Nanoparticles loaded with drugs can help design personalized cancer treatments.
Cancer treatment is moving towards personalized therapies that promise better efficacy and less side effects. Tumors of the same type in different patients present in fact subtle differences that may change some of their biological features and their sensitivity to drugs.
The design of personalized therapies is based today on determining the ‘molecular profile’ of a tumor. Tumors are characterized according to the presence or absence in their cells of certain proteins and gene transcripts, which, as such, become tumor markers.
The molecular profile
A well-known example is represented by breast cancer that can be classified depending on the presence on tumor cells of hormone receptors like estrogen and progesterone receptors. Patients with estrogen-receptor positive breast tumors will be treated with drugs blocking the activity of this molecule. However, the same drugs will be useless in patients with estrogen-receptor negative tumors.
Therefore, knowing the molecular profile of a cancer can help doctors choose the most effective therapy, while sparing patients from the undesirable effects of inactive drugs.
Establishing the molecular profile of a cancer is no simple matter though. It requires the analysis of gene expression in a biopsy taken from the tumor to obtain the so-called ‘gene signature’ of that tumor. By examining the biomarkers contained in the gene signature (i.e. the genes that are active or not in the biopsy and are relevant to the tumor development), a doctor can classify the tumor and understand whether or not it may respond to a certain therapy.
Besides being long and laborious, this method can be vain if the resulting gene signature does not contain known biomarkers. In addition, sometimes a tumor fails to respond to a drug despite its molecular profile suggested it would, because it activates mechanisms that make it drug-resistant and that are unpredictable from the analysis of its gene signature.
How to improve then the search for effective drugs in each cancer patient and speed up the design of personalized therapies? It would be great if, before starting a therapy, it was possible to test small doses of several drugs, at the same time, in a patient and compare their effects on the tumor, so to identify the one that works best.
Is this just fantasy? Well, no more.
The study of Yaari and colleagues from the Israel Institute of Technology in Haifa, published in Nature Communication, opens a way to this achievement.
The scientists used nanoparticles to target different drugs to a single tumor. Among the existent types of nanoparticles, researchers opted for using liposomes. These small vesicles are composed of an aqueous center, in which drugs can be dissolved, surrounded by a double layer of lipids, which can bind to cell membranes.
Three different batches of liposomes were prepared, each one containing an anticancer drug commonly used in human breast cancer therapy: cisplatin, gemcitabine, or doxorubicin. To identify the batches, the researchers then ‘labelled’ them by introducing a specific mix of short DNA sequences. In this way, after mixing different liposomes, the scientists could know which drug was contained in each of them by extracting the DNA they carried and sequencing it. Each DNA combination thus ‘marked’ the liposomes like a barcode.
To test the system, the researchers turned to mice bearing mammary tumors. They injected the mice intravenously with a mixture of 5 types of barcoded liposomes: liposomes carrying the three chemotherapeutic drugs, and two types of control liposomes: one loaded with caffeine (that has no anticancer effects), and one empty liposome.
Since most tumors are perfused by leaky blood vessels, the liposomes could leave the blood circulation once they reached the tumor, and accumulate there. The small quantity of liposomes that was injected allowed for one tumor cell to pick up only one liposome.
48 hours after the injection, the researchers took a tumor biopsy that, as expected, turned out to be composed of both live and dead cells containing the liposomes. Live cells had likely received the empty liposomes, or those carrying either caffeine or a chemotherapeutic drug to which they were resistant. On the other hand, dead cells had probably incorporated liposomes loaded with an effective drug.
The most powerful drug
Now, which of the three injected drugs had killed most tumor cells?
The scientists separated live from dead cells, extracted the barcoded DNAs from both, and sequenced it. They found that the majority of dead cells contained the barcode corresponding to gemcitabine, which also turned out to be the most powerful drug against the tumors. Cisplatin and doxorubicin also killed some tumor cells but less efficiently than gemcitabine, while caffeine had a negligible effect and the empty liposomes were inactive.
To test if their prediction of gemcitabine being the best therapy for their experimental tumors was correct, the researchers compared the effects of the three drugs on the tumor-bearing mice. After 20 days of treatment, they found that mice that received gemcitabine had much smaller tumors than those treated with the other drugs, thus confirming their diagnostic results.
This study demonstrates that it is possible to use barcoded liposomes to rapidly test the efficacy of anti-cancer drugs directly in a patient. Thus, selecting and designing the best personal cancer treatment seems increasingly conceivable in the near future.
Moving on to human trials
Of course, moving from experimental tumors in mice to human cancer patients will present several difficulties regarding, for instance, the efficiency of liposomes in targeting a tumor, the identification of tumor areas containing the liposomes and the extraction of a corresponding biopsy, just to mention a few.
Nevertheless, once adapted and optimized for clinical use, this technique promises to be a very useful tool to complement other cancer therapies currently used.
 Yaari, Z., da Silva, D., Zinger, A., Goldman, E., Kajal, A., Tshuva, R., Barak, E., Dahan, N., Hershkovitz, D., Goldfeder, M., Roitman, J., & Schroeder, A. (2016). Theranostic barcoded nanoparticles for personalized cancer medicine Nature Communications, 7 DOI: 10.1038/ncomms13325