Association between TP53 gene codon72 polymorphism and prostate cancer risk: A systematic review and meta-analysis

Significance of TP53 Mutational Status-Associated Signature in the Progression and Prognosis of Endometrial Carcinoma

Background. TP53 mutations are associated with poor outcome for patients with endometrial carcinoma (EC). However, to date, there have been no studies focused on the construction of TP53 mutational status-associated signature in EC. In this study, we aim to conduct a TP53 mutation-associated prognostic gene signature for EC. Methods. Hence, we explored the mutational landscape of TP53 in patients with EC based on the simple nucleotide variation data downloaded from The Cancer Genome Atlas (TCGA) database. Differential expression analysis and least absolute shrinkage and selection operator (LASSO)–Cox analysis was used to establish TP53 mutation-associated prognostic gene signature. The overall survival rate between the high-risk and low-risk groups was compared by the Kaplan–Meier (K-M) method. Results. We found that the TP53 mutation was associated with poor outcome, older age, lower BMI, and higher grade and stage of EC in patients. A TP53 mutational status-associated signature was established based on transcriptome profiling data. Moreover, the patients in TCGA database were categorized into high- and low-risk groups. Kaplan–Meier (K-M) analysis indicated that the patients in the high-risk group have poor survival outcome. Furthermore, receiver operating characteristic (ROC) curves confirmed the robust prognostic prediction efficiency of the TP53 mutational status-associated signature. Finally, the prognostic ability was successfully verified in the other two datasets from cBioPortal database as well as in 60 clinical specimens. Univariate (hazard ratio $\left(\text{HR}\right)=1.041$ , $95\%\text{CI}=1.031–1.051$ , $p<0.001$ ) and multivariate (hazard ratio $\left(\text{HR}\right)=1.029$ , $95\%\text{CI}=1.018–1.040$ , $p<0.001$ ) Cox regression analyses indicated that the TP53 mutational status-associated signature could be used as an independent prognostic factor for EC patients. Conclusion. In summary, our research constructed a powerful TP53 mutational status-associated signature that could be a potential novel prognostic biomarker and therapeutic target for EC.

Study on the Multitarget Mechanism and Active Compounds of Essential Oil from Artemisia argyi Treating Pressure Injuries Based on Network Pharmacology

In order to comprehensively explore multitarget mechanism and key active compounds of Artemisia argyi essential oil (AAEO) in the treatment of pressure injuries (PIs), we analyzed the biological functions and pathways involved in the intersection targets of AAEO and PIs based on network pharmacology, and the affinity of AAEO active compounds and core targets was verified by molecular docking finally. In our study, we first screened 54 effective components according to the relative content and biological activity. In total, 103 targets related to active compounds of AAEO and 2760 targets associated with PIs were obtained, respectively, and 50 key targets were overlapped by Venny 2.1.0. The construction of key targets-compounds network was achieved by the STRING database and Cytoscape 3.7.2 software. GO analysis from Matespace shows that GO results are mainly enriched in biological processes, including adrenergic receptor activity, neurotransmitter clearance, and neurotransmitter metabolic process. KEGG analysis by the David and Kobas website shows that the key targets can achieve the treatment on PIs through a pathway in cancer, PI3K-Akt signaling pathway, human immunodeficiency virus 1 infection, MAPK signaling pathway, Wnt signaling pathway, etc. In addition, molecular docking results from the CB-Dock server indicated that active compounds of AAEO had good activity docking with the first 10 key targets. In conclusion, the potential targets and regulatory molecular mechanisms of AAEO in the treatment of PIs were analyzed by network pharmacology and molecular docking. AAEO can cure PIs through the synergistic effect of multicomponent, multitarget, and multipathway, providing a theoretical basis and new direction for further study.

Identification of Germline Genetic Variants that Increase Prostate Cancer Risk and Influence Development of Aggressive Disease

Prostate cancer (PrCa) is a heterogeneous disease, which presents in individual patients across a diverse phenotypic spectrum ranging from indolent to fatal forms. No robust biomarkers are currently available to enable routine screening for PrCa or to distinguish clinically significant forms, therefore late stage identification of advanced disease and overdiagnosis plus overtreatment of insignificant disease both remain areas of concern in healthcare provision. PrCa has a substantial heritable component, and technological advances since the completion of the Human Genome Project have facilitated improved identification of inherited genetic factors influencing susceptibility to development of the disease within families and populations. These genetic markers hold promise to enable improved understanding of the biological mechanisms underpinning PrCa development, facilitate genetically informed PrCa screening programmes and guide appropriate treatment provision. However, insight remains largely lacking regarding many aspects of their manifestation; especially in relation to genes associated with aggressive phenotypes, risk factors in non-European populations and appropriate approaches to enable accurate stratification of higher and lower risk individuals. This review discusses the methodology used in the elucidation of genetic loci, genes and individual causal variants responsible for modulating PrCa susceptibility; the current state of understanding of the allelic spectrum contributing to PrCa risk; and prospective future translational applications of these discoveries in the developing eras of genomics and personalised medicine.

The Impact of HMGB1 Polymorphisms on Prostate Cancer Progression and Clinicopathological Characteristics

Prostate cancer is one of the major cancers of the genitourinary tract. High-mobility group box 1 (HMGB1) was suggested as a promising therapeutic target for prostate cancer. In this study, we aim to elucidate the associations of HMGB1 single nucleotide polymorphisms (SNPs) with prostate cancer susceptibility and clinicopathological characteristics. The HMGB1 SNPs rs1412125, rs2249825, rs1045411, and rs1360485 in 579 prostate cancer patients and 579 cancer-free controls were analyzed with real-time polymerase chain reactions (real-time PCR). All of the data were evaluated with SAS statistical software. Our results showed that the HMGB1 rs1045411 T allele genotype was significantly associated with advanced pathologic T stage (odds ratio (OR) = 1.433, 95% confidence interval (CI) = 1.021–2.012; p = 0.037) and pathologic N1 stage (OR = 2.091, 95% CI = 1.160–3.767; p = 0.012), and the rs1360485 polymorphic CT + TT genotype was associated with pathologic Gleason grade group (4 + 5) (OR = 1.583, 95% CI = 1.017–2.462; p = 0.041), pathologic T stage (3 + 4) (OR = 1.482, 95% CI = 1.061–2.070; p = 0.021), and pathologic N1 stage (OR = 2.131, 95% CI = 1.178–3.852; p = 0.011) compared with their wild-type carriers. In conclusion, our results revealed that the HMGB1 SNPs were associated with the clinical status of prostate cancer. The HMGB1 SNPs may have the potential to predict prostate cancer disease progression.