Hereditary retinoblastoma iPSC model reveals aberrant spliceosome function driving bone malignancies

Tu, Jian; Huo, Zijun; Yu, Yao; Zhu, Dandan; Xu, An; Huang, Mo-Fan; Hu, Ruifeng; Wang, Ruo–Yu; Gingold, Julian A.; Chen, Yi‐Hung; Tsai, Kuang‐Lei; Forcioli-Conti, Nicolas R.; Huang, Sarah X.L.; Webb, Thomas R.; Su, Jie; Bazer, Danielle; Jia, Peilin; Yustein, Jason T.; Wang, Lisa L.; Hung, Mien‐Chie; Zhao, Zhongming; Huff, Chad; Shen, Jingnan; Zhao, Ruiying; Lee, Dung‐Fang

doi:10.1073/pnas.2117857119

Cited by 20 publications

(19 citation statements)

References 43 publications

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“…In addition, SPRY2 (Sprouty RTK Signaling Antagonist 2) encodes a protein that belongs to the Sprouty family [ 34 – 37 ]. Outcomes from GSEA were enriched for p53 SIGNALING PATHWAY and SPLICEOSOME, in agreement with previous findings, indicating that the gene plays an important role in RB initiation and development [ 38 , 39 ].…”

Section: Discussionsupporting

confidence: 90%

Retinoblastoma gene expression profiling based on bioinformatics analysis

Murai

et al. 2023

BMC Med Genomics

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Background Retinoblastoma (RB) is frequently occurring malignant tumors that originate in the retina, and their exact cause and development mechanisms are yet to be fully comprehended. In this study, we identified possible biomarkers for RB and delved into the molecular mechanics linked with such markers. Methods In this study GSE110811 and GSE24673 were analyzed. Weighted gene co-expression network analysis (WGCNA) was applied to screen modules and genes associated with RB. By overlapping RB-related module genes with differentially expressed genes (DEGs) between RB and control samples, differentially expressed retinoblastoma genes (DERBGs) were acquired. A gene ontology (GO) enrichment analysis and a kyoto encyclopedia of genes and genomes (KEGG) enrichment analysis were conducted to explore the functions of these DERBGs. To study the protein interactions of DERBGs, a protein–protein interaction (PPI) network was constructed. Hub DERBGs were screened using the least absolute shrinkage and selection operator (LASSO) regression analysis, as well as the random forest (RF) algorithm. Additionally, the diagnostic performance of RF and LASSO methods was evaluated using receiver operating characteristic (ROC) curves and single-gene gene set enrichment analysis (GSEA) was conducted to explore the potential molecular mechanisms involved with these Hub DERBGs. In addition, the competing endogenous RNA (ceRNA) regulatory network of Hub DERBGs was constructed. Result About 133 DERBGs were found to be associated with RB. GO and KEGG enrichment analyses revealed that the important pathways of these DERBGs. Furthermore, the PPI network revealed 82 DERBGs interacting with each other. By RF and LASSO methods, PDE8B, ESRRB, and SPRY2 were identified as Hub DERBGs in patients with RB. From the expression assessment of Hub DERBGs, it was found that the levels of expression of PDE8B, ESRRB, and SPRY2 were significantly decreased in the tissues of RB tumors. Secondly, single-gene GSEA revealed a connection between these 3 Hub DERBGs and oocyte meiosis, cell cycle, and spliceosome. Finally, the ceRNA regulatory network revealed that hsa-miR-342-3p, hsa-miR-146b-5p, hsa-miR-665, and hsa-miR-188-5p may play a central role in the disease. Conclusion Hub DERBGs may provide new insight into RB diagnosis and treatment based on the understanding of disease pathogenesis.

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Section: Discussionsupporting

confidence: 90%

Retinoblastoma gene expression profiling based on bioinformatics analysis

Murai

et al. 2023

BMC Med Genomics

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“…Patient-derived iPSCs present a powerful cancer platform to assess the cellular signaling, transcriptional, and chromatin landscapes resulting from well-defined genetic alterations and provide potentially therapeutic insights into the early events of tumor initiation 26,[43][44][45][46][47][48] . Oncogenic activities of mutant p53s have been demonstrated in human Fig.…”

Section: Discussionmentioning

confidence: 99%

“…RNA-seq was performed by either UTHealth Houston Cancer Genomics Center or BGI Genomics. All RNA-seq data analyses were performed using Galaxy Community Hub ( https://galaxyproject.org/ ) to calculate FPKM (Fragments Per Kilobase of transcript per Million) as described previously 26 , 46 , 47 .…”

Section: Methodsmentioning

confidence: 99%

“…The tumor xenograft assay was performed using a method described previously 26 , 46 . LNZ308-p53(G245D) glioma lines were transduced with indicated shRNAs or genes, and inoculated into 8-week-old female Foxn1 nu mice subcutaneously.…”

Section: Methodsmentioning

confidence: 99%

“…ChIP-seq and ChIP-PCR analysis. ChIP was performed using modified previous methods 46 . For p53 and H3K27Ac, cells were fixed in 1% formaldehyde (Thermo Fisher Scientific, 28906) at room temperature for 10 min.…”

Section: Wt and Lfs Ipsc Generation And Cell Culturementioning

confidence: 99%

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Rewired m6A epitranscriptomic networks link mutant p53 to neoplastic transformation

Liu

Huang

et al. 2023

Nat Commun

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N6-methyladenosine (m6A), one of the most prevalent mRNA modifications in eukaryotes, plays a critical role in modulating both biological and pathological processes. However, it is unknown whether mutant p53 neomorphic oncogenic functions exploit dysregulation of m6A epitranscriptomic networks. Here, we investigate Li-Fraumeni syndrome (LFS)-associated neoplastic transformation driven by mutant p53 in iPSC-derived astrocytes, the cell-of-origin of gliomas. We find that mutant p53 but not wild-type (WT) p53 physically interacts with SVIL to recruit the H3K4me3 methyltransferase MLL1 to activate the expression of m6A reader YTHDF2, culminating in an oncogenic phenotype. Aberrant YTHDF2 upregulation markedly hampers expression of multiple m6A-marked tumor-suppressing transcripts, including CDKN2B and SPOCK2, and induces oncogenic reprogramming. Mutant p53 neoplastic behaviors are significantly impaired by genetic depletion of YTHDF2 or by pharmacological inhibition using MLL1 complex inhibitors. Our study reveals how mutant p53 hijacks epigenetic and epitranscriptomic machinery to initiate gliomagenesis and suggests potential treatment strategies for LFS gliomas.

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Organoids for Cancer Research: Advances and Challenges

Xin,

Li,

Wang

et al. 2024

Advanced Biology

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As 3D culture technology advances, new avenues have opened for the development of physiological human cancer models. These preclinical models provide efficient ways to translate basic cancer research into clinical tumor therapies. Recently, cancer organoids have emerged as a model to dissect the more complex tumor microenvironment. Incorporating cancer organoids into preclinical programs have the potential to increase the success rate of oncology drug development and recapitulate the most efficacious treatment regimens for cancer patients. In this review, four main types of cancer organoids are introduced, their applications, advantages, limitations, and prospects are discussed, as well as the recent application of single‐cell RNA‐sequencing (scRNA‐seq) in exploring cancer organoids to advance this field.

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Hereditary retinoblastoma iPSC model reveals aberrant spliceosome function driving bone malignancies

Cited by 20 publications

References 43 publications

Retinoblastoma gene expression profiling based on bioinformatics analysis

Retinoblastoma gene expression profiling based on bioinformatics analysis

Rewired m6A epitranscriptomic networks link mutant p53 to neoplastic transformation

Organoids for Cancer Research: Advances and Challenges

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