Immune Infiltrate Dynamics in Cancer Progression
Abstract
Significance: Immunotherapies have demonstrated remarkable efficacy as anti-tumor agents in some patients; however, it is unclear why the majority of patients are unresponsive to immune activation. Recent evidence suggests that immune cells can both promote and inhibit tumor progression depending on the signals received from the tumor microenvironment. The two main cell types in the tumor microenvironment are fibroblasts and immune cells. An increased presence of fibroblasts is typically associated with poor prognosis while an increased presence of immune cells is an indicator of good prognosis. However, it is unclear if fibroblasts and immune cells affect prognosis independently or through an interdependent interaction. We have observed that fibroblast-rich tumors are also frequently rich in immune cells, ruling out the possibility of a simple spatial competition between these two cell types. It is important to note that immune cells are extremely diverse and that some immune cell types are anti-tumorigenic while others are pro-tumorigenic. We propose that fibroblasts alter the composition of immune cell infiltrates in tumors to tip the balance toward the pro-tumorigenic immune cell types. This hypothesis is supported by our preliminary data showing that fibroblast-rich tumors have an increased presence of pro-tumorigenic and decreased presence of anti-tumorigenic, immune cells. We will validate these data and attempt to therapeutically reverse the balance of immune cell types using three different approaches: Approach 1: Computational identification of fibroblasts and immune cell types associated with clinical outcomes. Since there are many immune cell types and their roles in anti-tumor immunity are poorly understood, we will first develop a computational model to identify potential immune cell types that are over-represented in fibroblast-rich tumors and under-represented in fibroblast-poor tumors. Such a computational approach is possible because more than 1,000 patient tumors have been sequenced and their genetic profiles stored in public repositories. Recently, individual immune cell types have also been sequenced. By comparing the genetic profile of each tumor with the genetic profile of each immune cell type, we can calculate the over- and under-representation of each immune cell type in each tumor. Based on their genetic profiles, we will group the tumors into fibroblast-rich and fibroblast-poor tumors to identify which immune cell types are differentially represented in these two groups. Using the same computational analysis, we will identify over- and under-represented immune cell types associated with clinical outcomes, such as chemoresistance, recurrence, and overall survival. Approach 2: Pathological validation of fibroblasts and immune cell types associated with clinical outcomes. Clinically relevant immune cell types identified by the computational approach will be validated in surgically removed primary, metastatic, and recurrent patient tumors using two methods. The first method uses specific representative markers to quantify immune cell types of interest in disaggregated human tumors. The second method uses similar markers to determine the location of specific immune cell types. The first method will allow for precise quantification of immune cell types during ovarian cancer progression while the second method will provide spatial information, such as whether the immune cells have successfully infiltrated the tumor islets or remained trapped by fibroblasts and whether certain cell types are spatially aggregated, indicating their possible physical interaction. By studying metastatic and recurrent tumors, we will also learn how tumor progression and chemotherapy change the spatiotemporal composition of individual immune cell types. Approach 3: Demonstrating the efficacy of anti-fibroblast agents in improving the immune response to tumors. Fibroblast-targeting therapeutic app
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 07, 2017
- Source ID
- W81XWH1710144
Entities
People
- Sandra Orsulic
Organizations
- Cedars-Sinai Medical Center
- United States Army