Mo1557 DNA Methylation in Gastric Mucosae is Associated With the Severity of Mucosal Inflammation Involving the Risk of Diffuse-Type Gastric Cancer

Epithelial-mesenchymal transition (EMT) plays an important role in the acquisition of cancer stem cell (CSC) feature and drug resistance, which are the main hallmarks of cancer malignancy. Although previous findings have shown that several signaling pathways are activated in cancer progression, the precise mechanism of signaling pathways in EMT and CSCs are not fully understood. In this study, we focused on the intestinal and diffuse-type gastric cancer (GC) and analyzed the gene expression of public RNAseq data to understand the molecular pathway regulation in different subtypes of gastric cancer. Network pathway analysis was performed by Ingenuity Pathway Analysis (IPA). A total of 2815 probe set IDs were significantly different between intestinal- and diffuse-type GC data in cBioPortal Cancer Genomics. Our analysis uncovered 10 genes including male-specific lethal 3 homolog (Drosophila) pseudogene 1 (MSL3P1), CDC28 protein kinase regulatory subunit 1B (CKS1B), DEAD-box helicase 27 (DDX27), golgi to ER traffic protein 4 (GET4), chromosome segregation 1 like (CSE1L), translocase of outer mitochondrial membrane 34 (TOMM34), YTH N6-methyladenosine RNA binding protein 1 (YTHDF1), ribonucleic acid export 1 (RAE1), par-6 family cell polarity regulator beta (PARD6B), and MRG domain binding protein (MRGBP), which have differences in gene expression between intestinal- and diffuse-type GC. A total of 463 direct relationships with three molecules (MYC, NTRK1, UBE2M) were found in the biomarker-filtered network generated by network pathway analysis. The networks and features in intestinal- and diffuse-type GC have been investigated and profiled in bioinformatics. Our results revealed the signaling pathway networks in intestinal- and diffuse-type GC, bringing new light for the elucidation of drug resistance mechanisms in CSCs.

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PO-309 Identification of genomic aberrations associated with lymph node metastasis in diffuse-type gastric cancer

10.1136/esmoopen-2018-eacr25.339 ◽

2018 ◽

Author(s):

D Lee

Keyword(s):

Gastric Cancer ◽

Lymph Node ◽

Lymph Node Metastasis ◽

Diffuse Type ◽

Node Metastasis ◽

Genomic Aberrations ◽

Diffuse Type Gastric Cancer

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Identification of a molecular signature of prognostic subtypes in diffuse-type gastric cancer

Gastric Cancer ◽

10.1007/s10120-019-01029-4 ◽

2019 ◽

Vol 23 (3) ◽

pp. 473-482 ◽

Cited By ~ 4

Author(s):

Seon-Kyu Kim ◽

Hee-Jin Kim ◽

Jong-Lyul Park ◽

Haejeong Heo ◽

Seon-Young Kim ◽

...

Keyword(s):

Gastric Cancer ◽

Tissue Microarray ◽

Microarray Analysis ◽

Cox Regression ◽

Molecular Signature ◽

Diffuse Type ◽

Rna Seq ◽

Tissue Samples ◽

Diffuse Type Gastric Cancer ◽

Tissue Microarray Analysis

Abstract Background Although recent advances in high-throughput technology have provided many insights into gastric cancer (GC), few reliable biomarkers for diffuse-type GC have been identified. Here, we aim to identify a prognostic and predictive signature of diffuse-type GC heterogeneity. Methods We analyzed RNA-seq-based transcriptome data to identify a molecular signature in 150 gastric tissue samples including 107 diffuse-type GCs. The predictive value of the signature was verified using other diffuse-type GC samples in three independent cohorts (n = 466). Log-rank and Cox regression analyses were used to estimate the association between the signature and prognosis. The signature was also characterized by somatic variant analyses and tissue microarray analysis between diffuse-type GC subtypes. Results Transcriptomic profiling of RNA-seq data identified a signature which revealed distinct subtypes of diffuse-type GC: the intestinal-like (INT) and core diffuse-type (COD) subtypes. The signature showed high predictability and independent clinical utility in diffuse-type GC prognosis in other patient cohorts (HR 2.058, 95% CI 1.53–2.77, P = 1.76 × 10–6). Integrative mutational and gene expression analyses demonstrated that the COD subtype was responsive to chemotherapy, whereas the INT subtype was responsive to immunotherapy with an immune checkpoint inhibitor (ICI). Tissue microarray analysis showed the practical utility of IGF1 and NXPE2 for predicting diffuse-type GC heterogeneity. Conclusions We present a molecular signature that can identify diffuse-type GC patients who display different clinical behaviors as well as responses to chemotherapy or ICI treatment.

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