CoChat
Sign Up
Cited by 73Acute Myeloid Leukemia ResearchRetinoids in leukemia and cellular processesRNA Research and Splicing

Surface antigen-guided CRISPR screens identify regulators of myeloid leukemia differentiation

Open access
Wang, Eric, Zhou, Hua, Nadorp, Bettina, Cayanan, Geraldine, Chen, Xufeng, Yeaton, Anna H., Nomikou, Sofia, Witkowski, Matthew T. +6 more·2021·Cell Stem Cell
DOI 10.1016/j.stem.2020.12.005PMC PMC8145876
Open this paper in CoChat — free account

Abstract

SUMMARY Lack of cellular differentiation is a hallmark of many human cancers, including acute myeloid leukemia (AML). Strategies to overcome such differentiation blockade represent an approach for treating AML patients. To identify targets for differentiation based therapies, we applied an integrated cell surface-based CRISPR platform to assess genes involved in maintaining the undifferentiated state of leukemia cells. Here, we identify the RNA-binding protein, ZFP36L2, as a critical regulator of AML maintenance and differentiation. Mechanistically, ZFP36L2 interacts with the 3’ untranslated region of key myeloid maturation genes, including the ZFP36 paralogs, to promote their mRNA degradation and suppress terminal myeloid cell differentiation. Genetic inhibition of ZFP36L2 restores mRNA stability of these targeted transcripts and ultimately triggers myeloid differentiation in leukemia cells. Epigenome profiling of several primary AML patients revealed enhancer modules near ZFP36L2 that associated with distinct AML cell states, establishing a coordinated epigenetic and post-transcriptional mechanism that shapes leukemic differentiation.

AI snapshot

Written from the paper’s full text.

TL;DR

The authors combined genome-wide and single-cell CRISPR screens with cell-surface markers to find regulators of myeloid leukemia differentiation, converging on the RNA-binding protein ZFP36L2. ZFP36L2 promotes degradation of mRNAs that drive myeloid maturation, including ZFP36 paralogs, and an AML-associated enhancer near ZFP36L2 is linked to stem-like versus monocytic leukemia states.

Key findings

  • In Cas9-expressing THP-1 AML cells, a Brunello library of >78,000 sgRNAs targeting 19,115 protein-coding genes was screened by sorting CD14-high/low and CD11B-high/low cells after 12 days; CD14 and CD11B guides scored as top negative hits, validating the approach. Filtering against public cancer dependency data identified 12 candidates with CRISPR score >1, leukemia dependency score < −0.5, and non-leukemia dependency score > −0.5, including ZFP36L2, GFI1, MED16, and MED24.
  • ZFP36L2 loss reduced AML growth, increased apoptosis, impaired S-phase progression, and induced myeloid differentiation; in MOLM-13 xenografts, ZFP36L2 knockout delayed leukemia progression and prolonged survival. ZFP36L2 was dispensable in several non-AML lines, and normal HSPC assays showed only mild colony and competitive defects, whereas MLL-AF9 NRASG12D cells had robust growth defects.
  • eCLIP in MOLM-13 and THP-1 cells found roughly 14,000 and 19,000 enriched peaks, respectively, with >74% overlap and about 16–20% mapping to AU-rich elements in 3′ UTRs. Overlap of 3,741 confident binding sites with upregulated genes after ZFP36L2 knockout implicated targets such as CEBPB, IL1B, ITGB2, and NOTCH1; ZFP36L2 loss also lengthened CEBPB poly(A) tails, and ZFP36 and ZFP36L1 were direct targets.
  • An AML-enriched enhancer downstream of ZFP36L2, termed enhZFP36L2, showed HOXA9/MEIS1 co-occupancy; CRISPRi at this enhancer reduced ZFP36L2 and increased CD14 and ZFP36L1. Across 56 primary AML samples, enhancer H3K27ac correlated with a myeloid differentiation score (r = 0.65), and enhZFP36L2-high (n = 13) versus -low (n = 7) samples differed in 2,929 genes, with high samples showing stem-like signatures and low samples showing monocytic features.

Methods

  • Genome-wide CRISPR/Cas9 screens were performed in Cas9-expressing THP-1 MLL-AF9 NRASG12D cells using the Brunello library, followed by FACS for CD14-high/low or CD11B-high/low populations and deep sequencing of sgRNA counts.
  • ECCITE-seq coupled pooled sgRNAs targeting 12 candidates plus 6 non-targeting controls with scRNA-seq, CD11B/CD16 antibody-derived tags, and sgRNA capture in 1,935 THP-1 cells, averaging about 3,300 transcripts and one sgRNA per cell (n = 45 cells/sgRNA).
  • Mechanistic and epigenetic work included eCLIP in MOLM-13 and THP-1, RNA-seq, poly(A) tail-length assays, ChIP-seq, Hi-C, ATAC-seq, CRISPRi, mouse leukemia xenografts, and HSPC colony/competition assays; patient analyses used public and primary AML datasets with CIBERSORT, GSEA, and differential expression.

Limitations

  • The paper states that its main limitation is limited functional assessment of the differentiation candidates in normal hematopoiesis; it calls for further in vitro and in vivo ablation studies in normal human hematopoiesis to strengthen the rationale for differentiation-based therapies.
  • Evident from the text: the primary screens relied heavily on THP-1 cells and selected AML lines, while much of the patient-level enhancer analysis used relatively small subsets (e.g., 13 enhZFP36L2-high and 7 -low samples) and public datasets.
  • Evident from the text: no ZFP36L2 inhibitors are currently available, and the study notes that pharmacologic modulation of RNA processing remains a potential but not yet established therapeutic route.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1016/j.stem.2020.12.005

Cites

92 of 92 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Claims the paper makes

0 of 1 cited sources checked · 0 supported · 0 flagged

  • Findingcitation

    Targeting Zfp36l2 in an aggressive MLL-AF9 NrasG12D mouse model causes substantial defects in leukemia growth in vitro.

    “Moreover, targeting Zfp36l2 in an aggressive MLL-AF9 NrasG12D mouse model (Zuber et al., 2011a) showed substantial defects in leukemia growth in vitro”
    Quote in the paperSubstantial claim
  • Findingown data

    eCLIP analysis showed >74% overlap of annotated mRNAs bound by ZFP36L2 in both AML cell lines.

    “Our eCLIP analysis showed a strong overlap (>74%) of annotated mRNAs bound by ZFP36L2 in both AML cell lines.”
    Quote in the paperSubstantial claim
  • Findingown data

    ZFP36L2 is dispensable for growth of non-AML cell lines across a broad range of cancer types.

    “In contrast, ZFP36L2 was dispensable for the growth of non-AML cell lines across a broad range of cancer types”
    Quote in the paperSubstantial claim
  • Findingown data

    ZFP36L2 acts as a key controller of AML upkeep and differentiation.

    “Here, we identify the RNA-binding protein, ZFP36L2, as a critical regulator of AML maintenance and differentiation.”
    Quote in the paperSubstantial claim
  • Findingown data

    Transcriptional activation of ZFP36L2 results in decreased ZFP36 mRNA levels.

    “We observed that transcriptional activation of ZFP36L2 resulted in a decrease in ZFP36 mRNA levels”
    Quote in the paperSubstantial claim
  • May combine two claims. 24
  • Classified as probably not a substantial claim. 7
  • The quote only partly states this claim. 1

  • May combine two claims.

    Findingown data

    ZFP36L2 is required for AML cell survival and differentiation.

    “Our top-scoring candidate was the RNA-binding protein, ZFP36L2 (also known as TIS11D), which is required for AML cell survival and differentiation”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Genetic ablation of ZFP36L2 reduces AML growth and induces apoptosis, impaired S-phase cell cycle arrest, and myeloid differentiation.

    “Genetic ablation of ZFP36L2 (ZFP36L2-KO) strongly reduced AML growth and led to marked induction of apoptosis, impaired S-phase cell cycle arrest and myeloid differentiation”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    ITGB2/CD18 is a direct ZFP36L2 target and scored as the top negative hit in the CD11B cell surface screen.

    “In addition, we identified ITGB2/CD18, a known binding partner for CD11B as a direct ZFP36L2 target which also scored as the top negative hit in our CD11B cell surface screen”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    The genome-wide CRISPR screens identified genes broadly needed for leukemia growth whose loss promotes AML differentiation, including ZFP36L2.

    “Our screens converged on a number of genes that are broadly required for leukemia growth whose loss-of-function promotes AML differentiation, including ZFP36L2, a previously uncharacterized dependency in AML.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    In healthy donor bone marrow, ZFP36 and ZFP36L1 are highly expressed in monocytic populations, while ZFP36L2 is highly expressed in stem and progenitor stages and gradually decreases during myeloid differentiation.

    “Analysis of healthy donor bone marrow showed ZFP36 and ZFP36L1 to be highly expressed in monocytic populations, whereas ZFP36L2 expression was highly expressed in stem and progenitor stages and gradually decreases during myeloid differentiation”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    ZFP36 and ZFP36L1 mRNAs are direct targets of ZFP36L2 that are upregulated in ZFP36L2-KO and bound by ZFP36L2 in AML cells.

    “Interestingly, we found the ZFP36 paralogs, ZFP36 and ZFP36L1 mRNAs, were among the direct targets of ZFP36L2 that were upregulated in ZFP36L2-KO and bound by ZFP36L2 in AML cells”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    PMA treatment of AML cells downregulates ZFP36L2 in differentiated macrophages and substantially upregulates ZFP36L2 direct mRNA targets.

    “AML cells treated with the differentiation-inducing agent, phorbol myristate acetate (PMA) (Phanstiel et al., 2017) downregulated expression of ZFP36L2 in PMA-differentiated macrophages, whereas ZFP36L2 direct mRNA targets were substantially upregulated”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Loss of ZFP36L2 in AML cells leads to longer poly(A) tail length of CEBPB mRNA, associated with increased mRNA stability.

    “We also show that loss of ZFP36L2 in AML cells led to longer poly(A) tail length of CEBPB mRNA which is associated with increased mRNA stability”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Findingcitation

    Most ZFP36L2-bound mRNAs mapped to AU-rich elements on 3' UTRs (~16-20%).

    “In agreement with previous reports (Hudson et al., 2004), majority of ZFP36L2-bound mRNAs mapped to A-U rich elements (AREs) on 3’ UTRs (~ 16–20%)”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    ZFP36L2 loss is associated with upregulation of monocytic/macrophage-associated genes (CD14, CSF1R, CEBPB, IL1B, MMP9) and downregulation of leukemia stem cell signatures.

    “ZFP36L2 loss associated with upregulation of several key monocytic/macrophage-associated genes (e.g. CD14, CSF1R, CEBPB, IL1B, and MMP9) and downregulated genes associated with leukemia stem cell (LSC) signatures”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingreasoning

    Genetic inhibition of ZFP36L2 restores stability of its target mRNAs and triggers myeloid differentiation in leukemia cells.

    “Genetic inhibition of ZFP36L2 restores mRNA stability of these targeted transcripts and ultimately triggers myeloid differentiation in leukemia cells.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    Zfp36l2 knockout in mouse HSPCs leads to mild reduction in colony formation and depletion of HSPCs compared with non-targeting control.

    “Our results showed that Zfp36l2 knockout led to a mild reduction in colony formation and depletion of HSPCs when compared to non-targeting sgRosa”
    Quote in the paperNot a substantial claim

  • The quote only partly states this claim.

    Findingown data

    Overlap of confident eCLIP binding sites with genes upregulated in ZFP36L2-KO RNA-seq revealed direct targets including CEBPB, IL1B, ITGB2, and NOTCH1.

    “This analysis revealed several important genes (e.g. CEBPB, IL1B, ITGB2 and NOTCH1) that have been shown to play a pivotal role in monocytic and leukemic differentiation”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    enhZFP36L2Low patients exhibit higher expression of monocyte-associated genes (CD14, ITGAM, IRF8, CEBPB) and terminally differentiated AML signatures including ZFP36L1 and ZFP36.

    “enhZFP36L2Low patients exhibited higher expression of monocyte-associated genes (e.g. CD14, ITGAM, IRF8, and CEBPB) and terminally differentiated AML signatures, including the ZFP36 paralogs, ZFP36L1 and ZFP36”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingcitation

    Higher ZFP36L2 expression in AML patients is associated with genetic alterations in NPM1 and IDH1 and elevated HOXA9 levels.

    “Our analysis of AML patients found that higher ZFP36L2 expression were associated with genetic alterations in NPM1 and IDH1 and elevated HOXA9 levels”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Findingown data

    Patients with enhZFP36L2High exhibit stem-like phenotypes, whereas enhZFP36L2Low cohorts are enriched for monocytic AML blasts.

    “Patients associated with enhZFP36L2High exhibited stem-like phenotypes, whereas ZFP36L2Low cohorts were enriched for monocytic AML blast.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Findingown data

    CRISPRi targeting enhZFP36L2 in MOLM-13 cells decreases ZFP36L2 expression and elevates CD14 and ZFP36L1 mRNA levels.

    “Consistently, we observed that sgRNAs targeting enhZFP36L2 led to decreased ZFP36L2 expression and elevated mRNA levels of CD14 and ZFP36L1”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    ZFP36L2 binds the 3' UTR of myeloid maturation transcripts, including ZFP36 paralogs, and drives their degradation, thereby suppressing terminal myeloid differentiation.

    “Mechanistically, ZFP36L2 interacts with the 3’ untranslated region of key myeloid maturation genes, including the ZFP36 paralogs, to promote their mRNA degradation and suppress terminal myeloid cell differentiation.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Transcriptional activation of ZFP36 strongly suppresses human myeloid leukemia cells but does not alter ZFP36L2 expression, suggesting paralog regulation does not occur through a negative feedback loop.

    “Inversely, transcriptional activation of ZFP36 led to strong suppression in human myeloid leukemia cells but did not alter ZFP36L2 expression, suggesting that ZFP36 paralog regulation do not occur through a negative feedback loop”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    ZFP36L2 is an AML dependency that relies on its RNA-binding domain to suppress AML blast differentiation.

    “Collectively, these data provide genetic evidence that ZFP36L2 is an AML dependency that relies on its RNA-binding domain to suppress AML blast differentiation.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    sgRNAs targeting CD14 or CD11B in their respective screens were the top negative hits, validating the screening approach.

    “We found sgRNAs targeting CD14 or CD11B in their respective screens scored as the top negative hits, thereby validating our screening method.”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Interpretationown data

    Inhibition of ZFP36 or ZFP36L1 shows minimal requirement for leukemic survival, suggesting a non-redundant role for ZFP36L2 in AML survival.

    “Furthermore, inhibition of the other ZFP36 paralogs, ZFP36 or ZFP36L1 showed minimal requirement for leukemic survival suggesting a non-redundant role for ZFP36L2 in AML survival”
    Quote in the paperSubstantial claim

  • May combine two claims.

    Study design and conductown data

    In ECCITE-seq, most single cells carrying candidate sgRNAs showed increased CD11B protein relative to non-targeting sgRNAs, validating the cell surface screens.

    “Analysis of ADT-seq libraries showed majority of single cells harboring candidate sgRNAs led to increased protein expression of CD11B relative to non-targeting sgRNAs, thereby validating our cell surface-based screens”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    For ATAC-seq PCR steps 3-5, the transposed library was amplified for a number of cycles based on quantitative PCR to stop amplification before saturation, reducing GC and size bias.

    “For PCR steps 3–5, transposed library was amplified with number of cycles based on quantitative PCR in order to stop amplification prior to saturation, thus reducing GC and size bias in PCR.”
    Quote in the paperNot a substantial claim

  • Classified as probably not a substantial claim. May combine two claims.

    Study design and conductreasoning

    In ECCITE-seq analysis, cells were included only if they had more than 400 and fewer than 6000 unique feature counts and less than 15% of transcripts from mitochondrial genes, to remove low-quality cells and droplets containing multiple cells.

    “We included cells with more than 400, and less than 6000 unique feature counts, and only kept cells with less than 15% of their transcripts originating from mitochondrial genes to exclude low-quality cells and multiple cells captured in droplets.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductown data

    eCLIP studies were performed in duplicate.

    “eCLIP studies were performed in duplicates by Eclipse Bioinnovations Inc (San Diego, www.eclipsebio.com) according to the published single-end seCLIP protocol(Van Nostrand et al., 2017) with the following modifications.”
    Quote in the paperNot a substantial claim

  • May combine two claims.

    Interpretationown data

    ZFP36L2 is a central post-transcriptional suppressor of leukemia differentiation and a broad therapeutic vulnerability in human AML.

    “We have defined a context-dependent role for the RNA-binding protein, ZFP36L2 as a central, post-transcriptional suppressor of leukemia differentiation and a broad therapeutic vulnerability in human AML.”
    Quote in the paperSubstantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductcitation

    In ECCITE-seq analysis, mixscape was used to remove cells that escaped molecular perturbation before linear discriminant analysis-based dimensionality reduction to visualize guide-induced perturbation.

    “We further used mixscape to remove cells that escaped molecular perturbation and performed linear discriminant analysis-based dimensionality reduction to visualize the perturbation induced by the guides”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing).

    Study design and conductnone given

    The study did not use statistical methods to predetermine sample size.

    “No statistical methods were used to predetermine the sample size.”
    Quote in the paperNot a substantial claim

  • Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.

    Study design and conductown data

    For Hi-C library preparation, PCR cycling steps 2-4 used a number of cycles that kept amplification in the linear range, with expected library size distribution confirmed by agarose gel.

    “For cycling PCR steps 2–4, the number of cycles used ensured PCR amplification remained in the linear range with the expected library size distribution as assessed by agarose gel visualization.”
    Quote in the paperNot a substantial claim
30 of 30

  • The paper relies on this without support.

    Before this study, no genome-wide assessment had examined genes that maintain the undifferentiated state of leukemia cells.

    “However, to date, there has not been a genome-wide assessment of genes involved in maintaining the undifferentiated state of leukemia cells.”

  • The paper relies on this without support.

    The fundamental gene regulatory networks governing the undifferentiated state of leukemic blasts remain unclear.

    “Despite our current understanding of hematopoietic cell differentiation, the fundamental gene regulatory networks that governs the undifferentiated state of leukemic blasts remain unclear.”

  • The paper relies on this without support.

    Failure to differentiate is a hallmark of many human cancers, including AML.

    “Lack of cellular differentiation is a hallmark of many human cancers, including acute myeloid leukemia (AML).”
3 of 3

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • In a bulk Cas13d CRISPR screen of 439 genes, 26 genes were selected that consistently influenced differentiation across multiple independent gRNAs and had been identified in orthogonal pooled Cas9 screens.

    “By comparing gRNA representation between low and high-expressing bins, we selected 26 genes that influenced differentiation consistently across multiple independent gRNAs and that have also been identified previously in orthogonal pooled Cas9 screens23 (Extended Data Fig. 6a–h and Supplementary Table 4).”

    From Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq (2023) · cites this paper as [23]

  • In prior Cas9 screens, 240 genes led to CD11b or CD14 upregulation.

    “We selected 240 genes that led to CD11b or CD14 upregulation in Cas9 screens23, in addition to 199 control genes in TLR4-signaling.”

    From Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq (2023) · cites this paper as [23]

  • Differential gene expression signatures for single-gene perturbations from ECCITE-seq (5′ scRNA-seq, Cas9) were readily reproduced in CaRPool-seq (3′ scRNA-seq, Cas13d) data.

    “We found that the differential gene expression signatures for single-gene perturbations obtained using ECCITE-seq (5′ scRNA-seq, Cas9 perturbation)23 can be readily reproduced in our CaRPool-seq (3′ scRNA-seq, Cas13d perturbation) data (Extended Data Fig. 8a,b).”

    From Efficient combinatorial targeting of RNA transcripts in single cells with Cas13 RNA Perturb-seq (2023) · cites this paper as [23]

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Two culture media are specified for 501MEL cells

    Minor

    The cell-culture methods place 501MEL cells in both DMEM and RPMI-1640 without distinguishing separate conditions.

1 of 1

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Wang, E., Zhou, H., Nadorp, B., Cayanan, G., Chen, X., Yeaton, A. H., Nomikou, S., Witkowski, M. T., Narang, S., Kloetgen, A., Thandapani, P., Ravn-Boess, N., Tsirigos, A., & Aifantis, I.
Affiliations
NYU Langone Health (US)
Corresponding author
  • Wang, Eric
  • Aifantis, Iannis
ORCID
Venue
Cell Stem Cell
Publisher
Elsevier BV
Published
2021-04
Volume
28
Issue
4
Pages
718-731.e6
ISSN
  • 1875-9777 (ISSN-L)
  • 1934-5909
DOI
10.1016/j.stem.2020.12.005
PMC
PMC8145876
OpenAlex
W3118303034
Semantic Scholar
cbe8b432eb20e6f26a3325e43d1f928046d9bfee
Cited by
66
References
91
Citations by year
2026: 12 · 2025: 9 · 2024: 14 · 2023: 12 · 2022: 16 · 2021: 3
FWCI
8.48
Type
journal article
Language
en
Open access
Licence
Locations
  • Cell stem cell (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • National Cancer Institute (R01CA216421, 1P01CA229086, R01CA228135, R01CA202025, 1R01CA194923, P30CA016087-30, R01CA149655, R01CA133379)
  • New York State Stem Cell Science
  • Leukemia and Lymphoma Society
  • Stanford Genome Technology Center
  • National Institutes of Health
  • American Cancer Society (RSG-15-189-01-RMC)
  • St. Baldrick&apos;s Foundation (581357)
  • Alexander S. Onassis Public Benefit Foundation (F ZP 036-1/2019-2020)
Topics
  • Health Sciences › Medicine › Hematology › Acute Myeloid Leukemia Research
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Retinoids in leukemia and cellular processes
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
Keywords
acute myeloid leukemia, myeloid differentiation, ZFP36L2, RNA-binding proteins, mRNA stability, 3' untranslated region, post-transcriptional regulation, epigenetic regulation, CRISPR screen, cell surface
MeSH terms
Antigens, Surface, Cell Differentiation, Hematopoiesis, Humans, Leukemia, Myeloid, Acute, Clustered Regularly Interspaced Short Palindromic Repeats

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-05.

Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-05.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review