Gastric cancer in proximal site exerts poorer survival outcome with divergent genetic features than distal site. (October 2020)
- Record Type:
- Journal Article
- Title:
- Gastric cancer in proximal site exerts poorer survival outcome with divergent genetic features than distal site. (October 2020)
- Main Title:
- Gastric cancer in proximal site exerts poorer survival outcome with divergent genetic features than distal site
- Authors:
- Zhao, Qingchao
Chen, Ke
Tong, Weiwei
Ge, Changqing
Zhao, Dongqiang - Abstract:
- Graphical abstract: Highlights: PGC exerts poorer survival outcome than DGC based on the SEER database. Specific genetic features for PGC and DGC was depicted. Serine protease and ion channel activity conttribute to PGC poor prognosis. Alcohol, retinol, and lipoprotein metabolism are the features for DGC malignancy. 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 identifiedGraphical abstract: Highlights: PGC exerts poorer survival outcome than DGC based on the SEER database. Specific genetic features for PGC and DGC was depicted. Serine protease and ion channel activity conttribute to PGC poor prognosis. Alcohol, retinol, and lipoprotein metabolism are the features for DGC malignancy. 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. … (more)
- Is Part Of:
- Computational biology and chemistry. Volume 88(2020)
- Journal:
- Computational biology and chemistry
- Issue:
- Volume 88(2020)
- Issue Display:
- Volume 88, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 88
- Issue:
- 2020
- Issue Sort Value:
- 2020-0088-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-10
- Subjects:
- Stomach -- Carcinoma -- Location -- TCGA -- Prognosis
Chemistry -- Data processing -- Periodicals
Biology -- Data processing -- Periodicals
Biochemistry -- Data processing
Biology -- Data processing
Molecular biology -- Data processing
Periodicals
Electronic journals
542.85 - Journal URLs:
- http://www.sciencedirect.com/science/journal/14769271 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compbiolchem.2020.107360 ↗
- Languages:
- English
- ISSNs:
- 1476-9271
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3390.576700
British Library DSC - BLDSS-3PM
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- 15501.xml