A new genomics tool has been developed by BGI which performs accurate and specific classification of the mixed reads derived from the host and tumour xenografts.
The genomics organisation revealed that it has successfully developed a new filtering tool, PDXomics, which can be used for tumour xenograft research and applications.
However, the tool is very robust, which means that researchers could develop the specific patient-derived xenografts (PDX) and advance the oncology drug discovery, biomarker development and their future applications.
Xenograft models have many applications in biomedical research, including the fields of oncology, immunology and HIV pathology. Although there has been an increased use of tumour-specific PDX, the progress has been hampered by the contamination resulted from the inevitable mixing between the host and the xenografts.
Looking to address the problem, researchers from BGI developed a fast, accurate and specific tool to classify the xenograft-derived sequence read data. They achieved this by evaluating the tool on genomic data from three pairs of xenografts and case-matched primary tumour samples. They then mapped the sequence reads to a mixed reference-set, finding that the results showed that PDXomics could specifically filter the results.
Zonghui Peng, director, department of the pharmaceutical and biotech cooperation at BGI, said: “Over the past two decades, the applications of PDX have made great impact on the development of translational medicine. With the rapid development of next-generation sequencing (NGS) technology, PDXomics will be a robust tool in the optimisation and screening of xenograft models in the near future, with the benefits of fast turnaround time, low cost and high efficiency.”
To ensure the accuracy of PDXomics, researchers compared the analysis results with the two traditional methods, finding that PDXomics could significantly reduce the false-positive rate (FPR) of identified single-nucleotide mutations, and improve the accuracy of variation detection.
BGI has a proven track record in research such as this, generating more than 200 publications in top-tier journals such as Nature and Science.