Alu-dependent RNA editing of GLI1 promotes malignant regeneration in multiple myeloma

Lazzari, Elisa; Mondala, Phoebe; Santos, Nathaniel Delos; Miller, Amber C.; Pineda, Gabriel; Jiang, Qingfei; Leu, Heather; Ali, Shawn; Ganesan, Anusha-Preethi; Wu, C.; Costello, Caitlin; Minden, Mark D.; Chiaramonte, R.; Stewart, AK; Crews, Leslie; Jamieson, Catriona

doi:10.1038/s41467-017-01890-w

Cited by 98 publications

(123 citation statements)

References 44 publications

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“…These findings might suggest that RNA editing of GLI1 can have a negative impact on GLI1-dependent tumorigenesis. However, it was recently shown that GLI1 editing is associated with multiple myeloma development, highlighting the context-specific impact of this GLI1 post-transcriptional modification in tumor biology and suggesting that additional investigation into this complex phenomenon is required (Lazzari et al, 2017).…”

Section: Introductionmentioning

confidence: 99%

Identification of novel GLI1 target genes and regulatory circuits in human cancer cells

et al. 2018

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Hedgehog (HH) signaling is involved in many physiological processes, and pathway deregulation can result in a wide range of malignancies. Glioma‐associated oncogene 1 (GLI1) is a transcription factor and a terminal effector of the HH cascade. Despite its crucial role in tumorigenesis, our understanding of the GLI1 cellular targets is quite limited. In this study, we identified multiple new GLI1 target genes using a combination of different genomic surveys and then subjected them to in‐depth validation in human cancer cell lines. We were able to validate >90% of the new targets, which were enriched in functions involved in neurogenesis and regulation of transcription, in at least one type of follow‐up experiment. Strikingly, we found that RNA editing of GLI1 can modulate effects on the targets. Furthermore, one of the top targets, FOXS1, a gene encoding a transcription factor previously implicated in nervous system development, was shown to act in a negative feedback loop limiting the cellular effects of GLI1 in medulloblastoma and rhabdomyosarcoma cells. Moreover, FOXS1 is both highly expressed and positively correlated with GLI1 in medulloblastoma samples of the Sonic HH subgroup, further arguing for the existence of FOXS1/GLI1 interplay in human tumors. Consistently, high FOXS1 expression predicts longer relapse‐free survival in breast cancer. Overall, our findings open multiple new avenues in HH signaling pathway research and have potential for translational implications.

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Section: Introductionmentioning

confidence: 99%

Identification of novel GLI1 target genes and regulatory circuits in human cancer cells

et al. 2018

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“…Several other papers published after 2014 [42, 43] also suggested some role for PTEN in glaucoma. MeTeOR also predicted an association between GLI1 and multiple myeloma, and in 2017, Alu-dependent RNA editing of GLI1 was shown to promote malignant regeneration in multiple myeloma [44].…”

Section: Resultsmentioning

confidence: 99%

Automated literature mining and hypothesis generation through a network of Medical Subject Headings

Wilson

et al. 2018

Preprint

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25 The scientific literature is vast, growing, and increasingly specialized, making it difficult to 26 connect disparate observations across subfields. To address this problem, we sought to develop 27 automated hypothesis generation by networking at scale the MeSH terms curated by the National 28 Library of Medicine. The result is a Mesh Term Objective Reasoning (MeTeOR) approach that 29 tallies associations among genes, drugs and diseases from PubMed and predicts new ones.30 Comparisons to reference databases and algorithms show MeTeOR tends to be more reliable. We 31 also show that many predictions based on the literature prior to 2014 were published 32 subsequently. In a practical application, we validated experimentally a surprising new 33 association found by MeTeOR between novel Epidermal Growth Factor Receptor (EGFR) 34 associations and CDK2. We conclude that MeTeOR generates useful hypotheses from the 35 literature (http://meteor.lichtargelab.org/). AUTHOR SUMMARY37 The large size and exponential expansion of the scientific literature forms a bottleneck to 38 accessing and understanding published findings. Manual curation and Natural Language 39 Processing (NLP) aim to address this bottleneck by summarizing and disseminating the 40 knowledge within articles as key relationships (e.g. TP53 relates to Cancer). However, these 41 methods compromise on either coverage or accuracy, respectively. To mitigate this compromise, 42 we proposed using manually-assigned keywords (MeSH terms) to extract relationships from the 43 publications and demonstrated a comparable coverage but higher accuracy than current NLP 44 methods. Furthermore, we combined the extracted knowledge with semi-supervised machine 45 learning to create hypotheses to guide future work and discovered a direct interaction between 46 two important cancer genes. 47 48 49 3 50 INTRODUCTION 51 It is difficult to keep abreast of new publications. Currently, PubMed contains over 28 million 52 papers (http://www.ncbi.nlm.nih.gov/pubmed)-3 million more than three years ago. This steady 53 accumulation of findings gives rise to a large number of latent connections that Literature-Based 54 Discovery (LBD) seeks to systematically recognize and integrate [1], such as Swanson's original 55 finding linking fish oil to the treatment of Raynaud's disease [2]. Since this original analysis, 56 LBD has been extensively replicated, automated and expanded [3-10], leading to new patterns of 57 inference -e.g. locating opposing actions of a disease and a drug on given physiological 58 functions [11] -and to new discoveries [12]. Successes include the automated discovery of 59 protein functions [13, 14] and of the genetic bases of disease [15, 16], as well as the stratification 60 of patient phenotypes [17] and outcomes [18]. 61A limitation of LBD, however, is its dependence on knowledge extraction. It either relies 62 on human curation, which is not scalable, or on comprehensive text-mining, for which 63 algorithms are less accurate [19, 20]. One of the largest curated m...

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“…In vivo studies showed that leukemia progenitor cells harboring this misspliced GSK3β gene displayed enhanced β-catenin expression, which was required for the self-renewal of leukemia stem cells (LSCs) [50]. It was estimated that the genomic amplification of ADAR1 occurred in 30-50% of multiple myeloma patients and portended an unfavorable prognosis [51]. The silencing of ADAR1 attenuated in vivo engraftment of myeloma through suppression of the transcriptional activity of GLI1 [51], a self-renewal agonist and candidate marker for CSCs [64].…”

Section: A-to-i Modification and Cancer Stem Cellsmentioning

confidence: 99%

“…It was estimated that the genomic amplification of ADAR1 occurred in 30-50% of multiple myeloma patients and portended an unfavorable prognosis [51]. The silencing of ADAR1 attenuated in vivo engraftment of myeloma through suppression of the transcriptional activity of GLI1 [51], a self-renewal agonist and candidate marker for CSCs [64]. Further studies have shown that ADAR1 can edit exon 12 of the GLI1 transcript, leading to a novel GLI1 protein with a point mutation ( Fig.…”

Section: A-to-i Modification and Cancer Stem Cellsmentioning

confidence: 99%

mRNA modification orchestrates cancer stem cell fate decisions

Liang

Lin

et al. 2020

Mol Cancer

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Despite their small numbers, cancer stem cells play a central role in driving cancer cell growth, chemotherapeutic resistance, and distal metastasis. Previous studies mainly focused on how DNA or histone modification determines cell fate in cancer. However, it is still largely unknown how RNA modifications orchestrate cancer cell fate decisions. More than 170 distinct RNA modifications have been identified in the RNA world, while only a few RNA base modifications have been found in mRNA. Growing evidence indicates that three mRNA modifications, inosine, 5methylcytosine, and N 6 -methyladenosine, are essential for the regulation of spatiotemporal gene expression during cancer stem cell fate transition. Furthermore, transcriptome-wide mapping has found that the aberrant deposition of mRNA modification, which can disrupt the gene regulatory network and lead to uncontrollable cancer cell growth, is widespread across different cancers. In this review, we try to summarize the recent advances of these three mRNA modifications in maintaining the stemness of cancer stem cells and discuss the underlying molecular mechanisms, which will shed light on the development of novel therapeutic approaches for eradicating cancer stem cells.

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Alu-dependent RNA editing of GLI1 promotes malignant regeneration in multiple myeloma

Cited by 98 publications

References 44 publications

Identification of novel GLI1 target genes and regulatory circuits in human cancer cells

Identification of novel GLI1 target genes and regulatory circuits in human cancer cells

Automated literature mining and hypothesis generation through a network of Medical Subject Headings

mRNA modification orchestrates cancer stem cell fate decisions

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