“…Consistently, we observed that OPC-B2 inhibited glucose uptake and HK1 expression in a dose-dependent manner ( Fig. 4 A–B), consistent with AKT activity on regulation of HK1 protein expressions and glucose metabolism [ 27 , 40 ]. Fig.…”
The well-documented anticarcinogenic properties of natural polyphenolic proanthocyanidins (OPC) have been primarily attributed to their antioxidant and anti-inflammatory potency. Emerging evidence suggests that OPC may target canonical oncogenic pathways, including PI3K/AKT; however, the underlying mechanism and therapeutic potential remain elusive. Here we identify that proanthocyanidin B2 (OPC–B2) directly binds and inhibits AKT activity and downstream signalling, thereby suppressing tumour cell proliferation and metabolism
in vitro
and in a xenograft and diethyl-nitrosamine (DEN)-induced hepatocellular carcinoma (HCC) mouse models. We further find that OPC-B2 binds to the catalytic and regulatory PH domains to lock the protein in a closed conformation, similar to the well-studied AKT allosteric inhibitor MK-2206. Molecular docking and dynamic simulation suggest that Lys297 and Arg86 are critical sites of OPC-B2 binding; mutation of Lys297 or Arg86 to alanine completely abolishes the antitumor effects of OPC-B2 but not MK-2206. Together, our study reveals that OPC-B2 is a novel allosteric AKT inhibitor with potent anti-tumour efficacy beyond its antioxidant and anti-inflammatory properties.
“…Consistently, we observed that OPC-B2 inhibited glucose uptake and HK1 expression in a dose-dependent manner ( Fig. 4 A–B), consistent with AKT activity on regulation of HK1 protein expressions and glucose metabolism [ 27 , 40 ]. Fig.…”
The well-documented anticarcinogenic properties of natural polyphenolic proanthocyanidins (OPC) have been primarily attributed to their antioxidant and anti-inflammatory potency. Emerging evidence suggests that OPC may target canonical oncogenic pathways, including PI3K/AKT; however, the underlying mechanism and therapeutic potential remain elusive. Here we identify that proanthocyanidin B2 (OPC–B2) directly binds and inhibits AKT activity and downstream signalling, thereby suppressing tumour cell proliferation and metabolism
in vitro
and in a xenograft and diethyl-nitrosamine (DEN)-induced hepatocellular carcinoma (HCC) mouse models. We further find that OPC-B2 binds to the catalytic and regulatory PH domains to lock the protein in a closed conformation, similar to the well-studied AKT allosteric inhibitor MK-2206. Molecular docking and dynamic simulation suggest that Lys297 and Arg86 are critical sites of OPC-B2 binding; mutation of Lys297 or Arg86 to alanine completely abolishes the antitumor effects of OPC-B2 but not MK-2206. Together, our study reveals that OPC-B2 is a novel allosteric AKT inhibitor with potent anti-tumour efficacy beyond its antioxidant and anti-inflammatory properties.
“…Second, our data showed that the abundance of cyclin A is highly correlated with the Fubp1 level during cell cycle progression ( Figure 1 A,B). As we previously generated control (LC-GFP) and Fubp1-deficient (LC-Fubp1) NIH3T3 fibroblasts by utilizing the CRISPR/Cas system [ 29 ], we used these cells to experimentally test our hypothesis. As expected, both Ccna1 and Ccna2 transcript levels were significantly reduced in Fubp1-deficient cells ( Figure 1 C).…”
The discovery of novel and critical genes implicated in malignant development is a topic of high interest in cancer research. Intriguingly, a group of genes named “double-agent” genes were reported to have both oncogenic and tumor-suppressive functions. To date, less than 100 “double-agent” genes have been documented. Fubp1 is a master transcriptional regulator of a subset of genes by interacting with a far upstream element (FUSE). Mounting evidence has collectively demonstrated both the oncogenic and tumor suppressive roles of Fubp1 and the debate regarding its roles in tumorigenesis has been around for several years. Therefore, the detailed molecular mechanisms of Fubp1 need to be determined in each context. In the present study, we showed that the Fubp1 protein level was enriched in the S phase and we identified that Fubp1 deficiency altered cell cycle progression, especially in the S phase, by downregulating the mRNA expression levels of Ccna genes encoding cyclin A. Although this Fubp1-cyclin A axis appears to exist in several types of tumors, Fubp1 showed heterogeneous expression patterns among various cancer tissues, suggesting it exhibits multiple and complicated functions in cancer development. In addition, we showed that Fubp1 deficiency confers survival advantages to cells against metabolic stress and anti-cancer drugs, suggesting that Fubp1 may play both positive and negative roles in malignant development.
“…rs11807240 in FUBP1 , which upregulates the mRNA levels of the two hexokinase genes Hk1 and Hk2 - the rate limiting enzymes of glycolysis. A positive correlation between FUBP1 mRNA and both of hexokinases was found in several types of cancers (Kang, Lee, Kim, Lee, & Kim, 2019). Variants in LCA5 gene were shown to modify glucose response in a clinical trial of insulin and potassium (GIK) infusion in acute coronary syndromes (Ellis et al, 2015).…”
Background: Clinical data suggest that BMI and gestational weight gain (GWG) are strongly interconnected phenotypes, however the genetic basis of the latter is rather unclear. Here we aim to find genes and genetic variants which influence BMI and/or GWG. Methods: We have genotyped 316 type 1 diabetics using Illumina Infinium Omni Express Exome-8 v1.4 arrays. The GIANT, ARIC and T2D-GENES summary statistics were used for TWAS (performed with PrediXcan) in adipose tissue. Next, the analysis of association of imputed expression with BMI in the general and diabetic cohorts (Analysis 1 and 2) or GWG (Analysis 3 and 4) was performed, followed by variant association analysis (1Mb around identified loci) with the mentioned phenotypes. Results: In Analysis 1 we have found 175 BMI associated genes and 19 variants (p<10-4) which influenced GWG, with the strongest association for rs11465293 in CCL24 (p=3.18E-06). Analysis 2, with diabetes included in the model, led to discovery of 1812 BMI associated loci and 207 variants (p<10-4) influencing GWG, with the strongest association for rs9690213 in PODXL (p=9.86E-07). In Analysis 3, among 648 GWG associated loci, 2091 variants were associated with BMI (FDR<0.05). In Analysis 4, 7 variants in GWG associated loci influenced BMI in the ARIC cohort. Conclusions: Here, we have shown that loci influencing BMI might have an impact on GWG and GWG associated loci might influence BMI, both in the general and T1DM cohorts. The results suggest that both phenotypes are related to insulin signaling, glucose homeostasis, mitochondrial metabolism, ubiquitinoylation and inflammatory responses.
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