Radiogenomic Analysis to Identify Imaging Phenotypes Associated with Drug Response Gene Expression Programs in Hepatocellular Carcinoma Michael D. Kuo, MD, Jeremy Gollub, PhD, Claude B. Sirlin, MD, Clara Ooi, MD, and Xin Chen, PhD PURPOSE: 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. MATERIALS AND METHODS: 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 18,000 genes) to identify relationships between the imaging traits and underlying tumor gene expression. Enrich- ment for a predefined doxorubicin-response gene expression program was then performed against the imaging phenotype–associated genes and enrichment determined. RESULTS: 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. CONCLUSIONS: 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. J Vasc Interv Radiol 2007; 18:821– 831 Abbreviations: cDNA = complementary DNA, FDR = false discovery rate, HCC = hepatocellular carcinoma, SAM = significance analysis of microarrays MICROARRAY analysis of gene ex- pression is a powerful tool that en- ables one to survey, in parallel, the expression of thousands of genes at once (1–4). As a result of the ability to identify differential changes in the ex- pression level of many genes simulta- neously, thematic expression patterns can emerge that are indicative of un- derlying biologic processes and can provide insights into the transcrip- tional state of a cell. Because cancer is fundamentally a disease of genetic in- stability, functional genomics ap- proaches have naturally lent them- selves to the study of cancer, where they have been used to delineate ge- netic programs and molecular markers associated with tumor biology and pa- tient prognosis for a large variety of human cancers on a tumor-by-tumor basis (5–9). Researchers have also be- gun to use this technology to identify gene expression programs associated with therapeutic outcome (10 –12). Hepatocellular carcinoma (HCC) is the fifth most common cause of cancer deaths (13). It is a molecularly hetero- geneous disease with an unpredictable natural history and treatment response profile. Although local-regional thera- pies such as transarterial chemoemboli- zation have demonstrated substantial survival benefits in patients with unre- sectable disease, treatment response is not uniform, with some patients clearly responding better than others to the same therapy (14,15). It is likely that From the Department of Radiology, University of Cal- ifornia-San Diego Medical Center, San Diego, CA 92103 (M.D.K., C.B.S.); Department of Biochemistry, Stanford University, Stanford, Calif (J.G.); Department of Radiology, University of Hong Kong, Shatin, Hong Kong (C.O.); and Department of Pharmacy Biophar- maceutical Sciences, University of California-San Fran- cisco, San Francisco, Calif (X.C.). Received January 6, 2006; final revision received and accepted April 23, 2007. From the 2006 SIR Annual Meeting. Address correspondence to M.D.K.; E-mail: mkuo@ucsd.edu. None of the authors has identified a conflict of in- terest. © SIR, 2007 DOI: 10.1016/j.jvir.2007.04.031 Young Investigator Award 821