The new generation of therapies targeting specific mutations in tumors, while promising, has delivered underwhelming results. The problem is that while genomic analysis can uncover various “druggable” abnormalities, we have no immediate way to determine which abnormality is actually driving the cancer. This approach has resulted in a meager 12% success rate with a few exceptions.
At UC Davis Comprehensive Cancer Center, we are working to make personalized treatment more precise through a collaborative research effort with the NCI-designated Jackson Laboratory headquartered in Bar Harbor, Maine, with operations in West Sacramento, California.
In August, we published a proof-of-concept paper in PLOS One
that described our research using tumor xenografts in mice to test and identify more precise treatments for bladder cancer patients.
Part of the problem, in bladder cancer treatment, is that while combination chemotherapy can be effective for up to half of all patients with invasive and advanced disease, no other FDA-approved therapy is available when first-line therapies fail. Other therapies are occasionally used, but, in general, less than 20% of patients will benefit. So far, no test can identify potential responders before treatment.
We used the patient-derived xenograft (PDX) platform to test various treatments in mice prior to treating the patient. We obtained bladder tumors directly from individual patients, grafted them into mice at Jackson Laboratory, and identified actionable mutations through next-generation sequencing. We developed as many mice carrying patient-specific xenografts as needed to simultaneously test multiple therapies.
Interestingly, this PDX platform is patient-specific. Cell lines and their derived xenografts have been traditionally used to test drug efficacy. These cells, however, are homogeneous and genetically different from patient cancers. After the cells are cultured, their gene expression profile is dramatically different from those of parental tumor xenografts.
These changes cannot be reversed after re-implantation. Therefore, it is not surprising that prediction models for drug response based on the genetic information of cell lines, such as the Genomics of Drug Sensitivity in Cancer and the Cancer Cell Line Encyclopedia, frequently fail to predict drug efficacy in the clinic. Our PDXs, not only retained the morphology of their parental cancer cells, but also showed remarkable genetic fidelity—between 92%–97%—of their original patient tumors.
There are many applications of this PDX platform in the era of precision. First, we determined its application in identification of effective chemotherapeutic drugs. The GC (gemcitabine and cisplatin/ carboplatin) regimen is commonly used as a first-line therapy in bladder cancer. We determined the PDX sensitivity to cisplatin, gemcitabine, and the drugs in combination. Of the first six PDXs we tested (10-12 mice per treatment group), five were resistant to cisplatin and two were resistant to gemcitabine. Chemo-resistance to one drug could be overcome by the other drug, leaving four of the six PDXs sensitive to this G/C combination. Our findings suggest that, even though cisplatin and gemcitabine are commonly used in combination, many cancers respond to one drug, while the other has little effect on the cancer, but causes toxicity.