The use of systemic chemotherapy for breast cancer has contributed to the recent decline in breast cancer mortality;however, an unacceptable number of patients fail systemic therapy and die of disseminated disease. Identifying factors important in resistance and directing patients towards more effective treatment is the translational goal of Project 3. Using quantitative PET imaging to measure glucose metabolism, and more recently dynamic contrast-enhanced (DCE) MRI to measure blood flow, we have identified an in vivo metabolic signature for locally advanced breast cancer (LABC) resistant to neoadjuvant chemotherapy as (1) a pre-therapy mismatch between metabolism and perfusion, (2) persistent or even increased tumor perfusion despite treatment, and (3) an altered pattern of glucose metabolism relative to glucose delivery after treatment. This pattern predicts incomplete response, early relapse and death independent of established prognostic factors, including pathologic primary tumor and nodal pathologic response. We have also found this pattern is more profoundly associated with triple-negative (TN, ER/PR/HER2 negative) tumors versus those that express ER/PR and/or over-express HER2. We now propose to translate our clinical, in vivo findings in patients back into the laboratory to identify the biologic features of tumors underlying these findings. In a cohort of LABC patients undergoing neoadjuvant chemotherapy, we will (1) compare imaging findings to tumor phenotype determined by IHC and expression microarrays to determine which molecular pathways are most involved In the resistant imaging phenotype, (2) determine the role ofthe tumor microenvironment, specifically tumor hypoxia measured by FMISO PET and the expression ofthe hypoxic tissue markers measured by IHC, and (3) relate macroscopic metabolic properties measured by imaging to cellular metabolism in biopsy specimens and a panel of cell lines using ToF-SIMS, with the goal of relating findings on metabolic pathways measured in cell lines to the resistant phenotype seen in patients. Successful completion of the studies will identify breast cancer patients likely to fail systemic chemotherapy and direct therapy towards those biologic targets most likely to overcome resistance.
This Project will investigate quantitative in vivo imaging as a means of identifying breast cancers resistant to systemic therapy and directing the patient towards more effective therapy. The primary translational goal of the project is to relate in vivo imaging findings predictive of poor response and patient outcome to underlying tumor biology with the goal of directing treatment targeted to specific resistance factors.
|Berger, Carolina; Sommermeyer, Daniel; Hudecek, Michael et al. (2015) Safety of targeting ROR1 in primates with chimeric antigen receptor-modified T cells. Cancer Immunol Res 3:206-16|
|Stephan, Sirkka B; Taber, Alexandria M; Jileaeva, Ilona et al. (2015) Biopolymer implants enhance the efficacy of adoptive T-cell therapy. Nat Biotechnol 33:97-101|
|Jensen, Michael C; Riddell, Stanley R (2014) Design and implementation of adoptive therapy with chimeric antigen receptor-modified T cells. Immunol Rev 257:127-44|
|Marcondes, A Mario; Karoopongse, Ekapun; Lesnikova, Marina et al. (2014) ?-1-Antitrypsin (AAT)-modified donor cells suppress GVHD but enhance the GVL effect: a role for mitochondrial bioenergetics. Blood 124:2881-91|
|Partridge, Savannah C; Stone, Karen M; Strigel, Roberta M et al. (2014) Breast DCE-MRI: influence of postcontrast timing on automated lesion kinetics assessments and discrimination of benign and malignant lesions. Acad Radiol 21:1195-203|
|Riddell, Stanley R; Sommermeyer, Daniel; Berger, Carolina et al. (2014) Adoptive therapy with chimeric antigen receptor-modified T cells of defined subset composition. Cancer J 20:141-4|
|Kennedy, Jacob J; Abbatiello, Susan E; Kim, Kyunggon et al. (2014) Demonstrating the feasibility of large-scale development of standardized assays to quantify human proteins. Nat Methods 11:149-55|
|Hudecek, Michael; Lupo-Stanghellini, Maria-Teresa; Kosasih, Paula L et al. (2013) Receptor affinity and extracellular domain modifications affect tumor recognition by ROR1-specific chimeric antigen receptor T cells. Clin Cancer Res 19:3153-64|
|Sun, Jianping; Zheng, Yingye; Hsu, Li (2013) A unified mixed-effects model for rare-variant association in sequencing studies. Genet Epidemiol 37:334-44|
|Qu, Xiaoyu; Randhawa, Grace; Friedman, Cynthia et al. (2013) A three-marker FISH panel detects more genetic aberrations of AR, PTEN and TMPRSS2/ERG in castration-resistant or metastatic prostate cancers than in primary prostate tumors. PLoS One 8:e74671|
Showing the most recent 10 out of 14 publications