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Radiogenomic Analysis to Identify Imaging Phenotypes Associated with Drug Response Gene Expression Programs in Hepatocellular Carcinoma

2007; Elsevier BV; Volume: 18; Issue: 7 Linguagem: Inglês

10.1016/j.jvir.2007.04.031

1535-7732

Michael Kuo, Jeremy Gollub, Claude B. Sirlin, Clara Ooi, Xin Chen,

Pancreatic and Hepatic Oncology Research

To determine whether conventional contrast-enhanced computed tomography (CT) could be used to identify imaging phenotypes associated with a doxorubicin drug response gene expression program in hepatocellular carcinoma (HCC) by using an integrated imaging-genomic approach.Thirty HCCs were analyzed and scored individually across six predefined imaging phenotypes. Unsupervised and supervised bioinformatics analyses were performed to correlate the imaging scores with the corresponding tumor microarray data (each microarray contained gene expression measurements across approximately 18,000 genes) to identify relationships between the imaging traits and underlying tumor gene expression. Enrichment for a predefined doxorubicin-response gene expression program was then performed against the imaging phenotype-associated genes and enrichment determined.An imaging phenotype related to tumor margins on arterial phase images demonstrated significant correlation with the doxorubicin-response transcriptional program (P < .05, q < 0.1). It was also significantly associated with HCC venous invasion and tumor stage (P < .05, q < 0.1). Tumors with higher tumor margin scores were more strongly associated with the doxorubicin resistance transcriptional program and had a greater prevalence of venous invasion and worse stage. Tumors with lower tumor margin scores, however, demonstrated a converse relationship.It is possible to identify HCC imaging phenotypes at CT that correlate with a doxorubicin drug response gene expression program. Given the role of doxorubicin in regional therapies for HCC management, it is possible that such an approach could be used to guide HCC therapy on a tumor-by-tumor basis on the basis of underlying tumor gene expression patterns.