1 Checkpoint inhibitors (CPI) have significantly improved outcomes in many tumor types, but there is still 2 immense room for improvement. A tremendous amount of preclinical and clinical research thus is aimed at 3 evaluating combination therapeutic regimens that may increase CPI response rate as well as identifying 4 biomarkers that indicate whether a patient will benefit from or be resistant to immunotherapy. 5 Cryoablation is a promising adjunctive strategy that may be able to significantly increase the CPI response 6 rate. Cryoablation of a single metastatic focus causes necrotic cell death, rupturing cell membranes through 7 alternating freeze and thaw cycles. Tumoral antigens are released along with inflammatory intracellular 8 contents. This markedly inflammatory reaction activates dendritic cells to take up the released tumor antigen 9 which, in turn, activates the adaptive immune system to attack tumor sites elsewhere in the body. 10 I have developed a dual-implanted tumor model to investigate the systemic benefit of adjunctive cryoablation 11 and have found that when added to CPI therapy cryoablation significantly increases the complete response 12 rate of the non-ablated tumor relative to CPI alone. As adding cryoablation to CPI is minimally studied, there 13 remains significant work to identify biomarkers to determine which tumors will benefit most by cryoablation 14 addition. To identify response biomarkers I am helped by a unique investigative tool that I co-invented, 15 granzyme B PET imaging. Localizing to the site of active immune-mediated tumor killing, granzyme B PET 16 allows us to distinguish CPI responders from non-responders prior to changes in tumor size. We can then 17 interrogate the immune-response while it is still active, facilitating unique insights. 18 In this proposal, in a murine tumor model I will develop an optimized preclinical cryoablation and CPI regimen 19 across multiple tumor lines reflective of the range of CPI responsiveness. In these models I will then use 20 granzyme B PET imaging to help identify genomic and non-genomic biomarkers of response and identify 21 mechanisms of resistance to the combination of cryoablation and CPI. I will also simultaneously be leading a 22 clinical trial evaluating the ability of cryoablation to increase pembrolizumab response in metastatic urothelial 23 carcinoma. From patient blood and biopsy specimens obtained at the time of cryoablation I propose to analyze 24 the tumoral and systemic immune microenvironment for response biomarkers in these patients. These data will 25 be essential to guide the development of future optimized clinical protocols evaluating the ability of cryoablation 26 to increase systemic immunity across multiple tumor types. I will conduct this research in the excellent 27 research environment of MGH, guided by mentors expert in the fields of immunology, immuno-oncology, and 28 interventional radiology. Their guidance will help ensure the success of this project and my successful 29 transition to an independent research career.

Public Health Relevance

This study aims to advance understanding of adjunctive cryoablation?s ability to increase checkpoint inhibitor response by identifying biomarkers predictive of response as well as mechanisms of resistance. Biomarkers will be identified in preclinical murine models with the aid of granzyme B PET imaging and also identified from clinical biopsy specimens obtained from a prospective clinical trial of cryoablation and pembrolizumab in metastatic urothelial carcinoma. This study will help to define which cancer patients on immunotherapy are most likely to benefit from the addition of cryoablation and how resistance to adjunctive cryoablation can be overcome.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Clinical Investigator Award (CIA) (K08)
Project #
1K08CA245257-01A1
Application #
10055056
Study Section
Subcommittee I - Transistion to Independence (NCI)
Program Officer
Lim, Susan E
Project Start
2020-08-01
Project End
2025-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Massachusetts General Hospital
Department
Type
DUNS #
073130411
City
Boston
State
MA
Country
United States
Zip Code
02114