Every new drug treatment must be tested several times to obtain approval from health organizations before it can be used in the clinic. However, if a personalized treatment designed for a single patient, it will have a significant effect only for that individual. Therefore, the routine approval processes for therapies based on treating other organisms and individuals will not provide the appropriate treatment response. A recent study by Pauli and colleagues introduced a platform to address this challenge. For drug treatment validation and safety testing, this platform first applies patient-derived tumor organoid (PDTO) cultures followed by patient-derived xenograft (PDX) models 3,5,13,14. However, analyzing the hundreds of drugs and thousands of possible drug combinations using this platform remains a considerable and complex challenge 20. Our protocol, enabled us to extract personalized drug options that could potentially be introduced as the primary input for that of Pauli’s platform.
In the present study, we created an IPPGE for each patient by comparing the gene expression interval of healthy individuals and breast cancer patients. The resulting IPPGE was unique to each patient, like a fingerprint (Fig. 2A and 2B). A previous study reported variations in gene expression patterns in different cancer phenotypes and also in the patients 11. Importantly, although patients have many common perturbed genes, the gene expression compared to the health interval plays a pivotal role in drug selection. Thus, the drugs and their gene targets in this study were selected in such a way as to target the most perturbed genes and not to have a useless effect on genes that were within the health interval. However, the personalized drug combinations were observed to have drugs in common among the patients to control common perturbed genes (Table 1). Therefore, each patient's unique IPPGE appeared to be effective in extracting accurate personalized drug combinations.
Potential of drug combinations derived from patient IPPGEs
Cancers are complex diseases regulated by the interaction of multiple signaling pathways through crosstalk. A single drug is thought to be capable of targeting only one signaling pathway for a disease; however, an alternative signaling pathway can be activated to maintain tumor development. A combination of drugs has been recommended to prevent drug resistance and to make the treatment more effective 6,7,2. The current study also found that each medication affected a certain number of a patient's oncogenes; the protocol extracted complementary drugs that affected the largest number of oncogenes. We found that drug combinations derived from patient IPPGEs had stronger treatment potential due to their more targeted effects on oncogenes. In addition to the drug combination extracted for each patient, the effect of each drug alone was also recorded (Table 1). The use of drug combinations with the personalized medicine approach can lead to the identification of drug combinations that have the potential to produce a more significant effect in the patient.
Several drug repurposing studies have reported significant anticancer efficacy for nonspecialized drugs. One of the first drug repurposing studies showed that the anti-ulcer drug cimetidine to be a therapeutic candidate for the treatment of adenocarcinoma of the lung 1,16. Subsequent studies have found that combination drug therapy increases the success of drug repurposing 8,12,18. We found that drug combinations extracted from the Beta group had an equal or greater potential than those from the Alpha group for patient treatment (Table 1 and Supplementary Fig. S1). This finding has two distinct interpretations; First, nonspecialized drugs may be used as adjunctive treatments in addition to specialized medications. Second, according to the observations, some nonspecialized cancer drugs were identified as the potential main treatment. The present study shows that the IPPGE can be highly unique to each patient, and the IPPGE can play an important role in extracting a personalized combination of drugs. Notably, personalized drugs with high therapeutic potential for a particular patient can include nonspecialized drugs.
In this study, we used FDA-approved drugs to assess the safety and interactions of the drug combinations, but there is great therapeutic potential among other small molecules for use as treatment options to extract future personalized drug combinations if reliable mechanisms are identified to assess drug safety and identify their interactions.