The CYP19A1 rs700519 Polymorphism and Breast Cancer Susceptibility in China: A Case-Control Study and Updated Meta-Analysis

Association between NUDT17 polymorphisms and breast cancer risk

BACKGROUND

Breast cancer (BC) is the leading cause of cancer death among women worldwide. The nudix hydrolase 17 (NUDT17) may play notable roles in cancer growth and metastasis. In this study, we explored the importance of NUDT17 gene polymorphism in patients with BC.

METHODS

In our study, 563 BC patients and 552 healthy controls participated. We used logistic regression analysis to calculate odds ratios (OR) and 95% confidence intervals (CI), and multifactor dimension reduction (MDR) analysis of SNP-SNP interactions. Finally, UALCAN and THPA databases were used for bioinformatics analysis.

RESULTS

The rs9286836 G allele was associated with a decreased the BC risk (p = 0.022), and the carriers of rs2004659 G allele had a 32% decreased risk of BC than individuals with allele A (p = 0.004). In the four genetic models, rs9286836 and rs2004659 reduced the risk of BC. Additionally, we found that the NUDT17 SNPs were associated with BC risk under age, tumor size, and clinical stage stratification. The MDR analysis showed that the five-locus interaction model was the best in the multi-locus model.

CONCLUSION

Our study found that NUDT17 single nucleotide polymorphisms are associated with BC susceptibility in Chinese Han population.

Nanomedicine-Based Drug-Targeting in Breast Cancer: Pharmacokinetics, Clinical Progress, and Challenges

Breast cancer (BC) is a malignant neoplasm that begins in the breast tissue. After skin cancer, BC is the second most common type of cancer in women. At the end of 2040, the number of newly diagnosed BC cases is projected to increase by over 40%, reaching approximately 3 million worldwide annually. The hormonal and chemotherapeutic approaches based on conventional formulations have inappropriate therapeutic effects and suboptimal pharmacokinetic responses with nonspecific targeting actions. To overcome such issues, the use of nanomedicines, including liposomes, nanoparticles, micelles, hybrid nanoparticles, etc., has gained wider attention in the treatment of BC. Smaller dimensional nanomedicine (especially 50-200 nm) exhibited improved in vivo effectiveness, such as better tissue penetration and more effective tumor suppression through enhanced retention and permeation, as well as active targeting of the drug. Additionally, nanotechnology, which further extended and developed theranostic nanomedicine by incorporating diagnostic and imaging agents in one platform, has been applied to BC. Furthermore, hybrid and theranostic nanomedicine has also been explored for gene delivery as anticancer therapeutics in BC. Moreover, the nanocarriers' size, shape, surface charge, chemical compositions, and surface area play an important role in the nanocarriers' stability, cellular absorption, cytotoxicity, cellular uptake, and toxicity. Additionally, nanomedicine clinical translation for managing BC remains a slow process. However, a few cases are being used clinically, and their progress with the current challenges is addressed in this Review. Therefore, this Review extensively discusses recent advancements in nanomedicine and its clinical challenges in BC.

Clinical Eosinophil-Associated Genes can Serve as a Reliable Predictor of Bladder Urothelial Cancer

Background: Numerous studies have shown that infiltrating eosinophils play a key role in the tumor progression of bladder urothelial carcinoma (BLCA). However, the roles of eosinophils and associated hub genes in clinical outcomes and immunotherapy are not well known. Methods: BLCA patient data were extracted from the TCGA database. The tumor immune microenvironment (TIME) was revealed by the CIBERSORT algorithm. Candidate modules and hub genes associated with eosinophils were identified by weighted gene co-expression network analysis (WGCNA). The external GEO database was applied to validate the above results. TIME-related genes with prognostic significance were screened by univariate Cox regression analysis, lasso regression, and multivariate Cox regression analysis. The patient's risk score (RS) was calculated and divided subjects into high-risk group (HRG) and low-risk group (LRG). The nomogram was developed based on the risk signature. Models were validated via receiver operating characteristic (ROC) curves and calibration curves. Differences between HRG and LRG in clinical features and tumor mutational burden (TMB) were compared. The Immune Phenomenon Score (IPS) was calculated to estimate the immunotherapeutic significance of RS. Half-maximal inhibitory concentrations (IC50s) of chemotherapeutic drugs were predicted by the pRRophetic algorithm. Results: 313 eosinophil-related genes were identified by WGCNA. Subsequently, a risk signature containing 9 eosinophil-related genes (AGXT, B3GALT2, CCDC62, CLEC1B, CLEC2D, CYP19A1, DNM3, SLC5A9, SLC26A8) was finally developed via multiplex analysis and screening. Age (p < 0.001), grade (p < 0.001), and RS (p < 0.001) were independent predictors of survival in BLCA patients. Based on the calibration curve, our risk signature nomogram was confirmed as a good predictor of BLCA patients' prognosis at 1, 3, and 5 years. The association analysis of RS and immunotherapy indicated that low-risk patients were more credible for novel immune checkpoint inhibitors (ICI) immunotherapy. The chemotherapeutic drug model suggests that RS has an effect on the drug sensitivity of patients. Conclusions: In conclusion, the eosinophil-based RS can be used as a reliable clinical predictor and provide insights into the precise treatment of BLCA.

Comprehensive kinomic study via a chemical proteomic approach reveals kinome reprogramming in hepatocellular carcinoma tissues

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. Kinases are attractive therapeutic targets since they are commonly altered in cancers. Here, to identify kinases of potential therapeutic interest in HCC, a quantitative kinomic study of tumour and adjacent non-tumour liver tissues was performed using a chemical proteomics approach. In total, 124 kinases were found differentially expressed and they were distributed over all nine kinase groups. Exploration of The Cancer Genome Atlas (TCGA) data showed that the dysregulation of 45 kinases was correlated with poor prognosis in HCC patients. We then tested 11 inhibitors targeting 12 crucial protein kinases alone or in combination for their ability to inhibit cell growth in Hep3B and PLC/PRF/5 cell lines. Six inhibitors significantly reduced viability in both cell lines. Combination inhibition of polo-like kinase 1 (PLK1) and casein kinase 1 epsilon (CSNK1E) significantly induced growth arrest in both cell lines synergistically. In summary, our analysis presents the most complete view of kinome reprogramming in HCC and provides novel insight into crucial kinases in HCC and potential therapeutic targets for HCC treatment. Moreover, the identification of hundreds of differentially expressed kinases forms a rich resource for novel drug targets or diagnostic biomarker discovery. Data are available via ProteomeXchange (identifier PXD023806).