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In this report, galactosylated poly(ethylene glycol) methacrylate-st-3-guanidinopropyl methacrylamide copolymers (galactosylated PEGMA-st-GPMA, GGP) are developed as siRNA carriers to inhibit Survivin mRNA expression. GGPs are combined with Survivin siRNAs to form siRNA/GGP polyplexes. The polyplexes particles were examined by a dynamic light scattering. It showed that GGP copolymers could condense siRNA to form particles with diameter from 128 to 423 nm and zeta potential value in the range from +2.4 to +14.9 mV at various charge ratios (N/P). The MTT assay data of siRNA/GGP polyplexes on human hepatocellular liver carcinoma cells (HepG2) and human cervix epithelial carcinoma cells (HeLa) indicated that GGP copolymer had better cell viabilities than polyethyleimine (PEI). The transfection of siRNA/GGP polyplexes was detected by real-time quantitative PCR (RT-qPCR) in HepG2 cell line. We found that the siRNA/GGP polyplexes could effectively silence Survivin mRNA expression in the serum-free media (p < 0.01). In the presence of 10% serum medium, the Survivin mRNA expressed has significant difference between siRNA/GGP polyplexes and blank (p < 0.05). The galactose competition assay showed that galactosylated PEGMA-st-GPMA (GGP) may provide the targeting to HepG2 cells mediating by asialoglycoproteins receptors (ASGP-R). Furthermore, Survivin siRNA/GGP polyplexes could significantly (p < 0.01) inhibit both HepG2 tumor growth and Survivin protein expression in vivo studies in a xenograft mouse model.

Background. Cancer cells undergo various rewiring of metabolism and dysfunction of epigenetic modification to support their biosynthetic needs. Although the major features of metabolic reprogramming have been elucidated, the global metabolic genes linking epigenetics were overlooked in pan-cancer. Objectives. Identifying the critical metabolic signatures with differential expressions which contributes to the epigenetic alternations across cancer types is an urgent issue for providing the potential targets for cancer therapy. Method. The differential gene expression and DNA methylation were analyzed by using the 5726 samples data from the Cancer Genome Atlas (TCGA). Results. Firstly, we analyzed the differential expression of metabolic genes and found that cancer underwent overall metabolism reprogramming, which exhibited a similar expression trend with the data from the Gene Expression Omnibus (GEO) database. Secondly, the regulatory network of histone acetylation and DNA methylation according to altered expression of metabolism genes was summarized in our results. Then, the survival analysis showed that high expression of DNMT3B had a poorer overall survival in 5 cancer types. Integrative altered methylation and expression revealed specific genes influenced by DNMT3B through DNA methylation across cancers. These genes do not overlap across various cancer types and are involved in different function annotations depending on the tissues, which indicated DNMT3B might influence DNA methylation in tissue specificity. Conclusions. Our research clarifies some key metabolic genes, ACLY, SLC2A1, KAT2A, and DNMT3B, which are most disordered and indirectly contribute to the dysfunction of histone acetylation and DNA methylation in cancer. We also found some potential genes in different cancer types influenced by DNMT3B. Our study highlights possible epigenetic disorders resulting from the deregulation of metabolic genes in pan-cancer and provides potential therapy in the clinical treatment of human cancer. [ABSTRACT FROM AUTHOR]

Transcription factors are recognized as the key regulators of gene expression. However, the changes in the correlation of transcription factors and their target genes between normal and tumor tissues are usually ignored. In this research, we used mRNA expression profile data from The Cancer Genome Atlas which included 5726 samples across 11 major human cancers to perform co-expression analysis by the Pearson correlation coefficients. Then, integrating 81,357 pairs of transcription factors and target genes from transcription factors databases to find out the changes in the co-expression correlation of these gene pairs from normal to tumor tissues. Based on the changes in the number of co-expressed TF-TG pairs and changes in the level of co-expression, we found the generally reduced correlation between transcription factors and their target genes in cancer. Additionally, we screened out universal and specific transcription factors-target genes pairs which may significant influence particular cancer. Then, we obtained 423 cancer cell line expression profiles from Broad Institute Cancer Cell Line Encyclopedia to verify our results. Some of these pairs like XRCC5-XRCC6 have been reported to involve in multiple cancers, while pairs like IRF1-PSMB9 without any previous articles related to tumor but involve in the biological processes of cancer, which are of great potential to be therapeutic targets. Our research may provide insights to better understand the tumor development mechanisms and find potential therapeutic targets. [ABSTRACT FROM AUTHOR]