Comprehensive analysis of pyroptotic gene prognostic signatures associated with tumor immune microenvironment and genomic mutation in breast cancer.

{"sci_version": "1.2", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:36090993", "kind": "science-record", "revision": 3, "content_hash": "sha256:e688530ea9354464960adec4ca4d37c140d63a735b9947f1eb33327e07de4c41", "created_at": "2026-11-01T18:15:19Z", "updated_at": "2026-11-01T21:28:53Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Comprehensive analysis of pyroptotic gene prognostic signatures associated with tumor immune microenvironment and genomic mutation in breast cancer.", "doi": "10.3389/fimmu.2022.933779", "pmid": "36090993", "authors": ["Hongfei Zhang", "Xiafei Yu", "Junzhe Yang", "Gao He", "Xiaoqiang Zhang", "Xian Wu", "Li Shen", "Yi Zhou", "Xuyu Cheng", "Xiaoan Liu", "Yanhui Zhu"], "journal": "Frontiers in immunology", "year": 2022, "abstract": "Background: Breast cancer is becoming a tumor with the highest morbidity rate, and inflammation-induced cell death namely pyroptosis reportedly plays dual roles in cancers. However, the specific mechanism between pyroptosis and the clinical prognosis of breast cancer patients is indistinct. Hence, novel pyroptosis-related biomarkers and their contributing factors deserve further exploration to predict the prognosis in breast cancer.\nMethods: Pearson's correlation analysis, and univariate and multivariate Cox regression analysis were utilized to obtain six optimal pyroptosis-related gene prognostic signatures (Pyro-GPS). The risk score of each breast cancer patient was calculated. Next, a Pyro-GPS risk model was constructed and verified in TCGA cohort (n=1,089) and GSE20711 cohort (n=88). Then analyses of immune microenvironment, genomic variation, functional enrichment, drug response and clinicopathologic feature stratification associated with the risk score of Pyro-GPS were performed. Subsequently, a nomogram based on the risk score and several significant clinicopathologic features was established. Ultimately, we further investigated the role of CCL5 in the biological behavior of MDA-MB-231 cell line.\nResults: The low-risk breast cancer patients have better survival outcomes than the high-risk patients. The low-risk patients also show higher immune cell infiltration levels and immune-oncology target expression levels. There is no significant difference in genetic variation between the two risk groups, but the frequency of gene mutations varies. Functional enrichment analysis shows that the low-risk patients are prominently correlated with immune-related pathways, whereas the high-risk patients are enriched in cell cycle, ubiquitination, mismatch repair, homologous recombination and biosynthesis-related pathways. Pyro-GPS is positively correlated with the IC50 of anti-tumor drugs. Furthermore, comprehensive analyses based on risk score and clinicopathological features were performed to predict the prognosis of breast cancer patients. Additionally, in vitro experiments confirmed that breast cancer cells with high expression of CCL5 had weaker proliferation, invasion and metastasis abilities as well as stronger apoptosis and cell cycle arrest abilities.\nConclusions: The risk score of Pyro-GPS can serve as a promising hallmark to predict the prognosis of BRCA patients. Risk score evaluation may assist to acquire relevant information of tumor immune microenvironment, genomic mutation status, functional pathways and drug sensitivity, and thus provide more effective personalized strategies.", "claims": [{"id": "claim-data-access", "statement": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:36090993", "locator": "sections[29] \"Data availability statement\" paragraph 2", "quote": "The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The risk score can independently predict poor survival in breast cancer patients (HR: 1.068, 95%CI: 1.037–1.100, p< 0.001).", "kind": "quantitative", "target": {"value": 95.0, "unit": "per cent", "tolerance": null, "source": "The multivariate Cox regression analysis proves that the risk score can independently predict poor survival (HR: 1.068, 95%CI: 1.037–1.100, p< 0.001, Figure 6C )."}, "evidence": [{"asset": "source:pmid:36090993", "locator": "sections[24] \"Stratification analysis and independent prognostic value of Pyro-GPS risk model\" paragraph 2", "quote": "The multivariate Cox regression analysis proves that the risk score can independently predict poor survival (HR: 1.068, 95%CI: 1.037–1.100, p< 0.001, Figure 6C )."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "complete", "objective": "The risk score can independently predict poor survival in breast cancer patients (HR: 1.068, 95%CI: 1.037–1.100, p< 0.001).", "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:36090993"], "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:GSE20711"], "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:GSE20711"], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": []}, "data": {"state": "partial", "assets": [{"id": "source:pmid:36090993", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.3389/fimmu.2022.933779", "sha256": "sha256:a8cbee64bf1166f9107c4cc6b5b296340918f74e3aa712cf4ebed125c356391d", "bytes": 67544, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.3389/fimmu.2022.933779", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC9453314", "source": "europe_pmc_fulltext", "coverage": "whole_body", "text_hash_scope": "rendered_section_body"}}, {"id": "data:geo:GSE20711", "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=GSE20711", "sha256": null, "bytes": null, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "GSE20711", "version": null, "note": "The original contributions presented in the study are included in the article/ Supplementary Material . 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Conclusions"], "order_basis": "paper_text_order:2354", "id": "assay:1"}, {"role": "data_generation", "definition_id": "transfection", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.99, "evidence": ["Materials and methods Cell culture and transfection MDA-MB-231 cells were cultured in 10% fetal", "dified atmosphere of 5% CO2 at 37°C and cell transfection was accomplished by using Lipofectamine® 300"], "order_basis": "paper_text_order:2782", "id": "assay:2"}, {"role": "data_generation", "definition_id": "cell_culture", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.77, "evidence": ["lture and transfection MDA-MB-231 cells were cultured in 10% fetal bovine serum in a humidified atmos"], "order_basis": "paper_text_order:2811", "id": "assay:3"}, {"role": "data_generation", "definition_id": "western_blot", "definition_version": "99e1195c7d6f", "definition_digest": null, "required_operations": [], "support_state": "partial", "source_hashes": {"assay_lexicon": "99e1195c7d6f"}, "confidence": 0.93, "evidence": ["CL5 protein expression level was detected by western blot analysis to confirm whether the cell line wa"], "order_basis": "paper_text_order:3024", "id": "assay:4"}, {"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": ["Univariate and multivariable Cox regression analyses demonstrated that the risk score derived from the Pyro-GPS model can serve as an independent prognostic factor for breast cancer patients in the TCGA cohort."], "order_basis": "consumes_earlier_output", "id": "assay:5"}]}