CCNA2 and KIF23 are molecular targets for the prognosis of adenoid cystic carcinoma.

OBJECTIVE: Adenoid cystic carcinoma (ACC) is a tumor type derived from glands. However, relationship between CCNA2 and KIF23, and adenoid cystic carcinoma remains unclear. METHODS: GSE36820 and GSE88804 profiles for ACC were obtained from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified, and Weighted Gene Co-expression Network Analysis (WGCNA) was conducted. Subsequently, the construction and analysis of protein-protein interaction (PPI) network, functional enrichment analysis, and Gene Set Enrichment Analysis (GSEA) were performed. A gene expression heat map was generated to visually depict the expression difference of core genes between adenoid cystic carcinoma and normal samples. TargetScan was employed to identify miRNAs that regulated central DEGs. Western blotting (WB) was conducted for cell verification. RESULTS: A total of 885 DEGs were identified. GO and KEGG analyses revealed their main enrichment in responses to chemical stimuli, cell proliferation, tissue development, and regulation of cell proliferation. The GO and KEGG results indicated significant enrichment in aldosterone-regulated sodium reabsorption, the cell cycle, and the PPAR signaling pathway. Notably, core genes (CCNA2 and KIF23) were found to be highly expressed in Adenoid Cystic Carcinoma samples and expressed at low levels in normal samples. WB validated the overexpression of CCNA2 and KIF23 in the Adenoid Cystic Carcinoma group, confirming the protein-level changes associated with cell cycle, metastasis, apoptosis, and inflammatory factors in Adenoid Cystic Carcinoma groups with gene overexpression and knockout. CONCLUSIONS: CCNA2 and KIF23 exhibit high expression levels in ACC, suggesting their potential role as molecular targets for this malignancy.

CDK1 and CCNA2 play important roles in oral squamous cell carcinoma.

Oral squamous cell carcinoma (OSCC) is a malignant tumor that occurs in oral cavity and is dominated by squamous cells. The relationship between CDK1, CCNA2, and OSCC is still unclear. The OSCC datasets GSE74530 and GSE85195 configuration files were downloaded from the Gene Expression Omnibus (GEO) database and were derived from platforms GPL570 and GPL6480. Differentially expressed genes (DEGs) were screened. The weighted gene co-expression network analysis, functional enrichment analysis, gene set enrichment analysis, construction and analysis of protein-protein interaction (PPI) network, Comparative Toxicogenomics Database analysis were performed. Gene expression heatmap was drawn. TargetScan was used to screen miRNAs that regulate central DEGs. A total of 1756 DEGs were identified. According to Gene Ontology (GO) analysis, they were predominantly enriched in processes related to organic acid catabolic metabolism, centromeric, and chromosomal region condensation, and oxidoreductase activity. In Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the DEGs were mainly concentrated in metabolic pathways, P53 signaling pathway, and PPAR signaling pathway. Weighted gene co-expression network analysis was performed with a soft-thresholding power set at 9, leading to the identification of 6 core genes (BUB1B, CCNB1, KIF20A, CCNA2, CDCA8, CDK1). The gene expression heatmap revealed that core genes (CDK1, CCNA2) were highly expressed in OSCC samples. Comparative Toxicogenomics Database analysis demonstrated associations between the 6 genes (BUB1B, CCNB1, KIF20A, CCNA2, CDCA8, CDK1) and oral tumors, precancerous lesions, inflammation, immune system disorders, and tongue tumors. The associated miRNAs for CDK1 gene were hsa-miR-203a-3p.2, while for CCNA2 gene, they were hsa-miR-6766-3p, hsa-miR-4782-3p, and hsa-miR-219a-5p. CDK1 and CCNA2 are highly expressed in OSCC. The higher the expression of CDK1 and CCNA2, the worse the prognosis.

Research on SPAD Estimation Model for Spring Wheat Booting Stage Based on Hyperspectral Analysis.

With the rapid progression of agricultural informatization technology, the methodologies of crop monitoring based on spectral technology are constantly upgraded. In order to carry out the efficient, precise and nondestructive detection of relative chlorophyll (SPAD) during the booting stage, we acquired hyperspectral reflectance data about spring wheat vertical distribution and adopted the fractional-order differential to transform the raw spectral data. After that, based on correlation analysis, fractional differential spectra and fractional differential spectral indices with strong correlation with SPAD were screened and fused. Then, the least-squares support vector machine (LSSSVM) and the least-squares support vector machine (SMA-LSSSVM) optimized on the slime mold algorithm were applied to construct the estimation models of SPAD, and the model accuracy was assessed to screen the optimal estimation models. The results showed that the 0.4 order fractional-order differential spectra had the highest correlation with SPAD, which was 9.3% higher than the maximum correlation coefficient of the original spectra; the constructed two-band differential spectral indices were more sensitive to SPAD than the single differential spectra, in which the correlation reached the highest level of 0.724. The SMA-LSSSVM model constructed based on the two-band fractional-order differential spectral indices was better than the single differential spectra and the integration of both, which realized the assessment of wheat SPAD.

PRPH2 Activates Hippo Signalling and Suppresses the Invasion and Anoikis Inhibition of Laryngeal Cancer.

INTRODUCTION: Laryngeal cancer is the most common head and neck cancer worldwide. It is urgent to identify the mechanisms underlying laryngeal cancer pathogenesis. In the present study, we investigated the biological functions of Peripherin 2 (PRPH2) in laryngeal cancer and uncovered the molecular mechanism underlying this disease. METHODS: Laryngeal cancer tissues were used to analyze the expression of PRPH2. In vitro transwell matrigel invasion assay and annexin V anoikis assay in laryngeal cancer cells were conducted to investigate PRPH2 related biological functions. Quantitative real-time PCR and Western blotting were performed to investigate the expression and mechanism of PRPH2 in laryngeal cancer. RESULTS: We found that the expression of PRPH2 was significantly downregulated in laryngeal cancer tissues. Overexpression of PRPH2 suppressed the invasion and anoikis inhibition of laryngeal cancer cells. Furthermore, PRPH2 overexpression increased the phosphorylation of YAP and LATS1 and decreased the activities of Rho GTPases, while PRPH2 knockdown had opposite effects. Inhibitors of the Hippo pathway abrogated PRPH2 knockdown-induced laryngeal cancer cell invasion and anoikis inhibition. DISCUSSION: These results suggested that PRPH2 suppresses laryngeal cancer cell invasion and anoikis inhibition by activating Hippo signalling. PRPH2 may serve as a potential therapeutic target for laryngeal cancer in the future.