[Identification of biomarkers for early detection in gastric cancer and its clinical biological significance.].

OBJECTIVE: To systematically understand the cellular and molecular mechanism of gastric cancer (GC) development and to discover early diagnosis and predictive biomarkers, which will be used for early diagnosis and novel treatment targets. METHODS: 70 mer 22 K-oligonucleotide microarrays and bioinformatic analysis were conducted to recognize gene expression profiles in GC and normal appearing tissue (NAT). The control group was collected from non-tumor patients including 20 specimen mixture as a common reference (CR) and 5 individuals as additional control. Our results showed that 837 different expression genes (DEGs) were identified in GC while 570 DEGs were in NATs by Bayesian analysis (P<0.001, Fold change>2.0) as compared respectively with CR. An interesting finding is that we identified 67 over-expressed genes in both GC and NAT tissues, and these gene expression alterations could not be detected by comparison of GC with NATs, which were normally used in routine experiment design. Most of these genes were involved in the control of cell proliferation, metabolism and differentiation. RESULTS: These differential expressed genes were confirmed at mRNA and protein levels in primary tumors using RT-PCR and immunohistochemistry (IHC). The results showed that three genes, EGR1, CYR61 and ADAMTS1 were over expressed in both GC and NATs at mRNA level. These results were consistent with oligo microarray data. Another interesting finding is that these three genes were also over-expressed in intestinal metaplasia (IM) and dysplasia (DYS), which indicated that these three genes might be potential biomakers for early detection of GC. CONCLUSION: Through the systematic analysis of gene expression profiles in GC tissues, NAT and CR normal tissues, we identified a group of genes over-expressed both in GC and precancerous lesions, which might be potential biomarkers for early GC diagnosis.

[Relations of transforming growth factor-beta1 expression to differentiation and prognosis of advanced gastric cancer].

OBJECTIVE: To clarify the correlation of transforming growth factor-beta1 (TGF-beta1) expression with the differentiation and prognosis of advanced gastric cancer (GC). METHODS: Whole genome expression chip hybridization, was used to detect the expression of TGF-beta1 and TGF-betaR1 in 20 specimens of intestinal-type GC and para-cancer tissues. RT-PCR and immunohistochemistry (IHC) analysis were used to detect the mRNA and protein expression of TGF-beta1 and TGF-betaR1 in 30 specimens of intestinal-type GC tissue and para-cancer tissues. The mixture of gastric mucosa tissues from 20 non-tumor patients was used as common reference. RESULTS: The expression level of TGF-beta1 and TGF-betaR-1 genes was higher in the GC tissues than in the para-cancer tissues. However, the expression of Smad gene family was not significantly different between the GC tissues and para-tumor normal tissues. TGF-beta1 gene expression and TGF-betaR1 gene expression were higher in the GC tissues. RT-PCR showed that both TGF-beta1 and TGF-betaR-1 genes were highly expressed in the mRNA level in 21 of the 30 CC patients IHC showed that TGF-beta1 protein was expressed mainly in the cytoplasm. 32 of the 90 specimens of GC tissue were highly positive in TGF-beta1 protein (64%), in comparison with the positive rate of 5% (1/20) in the para-cancer normal tissues. The TGF-beta1 protein expression rate of the highly and moderately differentiated GC tissues was 59% (59%, 23/39), significantly higher than that of the lowly differentiated GC tissues (18%, 9/51, P < 0.01). IHC showed that the TGF-beta R-I rate was 57% (42/74) in the well differentiated specimens, particularly 68% (26/38) in the highly differentiated specimens, and was 44% in the poorly differentiated GC (6/20, P < 0.05). Log rank test showed that the prognosis of the patients positive in TGF-beta1 was significantly better than those negative in TGF-beta1 (P = 0.0058). However, the survival rate did not differ significantly according to TGF-beta R-I expression (P = 0.8453). CONCLUSION: TGF-beta1 expression is significantly correlated with the differentiation degree of GC. Moreover, positive expression of TGF-beta1 is a favorable prognostic factor in advanced GC. Expression of TGF-beta1 may be an important preoperative prognostic variable for advanced GC.