My projects currently focus on the role of immune cells in neuro-glial tumor development. For example, the interactions between tumor and its microenvironment are often critical to uncovering the mechanisms of tumor survival. A striking example is the recent success of immunotherapy approaches that expose tumor cells to immune attack by disrupting a specific interaction between the tumor and infiltrating lymphocytes. The tumor can also repress immune response by inducing complex interactions among dozens of immune and stromal cell types that typically make up tumor microenvironment, however those remain largely uncharacterized as we currently lack systematic approaches to uncover relevant cell-cell interactions. The alternative to killing tumor cells, either directly or through immune system, is to force them to differentiate. Such strategy is particularly promising for tumors arising due to failure of progenitor populations to follow proper differentiation cascade. Here as well, the progress has been limited by lack of understanding of specific intercellular signals that that are disrupted in tumorigenesis.
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We use a systematic approach for characterizing cell-cell interactions in complex microenvironments through joint analysis of spatially-resolved and disassociated single-cell transcriptomics. We apply it to identify inter-cellular signals and pathways that can push tumors of neural crest origin, including as pheochromocytoma (PCC), paraganglioma (PGL) and neuroblastoma (NB), towards terminal differentiation. Building on our expertise with neural crest development, we use single-cell profiling to map individual tumor cells onto developmental trajectory of neural crest differentiation. Spatial transcriptomics analysis is used to identify the sources and nature of microenvironment signals that channel neural crest differentiation during normal development. Contrasting interactions in normal and tumor tissues we aim to identify factors, pathways or signals that would push that PCC, PGL and NB tumors towards terminal sympatho-adrenal fates. The development of this novel systematic approach requires a combination of diverse expertise available in the assembled team, combining neurooncology with statistical models, immunology, computation, molecular and developmental biology.
Besides, knowledge of the pathways and target genes that can drive tumors into less metastatic and rather differentiated states can be a key for cancer treatment. To achieve this, we need to understand heterogeneity and ?differentiation-like? status of cancer cells as compared to their normal origin cell types. We also need to know the differentiation path of normal cancer-originating cells in terms of expressed genes and the role of microenvironment in differentiation process. The microenvironment and the exchange of signals between the cells within the tumor or in a developing embryo are keys defining the properties and structure of populations as well as for driving their transitions. We harness the power of knowledge of such interactions interpreted within a logic of normal development superimposed onto tumors. Here, we use human sympatho-adrenal cancers and mouse model systems to develop such comparative microenvironment and differentiation trajectory analysis, to make predictions and, finally, perform pre-clinical validations of envisioned tumor-differentiation strategies.
Our preliminary data point at specific nerve-associated progenitors in adrenal gland as a likely reservoir for NB, PCC and PGL progenitors in the sympathoadrenal region (see our recent manuscript in Furlan et al., Science 2017). Our approach is based on unbiased classification of cell subtypes (Fan et al., 2016) and their computational alignment along a multidimensional manifold that may take a different shape depending on a branching nature of the cell fate decision tree. Our new method (manuscript in revision, Nature) that works differently from published analogs (Shin et al., 2015; Trapnell et al., 2014) allows to identify fate split points and fate-controlling genes that might play a role in cancer initiation specifically under the influence of specific mutations that can be tested in this bioinformatics framework. Our biological hypothesis includes that abnormal fate-selection events in specific sympathetic, glomus and chromaffin progenitors and stem cells can lead to cancer development. Currently, it is not clear how fate selection and decision-making machinery (Hardwick and Philpott, 2014) is related to the development of cancer. For the first time, we explore this dimension of cancer biology.