Carcinoma progression and metastasis are directed by interactions between epithelial tumor cells and components of the tumor cell microenvironment. In particular, cell-extracellular matrix (ECM) interactions have been demonstrated to influence tumor growth, metastatic potential, and drug resistance. However, the complexity of ECM composition within in vivo tumor microenvironments has limited the understanding of the underlying mechanisms. We have recently developed a cell microarray platform that enabled the systematic analysis of lung adenocarcinoma cell drug responses within defined ECM microenvironments. This approach further facilitated the assessment of the role of ASCL1, a transcription factor associated with a subset of adenocarcinoma tumors exhibiting neuroendocrine differentiation. Building on these findings, we hypothesize that ECM composition influences adenocarcinoma cell signaling and sensitivity to drugs, and that neuroendocrine tumor cells are differentially regulated by ECM components. Here, we propose to examine these processes by incorporating both patient sample analysis and controlled in vitro experiments.
In aim 1, we will examine the ECM composition within stage I adenocarcinoma tumor samples. We will aim to define patient-to- patient variation as well as evaluate potential differences between ASCL1(+) and ASCL1(-) tumors. In addition, we will explore potential correlations between ECM composition and patient outcome.
In aim 2, we will investigate the effects of ECM on cell signaling and drug responses using adenocarcinoma cell lines with differential levels of ASCL1 expression. In these studies we will examine the functional effects of ECM and ASCL1 interactions. We anticipate that these studies will reveal new insights into the combinatorial regulation of drug responses and establish ECM expression profiles as potential biomarkers towards the personalization of lung adenocarcinoma treatments.
The overall goal of this project is to identify extracellular matrix biomarkers of drug response in lung adenocarcinoma. These efforts will establish foundational insights into how the interplay between extracellular matrix composition and intrinsic gene expression characteristics influence cell signaling and drug responsiveness, and will set the stage for the development of targeted therapies for tumors with distinct matrix and genomics profiles.
