Rabbit Anti-Human RACGAP1 (Phospho-Ser387) polyclonal antibody

High proliferation rates are characteristic of cancer, and proliferation markers make up the majority of genes included in RNA-based prognostic gene signatures applied for breast cancer patients. Based on prior data on differences in molecular subgroups of breast cancer, we hypothesized that the significance of single proliferation markers might differ in luminal, Her2-positive and triple-negative subtypes. Therefore, we compared mRNA expression data of Ki67, TOP2A, and RacGAP1 using a pool of 562 Affymetrix U133A microarrays from breast cancer samples. "Luminal," "triple-negative," and "Her2-positive" subcohorts were defined by ESR1 and ERBB2 mRNA expression using pre-defined cut-offs. The analysis of the three potential proliferation markers revealed subtype-specific differences: in luminal carcinomas, expression of all three markers was a significant indictor of early recurrence in univariate and multivariate analysis, but RacGAP1 was superior to Ki67 and TOP2A in significance. In triple-negative tumors, only Ki67 was a significant and independent marker, whereas none of the markers showed a significant prognostic impact in Her2-positive cases. Within the group of luminal carcinomas, the proliferation markers had different impact depending on the treatment of patients: in untreated patients, Ki67, TOP2A, and RacGAP1 were significant and independent prognostic markers. In chemotherapy-treated patients, overexpression of all three markers was predictive for early recurrence, but only RacGAP1 retained significance in multivariate analysis. In contrast, RacGAP1 was the only predictive proliferation marker in the endocrine treatment group. These data point to subtype-specific differences in the relevance of proliferation-associated genes, and RacGAP1 might be a strong prognostic and predictive marker in the luminal subgroup.

The molecular mechanism of the pathological progression from cirrhosis to hepatocellular carcinoma (HCC) remains elusive. In the present study, tissue samples from normal liver, cirrhosis and HCC were subjected to differentially gene expression analysis, weighted gene correlation network analysis to identify the twenty hub genes (TOP2A, CDC20, PTTG1, CDCA5, CCNB2, PRC1, KIF20A, SF3B4, HSP90AB1, FOXD2, PLOD3, CCT3, SETDB1, VPS45, SPDL1, RACGAP1, MED24, KIAA0101, ZNF282, and USP21) in the pathological progression from cirrhosis to HCC. Each sample was calculated a hub gene set variation analysis (HGSVA) score using Gene Set Variation Analysis, The HGSVA score significantly increased with progression from cirrhosis to HCC, and this result was validated in two independent data sets. Moreover, this score may be used as a blood-based marker for HCC and is an independent prognostic factor of recurrence-free survival (RFS) and overall survival (OS). High expression of the hub genes may be driven by hypomethylation. The twenty gene-based gene set variation score may reflect the pathological progression from cirrhosis to HCC and is an independent prognostic factor for both OS and RFS.