Background: Circular RNAs (circRNAs) have recently emerged as a new family of noncoding RNAs that are involved in the causation and progression of various cancers. However, the roles of circRNAs in the tumorigenesis of gastric cancer (GC) are still largely unknown. Methods: The expression profiles of circRNAs in GC were identified in open GEO database and were evaluated at the mRNA level in clinical GC samples compared with paired non-tumorous tissues. Kaplan-Meier survival curve was used to analyze the correlation of circRNA and patients’ prognosis. Subsequently, the circular structures of candidate circRNAs were validated by Sanger sequencing, divergent primer PCR, and RNase R treatments. Gain- and loss-of-function analyses were performed to evaluate the functional significance of it in GC initiation and progression. Dual-luciferase reporter and RNA pull-down assays were used to identify the microRNA (miRNA) sponge mechanism of circRNAs. Results: The expression of circRHOBTB3 was lower in GC tissues and cell lines. Downregulation of circRHOBTB3 was significantly correlated with poor differentiation and unfavorable prognosis in patients with GC. Overexpression of circRHOBTB3 in GC cells led to decreased proliferation and induced G₁/S arrest in vitro, accompanied with inhibited xenograft tumor growth in vivo, while the opposite effects were achieved in circRHOBTB3-silenced cells. Furthermore, we demonstrated that circRHOBTB3 acts as a sponge for miR-654-3p and verified that p21 is a novel target of miR-654-3p. Conclusion: Taken together, this study revealed that circRHOBTB3 might function as competing endogenous RNA (ceRNA) for miR-654-3p, which could contribute to growth inhibition of GC through activating p21 signaling pathway. Our data suggested that circRHOBTB3 would serve as a novel promising diagnosis marker and therapeutic target for GC.

To develop and validate a radiomics signature for the prediction of gastric cancer (GC) survival and chemotherapeutic benefits. In this multicenter retrospective analysis, we analyzed the radiomics features of portal venous-phase computed tomography in 1591 consecutive patients. A radiomics signature was generated by using the Lasso-Cox regression model in 228 patients and validated in internal and external validation cohorts. Radiomics nomograms integrating the radiomics signature were constructed, demonstrating the incremental value of the radiomics signature to the traditional staging system for individualized survival estimation. The performance of the nomograms was assessed with respect to calibration, discrimination, and clinical usefulness. The radiomics signature consisted of 19 selected features and was significantly associated with DFS (disease-free survival) and OS (overall survival). Multivariate analysis demonstrated that the radiomics signature was an independent prognostic factor. Incorporating the radiomics signature into the radiomics-based nomograms resulted in better performance for the estimation of DFS and OS than the clinicopathological nomograms and TNM staging system, with improved accuracy of the classification of survival outcomes. Further analysis showed that stage II and III patients with higher radiomics scores exhibited a favorable response to chemotherapy. In conclusion, the newly developed radiomics signature is a powerful predictor of DFS and OS, and it may predict which patients with stage II and III GC benefit from chemotherapy.

Molecular biomarkers that predict disease progression might promote drug development and therapeutic strategies in aggressive cancers, such as gastric cancer (GC). High-throughput mRNA sequencing (RNA-seq) revealed that collagen type X alpha 1 (COL10A1) is a disease progression-associated gene. Analysis of 103 GC patients showed that high COL10A1 mRNA expression was associated with GC metastasis and reduced survival. We analyzed the COL10A1 promoter using the UCSC genome website and JASPAR database, and we found potential SOX9 binding site. Here, we demonstrated that SOX9 and COL10A1 were both up-regulated in GC. We observed a positive correlation between the expression patterns of SOX9 and COL10A1 in GC cells and tissues. The results of electrophoretic mobility shift assay (EMSA), chromatin immunoprecipitation (ChIP) assay and promoter reporter indicated that SOX9 could directly bind to the COL10A1 gene promoter and activate its transcription. Biological function experiments showed that COL10A1 regulated the migration and invasion of GC cells. Knockdown COL10A1 inhibited lung and abdominal cavity metastasis in a nude mouse model. Moreover, transforming growth factor-β1 (TGF-β1) treatment up-regulated the phosphorylation of Smad2 and increased SOX9 and COL10A1 expression. COL10A1 was confirmed to be a potential inducer of epithelial-to-mesenchymal transition (EMT). SOX9 was essential for COL10A1-mediated EMT, and cell migration, invasion and metastasis. Co-expression of SOX9 and COL10A1 was associated with tumor progression and was strongly predictive of overall survival in GC patients. In summary, this study elucidated the mechanistic link between COL10A1 and the TGF-β1-SOX9 axis. These findings indicated that COL10A1 might play a crucial role in GC progression and serve as a potential biomarker and therapeutic target in GC patients.

We aimed to evaluate whether radiomic feature-based fluorine 18 (¹⁸F) fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging signatures allow prediction of gastric cancer (GC) survival and chemotherapy benefits.

The tumor microenvironment (TME) is modified by its cellular or acellular components throughout the whole period of tumor development. The dynamic modulation can reprogram tumor initiation, growth, invasion, metastasis, and response to therapies. Hence, the focus of cancer research and intervention has gradually shifted to TME components and their interactions. Accumulated evidence indicates neural and immune factors play a distinct role in modulating TME synergistically. Among the complicated interactions, neurotransmitters, the traditional neural regulators, mediate some crucial regulatory functions. Nevertheless, knowledge of the exact mechanisms is still scarce. Meanwhile, therapies targeting the TME remain unsatisfactory. It holds a great prospect to reveal the molecular mechanism by which the interplay between the nervous and immune systems regulate cancer progression for laying a vivid landscape of tumor development and improving clinical treatment.

BACKGROUND: The tumor immune microenvironment can provide prognostic and therapeutic information. We aimed to develop noninvasive imaging biomarkers from computed tomography (CT) for comprehensive evaluation of immune context and investigate their associations with prognosis and immunotherapy response in gastric cancer (GC). METHODS: This study involved 2,600 patients with GC from 9 independent cohorts. We developed and validated 2 CT imaging biomarkers (lymphoid radiomics score [LRS] and myeloid radiomics score [MRS]) for evaluating the IHC-derived lymphoid and myeloid immune context respectively, and integrated them into a combined imaging biomarker [LRS/MRS: low(−) or high(+)] with 4 radiomics immune subtypes: 1 (−/−), 2 (+/−), 3 (−/+), and 4 (+/+). We further evaluated the imaging biomarkers’ predictive values on prognosis and immunotherapy response. RESULTS: The developed imaging biomarkers (LRS and MRS) had a high accuracy in predicting lymphoid (AUC range: 0.765–0.773) and myeloid (AUC range: 0.736–0.750) immune context. Further, similar to the IHC-derived immune context, 2 imaging biomarkers (HR range: 0.240–0.761 for LRS; 1.301–4.012 for MRS) and the combined biomarker were independent predictors for disease-free and overall survival in the training and all validation cohorts (all P < 0.05). Additionally, patients with high LRS or low MRS may benefit more from immunotherapy ( P < 0.001). Further, a highly heterogeneous outcome on objective response rate was observed in 4 imaging subtypes: 1 (−/−) with 27.3%, 2 (+/−) with 53.3%, 3 (−/+) with 10.2%, and 4 (+/+) with 30.0% ( P < 0.0001). CONCLUSION: The noninvasive imaging biomarkers could accurately evaluate the immune context and provide information regarding prognosis and immunotherapy for GC.