{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,30]],"date-time":"2026-08-30T05:16:22Z","timestamp":1788066982355,"version":"build-2784847793"},"reference-count":44,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T00:00:00Z","timestamp":1787875200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82574882"],"award-info":[{"award-number":["82574882"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["82074286"],"award-info":[{"award-number":["82074286"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"award":["82574882"],"award-info":[{"award-number":["82574882"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"award":["82074286"],"award-info":[{"award-number":["82074286"]}],"id":[{"id":"https:\/\/ror.org\/01h0zpd94","id-type":"ROR","asserted-by":"publisher"}]},{"name":"Open Fund Project of the NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor","award":["NHCDP2024005"],"award-info":[{"award-number":["NHCDP2024005"]}]},{"name":"Drug Efficacy and Health Risk Assessment Key Laboratory of Zhenjiang","award":["SS2024006"],"award-info":[{"award-number":["SS2024006"]}]},{"DOI":"10.13039\/501100004608","name":"Natural Science Foundation of Jiangsu Province","doi-asserted-by":"crossref","award":["BK20251851"],"award-info":[{"award-number":["BK20251851"]}],"id":[{"id":"10.13039\/501100004608","id-type":"DOI","asserted-by":"crossref"}]},{"name":"Zhenjiang Science and Technology Development Foundation","award":["SH2025069"],"award-info":[{"award-number":["SH2025069"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Pharmaceuticals"],"abstract":"<jats:p>Background\/Objectives: Breast cancer exhibits substantial molecular heterogeneity, resulting in diverse therapeutic vulnerabilities and limiting the efficacy of single-agent therapies. Although multi-target strategies may offer improved therapeutic benefit, the systematic identification of synergistic higher-order target combinations remains challenging. This study aimed to identify and validate effective higher-order target combinations for heterogeneous breast cancer. Methods: DeepMDS, a previously developed deep learning-based multi-compound synergy prediction model, was used to prioritize candidate target combinations for breast cancer. Exhaustive two-target and three-target combinations were ranked in the gene-expression contexts of ER-positive luminal-like MCF-7 and triple-negative MDA-MB-231 breast cancer cells. The top-ranked target combinations were evaluated using single, pairwise, and triple small interfering RNA (siRNA) perturbations. Representative inhibitors were subsequently assessed in fixed-ratio combinations in MCF-7, MDA-MB-231, and 4T1 cells and in a 4T1 syngeneic mouse experiment. Results: BIRC5-NAMPT-TOP1 ranked first in both cell lines. Triple siRNA co-transfection targeting BIRC5, NAMPT, and TOP1 produced the strongest antiproliferative effects, with inhibition rates of 62.94% in MCF-7 cells and 55.62% in MDA-MB-231 cells. The corresponding inhibitors, LQZ-7I, FK866, and topotecan, exhibited synergistic antiproliferative activity at multiple molar ratios, with combination index values below 1. The optimized 2.5:10:1 molar ratio showed strong synergy in MCF-7, MDA-MB-231, and 4T1 cells, with combination index values of 0.26, 0.19, and 0.15, respectively. In tumor-bearing mice model, the triple-inhibitor regimen achieved a tumor inhibition rate of 62.05%. Topotecan-containing groups showed hematological alterations, whereas no statistically detectable elevations were observed in the measured terminal serum hepatic or renal biomarkers. Conclusions: The BIRC5-NAMPT-TOP1 combination showed reproducible phenotypic activity in the tested genetic and pharmacological models. These findings support the use of DeepMDS as a hypothesis-generation tool for higher-order target prioritization.<\/jats:p>","DOI":"10.3390\/ph19091363","type":"journal-article","created":{"date-parts":[[2026,8,28]],"date-time":"2026-08-28T18:33:52Z","timestamp":1787942032000},"page":"1363","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Artificial Intelligence-Guided Prioritization and Experimental Evaluation of Synergistic Target Combinations for Breast Cancer Therapy"],"prefix":"10.3390","volume":"19","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-9628-1331","authenticated-orcid":false,"given":"Chunlai","family":"Feng","sequence":"first","affiliation":[{"name":"School of Pharmacy, Jiangsu University, Zhenjiang 212013, China"},{"name":"Research Center for Intelligent Healthcare and Digital Health Technology, Affiliated Yixing People\u2019s Hospital of Jiangsu University, Yixing 214205, China"},{"name":"China\u2019s National Health Commission (NHC) Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou 730000, China"},{"name":"Key Laboratory of Zhenjiang, School of the Environment and Safety Engineering, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"conceptualization","vocabulary":"credit"},{"role":"methodology","vocabulary":"credit"},{"role":"writing-review-editing","vocabulary":"credit"}]},{"given":"Qiuqi","family":"Feng","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-original-draft","vocabulary":"credit"},{"role":"data-curation","vocabulary":"credit"},{"role":"visualization","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-7110-1345","authenticated-orcid":false,"given":"Shengnan","family":"She","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"formal-analysis","vocabulary":"credit"},{"role":"investigation","vocabulary":"credit"}]},{"given":"Ruojing","family":"Yang","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"}]},{"given":"Mengru","family":"Li","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"}]},{"given":"Lu","family":"Gong","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Jiangsu University, Zhenjiang 212013, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"investigation","vocabulary":"credit"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5566-817X","authenticated-orcid":false,"given":"Mengjie","family":"Rui","sequence":"additional","affiliation":[{"name":"School of Pharmacy, Jiangsu University, Zhenjiang 212013, China"},{"name":"Engineering and Technology Institute of Jiangsu University, Zhenjiang 212013, China"}],"role":[{"vocabulary":"crossref","role":"author"},{"role":"writing-review-editing","vocabulary":"credit"},{"role":"supervision","vocabulary":"credit"},{"role":"resources","vocabulary":"credit"}]}],"member":"1968","published-online":{"date-parts":[[2026,8,28]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"102339","DOI":"10.1016\/j.ctrv.2022.102339","article-title":"Global challenges and policy solutions in breast cancer control","volume":"104","author":"Trapani","year":"2022","journal-title":"Cancer Treat. 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