Small cell lung cancer (SCLC) is a devastating illness with frequent metastases and poor outcome. Years of research and innovative treatment yielded improved understanding of SCLC biology and control of symptoms, but little increase in the area of early diagnosis and tumor behavior. The major goals of this project are to discover and validate patterns of copy number alterations and of protein expression associated with clinically relevant outcomes such as diagnosis, response to therapy and prognosis of SCLC. Our specific hypothesis behind the proposed research is that SCLCs carry a number of copy number alterations that determines the expression profiles of proteins that are implicated in tumor progression, response to therapy and carry prognostic information. We will use three approaches to test the hypothesis. First, we propose to test this hypothesis with a unique in depth analysis of carefully selected SCLC tissues based on clinical outcomes with high throughput technologies. We will use combined genomic and proteomic analysis to select the most quantifiable candidate biomarker signatures in SCLC. These molecular signatures will lead to greater insight into lung tumorigenesis, tumor behavior and improved diagnostic tools to allow earlier and more targeted therapeutic interventions in an attempt to reduce the morbidity and mortality from SCLC. Second, we will perform a detailed comparative molecular analysis between SCLC and NSCLCs and address specificity of diagnostic signatures. We will use detailed biostatistical approaches to address stability of the signature which will highlight several novel genes/proteins associated with the disease and underscore a key molecular pathway that may offer promise in the design of future therapies. Third, because our preliminary data suggest a distinct role of focal adhesion pathway in SCLC progression, we propose to begin investigating this pathway and determine how it may impact on SCLC behavior. To achieve our goals, we propose the following specific aims:
Specific Aim 1 : We propose to identify SCLC-specific candidate biomarkers of diagnosis, time to progression and survival by detailed molecular analysis. We will test the hypothesis that SCLCs carry genomic alterations that determines the expression profiles of proteins that are implicated in tumor progression. Array CGH and shotgun proteomics represent our key discovery platforms.
Specific Aim 2 : We propose to perform a detailed comparative genomic and proteomic analysis between SCLC and NSCLCs to identify potential new molecular diagnostic targets. We will test the hypothesis that specific molecular pathways and potential therapeutic targets can be deduced from careful differential molecular analysis. The concept behind ourstrategy is the use of various approaches for theanalysis of clinically relevant samples obtainedfrom the same patient, along with the systematic integration of the biological and clinical data.
Specific Aim 3 : We propose to investigate the focal adhesion signaling pathway that emerges from our preliminary data as activated in SCLC. We will confirm FAK amplification in SCLC, determine the expression level in tissue microarrays, and determine a role of FAK in SCLC by blocking and knocking down, or overexpressing FAK. We will assess the impact of these changes primarily on cell adhesion, motility and invasion properties. We will determine the clinical correlates of this molecular pathway in tissue microarrays (TMA) for response to therapy, progression of disease and overall survival.
The management of lung cancer is a top priority in our Veterans population because of its high prevalence and associated mortality. Small-cell lung cancer (SCLC) is the most aggressive form of lung cancer and is strongly associated with cigarette smoking, a tendency for early dissemination, and short survival. This research proposal's main goal is to discover new molecular biomarkers of SCLC to address an urgent need for improved management of SCLC. Using state of the art revolutionary technologies will guide the identification of the involved genes and proteins that may represent new tools for early diagnosis, progression, and response to therapy. This translational work offers considerable promise for the benefit of this group of Veterans. Ultimately, by detecting SCLC early in its course, we hope to provide patients and loved ones with decrease pain and suffering and possibly a chance for a cure.
|Udyavar, Akshata R; Wooten, David J; Hoeksema, Megan et al. (2017) Novel Hybrid Phenotype Revealed in Small Cell Lung Cancer by a Transcription Factor Network Model That Can Explain Tumor Heterogeneity. Cancer Res 77:1063-1074|