{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T15:13:41Z","timestamp":1786115621861,"version":"build-2736575974"},"reference-count":80,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Genes"],"abstract":"<jats:p>Background: Cellular senescence exerts a complex influence on BRCA progression and TME remodeling. However, the specific roles of ASIGs in regulating the TME and determining patient outcomes remain unclear. Methods: Using TCGA (training), METABRIC (validation), and single-cell RNA-seq datasets, we systematically characterized ASIGs in BRCA. Prognostic ASIGs were identified to define molecular subtypes and construct a 17-gene LASSO-Cox risk model, which was integrated with clinical factors to develop a prognostic nomogram. Microenvironmental features and cell\u2013cell communication networks were deconstructed using computational deconvolution and single-cell algorithms (SCISSOR and CellChat). Results: We established a robust 17-gene ASIG-based prognostic signature that effectively stratified BRCA patients into high- and low-risk groups and served as an independent prognostic predictor (HR = 3.94, p &lt; 0.001). The nomogram accurately predicted 1-, 3-, and 5-year overall survival. Notably, the two risk groups exhibited strikingly distinct TME landscapes. The low-risk group was characterized by a coordinated, B cell-centric immune network, whereas the high-risk group displayed T cell exhaustion and immunosuppressive myeloid infiltration. Conclusions: The ASIG-based prognostic risk model is independent of traditional clinicopathological factors, providing a robust tool for patient risk stratification and offering biological insights into senescence-driven microenvironmental remodeling.<\/jats:p>","DOI":"10.3390\/genes17080921","type":"journal-article","created":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T15:08:09Z","timestamp":1785856089000},"page":"921","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrated Single-Cell and Bulk RNA-Sequencing Analysis Identifies an Aging-Related Gene Signature for Prognosis in Breast Cancer"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-3571-8942","authenticated-orcid":false,"given":"Pengcheng","family":"Chen","sequence":"first","affiliation":[{"name":"School of Artificial Intelligence, Taizhou University, Taizhou 318000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yindan","family":"Lin","sequence":"additional","affiliation":[{"name":"Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA"},{"name":"Department of Toxicology and Cancer Biology, College of Medicine, University of Kentucky, Lexington, KY 40536, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingjia","family":"Li","sequence":"additional","affiliation":[{"name":"Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Fudan University, Shanghai 201203, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiwei","family":"Gu","sequence":"additional","affiliation":[{"name":"Markey Cancer Center, University of Kentucky, Lexington, KY 40536, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xueyun","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Medicine, Taizhou University, Taizhou 318000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,4]]},"reference":[{"key":"ref_1","first-page":"12","article-title":"Cancer statistics, 2024","volume":"74","author":"Siegel","year":"2024","journal-title":"CA Cancer J. Clin."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/s40164-022-00363-1","article-title":"Breast cancer heterogeneity and its implication in personalized precision therapy","volume":"12","author":"Guo","year":"2023","journal-title":"Exp. Hematol. Oncol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3786","DOI":"10.1172\/JCI60534","article-title":"Heterogeneity in breast cancer","volume":"121","author":"Polyak","year":"2011","journal-title":"J. Clin. Investig."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1047","DOI":"10.1152\/physrev.00020.2018","article-title":"Cellular Senescence: Aging, Cancer, and Injury","volume":"99","author":"Calcinotto","year":"2019","journal-title":"Physiol. Rev."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1007\/s11357-015-9764-2","article-title":"Cellular senescence: From growth arrest to immunogenic conversion","volume":"37","author":"Burton","year":"2015","journal-title":"Age"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1093\/jnci\/94.8.606","article-title":"Endogenous Sex Hormones and Breast Cancer in Postmenopausal Women: Reanalysis of Nine Prospective Studies","volume":"94","author":"Group","year":"2002","journal-title":"J. Natl. Cancer Inst."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1053\/j.seminoncol.2009.03.001","article-title":"Breast cancer before age 40 years","volume":"36","author":"Anders","year":"2009","journal-title":"Semin. Oncol."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Jiang, X., Shen, H., Shang, X., Fang, J., Lu, Y., Lu, Y., Zheng, J., and Fu, P. (2022). Recent Advances in the Aging Microenvironment of Breast Cancer. Cancers, 14.","DOI":"10.3390\/cancers14204990"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"18","DOI":"10.1016\/j.cancergen.2024.06.002","article-title":"Cancer treatments: Past, present, and future","volume":"286\u2013287","author":"Sonkin","year":"2024","journal-title":"Cancer Genet."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"243","DOI":"10.1016\/j.cell.2022.11.001","article-title":"Hallmarks of aging: An expanding universe","volume":"186","author":"Blasco","year":"2023","journal-title":"Cell"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1194","DOI":"10.1016\/j.cell.2013.05.039","article-title":"The hallmarks of aging","volume":"153","author":"Blasco","year":"2013","journal-title":"Cell"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1158\/2159-8290.CD-21-1059","article-title":"Hallmarks of Cancer: New Dimensions","volume":"12","author":"Hanahan","year":"2022","journal-title":"Cancer Discov."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"S27","DOI":"10.1016\/S0962-8924(01)82148-6","article-title":"Cellular senescence as a tumor-suppressor mechanism","volume":"11","author":"Campisi","year":"2001","journal-title":"Trends Cell Biol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1172\/JCI95148","article-title":"Mechanisms and functions of cellular senescence","volume":"128","author":"Herranz","year":"2018","journal-title":"J. Clin. Investig."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"3333","DOI":"10.1002\/1878-0261.13268","article-title":"Cellular senescence and the tumour microenvironment","volume":"16","author":"Takasugi","year":"2022","journal-title":"Mol. Oncol."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"99","DOI":"10.1146\/annurev-pathol-121808-102144","article-title":"The senescence-associated secretory phenotype: The dark side of tumor suppression","volume":"5","author":"Desprez","year":"2010","journal-title":"Annu. Rev. Pathol. Mech. Dis."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1007","DOI":"10.1016\/j.devcel.2023.05.010","article-title":"Reshaping of the tumor microenvironment by cellular senescence: An opportunity for senotherapies","volume":"58","author":"Gil","year":"2023","journal-title":"Dev. Cell"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1186\/s12943-024-02096-7","article-title":"Cellular senescence and SASP in tumor progression and therapeutic opportunities","volume":"23","author":"Dong","year":"2024","journal-title":"Mol. Cancer"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Huang, R., Wang, H., Hong, J., Wang, Z., Wu, J., Huang, O., He, J., Chen, W., Li, Y., and Chen, X. (2023). A senescence-associated signature refines the classification of different modification patterns and characterization of tumor immune microenvironment infiltration in triple-negative breast cancer. Front. Pharmacol., 14.","DOI":"10.3389\/fphar.2023.1191910"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"75","DOI":"10.1038\/s41580-020-00314-w","article-title":"Cellular senescence in ageing: From mechanisms to therapeutic opportunities","volume":"22","author":"Krizhanovsky","year":"2021","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1186\/s13045-023-01426-4","article-title":"Aging microenvironment and antitumor immunity for geriatric oncology: The landscape and future implications","volume":"16","author":"Zhao","year":"2023","journal-title":"J. Hematol. Oncol."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"8570","DOI":"10.1038\/ncomms9570","article-title":"The transcriptional landscape of age in human peripheral blood","volume":"6","author":"Peters","year":"2015","journal-title":"Nat. Commun."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"65","DOI":"10.1016\/j.critrevonc.2007.09.001","article-title":"Impact of aging on the biology of breast cancer","volume":"66","author":"Benz","year":"2008","journal-title":"Crit. Rev. Oncol. Hematol."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1424","DOI":"10.1038\/nm.4000","article-title":"Cellular senescence in aging and age-related disease: From mechanisms to therapy","volume":"21","author":"Childs","year":"2015","journal-title":"Nat. Med."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhu, Z., Jiang, L., and Ding, X. (2023). Advancing Breast Cancer Heterogeneity Analysis: Insights from Genomics, Transcriptomics and Proteomics at Bulk and Single-Cell Levels. Cancers, 15.","DOI":"10.3390\/cancers15164164"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"6218","DOI":"10.1038\/s41467-021-26407-4","article-title":"Microenvironmental IL-6 inhibits anti-cancer immune responses generated by cytotoxic chemotherapy","volume":"12","author":"Bent","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"3924","DOI":"10.1158\/1078-0432.CCR-15-2463","article-title":"Tumor-Produced Interleukin-8 Attracts Human Myeloid-Derived Suppressor Cells and Elicits Extrusion of Neutrophil Extracellular Traps (NETs)","volume":"22","author":"Alfaro","year":"2016","journal-title":"Clin. Cancer Res."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"2383","DOI":"10.1158\/1078-0432.CCR-20-1319","article-title":"IL8, Neutrophils, and NETs in a Collusion against Cancer Immunity and Immunotherapy","volume":"27","author":"Teijeira","year":"2021","journal-title":"Clin. Cancer Res."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Tominaga, K., and Suzuki, H.I. (2019). TGF-\u03b2 Signaling in Cellular Senescence and Aging-Related Pathology. Int. J. Mol. Sci., 20.","DOI":"10.3390\/ijms20205002"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1016\/j.trecan.2020.02.022","article-title":"Turning Cold into Hot: Firing up the Tumor Microenvironment","volume":"6","author":"Duan","year":"2020","journal-title":"Trends Cancer"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"e343","DOI":"10.1002\/mco2.343","article-title":"Hot and cold tumors: Immunological features and the therapeutic strategies","volume":"4","author":"Wang","year":"2023","journal-title":"MedComm"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1888","DOI":"10.1016\/j.cell.2019.05.031","article-title":"Comprehensive Integration of Single-Cell Data","volume":"177","author":"Stuart","year":"2019","journal-title":"Cell"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/j.cels.2015.12.004","article-title":"The Molecular Signatures Database (MSigDB) hallmark gene set collection","volume":"1","author":"Liberzon","year":"2015","journal-title":"Cell Syst."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Saul, D., and Kosinsky, R.L. (2021). Single-Cell Transcriptomics Reveals the Expression of Aging- and Senescence-Associated Genes in Distinct Cancer Cell Populations. Cells, 10.","DOI":"10.3390\/cells10113126"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"11479","DOI":"10.1038\/ncomms11479","article-title":"The somatic mutation profiles of 2,433 breast cancers refines their genomic and transcriptomic landscapes","volume":"7","author":"Pereira","year":"2016","journal-title":"Nat. Commun."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1334","DOI":"10.1038\/s41588-021-00911-1","article-title":"A single-cell and spatially resolved atlas of human breast cancers","volume":"53","author":"Wu","year":"2021","journal-title":"Nat. Genet."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1572","DOI":"10.1093\/bioinformatics\/btq170","article-title":"ConsensusClusterPlus: A class discovery tool with confidence assessments and item tracking","volume":"26","author":"Wilkerson","year":"2010","journal-title":"Bioinformatics"},{"key":"ref_38","unstructured":"Therneau, T. (2015). A Package for Survival Analysis in R, R Foundation for Statistical Computing. R Package Version 2.38."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Kassambara, A., Kosinski, M., and Biecek, P. (2016). survminer: Drawing Survival Curves Using \u2018ggplot2\u2019, R Foundation for Statistical Computing. R Package Version 0.4.9.","DOI":"10.32614\/CRAN.package.survminer"},{"key":"ref_40","unstructured":"Sheng, J., Qiu, P., and Geyer, C. (2019). TSHRC: Two Stage Hazard Rate Comparison, R Foundation for Statistical Computing. R Package Version 0.1\u20136."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"e47","DOI":"10.1093\/nar\/gkv007","article-title":"limma powers differential expression analyses for RNA-sequencing and microarray studies","volume":"43","author":"Ritchie","year":"2015","journal-title":"Nucleic Acids Res."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1038\/nmeth.3337","article-title":"Robust enumeration of cell subsets from tissue expression profiles","volume":"12","author":"Newman","year":"2015","journal-title":"Nat. Methods"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2612","DOI":"10.1038\/ncomms3612","article-title":"Inferring tumour purity and stromal and immune cell admixture from expression data","volume":"4","author":"Yoshihara","year":"2013","journal-title":"Nat. Commun."},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"H\u00e4nzelmann, S., Castelo, R., and Guinney, J. (2013). GSVA: Gene set variation analysis for microarray and RNA-seq data. BMC Bioinform., 14.","DOI":"10.1186\/1471-2105-14-7"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"527","DOI":"10.1038\/s41587-021-01091-3","article-title":"Identifying phenotype-associated subpopulations by integrating bulk and single-cell sequencing data","volume":"40","author":"Sun","year":"2022","journal-title":"Nat. Biotechnol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"1088","DOI":"10.1038\/s41467-021-21246-9","article-title":"Inference and analysis of cell-cell communication using CellChat","volume":"12","author":"Jin","year":"2021","journal-title":"Nat. Commun."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"697","DOI":"10.1007\/s00428-018-2301-9","article-title":"The new TNM-based staging of breast cancer","volume":"472","author":"Cserni","year":"2018","journal-title":"Virchows Arch."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1281","DOI":"10.1016\/j.cell.2021.01.022","article-title":"Inhibitory CD161 receptor identified in glioma-infiltrating T cells by single-cell analysis","volume":"184","author":"Mathewson","year":"2021","journal-title":"Cell"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"938","DOI":"10.1038\/nm.3909","article-title":"The prognostic landscape of genes and infiltrating immune cells across human cancers","volume":"21","author":"Gentles","year":"2015","journal-title":"Nat. Med."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1578","DOI":"10.1016\/j.ccell.2021.09.010","article-title":"Single-cell analyses reveal key immune cell subsets associated with response to PD-L1 blockade in triple-negative breast cancer","volume":"39","author":"Zhang","year":"2021","journal-title":"Cancer Cell"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1751","DOI":"10.1007\/s10495-025-02116-x","article-title":"Polymeric immunoglobulin receptor (pIgR) in cancer progression: A critical role and potential therapeutic target","volume":"30","author":"Qian","year":"2025","journal-title":"Apoptosis"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Zhao, J., Chen, W., Li, L., Zhang, Z., and Wang, Y. (2025). JCHAIN: A Prognostic Marker Based on Pan-Cancer Analysis to Inhibit Breast Cancer Progression. Genes, 16.","DOI":"10.3390\/genes16091070"},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"631","DOI":"10.3892\/ol.2020.11640","article-title":"Downregulation of CLCA4 expression is associated with the development and progression of colorectal cancer","volume":"20","author":"Wei","year":"2020","journal-title":"Oncol. Lett."},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Zhang, Q., Liu, Y., Wang, X., Zhang, C., Hou, M., and Liu, Y. (2023). Integration of single-cell RNA sequencing and bulk RNA transcriptome sequencing reveals a heterogeneous immune landscape and pivotal cell subpopulations associated with colorectal cancer prognosis. Front. Immunol., 14.","DOI":"10.3389\/fimmu.2023.1184167"},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"114824","DOI":"10.1016\/j.biopha.2023.114824","article-title":"Mechanisms of CD8+ T cell exclusion and dysfunction in cancer resistance to anti-PD-(L)1","volume":"163","author":"Mortezaee","year":"2023","journal-title":"Biomed. Pharmacother."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1038\/s41698-024-00522-z","article-title":"Targeting M2-like tumor-associated macrophages is a potential therapeutic approach to overcome antitumor drug resistance","volume":"8","author":"Wang","year":"2024","journal-title":"npj Precis. Oncol."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1146\/annurev-immunol-090222-110914","article-title":"T Cell Exhaustion","volume":"42","author":"Baessler","year":"2024","journal-title":"Annu. Rev. Immunol."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1016\/j.jhep.2024.09.029","article-title":"FABP5+ lipid-loaded macrophages process tumour-derived unsaturated fatty acid signal to suppress T-cell antitumour immunity","volume":"82","author":"Yang","year":"2025","journal-title":"J. Hepatol."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"729","DOI":"10.1038\/nrm2233","article-title":"Cellular senescence: When bad things happen to good cells","volume":"8","author":"Campisi","year":"2007","journal-title":"Nat. Rev. Mol. Cell Biol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/j.cancergen.2025.09.006","article-title":"Galectin-9 promotes colon cancer development by polarizing macrophages toward the M2 phenotype","volume":"298\u2013299","author":"Zhang","year":"2025","journal-title":"Cancer Genet."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.cancergen.2025.03.004","article-title":"Identification of new immune target and signaling for cancer immunotherapy","volume":"294\u2013295","author":"Narote","year":"2025","journal-title":"Cancer Genet."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1007\/s13353-023-00805-4","article-title":"High expression of ACKR1 predicts a good prognosis and suppresses sarcoma cell progression via regulating the tumor immune microenvironment","volume":"65","author":"Lin","year":"2024","journal-title":"J. Appl. Genet."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Crawford, K.S., and Volkman, B.F. (2023). Prospects for targeting ACKR1 in cancer and other diseases. Front. Immunol., 14.","DOI":"10.3389\/fimmu.2023.1111960"},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1038\/s41586-019-1922-8","article-title":"B cells and tertiary lymphoid structures promote immunotherapy response","volume":"577","author":"Helmink","year":"2020","journal-title":"Nature"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1038\/s41416-018-0327-z","article-title":"The clinical role of the TME in solid cancer","volume":"120","author":"Giraldo","year":"2019","journal-title":"Br. J. Cancer"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1126\/science.ade2292","article-title":"CXCL9:SPP1 macrophage polarity identifies a network of cellular programs that control human cancers","volume":"381","author":"Bill","year":"2023","journal-title":"Science"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"4253","DOI":"10.1158\/0008-5472.CAN-17-3876","article-title":"Macrophage-Derived Granulin Drives Resistance to Immune Checkpoint Inhibition in Metastatic Pancreatic Cancer","volume":"78","author":"Quaranta","year":"2018","journal-title":"Cancer Res."},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Zaib, T., Cheng, K., Liu, T., Mei, R., Liu, Q., Zhou, X., He, L., Rashid, H., Xie, Q., and Khan, H. (2023). Expression of CD22 in Triple-Negative Breast Cancer: A Novel Prognostic Biomarker and Potential Target for CAR Therapy. Int. J. Mol. Sci., 24.","DOI":"10.3390\/ijms24032152"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"179","DOI":"10.1111\/imm.13952","article-title":"The Landscape of SPP1 + Macrophages Across Tissues and Diseases: A Comprehensive Review","volume":"176","author":"Palma","year":"2025","journal-title":"Immunology"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"430","DOI":"10.1007\/s10875-010-9501-7","article-title":"Aging affects human B cell responses","volume":"31","author":"Frasca","year":"2011","journal-title":"J. Clin. Immunol."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"88","DOI":"10.2174\/1871523018666190724124214","article-title":"Progranulin Regulates Inflammation and Tumor","volume":"19","author":"Liu","year":"2020","journal-title":"Antiinflamm. Antiallergy Agents Med. Chem."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"747","DOI":"10.1038\/35021093","article-title":"Molecular portraits of human breast tumours","volume":"406","author":"Perou","year":"2000","journal-title":"Nature"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"1160","DOI":"10.1200\/JCO.2008.18.1370","article-title":"Supervised risk predictor of breast cancer based on intrinsic subtypes","volume":"27","author":"Parker","year":"2009","journal-title":"J. Clin. Oncol."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Bastien, R.R., odr\u00edguez-Lescure, \u00c1., Ebbert, M.T., Prat, A., Mun\u00e1rriz, B., Rowe, L., Miller, P., Ruiz-Borrego, M., Anderson, D., and Lyons, B. (2012). PAM50 breast cancer subtyping by RT-qPCR and concordance with standard clinical molecular markers. BMC Med. Genom., 5.","DOI":"10.1186\/1755-8794-5-44"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.cancergen.2025.08.010","article-title":"Comprehensive analysis of oncogenic determinants across tumor types via multi-omics integration","volume":"298\u2013299","author":"Ubaid","year":"2025","journal-title":"Cancer Genet."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1093\/biomet\/81.3.515","article-title":"Proportional hazards tests and diagnostics based on weighted residuals","volume":"81","author":"Grambsch","year":"1994","journal-title":"Biometrika"},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Bellera, C.A., MacGrogan, G., Debled, M., de Lara, C.T., Brouste, V., and Mathoulin-P\u00e9lissier, S. (2010). Variables with time-varying effects and the Cox model: Some statistical concepts illustrated with a prognostic factor study in breast cancer. BMC Med. Res. Methodol., 10.","DOI":"10.1186\/1471-2288-10-20"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"1276","DOI":"10.1126\/science.abn4009","article-title":"Epigenetic clocks, aging, and cancer","volume":"378","author":"Johnstone","year":"2022","journal-title":"Science"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1182\/blood.2021014299","article-title":"Telomeres, aging, and cancer: The big picture","volume":"139","author":"Lansdorp","year":"2022","journal-title":"Blood"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1038\/s41576-022-00553-x","article-title":"Spatial biology of cancer evolution","volume":"24","author":"Seferbekova","year":"2023","journal-title":"Nat. Rev. Genet."}],"container-title":["Genes"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-4425\/17\/8\/921\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,6]],"date-time":"2026-08-06T04:18:23Z","timestamp":1785989903000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-4425\/17\/8\/921"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,4]]},"references-count":80,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2026,8]]}},"alternative-id":["genes17080921"],"URL":"https:\/\/doi.org\/10.3390\/genes17080921","relation":{},"ISSN":["2073-4425"],"issn-type":[{"value":"2073-4425","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,4]]}}}