Tumor Immune MicroEnvironment Facility

Division Of Basic Sciences - Nci

Investigators

Linked publications, trials & patents

Abstract

The microenvironment consists not only of tumor cells but also of physiological tissues which include the stroma with fibroblasts, blood vessels and white blood cells, especially T lymphocytes and macrophages, whose precursors are monocytes deriving from the myeloid lineage. Some tumors have a rich T lymphocyte infiltration. Innate immunity cells such as macrophages, granulocytes and immature myeloid cells from which monocytes or macrophages derive are also found in different densities. To study the evolvement of TIME and the interaction between tumor cells and other immune cells we developed and validated mainly 3 different panels of biomarkers to immuno-stain Formalin fixed paraffin embedded tumor tissue sections using immunofluorescence and opal technique. Each one of these panels included 7 markers. Panel 1 included: CD4, CD8, FOXP3, PDL1, Ki67, CK and Dapi. we use panel1 to phenotypically identify T lymphocytes and their subgroups: T helpers, Cytotoxic T cell, T regulators. Panel 2 included: CD68, CD163, CD56, CD4, CD8 and Dapi. We use panel 2 to identify macrophages and both subtypes, M1 and M2 and their interactions with CD4+ cells and CD8+ cells. Panel 3 included CD11b, CD68, CD14, CD15, CK, HLA-DR and DAPI. We use panel 3 to identify Myeloid derived suppressor cells MDSCs and both subtypes monocyte M-MDSC and Poly-morpho-nuclear PMN-MDSC. Applications and results: Immunotherapy, as a single agent, provides benefit to a small subset of PC patients, which is thought to be partially due to its known cold tumor immune microenvironment (TIME).. Prostvac is a therapeutic cancer vaccine engineered to activate an immune response against prostate-specific Antigen (PSA). Prostvac alone could induce systemic immune response by increasing immune-cell infiltrates in and around the tumor. In our study published in JITC 2020, 27 prostate cancer patients were enrolled in a an open-label, phase II study of neoadjuvant Prostvac vaccine. We evaluated increases in CD4 and CD8 T-cell infiltrates in Radical Prostatectomy (RP) tissue vs baseline biopsies, using our panel 1. We found that for non-compartmentalized analysis (NCA) and compartmentalized analysis (CA), tumor CD4 T-cell infiltrates were significantly increased in postvaccination RP specimens compared with baseline biopsies by NCA . By CA, an increase in both CD4 T-cell infiltrates at the tumor infiltrative margin and in CD8 T-cell infiltrates at the tumor were noted in postvaccination RP specimens compared with baseline biopsies. In a complimentary study, we explored the effect of Prostvac in combination with nivolumab in TIME of prostate cancer. We treated locally advanced prostate cancer patients (n=6) undergoing RP with neoadjuvant Prostvac in combination with nivolumab. Dynamic changes in TIME before and after treatment were studied using multiplex immunofluorescence (Opal Method). FFPE sections from matched pre-treated prostate biopsies and post-treated RP samples were stained with our validated T cell panel1. Combination immunotherapy significantly increased CD4+ T cells and CD8+ T cells densities in the invasive margin, intratumoral and the benign compartments. 5/6 and 4/6 patients showed more than 2Xincrease of CD4 and CD8 T cells in the TIME, respectively, in at least one of the three compartments, showing more effect that Prostvac alone. Increased proliferative indices in CD4+ and CD8+ T cells were also seen after treatment. Tregs were present in low frequencies in TIME (maximum of 12 cells/mm2) with no significant changes. Moreover, a significant drop in tumor cell Ki67 after treatment) suggests that the combination may control tumor growth. The combination of Neoadjuvant Prostvac and nivolumab was associated with increased immune cell infiltration in a cohort of early prostate cancer patients. More patients (10) will be enrolled in this combination study to confirm our finding and that the combined therapy has more benefit than the vaccine alone The Division of Cancer Prevention, NCI sponsored a study of Prostvac vs. Placebo in the active surveillance setting in prostate cancer. In this multicenter study, 154 patients with indolent localized prostate cancer who elected to go on active surveillance, were randomized 2:1 to receive vaccine vs. empty vector placebo. The primary endpoint of the study is immune infiltrate in vaccinated patients vs. placebo patients. We have other ongoing studies that involves clinical trials using bintrafusp alpha on patients with metastatic or locally advanced solid tumors. Expression of both TGF-Beta and PDL1 has been linked with poor prognosis in patients with cancer. Two agents targeting the PD1 / PDL1 pathway have been recently approved by the FDA with impressive duration of responses. Unfortunately, only a fraction of patients develops these responses. M7824 has been shown to have improved activity compared with the parent anti-PDL1 antibody (avelumab), which is now in phase III clinical testing. Bintrafusp alfa (M7824) is a bifunctional fusion protein that targets TGF Beta and PDL1. We have great interest to look at the changes happening in TIME after treatment with bintrafusp alfa. First, we looked at the changes of macrophages densities in non-small lung cancer cohort, and we found that for patients that had progressive disease there was an increase in M2 macrophages and a decrease in M1 macrophages. M1 densities increased in patients that has stable disease, along with T helpers and Cytotoxic T cells. M2 densities decreased in these patients after treatment. The presence of MDSCs in these tumors and their dynamic change is still under investigation. We are investigation the changes in TIME in patients with other cancer types and treated with bintrafusp alfa under protocols 15-C0179 and 18-C0056.We are requesting more tumor samples to have a high number of paired samples with matched pre and post treated samples. in a collaboration with the group of engineers at the Frederick national labs and the Brigham and women's hospital Harvard medical school, we are looking at TIME from spatial distribution angle. We are using our paired samples from patients treated with Bintrafusp alfa to develop a platform that leverage state-of-the-art image analysis techniques to better understand Whole Slide Images (WSI). Multiplex immunofluorescence (MxIF) images are few to 10s of channels that measure the expression of various markers (e.g., CD4, PD-L1, etc.) and therefore are an order of magnitude larger than H&E images. The use of artificial deep neural networks to automatically extract embedded features or patterns helps overcome challenges in traditional MxIF analysis and potentially enables high-level information beyond SA of images. We aim to build on advances in WSI analysis that enable cell-cell interactions to be represented as a graph that can be used as input to dimensionality reduction techniques like autoencoders. Working with a smaller dimension space allows us to use unsupervised clustering and form new groups of the Regions of Interest (ROIs) extracted from the WSI. These groups can suggest new hypotheses that explain the reasons behind the effectiveness of the drug. We will augment and test weakly supervised learning techniques where a single label is provided per WSI to predict the clinical outcome. We will use multiple-instance learning where ROIs with mixed positive and negative signals collectively predict the label of the WSI. Finally, we will utilize recent deep learning techniques like attention to identify important ROIs in the WSIs in making the clinical prediction. This study will push the frontiers of TIME analysis to better understand drug effects and prescribe new promising treatments for patients with cancer.