Skip to main content
Fig. 11 | BioData Mining

Fig. 11

From: Joint analysis of multiple high-dimensional data types using sparse matrix approximations of rank-1 with applications to ovarian and liver cancer

Fig. 11

Expression profiles of selected nuclear receptors and transporter genes associated with the \( {\boldsymbol{K}}_1/{\boldsymbol{k}}_2 \) liver signature. Shown are normalized expression profiles of selected genes associated with the \( {\boldsymbol{K}}_1/{\boldsymbol{k}}_2 \) signature in two experimental designs denoted by ICCvsHCC and NRMvsTUMOR. Each lettered panel contains top and bottom sub-panels showing the profile of a gene in the ICCvsHCC and NRMvsTUMOR designs, respectively. In the top panels, columns 1–6 represent ICC samples and columns 7–28 HCC samples, while in bottom sub-panels, columns 1–20 represent normal samples and columns 21–50 represent liver tumors (6 ICC, 2 sarcomas and 22 HCC). Red squares represent ICC samples, green triangles represent CL-HCC samples, and blue circles represent normal and HCC samples. a Top panel shows FXR is down-regulated on ICC (cols 1–6) relative to HCC while the bottom panel shows that FXR is uniformly up-regulated on the normals and preferentially down-regulated on a subset of tumors that includes 6 ICC and 2 of 7 CL-HCC. b HNF4A shows expression patterns similar to FXR over the two groupings of the samples, i.e., preferential down-regulation on the ICC and CL-HCC relative to the normals and HCCs. c SLC2A1/GLUT1 is a transporter that is negatively correlated with the \( {\boldsymbol{K}}_1/{\boldsymbol{k}}_2 \) PET parameter and preferentially up-regulated on the ICC and CL-HCC samples relative to the normal and HCC samples. d SLC6A14 is strikingly up-regulated on all 6 ICC samples and less so on 5 of 7 CL-HCC samples relative to the normal and HCC samples

Back to article page
\