HCC: RNA-Sequencing in Cirrhosis

Abstract

Hepatocellular carcinoma (HCC) ranks the most common types of cancer worldwide. As the fourth leading cause of cancer-related deaths, its prognosis remains poor. Most patients developed HCC on the basis of chronic liver disease. Cirrhosis is an important precancerous lesion for HCC. However, the molecular mechanisms in HCC development are still unclear. To explore the changes at the level of transcriptome in this process, we performed RNA-sequencing on cirrhosis, HCC and paracancerous tissues. Continuously changing mRNA was identified using Mfuzz cluster analysis, then their functions were explored by enrichment analyses. Data of cirrhotic HCC patients were obtained from TCGA, and a fatty acid metabolism (FAM)-related prognostic signature was then established. The performance and immunity relevance of the signature were verified in internal and external datasets. Finally, we validated the expression and function of ADH1C by experiments. As a result, 2012 differently expressed mRNA were identified by RNA-sequencing and bioinformatics analyses. Fatty acid metabolism was identified as a critical pathway by enrichment analyses of the DEGs. A FAM-related prognostic model and nomogram based on it were efficient in predicting the prognosis of cirrhotic HCC patients, as patients with higher risk scores had shorter survival time. Risk scores calculated by the signature were then proved to be associated with a tumor immune environment. ADH1C were downregulated in HCC, while silence of ADH1C could significantly promote proliferation and motility of the HCC cell line.

Identification and validation of a glycolysis‐related taxonomy for improving outcomes in glioma

“…Conversely, the GS1/3/4 subtypes displayed higher expression levels of SFRP2, SLC14A1, MKX, LUZP2, and USH1C; PRKCG, SV2B, SLC12A5, MAL2, and NEUROD6; L1CAM, CHGB, GPR17, GFRA1, and CRTAC1, respectively (Figure 4A). To identify the genes essential for prognostic variations in GS, we employed the Mfuzz package 21 to examine the expression trends of differentially expressed genes (DEGs). This analysis revealed eight clusters that were subsequently divided into two groups: the upregulated group (C5, C6, and C8) and the downregulated group (C1‐4 and C7).…”

Isobavachalcone Exhibits Potent Antifungal Efficacy by Inhibiting Enolase Activity and Glycolysis in Candida albicans

“…3 Nevertheless, the existing antifungal options are constrained and inadequate in effective addressing. 4,5 These include polyenes, which directly interact with the fungal membrane ergosterol, echinocandins that inhibit β-1,3glucan synthase, and azoles that target lanosterol 14-αdemethylase. 6 Furthermore, the escalating resistance of fungi to current drugs, particularly azoles, 7 and the emergence of the highly resistant Candida aruis 8 underscore the critical necessity for the exploration of novel antifungal compounds and the identification of new therapeutic targets.…”