Tumor-Immune Microenvironment Landscape of B-Lymphoblastic Leukemia in Bone Marrow Biopsies
Mentor Name: Vinodh Pillai
B-cell-acute lymphoblastic leukemia (B-ALL) is the most common cause of pediatric cancer. CD19-directed CAR T-cell therapy was developed at the University of Pennsylvania and tested at the Children’s Hospital of Philadelphia (CHOP) for the treatment of relapsed B-ALL. However, 15% of B-ALL patients do not achieve clinical remission or only show a partial response to CD19-directed CAR T-cell therapy. A significant subset of these patients also eventually relapses again, despite achieving clinical remission with CAR T-cell therapy. Thus, while novel immunotherapeutic agents such as blinatumomab, inotuzumab and CAR T-cell therapy are effective in treating relapsed B-ALL, it is difficult to predict who will respond to different immunotherapy treatments.
We hypothesize that the bone marrow biopsy tumor-immune microenvironment (TIME) impacts the response to various immunotherapeutic agents. Leukemia-infiltrating lymphocytes (LILs) are a crucial component of the TIME and reflect the ability of the host to mount an antitumor immune response. In addition, bone marrow fibrosis and/or immune suppressive microenvironment limits therapeutic access to the tumor compartment. However, TIME analysis has not been evaluated as a predictor of response to immunotherapy in B-ALL.
In this project, we aim to assess the B-ALL bone marrow TIME using a multiparametric approach: 1) The baseline LIL patterns of normal and B-ALL bone marrow biopsies will be established using CD3 immunohistochemistry (IHC), a prototypic pan T-cell marker that highlights all subsets of T cells. 2) Digital imaging will be used for a quantitative and qualitative assessment of the LIL patterns of pre-CAR bone marrow biopsies in a discovery cohort of CAR T-cell treated patients (n=166). 3) The baseline transcriptional signature of the immune and stromal microenvironment of normal and B-ALL bone marrows will be determined using a targeted 1392 gene panel (covering tumor and immune response genes and pathways). Through these analyses, baseline TIME in various genetic subtypes of B-ALL will be established. The TIME differences between diagnostic and relapsed B-ALL will then be ascertained using bioinformatic analysis of bulk and spatial transcriptomics and IHC data. Differences in the pre-infusion LIL patterns of responders, non-responders and relapses will be used to develop a model that will predict response to CAR T-cell therapy. Clinical and laboratory Standard Institute (CLSI) guidelines for laboratory test validation will be followed.
