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Background  SLIT-ROBO families of proteins mediate axon pathfinding and their expression is not solely confined to nervous system. Aberrant expression of  SLIT-ROBO  genes was repeatedly shown in a wide variety of cancers, yet data about their collective behavior in hepatocellular carcinoma (HCC) is missing. Hence, we quantified  SLIT-ROBO  transcripts in HCC cell lines, and in normal and tumor tissues from liver.    Methods  Expression of  SLIT-ROBO  family members was quantified by real-time qRT-PCR in 14 HCC cell lines, 8 normal and 35 tumor tissues from the liver. ANOVA and Pearson's correlation analyses were performed in R environment, and different clinicopathological subgroups were pairwise compared in Minitab. Gene expression matrices of cell lines and tissues were analyzed by Mantel's association test.    Results  Genewise hierarchical clustering revealed two subgroups with coordinate expression pattern in both the HCC cell lines and tissues:  ROBO1 ,  ROBO2 ,  SLIT1  in one cluster, and  ROBO4 ,  SLIT2 ,  SLIT3  in the other, respectively. Moreover,  SLIT-ROBO  expression predicted  AFP -dependent subgrouping of HCC cell lines, but not that of liver tissues.  ROBO1  and  ROBO2  were significantly up-regulated, whereas  SLIT3  was significantly down-regulated in cell lines with high- AFP  background. When compared to normal liver tissue,  ROBO1  was found to be significantly overexpressed, while  ROBO4  was down-regulated in HCC. We also observed that  ROBO1  and  SLIT2  differentiated histopathological subgroups of liver tissues depending on both tumor staging and differentiation status. However,  ROBO4  could discriminate poorly differentiated HCC from other subgroups.    Conclusion  The present study is the first in comprehensive and quantitative evaluation of  SLIT-ROBO  family gene expression in HCC, and suggests that the expression of  SLIT-ROBO  genes is regulated in hepatocarcinogenesis. Our results implicate that  SLIT-ROBO  transcription profile is bi-modular in nature, and that each module shows intrinsic variability. We also provide quantitative evidence for potential use of  ROBO1 ,  ROBO4  and  SLIT2  for prediction of tumor stage and differentiation status.

Quantification of SLIT-ROBO transcripts in hepatocellular carcinoma reveals two groups of genes with coordinate expression