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The key factors leading to transformed follicular lymphoma (t-FL) include the aberrations of epigenetic modifiers as early and driving events, especially mutations in the gene encoding for histone acetyltransferase. Therefore, reversal of this phenomenon by histone deacetylase (HDAC) inhibitors is essential for the development of new treatment strategies in t-FL. Several t-FL cell lines were treated with various doses of chidamide and subjected to cell proliferation, apoptosis and cell cycle analyses with CCK-8 assay, Annexin V/PI assay and flow cytometry, respectively. Chidamide dose-dependently inhibited cell proliferation, caused G0/G1 cycle arrest and triggered apoptosis in t-FL cells. In addition, the effects of chidamide on tumor growth were evaluated in vivo in xenograft models. RNA-seq analysis revealed gene expression alterations involving the PI3K-AKT signaling pathway might account for the mechanism underlying the antitumor activity of chidamide as a single agent in t-FL. These findings provide a basis for further clinical exploration of chidamide as a promising treatment for FL.

Background Metabolic reprogramming has been reported in various kinds of cancers and is related to clinical prognosis, but the prognostic role of pyrimidine metabolism in gastric cancer (GC) remains unclear. Methods Here, we employed DEG analysis to detect the differentially expressed genes (DEGs) in pyrimidine metabolic signaling pathway and used univariate Cox analysis, Lasso-penalizes Cox regression analysis, Kaplan–Meier survival analysis, univariate and multivariate Cox regression analysis to explore their prognostic roles in GC. The DEGs were experimentally validated in GC cells and clinical samples by quantitative real-time PCR. Results Through DEG analysis, we found NT5E, DPYS and UPP1 these three genes are highly expressed in GC. This conclusion has also been verified in GC cells and clinical samples. A prognostic risk model was established according to these three DEGs by Univariate Cox analysis and Lasso-penalizes Cox regression analysis. Kaplan–Meier survival analysis suggested that patient cohorts with high risk score undertook a lower overall survival rate than those with low risk score. Stratified survival analysis, Univariate and multivariate Cox regression analysis of this model confirmed that it is a reliable and independent clinical factor. Therefore, we made nomograms to visually depict the survival rate of GC patients according to some important clinical factors including our risk model. Conclusion In a word, our research found that pyrimidine metabolism is dysregulated in GC and established a prognostic model of GC based on genes differentially expressed in pyrimidine metabolism.

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