportional hazards regression, employing the ‘glmnet’ package in R."}}], "targets": [{"id": "target-published-estimate", "claim_id": "claim-target-result", "operation": "cox_ph", "expected_value": 95.0, "unit": "per cent", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none."}, {"id": "target-published-estimate-hazard-ratio", "claim_id": "claim-target-result", "operation": "cox_ph", "expected_value": 2.5, "unit": "hazard ratio", "tolerance": null, "state": "complete", "note": "The published estimate as the reader quoted it from the paper. No tolerance is published because the paper states none."}, {"id": "target-published-estimate-p-value", "claim_id": "claim-target-result", "operation": "cox_ph", "expected_value": 0.0001, "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."}], "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": ["cox_ph"], "missing_operations": [], "basis": "The paper names the method it used and the corpus's method extractor maps it onto the DSL catalogue: cox_proportional_hazards."}, "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": ["GSE231559", "GSE178318", "GSE29621", "GSE17536", "GSE39582"], "resolved_accessions": ["GSE231559", "GSE178318", "GSE29621", "GSE17536", "GSE39582"], "statements": ["We sourced the single-cell RNA-seq dataset from the Gene Expression Omnibus (GEO) database using the accession number GSE231559. The TCGA-COAD cohort dataset was obtained from The Cancer Genome Atlas (TCGA) portal, available at https://portal.gdc.cancer.gov/. For validation purposes, we also retrieved datasets GSE29621, GSE17536, and GSE39582 from the GEO database."], "basis": "The paper names GSE231559, GSE178318, GSE29621, GSE17536, GSE39582 in Gene Expression Omnibus (GEO) and the accession resolves in the repository. No dataset was downloaded and no licence was read."}}, "can_run": {"dsl_operations": ["cox_ph"], "assets": ["source:pmid:39487182", "data:geo:GSE17536"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE17536"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:37:18Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 12924, "completion_tokens": 2400, "cached_tokens": 256}}, "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:39487182", "type": "paper", "label": "pmid:39487182"}, {"id": "source:pmid:39487182", "type": "manuscript", "label": "PMID 39487182 full text"}, {"id": "data:geo:GSE17536", "type": "dataset", "label": "GEO GSE17536"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:39487182", "type": "paper", "label": "pmid:39487182"}, {"id": "source:pmid:39487182", "type": "manuscript", "label": "PMID 39487182 full text"}, {"id": "data:geo:GSE17536", "type": "dataset", "label": "GEO GSE17536"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-39487182", "type": "extraction", "used": ["source:pmid:39487182"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE17536", "type": "accession_resolution", "used": ["data:geo:GSE17536"], "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:39487182", "parent_hash": "sha256:7e9de9e2c7976fb21eb2c0a76cf1caed0ec4953439fae0435ac7cb184f5d602e", "fork_of": null, "generation": 1}, "gaps": ["asset:data:geo:GSE17536 licence not read", "asset:data:geo:GSE17536 not downloaded", "asset:data:geo:GSE178318 licence not read", "asset:data:geo:GSE178318 not downloaded", "asset:data:geo:GSE231559 licence not read", "asset:data:geo:GSE231559 not downloaded", "asset:data:geo:GSE29621 licence not read", "asset:data:geo:GSE29621 not downloaded", "asset:data:geo:GSE39582 licence not read", "asset:data:geo:GSE39582 not downloaded", "execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"role": "data_generation", "definition_id": "scrna_seq", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "unsupported", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["entifying distinct macrophage subsets. Using scRNA-seq data from primary colorectal cancer and live"], "order_basis": "paper_text_order:248", "id": "assay:1"}, {"role": "analysis", "definition_id": "survival_analysis", "definition_version": "f2132e96ae6c7a4e", "definition_digest": null, "required_operations": ["cox_ph"], "support_state": "supported", "source_hashes": {"dsl_catalogue": "f2132e96ae6c7a4e"}, "confidence": 1.0, "evidence": ["Subsequently, these genes were assessed using the least absolute shrinkage and selection operator (LASSO) method in Cox proportional hazards regression, employing the ‘glmnet’ package in R."], "order_basis": "consumes_earlier_output", "id": "assay:2"}]}