In 2016, an estimated 250,000 new cases of female breast cancer were diagnosed in the U.S., causing an estimated 40,000 deaths. Almost all breast cancer deaths are due to tumor progressive resistance to systemic therapies, followed by metastasis. Anticipating breast cancer chemoresistance is a significant clinical challenge because the changes in commonly monitored parameters, including tumor volume or glucose-analog uptake, have been shown to be poor predictors of resistance and often manifest only after resistance has occurred. The ability to accurately predict the onset of chemoresistance would allow physicians to make evidence based treatment changes in a timely manner, which could substantially improve patient outcomes. New preclinical imaging techniques designed to track resistance over the appropriate spatial and temporal scales could provide key insights into the effective management of chemoresistance in the clinic. The goal of the F99 phase is to develop a novel imaging technique called Diffuse and Nonlinear Imaging (DNI) that combines two different contrast mechanisms over spatial scales ranging from cm to ?m to monitor resistance in vivo. DNI utilizes multiply scattered photons for widefield mapping of tumor metabolism, and multiphoton interactions to achieve molecular, structural, and metabolic tumor imaging with cellular resolution in 3D. These techniques will be combined to make an integrated preclinical imaging system that is co-registered, providing unprecedented evaluation of tumor heterogeneity over a range of spatial scales and contrast mechanisms. DNI will integrate exogenous and molecularly targeted imaging agents with endogenous sources of imaging contrast to obtain a more complete picture of the in vivo tumor state.
The first aim i s to co-register nonlinear sectioning of vascular organization with oxygenation maps from diffuse imaging of preclinical mammary tumors through a window chamber.
The second aim i s to identify optical signatures of chemoresistance via DNI monitoring of treated preclinical mammary tumors. Lastly, the third aim is to link optical resistance metrics to heterogeneity in tumor vascular organization. The goal of the K00 phase is to study how the scheduling and spatial distribution of treatment affect the time-to- resistance. This entails tracking distinct clonal populations, and their complex dynamics and competition during drug-tumor interactions. Genetic and phenotypic markers of resistance and heterogeneity will be labeled with engineered nano-optical probes. These will enable longitudinal and simultaneous multiplexing and imaging of complex clonal interactions, and capturing of individual clonal dynamics in vivo in preclinical and clinical tumors. An optical technique will then be developed to use photorelease technology to control spatiotemporal treatment parameters and track drug distribution among clonal nests to study the effects of drug-tumor interactions on long-term resistance. Engineering an all-in-one investigative optical oncology platform that uses light to control treatment, map drug distribution, and image the resulting effects with various contrast mechanisms across different spatial and time scales, will provide novel insights into the effective treatment of resistant tumors.
The cancer research proposed here focuses on eliminating tumor resistance to cytotoxic therapies. I plan to approach this important topic by developing and leveraging optical and molecular methods that span the basic science, preclinical, and clinical domain, allowing for improved tumor phenotype evaluation over expanded spatial scales and contrast mechanisms. This will provide a new perspective and better understanding of molecular resistance mechanisms both in tumors and the tumor microenvironment, and will assist in developing new treatment strategies that mitigate or avoid resistance, ultimately extending the lives of cancer patients.
| Hayakawa, Carole K; Karrobi, Kavon; Pera, Vivian et al. (2018) Optical sampling depth in the spatial frequency domain. J Biomed Opt 23:1-14 |
| Pera, Vivian; Karrobi, Kavon; Tabassum, Syeda et al. (2018) Optical property uncertainty estimates for spatial frequency domain imaging. Biomed Opt Express 9:661-678 |
