Development of a survival prediction model for gastric cancer using serine proteases and their inhibitors

Abstract

Proteolytic enzymes play a key role in the metastatic stage of gastric cancer (GC). In this study, we aimed to identify the serine proteases (SPs) and their inhibitors (serpins) as related to GC. The gene expression profiles of 40 cases of GC were initially detected by cDNA microarray. The results of the differentially expressed SPs and their inhibitor genes from the microarrays were confirmed by real-time PCR. The status of the immunohistochemical staining of the confirmed genes in patients with complete data was used to develop a survival prediction model. Finally, the prediction model was tested in different groups of GC patients. As a result, seven genes, SERPINB5, KLK10, KLK11, HPN, SPINK1, SERPINA5 and PRSS8, were considered as GC progression-related genes. A survival prediction model including the immunohistochemical scores of three genes and the tumor node metastasis (TNM) score was developed: Survival time (months) = 88.8607 + 2.6395 SERPINB5 - 12.0772 KLK10 + 13.7562 KLK11 - 7.0318 TNM. In conclusion, SERPINB5, KLK10, KLK11, HPN, SPINK1, SERPINA5 and PRSS8 were GC progression-related SPs or serpin genes. The model consisting of the expression profiles of three genes extracted from the microarray study accompanied by the TNM score accurately predicts surgery-related survival of GC patients.

Figure 1.

Expression profiles of the three up-regulated genes in the microarray assay as determined by real-time PCR. (A) SERPINB5 was up-regulated with a 5.83-fold change in the GC specimens by microarray and demonstrated the same expression profile upon real-time PCR. (B) KLK10 was up-regulated with a 7.18-fold change in the GC specimens by microarray and demonstrated the same expression profile upon real-time PCR. (C) SERPINH1 showed a contradictory expression profile between the microarray and real-time PCR.

Figure 2.

Expression profiles of the down-regulated genes in the microarray assay as determined by real-time PCR. (A) KLK11, (B) HPN, (C) SPINK1, (D) SERPINA5 and (E) PRSS8 were all down-regulated in the GC specimens by real-time PCR and exhibited the same expression profiles as the microarray. (F) TMPRSS2 was excluded as the difference did not reach statistical significance (P=0.6250) by real-time PCR.

Figure 3.

Correlation of the RNA and protein expression profiles of SERPINB5, KLK10, KLK11 and HPN. The RNA expression profiles were positively correlated with the protein expression profiles, yet the correlations did not reach statistical significance: (A) r=0.1172, P=0.7472 for SERPINB5; (B) r=0.3433, P=0.3315 for KLK10; (C) r=0.5145, P=0.1281 for KLK11; (D) r=0.5092, P=0.1328 for HPN.

Figure 4.

The survival curves of the patients were assessed according to the IHC score. The survival rate of the entire test group of patients was divided according to the IHC scores of (A) SERPINB5 and (B) KLK10. Results showed that SERPINB5 and KLK10 were positively expressed in all patients and the patients with positive expression (IHC scores 7 and 8) exhibited a worse prognosis. The survival rate of the entire test group of patients was divided according to the IHC scores of (C) KLK11 and (D) HPN. KLK11 and HPN were negatively expressed in most of the patients, while the patients with negative expression of KLK11 and HPN demonstrated worse survival rates.