P2038 - Identification of Three Upregulated Genes in Tumor Tissues With Poor Prognosis in Gastric Cancer via Bioinformatical Analysis

Monday, October 25, 2021

10:30 AM – 4:15 PM PT

Location: Shoreline Exhibit Hall

Has Audio

Presenting Author(s)

Chenyu Sun, MD, MSc

AMITA Health Saint Joseph Hospital
Chicago, IL, United States

Chenyu Sun, MD, MSc¹, Na Hyun Kim, MD¹, John Pocholo W. Tuason, MD¹, Ce Cheng, DO², Chandur Bhan, MD¹, Sudha Misra, MD¹, Zain I. Siddiqui, MD¹, Yasmin A. Gerais, MD¹, Mohammed R. Gandam, MD¹, Jannell F. Lising, MD¹
¹AMITA Health Saint Joseph Hospital, Chicago, IL; ²University of Arizona College of Medicine, Tucson, AZ

Introduction: The purpose of the present academic work was to identify genes with worse prognoses of gastric cancer (GC).

Methods: GSE54129 & GSE64951 were extracted from GEO database. Differentially expressed genes (DEGs) between GC and normal specimen were identified via GEO2R online tools with logFC > 1 and adjust P value < 0.05. Raw data were checked in Venn software online to detect the common DEGs. The DEGs with logFC > 1 were considered as up-regulated genes. Gene ontology (GO) analysis and KEGG pathway analysis were conducted and visualized via DAVID and Bioinformatics online tool. PPI network was evaluated by STRING and hub genes were selected via CytoHubba app in Cytoscape. Kaplan Meier-plotter was used to conduct survival analysis. GEPIA website was used to analyze the expression. The best discriminate cut-off points between the high and low expression groups were assessed with the Receiver operating characteristic (ROC) curve and area under the curve (AUC) for overexpressed DEGs by using R software with pROC and ggplot2 packages to analyze data from TCGA-STAD with Log2 transformed FPKM.

Results: There are 174 GC & 52 normal tissue samples in the two profile datasets, and 605 and 1,860 up-regulated DEGs from GSE64951 and GSE54129, respectively. Venn diagram detected 62 commonly up-regulated DEGs. GO analysis indicated that they were enriched in integrin-mediated signaling pathway, extracellular matrix organization, and collagen fibril organization for biological processes (BP), and enriched in integrin complex, integrin alpha1-beta1 complex, and endoplasmic reticulum lumen for GO cell component (CC), and enriched in cell adhesion molecule binding, collagen-binding involved in cell-matrix adhesion, and transcription corepressor activity for molecular function (MF). KEGG analysis found that they were enriched in Axon guidance, Cell adhesion molecules (CAMs), and Leishmaniasis. Analysis of PPI network complex found top 10 genes as shown in the PPI network figure. Kaplan Meier plotter identified 3core genes (COL5A1, COL12A1, ITGBL1) associated with a worse prognosis (P < 0.05), and GEPIA found a higher expression level of them in GC tissues than normal tissue. ROC curve showed that AUC of COL5A1, COL12A1, ITGBL1 were 0.813, 0.831, and 0.646, respectively, and their cutoff values were 4.494, 2.789, and 0.900.

Discussion: In GC, COL5A1, COL12A1, and ITGBL1 are associated with poor prognoses that could be potential therapeutic targets., COL5A1 and COL12A1 could be potential diagnostic markers.

Figure: 1) Authentication of 62 common up-regulated DEGs through Venn diagram; 2) Volcano plot 3) Common DEGs PPI network constructed by STRING online database, showing PPI network complex that included 60 nodes and 37 edges, with top 10 genes of COL5A1, ITGB1, ITGA1, ITGB2, PTPN11, LOX, NRXN2, COL12A1, ITGBL1, DDICER1; 4) Bubble plot of Gene Ontology (GO) analysis and KEGG pathway analysis; 5) Kaplan Meier plotter: COL5A1, COL12A1, ITGBL1, genes were associated with a significantly worse survival rate (P < 0.05); 6) COL5A1, COL12A1, and ITGBL1 genes had a significant expression level in GC cancer specimen (P < 0.05), red color means tumor tissues and grey color means normal tissues; 7) Receiver Operating Characteristic (ROC) curve showing Area under the Curve (AUC) values of COL5A1, COL12A1, and ITGBL1

DEG

Genes Name

Up-regulated

TAF9B ZEB1 HOXA13 PALM2-AKAP2///AKAP2 ULK4 BCHE PTRF GSTM4 SPTBN1 IGHV4-31///IGHM///IGHG3///IGHG1///IGHD///IGHA2///IGHA1 HLF FHL1 ITGB1 SMCHD1 FKBP5 FLI1 CLIC5 ITGB2 IGFBP5 AVL9 GALNT15 HNRNPH1 ITGBL1 CREB1 SLC16A4 SRGAP1 SLC25A36 TFPI LOX SKIL HSPB7 EPHB2 ERC1 COL12A1 NRXN2 RENBP METTL8 PTPN11 RBM33 DICER1 ITGA1 SERPINA1 HLA- QB1 UHMK1 HOXA10 SRGAP2RNF207 FGF7 GUCY1A2 ANKFY1 BAZ2A EPG5 AEBP1 PCDH9 NES NUMA1 COL5A1 ATG16L1 TAOK1 FTX CCDC88A DCAF8

Table: All 62 commonly differentially expressed genes (DEGs) were detected from two profile datasets, of which all are up-regulated genes in the GC tissues compared to normal tissues

Disclosures:

Chenyu Sun indicated no relevant financial relationships.

Na Hyun Kim indicated no relevant financial relationships.

John Pocholo Tuason indicated no relevant financial relationships.

Ce Cheng indicated no relevant financial relationships.

Chandur Bhan indicated no relevant financial relationships.

Sudha Misra indicated no relevant financial relationships.

Zain Siddiqui indicated no relevant financial relationships.

Yasmin Gerais indicated no relevant financial relationships.

Mohammed Gandam indicated no relevant financial relationships.

Jannell Lising indicated no relevant financial relationships.

Chenyu Sun, MD, MSc¹, Na Hyun Kim, MD¹, John Pocholo W. Tuason, MD¹, Ce Cheng, DO², Chandur Bhan, MD¹, Sudha Misra, MD¹, Zain I. Siddiqui, MD¹, Yasmin A. Gerais, MD¹, Mohammed R. Gandam, MD¹, Jannell F. Lising, MD¹. P2038 - Identification of Three Upregulated Genes in Tumor Tissues With Poor Prognosis in Gastric Cancer via Bioinformatical Analysis, ACG 2021 Annual Scientific Meeting Abstracts. Las Vegas, Nevada: American College of Gastroenterology.