Identification and Validation of Novel Metastasis-Related Immune Gene Signature in Breast Cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:38634039", "kind": "science-record", "revision": 4, "content_hash": "sha256:393e352da847744088695ba60e4e4f7434599675ae656b50a27c5961d3c643fb", "created_at": "2026-11-01T19:20:36Z", "updated_at": "2026-11-01T22:11:42Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Identification and Validation of Novel Metastasis-Related Immune Gene Signature in Breast Cancer.", "doi": "10.2147/BCTT.S448642", "pmid": "38634039", "authors": ["Shen Ma", "Ran Hao", "Yi-Wei Lu", "Hui-Po Wang", "Jie Hu", "Yi-Xin Qi"], "journal": "Breast cancer (Dove Medical Press)", "year": 2024, "abstract": "Background: Distant metastasis remains the leading cause of death among patients with breast cancer (BRCA). The process of cancer metastasis involves multiple mechanisms, including compromised immune system. However, not all genes involved in immune function have been comprehensively identified.\nMethods: Firstly 1623 BRCA samples, including transcriptome sequencing and clinical information, were acquired from Gene Expression Omnibus (GSE102818, GSE45255, GSE86166) and The Cancer Genome Atlas-BRCA (TCGA-BRCA) dataset. Subsequently, weighted gene co-expression network analysis (WGCNA) was performed using the GSE102818 dataset to identify the most relevant module to the metastasis of BRCA. Besides, ConsensusClusterPlus was applied to divide TCGA-BRCA patients into two subgroups (G1 and G2). In the meantime, the least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a metastasis-related immune genes (MRIGs)_score to predict the metastasis and progression of cancer. Importantly, the expression of vital genes was validated through reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC).\nResults: The expression pattern of 76 MRIGs screened by WGCNA divided TCGA-BRCA patients into two subgroups (G1 and G2), and the prognosis of G1 group was worse. Also, G1 exhibited a higher mRNA expression level based on stemness index score and Tumor Immune Dysfunction and Exclusion score. In addition, higher MRIGs_score represented the higher probability of progression in BRCA patients. It was worth mentioning that the patients in the G1 group had a high MRIGs_score than those in the G2 group. Importantly, the results of RT-qPCR and IHC demonstrated that fasciculation and elongation protein zeta 1 (FEZ1) and insulin-like growth factor 2 receptor (IGF2R) were risk factors, while interleukin (IL)-1 receptor antagonist (IL1RN) was a protective factor.\nConclusion: Our study revealed a prognostic model composed of eight immune related genes that could predict the metastasis and progression of BRCA. Higher score represented higher metastasis probability. Besides, the consistency of key genes in BRCA tissue and bioinformatics analysis results from mRNA and protein levels was verified.", "claims": [{"id": "claim-method", "statement": "Then, by LASSO Cox regression algorithm, a model was established with 10-fold cross-validation based on the selected genes.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38634039", "locator": "sections[13] \"Generation of the Prognostic MRIGs_score\" paragraph 2", "quote": "Then, by LASSO Cox regression algorithm, a model was established with 10-fold cross-validation based on the selected genes."}], "state": "complete"}, {"id": "claim-data-access", "statement": "This study analyzed data from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus data base (GEO) (https://ncbi.nlm.nih.gov/geo/). These data are free and publicly available.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:38634039", "locator": "sections[32] \"Data Sharing Statement\" paragraph 2", "quote": "This study analyzed data from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus data base (GEO) (https://ncbi.nlm.nih.gov/geo/). These data are free and publicly available."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The LASSO-derived MRIGs_score showed acceptable discrimination of 1-, 2-, and 4-year progression-free survival in the TCGA-BRCA training set, with AUC values of 0.739, 0.736, and 0.694, respectively.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:38634039", "locator": "sections[25] \"Prognostic Value and Features of Prognostic Risk Model in the Training Set\" paragraph 2", "quote": "In addition, according to MRIGs_score, the 1-, 2-, and 4-year survival area under the curve (AUC) values of TCGA-BRCA patients were 0.739, 0.736, and 0.694, respectively (Figure 7B)."}, {"asset": "source:pmid:38634039", "locator": "sections[25] \"Prognostic Value and Features of Prognostic Risk Model in the Training Set\" paragraph 2", "quote": "The results demonstrated that MRIGs_score model exhibited an acceptable discriminatory ability for BRCA patients’ PFS."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The LASSO-derived MRIGs_score showed acceptable discrimination of 1-, 2-, and 4-year progression-free survival in the TCGA-BRCA training set, with AUC values of 0.739, 0.736, and 0.694, respectively.", "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:38634039"], "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:GSE102818"], "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:GSE102818"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:38634039", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.2147/BCTT.S448642", "sha256": "sha256:9d3d4eef1969aa026e8990df9c28c93c00a46c7bb6f431955cbd535152ef326f", "bytes": 50250, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.2147/BCTT.S448642", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC11021863", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE102818", "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=GSE102818", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE102818", "version": null, "note": "This study analyzed data from The Cancer Genome Atlas (TCGA) (https://portal.gdc.cancer.gov/) and Gene Expression Omnibus data base (GEO) (https://ncbi.nlm.nih.gov/geo/). 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Results: Th", "in the G2 group. Importantly, the results of RT-qPCR and IHC demonstrated that fasciculation and", "n quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Results: Th", "the G2 group. Importantly, the results of RT-qPCR and IHC demonstrated that fasciculation and"], "order_basis": "paper_text_order:1199", "id": "assay:1"}, {"role": "data_generation", "definition_id": "ihc", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["tive polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Results: The expression pattern of 76", "reaction (RT-qPCR) and immunohistochemistry (IHC). Results: The expression pattern of 76 MRIG", "oup. Importantly, the results of RT-qPCR and IHC demonstrated that fasciculation and elongati", "was washed clean and placed in formalin for immunohistochemistry (IHC). The study was approved by Ethics Comm"], "order_basis": "paper_text_order:1212", "id": "assay:2"}, {"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": ["Then, by LASSO Cox regression algorithm, a model was established with 10-fold cross-validation based on the selected genes."], "order_basis": "consumes_earlier_output", "id": "assay:3"}]}