Copy Number Profiling of MammaPrint™ Genes Reveals Association with the Prognosis of Breast Cancer Patients.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:28970850", "kind": "science-record", "revision": 7, "content_hash": "sha256:fb635f0fce6b53a3dcfbf37999d10eac48c194b998bdf9380a5c395dd672938f", "created_at": "2026-11-01T15:40:28Z", "updated_at": "2026-11-01T22:43:07Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Copy Number Profiling of MammaPrint™ Genes Reveals Association with the Prognosis of Breast Cancer Patients.", "doi": "10.4048/jbc.2017.20.3.246", "pmid": "28970850", "authors": ["Areej Fatima", "Fomaz Tariq", "Muhammad Faraz Arshad Malik", "Muhammad Qasim", "Farhan Haq"], "journal": "Journal of breast cancer", "year": 2017, "abstract": "PURPOSE: The MammaPrint™ gene signature, currently used in clinical practice, provides prognostic information regarding the recurrence and potential metastasis in breast cancer patients. However, the prognostic information of the 70 genes included can only be estimated at the RNA expression level. In this study, we investigated whether copy number information of MammaPrint™ genes at the DNA level can be used as a prognostic tool for breast cancer, as copy number variations (CNVs) are major contributors to cancer progression.\nMETHODS: We performed CNV profiling of MammaPrint™ genes in 59 breast cancer cell lines and 650 breast cancer patients, using publicly available data in The Cancer Genome Atlas (TCGA) database. Statistical analyses including Fisher exact test, chi-square test, and Kaplan-Meier survival analyses were performed.\nRESULTS: All MammaPrint™ genes showed recurrent CNVs, particularly in TCGA cohort. CNVs of 32 and 36 genes showed significant associations with progesterone receptor and estrogen rector, respectively. No genes showed a significant association with human epidermal growth factor receptor 2 status and lymph node status. In addition, only six genes were associated with tumor stages. RFC4, HRASLS, NMU, GPR126, SCUBE2, C20orf46, and EBF4 were associated with reduced survival and RASSF7 and ESM1 were associated with reduced disease-free survival.\nCONCLUSION: Based on these findings, a concordance of CNV-based genomic rearrangement with expression profiling of these genes and their putative roles in disease tumorigenesis was established. The results suggested that the CNV profiles of the MammaPrint™ genes can be used to predict the prognosis of breast cancer patients. In addition, this approach may lead to the development of new cancer biomarkers at the DNA level.", "claims": [{"id": "claim-method", "statement": "All statistical tests were performed using SPSS version 20.0 (IBM Corp., Armonk, USA), including Fisher exact test, chi-square test, and Kaplan-Meier overall survival and disease-free survival analyses. p-values were two-sided and p<0.05 was considered statistically significant. For data analysis of 59 breast cancer cell lines, we downloaded logR values generated by the CCLE database (https://portals.broadinstitute.org/ccle). Additionally, CNV values of breast cancer data for 773 patients was downloaded from TCGA database [3].", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28970850", "locator": "sections[4] \"Statistical analysis\" paragraph 2", "quote": "All statistical tests were performed using SPSS version 20.0 (IBM Corp., Armonk, USA), including Fisher exact test, chi-square test, and Kaplan-Meier overall survival and disease-free survival analyses. p-values were two-sided and p<0.05 was considered statistically significant."}, {"asset": "source:pmid:28970850", "locator": "sections[3] \"Study design\" paragraph 3", "quote": "For data analysis of 59 breast cancer cell lines, we downloaded logR values generated by the CCLE database (https://portals.broadinstitute.org/ccle)."}, {"asset": "source:pmid:28970850", "locator": "sections[3] \"Study design\" paragraph 3", "quote": "Additionally, CNV values of breast cancer data for 773 patients was downloaded from TCGA database [3]."}], "state": "complete"}, {"id": "claim-data-access", "statement": "For data analysis of 59 breast cancer cell lines, we downloaded logR values generated by the CCLE database (https://portals.broadinstitute.org/ccle).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:28970850", "locator": "sections[3] \"Study design\" paragraph 3", "quote": "For data analysis of 59 breast cancer cell lines, we downloaded logR values generated by the CCLE database (https://portals.broadinstitute.org/ccle)."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The results suggested that the CNV profiles of the MammaPrint™ genes can be used to predict the prognosis of breast cancer patients.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:28970850", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "We performed CNV profiling of MammaPrint™ genes in 59 breast cancer cell lines and 650 breast cancer patients, using publicly available data in The Cancer Genome Atlas (TCGA) database."}, {"asset": "source:pmid:28970850", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Statistical analyses including Fisher exact test, chi-square test, and Kaplan-Meier survival analyses were performed."}, {"asset": "source:pmid:28970850", "locator": "sections[0] \"Abstract\" paragraph 4", "quote": "The results suggested that the CNV profiles of the MammaPrint™ genes can be used to predict the prognosis of breast cancer patients."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The results suggested that the CNV profiles of the MammaPrint™ genes can be used to predict the prognosis of breast cancer patients.", "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:28970850"], "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": "blocked", "blocked_on": "data:accession_absent", "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": [], "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": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:28970850", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.4048/jbc.2017.20.3.246", "sha256": "sha256:54b8332ede83cedc3e9fc465b73950f0ccfeef3ec8eb4491722f7b03ac942983", "bytes": 16734, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.4048/jbc.2017.20.3.246", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC5620439", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "complete", "methods": [{"id": "method-1", "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": 1.0, "band": "reordered", "quote": "All statistical tests were performed using SPSS version 20.0 (IBM Corp., Armonk, USA), including Fisher exact test, chi-square test, and Kaplan-Meier overall survival and disease-free survival analyses. p-values were two-sided and p<0.05 was considered statistically significant. For data analysis of 59 breast cancer cell lines, we downloaded logR values generated by the CCLE database (https://portals.broadinstitute.org/ccle). Additionally, CNV values of breast cancer data for 773 patients was downloaded from TCGA database [3]."}}, {"id": "method-2", "family": "contingency_analysis", "specific": "chi_square", "label": "Categorical (contingency table) analysis", "dsl_operations": ["chi_square_test"], "missing_operations": [], "expressible": true, "parameters": {}, "data_shapes": ["categorical_cross_tabulation"], "evidence": {"score": 0.7, "band": "medium", "quote": "chi-square"}}], "targets": [], "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": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "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": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": ["For data analysis of 59 breast cancer cell lines, we downloaded logR values generated by the CCLE database (https://portals.broadinstitute.org/ccle)."], "basis": "The paper names no accession to its source data, so the data has to come from the authors."}}, "can_run": {"dsl_operations": ["survival_km"], "assets": ["source:pmid:28970850"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:None"]}, "gaps": ["data:accession_absent"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-10-31T18:32:15Z", "independence": "same_provider"}, "evidence_check": {"method": "reordered", "availability": null}, "calls": 8, "usage": {"prompt_tokens": 37971, "completion_tokens": 3838, "cached_tokens": 2088}}, "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:28970850", "type": "paper", "label": "pmid:28970850"}, {"id": "source:pmid:28970850", "type": "manuscript", "label": "PMID 28970850 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:28970850", "type": "paper", "label": "pmid:28970850"}, {"id": "source:pmid:28970850", "type": "manuscript", "label": "PMID 28970850 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-28970850", "type": "extraction", "used": ["source:pmid:28970850"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-None", "type": "accession_resolution", "used": ["data:geo:None"], "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:28970850", "parent_hash": "sha256:5febec901a4e260570d80b30389d5d4f510c3863812e42845389982c4546d05f", "fork_of": null, "generation": 6}, "gaps": ["execution.not_run", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:obtain_source_data blocked on data:accession_absent"], "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": ["All statistical tests were performed using SPSS version 20.0 (IBM Corp., Armonk, USA), including Fisher exact test, chi-square test, and Kaplan-Meier overall survival and disease-free survival analyses. p-values were two-sided and p<0.05 was considered statistically significant. For data analysis of 59 breast cancer cell lines, we downloaded logR values generated by the CCLE database (https://portals.broadinstitute.org/ccle). Additionally, CNV values of breast cancer data for 773 patients was downloaded from TCGA database [3]."], "order_basis": "analysis_only", "id": "assay:1"}]}