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Activity Number:
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246
- Contributed Poster Presentations: International Indian Statistical Association
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Type:
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Contributed
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Date/Time:
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Monday, July 31, 2017 : 2:00 PM to 3:50 PM
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Sponsor:
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International Indian Statistical Association
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Abstract #324223
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Title:
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Linear Mixed Effects Model Approach to Analyze Change in Tumor Growth of Colorectal Cancer Mouse Model.
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Author(s):
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Ramu G Sudhagoni* and Khosrow Rezvani and Jessica Freeling
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Companies:
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The University of South Dakota and The University of South Dakota and The University of South Dakota
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Keywords:
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linear mixed models ;
longitudinal data ;
colorectal cancer ;
UBXN2A protein
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Abstract:
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Despite advances in treatment regimens, 50% of colorectal carcinoma (CRC) patients develop recurrent disease with an abysmal 5-year survival rate of ?12%. The primary barrier to reduce CRC mortality rates is the lack of gene targets capable of inhibiting CRC recurrence. A novel tumor suppressor gene called UBXN2A, an ubiquitin-like (UBX) domain-containing protein, has been shown to selectively inhibit tumor growth. Our central hypothesis for this study: UBXN2A is necessary and sufficient to inhibit CRC tumor growth in mouse model of colon cancer. To examine our research hypothesis: A linear longitudinal mixed effects model approach was utilized to model the change in tumor growth between Wild-Type and UBXN2A+/- mouse models over the time period. Our results provided in this study indicate that haploinsufficiency of UBXN2A can significantly increases tumorigenesis in mouse model of colorectal cancer probably in a gender dependent manner. This study will advance the field by defining the role of UBXN2A in CRC oncogenesis and will justify further pursuit of UBXN2A as a therapeutic target to improve the survival rate of patients with recurrent CRC.
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Authors who are presenting talks have a * after their name.
