A study done by researchers from the McGovern Medical School and the UTHealth School of Biomedical Informatics has found a likely reason why some cancer treatments that eliminate cancerous cells in mouse research models aren’t as effective during human trials. The study was reported in the Nature Communications journal.
For the study, the researchers reported the broad existence of mouse virus cells seen in xenografts that were derived from patients. These patient-derived xenograft (“PDX”) models were created by implanting tumor tissues from humans in mice that are immune deficient. These mice are often used while developing and testing cancer treatments.
The study’s senior author, who is also a professor at the School of Biomedical Informatics, W. Jim Zheng, stated that the researchers discovered that when they implanted human tumors into mice, the tumor differed from the tumor that was extracted from the cancer sufferer. He added that most of the tumors they tested had been compromised by mice viruses.
The researchers also examined 184 sets of data that were produced from sequencing xenograft samples using a data-driven approach. They found the existence of unique mouse viruses in 170 samples. Zheng explained that the infection has been linked to considerable modifications in tumors which could potentially impact PDX during human drug testing.
Zheng also noted that when researchers were trying to find ways to eliminate a tumor through the PDX approach, they assumed the tumor in mice would be the same as in cancer patients. However, they were not. This insight made the outcomes of a potential cancer treatment seem promising when one observed that the medication eliminated the tumor in mice; however, it wouldn’t work in humans. This is because the drug killed the tumor, which had been compromised by the viruses present in mice, not in the patient.
Zheng hopes that his results will alter scientists’ approach to finding ways to eliminate tumor cells. He stated that all researchers shared the joint goal of finding a treatment for cancer. Currently, there is a total of 210 ongoing study projects using PDX models that have been financed by the NIH; they have a combined yearly fiscal budget of more than $116 million. He declared that to ensure future patients received effective treatments, quality control needed to tighten up and researchers needed to rely on models that weren’t compromised.
The study is a collaboration involving the Data Science and Informatics Core for Cancer Research at the School of Biomedical Informatics and the McGovern Medical School Texas Therapeutics Institute, Institute of Molecular Medicine (“IMM”).
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