An herbal drug combination identified by knowledge graph alleviates the clinical symptoms of plasma cell mastitis patients: a nonrandomized controlled trial
Abstract
Background
Plasma cell mastitis (PCM) is a nonbacterial breast inflammation with severe and intense clinical manifestation yet treatment methods for PCM are still rather limited. Although the mechanism of PCM remains unclear, mounting evidences suggest that the dysregulation of immune system is closely associated with the pathogenesis of PCM. Drug combinations or combination therapy could exert improved efficacy and reduced toxicity through hitting multiple discrete cellular targets.
Methods
We have developed a knowledge graph architecture towards immunotherapy and systematic immunity that consists of herbal drug-target interactions with a novel scoring system to select drug combinations based on target-hitting rates and phenotype relativeness. To this end, we employed this knowledge graph to identify an herbal drug combination for PCM and we subsequently evaluated the efficacy of the herbal drug combination in clinical trial
Results
Our clinical data suggests that the herbal drug combination could significantly reduce the serum level of various inflammatory cytokines, downregulate serum IgA and IgG level, reduce the recurrence rate and reverse the clinical symptoms of PCM patients with improvements of general health status.
Conclusions
In summary, we reported that an herbal drug combination identified by knowledge graph can alleviate the clinical symptoms of plasma cell mastitis patients. We demonstrated that the herbal drug combination holds great promise as an effective remedy for PCM, acting through the regulation of immunoinflammatory pathways and improvement of systematic immune level. In particular, the herbal drug combination could significantly reduce the recurrence rate of PCM, a major obstacle for PCM treatment. Our data suggests that the herbal drug combination is expected to feature prominently in future PCM treatment.
Funding
C. Liu’s lab was supported by grants from the Public Health Science and Technology Project of Shenyang (Grant: 22-321-32-18); Y. Yang’s laboratory was supported by the National Natural Science Foundation of China (Grant: 81874301), the Fundamental Research Funds for Central University (Grant: DUT22YG122) and the Key Research project of ‘be Recruited and be in Command’ in Liaoning Province (Personal Target Discovery for Metabolic Diseases).
Clinical trial number
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