Abstract Small Cell Lung Cancer (SCLC) is characterized by rapid tumor growth and currently, there are few therapeutic options or predictive biomarkers. Patient derived xenograft (PDX) models are capable of recapitulating solid tumor growth including the intra-tumor heterogeneity (ITH) observed in the original patient tumor. The present study aimed to correlate surface marker profiles of SCLC PDX models with previously observed drug responses to M2698, a potent, selective inhibitor of p70S6K and AKT 1/3, and investigate ITH through gene expression profiling of tumor cell subpopulations. Drug response data had been established in a preclinical screen of 45 PDX models of SCLC, in which two mice were implanted subcutaneously with tumors from each model; one mouse was treated with vehicle while the other was treated with M2698 25 mg/kg QD po until the tumor in the vehicle-treated mouse reached ~1200 mm3. Tumor control (stasis or regression) was seen in 12 (27%) of the models. We showed previously that cell surface marker profiles of PDX tumor tissue demonstrated high intra-model reproducibility for many surface markers and uniquely associate with each model. Also, distinctly heterogeneous markers were identified that allowed FACS sorting of tumor cell subpopulations with similarly distinct gene expression profiles. To build on these data, a subset of models that were the most and the least sensitive to M2698 (n=7) in the above described screen were selected for implantation into a new set of mice. Tumors were profiled once they reached ~800 mm3. We evaluated 80+ markers commonly used to identify tumor initiating cells (e.g. CD44, CD90, CD133, CD166, CD184), EMT or aggressiveness (e.g. CD166, EphB2, CD324, CD325), poor outcome in SCLC (CD49b, CD221, claudin3) or drug targets (e.g. CD184, EGFR, Her2) to establish extensive marker profiles. Our data reveal that surface marker profiles in these models allow a meaningful subclassification of SCLC PDX tissue. Correlation of these profiles with efficacy of M2698 (above) suggest that surface markers may have predictive value. Our results prequalify a number of these markers for validation. Furthermore, several models harbor cell subpopulations identifiable by various surface markers. Along with their distinct gene expression profiles this suggests an equilibrium between functionally different compartments within a lesion. In one case, the ratio of two populations shifted concurrently with growth differences, raising the possibility of a dynamic relationship between this equilibrium and the growth stage. Overall, our workflow may provide tools for sample characterization, quality control and elucidation of cellular response markers to varying selective pressures, such as drug challenges. Citation Format: Warren Porter, Eileen Snowden, Friedrich Hahn, Mitchell Ferguson, Frances Tong, William S. Dillmore, Anderson Clark, Hong Zhang, Rainer Blaesius. Surface protein marker and single cell gene expression profiling of individual tumor cells dissociated from small cell lung cancer pdx mouse models can be correlated with in vivo sensitivity to the p70S6K/AKT1/3 inhibitor M2698 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4710.