CLEAR-CELL CELL CARCINOMA, TUMOR IMMUNITY, IMMUNOTHERAPY, TUMOR MICROENVIRONMENT, HIGHLY MULTIPLEXED IMAGING, IMAGING MASS CYTOMETRY
Renal cell carcinoma (RCC) is one of the ten most common human cancers and improved therapies are needed. Recently, immune checkpoint blockade immunotherapy has shown promise in patients with RCC. Predictive biomarkers to stratify patients for clinical trials, and ultimately in the clinic, are needed to design effective therapeutic strategies. The immune profile of cancer patients may predict therapeutic responses, and a recent study has identified immune subtypes in RCC that are associated with patient outcome. There has thus far not been a comprehensive molecular study of immune phenotypes in RCC and of how these phenotypes relate to clinical features or to response of patients to immunotherapy. The Bodenmiller lab has previously reported an atlas of immune phenotypes generated from a cohort of ccRCC patients, but these studies were carried out prospectively and on dissociated tumor cells and thus did not examine spatial aspects of the diseased tissue. However, cancer is a tissue disease, in which tumor, immune and stromal cells interact in a dynamic ecosystem to influence outcome. An understanding of tumor biology and of how it influences clinical progression and therapeutic response therefore require the tumor system to be studied in its entirety. In previous work (Moch), we have used automated image analysis of tumors from a RCC patient cohort to predict cellular and environmental features associated with tumor outcome. However, since this study was based on immunohistochemistry, we could examine a relatively limited number of markers. There remains a need for a comprehensive, multiplexed imaging study of the tumor and immune environment in ccRCC. We propose to comprehensively analyze the ccRCC tumor ecosystem by imaging mass cytometry (IMC), a highly-multiplexed imaging technique, in a cohort of about 700 ccRCC patients with associated clinical information. Critically, recent work has uncovered an association between loss-of-function mutations in the tumor suppressor PBRM1 with response to immunotherapy in ccRCC. There is considerable interest in understanding the phenotypic consequences of genomic changes in ccRCC and how immune phenotypic features may influence response to immunotherapy. As part of this study, we will sequence a large fraction of tumors from our cohort. We will relate features of the tumor-immune microenvironment to clinical outcome and to genomic information, in particular to PBRM1 status. We hope that our analysis will yield informative biomarkers for stratification of patients receiving immunotherapy, identify novel therapeutic targets, and shed light on ccRCC ecosystem biology.