Background: As one of the most frequent chemical modifications in eukaryotic mRNAs, N6-methyladenosine (m6A) modification exerts important effects on mRNA stability, splicing, and translation. Recently, the regulatory role of m6A in tumorigenesis has been increasingly recognized. However, dysregulation of m6A and its functions in tumor epithelial-mesenchymal transition (EMT) and metastasis remain obscure. Methods: qRT-PCR and immunohistochemistry were used to evaluate the expression of methyltransferase-like 3 (METTL3) in gastric cancer (GC). The effects of METTL3 on GC metastasis were investigated through in vitro and in vivo assays. The mechanism of METTL3 action was explored through transcriptome-sequencing, m6A-sequencing, m6A methylated RNA immunoprecipitation quantitative reverse transcription polymerase chain reaction (MeRIP qRT-PCR), confocal immunofluorescent assay, luciferase reporter assay, co-immunoprecipitation, RNA immunoprecipitation and chromatin immunoprecipitation assay. Results: Here, we show that METTL3, a major RNA N6-adenosine methyltransferase, was upregulated in GC. Clinically, elevated METTL3 level was predictive of poor prognosis. Functionally, we found that METTL3 was required for the EMT process in vitro and for metastasis in vivo. Mechanistically, we unveiled the METTL3-mediated m6A modification profile in GC cells for the first time and identified zinc finger MYM-type containing 1 (ZMYM1) as a bona fide m6A target of METTL3. The m6A modification of ZMYM1 mRNA by METTL3 enhanced its stability relying on the “reader” protein HuR (also known as ELAVL1) dependent pathway. In addition, ZMYM1 bound to and mediated the repression of E-cadherin promoter by recruiting the CtBP/LSD1/CoREST complex, thus facilitating the EMT program and metastasis. Conclusions: Collectively, our findings indicate the critical role of m6A modification in GC and uncover METTL3/ZMYM1/E-cadherin signaling as a potential therapeutic target in anti-metastatic strategy against GC.

Background: UCA1 is a long non-coding RNA which was found overexpressed in various human cancers including gastric cancer (GC). It is identified that UCA1 promotes GC cells proliferation, migration and invasion, however, the role of UCA1 during the processes of immune escape is still not unclear. Methods: We collected 40 paired GC and non-tumor tissue samples. The level of UCA1 in GC and control tissue samples were determined by in situ hybridization and qRT-PCR. Cell viability was determined by MTT assay. GC cells’ migration capacities were examined by transwell assay. To understand the roles of UCA1 during immune escape, wildtype or UCA1 KO GC cells co-cultured with peripheral blood mononuclear cells or cytokine-induced killer cells in vitro. Mouse model was used to examine the function of UCA1 in vivo. Results: UCA1 promoted GC cells proliferation and migration, and inhibit apoptosis. UCA1 repressed miR-26a/b, miR-193a and miR-214 expression through direct interaction and then up-regulated the expression of PDL1. UCA1-KO GC cells could induce a higher IFNγ expression when co-cultured with peripheral blood mononuclear cells (PBMCs), and have a lower survival rate when co-cultured with cytokine-induced killer (CIK) cells in vitro. UCA1-KO GC cells formed smaller tumors, had higher miR-26a, −26b, −193a and − 214 level, reduced cell proliferation and increased apoptosis in xenograft mouse model. Conclusions: UCA1 overexpression protected PDL1 expression from the repression of miRNAs and contributed to the GC cells immune escape. UCA1 could serve as a potential novel therapeutic target for GC treatment.

Gastric cancer is heterogeneous and aggressive, especially with liver metastasis. This study aims to develop two nomograms to predict the overall survival (OS) and cancer-specific survival (CSS) of gastric cancer with liver metastasis (GCLM) patients. From January 2000 to December 2018, a total of 1936 GCLM patients were selected from the Surveillance, Epidemiology, and End Results Program (SEER) database. They were further divided into a training cohort and a validation cohort, with the OS and CSS serving as the study's endpoints. The correlation analyses were used to determine the relationship between the variables. The univariate and multivariate Cox analyses were used to confirm the independent prognostic factors. To discriminate and calibrate the nomogram, calibration curves and the area under the time-dependent receiver operating characteristic curve (time-dependent AUC) were used. DCA curves were used to examine the accuracy and clinical benefits. The clinical utility of the nomogram and the AJCC Stage System was compared using net reclassification improvement (NRI) and integrated differentiation improvement (IDI) (IDI). Finally, the nomogram and the AJCC Stage System risk stratifications were compared. There was no collinearity among the variables that were screened. The results of multivariate Cox regression analysis showed that six variables (bone metastasis, lung metastasis, surgery, chemotherapy, grade, age) and five variables (lung metastasis, surgery, chemotherapy, grade, N stage) were identified to establish the nomogram for OS and CSS, respectively. The calibration curves, time-dependent AUC curves, and DCA revealed that both nomograms had pleasant predictive power. Furthermore, NRI and IDI confirmed that the nomogram outperformed the AJCC Stage System. Both nomograms had satisfactory accuracy and were validated to assist clinicians in evaluating the prognosis of GCLM patients.

Following publication of the original article [1], authors reported Pro. Gang Zhao has to be considered as another corresponding author, according to his important contribution.

Helicobacter pylori (HP) infection is the greatest risk factor for gastric cancer (GC). Increasing evidence has clarified that tumor immune microenvironment (TIME) is closely related to the prognosis and therapeutic efficacy of HP-positive (HP+) GC patients. In this study, we aimed to construct a novel immune-related signature for predicting the prognosis and immunotherapy efficacy of HP+ GC patients. A total of 153 HP+ GC from three different cohorts were included in this study. An Immune-Related prognostic Signature for HP+ GC patients (IRSHG) was established using Univariate Cox regression, the LASSO algorithm, and Multivariate Cox regression. Univariate and Multivariate analyses proved IRSHG was an independent prognostic predictor for HP+ GC patients, and an IRSHG-integrated nomogram was established to quantitatively assessthe prognostic risk. The low-IRSHG group exhibited higher copy number load and distinct mutation profiles compared with the high-IRSHG group. In addition, the difference of hallmark pathways and immune cells infiltration between the two groups was investigated. Notably, tumor immune dysfunction and exclusion (TIDE) analysis indicated that the low-IRSHG group had a higher sensitivity to anti-PD-1 immunotherapy, which was validated by an external pabolizumab treatment cohort. Moreover, 98 chemotherapeutic drugs and corresponding potential biomarkers were identified for two groups, and several drugs with potential ability to reverse IRSHG score were identified using CMap analysis. Collectively, IRSHG may serve as a promising biomarker for survival outcome as well as immunotherapy efficacy. Furthermore, it can also help to prioritize potential therapeutics for HP+ GC patients, providing new insight for the personalized treatment of HP-infected GC.

Background: Gastric cancer (GC) is one of the most aggressive malignant tumors worldwide. Ferroptosis is a kind of iron-dependent cell death, which is proved to be closely related to tumor progression. In this study, we aim at constructing a ferroptosis-related lncRNAs signature to predict the prognosis of GC and explore potential therapies. Methods: Ferroptosis-Related LncRNAs Signature for GC patients (FRLSG) was constructed through univariate Cox regression, the LASSO algorithm, and multivariate Cox regression. Kaplan–Meier analysis, receiver operating characteristic curves, and risk score plot were applied to verify the predictive power of FRLSG. Gene Set Enrichment Analysis (GSEA) and immune infiltration analyses were conducted to explore the potential clinical value of the FRLSG. In addition, drug sensitivity prediction was applied to identify chemotherapeutic drugs with potential therapeutic effect. Results: Five ferroptosis-related lncRNAs (AC004816.1, AC005532.1, LINC01357, AL355574.1 and AL049840.4) were identified to construct FRLSG, whose expression level in GC were confirmed by experimental validation. Kaplan-Meier curve and ROC curve proved the reliability and effectiveness of the FRLSG in predicting the prognosis for GC patients. Several immune-related pathways were enriched in the high-FRLSG group, and further immune infiltration analyses demonstrated the high immune infiltration status of the high-FRLSG group. In addition, 19 and 24 candidate drugs with potential therapeutic effect were identified for the high- and low-FRLSG groups, respectively. Conclusions: FRLSG was an effective tool in predicting the prognosis of GC, which might help to prioritize potential therapeutics for GC patients.