Yeun‐Jun Chung

Many studies have demonstrated the mechanisms of progression to castration-resistant prostate cancer (CRPC) and novel strategies for its treatment. Despite these advances, the molecular mechanisms underlying the progression to CRPC remain unclear, and currently, no effective treatments for CRPC are available. Here, we characterized the key genes involved in CRPC progression to gain insight into potential therapeutic targets. Bicalutamide-resistant prostate cancer cells derived from LNCaP were generated and named Bical R. RNA sequencing was used to identify differentially expressed genes (DEGs) between LNCaP and Bical R. In total, 631 DEGs (302 upregulated genes and 329 downregulated genes) were identified. The Cytohubba plug-in in Cytoscape was used to identify seven hub genes (ASNS, AGT, ATF3, ATF4, DDIT3, EFNA5, and VEGFA) associated with CRPC progression. Among these hub genes, ASNS and DDIT3 were markedly upregulated in CRPC cell lines and CRPC patient samples. The patients with high expression of ASNS and DDIT3 showed worse disease-free survival in patients with The Cancer Genome Atlas (TCGA)-prostate adenocarcinoma (PRAD) datasets. Our study revealed a potential association between ASNS and DDIT3 and the progression to CRPC. These results may contribute to the development of potential therapeutic targets and mechanisms underlying CRPC progression, aiming to improve clinical efficacy in CRPC treatment.

The molecular mechanisms underlying melanoma metastasis remain poorly understood. In this study, we aimed to delineate the mechanisms underlying gene expression alterations during metastatic potential acquisition and characterize the metastatic subclones within primary cell lines. We performed single‐cell RNA sequencing of a poorly metastatic melanoma cell line (WM239A) and its subclones with high metastatic potential to the lung (113/6‐4L) and the brain (131/4‐5B1 and 131/4‐5B2). Unsupervised clustering of 8173 melanoma cells identified three distinct clusters according to cell type (‘Primary’, ‘Lung’ and ‘Brain’ clusters) with differential expression of MITF and AXL pathways and putative cancer and cell cycle drivers, with the lung cluster expressing intermediate but distinct gene profiles between primary and brain clusters. Principal component (PC) analysis revealed that PC2 (the second PC), which was positively associated with MITF expression and negatively with AXL pathways, primarily segregated cell types, in addition to PC1 of the cell cycle pathway. Pseudotime trajectory and RNA velocity analyses suggested the existence of cellular subsets with metastatic potential in the Primary cluster and an association between PC2 signature alteration and metastasis potential acquisition. Analysis of The Cancer Genome Atlas melanoma samples by clustering into PC2‐high and ‐low clusters by quartiles of PC2 signature expression revealed that the PC2‐high cluster was an independent significant factor for poor prognosis ( p ‐value = 0.003) with distinct genomic and transcriptomic characteristics, compared to the PC2‐low cluster. In conclusion, we identified signatures of melanoma metastasis with prognostic significance and putative pro‐metastatic subclones within a primary cell line.