Ask about this productRelated genes to: SLC22A18 antibody
- Gene:
- SLC22A18 NIH gene
- Name:
- solute carrier family 22 member 18
- Previous symbol:
- ORCTL2, BWSCR1A, IMPT1, SLC22A1L
- Synonyms:
- BWR1A, TSSC5, ITM
- Chromosome:
- 11p15.4
- Locus Type:
- gene with protein product
- Date approved:
- 1998-06-05
- Date modifiied:
- 2019-04-23
Related products to: SLC22A18 antibody
Related articles to: SLC22A18 antibody
- Sarcopenia (SARC) presents considerable challenges to the quality of life for the elderly and exerts a significant economic strain on healthcare systems. Contemporary therapeutic methods, such as physical activity, dietary supplementation, and medication, frequently demonstrate restricted effectiveness and significant individual variation. This study seeks to identify new therapeutic targets through the analysis of lysosomal autophagy-related differentially expressed genes (LARDEGs) associated with SARC. Differentially expressed genes(DEGs) related to SARC were identified through an extensive analysis of microarray datasets (GSE8479 and GSE1428) obtained from the Gene Expression Omnibus. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes pathway analysis, protein-protein interaction (PPI) network analysis, and Gene Set Enrichment Analysis were used to assess the biological functions, molecular pathways, autophagy-related molecular markers, and immune microenvironment linked to SARC DEGs. Our findings identified 12 LARDEGs, including BHLHE41, HLTF, UBE2D1, UBE2D2, NPC1, NDRG1, SLC22A18, CDKN1A, CALCOCO2, SCARB2, LGALS1, and RPS27A, that were significantly correlated with energy metabolism and mitochondrial function. We constructed a PPI network that identified six crucial hub genes: BHLHE41, UBE2D1, UBE2D2, CDKN1A, SCARB2, and RPS27A. This network provides significant insights into their functional roles and their potential as therapeutic targets. Additionally, an examination of immune infiltration demonstrated significant differences in the quantities of resting natural killer (NK) cells and M2 macrophages between SARC samples and control samples. CDKN1A displayed a positive correlation with M2 macrophages and an inverse relationship with resting NK cells. The results show how important the immune microenvironment is to the spread of SARC, suggesting promising pathways for the creation of immunotherapeutic strategies. Our research elucidates the molecular pathways implicated in SARC and establishes a foundation for future therapeutic approaches. However, additional validation is crucial to translating these findings into viable clinical applications. - Source: PubMed
Publication date: 2025/10/22
Zhou YeQian YueYuan XinZhu Qingqing - Breast cancer (BC) is the most common cancer and the leading cause of cancer death in women. Hereditary BC risk accounts for 25% of all cases. Pathological variants in known BC precursor genes explain only about 30% of hereditary BC cases, while the underlying genetic factors in most families remain unknown. Identifying hereditary cancer risk factors will help improve genetic counseling, cancer prevention, and cancer care. Here, we used whole-exome sequencing (WES) to identify genetic variants in 105 Vietnamese patients with BC and 50 healthy women. BC-associated variants were screened by the Franklin software and the criteria of the American College of Medical Genetics and Genomics (ACMG) and evaluated based on in silico analysis. In total, 56 variants were identified in 37 genes associated with BC, including , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , and in 41 patients. Among them, 12 variants were novel, and 10 variants were assessed as pathogenic/likely pathogenic by ACMG and ClinVar. Variants of uncertain significance (VUS) were evaluated using in silico prediction software to predict whether they are likely to cause the disease in patients. This is the first WES study to identify BC-associated genetic variants in Vietnamese patients, providing a comprehensive database of BC susceptibility gene variants. We suggest using WES as a tool to identify genetic variants in BC patients for risk prediction and treatment guidance. - Source: PubMed
Publication date: 2025/08/28
Van Tung NguyenLien Nguyen Thi KimHuan Le DucPhuong Pham CamMai Bui BichMai Nguyen Thi HoaHuong Tran Thi ThanhHuyen Phung ThiVan Chu NguyenVan Dung TranHuy Luu HongKien Dong ChiManh Dang VanLong Duong MinhLan Nguyen NgocHien Nguyen ThanhHanh Ha HongHoang Nguyen Huy - The improvement of carcass traits is a key focus in pig genetic breeding programs. To identify quantitative trait loci (QTLs) and genes linked to key carcass traits, we conducted a genome-wide association study (GWAS) using whole-genome sequencing data from 1118 commercial pigs (Duroc sires and Yorkshire/Landrace F1 dams). This study focused on six phenotypes: iodine value, belly firmness, belly side fat, total side thickness (belly SThK), belly subcutaneous fat (Subq), and belly seam. Phenotypes were measured using image analysis, DEXA, and fatty acid profiling, and genotyping was performed using low-pass sequencing (SkimSeq). After quality control, 18,911,793 single nucleotide polymorphisms (SNPs) were retained for further analysis. A GWAS was conducted using a linear mixed model implemented in GCTA. Key findings include a significant QTL on SSC15 (110.83-112.23 Mb), which is associated with the iodine value, containing genes such as , , , and , which have known roles in fatty acid metabolism. Additionally, , , and (120.74-121.88 Mb on SSC15) were linked to belly firmness, influencing muscle structure and fat composition. Three QTLs for belly side fat were identified on SSC1, SSC2, and SSC3, highlighting genes like , , and , which regulate fat deposition and lipid metabolism. The results provide novel molecular markers that can be incorporated into selective breeding programs to improve pork quality, fat distribution, and meat composition. These findings enhance our understanding of the genetic mechanisms underlying carcass belly traits while offering tools to improve pork quality, optimize fat composition, and align with consumer preferences in the meat production industry. - Source: PubMed
Publication date: 2025/04/29
Mozduri ZohrePlastow GrahamDekkers JackHoulahan KerryKemp RobertJuárez Manuel - The COVID-19 infection caused by SARS-CoV-2 in late 2019 posed unprecedented global health challenges of massive proportions. The persistent effects of COVID-19 have become a subject of significant concern amongst the medical and scientific community. This article aims to explore the probability of a link between the COVID-19 infection and the risk of lung cancer development. First, this article reports that SARS-CoV-2 induces severe inflammatory response and cellular stress, potentially leading to tumorigenesis through common pathways between SARS-CoV-2 infection and cancer. These pathways include the JAK/STAT3 pathway which is activated after the initiation of cytokine storm following SARS-CoV-2 infection. This pathway is involved in cellular proliferation, differentiation, and immune homeostasis. The JAK/STAT3 pathway is also hyperactivated in lung cancer which serves as a link thereof. It predisposes patients to lung cancer through myriad molecular mechanisms such as DNA damage, genomic instability, and cell cycle dysregulation. Another probable pathway to tumorigenesis is based on the possibility of an oncogenic nature of SARS-CoV-2 through hijacking the p53 protein, leading to cell oxidative stress and interfering with the DNA repair mechanisms. Finally, this article highlights the overexpression of the SLC22A18 gene in lung cancer. This gene can be overexpressed by the ZEB1 transcription factor, which was found to be highly expressed during COVID-19 infection. - Source: PubMed
Publication date: 2024/12/06
Amara AbdelbassetTrabelsi SaoussenHai AbdulZaidi Syeda Huma HSiddiqui FarahAlsaeed Sami - Lung cancer (LC) is a significant global health issue, with smoking as the most common cause. Recent epidemiological studies have suggested that individuals who smoke are more susceptible to COVID-19. In this study, we aimed to investigate the influence of smoking and COVID-19 on LC using bioinformatics and machine learning approaches. We compared the differentially expressed genes (DEGs) between LC, smoking, and COVID-19 datasets and identified 26 down-regulated and 37 up-regulated genes shared between LC and smoking, and 7 down-regulated and 6 up-regulated genes shared between LC and COVID-19. Integration of these datasets resulted in the identification of ten hub genes (SLC22A18, CHAC1, ROBO4, TEK, NOTCH4, CD24, CD34, SOX2, PITX2, and GMDS) from protein-protein interaction network analysis. The WGCNA R package was used to construct correlation network analyses for these shared genes, aiming to investigate the relationships among them. Furthermore, we also examined the correlation of these genes with patient outcomes through survival curve analyses. The gene ontology and pathway analyses were performed to find out the potential therapeutic targets for LC in smoking and COVID-19 patients. Moreover, machine learning algorithms were applied to the TCGA RNAseq data of LC to assess the performance of these common genes and ten hub genes, demonstrating high performances. The identified hub genes and molecular pathways can be utilized for the development of potential therapeutic targets for smoking and COVID-19-associated LC. - Source: PubMed
Publication date: 2024/10/22
Hossain Md AliRahman Mohammad ZahidurBhuiyan TouhidMoni Mohammad Ali