Citation

Gil Del Alcazar CR, Huh SJ, Ekram MB, Trinh A, Liu LL, Beca F, Zi X, Kwak M, Bergholtz H, Su Y, Ding L, Russnes HG, Richardson AL, Babski K, Min Hui Kim E, McDonnell CH, Wagner J, Rowberry R, Freeman GJ, Dillon D, Sorlie T, Coussens LM, Garber JE, Fan R, Bobolis K, Allred DC, Jeong J, Park SY, Michor F, Polyak K. 2017. Immune Escape in Breast Cancer During to Invasive Carcinoma Transition. Cancer discovery. 7(10):1098-1115. Pubmed: 28652380 DOI:10.1158/2159-8290.CD-17-0222

Abstract

To investigate immune escape during breast tumor progression, we analyzed the composition of leukocytes in normal breast tissues, ductal carcinoma (DCIS), and invasive ductal carcinomas (IDC). We found significant tissue and tumor subtype-specific differences in multiple cell types including T cells and neutrophils. Gene expression profiling of CD45CD3 T cells demonstrated a decrease in CD8 signatures in IDCs. Immunofluorescence analysis showed fewer activated GZMBCD8 T cells in IDC than in DCIS, including in matched DCIS and recurrent IDC. T-cell receptor clonotype diversity was significantly higher in DCIS than in IDCs. Immune checkpoint protein TIGIT-expressing T cells were more frequent in DCIS, whereas high PD-L1 expression and amplification of (encoding PD-L1) was only detected in triple-negative IDCs. Coamplification of a 17q12 chemokine cluster with subdivided HER2 breast tumors into immunologically and clinically distinct subtypes. Our results show coevolution of cancer cells and the immune microenvironment during tumor progression. The design of effective cancer immunotherapies requires the understanding of mechanisms underlying immune escape during tumor progression. Here we demonstrate a switch to a less active tumor immune environment during the to invasive breast carcinoma transition, and identify immune regulators and genomic alterations that shape tumor evolution. .
©2017 American Association for Cancer Research.

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Franziska Michor uses the tools of theoretical evolutionary biology, applied mathematics, statistics, and computational biology to address important questions in cancer research.

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