Histopathological biomarkers for nanomedicine-based cancer therapy

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Researchers from the Institute of Experimental Molecular Imaging at RWTH Aachen University publish results on the identification of suitable tumor patients in clinical trials for nanoparticle-based cancer therapies.

Nanomedical formulations have attracted increasing public attention since the development of coronavirus vaccines. These formulations use a wide variety of drug carriers in the size range from 10 to 1000 nanometers to safely transport sensitive molecules such as mRNA to their target region. Over the years, drug carriers have already been developed to transport chemotherapeutic drugs into tumors in a more targeted manner and with fewer side effects. Until now, however, there has been no method to ensure in clinical trials that tumors are treated with a sufficient accumulation of drug carriers. Researchers from the Institute of Molecular Imaging at RWTH Aachen University led by Jan-Niklas May and Twan Lammers, in close cooperation with AstraZeneca, have developed an easy-to-implement method for predicting the tumor accumulation of nanomedical drug carriers. The researchers have now published their findings in the internationally renowned journal Nature Biomedical Engineering.

It has been known since the 1980s that nanomedical drug carriers accumulate in tumors. Initially, it was assumed that a miracle weapon for cancer therapy, described by Paul Ehrlich as a "magic bullet", had been discovered. Almost 40 years later, however, it is clear that only a few of the numerous approaches have been successfully brought to the clinic. There are various explanations for this: on the one hand, the general difficulties in the development of new therapeutics, particularly with regard to efficacy, cost-effectiveness and production, and on the other hand, the diversity of tumors, even of the supposedly same type (for example, the different types of breast cancer).

While a preliminary histopathological examination of the tumor is used for targeted antibody therapies to ensure that a suitable therapy is selected for the individual tumor, no inclusion or exclusion criteria are usually applied for nanodrugs. In some studies, imaging methods with contrast agents or radioactively labeled nanomaterials were used to predict tumor accumulation and link it to a response to therapy. Although these methods are very specific and accurate, they require expensive imaging and, in the case of radiolabeling, the availability of nuclear medicine laboratories and clinics and have therefore not yet been widely used in clinical trials or clinical practice.

This was the starting point for the researchers, who hypothesized that certain properties of the tumour promote the accumulation of nanomedical drug carriers and can be used as histopathological biomarkers. In a preclinical data set, various potential biomarkers of the tumor microenvironment such as macrophages, collagens, blood vessels and the maturity of the blood vessels were examined and tested to see whether there is a connection between the occurrence of biomarkers and the accumulation of drug carriers.

The results were further analyzed using a machine learning methodology to identify a promising duo of biomarkers (blood vessels and macrophages). In close cooperation with researchers from AstraZeneca, the biomarkers were tested in thirteen additional tumor models. This again showed that models with many blood vessels and macrophages have a higher nano drug accumulation than models with fewer blood vessels and macrophages. Finally, human tumor tissue and biopsies from the pathology archive of the Aachen University Hospital were examined, which corresponded to the characteristics of a previously published data set in which the accumulation of radioactively labeled liposomes in the tumor was measured in patients. By quantifying macrophages and blood vessels as histopathological biomarkers, tumors with lower nanodrug accumulation could be distinguished from tumors with higher nanodrug accumulation.

As biopsies are routinely used for tumor diagnostics, they are available for almost every tumor patient. Using comparatively inexpensive histological staining, a simple procedure has thus been developed that enables the treatment of tumors that are likely to respond to therapy based on a prediction of nanomaterial accumulation. This can not only help patients, but also researchers to translate new nanomedical formulations more efficiently. A better understanding of the enrichment of drug carrier systems also lays an important foundation for the further development of biomaterials as part of the TransMedMat Cluster of Excellence initiative.

This consortium of interdisciplinary scientists is working on the development, production and translation of transformative biomedical materials. These should be able to interact with the human body and adapt to biological interfaces independently or through external triggers, or modulate the biological interfaces. Ultimately, the clinical translation of the nanomaterials developed in the Cluster of Excellence will also benefit from the use of specific (histopathological) biomarkers to stratify patients and enable personalized therapeutic approaches.