Decoding global gene expression programs in liver cancer by noninvasive imaging.
Paralleling the diversity of genetic and protein activities, pathologic human tissues also exhibit diverse radiographic features. Here we show that dynamic imaging traits in non-invasive computed tomography (CT) systematically correlate with the global gene expression programs of primary human liver cancer. Combinations of twenty-eight imaging traits can reconstruct 78% of the global gene expression profiles, revealing cell proliferation, liver synthetic function, and patient prognosis. Thus, genomic activity of human liver cancers can be decoded by noninvasive imaging, thereby enabling noninvasive, serial and frequent molecular profiling for personalized medicine.
Segal
Eran
E
Dept. of Computer Science and Applied Mathematics, Weizmann Institute of Science, Rehovot 76100, Israel.
Sirlin
Claude B
CB
Ooi
Clara
C
Adler
Adam S
AS
Gollub
Jeremy
J
Chen
Xin
X
Chan
Bryan K
BK
Matcuk
George R
GR
Barry
Christopher T
CT
Chang
Howard Y
HY
Kuo
Michael D
MD
D014408:Biomarkers, Tumor / Q000378:metabolism*; D006528:Carcinoma, Hepatocellular / Q000378:metabolism*; D020869:Gene Expression Profiling / Q000379:methods*; D006801:Humans; D008099:Liver / Q000378:metabolism; D008113:Liver Neoplasms / Q000000981:diagnostic imaging / Q000378:metabolism*; D009363:Neoplasm Proteins / Q000378:metabolism*; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D014057:Tomography, X-Ray Computed / Q000379:methods*
D014408:Biomarkers, Tumor; D009363:Neoplasm Proteins