Qingchao Zhao1, Ke Chen2, Weiwei Tong3, Changqing Ge4, Dongqiang Zhao5. 1. Department of Endoscopy, No.2 Hospital of Baoding, Baoding, 071051, Hebei, China. 2. Department of Endoscopy, Fudan University Shanghai Cancer Center, 200032, Shanghai, China. 3. Bioinformatics Department, Peking Jabrehoo Med Tech Co., Ltd, 102629, Beijing, China. 4. No.2 Hospital of Baoding, Baoding, 071051, Hebei, China. 5. Department of Gastroenterology, The Second Hospital of HeBei Medical University, Shijiazhuang, 050000, Hebei, China. Electronic address: hbzdq1998@163.com.
Abstract
BACKGROUND: Anatomical subsites always harbor specific biological features in carcinogenesis. The divergent prognosis of proximal gastric cancer (PGC) and distal gastric cancer (DGC) has been reported. The current study aimed to comprehensively interpret anatomic subsite-specific genomic profiles, which may improve the effectiveness of personalized management. METHODS: Survival and genomic data from the online Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases were queried for prognostic and genetic analysis, respectively. Propensity score matching (PSM) analysis was performed to balance patient epidemiological factors. Differentially expressed genes (DEGs) were analyzed using the DESeq algorithm. Functional enrichment was performed by the clusterProfiler package. The protein-protein interaction network of DEGs was predicted by the online STRING database. RESULTS: A total of 3,955 patient pairs were assembled by PSM in SEER data with even background characteristics. Prognostic analysis indicated worse overall survival of PGC than DGC (17 vs 20 months, p = 0.0002). Genetic analysis of TCGA database identified 280 DEGs, 90 of which were upregulated in the DGC group and the remaining 190 were upregulated in the PGC group. Functional enrichment analysis indicated that kallikrein serine protease activity, ion channel (Na+/Cl-) activity, and cytoskeleton constituent might be attributed to the poor prognosis observed in PGC. Furthermore, alcohol, retinol, and lipoprotein metabolism were the features for DGC malignancy. CONCLUSION: The current study first demonstrated that PGC exerts poorer survival outcome than DGC based on the SEER database. Further bioinformatic investigation depicts the specific genetic features for PGC and DGC, which may generate differences in tumor malignancy. Our findings provide promising genetic targets for future specific and individualized gastric cancer therapy.
BACKGROUND: Anatomical subsites always harbor specific biological features in carcinogenesis. The divergent prognosis of proximal gastric cancer (PGC) and distal gastric cancer (DGC) has been reported. The current study aimed to comprehensively interpret anatomic subsite-specific genomic profiles, which may improve the effectiveness of personalized management. METHODS: Survival and genomic data from the online Surveillance, Epidemiology, and End Results (SEER) and The Cancer Genome Atlas (TCGA) databases were queried for prognostic and genetic analysis, respectively. Propensity score matching (PSM) analysis was performed to balance patient epidemiological factors. Differentially expressed genes (DEGs) were analyzed using the DESeq algorithm. Functional enrichment was performed by the clusterProfiler package. The protein-protein interaction network of DEGs was predicted by the online STRING database. RESULTS: A total of 3,955 patient pairs were assembled by PSM in SEER data with even background characteristics. Prognostic analysis indicated worse overall survival of PGC than DGC (17 vs 20 months, p = 0.0002). Genetic analysis of TCGA database identified 280 DEGs, 90 of which were upregulated in the DGC group and the remaining 190 were upregulated in the PGC group. Functional enrichment analysis indicated that kallikrein serine protease activity, ion channel (Na+/Cl-) activity, and cytoskeleton constituent might be attributed to the poor prognosis observed in PGC. Furthermore, alcohol, retinol, and lipoprotein metabolism were the features for DGC malignancy. CONCLUSION: The current study first demonstrated that PGC exerts poorer survival outcome than DGC based on the SEER database. Further bioinformatic investigation depicts the specific genetic features for PGC and DGC, which may generate differences in tumor malignancy. Our findings provide promising genetic targets for future specific and individualized gastric cancer therapy.