Abstract

With sunitinib treatment of metastatic renal cell carcinoma, most patients end up developing resistance over time. Recent clinical trials have shown that individualizing treatment protocols could delay resistance and result in better outcomes. We developed an in vivo xenograft tumor model and compared tumor growth rate, morphological, and transcriptomic differences between alternative and traditional treatment schedules. Our results show that the alternative treatment regime could delay/postpone cancer progression. Additionally, we identified distinct morphological changes in the tumor with alternative and traditional treatments, likely due to the significantly dysregulated signaling pathways between the protocols. Further investigation of the signaling pathways underlying these morphological changes may lead potential therapeutic targets to be used in a combined treatment with sunitinib, which offers promise in postponing/reversing the resistance of sunitinib.

Highlights

  • Renal cell carcinoma (RCC) is an epithelial malignancy of the renal tubules [1]

  • The mechanisms of resistance that develop to TKIs such as sunitinib are poorly understood

  • A recent clinical trial by Bjarnason et al showed that an “individualized” dosing of sunitinib might improve outcomes for patients [12]

Read more

Summary

Introduction

Renal cell carcinoma (RCC) is an epithelial malignancy of the renal tubules [1]. It affects 2–3% of the world population with the highest incidence rate in Europe (7–34/100,000 males and 3–15/100,000 females) [1]. The pathogenesis of ccRCC is deeply related to the loss of function of VHL, which results in a pro-angiogenic gene expression signature by the destabilization of hypoxia-inducible factors [5]. CcRCC is characterized by an extensive network of thin-walled, staghorn-shaped vasculature [5]. Another important pathway implemented in ccRCC pathogenesis is the PI3K/AKT/MTOR pathway, which is currently targeted in therapies [5]. Mutation in SETD2 and SWI/SNF chromatin remodeling complex is characterized in ccRCC [5]

Objectives
Methods
Results
Conclusion
Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call