Carboxylesterase 4A Inhibits the Malignant Biological Behavior of Nasopharyngeal Carcinoma via the PI3K/AKT Pathway

BACKGROUND

Carboxylesterase 4A (CES4A) belongs to the member of the carboxylesterase family, yet there has been limited research into its malignant biological behavior in malignant tumors. Here, we aim to investigate the expression, cellular biological functions, and the potential underlying mechanism of CES4A in nasopharyngeal carcinoma (NPC).

METHOD

A standardized mean difference (SMD) analysis was used to analyze the dysregulation of CES4A based on the gene expression omnibus (GEO) database. qRT-PCR and immunohistochemical staining (IHC) were used to identify the mRNA and protein levels of CES4A in NPC cell lines and tissues, respectively. CCK-8, colony formation, wound healing and transwell assays were utilized to estimate cellular growth and metastasis, respectively. Western blot was conducted to evaluate the activity of PI3K/AKT signaling pathway.

RESULT

Both mRNA and protein expression of CES4A was significantly diminished both in NPC cell lines and primary tumor tissues. Ectopic expression of CES4A restrains the proliferation, colony formation, migration and invasion of NPC. Additionally, KEGG analysis based on GEO data and high-throughput transcriptome sequencing of cell lines all strongly suggested that CES4A was involved in regulating phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway. It was observed that AKT and phosphorylated AKT were remarkably reduced in CES4A overexpressing NPC cells, indicating that PI3K/AKT signaling pathway is hindered by CES4A.

CONCLUSION

CES4A expression is silenced in NPC, functioning as a tumor suppressor by negatively modulating the PI3K/AKT signaling pathway.

Two-Photon Photodynamic Therapy Targeting Cancers with Low Carboxylesterase 2 Activity Guided by Ratiometric Fluorescence

Human carboxylesterase 2 (hCES2) converts anticancer prodrugs, such as irinotecan, into their active metabolites via phase I drug metabolism. Owing to interindividual variability, hCES2 serves as a predictive marker of patient response to hCES2-activated prodrug-based therapy, whereby a low intratumoral hCES2 activity leads to therapeutic resistance. Despite the ability to identify nonresponders, effective treatments for resistant patients are needed. Clinically approved photodynamic therapy is an attractive alternative for irinotecan-resistant patients. Here, we describe the application of our hCES2-selective small-molecule ratiometric fluorescent chemosensor, Benz-AP, as a single theranostic agent given its discovered functionality as a photosensitizer. Benz-AP produces singlet oxygen and induces photocytotoxicity in cancer cells in a strong negative correlation with hCES2 activity. Two-photon excitation of Benz-AP produces fluorescence, singlet oxygen, and photocytotoxicity in tumor spheroids. Overall, Benz-AP serves as a novel theranostic agent with selective photocytotoxicity in hCES2-prodrug resistant cancer cells, making Benz-AP a promising agent for in vivo applications.

Transcriptome analysis reveals key genes and pathways related to sex differentiation in the Chinese soft-shelled turtle (Pelodiscus sinensis)

Most vertebrates exhibit sexual dimorphisms in size, colour, behaviour, physiology and many others. The Chinese soft-shelled turtle (Pelodiscus sinensis) male individuals reach a larger size than females which produce significant economic implications in aquaculture. However, the mechanisms of sex determination and plastic patterns of sex differentiation in P. sinensis remain unclear. Here, comparative transcriptome analysis on male and female embryonic gonads prior to gonad formation and stages mediated gonadal differentiation of P. sinensis were performed to characterize the potential sex-related genes and their molecular pathways in P. sinensis. A total of 6369 differentially expressed genes (DEGs) were identified from day 9 and day 16 and assigned to 626 GO pathways and 161 KEGG signalling pathways, including ovarian steroidogenesis pathway, steroid hormone biosynthesis pathways, and the GnRH signalling pathway (P < 0.05). Moreover, protein interaction network analyses revealed that Akr1c3, Sult2b1, Sts, Cyp3a, Cyp1b1, Sox30 and Lhx9 might be key candidate genes for sex differentiation in P. sinensis. These data provide a genomic rationale for the sex differentiation of P. sinensis and enrich the candidate gene pool for sex differentiation.

Genetic Analysis Reveals a Significant Contribution of CES1 to Prostate Cancer Progression in Taiwanese Men

The genes that influence prostate cancer progression remain largely unknown. Since the carboxylesterase gene family plays a crucial role in xenobiotic metabolism and lipid/cholesterol homeostasis, we hypothesize that genetic variants in carboxylesterase genes may influence clinical outcomes for prostate cancer patients. A total of 478 (36 genotyped and 442 imputed) single nucleotide polymorphisms (SNPs) in five genes of the carboxylesterase family were assessed in terms of their associations with biochemical recurrence (BCR)-free survival in 643 Taiwanese patients with prostate cancer who underwent radical prostatectomy. The strongest association signal was shown in CES1 (P = 9.64×10^-4 for genotyped SNP rs8192935 and P = 8.96 × 10^-5 for imputed SNP rs8192950). After multiple test correction and adjustment for clinical covariates, CES1 rs8192935 (P = 9.67 × 10^-4) and rs8192950 (P = 9.34 × 10^-5) remained significant. These SNPs were correlated with CES1 expression levels, which in turn were associated with prostate cancer aggressiveness. Furthermore, our meta-analysis, including eight studies, indicated that a high CES1 expression predicted better outcomes among prostate cancer patients (hazard ratio 0.82, 95% confidence interval 0.70-0.97, P = 0.02). In conclusion, our findings suggest that CES1 rs8192935 and rs8192950 are associated with BCR and that CES1 plays a tumor suppressive role in prostate cancer.

Gene network-based cancer prognosis analysis with sparse boosting

High-throughput gene profiling studies have been extensively conducted, searching for markers associated with cancer development and progression. In this study, we analyse cancer prognosis studies with right censored survival responses. With gene expression data, we adopt the weighted gene co-expression network analysis (WGCNA) to describe the interplay among genes. In network analysis, nodes represent genes. There are subsets of nodes, called modules, which are tightly connected to each other. Genes within the same modules tend to have co-regulated biological functions. For cancer prognosis data with gene expression measurements, our goal is to identify cancer markers, while properly accounting for the network module structure. A two-step sparse boosting approach, called Network Sparse Boosting (NSBoost), is proposed for marker selection. In the first step, for each module separately, we use a sparse boosting approach for within-module marker selection and construct module-level 'super markers'. In the second step, we use the super markers to represent the effects of all genes within the same modules and conduct module-level selection using a sparse boosting approach. Simulation study shows that NSBoost can more accurately identify cancer-associated genes and modules than alternatives. In the analysis of breast cancer and lymphoma prognosis studies, NSBoost identifies genes with important biological implications. It outperforms alternatives including the boosting and penalization approaches by identifying a smaller number of genes/modules and/or having better prediction performance.