Effect of human S100A13 gene silencing on FGF-1 transportation in human endothelial cells

Identification of a novel immune-related gene signature for prognosis and the tumor microenvironment in patients with uveal melanoma combining single-cell and bulk sequencing data

Introduction

Uveal melanoma (UVM) is the most invasive intraocular malignancy in adults with a poor prognosis. Growing evidence revealed that immune-related gene is related to tumorigenesis and prognosis. This study aimed to construct an immune-related prognostic signature for UVM and clarify the molecular and immune classification.

Methods

Based on The Cancer Genome Atlas (TCGA) database, single-sample gene set enrichment (ssGSEA) and hierarchical clustering analysis were performed to identify the immune infiltration pattern of UVM and classify patients into two immunity clusters. Then, we proposed univariate and multivariate Cox regression analysis to identify immune-related genes that related to overall survival (OS) and validated in the Gene Expression Omnibus (GEO) external validation cohort. The molecular and immune classification in the immune-related gene prognostic signature defined subgroups were analyzed.

Results

The immune-related gene prognostic signature was constructed based on S100A13, MMP9, and SEMA3B genes. The prognostic value of this risk model was validated in three bulk RNA sequencing datasets and one single-cell sequencing dataset. Patients in the low-risk group had better OS than those in the high-risk group. The receiver-operating characteristic (ROC) analysis revealed its strong predictive ability for UVM patients. Lower expression of immune checkpoint genes was presented in the low-risk group. Functional studies showed that S100A13 knockdown via siRNA inhibited UVM cell proliferation, migration, and invasion in vitro, with the increased expression of reactive oxygen species (ROS) related markers in UVM cell lines.

Discussion

The immune-related gene prognostic signature is an independent predictive factor for the survival of patients with UVM and provides new information about cancer immunotherapy in UVM.

Associations between serum concentrations of perfluoroalkyl substances and DNA methylation in women exposed through drinking water: A pilot study in Ronneby, Sweden

BACKGROUND

Perfluoroalkyl substances (PFAS) are widespread synthetic substances with various adverse health effects. A potential mechanism of toxicity for PFAS is via epigenetic changes, such as DNA methylation. However, few studies have evaluated associations between PFAS exposure and DNA methylation among adults, and data is especially scarce for women. Furthermore, exposure to environmental pollutants has been associated with epigenetic age acceleration, but no studies have yet evaluated whether PFAS is associated with epigenetic age acceleration.

OBJECTIVES

To investigate whether exposure to PFAS is associated with alteration of DNA methylation and epigenetic age acceleration among women.

METHODS

In this observational pilot study, 59 women (aged 20-47 years at enrollment in 2014) from Ronneby, Sweden, an area with historically high PFAS exposure due to local drinking water contamination, were divided into three PFAS exposure groups (low, medium, and high). Genome-wide methylation of whole-blood DNA was analyzed using the Infinium MethylationEPIC BeadChip. Ingenuity Pathway Analysis was used for in silico functional assessment. Epigenetic age acceleration was derived from the DNA methylation data using Horvath's epigenetic skin and blood clock.

RESULTS

117 differentially methylated positions (q < 0.017) and one near-significantly differentially methylated region (S100A13, FWER = 0.020) were identified. In silico functional analyses suggested that genes with altered DNA methylation (q < 0.05) were annotated to cancer, endocrine system disorders, reproductive system disease, as well as pathways such as estrogen receptor signaling, cardiac hypertrophy signaling, PPARα/RXRα activation and telomerase signaling. No differences in epigenetic age acceleration between PFAS exposure groups were noted (p = 0.43).

CONCLUSION

The data suggests that PFAS exposure alters DNA methylation in women highly exposed to PFAS from drinking water. The observed associations should be verified in larger cohorts, and it should also be further investigated whether these changes in methylation also underlie potential phenotypic changes and/or adverse health effects of PFAS.

Genome-wide analysis of DNA methylation identifies S100A13 as an epigenetic biomarker in individuals with chronic (≥ 30 years) type 2 diabetes without diabetic retinopathy

Background

This study aimed to determine the epigenetic biomarkers of diabetic retinopathy (DR) in subjects with type 2 diabetes mellitus (T2DM). This retrospective study is based on the Shanghai Xinjing community prevention and treatment administrative system of chronic diseases. The subjects enrolled herein were T2DM patients who had undergone long-term follow-up evaluation in the system. Two consecutive studies were conducted. In the discovery cohort, among 19 subjects who had developed DR with a DM duration < 3 years and 21 subjects without DR > 30 years after being diagnosed with DM, an Infinium Human Methylation 850 Beadchip was used to identify differential methylation regions (DMRs) and differential methylation sites (DMSs). The function of the genes was assessed through KEGG enrichment analysis, Gene Ontology (GO) analysis, and pathway network analysis. In the replication cohort, 87 DR patients with a short DM duration and 89 patients without DR over a DM duration > 20 years were compared to assess the association between DMSs and DR upon pyrosequencing.

Results

A total of 34 DMRs were identified. Genes containing DMSs with the top 5 highest beta value differences between DR and non-DR participants were located on chromosome 1 and were present in the S100A13 gene, which was associated with 71 GO terms. Two S100A13 gene sites, i.e., cg02873163 and cg11343894, displayed a good correlation with DR on pyrosequencing.

Conclusions

DMSs in the S100A13 gene may be potential biomarkers of DR.

Prognostic values of S100 family mRNA expression in ovarian cancer

S100 family is made up of at least 20 calcium-binding proteins which are involved in many cellular processes. The prognostic values of individual S100 member in ovarian cancer patients are still unknown. In this study, we performed a detailed prognostic values of S100 in ovarian cancer. The mRNA expression levels of S100 family in various cancers were analyzed via the Oncomine, and the protein-protein interaction network of S100 family was analyzed via String. The prognostic values of individual S100 member were evaluated via Kaplan-Meier Plotter. The S100 family genes expression and mutation were analyzed via cBioProtal. We observed that the mRNA expression of most S100 family were overexpressed in ovarian cancer compared with normal tissues. In survival analysis in Kaplan-Meier Plotter, 10 members of S100 family showed significant correlation with overall survival in ovarian cancer patients. The trends of high expression of individual S100 members were nearly the same in different subtype and pathological grades. However, the S100 family genes expression and mutation showed no significant prognostic values in overall survival and disease free survival in ovarian cancer patients. Although, the results need more verification both in clinical trials and fundamental experiments, our study provide new insights for the prognostic function of S100 family in ovarian cancer and might promote development of S100 targeted inhibitors for the new treatment of ovarian cancer.

The association between S100A13 and HMGA1 in the modulation of thyroid cancer proliferation and invasion

BACKGROUND

S100A13 and high mobility group A (HMGA1) are known to play essential roles in the carcinogenesis and progression of cancer. However, the correlation between S100A13 and HMGA1 during cancer progression is not yet well understood. In this study, we determined the effects of S100A13 on HMGA1 expression in thyroid cancer cells and examined the role of HMGA1 in thyroid cancer progression.

METHODS

Stable ectopic S100A13 expression TT cellular proliferation was evaluated by nude mice xenografts assays. The effect of lentivirus-mediated S100A13 knockdown on thyroid cancer cellular oncogenic properties were evaluated by MTT, colony formation assays and transwell assays in TPC1 and SW579 cells. The effect of siRNA-mediated HMGA1 knockdown on thyroid cancer cellular proliferation and invasion were evaluated by MTT, colony formation assays and transwell assays. The tissue microarray was performed to investigate the correlation between S100A13 and HMGA1 expression in tumor tissues.

RESULTS

The ectopic expression of S100A13 could increase tumor growth in a TT cell xenograft mouse model. Moreover, lentivirus-mediated S100A13 knockdown led to the inhibition of cellular oncogenic properties in thyroid cancer cells, and HMGA1 was found to be involved in the effect of S100A13 on thyroid cancer growth and invasion. Furthermore, siRNA-mediated HMGA1 knockdown was proved to inhibit the growth of TPC1 cells and invasive abilities of SW579 cells. Clinically, it was revealed that both S100A13 and HMGA1 showed a higher expression levels in thyroid cancer cases compared with those in matched normal thyroid cases (P = 0.007 and P = 0.000); S100A13 and HMGA1 expressions were identified to be positively correlated (P = 0.004, R = 0.316) when analyzed regardless of thyroid cancer types.

CONCLUSIONS

This is the first report for the association between HMGA1 and S100A13 expression in the modulation of thyroid cancer growth and invasion. Those results would provide an essential insight into the effect of S100A13 on carcinogenesis of thyroid tumor, rending S100A13 to be potential biological marker for the diagnosis of thyroid cancer.

Proteomics analysis of melanoma metastases: association between S100A13 expression and chemotherapy resistance

BACKGROUND

Disseminated cutaneous malignant melanoma (CMM) is commonly unresponsive to standard chemotherapies, and there are as yet no predictive markers of therapy response.

METHODS

In the present study we collected fresh-frozen pretreatment lymph-node metastasis samples (n=14) from melanoma patients with differential response to dacarbazine (DTIC) or temozolomide (TMZ) chemotherapy, to identify proteins with an impact on treatment response. We performed quantitative protein profiling using tandem mass spectrometry and compared the proteome differences between responders (R) and non-responders (NR), matched for age, gender and histopathological type of CMM.

RESULTS

Biological pathway analyses showed several signalling pathways differing between R vs NR, including Rho signalling. Gene expression profiling data was available for a subset of the samples, and the results were compared with the proteomics data. Four proteins with differential expression between R and NR were selected for technical validation by immunoblotting (ISYNA1, F13A1, CSTB and S100A13), and CSTB and S100A13 were further validated on a larger sample set by immunohistochemistry (n=48). The calcium binding protein S100A13 was found to be significantly overexpressed in NR compared with R in all analyses performed.

CONCLUSIONS

Our results suggest that S100A13 is involved in CMM resistance to DTIC/TMZ.

Protein-phospholipid interactions in nonclassical protein secretion: problem and methods of study

Extracellular proteins devoid of signal peptides use nonclassical secretion mechanisms for their export. These mechanisms are independent of the endoplasmic reticulum and Golgi. Some nonclassically released proteins, particularly fibroblast growth factors (FGF) 1 and 2, are exported as a result of their direct translocation through the cell membrane. This process requires specific interactions of released proteins with membrane phospholipids. In this review written by a cell biologist, a structural biologist and two membrane engineers, we discuss the following subjects: (i) Phenomenon of nonclassical protein release and its biological significance; (ii) Composition of the FGF1 multiprotein release complex (MRC); (iii) The relationship between FGF1 export and acidic phospholipid externalization; (iv) Interactions of FGF1 MRC components with acidic phospholipids; (v) Methods to study the transmembrane translocation of proteins; (vi) Membrane models to study nonclassical protein release.