Presentation Title

Characterization of the Role of CAV1 in Cellular Proliferation Pathways in a CD4+ T Helper Cell

Advisor Information

Christine Cutucache

Location

Dr. C.C. and Mabel L. Criss Library

Presentation Type

Poster

Start Date

7-3-2014 1:00 PM

End Date

7-3-2014 4:00 PM

Abstract

Caveolin-1 (CAV1) is a vital scaffold protein that regulates tumor progression in various types of cancers and is overexpressed in T and B cell lymphocytic leukemias (Sawanda et al., 2010; Goetz et al., 2008). Additionally, previous studies have revealed that CAV1 is involved in cell-to-cell communication, cellular migration, and immune synapse formation-all malfunctions present in hematological malignancies (Mittal et al., 2009; Gilling et al., 2010; Gilling et al., 2012). As these are vital components of the immune response and cancer progression, we hypothesize that CAV1 regulates key functions in immune effector cells such as CD4+ T lymphocytes. Therefore, we examined the mechanism of action of CAV1 on cellular proliferation in a CD4+ T helper cell. Using the Cell Collective model-building software, an in silico model with the ability to dynamically model molecular signaling in T lymphocytes was constructed. This model, consisting of 193 nodes and local interactions involving CAV1, was successfully validated with primary literature and in vitro immunohistochemistry results. Next, the model was simulated under various conditions, including CAV1 +/+, CAV1+/-, and CAV1-/-, in both normal and diseased samples. Experimental results indicate a signature of molecules that were highly affected by CAV1 knock out. Specifically, CAV1 regulates cellular proliferation, cell survival, and cytoskeletal rearrangement-all of which are documented to be upregulated in lymphocytic leukemias. These results will be further validated with in vivo experiments using Cav1-/- mice to determine the impact that Cav1 has on downstream molecules contributing to cellular proliferation. With this comprehensive model, protein expression levels and consequences of gene mutations can be predicted and valuable insight regarding biological systems can be elucidated.

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COinS
 
Mar 7th, 1:00 PM Mar 7th, 4:00 PM

Characterization of the Role of CAV1 in Cellular Proliferation Pathways in a CD4+ T Helper Cell

Dr. C.C. and Mabel L. Criss Library

Caveolin-1 (CAV1) is a vital scaffold protein that regulates tumor progression in various types of cancers and is overexpressed in T and B cell lymphocytic leukemias (Sawanda et al., 2010; Goetz et al., 2008). Additionally, previous studies have revealed that CAV1 is involved in cell-to-cell communication, cellular migration, and immune synapse formation-all malfunctions present in hematological malignancies (Mittal et al., 2009; Gilling et al., 2010; Gilling et al., 2012). As these are vital components of the immune response and cancer progression, we hypothesize that CAV1 regulates key functions in immune effector cells such as CD4+ T lymphocytes. Therefore, we examined the mechanism of action of CAV1 on cellular proliferation in a CD4+ T helper cell. Using the Cell Collective model-building software, an in silico model with the ability to dynamically model molecular signaling in T lymphocytes was constructed. This model, consisting of 193 nodes and local interactions involving CAV1, was successfully validated with primary literature and in vitro immunohistochemistry results. Next, the model was simulated under various conditions, including CAV1 +/+, CAV1+/-, and CAV1-/-, in both normal and diseased samples. Experimental results indicate a signature of molecules that were highly affected by CAV1 knock out. Specifically, CAV1 regulates cellular proliferation, cell survival, and cytoskeletal rearrangement-all of which are documented to be upregulated in lymphocytic leukemias. These results will be further validated with in vivo experiments using Cav1-/- mice to determine the impact that Cav1 has on downstream molecules contributing to cellular proliferation. With this comprehensive model, protein expression levels and consequences of gene mutations can be predicted and valuable insight regarding biological systems can be elucidated.