Functional enrichment analysis reveals the involvement of DARS2 in multiple biological pathways and its potential as a therapeutic target in esophageal carcinoma.

OBJECTIVE: The enzyme Aspartyl tRNA synthetase 2 (DARS2) is a crucial enzyme in the mitochondrial tRNA synthesis pathway, playing a critical role in maintaining normal mitochondrial function and protein synthesis. However, the role of DARS2 in ESCA is unclear. MATERIALS AND METHODS: Transcriptional data of pan-cancer and ESCA were downloaded from UCSC XENA, TCGA, and GEO databases to analyze the differential expression of DARS2 between tumor samples and normal samples, and its correlation with clinicopathological features of ESCA patients. R was used for GO, KEGG, and GSEA functional enrichment analysis of DARS2 co-expression and to analyze the connection of DARS2 with glycolysis and m6A-related genes. In vitro experiments were performed to assess the effects of interfering with DARS2 expression on ESCA cells. TarBase v.8, mirDIP, miRTarBase, ENCORI, and miRNet databases were used to analyze and construct a ceRNA network containing DARS2. RESULTS: DARS2 was overexpressed in various types of tumors. In vitro experiments confirmed that interfering with DARS2 expression significantly affected the proliferation, migration, apoptosis, cell cycle, and glycolysis of ESCA cells. DARS2 may be involved in multiple biological pathways related to tumor development. Furthermore, correlation and differential analysis revealed that DARS2 may regulate ESCA m6A modification through its interaction with METTL3 and YTHDF1. A ceRNA network containing DARS2, DLEU2/has-miR-30a-5p/DARS2, was successfully predicted and constructed. CONCLUSIONS: Our findings reveal the upregulation of DARS2 in ESCA and its association with clinical features, glycolysis pathway, m6A modification, and ceRNA network. These discoveries provide valuable insights into the molecular mechanisms underlying ESCA.

SPC25 as a novel therapeutic and prognostic biomarker and its association with glycolysis, ferroptosis and ceRNA in lung adenocarcinoma.

OBJECTIVE: Spindle pole body component 25 (SPC25) is an important cyclin involved in chromosome segregation and spindle dynamics regulation during mitosis. However, the role of SPC25 in lung adenocarcinoma (LAUD) is unclear. MATERIALS AND METHODS: The differential expression of SPC25 in tumor samples and normal samples was analyzed using TIMER, TCGA, GEO databases, and the correlation between its expression and clinicopathological features and prognosis in LUAD patients. Biological pathways that may be enriched by SPC25 were analyzed using GSEA. In vitro cell experiments were used to evaluate the effect of knocking down SPC25 expression on LUAD cells. Correlation analysis and differential analysis were used to assess the association of SPC25 expression with genes related to cell cycle, glycolysis, and ferroptosis. A ceRNA network involving SPC25 was constructed using multiple database analyses. RESULTS: SPC25 was highly expressed in LUAD, and its expression level could guide staging and predict prognosis. GSEA found that high expression of SPC25 involved multiple cell cycles and glycolytic pathways. Knocking down SPC25 expression significantly affected the proliferation, migration and apoptosis of LUAD cells. Abnormal SPC25 expression levels can affect cell cycle progression, glycolytic ability and ferroptosis regulation. A ceRNA network containing SPC25, SNHG15/hsa-miR-451a/SPC25, was successfully predicted and constructed. CONCLUSIONS: Our findings reveal the association of up-regulation of SPC25 in LUAD and its expression with clinical features, prognosis prediction, proliferation migration, cell cycle, glycolysis, ferroptosis, and ceRNA networks. Our results indicate that SPC25 can be used as a biomarker in LUAD therapy and a target for therapeutic intervention.

Unveiling facial kinship: The BioKinVis dataset for facial kinship verification and genetic association studies.

Facial image-based kinship verification represents a burgeoning frontier within the realms of computer vision and biomedicine. Recent genome-wide association studies have underscored the heritability of human facial morphology, revealing its predictability based on genetic information. These revelations form a robust foundation for advancing facial image-based kinship verification. Despite strides in computer vision, there remains a discernible gap between the biomedical and computer vision domains. Notably, the absence of family photo datasets established through biological paternity testing methods poses a significant challenge. This study addresses this gap by introducing the biological kinship visualization dataset, encompassing 5773 individuals from 2412 families with biologically confirmed kinship. Our analysis delves into the distribution and influencing factors of facial similarity among parent-child pairs, probing the potential association between forensic short tandem repeat polymorphisms and facial similarity. Additionally, we have developed a machine learning model for facial image-based kinship verification, achieving an accuracy of 0.80 in the dataset. To facilitate further exploration, we have established an online tool and database, accessible at http://120.55.161.230:88/.