Tumors are often highly heterogeneous, with a number of functionally different cells existing within a single tumor, giving some cells the ability to initiate new tumors, metastasize, and/or become resistant to chemotherapy. Small Cell Lung Cancer (SCLC) is often a heterogeneous tumor, and is characterized by a low 5- year survival rate, high metastatic rates, and rapid acquisition of chemoresistance. The heterogeneous nature of this tumor makes it difficult to study and to treat, as current attempts to understand tumor dynamics use a bulk approach that averages the contribution of all cells within a tumor. Commonly upregulated in cancer, the core pluripotency networks of Sox2, Oct4, and Nanog have a profound effect as master regulators of pluripotency, and their expression in cancers leads to poor clinical outcomes. Sox2 in particular is often highly expressed in SCLC, and is a marker of lung progenitor cells. Expression of these factors can reprogram cells to an induced pluripotent state, and may contribute to enhanced plasticity in cancer. Therefore, I hypothesize that the dysregulation of pluripotency factors imparts a high degree of cellular plasticity SCLC, driving its growth, metastasis, and chemoresistance. I will test this hypothesis in two aims using a cellular barcoding lineage tracing approach combined with single-cell RNA sequencing (scRNAseq).
Aim 1 seeks to trace the contribution of individual cells towards tumor growth and chemoresistance in xenograft models of SCLC. I will use a lentivirus that will insert a unique genetic barcode, as well as a GFP tag in to SCLC cell lines that represent the two most common molecular subtypes of SCLC. The cells will be sampled prior to xenografting, and will then be xenografted in to nude mice. At the end of this aim, the endpoint xenograft, as well as the early tumor sample will be evaluated by scRNAseq, which will provide data to evaluate gene networks responsible for tumor initiation, progression, and chemoresistance. I will validate identified candidates by knockdown experiments in cell culture to elucidate the role of the gene candidates, with a particular focus on progenitor and stem pathways.
Aim 2 will describe the genes responsible for growth, metastasis, and chemoresistance in a mouse model of SCLC. The well-characterized SCLC Rblox/lox, p53lox/lox, p130lox/lox mouse model, bread to an H11lox-stop-lox-Cas9 mouse will be used in combination with an adeno-associated virus containing a gRNA to Rosa26, and Rosa26 homology arms flanking a GFP and barcode sequence. Shortly after tumor initiation by intratracheal Cre expression, the barcoding-AAV will be injected into the trachea in order to barcode the newly-formed tumors. After tumors grow, metastasize, and acquire chemoresistance, they will be dissected and primary tumors, metastases, and early tumor samples collected by intratracheal brushing will undergo scRNA-seq to identify the genes responsible for growth, metastasis, and chemoresistance. The successful completion of this work will identify the genes responsible for tumor dynamics, develop the in vivo cellular barcoding approach and lead to the identification of potential therapeutic targets.
Small Cell Lung Cancer (SCLC) is a very aggressive tumor with a low 5-year survival rate and very high rates of metastases. Part of what makes this tumor so devastating and difficult to treat is that it is a heterogeneous tumor, meaning there are sub-population(s) of cells within a single tumor that may have the ability to form new tumors in distant organs, and/or are resistant to chemotherapy. Traditionally, this sort of cellular heterogeneity within a single tumor is difficult to study, as there is no good way to trace individual cells over the course of a tumor's life, However, this proposed research will utilize genetic barcode technology to trace cells during the progression of the tumor, and study their genetics during tumor development. The knowledge gained from this research will expand our understanding of the genetics of SCLC, and lead to potential therapeutic targets.
