Nucleocytoplasmic ß-catenin expression contributes to neuroendocrine differentiation in muscle invasive bladder cancer.

Bladder cancers are heterogeneous in nature, showing diverse molecular profiles and histopathological characteristics, which pose challenges for diagnosis and treatment. However, understanding the molecular basis of such heterogeneity has remained elusive. This study aimed to elucidate the molecular landscape of neuroendocrine-like bladder tumors, focusing on the involvement of ß-catenin localization. Analyzing the transcriptome data and benefiting from the molecular classification tool, we undertook an in-depth analysis of muscle-invasive bladder cancers to uncover the molecular characteristics of the neuroendocrine-like differentiation. The study explored the contribution of transcription factors and chromatin remodeling complexes to neuroendocrine differentiation in bladder cancer. The study revealed a significant correlation between ß-catenin localization and neuroendocrine differentiation in muscle-invasive bladder tumors, highlighting the molecular complexity of neuroendocrine-like tumors. Enrichment of YY1 transcription factor, E2F family members, and Polycomb repressive complex components in ß-catenin-positive tumors suggest their potential contribution to neuroendocrine phenotypes. Our findings contribute valuable insights into the molecular complexity of neuroendocrine-like bladder tumors. By identifying potential therapeutic targets and refining diagnostic strategies, this study advances our understanding of endocrinology in the context of bladder cancer. Further investigations into the functional implications of these molecular relationships are warranted to enhance our knowledge and guide future therapeutic interventions.

Generation of Anterior Segment of the Eye Cells from hiPSCs in Microfluidic Platforms.

Ophthalmic diseases affect many people, causing partial or total loss of vision and a reduced quality of life. The anterior segment of the eye accounts for nearly half of all visual impairment that can lead to blindness. Therefore, there is a growing demand for ocular research and regenerative medicine that specifically targets the anterior segment to improve vision quality. This study aims to generate a microfluidic platform for investigating the formation of the anterior segment of the eye derived from human induced pluripotent stem cells (hiPSC) under various spatial-mechanoresponsive conditions. Microfluidic platforms are developed to examine the effects of dynamic conditions on the generation of hiPSCs-derived ocular organoids. The differentiation protocol is validated, and mechanoresponsive genes are identified through transcriptomic analysis. Several culture strategies is implemented for the anterior segment of eye cells in a microfluidic chip. hiPSC-derived cells showed anterior eye cell characteristics in mRNA and protein expression levels under dynamic culture conditions. The expression levels of yes-associated protein and transcriptional coactivator PDZ binding motif (YAP/TAZ) and PIEZO1, varied depending on the differentiation and growth conditions of the cells, as well as the metabolomic profiles under dynamic culture conditions.

Retinoids and EZH2 inhibitors cooperate to orchestrate anti-oncogenic effects on bladder cancer cells.

The highly mutated nature of bladder cancers harboring mutations in chromatin regulatory genes opposing Polycomb-mediated repression highlights the importance of targeting EZH2 in bladder cancer. Furthermore, the critical role of the retinoic acid signaling pathway in the development and homeostasis of the urothelium, and the anti-oncogenic effects of retinoids are well established. Therefore, our aim is to simultaneously target EZH2 and retinoic acid signaling in bladder cancer to potentiate the therapeutic response. Here we report that this coordinated targeting strategy stimulates an anti-oncogenic profile, as reflected by inducing a synergistic reduction in cell viability that was associated with increased apoptosis and cell cycle arrest in a cooperative and orchestrated manner. This study characterized anti-oncogenic transcriptional reprogramming centered on the transcriptional regulator CHOP by stimulating the endoplasmic reticulum stress response. We further portrayed a molecular mechanism whereby EZH2 maintains H3K27me3-mediated repression of a subset of genes involved in unfolded protein responses, reflecting the molecular mechanism underlying this co-targeting strategy. These findings highlight the importance of co-targeting the EZH2 and retinoic acid pathway in bladder cancers and encourage the design of novel treatments employing retinoids coupled with EZH2 inhibitors in bladder carcinoma.

StemnesScoRe: an R package to estimate the stemness of glioma cancer cells at single-cell resolution.

Background/aim: Glioblastoma is the most heterogeneous and the most difficult-to-treat type of brain tumor and one of the deadliest among all cancers. The high plasticity of glioma cancer stem cells and the resistance they develop against multiple modalities of therapy, along with their high heterogeneity, are the main challenges faced during treatment of glioblastoma. Therefore, a better understanding of the stemness characteristics of glioblastoma cells is needed. With the development of various single-cell technologies and increasing applications of machine learning, indices based on transcriptomic and/or epigenomic data have been developed to quantitatively measure cellular states and stemness. In this study, we aimed to develop a glioma-specific stemness score model using scATAC-seq data for the first time. Materials and methods: We first applied three powerful machine-learning algorithms, i.e. random forest, gradient boosting, and extreme gradient boosting, to glioblastoma scRNA-seq data to discover the most important genes associated with cellular states. We then identified promoter and enhancer regions associated with these genes. After downloading the scATAC-seq peaks and their read counts for each patient, we identified the overlapping regions between the single-cell peaks and the peaks of genes obtained through machine-learning algorithms. Then we calculated read counts that were mapped to these overlapping regions. We finally developed a model capable of estimating the stemness score for each glioma cell using overlapping regions and the importance of genes predictive of glioblastoma cellular states. We also created an R package, accessible to all researchers regardless of their coding proficiency. Results: Our results showed that mesenchymal-like stem cells display higher stemness scores compared to neural-progenitor-, oligodendrocyte-progenitor-, and astrocyte-like cells. Conclusion: scATAC-seq can be used to assess heterogeneity in glioblastoma and identify cells with high stemness characteristics. The package is publicly available at https://github.com/Necla/StemnesScoRe and includes documentation with implementation of a real-data experiment.