Distinct Signaling Profiles and Drug Responses Identify Subpopulations of Pediatric T-Cell Acute Lymphoblastic Leukemia and Lymphoma Patients.

Abstract 1595

Poster Board I-621

Intensive chemotherapy has dramatically improved cure rates for children with T-cell acute lymphoblastic leukemia (T-ALL) and lymphoblastic lymphoma (T-LL). However, short-term and long-term toxicities have also increased while response rates to salvage therapy for relapsed patients remain dismal. Unfortunately, due to limits of technology and the paucity of clinical material available in children that often present with large mediastinal masses, biologic parameters for risk stratification of pediatric T precursor malignancies are limited relative to pre-B ALL. Thus, most T-ALL/LL patients are treated similarly on current protocols. Limited biologic features for risk stratification likely results in overtreatment of some children while precluding patients with high-risk disease from novel therapeutic approaches upfront. Since aberrant signal transduction is a key feature driving malignant cell behavior, we hypothesized that malignant T cells would possess distinct signaling networks relative to normal thymocytes and that differences in signaling profiles could be used to identify distinct subpopulations of T-ALL/LL patients at diagnosis. To test this hypothesis, we developed a phospho-flow cytometry platform to interrogate signaling networks at the single cell level in normal and malignant T precursor cells. Previous studies in mice and humans demonstrated that approximately 95% of thymocytes normally die before exiting the thymus. Since functional T cell receptor (TCR) and IL-7 signals are known to be critical for normal thymocyte survival, we reasoned that malignant T cells might retain dependence on these signaling networks. We thus optimized stimulation conditions with both sub-optimal and saturating concentrations of anti-TCR, anti-CD28 co-stimulation, IL-7, PMA, and pervanadate. Anti-sera to 15 key intracellular protein targets in these signaling networks were validated. To distinguish malignant from normal cells, cell surface staining for 8 epitopes that survive the fixation and permeabilization steps of the assay was established. Fluorescent cell bar coding was utilized for analysis of multiple samples in a single tube, enabling high-throughput screening while minimizing experimental variability and reagent use. Using this novel platform we simultaneously measured the phospho-protein response of 107 signaling nodes in the basal state and in response to stimulation in precursor T cell lines and a panel of banked patient samples. Analysis of pilot data identified the most robust and key signaling nodes for each of the major MAPK, PI3K, and JAK-STAT pathways. Given the limited number of cells in most tissue bank samples, we then focused the platform on the 30 most informative signaling nodes. Simultaneous measurement of pERK, pS6, pSTAT5, pBcl-2, Bcl-Xl, pNFkB, PTEN, intracellular Notch and PI3K levels in the basal state and with stimulation reveals T-ALL/LL patient subpopulations with distinct signaling profiles. Interestingly, a dichotomous pattern of either hypo- or hyper-responsiveness to stimulation is emerging. Measurement of patient signaling networks is also elucidating complex crosstalk between the classically separate MAPK and PI3K signaling pathways. Informed by the patient data, targeted inhibitors are being used to unveil the interdependence of these pathways in response to stimulation and their role in apoptosis. We have also extended this approach to analyze drug responses in patient samples in vitro at the single cell level. Using a Casapse 3 based flow-cytometry assay, we find distinct patterns of sensitivity to dexamethasone, methotrexate, and nelarabine in primary patient samples. The data demonstrates that flow cytometry represents a powerful approach for reliably interrogating the biologic properties of malignant T cells, reveals distinct subpopulations of T-ALL/LL patients that were previously unappreciated, may potentially discover synergistic uses of targeted inhibitors for therapy and perhaps even highlight novel drug targets. This approach warrants further study to determine whether these profiles have prognostic significance and whether in vitro drug responses could be used to predict outcome in the context of clinical trials.