Circular MTHFD2L RNA-encoded CM-248aa inhibits gastric cancer progression by targeting the SET-PP2A interaction.

The available targeted therapies for gastric cancer (GC) are still limited, so it is important to discover novel molecules as potential treatment options. Proteins or peptides encoded by circular RNAs (circRNAs) are increasingly reported to play essential roles in malignancies. The aim of the present study was to identify an undiscovered protein encoded by circRNA and explore its key role and molecular mechanism in GC progression. CircMTHFD2L (hsa_circ_0069982) was screened and validated as a downregulated circRNA with coding potential. The protein encoded by circMTHFD2L, named CM-248aa, was identified for the first time by immunoprecipitation and mass spectrometry. CM-248aa was significantly downregulated in GC, while its low expression was associated with advanced tumor-node-metastasis (TNM) stage and histopathological grade. Low expression of CM-248aa could be an independent risk factor for poor prognosis. Functionally, CM-248aa, instead of circMTHFD2L suppressed the proliferation and metastasis of GC in vitro and in vivo. Mechanistically, CM-248aa competitively targeted the acidic domain of SET nuclear oncogene (SET) and acted as an endogenous inhibitor of the SET-protein phosphatase 2A interaction to promote dephosphorylation of AKT, extracellular signal-regulated kinase, and P65. Our discovery revealed that CM-248aa could be a potential prognostic biomarker and endogenous therapeutic option for GC.

m6A modification-mediated lncRNA TP53TG1 inhibits gastric cancer progression by regulating CIP2A stability.

Long noncoding RNAs (lncRNAs) are associated with various types of cancer. However, the precise roles of many lncRNAs in tumor progression remain unclear. In this study, we found that the expression of the lncRNA TP53TG1 was downregulated in gastric cancer (GC) and it functioned as a tumor suppressor. In addition, low TP53TG1 expression was significantly associated with poor survival in patients with GC. TP53TG1 inhibited the proliferation, metastasis, and cell cycle progression of GC cells, while it promoted their apoptosis. m6A modification sites are highly abundant on TP53TG1, and demethylase ALKBH5 reduces TP53TG1 stability and downregulates its expression. TP53TG1 interacts with cancerous inhibitor of protein phosphatase 2A (CIP2A) and triggers its ubiquitination-mediated degradation, resulting in the inhibition of the PI3K/AKT pathway. These results suggest that TP53TG1 plays an important role in inhibiting the progression of GC and provides a crucial target for GC treatment.

Patient stratification based on urea cycle metabolism for exploration of combination immunotherapy in colon cancer.

BACKGROUND: Owing to the low ratio of patients benefitting from immunotherapy, patient stratification becomes necessary. An accurate patient stratification contributes to therapy for different tumor types. Therefore, this study aimed to subdivide colon cancer patients for improved combination immunotherapy. METHODS: We characterized the patients based on urea cycle metabolism, performed a consensus clustering analysis and constructed a risk model in the cancer genome atlas cohort. Colon cancer patients were further categorized into two tags: clusters, and risk groups, for the exploration of combination immunotherapy. In addition to external validation in the Gene Expression Omnibus datasets, several images of immunohistochemistry were used for further validation. RESULTS: Patient characterization based on urea cycle metabolism was related to immune infiltration. An analysis of consensus clustering and immune infiltration generated a cluster distribution and identified patients in cluster 1 with high immune infiltration levels as hot tumors for immunotherapy. A risk model of seven genes was constructed to subdivide the patients into low- and high-risk groups. Validation was performed using a cohort of 731 colon cancer patients. Patients in cluster 1 had a higher immunophenoscore (IPS) in immune checkpoint inhibitor therapy, and those other risk groups displayed varying sensitivities to potential combination immunotherapeutic agents. Finally, we subdivided the colon cancer patients into four groups to explore combination immunotherapy. Immunohistochemistry analysis showed that protein expression of two genes were upregulated while that of other two genes were downregulated or undetected in cancerous colon tissues. CONCLUSION: Using subdivision to combine chemotherapy with immunotherapy would not only change the dilemma of immunotherapy in not hot tumors, but also promote the proposition of more rational personalized therapy strategies in future.

Turning to immunosuppressive tumors: Deciphering the immunosenescence-related microenvironment and prognostic characteristics in pancreatic cancer, in which GLUT1 contributes to gemcitabine resistance.

Increasing evidence indicates that the remodeling of immune microenvironment heterogeneity influences pancreatic cancer development, as well as sensitivity to chemotherapy and immunotherapy. However, a gap remains in the exploration of the immunosenescence microenvironment in pancreatic cancer. In this study, we identified two immunosenescence-associated isoforms (IMSP1 and IMSP2), with consequential differences in prognosis and immune cell infiltration. We constructed the MLIRS score, a hazard score system with robust prognostic performance (area under the curve, AUC = 0.91), based on multiple machine learning algorithms (101 cross-validation methods). Patients in the high MLIRS score group had worse prognosis (P < 0.0001) and lower abundance of immune cell infiltration. Conversely, the low MLIRS score group showed better sensitivity to chemotherapy and immunotherapy. Additionally, our MLIRS system outperformed 68 other published signatures. We identified the immunosenescence microenvironmental windsock GLUT1 with certain co-expression properties with immunosenescence markers. We further demonstrated its positive modulation ability of proliferation, migration, and gemcitabine resistance in pancreatic cancer cells. To conclude, our study focused on training of composite machine learning algorithms in multiple datasets to develop a robust machine learning modeling system based on immunosenescence and to identify an immunosenescence-related microenvironment windsock, providing direction and guidance for clinical prediction and application.

PMN-MDSCs accumulation induced by CXCL1 promotes CD8+ T cells exhaustion in gastric cancer.

Myeloid-derived suppressor cells (MDSCs) accumulation in multiple tumor is associated with immune checkpoint inhibitors (ICIs) resistance. However, mechanisms of MDSCs in ICIs resistance of gastric cancer (GC) have not been thoroughly explored. In this study, we found that the PMN-MDSCs frequency rather than the M-MDSCs frequency was correlated with the survival of GC patients and CXCL1 induced PMN-MDSCs accumulation in GC. S100A8/A9 heterodimer, a hallmark of MDSCs, upregulated the CXCL1 expression in GC cells through the TLR4/p38 MAPK/NF-κB pathway. Notably, PMN-MDSCs exerted immunosuppressive effect through S100A8/A9. Mechanically, S100A8/A9 led to CD8+ T cells exhaustion including inhibiting CD8+ T cells glycolysis, proliferation and TNF-α and IFN-γ production, which was dependent on TLR4/AKT/mTOR pathway. In tumor-bearing mice, the CXCR2 antagonist SB225002 decreased PMN-MDSCs accumulation, increased CD8+ T cells infiltration in GC and further enhanced anti-tumor efficacy of anti-PD-1. Taken together, our study identified that CXCL1 induced PMN-MDSCs accumulation in GC, and unveiled how PMN-MDSCs promoted CD8+ T cells exhaustion, which may provide a potential therapeutic strategy for GC.

p53-Induced LINC00893 Regulates RBFOX2 Stability to Suppress Gastric Cancer Progression.

Long noncoding RNAs (lncRNAs) have been reported to regulate diverse tumorigenic processes. However, little is known about long intergenic non-protein coding RNA 00893 (LINC00893) and its role in gastric cancer (GC). Herein we investigated its biological functions and molecular mechanism in GC. LINC00893 was decreased in GC tissues but significantly elevated in AGS cells after treatment with Nutlin-3. In GC patients, it was found that low expression of LINC00893 was correlated with tumor growth, metastasis and poor survival. Functionally, overexpression of LINC00893 suppressed the proliferation, migration and invasion of GC cells. Mechanistically, LINC00893 regulated the expression of epithelial-mesenchymal transition (EMT)-related proteins by binding to RNA binding fox-1 homolog 2 (RBFOX2) and promoting its ubiquitin-mediated degradation, thus suppressing the EMT and related functions of GC. In addition, the transcription factor p53 can regulate the expression of LINC00893 in an indirect way. Taken together, these results suggested that LINC00893 regulated by p53 repressed GC proliferation, migration and invasion by functioning as a binding site for RBFOX2 to regulate its stability and the expression of EMT-related proteins. LINC00893 acts as a tumor-inhibiting lncRNA that is induced by p53 in GC and regulates EMT by binding to RBFOX2, thus providing a novel experimental basis for the clinical treatment of GC.

Necroptosis-Related lncRNAs: Predicting Prognosis and the Distinction between the Cold and Hot Tumors in Gastric Cancer.

BACKGROUND: In the face of poor prognosis and immunotherapy failure of gastric cancer (GC), this project tried to find new potential biomarkers for predicting prognosis and precision medication to ameliorate the situation. METHODS: To form synthetic matrices, we retrieved stomach adenocarcinoma transcriptome data from Genotype-Tissue Expression Project (GTEx) and The Cancer Genome Atlas (TCGA). Necroptosis-related prognostic lncRNA was identified by coexpression analysis and univariate Cox regression. Then we performed the least absolute shrinkage and selection operator (LASSO) to construct the necroptosis-related lncRNA model. Next, the Kaplan-Meier analysis, time-dependent receiver operating characteristics (ROC), univariate Cox (uni-Cox) regression, multivariate Cox (multi-Cox) regression, nomogram, and calibration curves were made to verify and evaluate the model. Gene set enrichment analyses (GSEA), principal component analysis (PCA), immune analysis, and prediction of the half-maximal inhibitory concentration (IC50) in risk groups were also analyzed. For further discussing immunotherapy between the cold and hot tumors, we divided the entire set into two clusters based on necroptosis-related lncRNAs. RESULTS: We constructed a model with 16 necroptosis-related lncRNAs. In the model, we found the calibration plots showed a good concordance with the prognosis prediction. The area's 1-, 2-, and 3-year OS under the ROC curve (AUC) were 0.726, 0.763, and 0.770, respectively. Risk groups could be a guide of systemic treatment because of significantly different IC50 between risk groups. Above all, clusters could help distinguish between the cold and hot tumors effectively and contribute to precise mediation. Cluster 2 was identified as the hot tumor and more susceptible to immunotherapeutic drugs. CONCLUSION: The results of this project supported that necroptosis-related lncRNAs could predict prognosis and help make a distinction between the cold and hot tumors for improving individual therapy in GC.