4C; r = −0.367, P = 0.013). Our results indicate that up-regulation of SLC29A2 could potentially be an important predictive biomarker for vascular invasion and poor outcome for patients with HCC. To investigate the role of amplification of FNDC3B and SLC29A2 in HCC tumorigenesis, we overexpressed FNDC3B or SLC29A2 in unamplified

HCC cells (Huh6) and examined the potential activation of the downstream signaling pathway. Our results demonstrated that overexpressed FNDC3B and SLC29A2 increased cell proliferation (Supporting Information Fig. 5A) and were validated by up-regulation of Ki-67 protein expression (Supporting click here Information Fig. 5B). To further dissect the activation of downstream signaling pathways involved in augmenting cell proliferation, we examined the expression and activation of v-akt murine thymoma viral oncogene homolog 1 (AKT) and STAT3. Our results showed that activation of the

STAT3 pathway through increased Tyr705 phosphorylation was detected in FNDC3B- and SLC29A2-overexpressed Huh6 cells, but phosphorylation of Ser427 of AKT was not (Supporting Information Fig. 5C). The relatively activated STAT3 signaling pathway was also detected in FNDC3B- and SLC29A2-amplified Hep3B but not in unamplified Huh6 (Supporting Information Fig. 5D). Together, our results suggest that amplification of FNDC3B or SLC29A2 could lead to activation of the downstream STAT3 signaling pathway, confer selective MAPK Inhibitor Library manufacturer Forskolin growing advantages, and promote tumorigenesis of HCC. In this study, we developed a comprehensive approach to analyzing genome-wide CNAs of cancer genomes with high-density SNP arrays and to searching for cancer genes by identification of overlapped amplicons

and HDs in multiple cancer cell lines. First, we established the CNA analysis protocol and criteria without the need for precious genomic DNAs isolated from tumor-adjacent normal tissues. Our results suggest that a reference pool of high-density SNP arrays requires at least 10 reference samples from healthy individuals to minimize signal variations between the SNP arrays (Supporting Information Fig. 6). The number of reference samples required for CNA analysis was based on the minimal number of reference samples required to obtain the minimal variation of standard deviations of SNP intensities and to stabilize the number of aberrant SNPs from tested cancer genome arrays. Because our main purpose was searching for target genes in cancer genomes with the exclusion of false-positive signals, we established highly stringent criteria for defining amplicons (at least 10 continuous SNPs with an ICN ≥ 4) and HDs (at least 10 continuous SNPs with an ICN ≦ 0.4). The defined threshold for amplicons (ICN ≥ 4) was intended to avoid the inclusion of common trisomic regions, and the defined threshold for HDs (ICN ≦ 0.4) was aimed at the direct exclusion of loss-of-heterozygosity regions in cancer genomes.

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