30 research outputs found

    Cholangiocarcinoma: Correlation between Molecular Profiling and Imaging Phenotypes

    No full text
    <div><p>Purpose</p><p>To investigate associations between imaging features of cholangiocarcinoma by visual assessment and texture analysis, which quantifies heterogeneity in tumor enhancement patterns, with molecular profiles based on hypoxia markers.</p><p>Methods</p><p>The institutional review board approved this HIPAA-compliant retrospective study of CT images of intrahepatic cholangiocarcinoma, obtained before surgery. Immunostaining for hypoxia markers (EGFR, VEGF, CD24, P53, MDM2, MRP-1, HIF-1α, CA-IX, and GLUT1) was performed on pre-treatment liver biopsies. Quantitative imaging phenotypes were determined by texture analysis with gray level co-occurrence matrixes. The correlations between quantitative imaging phenotypes, qualitative imaging features (measured by radiographic inspection alone), and expression levels of the hypoxia markers from the 25 tumors were assessed.</p><p>Results</p><p>Twenty-five patients were included with a median age of 62 years (range: 54–84). The median tumor size was 10.2 cm (range: 4–14), 10 (40%) were single tumors, and 90% were moderately differentiated. Positive immunostaining was recorded for VEGF in 67% of the cases, EGFR in 75%, and CD24 in 55%. On multiple linear regression analysis, quantitative imaging phenotypes correlated significantly with EGFR and VEGF expression levels (R<sup>2</sup> = 0.4, <i>p</i><0.05 and R<sup>2</sup> = 0.2, <i>p</i><0.05, respectively), while a trend was demonstrated with CD24 expression (R<sup>2</sup> = 0.33, <i>p</i> = 0.1). Three qualitative imaging features correlated with VEGF and CD24 expression (P<0.05), however, none of the qualitative features correlated with the quantitative imaging phenotypes.</p><p>Conclusion</p><p>Quantitative imaging phenotypes, as defined by texture analysis, correlated with expression of specific markers of hypoxia, regardless of conventional imaging features.</p></div

    Characterization of hepatocellular adenoma and carcinoma using microRNA profiling and targeted gene sequencing

    No full text
    <div><p>Background</p><p>Hepatocellular adenomas (HCA) are benign liver tumors that may transform into hepatocellular carcinoma (HCC), but the molecular drivers of this transformation remain ill-defined. This study evaluates the molecular changes in HCA and HCC and in comparison to their adjacent non-neoplastic liver.</p><p>Methods</p><p>11 patients with HCA and 10 patients with HCC without underlying hepatitis or cirrhosis were included in this pilot study. Tumor and non-tumor liver tissues were selected for immunohistochemical staining, small RNA sequencing, and targeted gene sequencing. We compared microRNA expressions and mutations between HCA and HCC and non-neoplastic liver.</p><p>Results</p><p>HCA were classified as inflammatory (n = 6), steatotic (n = 4), or β-catenin activated (n = 1) subtypes. MicroRNA profile of all 3 HCA subtypes clustered between that of normal liver and HCC in principal component analysis. In both HCA and HCC, miR-200a, miR-429, and miR-490-3p were significantly downregulated compared to normal liver, whereas miR-452, miR-766, and miR-1180 were significantly upregulated. In addition, compared to HCA, HCC had significantly higher expression of members of the chromosome 19 miRNA cluster (C19MC), including miR-515-5p, miR-517a, miR-518b, and miR-520c-3p.</p><p>Conclusions</p><p>This study indicates that while there are significant differences in the molecular profile between HCA and HCC, several miRNAs are similarly deregulated in HCA and HCC compared to adjacent normal liver. These results may provide insights into the drivers of hepatocarcinogenesis and warrant further investigations.</p></div

    Characterization of hepatocellular adenoma and carcinoma using microRNA profiling and targeted gene sequencing - Fig 3

    No full text
    <p>HCC had significantly higher mean expression of chromosome 19 miRNA cluster than HCA and normal liver adjacent to HCA in (A) miR-518b, (B) miR-520c-3p, (C) miR-515-5p, and (D) miR-517a. Horizontal bars represent mean value +/- standard deviation.</p

    Representative tumors with high and low values for each texture feature (A).

    No full text
    <p>Schematic of prediction model of protein expression constructed from quantitative imaging phenotypes. Quantitative image phenotypes are derived via texture analysis: the tumor region is extracted from CT, texture feature statistics are automatically computed based on the region of interest (B).</p

    Selected linear regression plots of texture features with respect to protein expression levels.

    No full text
    <p>The 95% confidence interval is rendered. For descriptive purpose, each protein is plotted against the texture feature that contributed the most to the prediction model (A). Two intrahepatic cholangiocarcinomas with low (top row) and high (bottom row) VEGF/EGFR protein expression by immunohistochemistry. After semi-automated segmentation of tumor borders from CT images, the tumor pixel attenuation values are evaluated for texture features. Axial slices of the segmented tumors are shown with texture features calculated for each slice and averaged. (B).</p
    corecore