Lung cancer is the leading cause of cancer death in the United States, accounting for approximately 160,000 deaths in 2009. The molecular mechanisms implicated in lung cancer development and progressions are not well understood. Recent evidence points to a complex interaction between the malignant cells and their microenvironment. However, much of our knowledge of the role of the tumor microenvironment comes from studies isolating the interactions between the malignant cells and a single component of the microenvironment, along a single pathway. We will reconstruct the first Tumor Microenvironment Interactome (TMI) of lung adenocarcinoma, which will identify global intra- and inter-cellular regulatory interactions between human malignant cells and their associated infiltrating immune cells, endothelial cells and fibroblasts. The TMI will be derived from global gene expression analysis of specific tumor microenvironment cell populations directly obtained from human lung cancer specimens using fluorescence-activated cell sorting (Specific Aim 1). The TMI will be reconstructed using novel computational approaches for inferring regulation among modules of genes (Specific Aim 2). From the TMI, we will identify candidate mediating factors, such as secreted cytokines, that regulate processes across the multiple cell subpopulations. We will specifically focus on the factors most associated with survival outcomes, by leveraging public domain expression data with long term survival outcomes (Specific Aim 2). We will use a combination of cell lines and animal models in the validation studies to test the effect of the candidate mediating factors on tumor behavior (Specific Aim 3). Through the reconstructed TMI, we will create a more global understanding of the lung tumor microenvironment. Our ultimate goal is to identify biologically and clinically relevant molecular targets that could be used to develop more effective therapies for lung cancer. The lung adenocarcinoma TMI will also be made publically available to the scientific research community as a hypothesis generation tool for evaluating the role of genes of interest.
We adopt a systems-biology approach to reconstruct a regulatory network of lung adenocarcinoma, deriving intra- and inter-cellular interactions. Our work promises to reveal novel therapeutic targets, as well as potential combinations of existing molecularly-targeted therapeutics that could lead to more effective treatment of human lung adenocarcinoma.
|Zhang, Weiruo; Bouchard, Gina; Yu, Alice et al. (2018) GFPT2-Expressing Cancer-Associated Fibroblasts Mediate Metabolic Reprogramming in Human Lung Adenocarcinoma. Cancer Res 78:3445-3457|
|Gentles, Andrew J; Bratman, Scott V; Lee, Luke J et al. (2015) Integrating Tumor and Stromal Gene Expression Signatures With Clinical Indices for Survival Stratification of Early-Stage Non-Small Cell Lung Cancer. J Natl Cancer Inst 107:|
|Newman, Aaron M; Liu, Chih Long; Green, Michael R et al. (2015) Robust enumeration of cell subsets from tissue expression profiles. Nat Methods 12:453-7|
|Zhao, Xi; Rødland, Einar Andreas; Tibshirani, Robert et al. (2015) Molecular subtyping for clinically defined breast cancer subgroups. Breast Cancer Res 17:29|
|Gentles, Andrew J; Newman, Aaron M; Liu, Chih Long et al. (2015) The prognostic landscape of genes and infiltrating immune cells across human cancers. Nat Med 21:938-945|
|Feng, Weiguo; Gentles, Andrew; Nair, Ramesh V et al. (2014) Targeting unique metabolic properties of breast tumor initiating cells. Stem Cells 32:1734-45|