e20587 Background: Small cell lung carcinoma (SCLC) is an aggressive, tobacco-associated tumor with neuroendocrine features characterized by rapid growth, metastatic progression, and initial response followed by almost invariable resistance to therapy. Studies to date have not resolved the extent that diverse transcriptional programs drive SCLC and contribute to its lethality. Methods: We combined one of the largest and most diverse inventories of patient-derived xenograft models of SCLC with an ex vivo culture system that maintains transcriptional fidelity with matched primary SCLC tumor to identify transcriptional state heterogeneity. Using the expression of the Ascl1, NeuroD1, and Yap1 as markers of well-conserved SCLC states, we developed a state-of-the-art fluorescent platform that can directly measure single-cell state transitions in a multi-layered ecosystem using tandemly integrated reporters. We modeled population dynamics using a discrete time Markov chain and directly measure single-cell state transitions. Results: We show significant cell-state heterogeneity in several SCLC primary tumors, patient-derived xenografts (PDX), and ex vivo cultures. These states comprise distinct subpopulations marked by the master regulatory transcription factors (TFs) Ascl1, NeuroD1, and Yap1. Ex vivo, the 3 TFs are associated with suspension aggregates of small neuroendocrine cells, pre-suspension (loosely adherent) aggregates, and large mesenchymal cells with visible cytoplasm and spindle-like membrane extensions, respectively. We have observed equilibria in cell-state proportions in SCLC tumors both in vivo (PDX) and ex vivo. In addition, we have shown that the “elasticity” of SCLC responses, measured as the extent of clinical response during chemotherapy followed by the time to relapse from the end of therapy, is dependent on tumor TF levels. These observations suggest that mechanistic modeling of intra-tumoral state dynamics is of high clinical relevance. Conclusions: Our integrative approach is poised to formulate and validate a unified model of cellular states and program diversity in SCLC. If successful, the characterization of malignant cell ontogenic programs, their plasticity, and the advancement of new therapies designed to combat plasticity by epigenetic reprogramming will create a new scientific canvas for the study of this highly lethal disease.
Translational Traits of Non-Small-Cell Lung Carcinoma with Drug Resistances by Dual mRNA and Protein Quantification at the Single Cell Level
