A comprehensive review in "Biofunct. Mater." meticulously details the most recent advancements and clinical translation of intelligent nanodrugs for breast cancer treatment. This paper presents an exhaustive overview of subtype-specific nanostrategies, the clinical benefits of FDA-approved nanodrugs, and innovative approaches to address tumor heterogeneity and treatment resistance. This serves as a foundational framework and pragmatic guide for enhancing precision-based breast cancer therapies.
Breast cancer, the most common cancer among women worldwide, is a major therapeutic challenge because of its profound heterogeneity. Breast cancer can be classified into several molecular subtypes, such as Luminal A, HER2-positive, and triple-negative breast cancer (TNBC), and a treatment that is effective for one patient may not work for another. In addition to this intrinsic heterogeneity, drug resistance and serious side effects have prompted the pursuit of more accurate and precise therapeutic strategies.
Nanomedicine, utilizing engineered nanoparticles for targeted drug delivery to tumors, presents a promising avenue for future treatment strategies. However, the design of an appropriate nanocarrier for individual patients has historically been a complex and often inefficient process of trial and error. The multitude of potential design parameters, including size, surface charge, and targeting ligand density, leads to a combinatorial explosion that is not feasible to test experimentally.
In this review, researchers from Shanghai Jiao Tong University School of Medicine and Guangdong Medical University have proposed a novel, data-driven solution to address the aforementioned challenge. They introduce an "AI-multi-omics intelligent delivery paradigm," in which a machine learning model is utilized to predict the optimal design of nanocarriers. This prediction is based on the unique biological signatures specific to a patient's tumor.
"We have transitioned from a universal, one-size-fits-all methodology to a subtype-specific, intelligent drug delivery system," states corresponding author Meng-Yao Li. "Many studies demonstrate that the incorporation of multi-omics data with artificial intelligence can effectively simplify complex processes. For example, in the case of aggressive Luminal B tumors, our model significantly enhanced the synchronization between drug release and peak tumor proliferation rates, increasing it by a factor of 2.8 compared to traditional static nanocarriers."
The review methodically delineates the manner in which this paradigm capitalizes on subtype-specific vulnerabilities. In the case of HER2-positive breast cancer, the utilization of trastuzumab-conjugated dendrimers resulted in a reduction of off-target toxicity by 47%. For the treatment of TNBC, a notoriously difficult-to-treat subtype, the employment of EGFR-antibody liposomes amplified tumor accumulation by a factor of 3.2.
The study also presents a comprehensive review of the current state of clinical nanomedicine, ranging from FDA-approved drugs such as Doxil®—which significantly decreases the cardiotoxicity of doxorubicin from 18% to 3%—to promising therapies currently under clinical trials. Notably, preliminary results for ²²⁵Ac-liposomes indicate that 77.8% of patients with metastatic TNBC achieved stable disease status for a duration of six months or longer, without any observed bone marrow toxicity.
"The potential is profound," elucidates Yimao Wu, a co-first author of the review. "This transcends mere incremental advancements. It offers a viable roadmap to engineer health, morphing breast cancer from a perilous disease into a manageable condition via personalized nanotherapeutic intervention."
The authors recognize that issues related to large-scale manufacturing and long-term safety continue to impede clinical adoption. Nevertheless, with the incorporation of AI, multi-omics data, and biomimetic nanocarriers such as exosomes, the trajectory of breast cancer treatment is on course to be notably more accurate and efficacious in the future.
This paper 'Intelligent delivery and clinical transformation of nanomedicine in breast cancer: from basic research to individualized therapy' was published in Biofunctional Materials (ISSN: 2959-0582), an online multidisciplinary open access journal aiming to provide a peer-reviewed forum for innovation, research and development related to bioactive materials, biomedical materials, bio-inspired materials, bio-fabrications and other bio-functional materials.
Citation: Wu Y, Chen Z, Chen X, Li M. Intelligent delivery and clinical transformation of nanomedicine in breast cancer: from basic research to individualized therapy. Biofunct. Mater. 2025(3):0014.https://doi.org/10.55092/bm20250014
