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Full-Text Articles in Biostatistics
Upregulation Of Cd36, A Fatty Acid Translocase, Promotes Colorectal Cancer Metastasis By Increasing Mmp28 And Decreasing E-Cadherin Expression, James Drury, Piotr G. Rychahou, Courtney O. Kelson, Mariah E. Geisen, Yuanyuan Wu, Daheng He, Chi Wang, Eun Y. Lee, B. Mark Evers, Yekaterina Y. Zaytseva
Upregulation Of Cd36, A Fatty Acid Translocase, Promotes Colorectal Cancer Metastasis By Increasing Mmp28 And Decreasing E-Cadherin Expression, James Drury, Piotr G. Rychahou, Courtney O. Kelson, Mariah E. Geisen, Yuanyuan Wu, Daheng He, Chi Wang, Eun Y. Lee, B. Mark Evers, Yekaterina Y. Zaytseva
Surgery Faculty Publications
Altered fatty acid metabolism continues to be an attractive target for therapeutic intervention in cancer. We previously found that colorectal cancer (CRC) cells with a higher metastatic potential express a higher level of fatty acid translocase (CD36). However, the role of CD36 in CRC metastasis has not been studied. Here, we demonstrate that high expression of CD36 promotes invasion of CRC cells. Consistently, CD36 promoted lung metastasis in the tail vein model and GI metastasis in the cecum injection model. RNA-Seq analysis of CRC cells with altered expression of CD36 revealed an association between high expression of CD36 and upregulation …
Multivariate Statistical Modeling For Radio-Genomics Study, Tiantian Zeng
Multivariate Statistical Modeling For Radio-Genomics Study, Tiantian Zeng
Theses and Dissertations--Statistics
Radiogenomics is a new direction in cancer research that focuses on the associations among radiomics, genomics and clinical outcome. Currently, the major challenge for Radiogenomics lies in the effective integration of genomics and imaging data for promising clinical outcome prediction. Herein, we propose a multivariate joint model that can integrate imaging and genomic data for better predicting the clinical outcome. Specifically, we jointly consider two multivariate group lasso models, one regresses imaging features on genomic features, and the other regresses patient’s clinical outcome on genomic features. An L1 penalty term is introduced for each variable, and weight in the penalty …