General Session Abstracts最新文献

{"title":"Abstract GS1-05: Apobec3 induced mutagenesis sensitizes murine models of triple negative breast cancer to immunotherapy by activating B-cells and CD4+ T-cells","authors":"Daniel P. Hollern, Nuo Xu, Kevin R. Mott, Xiaping He, Kelly Carey-Ewend, Ds Marron, James B. Ford, J. Parker, B. Vincent, J. Serody, C. Perou","doi":"10.1158/1538-7445.SABCS18-GS1-05","DOIUrl":"https://doi.org/10.1158/1538-7445.SABCS18-GS1-05","url":null,"abstract":"Immune checkpoint inhibitor (ICI) therapies have led to remarkable clinical responses in cancers such as melanoma and non-small cell lung cancer. In breast cancer, current immunotherapy trials have placed an emphasis on triple negative breast cancers (TNBC), where early results suggest response rates of 10-20%. Thus, it is critical to identify predictive biomarkers to enhance patient selection for immunotherapy. With this goal in mind, we simulated a clinical trial employing anti-PD1 and anti-CTLA therapies in immune-intact genetically engineered mouse models (GEMMs) of TNBC. Testing of ICI therapies on 8 different GEMMs demonstrated that each model was resistant. Whole exome sequencing showed that each model also harbored a low mutation burden. Given that mutation load is predictive of immunotherapy response in other cancer types, and that Apobec3B activity is associated with higher tumor mutation burden (TMB) in breast cancer, we created two different tumor lines with overexpression of murine Apobec3. In contrast to the parental lines, the Apobec3 overexpressing lines showed an elevated tumor mutation burden and new mutations were consistent with the Apobec mutation signature. These TNBC lines with new mutations resulting from Apobec3 activity were exquisitely sensitive to anti-PD1/anti-CTLA4 combination therapy; as assessed by reduction in tumor volume and extended overall survival. To identify features that predict response, we examined resistant and sensitive tumors at pretreatment, at 1 week of treatment, and at end stage by flow cytometry and mRNA-seq. Gene expression profiling identified multiple immune signatures as predictive of response to ICI therapy; specifically CD8+ T-effector memory cells, CD4+ T-cells, and activated B-Cells. Similarly, gene expression analysis showed that these cell types increased at 1 week of therapy in sensitive models but not in resistant models. Flow cytometry confirmed these predictions. Next, we used an antibody based approach to separately deplete CD4+ T-Cells, CD8+ T-cells, or B-cells in Apobec3 mutagenized murine tumors receiving aPD1/aCTLA4 combination therapy. In each case, depletion of these populations significantly reduced the therapeutic response. However, mice receiving combination immunotherapy and depleted for CD8+ T-cells still exhibited a significant extension in overall survival compared to non-treated controls. In contrast, the CD4+ T-cell depleted mice and B-cell depleted mice exhibited no ICI therapeutic benefit. Together, these data point to key immune biomarkers of response to anti-PD1/anti-CTLA4 therapy; we have further developed a genomic predictor of ICI response using our murine models and will test this on a human TNBC data set. Lastly, this GEMM system provides a rich RNA-seq resource, and new immune-activated models for TNBC, which uncovered a key role for B-cells and CD4+ T-cells in response to ICI therapies. Citation Format: Hollern DP, Xu N, Mott KR, He X, Carey-Ewend K, Marro","PeriodicalId":12697,"journal":{"name":"General Session Abstracts","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88417407","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}