A molecular classification system for estimating radiotherapy response and anticancer immunity for individual breast cancer patients.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:37927478", "kind": "science-record", "revision": 3, "content_hash": "sha256:1987b971e923a58efb7579e067009fa1243423932f2daff5138e5526caf3ee4b", "created_at": "2026-11-01T19:02:48Z", "updated_at": "2026-11-01T22:10:35Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "A molecular classification system for estimating radiotherapy response and anticancer immunity for individual breast cancer patients.", "doi": "10.3389/fonc.2023.1288698", "pmid": "37927478", "authors": ["Jiaxuan Zhang", "Long Li", "Haotian Shang", "Zhaoyan Feng", "Tengfei Chao"], "journal": "Frontiers in oncology", "year": 2023, "abstract": "Objective: Radiotherapy is a cornerstone of breast cancer therapy, but radiotherapy resistance is a major clinical challenge. Herein, we show a molecular classification approach for estimating individual responses to radiotherapy.\nMethods: Consensus clustering was adopted to classify radiotherapy-sensitive and -resistant clusters in the TCGA-BRCA cohort based upon prognostic differentially expressed radiotherapy response-related genes (DERRGs). The stability of the classification was proven in the GSE58812 cohort via NTP method and the reliability was further verified by quantitative RT-PCR analyses of DERRGs. A Riskscore system was generated through Least absolute shrinkage and selection operator (LASSO) analysis, and verified in the GSE58812 and GSE17705. Treatment response and anticancer immunity were evaluated via multiple well-established computational approaches.\nResults: We classified breast cancer patients as radiotherapy-sensitive and -resistant clusters, namely C1 and C2, also verified by quantitative RT-PCR analyses of DERRGs. Two clusters presented heterogeneous clinical traits, with poorer prognosis, older age, more advanced T, and more dead status in the C2. The C1 tumors had higher activity of reactive oxygen species and response to X-ray, proving better radiotherapeutic response. Stronger anticancer immunity was found in the C1 tumors that had rich immune cell infiltration, similar expression profiling to patients who responded to anti-PD-1, and activated immunogenic cell death and ferroptosis. The Riskscore was proposed for improving patient prognosis. High Riskscore samples had lower radiotherapeutic response and stronger DNA damage repair as well as poor anticancer immunity, while low Riskscore samples were more sensitive to docetaxel, doxorubicin, and paclitaxel.\nConclusion: Our findings propose a novel radiotherapy response classification system based upon molecular profiles for estimating radiosensitivity for individual breast cancer patients, and elucidate a methodological advancement for synergy of radiotherapy with ICB.", "claims": [{"id": "claim-method", "statement": "DERRGs with p-value<0.05 were employed for consensus clustering analysis via the ConsensusClusterPlus package (24).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:37927478", "locator": "sections[7] \"Consensus clustering analysis\" paragraph 2", "quote": "DERRGs with p-value<0.05 were employed for consensus clustering analysis via the ConsensusClusterPlus package (24)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . 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Further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "We classified breast cancer patients as radiotherapy-sensitive and -resistant clusters, namely C1 and C2, also verified by quantitative RT-PCR analyses of DERRGs.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:37927478", "locator": "sections[0] \"Abstract\" paragraph 3", "quote": "We classified breast cancer patients as radiotherapy-sensitive and -resistant clusters, namely C1 and C2, also verified by quantitative RT-PCR analyses of DERRGs."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "We classified breast cancer patients as radiotherapy-sensitive and -resistant clusters, namely C1 and C2, also verified by quantitative RT-PCR analyses of DERRGs.", "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:37927478"], "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. 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