The CAV1 Dependent Gene Expression Profile In Chronic Lymphocytic Leukemia
Advisor Information
Christine Cutucache
Location
UNO Criss Library, Room 231
Presentation Type
Oral Presentation
Start Date
7-3-2014 1:45 PM
End Date
7-3-2014 2:00 PM
Abstract
Caveolin-1 (CAV1), a cell membrane protein, is heterogeneously expressed in different types of cancer. In some types of cancer (i.e. breast cancer and prostate cancer), the protein is present in low amounts. Evidence suggests that this low expression promotes cell cycle progression. Conversely, we reported previously that high expression of CAV1 in chronic lymphocytic leukemia (CLL) in the lymph node and in the bone marrow correlates to lower survival rates and survival times for cancer patients. To determine the mechanism of action by which CAV1 expression can predict clinical prognosis in CLL, we used a bioinformatics approach to determine complete gene expression correlative to CAV1 expression in CLL tumor samples from 17 different patients. As expected, CAV1 expression was heterogeneous across samples. In fact, CAV1 expression variation exceeded 2 orders of magnitude among the samples. Genes whose expression correlated to CAV1 expression were validated via linear regression analysis. The results of these experiments included the identification of 165 genes whose expression correlated to the expression of CAV1 (n=17 |r|>0.7) in CLL cases from lymph node. These genes should be investigated for their role in disease progression in CLL.
The CAV1 Dependent Gene Expression Profile In Chronic Lymphocytic Leukemia
UNO Criss Library, Room 231
Caveolin-1 (CAV1), a cell membrane protein, is heterogeneously expressed in different types of cancer. In some types of cancer (i.e. breast cancer and prostate cancer), the protein is present in low amounts. Evidence suggests that this low expression promotes cell cycle progression. Conversely, we reported previously that high expression of CAV1 in chronic lymphocytic leukemia (CLL) in the lymph node and in the bone marrow correlates to lower survival rates and survival times for cancer patients. To determine the mechanism of action by which CAV1 expression can predict clinical prognosis in CLL, we used a bioinformatics approach to determine complete gene expression correlative to CAV1 expression in CLL tumor samples from 17 different patients. As expected, CAV1 expression was heterogeneous across samples. In fact, CAV1 expression variation exceeded 2 orders of magnitude among the samples. Genes whose expression correlated to CAV1 expression were validated via linear regression analysis. The results of these experiments included the identification of 165 genes whose expression correlated to the expression of CAV1 (n=17 |r|>0.7) in CLL cases from lymph node. These genes should be investigated for their role in disease progression in CLL.