S100A16 up-regulates Oct4 and Nanog expression in cancer stem-like cells of Yumoto human cervical carcinoma cells

The role of miR-6884-5p in epithelial-mesenchymal transition in non-small cell lung cancer

Significant progress has been made in the management of non-small cell lung cancer (NSCLC), though a big barrier remains, which is epithelial-mesenchymal transition (EMT). Our study aimed to evaluate the function of miR-6884-5p and S100A16 in EMT-aggravated NSCLC. The tumor tissues and adjacent tissues from 92 NSCLC patients were collected to analyze the expression of miR-6884-5p and S100A16. Then lung cancer cell line A549 was co-transfected with miR-6884-5p mimics and S100A16 to further evaluate their function. Compared to adjacent tissues, low expression of miR-6884-5p was observed in the NSCLC tissues and associated with severe NSCLC progression. MiR-6884-5p expression was negatively correlated with EMT in NSCLC. Luciferase assay data revealed that miR-6884-5p could directly bind to the 3'UTR of S100A16 and inhibited the expression of S100A16 in A549 cells. Moreover, miR-6884-5p mimics significantly ameliorated EMT progression, and overexpression of S100A16 could reverse the inhibitory effect of miR-6884-5p in A549 cells. MiR-6884-5p inhibited EMT through directly targeting S100A16 in NSCLC. Our findings suggest that miR-6884-5p could be a diagnostic marker of NSCLC, as well as a potential candidate for NSCLC treatment.

Expression and gene regulatory network of S100A16 protein in cervical cancer cells based on data mining

S100A16 protein belongs to the S100 family of calcium-binding proteins, which is widely distributed in human tissues and highly conserved. S100 calcium-binding proteins possess broad biological functions, such as cancer cell proliferation, apoptosis, tumor metastasis, and inflammation (Nat Rev Cancer 15:96-109, 2015). The S100A16 protein was initially isolated from a cell line derived from astrocytoma. The S100A16 protein, consisting of 103 amino acids, is a small acidic protein with a molecular weight of 11,801.4 Da and an isoelectric point (pI) of 6.28 (Biochem Biophys Res Commun 313:237-244, 2004). This protein exhibits high conservation among mammals and is widely expressed in various human tissues (Biochem Biophys Res Commun 322:1111-1122, 2004). Like other S100 proteins, S100A16 contains two EF-hand motifs that form a helix-loop-helix structural domain. The N-terminal domain and the C-terminal domain of S100A16 are connected by a "hinge" linker.S100A16 protein exhibits distinct characteristics that distinguish it from other S100 proteins. A notable feature is the presence of a single functional Ca2 + binding site located in the C-terminal EF-hand, consisting of 12 amino acids per protein monomer (J Biol Chem 281:38905-38917, 2006). In contrast, the N-terminal EF-hand of S100A16 comprises 15 amino acids instead of the typical 14, and it lacks the conserved glutamate residue at the final position. This unique attribute may contribute to the impaired Ca2 + binding capability in the N-terminal region (J Biol Chem 281:38905-38917, 2006). Studies have shown an integral role of S100 calcium-binding proteins in the diagnosis, treatment, and prognosis of certain diseases (Cancers 12:2037, 2020). Abnormal expression of S100A16 protein is implicated in the progression of breast and prostate cancer, but an inhibitor of oral cancer and acute lymphoblastic leukemia tumor cell proliferation (BMC Cancer 15:53, 2015; BMC Cancer 15:631, 2015). Tu et al. (Front Cell Dev Biol 9:645641, 2021) indicate that the overexpression of S100A16 mRNA in cervical cancer(CC) such as cervical squamous cell carcinoma and endocervical adenocarcinoma as compared to the control specimens. Tomiyama N. and co-workers (Oncol Lett 15:9929-9933, 2018) (Tomiyama, N) investigated the role of S100A16 in cancer stem cells using Yumoto cells (a CC cell line),The authors found upregulation of S100A16 in Yumoto cells following sphere formation as compared to monolayer culture.Despite a certain degree of understanding, the exact biological function of S100A16 in CC is still unclear. This article explores the role of S100A16 in CC through a bioinformatics analysis. Referencing the mRNA expression and SNP data of cervical cancer available through The Cancer Genome Atlas (TCGA) database, we analyzed S100A16 and its associated regulatory gene expression network in cervical cancer. We further screened genes co-expressed with S100A16 to hypothesize their function and relationship to the S100A16 cervical cancer phenotype.Our results showed that data mining can effectively elucidate the expression and gene regulatory network of S100A16 in cervical cancer, laying the foundation for further investigations into S100A16 cervical tumorigenesis.

BCL7B, a SWI/SNF complex subunit, orchestrates cancer immunity and stemness

Cancer is one of the main causes of human death. Here, we focus on the B-cell lymphoma 7 protein family member B (BCL7B) gene, an accessory subunit of the SWI/SNF chromatin-remodelling complex. To characterize the function of BCL7B, heterozygous BCL7B-deficient stomach cancer cell lines were generated with the CRISPR/Cas9 genome editing system. The comprehensive gene expression patterns were compared between parental cells and each ΔBCL7B cell line by RNA-seq. The results showed marked downregulation of immune-related genes and upregulation of stemness-related genes in the ΔBCL7B cell lines. Moreover, by ChIP-seq analysis with H3K27me3 antibody, the changes of epigenetic modification sequences were compared between parental cells and each ΔBCL7B cell line. After machine learning, we detected the centroid sequence changes, which exerted an impact on antigen presentation. The regulation of BCL7B expression in cancer cells gives rise to cancer stem cell-like characteristics and the acquisition of an immune evasion phenotype.

Integrative analysis of gene expression and DNA methylation to identify biomarkers of non-genital warts induced by low-risk human papillomaviruses infection

Background

Human papillomaviruses have been shown to dysregulate the gene expression and DNA methylation profiles of their host cells over the course of infection. However, there is a lack of information on the impact of low-risk HPV infection and wart formation on host cell's expression and methylation patterns. Therefore, the objective of this study is to analyse the genome and methylome of common warts using an integrative approach.

Methods

In the present study, gene expression (GSE136347) and methylation (GSE213888) datasets of common warts were obtained from the GEO database. Identification of the differentially expressed and differentially methylated genes was carried out using the RnBeads R package and the edgeR Bioconductor package. Next, functional annotation of the identified genes was obtained using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Network construction and analyses of the gene-gene, protein-protein, and signaling interactions of the differentially expressed and differentially methylated genes was performed using the GeneMANIA web interface, the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and the Signaling Network Open Resource 2.0 (SIGNOR 2.0), respectively. Lastly, significant hub genes were identified using the Cytoscape application CytoHubba.

Results

A total of 276 genes were identified as differentially expressed and differentially methylated in common warts, with 52% being upregulated and hypermethylated. Functional enrichment analysis identified extracellular components as the most enriched annotations, while network analyses identified ELN, ITGB1, TIMP1, MMP2, LGALS3, COL1A1 and ANPEP as significant hub genes.

Conclusions

To the best knowledge of the authors, this is the first integrative study to be carried out on non-genital warts induced by low-risk HPV types. Future studies are required to re-validate the findings in larger populations using alternative approaches.

An inhibitor of BRD4, GNE987, inhibits the growth of glioblastoma cells by targeting C-Myc and S100A16

PURPOSE

Among children, glioblastomas (GBMs) are a relatively common type of brain tumor. BRD4 expression was elevated in GBM and negatively correlated with the prognosis of glioma. We investigated the anti-GBM effects of a novel BRD4 inhibitor GNE987.

METHODS

We evaluated the anti-tumor effect of GNE987 in vitro and in vivo by Western blot, CCK8, flow cytometry detection, clone formation, the size of xenografts, and Ki67 immunohistochemical staining, and combined ChIP-seq with RNA-seq techniques to find its anti-tumor mechanism.

RESULTS

In vitro experiments showed that GNE987 significantly degraded BRD4, inhibited the proliferation of GBM cells, blocked the cell cycle, and induced apoptosis. Similarly, in vivo experiments, GNE987 also inhibited GBM growth as seen from the size of xenografts and Ki67 immunohistochemical staining. Based on Western blotting, GNE987 can significantly reduce the protein level of C-Myc; meanwhile, we combined ChIP-seq with RNA-seq techniques to confirm that GNE987 downregulated the transcription of S100A16 by disturbing H3K27Ac. Furthermore, we validated that S100A16 is indispensable in GBM growth.

CONCLUSION

GNE987 may be effective against GBM that targets C-Myc expression and influences S100A16 transcription through downregulation of BRD4.

Cancer stem cell characteristics and their potential as therapeutic targets

Cancer stem cells (CSCs) are a tumour subpopulation whose capacity for self-renewal, differentiation and proliferation generates unfavourable patient outcomes, including therapeutic resistance and metastasis. Much research has focused on the generation, biomarkers and therapeutic resistance of CSCs, as well as the development of CSC-targeted therapies. Reviews to date have either addressed general CSC characteristics or focused on CSCs from a well-studied cancer. Increasingly, specific treatment plans based on identification of molecular features and biomarkers of a patient's cancer, rather than classification according to tissue origin or bulk tumour properties, are leading to better patient outcomes. Here, we compare CSC characteristics, specifically their biomarkers and molecular features, and identify those that are common to a number of cancers. Identification of CSC markers that suggest therapeutic strategies has led to several successful in vitro and animal tests, recommending clinical trials of treatments with potentially enhanced therapeutic benefits, especially for recurring cancers.

S100A16 promotes metastasis and progression of pancreatic cancer through FGF19-mediated AKT and ERK1/2 pathways

The S100 protein family genes play a crucial role in multiple stages of tumorigenesis and progression. Most of S100 genes are located at chromosome locus 1q21, which is a region frequently rearranged in cancers. Here, we examined the expression of the S100 family genes in paired pancreatic ductal adenocarcinoma (PDAC) samples and further validated the expression of S100A16 by immunohistochemistry staining. We found that S100A16 is significantly upregulated in clinical PDAC samples. However, its roles in PDAC are still unclear. We next demonstrated that S100A16 promotes PDAC cell proliferation, migration, invasion, and metastasis both in vitro and in vivo. Knockdown of S100A16 induces PDAC cell cycle arrest in the G2/M phase and apoptosis. Furthermore, we also demonstrated that S100A16 promotes PDAC cell proliferation, migration, and invasion via AKT and ERK1/2 signaling in a fibroblast growth factor 19 (FGF19)-dependent manner. Taken together, our results reveal that S100A16 is overexpressed in PDAC and promotes PDAC progression through FGF19-mediated AKT and ERK1/2 signaling, suggesting that S100A16 may be a promising therapeutic target for PDAC. S100A16 was upregulated in PDAC and associated with prognosis of PDAC patients. S100A16 regulates apoptosis and the cell cycle of pancreatic cancer cells. S100A16 promotes the progression of pancreatic cancer by AKT-ERK1/2 signaling. S100A16 may be a promising therapeutic target for PDAC.

Advancing the Role of Gamma-Tocotrienol as Proteasomes Inhibitor: A Quantitative Proteomic Analysis of MDA-MB-231 Human Breast Cancer Cells

Tocotrienol, an analogue of vitamin E has been known for its numerous health benefits and anti-cancer effects. Of the four isoforms of tocotrienols, gamma-tocotrienol (γT3) has been frequently reported for their superior anti-tumorigenic activity in both in vitro and in vivo studies, when compared to its counterparts. In this study, the effect of γT3 treatment in the cytoplasmic and nuclear fraction of MDA-MB-231 human breast cancer cells were assessed using the label-free quantitative proteomics analysis. The cytoplasmic proteome results revealed the ability of γT3 to inhibit a group of proteasome proteins such as PSMA, PSMB, PSMD, and PSME. The inhibition of proteasome proteins is known to induce apoptosis in cancer cells. As such, the findings from this study suggest γT3 as a potential proteasome inhibitor that can overcome deficiencies in growth-inhibitory or pro-apoptotic molecules in breast cancer cells. The nuclear proteome results revealed the involvement of important nuclear protein complexes which hardwire the anti-tumorigenesis mechanism in breast cancer following γT3 treatment. In conclusion, this study uncovered the advancing roles of γT3 as potential proteasomes inhibitor that can be used for the treatment of breast cancer.

Genome-wide screening of abberant methylated drivers combined with relative risk loci in bladder cancer

Background

To explore important methylation‐driven genes (MDGs) and risk loci to construct risk model for prognosis of bladder cancer (BCa).

Methods

We utilized TCGA‐Assembler package to download 450K methylation data and corresponding transcriptome profiles. MethylMix package was used for identifying methylation‐driven genes and functional analysis was mainly performed based on ConsensusPathDB database. Then, Cox regression method was utilized to find prognostic MDGs, and we selected 17 hub genes via stepwise regression and multivariate Cox models. Kruskal‐Wallis test was implemented for comparisons between risk with other clinical variables. Moreover, we constructed the risk model and validated it in http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507. Gene set enrichment analysis was performed using the levels of risk score as the phenotype. Additionally, we further screened out the relative methylation sites associated with the 17 hub genes. Cox regression and Survival analysis were conducted to find the specifically prognostic sites.

Results

Two hundred and twenty‐eight MDGs were chosen by ConsensusPathDB database. Results revealed that most conspicuous pathways were transcriptional mis‐regulation pathways in cancer and EMT. After Cox regression analysis, 17 hub epigenetic MDGs were identified. We calculated the risk score and found satisfactory predictive efficiency by ROC curve (AUC = 0.762). In the validation group from http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE13507, 17 hub genes remained higher predictive value with AUC = 0.723 and patients in high‐risk group. Meanwhile, Kruskal‐Wallis test revealed that higher risk score correlated with a higher level of TNM stage, tumor grade, and advanced pathological stages. Then, identified 38 risk methylated loci that highly associated with prognosis. Last, gene set enrichment analysis revealed that high‐risk level of MDGs may correlate with several important pathways, including MAPK signaling pathway and so on.

Conclusion

Our study indicated several hub‐MDGs, calculated novel risk score and explored the prognostic value in BCa, which provided a promising approach to BCA prognosis assessment.

MicroRNA-6884-5p Regulates the Proliferation, Invasion, and EMT of Gastric Cancer Cells by Directly Targeting S100A16

S100 binding protein A16 (S100A16) expression levels are closely associated with microRNA (miRNA) processing. Higher levels of S100A16 are reported during the progression of many cancers. Our study mainly explored the interaction between S100A16 and miR-6884-5p in gastric cancer (GC). Quantitative real-time polymerase chain reaction (qRT-PCR) was used to determine the level of S100A16 and miR-6884-5p in GC tissues and cell lines. The si-S100A16, pcDNA-S100A16, miR-6884-5p mimic or inhibitor was transfected into GC cells, and the effects of S100A16 and miR-6884-5p on the proliferation, invasion, and epithelial-mesenchymal transition (EMT) were explored by qRT-PCR and Western blot assays. Luciferase assays were performed to validate S100A16 as an miR-6884-5p target in GC cells. In our study, we found that the level of miR-6884-5p was significantly decreased and the expression of S100A16 was significantly increased in GC tissues and cell lines. There was a close association between these changes. Knockdown of S100A16 significantly inhibited the proliferation, invasion, and EMT of GC cells. The bioinformatics analysis predicted that S100A16 is a potential target gene of miR-6884-5p, and the luciferase reporter assay confirmed that miR-6884-5p could directly target S100A16. Introduction of miR-6884-5p to GC cells had similar effects to S100A16 silencing. Overexpression of S100A16 in GC cells partially reversed the inhibitory effects of the miR-6884-5p mimic. miR-6884-5p inhibited the proliferation, invasion, and EMT of GC cells by directly decreasing S100A16 expression.