RCCs affect a wide range of demographics in the U.S. At the time of diagnosis, ~30% of RCC patients already have metastatic disease and ~30% of patients will recur. 5-year survival for patients who recur is smaller than 10%. Although immunotherapy is transforming cancer care, the response rate is only ~25%, and it’s still unclear how to distinguish responsive patients. The stroma/immune cellular components are critical for immunotherapy response and prognosis in RCC patients. Therefore, it is essential to accurately characterize tumor immunity responses in RCC on the genome-wide scale. We propose to first dissect bulk tumor expression into the tumor cell, normal parenchyma, and tumor stroma/...

Read More

RCCs affect a wide range of demographics in the U.S. At the time of diagnosis, ~30% of RCC patients already have metastatic disease and ~30% of patients will recur. 5-year survival for patients who recur is smaller than 10%. Although immunotherapy is transforming cancer care, the response rate is only ~25%, and it’s still unclear how to distinguish responsive patients. The stroma/immune cellular components are critical for immunotherapy response and prognosis in RCC patients. Therefore, it is essential to accurately characterize tumor immunity responses in RCC on the genome-wide scale. We propose to first dissect bulk tumor expression into the tumor cell, normal parenchyma, and tumor stroma/immune components, and based on this, to further focus on the profiling of stroma immune infiltrations. Aim 1: Develop a Bayesian model to dissect bulk RCC gene expression into the tumor, stroma (immune) and normal components. We will use data from 35 matched patient trios, with each trio consisting of one bulk tumor, one tumorgraft, and one adjacent normal tissue RNA-Seq dataset. Aim 2: Profiling stromal immune cell infiltration in new tumor samples without matched tumorgraft RNASeq data by 1) refining signature genes for various types of immune cells and 2) developing a novel differential enrichment algorithm. Aim 3: Determine the capability of immune infiltrate data for predicting prognosis and response to immunotherapy for RCCs. Prognostic and predictive modeling will be carried out based on the abundances of different types of stromal immune cells (Aim 2). Impact: (1) The prognostic and predictive algorithms for clinical outcomes will allow clinicians to tailor a treatment plan for each individual patient; (2) The delineation of the infiltrating immune cells will enhance our understanding of the mechanism of tumor immunity; (3) Characterizing the expression profiles of each cellular component in tumor will lead to a comprehensive view of RCC molecular mechanisms.

Read Less