A common single-nucleotide polymorphism in the telomerase reverse transcriptase (TERT) promoter, rs2853669 influences patient survival rates and the risk of developing cancer. Recently, several lines of evidence suggest that the rs2853669 suppresses TERT promoter mutation-mediated TERT expression levels and cancer mortality as well as recurrence rates. However, no reports are available on the impact of rs2853669 on TERT expression in hepatocellular carcinoma (HCC) and its association with patient survival. Here, we found that HCC-related overall and recurrence-free survival rates were not associated with TERT promoter mutation individually, but rs2853669 and the TERT promoter mutation in combination were associated with poor survival rates. TERT mRNA expression and telomere fluorescence levels were greater in patients with HCC who had both the combination. The combination caused TERT promoter methylation through regulating the binding of DNA methyltransferase 1 and histone deacetylase 1 to the TERT promoter in HCC cell lines. The TERT expression level was significantly higher in HCC tumor with a methylated promoter than in that with an unmethylated promoter. In conclusion, we demonstrate a substantial role for the rs2853669 in HCC with TERT promoter mutation, which suggests that the combination of the rs2853669 and the mutation indicate poor prognoses in liver cancer.

In this paper, we propose a new capsule network architecture called Attention Routing CapsuleNet (AR CapsNet). We replace the dynamic routing and squash activation function of the capsule network with dynamic routing (Capsu-leNet) with the attention routing and capsule activation. The attention routing is a routing between capsules through an attention module. The attention routing is a fast forwardpass while keeping spatial information. On the other hand, the intuitive interpretation of the dynamic routing is finding a centroid of the prediction capsules. Thus, the squash activation function and its variant focus on preserving a vector orientation. However, the capsule activation focuses on performing a capsule-scale activation function.We evaluate our proposed model on the MNIST, affNIST, and CIFAR-10 classification tasks. The proposed model achieves higher accuracy with fewer parameters (×0.65 in the MNIST, ×0.82 in the CIFAR-10) and less training time than CapsuleNet (×0.19 in the MNIST, ×0.35 in the CIFAR-10). These results validate that designing a capsule-scale operation is a key factor to implement the capsule concept.Also, our experiment shows that our proposed model is transformation equivariant as CapsuleNet. As we perturb each element of the output capsule, the decoder attached to the output capsules shows global variations. Further experiments show that the difference in the capsule features caused by applying affine transformations on an input image is significantly aligned in one direction.

Glioblastoma is frequently associated with TP53 mutation, which is linked to a worse prognosis and response to conventional treatments (chemoradiotherapy). Therefore, targeting TP53 is a promising strategy to overcome this poor therapeutic response. Tumor-treating fields (TTFields) are a recently approved treatment for newly diagnosed glioblastoma, which involves direct application of lowintensity, intermediate-frequency alternating electric fields to the tumor, thereby offering a local tumor-killing effect. However, the influence of TP53 mutation status on the effectiveness of TTFields is controversial. Here, we identified the key gene signatures and pathways associated with TTFields in four glioblastoma cell lines varying in TP53 mutation status using gene profiling and functional annotation. Overall, genes associated with the cell cycle, cell death, and immune response were significantly altered by TTFields regardless of TP53 status. TTFields appeared to exert enhanced anticancer effects by altering the immune system in the inflammatory environment and regulating cell cycle-and cell death-related genes, but the precise genes influenced vary according to TP53 status. These results should facilitate detailed mechanistic studies on the molecular basis of TTFields to further develop this modality as combination therapy, which can improve the therapeutic effect and minimize side effects of chemoradiotherapy. Glioblastoma (GBM) a histological subtype of glioma in which most patients survive for an average of 12-15 months 1. In primary and secondary GBM, TP53 mutation is observed in up to 30% and 70% of cases, respectively, which results in a common molecular abnormality 2. TP53 is a major tumor suppressor that selectively eliminates mutated or damaged cells 3 , reduces the proliferation of cancer cells, and prevents the malignant transformation of normal cells 4. Moreover, TP53 regulates transcriptional target genes involved in many cellular responses including apoptosis 5 , senescence 6 , DNA repair 7 , and cell cycle 8 , among others. Several decades of research of glioma has shown that not only does TP53 serve a central role in the regulatory network of tumorigenesis, but also that the TP53 status is closely associated with the disease progression and survival of patients with GBM during radio-and chemotherapy 9,10. Several researchers have suggested that TP53-based targeted therapy is a promising approach for treating GBM, but its value as a prognostic marker in the clinical field is unclear. Microarray analysis is a useful method for evaluating therapies for GBM to detect differential expression between normal and cancer cells following treatment with specific drugs or physical procedures 11,12. TP53 has functional effects on the transcriptional profiles of genes in several cancer cell lines 13 , but the impact of tumortreating fields (TTFields) on GBM according to the TP53 status remains unknown. TTFields has been proposed as an effective cancer treatment in combination with other therapies 14. Alternating ele...

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Class I phosphoinositide 3‐kinase (PI3K) signaling is a major pathway in human cancer development and progression. Among the four PI3K isoforms, PI3Kα and PI3Kβ are ubiquitously expressed, whereas PI3Kγ and PI3Kδ are found primarily in leukocytes. Until now, PI3K targeting in solid tumors has focused on inhibiting PI3Kα‐mediated and PI3Kβ‐mediated cancer cell–intrinsic PI3K activity. The role of PI3Kδ in solid tumors is unknown. Here, we evaluated the effects of PI3Kδ using established hepatocellular carcinoma (HCC) cells, malignant hepatocytes derived from patients with advanced HCC, murine models, and HCC tissues using RNA sequencing, quantitative PCR, immunoblotting, immunofluorescence, microarray, liquid chromatography–tandem mass spectrometry, and kinase assay. We established a chemical carcinogenesis model of liver malignancy that reflects the malignant phenotype and the in vivo environment of advanced HCC. In this in vivo advanced HCC‐mimic system using HCC cells treated with hydrogen peroxide (H2O2), we showed that H2O2 selectively increases PI3Kδ activity while decreasing that of other class I PI3Ks. Blocking PI3Kδ activity with a PI3Kδ inhibitor or small interfering RNA–mediated PI3Kδ gene silencing inhibited HCC‐cell proliferation and dampened key features of malignant HCC, including the up‐regulation of telomerase reverse transcriptase (TERT). Mechanistically, H2O2 induced oxidative modification of the serpin peptidase inhibitor, serpin peptidase inhibitor (SERPINA3), blocking its ubiquitin‐dependent degradation and enhancing its activity as a transcriptional activator of PI3Kδ and TERT. High PI3Kδ levels in HCC were found to correlate with poor survival rates, with human advanced HCC showing positive correlations between the protein levels of oxidized SERPINA3, PI3Kδ, and TERT. Thus, PI3Kδ plays significant roles in malignant liver tumors. Conclusion: Our data identify PI3Kδ inhibition, recently approved for the treatment of human B‐cell malignancies, as a potential treatment for HCC.