This study aims to discover the therapeutic effect of chemokine (CXC motif) receptor 4 (CXCR4) antagonist AMD3100 combined with transcatheter arterial chemoembolization (TACE) in a rat model with hepatocellular carcinoma (HCC). An orthotopic model of HCC was established and treated with TACE (doxorubicin‐lipiodol emulsion) with or without AMD3100. The tumor volume was measured by magnetic resonance imaging (MRI). Histopathological changes were detected by hematoxylin–eosin (HE) staining. HCC cell apoptosis was assessed by terminal deoxyribonucleotidyl transferase (TdT)‐mediated biotin‐16‐dUTP nick‐end labeling (TUNEL) staining. Immunohistochemistry was used to detect the expression of CD34, hypoxia‐inducible factor 1α (HIF‐1α), vascular endothelial growth factor (VEGF), and Ki67. Gene and protein expressions were quantified by quantitative reverse‐transcription polymerase chain reaction (qRT‐PCR) and western blotting, respectively. Both TACE and AMD3100 reduced the tumor volume in orthotopic rat model of HCC with the decreased CXCR4 expression in tumor tissues, and the combination had better effect. However, TACE increased the microvessel density (MVD) in HCC tissues of rats, while AMD3100 treatment reduced MVD in HCC tissues. AMD3100 reduced the TACE induced MVD in HCC tissues with the reduction of HIF‐1α and VEGF expression. Either AMD3100 or TACE could promote HCC cell apoptosis accompanying by decreased cell proliferation, and their combined use had better therapeutic effects. CXCR4 antagonist AMD3100 enhance therapeutic efficacy of TACE in rats with HCC via promoting the HCC cell apoptosis, reducing cell proliferation, and inhibiting MVD, thus reducing tumor volume.

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Background Genome instability lncRNA (GILnc) is prevalently related with gastric cancer (GC) pathophysiology. However, the study on the relationship GILnc and prognosis and drug sensitivity of GC remains scarce. Method We extracted expression data of 375 GC patients from TCGA cohort and 205 GC patients from GSE26942 cohort. Then, lncRNA was separated from expression data, and systematically characterized the 8 marker lncRNAs using the LASSO method. Next, we constructed a GILnc model (GILnc score) to quantify the GILnc index of each GC patient. Finally, we analyzed the relationship between GILnc score and clinical traits including survival outcomes, TP53, and drug sensitivity of GC. Results Based on a computational frame, 205 GILncs in GC has been identified. Then, a 8 GILncs was successfully established to predict overall survival in GC patients based on LASSO analysis, divided GC samples into high GILnc score and low GILnc score groups with significantly different outcome and was validated in multiple independent patient cohorts. Furthermore, GILnc model is better than the prediction performance of two recently published lncRNA signatures, and the high GILnc score group was more sensitive to mitomycin. Besides, the GILnc score has greater prognostic significance than TP53 mutation status alone and is capable of identifying intermediate subtype group existing with partial TP53 functionality in TP53 wild-type patients. Finally, GILnc signature as verified in GSE26942. Conclusion We applied bioinformatics approaches to suggest that a 8 GILnc signature could serve as prognostic biomarkers, and provide a novel direction to explore the pathogenesis of GC.