Cancer immunotherapy, the utilization of the patients? own immune system to treat cancer, has emerged as a powerful new strategy in cancer treatment. An unmet need in cancer immunotherapy treatment has been the lack of a predictive biomarker for treatment response. Imaging, which has been the ?gold standard? for monitoring treatment response is unreliable in immunotherapy due to the pseudoprogression phenomenon. An immunotherapy biomarker will enable more personalized cancer treatment, response-adaptive treatment and cost reduction. One potential approach for the development of such predictive biomarkers is to utilize circulating tumor cells (CTCs). However, the currently available systems such as CellSearch? and other competing technologies do not have high enough sensitivity. Capio Biosciences has developed a novel biomimetic platform that is highly sensitive and specific in CTC capture. The tumor cell capture efficiency of the platform, which is trademarked as CapioCyte?, was shown to increase by up to 150-fold via a biomimetic combination of E-selectin-induced cell rolling and dendrimer-mediated multivalent binding. We have preliminary clinical data from various cohorts demonstrating that we can reliably capture high number of CTCs using CapioCyte?. To translate our technology, we aim to optimize our CapioCyte? immunotherapy chip design. This proposed SBIR Phase I study will progress through 2 specific aims.
In Aim 1, we will prepare and compare various CapioCyte? capture surfaces with different combinations of capture agents to engineer an optimized chip using a series of cell lines. Surface chemistries will also be developed to achieve controlled immobilization of the capture agents and facile isolation of CTCs (detachment from the capture surfaces), enabling post-capture analyses.
In Aim 2, the optimized CapioCyte? prototype will be validated using human blood samples from cancer patients receiving immunotherapy. The sensitivity and specificity of the CapioCyte? prototype will be measured and compared to those of CellSearch?. The captured CTCs will then be the subject of post-capture analysis, such as RNA sequencing, in addition to post-staining of the captured CTCs with aPD- L1 and p63. These efforts will reveal the relationship among kinetic changes of CTC counts, oncogene/target expression of CTCs, and clinical outcomes. Upon successful completion, we will have developed a biomarker for cancer immunotherapy response. Such a biomarker can ultimately enable personalized and response-adaptive immunotherapy cancer treatment.
Cancer immunotherapy, the utilization of the patients? own immune system to treat cancer, has emerged as a powerful new strategy in cancer treatment. An unmet need in cancer immunotherapy treatment has been the lack of a predicative biomarker for treatment response. Our application aims to address this challenge and develop a predicative biomarker for cancer immunotherapy therapy using circulating tumor cell capture technology.
