Identification of ARL4C as a Peritoneal Dissemination-Associated Gene and Its Clinical Significance in Gastric Cancer
In gastric cancer (GC), peritoneal dissemination (PD) occurs frequently and is incurable. In this study, we aimed to identify PD-associated genes in GC.
We identified a PD-associated gene using three GC datasets: highly disseminated peritoneal GC cell lines, the Singapore dataset and The Cancer Genome Atlas (TCGA) dataset. We assessed the clinicopathological significance of the gene expression using reverse transcription-quantitative polymerase chain reaction (RT-qPCR) and performed immunohistochemical analysis for the gene in our patient cohort. We also performed survival analyses of the gene in our patient cohort, the Singapore dataset and the GSE62254 datasets. Moreover, gene set enrichment analysis (GSEA) was performed using the Singapore and TCGA datasets. Finally, in vitro experiments such as invasion/migration assays, immunofluorescence staining of actin filaments, epidermal growth factor (EGF) treatment analysis, and gene expression analysis were conducted using three gene-knockdown GC cell lines (AGS, 58As9, MKN45).
ADP-ribosylation factor-like 4c (ARL4C) was identified as a PD-associated gene, and immunohistochemical analysis showed that ARL4C was overexpressed in GC cells. High ARL4C expression was associated with the depth of invasion (p < 0.01) and PD (p < 0.05) and was a poor prognostic factor (p < 0.05) in our patient cohort, the Singapore dataset and the GSE62254 dataset. ARL4C expression positively correlated with the epithelial–mesenchymal transition (EMT) gene set in GSEA. Moreover, ARL4C knockdown reduced invasion/migration capacity, SLUG expression, and the formation of lamellipodia or filopodia in AGS and 58As9 cells. Finally, EGF treatment increased ARL4C expression in MKN45 cells.
ARL4C was associated with PD and was a poor prognostic factor in GC, possibly through promoting invasive capacity by activation of both EMT and motility.
The authors would like to thank K. Oda, K. Kasagi, S. Sakuma, M. Oshiumi, and M. Utou for their technical assistance, Dr. T. Sato for statistical analysis, and Dr. Tyler Lahusen for English proofreading.
This work was supported in part by the following Grants and foundation: Japan Society for the Promotion of Science Grant-in-Aid for Scientific Research (Grant Nos.: 16K07177, 16K10543, 16K10397, 16K19197, 16K19107, 16H01576, 26461980, 26293303).
Qingjiang Hu, Takaaki Masuda, Kuniaki Sato, Taro Tobo, Sho Nambara, Shinya Kidogami, Naoki Hayashi, Yosuke Kuroda, Shuhei Ito, Hidetoshi Eguchi, Hiroshi Saeki, Eiji Oki, Yoshihiko Maehara, and Koshi Mimori have no potential conflicts of interest to declare.
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