Download
13073_2024_Article_1341.pdf 4,34MB
WeightNameValue
1000 Titel
  • CRISPR-Cas9 screens reveal common essential miRNAs in human cancer cell lines
1000 Autor/in
  1. Merk, Daniel |
  2. Paul, Linda |
  3. Tsiami, Foteini |
  4. Hohenthanner, Helen |
  5. Mohseni Kouchesfahani, Ghazal |
  6. Haeusser, Lara A |
  7. Walter, Bianca |
  8. Brown, Adam |
  9. Persky, Nicole |
  10. Root, David |
  11. Tabatabai, Ghazaleh |
1000 Verlag BioMed Central
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-06-17
1000 Erschienen in
1000 Quellenangabe
  • 16(1):82
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1186/s13073-024-01341-4 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11181638/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:title>Abstract</jats:title><jats:sec> <jats:title>Background</jats:title> <jats:p>Genome-wide functional screening using the CRISPR-Cas9 system is a powerful tool to uncover tumor-specific and common genetic dependencies across cancer cell lines. Current CRISPR-Cas9 knockout libraries, however, primarily target protein-coding genes. This limits functional genomics-based investigations of miRNA function.</jats:p> </jats:sec><jats:sec> <jats:title>Methods</jats:title> <jats:p>We designed a novel CRISPR-Cas9 knockout library (lentiG-miR) of 8107 distinct sgRNAs targeting a total of 1769 human miRNAs and benchmarked its single guide RNA (sgRNA) composition, predicted on- and off-target activity, and screening performance against previous libraries. Using a total of 45 human cancer cell lines, representing 16 different tumor entities, we performed negative selection screens to identify miRNA fitness genes. Fitness miRNAs in each cell line were scored using a combination of supervised and unsupervised essentiality classifiers. Common essential miRNAs across distinct cancer cell lines were determined using the 90th percentile method. For subsequent validation, we performed knockout experiments for selected common essential miRNAs in distinct cancer cell lines and gene expression profiling.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>We found significantly lower off-target activity for protein-coding genes and a higher miRNA gene coverage for lentiG-miR as compared to previously described miRNA-targeting libraries, while preserving high on-target activity. A minor fraction of miRNAs displayed robust depletion of targeting sgRNAs, and we observed a high level of consistency between redundant sgRNAs targeting the same miRNA gene. Across 45 human cancer cell lines, only 217 (12%) of all targeted human miRNAs scored as a fitness gene in at least one model, and fitness effects for most miRNAs were confined to small subsets of cell lines. In contrast, we identified 49 common essential miRNAs with a homogenous fitness profile across the vast majority of all cell lines. Transcriptional profiling verified highly consistent gene expression changes in response to knockout of individual common essential miRNAs across a diverse set of cancer cell lines.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusions</jats:title> <jats:p>Our study presents a miRNA-targeting CRISPR-Cas9 knockout library with high gene coverage and optimized on- and off-target activities. Taking advantage of the lentiG-miR library, we define a catalogue of miRNA fitness genes in human cancer cell lines, providing the foundation for further investigation of miRNAs in human cancer.</jats:p> </jats:sec>
1000 Sacherschließung
lokal Gene Expression Regulation, Neoplastic [MeSH]
lokal Negative selection screens
lokal Cell Line, Tumor [MeSH]
lokal Non-coding RNA
lokal miRNA
lokal Humans [MeSH]
lokal Neoplasms/genetics [MeSH]
lokal CRISPR-Cas9 knockout
lokal Gene Knockout Techniques [MeSH]
lokal Common essentiality
lokal Genes, Essential [MeSH]
lokal CRISPR-Cas Systems [MeSH]
lokal Research
lokal Gene Expression Profiling [MeSH]
lokal MicroRNAs/genetics [MeSH]
lokal Functional annotation
lokal RNA, Guide, CRISPR-Cas Systems/genetics [MeSH]
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0003-2935-6919|https://orcid.org/0009-0005-7830-2775|https://orcid.org/0009-0001-6070-0434|https://orcid.org/0009-0000-3761-4776|https://orcid.org/0009-0001-3156-7929|https://orcid.org/0000-0002-3288-4280|https://orcid.org/0000-0001-9734-4843|https://frl.publisso.de/adhoc/uri/QnJvd24sIEFkYW0=|https://orcid.org/0000-0002-9948-2761|https://orcid.org/0000-0001-5122-861X|https://orcid.org/0000-0002-3542-8782
1000 Hinweis
  • DeepGreen-ID: 1b119cd410fe4ea7ae9fb47a7fc53f4f ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search)
1000 Label
1000 Förderer
  1. Medizinischen Fakultät, Eberhard Karls Universität Tübingen |
  2. Deutsche Forschungsgemeinschaft |
  3. Adolf Leuze Stiftung |
  4. Medizinischen Fakultät, Eberhard Karls Universität Tübingen |
1000 Fördernummer
  1. -
  2. -
  3. -
  4. -
1000 Förderprogramm
  1. -
  2. -
  3. -
  4. -
1000 Dateien
1000 Förderung
  1. 1000 joinedFunding-child
    1000 Förderer Medizinischen Fakultät, Eberhard Karls Universität Tübingen |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Deutsche Forschungsgemeinschaft |
    1000 Förderprogramm -
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer Adolf Leuze Stiftung |
    1000 Förderprogramm -
    1000 Fördernummer -
  4. 1000 joinedFunding-child
    1000 Förderer Medizinischen Fakultät, Eberhard Karls Universität Tübingen |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
1000 Beschrieben durch
1000 @id frl:6503289.rdf
1000 Erstellt am 2025-02-05T20:22:00.697+0100
1000 Erstellt von 322
1000 beschreibt frl:6503289
1000 Zuletzt bearbeitet 2025-09-13T13:29:55.993+0200
1000 Objekt bearb. Sat Sep 13 13:29:55 CEST 2025
1000 Vgl. frl:6503289
1000 Oai Id
  1. oai:frl.publisso.de:frl:6503289 |
1000 Sichtbarkeit Metadaten public
1000 Sichtbarkeit Daten public
1000 Gegenstand von

View source