Identification of a novel immune-related gene signature by single-cell and bulk sequencing for the prediction of the immune landscape and prognosis of breast cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:39627792", "kind": "science-record", "revision": 3, "content_hash": "sha256:7a53dc6db225b4de5fa29b66676ecfb0f07dc2e83d635b3897996c9cda38c481", "created_at": "2026-11-01T20:29:54Z", "updated_at": "2026-11-01T22:13:14Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification of a novel immune-related gene signature by single-cell and bulk sequencing for the prediction of the immune landscape and prognosis of breast cancer.", "doi": "10.1186/s12935-024-03589-7", "pmid": "39627792", "authors": ["Yanlin Gu", "Zhengyang Feng", "Xiaoyan Xu", "Liyan Jin"], "journal": "Cancer cell international", "year": 2024, "abstract": "BACKGROUND: As a common cause of cancer-related deaths in women, BRCA (breast cancer) shows complexity and requires precise biomarkers and treatment methods. This study delves into the molecular makeup of BRCA, focusing on immune profiles, molecular subtypes, gene expression and single-cell analysis.\nMETHODS: XCell was used to assess immune infiltration based on TCGA (the Cancer Genome Atlas) data and the clustering analysis was made. Differentially expressed genes were examined in distinct clusters, and the WGCNA (weighted correlation network analysis) was made to establish co-expression networks. The prognostic models were developed by Cox and LASSO-Cox regression. The clustering analysis, GSEA (Gene set enrichment analysis), GSVA (gene set variation analysis) and communication analysis of the single-cell dataset GSE161529 were performed to investigate the functional relevance. Real-time polymerase chain reaction (RT-PCR) was employed for evaluating gene expression.\nRESULTS: The results revealed significant differences in immune cell infiltration between two clusters (C1 and C2). C2 had poorer survival outcomes, which was associated with higher expression of immune checkpoints PD1 and PD-L1. The gene modules identified via WGCNA were correlated with the immune-based subtypes. Then, a prognostic model comprising seven genes (ACSL1, ABCB5, XG, ADH4, OPN4, NPR3, NLGN1) was used to divide patients into high- and low-risk subgroups. The high-risk group had worse prognosis and higher scores of TIDE (Tumor Immune Dysfunction and Exclusion). The single-cell analysis depicted the immune landscape. Macrophages and endothelial cells exhibited higher AUCell scores. In cellular communication analysis, notably significant ligand-receptor interactions of HLA-DRA-> CD4 and TNFSF13B-> HLA-DPB1 were observed. The proportion of endothelial cells was correlated with risk scores. Finally, RT-PCR results illustrated the expression of seven genes in BRCA specimens.\nCONCLUSION: The integrative analysis provides new insights into molecular complexities of BRCA. Immune profiles and gene signatures hold potential for improving stratification of BRCA patients and guiding the development of personalized immunotherapy strategies.", "claims": [{"id": "claim-method", "statement": "The prognostic models were developed by Cox and LASSO-Cox regression.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39627792", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "The prognostic models were developed by Cox and LASSO-Cox regression."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The data analyzed in this study could be obtained from TCGA and GEO database.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:39627792", "locator": "sections[36] \"notes\" paragraph 1", "quote": "The data analyzed in this study could be obtained from TCGA and GEO database."}], "state": "complete"}, {"id": "claim-target-result", "statement": "A prognostic model comprising seven genes was used to divide patients into high- and low-risk subgroups, with the high-risk group exhibiting worse prognosis and higher TIDE scores.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:39627792", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "Then, a prognostic model comprising seven genes (ACSL1, ABCB5, XG, ADH4, OPN4, NPR3, NLGN1) was used to divide patients into high- and low-risk subgroups."}, {"asset": "source:pmid:39627792", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "The high-risk group had worse prognosis and higher scores of TIDE (Tumor Immune Dysfunction and Exclusion)."}, {"asset": "source:pmid:39627792", "locator": "sections[24] \"Construction of prognostic model\" paragraph 5", "quote": "The high-risk group exhibited significantly higher TIDE scores than the low-risk group."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "A prognostic model comprising seven genes was used to divide patients into high- and low-risk subgroups, with the high-risk group exhibiting worse prognosis and higher TIDE scores.", "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:39627792"], "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:GSE161529"], "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:GSE161529"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:39627792", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1186/s12935-024-03589-7", "sha256": "sha256:4dacf696fa5b6beba9d9f2249741607558d1599a0660ed092cc87e689d64cd3d", "bytes": 62562, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1186/s12935-024-03589-7", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11613745", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE161529", "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=GSE161529", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE161529", "version": null, "note": "The data analyzed in this study could be obtained from TCGA and GEO database.", "structure": {"repository": "GEO", "access_route": "GEO accession URL", "access_statement_verbatim": "The data analyzed in this study could be obtained from TCGA and GEO database.", "access_statement_kind": "data_availability_statement", "sample_accessions": ["GSM4909253", "GSM4909254", "GSM4909255", "GSM4909256", "GSM4909257", "GSM4909258", "GSM4909259", "GSM4909260", "GSM4909261", "GSM4909262", "GSM4909263", "GSM4909264", "GSM4909265", "GSM4909266", "GSM4909267", "GSM4909268", "GSM4909269", "GSM4909270", "GSM4909271", "GSM4909272", "GSM4909273", "GSM4909274", "GSM4909275", "GSM4909276", "GSM4909277", "GSM4909278", "GSM4909279", "GSM4909280", "GSM4909281", "GSM4909282", "GSM4909283", "GSM4909284", "GSM4909285", "GSM4909286", "GSM4909287", "GSM4909288", "GSM4909289", "GSM4909290", "GSM4909291", "GSM4909292", "GSM4909293", "GSM4909294", "GSM4909295", "GSM4909296", "GSM4909297", "GSM4909298", "GSM4909299", "GSM4909300", "GSM4909301", "GSM4909302", "GSM4909303", "GSM4909304", "GSM4909305", "GSM4909306", "GSM4909307", "GSM4909308", "GSM4909309", "GSM4909310", "GSM4909311", "GSM4909312", "GSM4909313", "GSM4909314", "GSM4909315", "GSM4909316", "GSM4909317", "GSM4909318", "GSM4909319", "GSM4909320", "GSM4909321"], "sample_count": 69, "group_sizes": null, "group_sizes_basis": null, "platform": "18573", "taxon": "Homo sapiens", "title": "scRNA-seq profiling of breast cancer tumors, BRCA1 mutant pre-neoplastic mammary gland cells and normal mammary gland cells", "resolution_checked_at": "2026-11-01T17:30:42Z", "resolution_check": "identifier_resolution_only_no_download_no_licence_read", "downloaded": false, "licence_read": false}}], "gaps": ["asset:data:geo:GSE161529 not downloaded", "asset:data:geo:GSE161529 licence not read"]}, "analysis": {"state": "partial", "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": "The prognostic models were developed by Cox and LASSO-Cox regression."}}, {"id": "method-2", "family": "group_comparison", "specific": "mann_whitney", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_mann_whitney"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Mann-Whitney"}}, {"id": "method-3", "family": "group_comparison", "specific": "wilcoxon", "label": "Group comparison", "dsl_operations": [], "missing_operations": ["group_comparison_wilcoxon"], "expressible": false, "parameters": {}, "data_shapes": ["two_or_more_groups_continuous"], "evidence": {"score": 0.8, "band": "high", "quote": "Wilcoxon"}}, {"id": "method-4", "family": "survival_analysis", "specific": "kaplan_meier", "label": "Survival analysis", "dsl_operations": ["survival_km"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "KM"}}, {"id": "method-5", "family": "survival_analysis", "specific": "log_rank_test", "label": "Survival analysis", "dsl_operations": ["logrank_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["time_to_event_with_censoring"], "evidence": {"score": 0.8, "band": "high", "quote": "Log-rank"}}, {"id": "method-6", "family": "clustering", "specific": "hierarchical", "label": "Clustering", "dsl_operations": ["hierarchical_cluster"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["feature_matrix"], "evidence": {"score": 0.8, "band": "high", "quote": "dendrogram"}}, {"id": "method-7", "family": "network_analysis", "specific": "pathway_enrichment", "label": "Network / pathway analysis", "dsl_operations": ["pathway_enrich"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["edge_list"], "evidence": {"score": 0.8, "band": "high", "quote": "GO enrichment"}}], "targets": [], "gaps": ["method.reader_differs_from_extractor"]}, "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": ["GSE161529"], "resolved_accessions": ["GSE161529"], "statements": ["The data analyzed in this study could be obtained from TCGA and GEO database."], "basis": "The paper names GSE161529 in GEO (Gene Expression Omnibus) database 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:39627792", "data:geo:GSE161529"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:GSE161529"]}, "gaps": []}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T19:40:30Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 15178, "completion_tokens": 1841, "cached_tokens": 264}}, "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:39627792", "type": "paper", "label": "pmid:39627792"}, {"id": "source:pmid:39627792", "type": "manuscript", "label": "PMID 39627792 full text"}, {"id": "data:geo:GSE161529", "type": "dataset", "label": "GEO GSE161529"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:39627792", "type": "paper", "label": "pmid:39627792"}, {"id": "source:pmid:39627792", "type": "manuscript", "label": "PMID 39627792 full text"}, {"id": "data:geo:GSE161529", "type": "dataset", "label": "GEO GSE161529"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-39627792", "type": "extraction", "used": ["source:pmid:39627792"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-GSE161529", "type": "accession_resolution", "used": ["data:geo:GSE161529"], "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:39627792", "parent_hash": "sha256:4400fb71f1e94ee04ad7529cb0482400acb142c4300cbe63c646f1c5ed2008e4", "fork_of": null, "generation": 2}, "gaps": ["asset:data:geo:GSE161529 licence not read", "asset:data:geo:GSE161529 not downloaded", "execution.not_run", "method.reader_differs_from_extractor", "review.human_critique", "review.independent_reader", "review.machine_critique"], "assays": [{"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": ["The prognostic models were developed by Cox and LASSO-Cox regression."], "order_basis": "analysis_only", "id": "assay:1"}]}