Search PubMedSearch

PubMed · 42330787

MicroRNAs and predicted targets in the switch from monolayered to spheroids of cholangiocarcinoma cells.

Abstract

BACKGROUND: Extrahepatic cholangiocarcinoma (eCCA) is characterized by marked molecular heterogeneity and limited therapeutic options. MicroRNAs (miRNAs) are key post-transcriptional regulators of cancer-related pathways, but their contribution to tumor adaptation in physiologically relevant models remains poorly understood. Three-dimensional (3D) tumor spheroids better mimic in vivo conditions than conventional two-dimensional (2D) cultures. METHODS: We compared miRNA expression profiles in two eCCA cell lines (Sk-ChA-1 and Mz-ChA-1) grown as monolayers (2D) or multicellular tumor spheroids (3D). MiRNA profiling was performed using NanoString technology. Predicted targets were analyzed by over-representation analysis, and selected miRNAs and genes were validated by RT-qPCR and ELISA-based assays. RESULTS: 3D growth induced extensive miRNA remodeling, with distinct (54 deregulated in Sk-ChA-1 and 29 in Mz-ChA-1 cells) and partially overlapping signatures (miR-1283, miR-577, and miR-2113). Among the shared miRNAs, predicted targets included DUSP10 and RBFOX1, while in spheroids, cell-specific multiple miRNAs converged on shared targets (TNRC6B, SMARCAD1, ATG14, HMGA2, and CLOCK) displaying inverse expression patterns. The transcriptional program impacted MAPK signaling, enhanced EMT, and activated stress-adaptive networks but attenuated proliferation in 3D Sk-ChA-1 cells, while Mz-ChA-1 cells retained a more epithelial and proliferative profile. In this context, we point out the involvement of miR-19b-3p using anti-miR transfection experiments. CONCLUSION: Our findings reveal a miRNA-driven regulatory landscape associated with 3D growth in eCCA, linking tumor architecture to signaling rewiring and cellular plasticity, and highlight potentially druggable candidate targets and pathways to investigate as candidates using inhibitors or gene therapy-based interventions.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Leda Roncoroni, Anna Terrazzan, Luca Elli, Pietro Ancona, Paula Olaizola, Silvia Tabano, Patrizia Colapietro, Filippo Gamberini, Chiara Orlandi, Gianluca Aguiari, Cristian Taccioli, Luisa Doneda, Nicoletta Bianchi. 2026-06-22. MicroRNAs and predicted targets in the switch from monolayered to spheroids of cholangiocarcinoma cells.. https://doi.org/10.1016/j.yexmp.2026.105059

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans