Clinical Significance of PRKCI Gene Expression in Cancerous Tissue in Patients With Gastric Cancer

Computational Image and Molecular Analysis Reveal Unique Prognostic Features of Immune Architecture in African Versus European American Women with Endometrial Cancer

Endometrial cancer (EC) disproportionately affects African American (AA) women in terms of progression and death. In our study, we sought to employ computerized image and bioinformatic analysis to tease out morphologic and molecular differences in EC between AA and European-American (EA) populations. We identified the differences in immune cell spatial patterns between AA and EA populations with markers of tumor biology, including histologic and molecular subtypes. The models performed best when they were trained and validated using data from the same population. Unsupervised clustering revealed a distinct association between immune cell features and known molecular subtypes of endometrial cancer that varied between AA and EA populations. Our genomic analysis revealed two distinct and novel gene sets with mutations associated with improved prognosis in AA and EA patients. Our study findings suggest the need for population-specific risk prediction models for women with endometrial cancer.

Protein Kinase C (PKC) Isozymes as Diagnostic and Prognostic Biomarkers and Therapeutic Targets for Cancer

Protein kinase C (PKC) is a large family of calcium- and phospholipid-dependent serine/threonine kinases that consists of at least 11 isozymes. Based on their structural characteristics and mode of activation, the PKC family is classified into three subfamilies: conventional or classic (cPKCs; α, βI, βII, and γ), novel or non-classic (nPKCs; δ, ε, η, and θ), and atypical (aPKCs; ζ, ι, and λ) (PKCλ is the mouse homolog of PKCι) PKC isozymes. PKC isozymes play important roles in proliferation, differentiation, survival, migration, invasion, apoptosis, and anticancer drug resistance in cancer cells. Several studies have shown a positive relationship between PKC isozymes and poor disease-free survival, poor survival following anticancer drug treatment, and increased recurrence. Furthermore, a higher level of PKC activation has been reported in cancer tissues compared to that in normal tissues. These data suggest that PKC isozymes represent potential diagnostic and prognostic biomarkers and therapeutic targets for cancer. This review summarizes the current knowledge and discusses the potential of PKC isozymes as biomarkers in the diagnosis, prognosis, and treatment of cancers.

PKCι Is a Promising Prognosis Biomarker and Therapeutic Target for Pancreatic Cancer

BACKGROUND

As the highest prevalent pancreatic cancer, pancreatic ductal adenocarcinoma (PDAC) ranks the 7th lethal malignancy worldwide. The late diagnosis, chemotherapeutic resistance, and high associated mortality make PDAC a dilemma facing the oncologists. Protein kinase C (PKC) enzymes have been shown to be important in different cancer progression.

METHODS

To understand the pattern of PKC enzymes in PDAC, we examined all PKC family member genes expression in PDAC and matched normal tissues. The critical role of PKCι was further investigated in different PDAC cells using cellular and molecular technology.

RESULTS

We found that PRKCI (PKCι) was the most significantly overexpressed PKCs in pancreatic cancer. However, little is known about its role and regulation of oncogenic signaling pathways in pancreatic cancer. In this study, we confirmed the overexpression of PKCι in PDAC, and this high expression was associated with poor prognosis of patients. We proved that knockdown of PKCι by small interfering RNA or shRNA significantly inhibited pancreatic cancer cell growth and migration or invasion. Conversely, PKCι overexpression promoted pancreatic cancer cell growth and migration. Moreover, bioinformatical and technical studies informed the participation of PKCι in regression of apoptosis in PDAC cells, which may be related to the regulation of both PI3K/AKT and Wnt/β-catenin pathways.

CONCLUSIONS

Therefore, our results are adding more insight into the importance of PKCι in pancreatic cancer. PKCι induces pancreatic cancer progression through activation of PI3K/AKT and Wnt/β-catenin signaling pathways, which may provide a promising therapeutic target for pancreatic cancer.

Impact of deleterious missense PRKCI variants on structural and functional dynamics of protein

Protein kinase C iota (PKC_ɩ) is a novel protein containing 596 amino acids and is also a member of atypical kinase family. The role of PKC_ɩ has been explored in neurodegenerative diseases, neuroblastoma, ovarian and pancreatic cancers. Single nucleotide polymorphisms (SNPs) have not been studied in PKC_ɩ till date. The purpose of the current study is to scrutinize the deleterious missense variants in PKC_ɩ and determine the effect of these variants on stability and dynamics of the protein. The structure of protein PKC_ɩ was predicted for the first time and post translational modifications were determined. Genetic variants of PKC_ɩ were retrieved from ENSEMBL and only missense variants were further analyzed because of its linkage with diseases. The pathogenicity of missense variants, effect on structure and function of protein, association with cancer and conservancy of the protein residues were determined through computational approaches. It is observed that C1 and the pseudo substrate region has the highest number of pathogenic SNPs. Variations in the kinase domain of the protein are predicted to alter overall phosphorylation of the protein. Molecular dynamic simulations predicted noteworthy change in structural and functional dynamics of the protein because of these variants. The study revealed that nine deleterious variants can possibly contribute to malfunctioning of the protein and can be associated with diseases. This can be useful in diagnostics and developing therapeutics for diseases related to these polymorphisms.

Expression profile of epithelial-mesenchymal transition-related genes as a prognostic biomarker for endometrial cancer

Epithelial-mesenchymal transition (EMT) is regulated by inducible factors, transcription factors, and a series of genes involved in diverse signaling pathways, which are correlated with tumor invasion and progression. In the present study, we analyzed the expression profile data of 1169 EMT-related genes in endometrial cancer (EC) from the Cancer Genome Atlas (TCGA) dataset, and performed consistency clustering to divide EC samples into two subgroups based on overall survival. The genes differentially expressed between the two subtypes included EMT-related genes. Univariate Cox analysis and least absolute shrinkage and selection operator (LASSO) were applied to construct a prognostic model based on the 44 genes signature. Five genes (L1CAM, PRKCI, ESR1, CDKN2A, and VIM) were finally included to establish a formula for prognostic risk score. The low-risk group showed significantly better prognosis compared with the high-risk group in the TCGA dataset. In addition, the risk-scoring model successfully predicted prognosis in an external GEO dataset (GSE102073). The relationship between ERα and vimentin levels was confirmed through immunohistochemistry. In conclusion, these data indicate that the expression profile of EMT-related genes could predict prognosis in EC.

Silencing circRNA protein kinase C iota (circ-PRKCI) suppresses cell progression and glycolysis of human papillary thyroid cancer through circ-PRKCI/miR-335/E2F3 ceRNA axis

The circular RNA PRKCI (circ-PRKCI; ID: hsa_circ_0122683) is highly expressed in human papillary thyroid cancer (PTC) tumors according to GSE93522 dataset. However, its role in PTC tumorigenesis remains to be documented. Here, quantitative real-time PCR showed that expression of circ-PRKCI was abnormally upregulated in human PTC patients' tumors and cells, and higher circ-PRKCI might predict lymph node metastasis and recurrence. Functionally, cell behaviors were measured by 3-(4,5-dimethylthiazolyl-2)-2,5-diphenyltetrazolium bromide assay, colony formation assay, fluorescence-activated cell sorting method, scratch wound assay, transwell assay, western blotting, and assay kits for glucose and lactate. As a result, circ-PRKCI knockdown could suppress cell cycle progression of PTC cells and restrain the abilities of cell proliferation, colony formation, wound closure, invasion, glucose consumption and lactate production, accompanied with decreased levels of matrix metalloproteinase-2 (MMP2), MMP9 and Snail. Moreover, above-mentioned inhibition could be imitated by overexpressing microRNA-335-5p (miR-335). Molecularly, circ-PRKCI functioned as a sponge for miR-335 and miR-335 could further targeted E2F transcription factor-3 (E2F3), according to dual-luciferase reporter assay and RNA immunoprecipitation. However, downregulating miR-335 diminished the effects of circ-PRKCI role on cell growth, metastasis and glycolysis in PTC cells; besides, there was a counteractive effect between miR-335 upregulation and E2F3 upregulation in PTC cells as well. Furthermore, xenograft experiment revealed that silencing circ-PRKCI could retard tumor growth of PTC cells in vivo. Collectively, circ-PRKCI exerted oncogenic role in PTC by antagonizing cell progression and glycolysis via regulating miR-335/E2F3 axis, suggesting circ-PRKCI was a potential biomarker and target for PTC.

Epigenetic Variation Analysis Leads to Biomarker Discovery in Gastric Adenocarcinoma

As one of the most common malignant tumors worldwide, gastric adenocarcinoma (GC) and its prognosis are still poorly understood. Various genetic and epigenetic factors have been indicated in GC carcinogenesis. However, a comprehensive and in-depth investigation of epigenetic alteration in gastric cancer is still missing. In this study, we systematically investigated some key epigenetic features in GC, including DNA methylation and five core histone modifications. Data from The Cancer Genome Atlas Program and other studies (Gene Expression Omnibus) were collected, analyzed, and validated with multivariate statistical analysis methods. The landscape of epi-modifications in gastric cancer was described. Chromatin state transition analysis showed a histone marker shift in gastric cancer genome by employing a Hidden-Markov-Model based approach, indicated that histone marks tend to label different sets of genes in GC compared to control. An additive effect of these epigenetic marks was observed by integrated analysis with gene expression data, suggesting epigenetic modifications may cooperatively regulate gene expression. However, the effect of DNA methylation was found more significant without the presence of the five histone modifications in our study. By constructing a PPI network, key genes to distinguish GC from normal samples were identified, and distinct patterns of oncogenic pathways in GC were revealed. Some of these genes can also serve as potential biomarkers to classify various GC molecular subtypes. Our results provide important insights into the epigenetic regulation in gastric cancer and other cancers in general. This study describes the aberrant epigenetic variation pattern in GC and provides potential direction for epigenetic biomarker discovery.

Targeting Rho GTPase Signaling Networks in Cancer

As key regulators of cytoskeletal dynamics, Rho GTPases coordinate a wide range of cellular processes, including cell polarity, cell migration, and cell cycle progression. The adoption of a pro-migratory phenotype enables cancer cells to invade the stroma surrounding the primary tumor and move toward and enter blood or lymphatic vessels. Targeting these early events could reduce the progression to metastatic disease, the leading cause of cancer-related deaths. Rho GTPases play a key role in the formation of dynamic actin-rich membrane protrusions and the turnover of cell-cell and cell-extracellular matrix adhesions required for efficient cancer cell invasion. Here, we discuss the roles of Rho GTPases in cancer, their validation as therapeutic targets and the challenges of developing clinically viable Rho GTPase inhibitors. We review other therapeutic targets in the wider Rho GTPase signaling network and focus on the four best characterized effector families: p21-activated kinases (PAKs), Rho-associated protein kinases (ROCKs), atypical protein kinase Cs (aPKCs), and myotonic dystrophy kinase-related Cdc42-binding kinases (MRCKs).