Genetic Variations in Thiamin Transferase SLC35F3 and the Risk of Hypertension in Koreans

TMC5 as a Marker of Tumor-Associated Telocytes in Hepatocellular Carcinoma

BACKGROUND

Tumor-associated telocytes (TATCs) perform a pivotal role in hepatocellular carcinoma (HCC) progression and correlate with poor patient outcomes. This study aims to identify specific markers of TATCs in HCC using single-nucleus RNA sequencing (snRNA-seq) and transcriptomic analyses.

METHODS

Comprehensive snRNA-seq and transcriptomic profiling were performed on HCC and adjacent non-cancerous tissues to detect differential expressed genes (DEGs) in TATCs. Bioinformatics tools, including STING and Cytoscape software, were employed to analyze protein-protein interactions and hub genes. Immune cell interactions were assessed via ligand-receptor network analysis.

RESULT

TATCs constituted 0.35% of cells in HCC tissues, with reduced proportions compared to para-cancerous tissues (0.35% vs 8.19%). Hub genes, including TOP2A (DNA topoisomerase Ⅱ alpha), BUB1B (BUB1 mitotic checkpoint serine/threonine kinase B), KIF11 (kinesin family member 11), and CENPF (centromere protein F) were identified in telocytes (TCs). Transcriptomics revealed 622 upregulated and 758 downregulated genes in TATCs versus TCs. TMC5 (transmembrane channel like 5) and SLC35F3 (solute carrier family 35 member F3) emerged as unique TATCs biomarkers, revealing significant associations with poor overall survival (OS) in HCC patients (HR = 1.499 for TMC5; HR = 1.562 for SLC35F3).

CONCLUSION

TMC5 and SLC35F3 are promising biomarkers for TATCs in HCC, warranting further validation to explore their clinical and therapeutic implications.

Screening and identification of key biomarkers associated with endometriosis using bioinformatics and next-generation sequencing data analysis

Background

Endometriosis is a common cause of endometrial-type mucosa outside the uterine cavity with symptoms such as painful periods, chronic pelvic pain, pain with intercourse and infertility. However, the early diagnosis of endometriosis is still restricted. The purpose of this investigation is to identify and validate the key biomarkers of endometriosis.

Methods

Next-generation sequencing dataset GSE243039 was obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) between endometriosis and normal control samples were identified. After screening of DEGs, gene ontology (GO) and REACTOME pathway enrichment analyses were performed. Furthermore, a protein–protein interaction (PPI) network was constructed and modules were analyzed using the Human Integrated Protein–Protein Interaction rEference database and Cytoscape software, and hub genes were identified. Subsequently, a network between miRNAs and hub genes, and network between TFs and hub genes were constructed using the miRNet and NetworkAnalyst tool, and possible key miRNAs and TFs were predicted. Finally, receiver operating characteristic curve analysis was used to validate the hub genes.

Results

A total of 958 DEGs, including 479 upregulated genes and 479 downregulated genes, were screened between endometriosis and normal control samples. GO and REACTOME pathway enrichment analyses of the 958 DEGs showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and muscle contraction. Further analysis of the PPI network and modules identified 10 hub genes, including vcam1, snca, prkcb, adrb2, foxq1, mdfi, actbl2, prkd1, dapk1 and actc1. Possible target miRNAs, including hsa-mir-3143 and hsa-mir-2110, and target TFs, including tcf3 (transcription factor 3) and clock (clock circadian regulator), were predicted by constructing a miRNA-hub gene regulatory network and TF-hub gene regulatory network.

Conclusions

This investigation used bioinformatics techniques to explore the potential and novel biomarkers. These biomarkers might provide new ideas and methods for the early diagnosis, treatment and monitoring of endometriosis.

Unveiling the Enigmatic Role of SLC35F3 in Lung Adenocarcinoma

BACKGROUND

The role of solute carrier family 35 member F3 (SLC35F3) in lung adenocarcinoma (LUAD) remains unclear. To address this gap, we conducted a study employing bioinformatics analysis and experimental validation.

METHODS

This study aimed to examine the expression patterns of SLC35F3 in various cancer types, particularly focusing on LUAD, by analyzing data from the Cancer Genome Atlas (TCGA) database to evaluate its clinical relevance. The research also explored potential regulatory mechanisms of SLC35F3, including its interactions with immune infiltration, tumor mutational burden (TMB), and drug sensitivity in LUAD. The investigation included analyzing SLC35F3 expression in single-cell sequencing of LUAD cells, examining genetic variations of SLC35F3 in LUAD, and assessing SLC35F3 expression in cell lines using quantitative real-time PCR (qRT-PCR).

RESULTS

The aberrant expression of SLC35F3 was observed in both pan-cancer and LUAD. In LUAD patients, a statistically significant increase in SLC35F3 expression was correlated with gender (p < 0.001) and was associated with poorer overall survival (OS) (p = 0.020). The expression of SLC35F3 was identified as an independent prognostic determinant in patients with LUAD (p = 0.032). SLC35F3 exhibited associations with various pathways, including cell cycle and more. SLC35F3 expression demonstrated correlations with immune infiltration, TMB, and some drugs in LUAD. Results indicated significant upregulation of SLC35F3 in both LUAD tissues and cell lines.

CONCLUSIONS

SLC35F3 may serve as a prognostic biomarker and immunotherapeutic target for patients with LUAD.

CLINICAL TRIAL REGISTRATION

Not applicable.

The construction of a novel prognostic prediction model for glioma based on GWAS-identified prognostic-related risk loci

Backgrounds

Glioma is a highly malignant brain tumor with a grim prognosis. Genetic factors play a role in glioma development. While some susceptibility loci associated with glioma have been identified, the risk loci associated with prognosis have received less attention. This study aims to identify risk loci associated with glioma prognosis and establish a prognostic prediction model for glioma patients in the Chinese Han population.

Methods

A genome-wide association study (GWAS) was conducted to identify risk loci in 484 adult patients with glioma. Cox regression analysis was performed to assess the association between GWAS-risk loci and overall survival as well as progression-free survival in glioma. The prognostic model was constructed using LASSO Cox regression analysis and multivariate Cox regression analysis. The nomogram model was constructed based on the single nucleotide polymorphism (SNP) classifier and clinical indicators, enabling the prediction of survival rates at 1-year, 2-year, and 3-year intervals. Additionally, the receiver operator characteristic (ROC) curve was employed to evaluate the prediction value of the nomogram. Finally, functional enrichment and tumor-infiltrating immune analyses were conducted to examine the biological functions of the associated genes.

Results

Our study found suggestive evidence that a total of 57 SNPs were correlated with glioma prognosis (p < 5 × 10-5). Subsequently, we identified 25 SNPs with the most significant impact on glioma prognosis and developed a prognostic model based on these SNPs. The 25 SNP-based classifier and clinical factors (including age, gender, surgery, and chemotherapy) were identified as independent prognostic risk factors. Subsequently, we constructed a prognostic nomogram based on independent prognostic factors to predict individualized survival. ROC analyses further showed that the prediction accuracy of the nomogram (AUC = 0.956) comprising the 25 SNP-based classifier and clinical factors was significantly superior to that of each individual variable.

Conclusion

We identified a SNP classifier and clinical indicators that can predict the prognosis of glioma patients and established a prognostic prediction model in the Chinese Han population. This study offers valuable insights for clinical practice, enabling improved evaluation of patients' prognosis and informing treatment options.

Effects of Interaction between SLC35F3 and Carbohydrate Intake on the Incidence of Metabolic Syndrome in Korean Middle-Aged Adults

Solute carrier family 35 member F3 (SLC35F3) mediates intracellular thiamine transport, which is crucial for carbohydrate metabolism as thiamine is required for key pathways such as glycolysis and the tricarboxylic acid cycle. This study aimed to investigate the impact of the interaction between SLC35F3 and dietary carbohydrate intake on the incidence of metabolic syndrome (MetS). The study included 3923 Korean adults over 40 years of age from the Korean Genome and Epidemiology Study. The association between dietary carbohydrate intake, SLC35F3 rs10910387 genotypes, and MetS incidence was studied using multivariable Cox proportional hazard models. Over an average of 8.5 years of follow-ups, we documented 1471 MetS cases. MetS incidence was 1.88 times greater in men with the TT genotype and the highest carbohydrate intake than in those with the CC genotype and lowest carbohydrate intake (Hazard Ratio (HR) 1.88, 95% confidence interval (CI) 1.03-3.41). MetS incidence were 2.22 and 2.53 times higher in women with the TT genotype and carbohydrate intake tertile 2 and 3, respectively, than those with the CC genotype and carbohydrate intake tertile 1 (HR 2.22, 95% CI 1.12-4.42; HR 2.53, 95% CI 1.38-4.61). In summary, we report a novel interaction between SLC35F3 rs10910387 genotypes and dietary carbohydrate intake on MetS in Koreans.