Renal Cell Carcinoma: How Biomarkers Could Affect Drug Development

According to the World Health Organization (WHO), a biomarker is defined as “any substance, structure, or process that can be measured in the body or its products and influence or predict the incidence of outcome or disease.”¹There has been an increasing amount of research focusing on biomarkers in numerous therapeutic areas, especially oncology. Within oncology, a biomarker could be utilized to determine which patients may respond the best to a new or old medication, based both on safety and efficacy.

An example of where biomarkers may help to select the best medication for a patient and also assist in drug development is the tyrosine kinase inhibitor (TKI) dovitinib for renal cell carcinoma (RCC). Dovitnib was developed as an oral TKI that targeted multiple signaling pathways within the progression of RCC. In animal models, dovitinib showed significant tumor reduction by inhibiting the platelet-derived growth factor receptor (PDGFR), vascular endothelial growth factor receptor (VEGFR), and fibroblast growth factor receptor (FGFR).^2,3

In a large phase 3 trial, dovitinib was compared to another oral TKI, sorafenib, in patients with metastatic RCC.⁴Patients in the dovitinib group had similar rates of progression-free survival (PFS) when compared with patients receiving sorafenib. In addition, the adverse events were similar between the two groups. Therefore, the authors concluded that although dovitinib did show activity in patients with metastatic RCC, it was no better than sorafenib. Similarly, a phase 2 study evaluating dovitinib versus sorafenib in patients with hepatocellular carcinoma (HCC) found similar overall survival (OS) and time to tumor progression (TTP).⁵

Based on these underwhelming results, the further development of dovitinib was slowed until recently. Oncology Venture is a company that will be in-licensing dovitinib from its parent company Novartis in hopes of using its specialized biomarker technology to help tailor its use in the correct patient population.  This technology is called Drug Response Prediction (DRP™) and analyzes the genetic makeup of a specific cancer within a patient in hopes of finding an optimal treatment.⁶The DRP™ is based on evaluating the messenger RNA (mRNA) of biopsies from patients with cancers such as RCC. It aims to determine which cancer cell lines may be resistant or sensitive to a certain chemotherapeutic agent. According to its website, the DRP™ biomarker system was validated within the RCC biopsy data from the phase 3 trial prior coming to this formal agreement with Novartis. This data has not yet been published, but will be interesting to review once it is made public. Although its more formal drug development was halted based on the above unimpressive clinical data, dovitinib was studied in a multitude of other solid organ malignancies including hepatocellular carcinoma, non-small  cell lung cancer, breast cancer, mesothelioma, gastrointestinal stromal tumor, thyroid cancer, and gliobastoma. Therefore, there may be additional biopsies from these trials that could be further analyzed for optimizing potential responders to dovitinib using the DRP™ technology. In addition to RCC, the DRP™ biomarkers have shown some promising results in those patients with non-small cell lung cancer, colon cancer, and gastroesophageal cancer.^7,8,9

Combining the available clinical data from previous dovitinib trials with the newer DRP™ biomarker technology is an example of how cancer therapy has already and continues to move towards a more personalized approach. By choosing the best medication for the ideal patient upfront, this could potentially increase efficacy, limit adverse events, and control exorbitant costs associated with clinical trials and post-approval treatments.

In the future, the strategy of developing accurate biomarkers may become more common than the traditional drug development process. Developing a new drug candidate from preclinical to clinical trials can be extremely expensive and time consuming with a high level of attrition. Companies may start to invest some of their drug development budget in biomarkers in hopes of maximizing the benefits of newer chemotherapeutic agents as well as older medications that may have fallen to the wayside.    

References

1. WHO International Programme on Chemical Safety Biomarkers in Risk Assessment: Validity and Validation. 2001. Retrieved from http://www.inchem.org/documents/ehc/ehc/ehc222.htm.
2. Sivanand S, Pena-Llopis S, Zhao H, et al.  A validated tumorgraft model reveals activity of dovitinib against renal cell carcinoma.  Sci Transl Med.2012;4:137ra75. doi: 10.1126/scitranslmed.3003643
3. Angevin E, Lopez-Martin J, Lin CC, et al. Phase I study of dovitinib (TKI258), an oral FGFR, VEGFR, and PDGFR inhibitors, in advanced or metastatic renal cell carcinoma.  Clin Cancer Res. 2013;19:1257-1268. doi: 10.1158/1078-0432.CCR-12-2885
4. Motzer RJ, Porta C, Vogelzang NJ, et al. Dovitinib versus sorafenib for third-line targeted treatment of patients with metastatic renal cell carcinoma:  an open-label, randomized phase 3 trial. Lancet Oncol. 2014;15(3):286-296. doi: 10.1016/S1470-2045(14)70030-0
5. Cheng AL, Thongprasert S, Lim HY, et al.  Randomized, open-label phase 2 study comparing frontline dovitinib versus sorafenib in patients with advanced hepatocellular carcinoma.  Hepatology. 2016;64(3):774-784. doi: 10.1002/hep.28600
6. DRP™ mpi Platform. www.medical-prognosis.com/our-solutionAccessed May 15, 2018. 
7. Buhl IK, Santoni-Ruqiu E, Ravn J, et al. Molecular prediction of adjuvant cisplatin efficacy in Non-Small Cell Lung Cancer (NSCLC)-validation in two independent cohortsPLoS One. 2018;13(3):e0194609.
8. Buhl IK, Gerster S, Delorenzi M, et al. Cell line derived 5-FU and irinotecan drug-sensitivity profiles evaluated in adjuvant colon cancer trial data. PLoS One.  2016;11(5):e0155123. doi: 10.1371/journal.pone.0194609
9. Winther M, Knudsen S, Dahlgaard J, et al.  Clinical impact of a novel microRNA chemo-sensitivity predictor in gastro-esophageal cancer. PLoS One. 2016;11(2):e0148070. doi: 10.1371/journal.pone.0148070