BACKGROUND: Stomach adenocarcinoma (STAD) is one of the common gastrointestinal cancers, characterized by late discovery and metastasis. However, research of gene methylation and expression in gastric cancer (GC) metastasis has been quite limited. This study aimed to investigate the altered gene expression patterns between metastasis and non-metastasis samples using high-throughput RNA and methylation profiles from a large number of patients. Another aim was to identify a specific potential metastasis biomarker, with the ability to predict the metastasis possibility and prognosis of patients with STAD. METHODS: In this study, we integrated The Cancer Genome Atlas (TCGA) program STAD datasets, analyzed the RNA expression and DNA methylation data between non-metastasis (M0) and distant metastasis (M1) samples, and evaluated the candidate biomarker in survival and prognosis of GC. RESULTS: Among all patients enrolled, 329 with M0 and M1 information were positive for RNA analysis, and 353 with M0 and M1 information were positive for methylation analysis. We found 29 upregulated and 200 downregulated genes in RNA level, and 5,046 hypermethylated and 8,563 hypomethylated probes in methylation level. Among these genes, we found high RNA expression level and low DNA methylation level of ALOX12B and PACSIN1 in GC metastasis samples. Patients with high expression of these 2 genes had poor overall survival (OS), progression-free survival (PFS), and post-progression survival (PPS). CONCLUSIONS: The expression levels of ALOX12B and PACSIN1 were higher in the metastasis than non-metastasis group, and participants with high expression of these 2 genes were found to have poor survival. The genes ALOX12B and PACSIN1 are potential biomarkers of metastasis and poor prognosis, especially in early stage GC, and provide additional information for subsequent comprehensive treatment of GC. 2021 Journal of Gastrointestinal Oncology. All rights reserved.
BACKGROUND: Stomach adenocarcinoma (STAD) is one of the common gastrointestinal cancers, characterized by late discovery and metastasis. However, research of gene methylation and expression in gastric cancer (GC) metastasis has been quite limited. This study aimed to investigate the altered gene expression patterns between metastasis and non-metastasis samples using high-throughput RNA and methylation profiles from a large number of patients. Another aim was to identify a specific potential metastasis biomarker, with the ability to predict the metastasis possibility and prognosis of patients with STAD. METHODS: In this study, we integrated The Cancer Genome Atlas (TCGA) program STAD datasets, analyzed the RNA expression and DNA methylation data between non-metastasis (M0) and distant metastasis (M1) samples, and evaluated the candidate biomarker in survival and prognosis of GC. RESULTS: Among all patients enrolled, 329 with M0 and M1 information were positive for RNA analysis, and 353 with M0 and M1 information were positive for methylation analysis. We found 29 upregulated and 200 downregulated genes in RNA level, and 5,046 hypermethylated and 8,563 hypomethylated probes in methylation level. Among these genes, we found high RNA expression level and low DNA methylation level of ALOX12B and PACSIN1 in GC metastasis samples. Patients with high expression of these 2 genes had poor overall survival (OS), progression-free survival (PFS), and post-progression survival (PPS). CONCLUSIONS: The expression levels of ALOX12B and PACSIN1 were higher in the metastasis than non-metastasis group, and participants with high expression of these 2 genes were found to have poor survival. The genes ALOX12B and PACSIN1 are potential biomarkers of metastasis and poor prognosis, especially in early stage GC, and provide additional information for subsequent comprehensive treatment of GC. 2021 Journal of Gastrointestinal Oncology. All rights reserved.
Entities:
Keywords:
ALOX12B; Early biomarker; PACSIN1; gastric cancer (GC); metastasis
Authors: Akiko Doi; In-Hyun Park; Bo Wen; Peter Murakami; Martin J Aryee; Rafael Irizarry; Brian Herb; Christine Ladd-Acosta; Junsung Rho; Sabine Loewer; Justine Miller; Thorsten Schlaeger; George Q Daley; Andrew P Feinberg Journal: Nat Genet Date: 2009-11-01 Impact factor: 38.330
Authors: Christine Mehner; Ann L Oberg; Krista M Goergen; Kimberly R Kalli; Matthew J Maurer; Aziza Nassar; Ellen L Goode; Gary L Keeney; Aminah Jatoi; Derek C Radisky; Evette S Radisky Journal: Genes Cancer Date: 2017-05